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A Pilot Proteomic Analysis of Salivary Biomarkers in Autism Spectrum Disorder
Abstract
Autism spectrum disorder (ASD) prevalence is increasing, with current estimates at 1/68–1/50 individuals diagnosed with an ASD. Diagnosis is based on behavioral assessments. Early diagnosis and intervention is known to greatly improve functional outcomes in people with ASD. Diagnosis, treatment monitoring and prognosis of ASD symptoms could be facilitated with biomarkers to complement behavioral assessments. Mass spectrometry (MS) based proteomics may help reveal biomarkers for ASD. In this pilot study, we have analyzed the salivary proteome in individuals with ASD compared to neurotypical control subjects, using MS-based proteomics. Our goal is to optimize methods for salivary proteomic biomarker discovery and to identify initial putative biomarkers in people with ASDs. The salivary proteome is virtually unstudied in ASD, and saliva could provide an easily accessible biomaterial for analysis. Using nano liquid chromatography-tandem mass spectrometry, we found statistically significant differences in several salivary proteins, including elevated prolactin-inducible protein, lactotransferrin, Ig kappa chain C region, Ig gamma-1 chain C region, Ig lambda-2 chain C regions, neutrophil elastase, polymeric immunoglobulin receptor and deleted in malignant brain tumors 1. Our results indicate that this is an effective method for identification of salivary protein biomarkers, support the concept that immune system and gastrointestinal disturbances may be present in individuals with ASDs and point toward the need for larger studies in behaviorally-characterized individuals.
... Some studies show that saliva can be a diagnostic tool to detect many systemic diseases [20], such as breast cancer, lung cancer, pancreatic cancer [21,22], Down syndrome [23], Sjögren's syndrome, heart failure, inflammatory processes [24], immune diseases [25], oxidative stress in oral diseases [26], obesity and childhood diabetes [27]. Wetie et al. (2015) [28] analyzed the saliva proteome of individuals with ASD by mass spectrometry and demonstrated significant differences in salivary proteins related to oxidative stress, lipid metabolism, and immunity [28,29]. Despite these findings, no precise and universally reproducible biomarkers have been identified in children with ADS. ...
... Some studies show that saliva can be a diagnostic tool to detect many systemic diseases [20], such as breast cancer, lung cancer, pancreatic cancer [21,22], Down syndrome [23], Sjögren's syndrome, heart failure, inflammatory processes [24], immune diseases [25], oxidative stress in oral diseases [26], obesity and childhood diabetes [27]. Wetie et al. (2015) [28] analyzed the saliva proteome of individuals with ASD by mass spectrometry and demonstrated significant differences in salivary proteins related to oxidative stress, lipid metabolism, and immunity [28,29]. Despite these findings, no precise and universally reproducible biomarkers have been identified in children with ADS. ...
... All are potential biomarkers. Among the proteins with potential application as biomarkers for ASD, Neutrophil elastase protein (EC 3.4.21.37) was overexpressed, corroborating previous studies by Wetie and colleagues, who applied nano-liquid chromatography-tandem mass spectrometry and found statistically significant differences in several salivary proteins of individuals with ASD compared to neurotypical control individuals, including neutrophil elastase [28]. Several studies indicated the presence of Neutrophil elastase with its main proteolytic activity associated with several pathological processes in a variety of acute and chronic inflammatory diseases [45][46][47]. ...
The lack of specific pharmacological therapy for Autistic Spectrum Disorder (ASD) and its clinical heterogeneity demand efforts directed toward the identification of biomarkers to aid in diagnosis. Proteomics offers a new perspective for studying the altered proteins associated with autism spectrum disorders (ASD) and we have saliva as an easy-to-collect biological fluid with important biomolecules for investigating biomarkers in various diseases. In this sense, saliva could be used to identify potential biomarkers of ASD. In the current work, saliva samples were collected from children with different degrees of ASD and healthy children and proteomics approaches were applied to generate data on differentially expressed proteins between groups which will serve as a basis for future validation studies as protein markers. Data are available via ProteomeXchange with identifier PXD030065. As results, 132 proteins were present in 80% of the saliva pools of all analyzed groups. Twenty-five proteins were identified as overexpressed in the group of severe and mild/moderate ASD carriers, among which, eight were identified as potential biomarkers for ASD.
... A utism spectrum disorder (ASD) as a prevalent neurodevelopmental condition is on the rise with the rate of 1/68 to 1/50 persons [1]. The typical ASD symptoms approved by Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), include social communication/interaction disability, repetitive behaviors, and sensory impairments [2]. ...
... www.gmj.ir nosis and treatment approaches of ASD [1]. ...
... In this light, many biomarker investigations of this heritable disorder have been widely studied via genomics, proteomics, and metabolomics [1,8]. However, identification of reliable biomarkers still requires more studies [9]. ...
Background:
Currently, the prevalence of autism spectrum disorder (ASD) is increasing, which widely spurs the interest in the molecular investigation. Thereby, a better understanding of the given disorder mechanisms is likely to be achieved. Bioinformatics suiting protein-protein interactions analysis via the application of high-throughput studies, such as protein array, is one of these achievements.
Materials and methods:
The gene expression data from Gene Expression Omnibus (GEO) database were downloaded, and the expression profile of patients with developmental delay and autistic features were analyzed via Cytoscape and its relevant plug-ins.
Results:
Our findings indicated that EGFR, ACTB, RHOA, CALM1, MAPK1, and JUN genes as the hub-bottlenecks and their related terms could be important in ASD risk. In other words, any expression modification in these genes could trigger dysfunctions in the corresponding biological processes.
Conclusion:
We suggest that differentially expressed genes could be used as suitable targets for ASD after being validated.
... In another study, we compared the saliva from children with ASD compared to controls using in-solution digestion and nanoLC-MS/MS, and found increased levels of prolactininducible protein, lactotransferrin, Ig kappa chain C region, Ig gamma-1 chain C region, Ig lambda-2 chain C regions, neutrophil elastase, polymeric immunoglobulin receptor and deleted in malignant brain tumors 1 in ASD samples [62]. We also found significantly elevated levels of statherin, histatin 1 and salivary acidic proline rich protein in controls, compared with ASD (Figs. 28.7 and 28.8). ...
... LGHPDTLNQGEFK Fig somehow suggested in our previous work, where we found a relationship between the proteins that are dysregulated, specifically ApoA1, ApoA4 and PON1 proteins, which suggested that the dysregulation happen at the protein complex level [61]. The 2D-PAGE study also supported the hypothesis that immunological responses are present in some forms of ASD [62]. ...
... In the 2D-PAGE study performed in our lab, we did a comparative analysis of the salivary proteome of children with ASD and matched controls using 2D-PAGE and nanoLC-ESI-MS/MS [63]. We found several proteins that were differentially expressed in ASD compared to controls, some of which were already identified in their prior study [62] and others that were novel. These proteins are shown in Figs. ...
Mass spectrometry (MS) has been increasingly used to study central nervous system (CNS) disorders, including autism spectrum disorders (ASDs). The first studies of ASD using MS focused on the identification of external toxins, but current research is more directed at understanding endogenous protein changes that occur in ASD (ASD proteomics). This chapter focuses on how MS has been used to study ASDs, with particular focus on proteomic analysis. Other neurodevelopmental disorders have been investigated using this technique, including genetic syndromes associated with autism such as fragile X syndrome (FXS) and Smith-Lemli-Opitz Syndrome (SLOS).
... Our group recently studied the effects of ketamine treatment on individuals with MDD using untargeted LC-MS/MS analysis of salivary samples collected before and after IV ketamine infusions, and comparing them with samples from healthy volunteers. The saliva collection and analysis procedure followed a published procedure [78]. Several protein level comparisons were made, including two within individual comparisons (S1 vs S1 and S2 vs S2) using pre-and posttreatment samples that came from the same individual, and a matched control. ...
... Lipocalin-1 isoform X1 is a member of the family of lipocalins which are extracellular transport proteins that bind a wide variety of hydrophobic ligands including lipids [91]. Mucin-5B and lipocalin-1 isoform X1 both have been found to be dysregulated in ASD as well [78,80,92], and thus suggests that these are both proteins affected by neurological disorders. Chain A, binary complex of 14-3-3 sigma and P53 Pt387-peptide is a peptide binding protein capable of binding small molecules [93]. ...
... Finally, proline-rich protein HaeIII subfamily 1 isoform CRA_b is a member of the proline rich glycoprotein family whose exact function is unknown [96]. However, several of these proteins have previously been identified at different levels in ASD studies, implicating the protein's potential role in neurological disorders [78]. ...
Major depressive disorder (MDD) is common. Despite numerous available treatments, many individuals fail to improve clinically. Diagnosis of MDD continues to be commonly accomplished via behavioral rather than biological methods. Biomarkers may provide objective diagnosis of MDD, and could include measurements of genes, proteins, and patterns of brain activity. Proteomic analysis and validation of biomarkers is less explored than other areas of biomarker research in MDD. Mass spectrometry (MS) is a comprehensive, unbiased means of proteomic analysis, which can be complemented by directed protein measurements, such as Western Blotting. Prior studies have focused on MS analysis of several human biomaterials in MDD, including human post-mortem brain, cerebrospinal fluid (CSF), blood components, and urine. Further studies utilizing MS and proteomic analysis in MDD may help solidify and establish biomarkers for use in diagnosis, identification of new treatment targets, and understanding of the disorder. A biomarker or a biomarker signature that facilitates a convenient and inexpensive predictive test for depression treatment response is highly desirable.
... A utism spectrum disorder (ASD) as a prevalent neurodevelopmental condition is on the rise with the rate of 1/68 to 1/50 persons [1]. The typical ASD symptoms approved by Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), include social communication/interaction disability, repetitive behaviors, and sensory impairments [2]. ...
... www.gmj.ir nosis and treatment approaches of ASD [1]. ...
... In this light, many biomarker investigations of this heritable disorder have been widely studied via genomics, proteomics, and metabolomics [1,8]. However, identification of reliable biomarkers still requires more studies [9]. ...
Background: Currently, the prevalence of autism spectrum disorder (ASD) is increasing, which widely spurs the interest in the molecular investigation. Thereby, a better understanding of the given disorder mechanisms is likely to be achieved. Bioinformatics suiting protein-protein interactions analysis via the application of high-throughput studies, such as protein array, is one of these achievements.Materials and Methods: The gene expression data from Gene Expression Omnibus (GEO) database were downloaded, and the expression profile of patients with developmental delay and autistic features were analyzed via Cytoscape and its relevant plug-ins.Results: Our findings indicated that EGFR, ACTB, RHOA, CALM1, MAPK1, and JUN genes as the hub-bottlenecks and their related terms could be important in ASD risk. In other words, any expression modification in these genes could trigger dysfunctions in the corresponding biological processes.Conclusion: We suggest that differentially expressed genes could be used as suitable targets for ASD after being validated.[GMJ.2019;8:e1367]
... Early diagnosis and intervention might improve functional outcomes in children with autism spectrum disorder. Diagnosis, prognosis, and monitoring of symptoms of autism spectrum disorder can also be helped with biomarkers [53]. ...
... Ngounou Wetie et al. [53] tried to optimize salivary proteomic biomarker methods and to identify initial biomarkers in children with autism spectrum disorders. They assumed that mass spectrometry-based proteomics could help expose biomarkers for autism spectrum disorder. ...
... They found statistically significant differences in several salivary proteins, e.g., the elevation of prolactin-inducible protein, lactotransferrin, Ig kappa chain C region, Ig gamma-1 chain C region, Ig lambda-2 chain C regions, neutrophil elastase, and polymeric immunoglobulin receptor and deletion in malignant brain tumors 1. Their achievement supports the concept that immune system and gastrointestinal disturbances may be present in individuals with autism spectrum disorders [53]. Bhandary and Hari [54] studied the role of saliva as a biomarker and oral health status of children with autism spectrum disorders. ...
A growing interest in the usability of saliva has been observed recently. Using saliva as a diagnostic material is possible because it contains a varied range of composites, organic and inorganic like proteins, carbohydrates, and lipids, which are secreted into saliva. Moreover, this applies to drugs and their metabolites. Saliva collection is noninvasive, and self-collection is possible. There is a lack of risk of injuries related to injection with needle, and it is generally safe. Human saliva has been successfully used, for example, in the diagnosis of many systemic diseases like cancers, autoimmunological diseases, infectious diseases (HIV, hepatitis, and malaria), and endocrinological diseases, as well as diseases of the gastrointestinal tract. Also, it is used in toxicological diagnostics, drug monitoring, and forensic medicine. The usefulness of saliva as a biological marker has also been extended to psychiatry. The specificity of mental illness and patients limits or prevents cooperation and diagnosis. In many cases, the use of saliva as a marker seems to be the most sensible choice.
... The multiple functions of CST-C include inhibition of cysteine proteases, host defense against pathogens, apoptosis, as well as roles in inflammatory diseases such as rheumatoid arthritis (Zi and Xu, 2018). CST-C is highly expressed by the salivary glands (Paraoan et al., 2010), in particular the submandibular and parotid glands (Saitou et al., 2020) and has been reported in numerous studies in saliva (Denny et al., 2008;Rao et al., 2009;Salazar et al., 2013;Ngounou Wetie et al., 2015). MMP-9 is a gelatinase in the matrix metalloproteinase family, essential proteolytic enzymes in wound healing and bone remodeling. ...
... HP is described as an acute-phase response protein stimulated by inflammatory cytokines such as TNFalpha and interleukins IL-1 and IL-6. HP binds to circulating hemoglobin thereby avoiding toxicity of free hemoglobin and has been detected before in saliva (Denny et al., 2008;Rao et al., 2009;Haigh et al., 2010;Salazar et al., 2013;Ngounou Wetie et al., 2015;Murr et al., 2017;Tvarijonaviciute et al., 2020) with significantly higher levels in individuals with oral lichen planus (Mateo et al., 2019), a chronic oral inflammatory condition. Only a few studies report total protein in saliva from individuals with MCI or AD. ...
Alzheimer’s disease (AD) is an insidious disease. Its distinctive pathology forms over a considerable length of time without symptoms. There is a need to detect this disease, before even subtle changes occur in cognition. Hallmark AD biomarkers, tau and amyloid-β, have shown promising results in CSF and blood. However, detecting early changes in these biomarkers and others will involve screening a wide group of healthy, asymptomatic individuals. Saliva is a feasible alternative. Sample collection is economical, non-invasive and saliva is an abundant source of proteins including tau and amyloid-β. This work sought to extend an earlier promising untargeted mass spectrometry study in saliva from individuals with mild cognitive impairment (MCI) or AD with age- and gender-matched cognitively normal from the South Australian Neurodegenerative Disease cohort. Five proteins, with key roles in inflammation, were chosen from this study and measured by ELISA from individuals with AD ( n = 16), MCI ( n = 15) and cognitively normal ( n = 29). The concentrations of Cystatin-C, Interleukin-1 receptor antagonist, Stratifin, Matrix metalloproteinase 9 and Haptoglobin proteins had altered abundance in saliva from AD and MCI, consistent with the earlier study. Receiver operating characteristic analysis showed that combinations of these proteins demonstrated excellent diagnostic accuracy for distinguishing both MCI (area under curve = 0.97) and AD (area under curve = 0.97) from cognitively normal. These results provide evidence for saliva being a valuable source of biomarkers for early detection of cognitive impairment in individuals on the AD continuum and potentially other neurodegenerative diseases.
... In these studies, serum and plasma were amongst the most common matrix utilized due to their mild invasiveness. The majority of these studies found a differential expression in proteins that are linked to the immune system, lipid metabolism, and platelet function pathways [51][52][53]. Paradoxically, one study failed to confirm the identity of the 8 peaks that were detected in MS and were found to be differentially expressed in ASD subjects [54]. Platelets and coagulation functions Cholesterol metabolism [53] It is important to note that biomarker discoveries are not limited to the brain, CSF, serum, and plasma; other body fluids such as saliva and urine can also be utilized. ...
... Platelets and coagulation functions Cholesterol metabolism [53] It is important to note that biomarker discoveries are not limited to the brain, CSF, serum, and plasma; other body fluids such as saliva and urine can also be utilized. Two studies utilized saliva samples from ASD patients and age-matched controls [51,58]. Although there were some subtle differences in their methodology, both studies were able to show significant differential expression of proteins related to the immune system pathway. ...
Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder characterized by impairments in two main areas: social/communication skills and repetitive behavioral patterns. The prevalence of ASD has increased in the past two decades, however, it is not known whether the evident rise in ASD prevalence is due to changes in diagnostic criteria or an actual increase in ASD cases. Due to the complexity and heterogeneity of ASD, symptoms vary in severity and may be accompanied by comorbidities such as epilepsy, attention deficit hyperactivity disorder (ADHD), and gastrointestinal (GI) disorders. Identifying biomarkers of ASD is not only crucial to understanding the biological characteristics of the disorder, but also as a detection tool for its early screening. Hence, this review gives an insight into the main areas of ASD biomarker research that show promising findings. Finally, it covers success stories that highlight the importance of precision medicine and the current challenges in ASD biomarker discovery studies.
... Moreover, when possible subsequent analysis/correlation with blood biomarker levels either within this protocol or at a later timepoint will be performed. The saliva samples will be analyzed for pro-inflammatory markers and for six inflammatory markers selected from a previous study [61]. ...
... Serum immunoglobulin glyco-signaturing will be performed using lectin microarrays and antiglycan ELISA profiling. Saliva samples will also be analyzed for proinflammatory cytokines and inflammatory markers selected from a previous study [61], and altered glycan and glycation products. ...
Autism Spectrum Disorder (ASD) affects approximately 1 child in 54, with a 35-fold increase since 1960. Selected studies suggest that part of the recent increase in prevalence is likely attributable to an improved awareness and recognition, and changes in clinical practice or service availability. However, this is not sufficient to explain this epidemiological phenomenon. Research points to a possible link between ASD and intestinal microbiota because many children with ASD display gastro-intestinal problems. Current large-scale datasets of ASD are limited in their ability to provide mechanistic insight into ASD because they are predominantly cross-sectional studies that do not allow evaluation of perspective associations between early life microbiota composition/function and later ASD diagnoses. Here we describe GEMMA (Genome, Environment, Microbiome and Metabolome in Autism), a prospective study supported by the European Commission, that follows at-risk infants from birth to identify potential biomarker predictors of ASD development followed by validation on large multi-omics datasets. The project includes clinical (observational and interventional trials) and pre-clinical studies in humanized murine models (fecal transfer from ASD probands) and in vitro colon models. This will support the progress of a microbiome-wide association study (of human participants) to identify prognostic microbiome signatures and metabolic pathways underlying mechanisms for ASD progression and severity and potential treatment response.
... Fewer proteomics studies on ASD have been published than those based on other disciplines, such as genomics or transcriptomics. Many of them rely on post-mortem brain tissues [50][51][52], serum [53][54][55][56], plasma [57][58][59], urine [63], saliva [60][61][62] direct samples or lymphoblastoid cell lines [64] ( Table 1). ...
... Saliva, urine, and blood samples have also been taken into consideration. In particular, saliva-based studies showed an alteration in the processes involved in antimicrobial peptides, immune response, and inflammation at the mucosal level [60][61][62]. ...
Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.
... Finally, there is an increase in studies using proteomic analysis, mainly in saliva, in order to detect markers for early ASD diagnosis. Ngounou Wetie et al. (2015) reported an increase in several proteins related to changes in the immune system, oxidative stress and lipid and cholesterol metabolism. In turn, Cortelazzo et al. (2016) reported changes in 12 plasma proteins, 10 of which were involved in the acute inflammatory process, besides the increase in lipid peroxidation, also observed in the studies by Al-Gadani et al. (2009). ...
Transtorno do Espectro Autista (TEA) é uma desordem de desenvolvimento neurológico caracterizada por diferentes graus de déficit na comunicação, interação social, aprendizagem, acompanhado por padrões repetitivos e estereotipados de comportamento. O diagnóstico de TEA é extremamente complexo devido à etiopatologia ainda desconhecida e à diversidade de sintomas apresentados pelos indivíduos, sendo realizado unicamente a partir de observações clínicas do comportamento do indivíduo. Este estudo tem como objetivo revisar os principais biomarcadores plasmáticos e salivares atualmente estudados para o diagnóstico precoce de TEA. Para esta revisão sistemática de literatura, foram utilizados o diretório e a base de dados online “Google Scholar” e “Publish Medliner” (PubMed), respectivamente, com os descritores: “Autism”, “Biomarker”, “Diagnostic”, “Saliva” e “Plasma”. Foram selecionados 564 estudos no PubMed e 185 no Google Scholar, por meio da triagem dos títulos. Após a leitura dos resumos, foram excluídos 647 estudos, seja por irrelevância ou por serem artigos de revisão, estudos genéticos ou não utilizarem amostras de plasma ou saliva. Os 102 estudos originais restantes foram avaliados na íntegra e 83 foram excluídos. Assim, dezenove artigos completos que atenderam aos critérios de inclusão foram utilizados na análise qualitativa. Os resultados identificaram cortisol, glutamato/GABA, glutationa, peroxidação lipídica, marcadores de estresse oxidativo, disfunção mitocondrial e citocinas pró-inflamatórias, especialmente IL-6, como os principais biomarcadores plasmáticos e salivares atualmente estudados para o diagnóstico precoce de TEA. No entanto, considerando que vários resultados foram controversos e inconclusivos, mais estudos são necessários para validar biomarcadores específicos como ferramentas diagnósticas. Os achados atuais incentivam estudos de maior precisão diagnóstica, controlados, multicêntricos e prospectivos.
... The protein composition of saliva has been studied from early on to find associated markers for the diagnosis and prognosis of ASD [15,16]. The mass spectrometric analysis of a patient cohort of 132 proteins were increased in ASD-positive patients, 25 of which were associated with a severe to moderate group of the elevated proteins, suggested as biomarkers for ASD calmodulin-3, plastin-2, and protein s100-a7 [17]. ...
Salivary biomarkers are increasingly being used as an alternative to diagnose and monitor the progression of various diseases due to their ease of use, on site application, non-invasiveness, and most likely improved patient compliance. Here, we highlight the role of salivary biosensors in the general population, followed by the application of saliva as a diagnostic tool in the pediatric population. We searched the literature for pediatric applications of salivary biomarkers, more specifically, in children from 0 to 18 years old. The use of those biomarkers spans autoimmune, developmental disorders, oncology, neuropsychiatry, respiratory illnesses, gastrointestinal disorders, and oral diseases. Four major applications of salivary proteins as biomarkers are: (1) dental health (caries, stress from orthodontic appliances, and gingivitis); (2) gastrointestinal conditions (eosinophilic esophagitis, acid reflux, appendicitis); (3) metabolic conditions (obesity, diabetes); and (4) respiratory conditions (asthma, allergic rhinitis, small airway inflammation, pneumonia). Genomics, metabolomics, microbiomics, proteomics, and transcriptomics, are various other classifications for biosensing based on the type of biomarkers used and reviewed here. Lastly, we describe the recent advances in pediatric biosensing applications using saliva. This work guides scientists in fabricating saliva-based biosensors by comprehensively overviewing the potential markers and techniques that can be employed.
... In earlier investigations, differential expression patterns of miRNAs in patients with ASD have been discovered in research, suggesting that miRNAs might be used as biomarkers for ASD screenings. Brain tissue, blood, and cultured peripheral lymphoblast were utilized to identify miRNA in ASD patients (Ngounou Wetie et al., 2015b). However, saliva, on the other hand, appears to be a handy biomaterial for finding miRNAs biomarkers, and a favored sample for families of ASD sufferers, as per latest investigations. ...
Autism spectrum disorder (ASD) is considered a complicated neurodevelopment disorder with rising prevalence globally. ASD is characterized by a series of events including varying degrees of defects in communication, learning, and social interaction which is accompanied by stereotypical behavioral patterns. Despite extensive research, the current diagnosis for ASD is complex and almost solely based on the behavioral assessments of the suspected individuals. The multifactorial etiopathology of this disease along with the diversity of symptoms among different individuals adds to the current intricacies for accurate prognosis of ASD. Hence, there exists a dire need for biologically relevant biomarkers for an early diagnosis and for tracking the efficacy of therapeutic interventions. Until recently, among various biofluids, saliva has gained increasing interest for biomarker identification, the advantages include the non-invasive nature and ease of sample handling. This mini-review aims to provide a succinct summary of recent literature on saliva-based diagnostic modalities for ASD, examine various studies that highlight the potential use of proteomic and/or RNA-based biomarkers. Finally, some conclusive perspectives of using the salivary system for ASD mechanistic details and diagnosis are also discussed.
... After overnight in-gel trypsin digestion, the peptides were extracted and purified by Zip-Tip reverse phase chromatography (C18 Ziptip™; Millipore, Billerica, MA, USA). The clean, concentrated peptide mixture was analyzed by nanoLC-MS/MS (a NanoAcquity UPLC coupled with a QTOF Ultima API MS; Waters, Milford, MA, USA), as described elsewhere [16]. The MS raw data from MassLynx software (MassLynx version 4.1, Waters) was converted to peak list (pkl) files by ProteinLynx Global Server software (PLGS version 2.4, Waters) as described elsewhere [17], using the following parameters: a background polynomial of order 5 and a background threshold of 35%, Savitzky-Golay smoothing type, 2 iterations and window of 3 channels, centroid top of 80% of peaks and minimum peak width of 4 channels. ...
It is thought that accurate risk assessment and early diagnosis of breast cancer (BC) can help reduce cancer-related mortality. Proteomics analysis of breast milk may provide biomarkers of risk and occult disease. Our group works on the analysis of human milk samples from women with BC and controls to investigate alterations in protein patterns of milk that could be related to BC. In the current study, we used mass spectrometry (MS)-based proteomics analysis of 12 milk samples from donors with BC and matched controls. Specifically, we used one-dimensional (1D)-polyacrylamide gel electrophoresis (PAGE) coupled with nanoliquid chromatography tandem MS (nanoLC-MS/MS), followed by bioinformatics analysis. We confirmed the dysregulation of several proteins identified previously in a different set of milk samples. We also identified additional dysregulations in milk proteins shown to play a role in cancer development, such as Lactadherin isoform A, O-linked N-acetylglucosamine (GlcNAc) transferase, galactosyltransferase, recoverin, perilipin-3 isoform 1, histone-lysine methyltransferase, or clathrin heavy chain. Our results expand our current understanding of using milk as a biological fluid for identification of BC-related dysregulated proteins. Overall, our results also indicate that milk has the potential to be used for BC biomarker discovery, early detection and risk assessment in young, reproductively active women.
... Genetic association studies, such as GWAS, CNV, whole genome, and exome sequencing 6,14,16,17 , have remarkable impact on pinpointing genes and genetic variants associated with ASD. Moreover, transcriptomic [18][19][20] and proteomic studies 21,22 have significantly contributed to our understanding of the disease machinery. However, there is no clear agreement between gene expression levels and the abundance of their corresponding encoded proteins 15 given that, at best, there is a 40-60% correlation between the mRNA and protein levels in certain organisms 23,24 . ...
Autism spectrum disorders (ASD) are a set of complex neurodevelopmental diseases characterized with repetitive behavioral patterns and communication disabilities. Using a systems biology method called MAPSD (Markov Affinity-based Proteogenomic Signal Diffusion) for joint modeling of proteome dynamics and a wide array of omics datasets, we identified a list of candidate ASD risk genes. Leveraging the collected biological signals as well as a large-scale protein-protein interaction network adjusted based on single cell resolution proteome properties in four brain regions, we observed an agreement between the known and the newly identified candidate genes that are spatially enriched in neuronal cells within cerebral cortex at the protein level. Moreover, we created a detailed subcellular localization enrichment map of the known and the identified genes across 32 micro-domains and showed that neuronal cells and neuropils share the largest fraction of signal enrichment in cerebral cortex. Notably, we showed that the identified genes are among the transcriptional biomarkers of inhibitory and excitatory neurons in human frontal cortex. Intersecting the identified genes with a single cell RNA-seq data on ASD brains further evidenced that 20 candidate genes, including GRIK1 , EMX2 , STXBP6 , and KCNJ3 are disrupted in distinct cell-types. Moreover, we showed that ASD risk genes are predominantly distributed in certain human interactome modules, and that the identified genes may act as the regulator for some of the known ASD loci. In summary, our study demonstrated how tissue-wide cell-specific proteogenomic modeling can reveal candidate genes for brain disorders that can be supported by convergent lines of evidence.
... A total of 11 immunoglobulins showed significantly altered expression in the ASD group compared with the TD group, consistent with previous findings (52). Two of these immunoglobulins, HLA class I histocompatibility antigen (HLA-A) and zinc-alpha-2-glycoprotein precursor (AZGP1), are known to be involved in antigen processing and presentation, as well as graft-vs. ...
Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders whose etiology and pathogenesis are not fully understood. To gain insight into the molecular basis of ASD, we performed comparative integrated proteomic and metabolomic analyses of urine samples from children diagnosed with ASD and healthy children. All 160 samples underwent proteomics analysis and 60 were analyzed by liquid chromatography-mass spectrometry to obtain metabolite profiles. We identified 77 differentially expressed proteins (DEPs; 21 downregulated and 56 upregulated) and 277 differentially expressed metabolites; 31 of the DEPs including glutathione, leukocyte antigens, glycoproteins, neural adhesion factors, and immunoglobulins, have been implicated in neuroinflammation. The proteomic analysis also revealed 8 signaling pathways that were significantly dysregulated in ASD patients; 3 of these (transendothelial leukocyte migration, antigen processing and presentation, and graft vs. host disease) were associated with the neuroimmune response. The metabolism of tryptophan, which is also related to the neuroimmune response, has been found to play a potential role in ASD. Integrated proteome and metabolome analysis showed that 6 signaling pathways were significantly enriched in ASD patients, 3 of which were correlated with impaired neuroinflammation (glutathione metabolism, metabolism of xenobiotics by cytochrome P450 and transendothelial migration of leukocyte). We also found a correlation between prostaglandin (PG) E2 levels and the inflammatory response in ASD. These results underscore the prominent role of the neuroimmune response in ASD and provide potential biomarkers that can be used for diagnosis or as targets for early intervention.
... In Parkinson's disease (PD) [182], amyotrophic lateral sclerosis (ALS) [183], as well as in neural tube defects (NTDs) [184], several new proteins, pathway alterations, and candidate biomarkers have been identified in CSF using label-free LC-MS/MS analysis [182]. In autism spectrum disorder (ASD), an LC-MS/MS-based proteomics study identified several differentially expressed proteins for discovering urinary [185] and salivary protein biomarkers [186]. The proteomic results obtained by HPLC-MS/MS and MALDI-TOF MS, validated by ESI-QTOF MS, were used to characterize potential plasma biomarkers for distinguishing patients with major depres-sive disorder (MDD) from patients with schizophrenia (SCZ) [187]. ...
Mass Spectrometry (MS) allows the analysis of proteins and peptides through a variety of methods, such as Electrospray Ionization-Mass Spectrometry (ESI-MS) or Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry (MALDI-MS). These methods allow identification of the mass of a protein or a peptide as intact molecules or the identification of a protein through peptide-mass fingerprinting generated upon enzymatic digestion. Tandem mass spectrometry (MS/MS) allows the fragmentation of proteins and peptides to determine the amino acid sequence of proteins (top-down and middle-down proteomics) and peptides (bottom-up proteomics). Furthermore, tandem mass spectrometry also allows the identification of post-translational modifications (PTMs) of proteins and peptides. Here, we discuss the application of MS/MS in biomedical research, indicating specific examples for the identification of proteins or peptides and their PTMs as relevant biomarkers for diagnostic and therapy.
... The novelty of the present study is that it shows a good correlation of saliva and serum IgG4 in both children with ASD and the healthy normal children for the first time. It also supports the earlier reports, which suggest saliva as an alternate diagnostic tool in ASD [27,28]. Diagnosis of the inflammatory markers and immunological parameters are generally done with blood and CSF samples. ...
Background:
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with wide spectrum of symptoms and few effective therapies. Evidence is suggestive of an association between immune system dysfunction and autism spectrum disorders (ASD) among children with ASD. Immunoglobulins (Ig) are found to be increased in the circulation of individuals with autism. The prospective study was aimed to estimate and correlate the levels of IgG4 in blood and saliva of children with autism.
Methodology:
Blood and unstimulated saliva were collected from 172 children (55 ASD, 57 healthy control, and 60 suspected parasitic infection) aged 0-18 years. Routine blood investigations were done. Serum and salivary IgG4 levels were analyzed using a commercially available enzyme-linked immunosorbent assay (ELISA) kit. Data were subjected to statistical analysis.
Results:
ELISA tests showed that the IgG4 levels in serum and saliva were significantly increased (P<0.05) in children with ASD as compared to normal control children. Both serum and saliva IgG4 levels showed a significant positive correlation (P<0.05).
Conclusion:
IgG4 can be used as a potential biomarker for the early detection of ASD. Further, saliva can be a diagnostic, noninvasive assessment tool for health monitoring of children with autism. Lay summary: The collection of saliva is easy and painless compared to other sample collection methods. The present study shows that, among children with autism, brain-reactive antibody, immunoglobulin G4 (gG4), is increased both in blood and saliva, and there is a significant correlation between the two levels. Therefore, the study recommends IgG4 as a potential biomarker for the early detection of autism, and saliva can be helpful in diagnosis and health monitoring of children with ASD.
... With the aim of identifying initial biomarkers in children with ASD, the optimization of mass-spectrometry-based salivary proteomic analysis was performed by Ngounou Wetie et al. [119]. Their results showed that nano liquid chromatography-tandem mass spectrometry (nano LC-MS/MS) of the salivary proteome could help expose the biomarkers for ASD; statistically significant differences were detected in several salivary proteins, e.g., the elevation of prolactin-inducible protein, lactotransferrin, Ig kappa chain C region, Ig gamma-1 chain C region, neutrophil elastase, polymeric immunoglobulin receptor, and deletion in malignant brain tumors 1, between ASD and normal, healthy individuals. ...
The diagnostic process for autism spectrum disorders (ASD) is based on a behavioral analysis of the suspected individual. Despite intensive research, no specific and valid biomarker has been identified for ASD, but saliva, with its advantages such as non-invasive collection, could serve as a suitable alternative to other body fluids. As a source of nucleic acid of both human and microbial origin, protein and non-protein molecules, saliva offers a complex view on the current state of the organism. Additionally, the use of salivary markers seems to be less complicated not only for ASD screening but also for revealing the etiopathogenesis of ASD, since enrolling neurotypical counterparts willing to participate in studies may be more feasible. The aim of the presented review is to provide an overview of the current research performed on saliva in relation to ASD, mutual complementing, and discrepancies that result in difficulties applying the observed markers in clinical practice. We emphasize the methodological limitations of saliva collection and processing as well as the lack of information regarding ASD diagnosis, which is critically discussed.
... Proteomic analysis using mass spectrometry can lead to the discovery of biomarkers in human biological fluids, including saliva. Studies by (Ngounou Wetie, Wormwood, Russell, et al., 2015) in an attempt to optimize the search for a saliva proteomic biomarker, analyzed the saliva proteome of individuals with ASD using the mass spectrometry (MS) technique and compared with neurotypical control individuals. The results showed statistically significant differences in several salivary proteins, including high prolactin-induced protein, lactotransferrin, Ig kappa chain C, Ig chain 1 region C, Ig lambda -2 chain C, neutrophil elastase, and polymeric immunoglobulin receptor. ...
The diagnosis of autistic spectrum disorder (ASD) remains clinical to this date. Immune dysfunction has been a recognized feature in ASD, and several researchers suggest that it can be used as a diagnostic tool by detecting biomarkers as well as an effective route for pharmacological intervention. The molecular biomarkers obtained from biological fluids are gaining relevance because of its lower invasiveness and ease of collection. Patients with autism are characterized by sensory reactivity and behavioral difficulties that can make sample collection problematic and, in this context, saliva appears to be a viable alternative for obtaining relevant biological information, being also especially indicated for children due to its painless and non-invasive sampling characteristics. Also, the saliva represents a valuable resource for studying possible biomarkers of autism. Following is a brief description of the main works published in recent years on saliva biomarkers for the diagnosis of autism. Copyright © 2020, Francisco S. B. Mota et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
... Under-expression of SMR3B has been found in infectious diseases (hepatitis) (Gonçalves et al, 2014) and neurological diseases (Ngounou Wetie et al, 2015). SM3B had its expression increased in both groups analyzed (5 and 10 km). ...
The aim was to characterize acute exercise-induced changes in salivary proteins of street runners. Saliva samples from 12 adult male athletes were collected before and immediately after a street race. Two groups were formed based on the distance covered, 5 km (n=4) and 10 km (n=8). Samples were subjected to depletion of amylase, albumin and immunoglobulin G. Then they were concentrated, digested and analyzed by nano-UPLC-tandem nano-ESI-MSE. A total of 69 proteins were identified. Significant changes were observed in the expression of 15 proteins in the 5 km group and 13 proteins in the 10 km group. Among the proteins with altered expression, only 7 had already been described in the literature in similar models (Alpha-Amylase 1, Lactoperoxidase, Alpha Skeletal Muscle Actin, Cystatin-B, Cystatin- SN, Cystatin- SA and Androgen-regulated Protein 3B in the submaxillary gland). This study has shown that street running induces acute changes in the salivary proteome. The results obtained add to the limited data available in the literature in the search for a better understanding of the acute effects of exercise.
Keywords:Proteomics; Mass Spectrometry; Exercise; Saliva.
... Hence, the objective and reliable biomarkers are needed for the diagnosis of autism. Previous proteomic studies on biomarkers and pathogenetic mechanisms of ASD have focused on blood, saliva and brain tissues (4)(5)(6)(7)(8). However, only a few studies have used urine. ...
Background:
Autism is a complex neurodevelopmental disorder. Objective and reliable biomarkers are crucial for the clinical diagnosis of autism. Urine can accumulate early changes of the whole body and is a sensitive source for disease biomarkers.
Methods:
The data-independent acquisition (DIA) strategy was used to identify differential proteins in the urinary proteome between autistic and non-autistic children aged 3-7 years. Receiver operating characteristic (ROC) curves were developed to evaluate the diagnostic performance of differential proteins.
Results:
A total of 118 differential proteins were identified in the urine between autistic and non-autistic children, of which 18 proteins were reported to be related to autism. Randomized grouping statistical analysis indicated that 91.5% of the differential proteins were reliable. Functional analysis revealed that some differential proteins were associated with axonal guidance signaling, endocannabinoid developing neuron pathway, synaptic long-term depression, agrin interactions at neuromuscular junction, phosphatase and tensin homolog deleted on chromosome 10 (PTEN) signaling and synaptogenesis signaling pathway. The combination of cadherin-related family member 5 (CDHR5) and vacuolar protein sorting-associated protein 4B (VPS4B) showed the best discriminative performance between autistic and non-autistic children with an area under the curve (AUC) value of 0.987.
Conclusions:
The urinary proteome could distinguish between autistic children and non-autistic children. This study will provide a promising approach for future biomarker research of neuropsychiatric disorders.
... In addition, pathways involved in redox mechanisms and inflammatory processes were in the focus (Voineagu et al., 2011;Feng et al., 2017;Gandal et al., 2018;Schwede et al., 2018;Abraham et al., 2019a;Gordon et al., 2021;Hewitson et al., 2021). However, there is a lack of overlap between the genes/proteins identified due to the heterogeneity of ASD and different cohorts of varying ages and severity of symptoms used in human proteomic/transcriptomics studies (Wetie et al., 2015b;Cortelazzo et al., 2016). Major gene/protein alterations identified throughout the studies mentioned in Supplementary Table 1 include interleukins and inflammatory cytokines, myelination, mitochondrial, and synaptic proteins (Broek et al., 2014;Wetie et al., 2015a;Feng et al., 2017). ...
Metal dyshomeostasis plays a significant role in various neurological diseases such as Alzheimer’s disease, Parkinson’s disease, Autism Spectrum Disorders (ASD), and many more. Like studies investigating the proteome, transcriptome, epigenome, microbiome, etc., for years, metallomics studies have focused on data from their domain, i.e., trace metal composition, only. Still, few have considered the links between other “omes,” which may together result in an individual’s specific pathologies. In particular, ASD have been reported to have multitudes of possible causal effects. Metallomics data focusing on metal deficiencies and dyshomeostasis can be linked to functions of metalloenzymes, metal transporters, and transcription factors, thus affecting the proteome and transcriptome. Furthermore, recent studies in ASD have emphasized the gut-brain axis, with alterations in the microbiome being linked to changes in the metabolome and inflammatory processes. However, the microbiome and other “omes” are heavily influenced by the metallome. Thus, here, we will summarize the known implications of a changed metallome for other “omes” in the body in the context of “omics” studies in ASD. We will highlight possible connections and propose a model that may explain the so far independently reported pathologies in ASD.
... In addition, these investigations are of utmost importance for attempts to identify biomarkers of autoimmune disorders such as Sjögren's syndrome 64 and systemic lupus erythematosus 65 . Finally, owing to noninvasive and easy collection of salivary samples, identifying disease biomarkers in saliva is of utmost importance for patients with neurological, psychiatric and neuroendocrine disorders such as autism 66 , schizophrenia and bipolar disorder 67 , and Parkinson's disease 68 . ...
Human saliva is rich in proteins of variable functions (e.g., enzymes, immunoglobulins, cytokines) and origin (blood plasma, salivary glands, or oral microflora). Circadian dynamics, volume and composition (electrolytes, pH, protein, etc.) of secreted saliva vary with local and systemic physiological and pathophysiological conditions. Therefore, the composition of saliva, protein in particular, has been intensively investigated to identify the potential markers and/or mechanisms of systemic and local diseases. Proteomic techniques used for the analysis of biological fluids have enabled great advances in salivary protein stabilization (as the main precondition for their analysis) and detection of those found in saliva in very low concentrations, including small proteins and peptides. This review brings the main characteristics of current proteomic techniques such as liquid chromatography-mass spectrometry, two-dimensional electrophoresis-mass spectrometry, and surface-enhanced laser desorption ionization/time of flight/mass spectrometry. These techniques enable simultaneous identification of hundreds and thousands of protein molecules, as well as identifying those of a potential biological value in particular states. This literature review is focused on the state-of-the-art and possibilities offered by proteomic techniques in analyzing the effects of orthodontic appliances on salivary protein composition and searching for potential markers of therapeutic success/failure or for the molecules by which therapeutic effects are achieved.
... The significant relationships found in the regression analysis may suggest that the potential crosstalk between oral bacteria and salivary miRNAs could be based on a general response of host to dysbiosis involving several miRNA families, as well as bacterial phyla [106][107][108][109][110][111][112][113]. ...
Recent evidence has demonstrated that salivary molecules, as well as bacterial populations, can be perturbed by several pathological conditions, including neuro-psychiatric diseases. This relationship between brain functionality and saliva composition could be exploited to unveil new pathological mechanisms of elusive diseases, such as Autistic Spectrum Disorder (ASD). We performed a combined approach of miRNA expression profiling by NanoString technology, followed by validation experiments in qPCR, and 16S rRNA microbiome analysis on saliva from 53 ASD and 27 neurologically unaffected control (NUC) children. MiR-29a-3p and miR-141-3p were upregulated, while miR-16-5p, let-7b-5p, and miR-451a were downregulated in ASD compared to NUCs. Microbiome analysis on the same subjects revealed that Rothia, Filifactor, Actinobacillus, Weeksellaceae, Ralstonia, Pasteurellaceae, and Aggregatibacter increased their abundance in ASD patients, while Tannerella, Moryella and TM7-3 decreased. Variations of both miRNAs and microbes were statistically associated to different neuropsychological scores related to anomalies in social interaction and communication. Among miRNA/bacteria associations, the most relevant was the negative correlation between salivary miR-141-3p expression and Tannerella abundance. MiRNA and microbiome dysregulations found in the saliva of ASD children are potentially associated with cognitive impairments of the subjects. Furthermore, a potential cross-talking between circulating miRNAs and resident bacteria could occur in saliva of ASD.
... If the goal is to compare (two or more) proteomes, then the samples are fractionated in such a way that no protein is lost. For example, if the sample is a biological fluid, then simply in-solution digestion or 1D-PAGE or 2D-PAGE followed by in gel digestion by trypsin should suffice for further MS analysis of those samples [3][4][5][6]. ...
The human genome is sequenced and is comprised of~30,000 genes, making humans just a little bit more complicated than worms or flies. However, complexity of humans is given by proteins that these genes code for, because one gene can produce many proteins mostly through alternative splicing and tissue-dependent expression of particular proteins. In addition, post-translational modifications (PTMs) in proteins greatly increase the number of gene products or protein isoforms. Furthermore, stable and transient interactions between proteins, protein isoforms/proteoforms and PTM-ed proteins (proteinprotein interactions, PPI) adds yet another level of complexity in humans and other organisms. In the past, all of these proteins were analyzed one at the time. Currently, they are analyzed by a less tedious method: mass spectrometry (MS) for two reasons: 1) because of the complexity of proteins, protein PTMs and PPIs and 2) because MS is the only method that can keep up with such a complex array of features. Here, we discuss the applications of mass spectrometry in protein analysis.
... In a simple, label-free method, a known concentration of an internal standard peptide can be spiked into samples prior to mass spectrometry analysis [148]. Likewise, an external standard peptide sample can be run in between samples on the mass spectrometer, and if the spectral count intensities of the standard runs are the same, the spectral counts/intensities of peptides in the actual samples can be compared as a relative quantitation [162][163][164][165]. In this case, the standard acts as proof that running conditions are identical enough that relative quantitation using spectral intensities can be used. ...
Proteomics is the field of study that includes the analysis of proteins, from either a basic science prospective or a clinical one. Proteins can be investigated for their abundance, variety of proteoforms due to post-translational modifications (PTMs), and their stable or transient protein–protein interactions. This can be especially beneficial in the clinical setting when studying proteins involved in different diseases and conditions. Here, we aim to describe a bottom-up proteomics workflow from sample preparation to data analysis, including all of its benefits and pitfalls. We also describe potential improvements in this type of proteomics workflow for the future.
... Transcriptomics studies use cDNA microarrays and high-throughput RNA sequencing technology to obtain gene expression data, combining with gene co-expression network analysis to discover the molecular mechanisms related to ASD [15,16]. Proteomics studies have found that the clinical manifestations of ASD may be related to changes in proteins, such as mutations leading to changes in protein and amino acid sequences, and mutations in gene regulatory regions leading to changes in protein expression or abnormal modification of proteins [17,18]. In recent years, the acquisition of specific biomarkers through metabolomics research is effective for early ASD screening and diagnosis. ...
... Because of its heterogeneous symptomatology and the push for more accurate and timely identifications, a significant amount of current medical research aims to identify specific differences in brain development (e.g. Courchesne, Campbell, & Solso, 2011) and genetic makeup (Yuen et al., 2017); and to create new diagnostic tools based on possible biomedical markers in blood (Anwar et al., 2018), urine (Suganya, Geetha, & Sujatha, 2015), or saliva (Ngounou Wetie et al., 2015), though results from these preliminary studies have yet to be validated. In the United States, the Interagency Autism Coordinating Committee recommended that the federal government double its autism research funding to "address the diagnosis, biology and causes of autism and, critically, efforts to improve services across the lifespan" (Pellicano et al., 2018, p. 82). ...
This qualitative research explored the knowledge, self-efficacy, and comfort of general education teachers supporting learners with high-functioning autism (HFA) in the mainstream classroom and their thoughts on related teacher professional development experiences and needs. 5 primary teachers from 5 different Ontario school boards participated in in-person, semi-structured interviews. 3 main findings emerged out of the data: (1) familiarity with students with HFA had a positive impact on teachers and students, which related to increased teacher self-efficacy and understanding of learners with HFA, changes to practice, and benefits to peers and other staff, with participants who had taught the greatest numbers of students with HFA reporting higher confidence ratings and demonstrating more knowledge of HFA; (2) systemic barriers impacted teachers’ ability to support all students, such as inadequate teacher preparation, inaccessibility of services, interventions, and physical and personnel resources; and (3) teachers envisioned their ideal professional development (PD) to support teacher learning, which included what they wanted to learn about HFA, factors increasing or decreasing the likelihood of their participation, as well as preferred characteristics and formats of PD, with all teachers underscoring the importance of opportunities to collaborate and problematize relevant classroom concerns with colleagues. Implications for teacher education programs and ongoing professional development for teachers, as well as potential directions for future research, are presented.
... Proteomics is the study of proteome, which consists from all proteins in a given sample. Proteomics involves sample preparation (and sometimes biochemical fractionation), protein digestion, mass spectrometry analysis, followed up data analysis for both protein identification and quantitation (40). Additional information that a particular proteomics experiment can provide is identification of protein isoforms, protein post-translational modifications and sometimes protein-protein interactions (41)(42)(43)(44). ...
Fatigue is a common and poorly understood problem that impacts approximately 45% of the United States (US) population. Fatigue has also been associated with fatigue-related driving accidents, school absences, decline in school performance and negative health outcomes. Fatigue has been linked to many diseases and is consistently underreported in medical care. Despite these high financial and societal costs, fatigue is a poorly understood problem and there is no consensus on how to measure fatigue. Proteomics is one of the most unbiased approach to measure differences in the protein levels from various biological fluids in two conditions, i.e. before and after mental exercise, aka fatigue. There are, however, challenges associated with such analyses: proteomics experiments are usually expensive and time consuming and also require a large number of participants. Here, we performed a proteomics experiment of three (pre- and post-fatigue) samples and also three matched controls (pre- and post-non-fatigue). We found no particular protein that has significant changes in fatigue sample upon treatment. We did note a potential association between changes in mental energy and Annexin A1. However, the study has value simply because it is an extra study in the field of fatigue, but also allows other to correlate our results with their results.
... Examination of autistic children in Turkey demonstrated a significant increase in serum NGF concentrations in ASD group as compared to neurotypic controls [6]. Certain other inflammatory markers including neutrophil elastase were also found to be elevated in ASD patients [7]. ...
Chronis rhinosinusitis is considered as a widespread public health issue with a prevalence of 10%. The disease significantly reduces quality of life and increases the risk of cardiovascular diseases as well as certain forms of cancer. Alteration of mucociliary clearance frequently observed in the patients and plays a significant role in disease pathogenesis. Certain studies have demonstrated that patients with chronic rhinosinusitis are characterized by significant reduction of essential trace elements and toxic metal overload. However, the particular mechanisms of the role of trace element dysbalance in chronic rhinosinusitis are unclear. We hypothesize that exposure to toxic trace elements (arsenic, nickel, cadmium) damages ciliary mucosal epithelium thus affecting mucociliary transport. In turn, altered mucociliary transport results in reduced removal of the inhaled metal-containing particles from nasal mucosa leading to their absorption and further aggravation of toxicity. Essential trace elements (zinc, selenium) play a significant role in regulation of mucociliary transport and immunity, thus their deficiency (either dietary or due to antagonism with toxic metals) may be associated with impaired functions and increased toxic metal toxicity. Therefore, a vicious circle involving metal accumulation and toxicity, essential element deficiency, impairment of mucociliary transport and metal particle removal, resulting in further accumulation of metals and aggravation of toxic effects is formed. The present hypothesis is supported by the findings on the impact of trace elements especially zinc and arsenic on mucociliary clearance, the role of mucociliary transport in heavy metal particles elimination from the airways, trace element dysbalance in chronic rhinosinusitis, as well as toxic and essential metal antagonism. The data from hypothesis testing and its verification may be used for development of therapeutic approach for management of chronic rhinosinusitis. Particularly, the use of essential elements (zinc, selenium) may reduce toxic metal toxicity thus destroying the vicious circle of heavy metal exposure, toxicity, alteration of mucociliary clearance, and aggravation of chronic rhinosinusitis. Essential element supplementation may be considered as a tool for management of chronic refractory rhinosinusitis. In addition, analysis of essential and toxic trace element status may provide an additional diagnostic approach to risk assessment of chronic rhinosinusitis in highly polluted environments.
... Ngounou Wetie et al. [77] have investigated the use of salivary proteins as possible markers for early onset of Autism Spectrum Disorders (ASDs). Authors have identified increased levels of apolipoproteins apoA1 and apoA4 and of serum paraoxonase/arylesterase 1 (PON1) in ASD sera compared to healthy controls in blood serum and have tested the hypothesis that levels of these peptides might also be elevated in saliva. ...
... As individuals with ASD and marked immune-inflammatory dysfunction are likely to benefit from treatment with TSO and other immunomodulatory treatments, future work should also measure the correlation between immune function changes and improvement in behaviour. Further exploration of target engagement of the CNS immune system and use of biomarkers such as PET measures of activated microglia (Suzuki et al. 2013), measures of pro-inflammatory cytokine profiles in blood and CSF (Jyonouchi et al. 2014;Rose and Ashwood 2014), and proteomic studies of salivary immune-inflammatory proteins (Ngounou Wetie et al. 2015) might help in selecting a patient population with immune-inflammatory dysfunction, who would be more likely to respond to TSO treatment, and provide evidence for target engagement associated with treatment response. ...
Objectives: Inflammatory mechanisms are implicated in the etiology of Autism Spectrum Disorder (ASD), and use of the immunomodulator Trichuris Suis Ova (TSO) is a novel treatment approach. This pilot study determined the effect sizes for TSO vs. placebo on repetitive behaviors, irritability and global functioning in adults with ASD.
Methods: A 28-week double-blind, randomized two-period crossover study of TSO vs. placebo in 10 ASD adults, ages 17 to 35, was completed, with a 4-week washout between each 12-week period at Montefiore Medical Center, Albert Einstein College of Medicine. Subjects with ASD, history of seasonal, medication or food allergies, Y-BOCS ≥ 6 and IQ ≥70 received 2500 TSO ova or matching placebo every two weeks of each 12-week period.
Results: Large effect sizes for improvement in repetitive behaviors (d = 1.0), restricted interests (d = 0.82), rigidity (d = 0.79), and irritability (d = 0.78) were observed after 12 weeks of treatment. No changes were observed in the social-communication domain. Differences between treatment groups did not reach statistical significance. TSO had only minimal, non-serious side effects.
Conclusions: This proof-of-concept study demonstrates the feasibility of TSO for the treatment of ASD, including a favorable safety profile, and moderate to large effect sizes for reducing repetitive behaviors and irritability.
... As summarized by Hassan et al. many important biological functions of PIP have been identified, such as the inhibition of bacterial growth, the involvement in fertilization, immune regulation, tumor progression and protein binding [3]. Recently, PIP was shown to be significantly increased in patients suffering from Autism Spectrum Disorder (ASD) [7]. The level of PIP can act as diagnostic marker or to monitor success of chemotherapy in breast cancer [8][9][10][11]. ...
Prolactin-inducible protein (PIP) is a glycoprotein found in body secretions from exocrine glands like saliva and seminal plasma. Important biological functions of PIP concentrations have been demonstrated, e.g. in tumor diagnosis and progression. PIP quantity has been also found useful to determine the success of chemotherapy of mammary carcinoma. Here, we present the analysis of the N-glycosylation of PIP isolated from different sources by LC-MS(/MS) and ¹H-NMR. We found a very uncommon N-type glycosylation of PIP in healthy individuals from both, seminal fluid and saliva. PIP carries unusual highly fucosylated N-linked glycans with multiple Lewisy (Ley) epitopes on bi-, tri- and tetraantennary structures resulting in up to nine fucosyl residues on a tetraantennary glycan. In most organs, Ley epitopes are not present on N-glycans except in case of a tumor when it is highly up-regulated and important for prognosis. Here, for the first time on a specific glycoprotein Ley antigens are unambiguously characterized on an N-type glycan by NMR spectroscopy. So far, for specific glycoproteins Ley epitopes had only been reported on O-glycans. Furthermore, a correlation between a nonsynonymous single nucleotide polymorphism (SNP) and glycosylation pattern was detected: individuals heterozygous for the SNP causing the amino acid exchange ⁵¹Gln to ⁵¹His have glycan structures with a higher degree of sialylation compared to individuals lacking the SNP.
... This is also true for recent studies examining metabolomics, 61 62 markers of inflammation 63 and oxidative stress, 64 and salivary proteomics. 65 Such findings cannot be readily generalized to early detection because biomarkers generally reflect dynamic processes that change over the course of development. Cross sectional studies of blood based biomarkers in newborn and infant samples may be more informative-for example, in one case-control study mRNA expression profiles in community identified toddlers with ASD differed from those of typically developing controls, with optimal sensitivity and specificity of 73% and 68%, respectively, in a cross validated sample. ...
Autism spectrum disorder (ASD) has a variety of causes, and its clinical expression is generally associated with substantial disability throughout the lifespan. Recent advances have led to earlier diagnosis, and deep phenotyping efforts focused on high risk infants have helped advance the characterization of early behavioral trajectories. Moreover, biomarkers that measure early structural and functional connectivity, visual orienting, and other biological processes have shown promise in detecting the risk of autism spectrum disorder even before the emergence of overt behavioral symptoms. Despite these advances, the mean age of diagnosis is still 4-5 years. Because of the broad consistency in published guidelines, parameters for high quality comprehensive assessments are available; however, such models are resource intensive and high demand can result in greatly increased waiting times. This review describes advances in detecting early behavioral and biological markers, current options and controversies in screening for the disorder, and best practice in its diagnostic evaluation including emerging data on innovative service models.
Per- and polyfluoroalkyl substances (PFAS) are a diverse family of industrially significant synthetic chemicals infamous for extreme environmental persistence and global environmental distribution. Many PFAS are bioaccumulative and biologically active mainly due to their tendency to bind with various proteins. These protein interactions may be the most important element in determining the accumulation potential and tissue distribution of individual PFAS. Trophodynamics studies including aquatic food webs present inconsistent evidence for PFAS biomagnification. This study strives to identify whether the observed variability in PFAS bioaccumulation potential among species could correspond with interspecies protein composition differences. Specifically, this work compares the perfluorooctane sulfonate (PFOS) serum protein binding potential and the tissue distribution of ten perfluoroalkyl acids (PFAAs) detected in alewife (Alosa pseudoharengus), deepwater sculpin (Myoxocephalus thompsonii), and lake trout (Salvelinus namaycush) of the Lake Ontario aquatic piscivorous food web. These three fish sera and fetal bovine reference serum all had unique total serum protein concentrations. Serum protein-PFOS binding experiments showed divergent patterns between fetal bovine serum and fish sera, suggesting potentially two different PFOS binding mechanisms. To identify interspecies differences in PFAS-binding serum proteins, fish sera were pre-equilibrated with PFOS, fractionated by serial molecular weight cut-off filter fractionation, followed by liquid chromatography-tandem mass spectrometry analysis of the tryptic protein digests and the PFOS extracts of each fraction. This workflow identified similar serum proteins for all fish species. However, serum albumin was only identified in lake trout, suggesting apolipoproteins are likely the primary PFAA transporters in alewife and deepwater sculpin sera. PFAA tissue distribution analysis provided supporting evidence for interspecies variations in lipid transport and storage, which may also contribute to the varied PFAA accumulation in these species. Proteomics data are available via ProteomeXchange with identifier PXD039145.
Autism spectrum disorder (ASD) is a developmental and neurological disease that starts in beginning of childhood and remains all through life. ASD manifested by difficulties in social communications and interactions and constrained, repetitive actions. ASD prevalence is steadily rising globally, posing significant social and economic consequences. There is currently no medication for autism treatment because its etiology is not fully known. However, there are several behavioral therapies that can help with supplementary symptoms of autism, especially if started at a young age. Finding biomarkers for ASD is thus becoming important. Although diagnostic biomarkers have not yet been developed, investigations of immune system, inflammation, and microRNAs, as well as genomics and gene testing, proteomics, metabolomics, and transcriptomics, have all been conducted. Many proteins can serve as ASD blood biomarkers since proteomic investigations show that several proteins' levels in plasma and serum are altered in ASD. This review aimed is to focus on protein biomarkers for ASD.
Introduction:
Autism spectrum disorder (ASD) is a neurodevelopmental disorder initiating in the first three years of life. Early initiation of management therapies can significantly improve the health and quality of life of ASD subjects. Thus, indicating the need for suitable biomarkers for the early identification of ASD. Various biological domains were investigated in the quest for reliable biomarkers. However, most biomarkers are in the preliminary stage, and clinical validation is yet to be defined. Exosome based research gained momentum in various Central Nervous System disorders for biomarker identification. However, the utility and prospect of exosomes in ASD is still underexplored.
Areas covered:
In the present review, we summarised the biomarker discovery current status and the future of brain-specific exosomes in understanding pathophysiology and its potential as a biomarker. The studies reviewed herein were identified via systematic search (dated: June 2021) of PubMed using variations related to autism (ASD OR autism OR Autism spectrum disorder) AND exosomes AND/OR biomarkers.
Expert opinion:
As exosomess are highly relevant in brain disorders like ASD, direct access to brain tissue for molecular assessment is ethically impossible. Thus investigating the brain-derived exosomes would undoubtedly answer many unsolved aspects of the pathogenesis and provide reliable biomarkers.
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by early-onset social-communication challenges, restricted and repetitive behaviors, or unusual sensory-motor behaviors. A lack of specific biomarkers hinders the early diagnosis and treatment of this disease in many children. This study analyzes and validates potential urinary biomarkers using mass spectrometry proteomics. Global proteomics profiles of urine from 19 ASD patients and 19 healthy control subjects were compared to identify significantly changed proteins. These proteins were validated with targeted proteomics using parallel reaction monitoring (PRM) in an independent validation set consisting of samples from 40 ASD patients and 38 healthy controls. A total of 34 significantly changed proteins were found in the discovery set, among which seven proteins were identified as potential biomarkers for ASD through PRM assays in the validation set. Of these seven proteins, immunoglobulin kappa variable 4–1, immunoglobulin kappa variable 3–20, and immunoglobulin lambda variable 1–51 were up-regulated, while ATP synthase F1 subunit alpha, 10 kDa heat shock protein, apolipoprotein C-III, and arylsulfatase F were down-regulated. Six of these seven proteins support previous findings that ASD is accompanied by altered immune response and lipid metabolism, as well as mitochondrial dysfunction. This study lays the groundwork for additional research using biomarkers to clinically diagnose ASD. The proteomics and PRM raw data of this study have been deposited under the accession number IPX0002592000 at iProX.
Significance
This study identified 34 proteins in urine of ASD patients that were significantly changed from the urinary proteins of healthy subjects using LC-MS/MS-based proteomics in a discovery set. Seven of these proteins were validated by PRM analysis in an independent validation set. This report represents the first description of combined label-free quantitative proteomics and PRM analysis of targeted proteins for discovery of ASD urinary biomarkers. The results will be helpful for early diagnosis and can provide additional insight into the molecular mechanisms of ASD.
Background
Autism spectrum disorder (ASD) is a neurodevelopmental disorder with complex genetics, characterized by impaired social communication and repetitive behaviors and interests. The involvement of lipid metabolism in ASD pathophysiology has been demonstrated in previous studies; however, the molecular mechanisms of abnormal lipid metabolism are not fully understood. A mutation in Lipoprotein lipase (LPL), which has central roles in lipid metabolism, has been identified in patients with ASD. We have reported that Lpl is downregulated in ASD model mice. Therefore, we explored the role of LPL in lipid metabolism in ASD patients.
Methods
We quantified LPL amount, LPL activity, and glycosylphosphatidylinositol-anchored high-density lipoprotein-binding protein 1 (GPIHBP1) amount in the plasma of ASD male subjects (n = 28) compared with typical development (TD) controls (n = 28), using enzyme-linked immunosorbent assay for LPL amount and fluorometric assays for LPL activity. We examined the correlations of plasma LPL with GPIHBP1 and clinical characteristic scores from the Autism Diagnostic Interview-Revised (ADI-R).
Results
There was higher LPL activity, but not LPL amount, in the plasma of ASD subjects compared with controls. Receiver operating characteristics analysis also demonstrated that pure LPL activity (LPL activity/LPL amount) is a useful indicator to distinguish ASD from TD controls. There were no correlations between plasma LPL and ADI-R scores; however, LPL activity was negatively correlated with GPIHBP1 levels in the plasma of ASD subjects.
Conclusions
Our results demonstrate increased activity of plasma LPL, regulated by GPIHBP1, in ASD, providing novel insights into the lipid metabolism associated with ASD pathophysiology.
Neurologic diseases (ND) are disorders of the brain affecting the central and peripheral nervous system, and characterized by a progressive loss of memory and cognition. Because of their complicated causes and manifestations, early diagnosis of these neurological conditions remains a great challenge and may involve invasive and painful tests. In this chapter, we will review some studies revealing salivary biomarkers of most known ND in humans and animals in order to establish an overview about the advances made in this field.
The development of biomarkers of psychiatric disease has been among the highest priorities in mental health research over the past century. The ideal biomarkers in this context would serve one of several purposes, such as (1) distinguish individuals with and without psychiatric disease, (2) provide evidence that treatments mitigate not only the behavioral symptoms of disorders but also the biological underpinnings, and (3) elucidate future risk for development of a disorder. To date, salivary markers have been used in each of these contexts. In this chapter, we summarize the history of the use of salivary biomarkers in research aimed at identifying, characterizing, and treating psychiatric disorders, such as mood and anxiety disorders, psychotic disorders, and neurodevelopmental disorders. Finally, this chapter reviews the strengths and limitations of the knowledge gained to date and introduces how salivary bioscience can contribute to the next generation of research on the course, causes, and treatment for psychiatric disorders.
Autism spectrum disorder (ASD) refers to a group of complex neurodevelopmental disorders characterized by social interaction and communication deficits and repetitive and stereotyped behaviors. As the etiology and pathogenesis of the disorder have not yet been elucidated, specific treatment and reliable diagnostic biomarkers are not available. Early behavioral interventions have been shown to substantially improve symptoms in children with ASD. Given the rapidly increasing prevalence of ASD, there is an urgent need to identify related diagnostic biomarkers. Although specific diagnostic markers for ASD have not been identified, the related research has made progress in different aspects. This review summarizes recent findings of the use of genes, proteins, peptides, and metabolites as diagnostic markers for ASD. The associated techniques include genetic testing and proteomic and metabolomic analyses. In addition, some studies have focused on single or several proteins and metabolites. Moreover, transcriptomic analysis, immune disturbances and cytokine may also be used for this purpose. The pathogenesis involving genes, proteins, and metabolites is also discussed here.
In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color “molecular microscope” by its emerging “molecular pictures” offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism’s reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and “Eco-Evo-Devo” integrative biology in the current context of global environmental challenges.
Background
The mechanisms underlying autism spectrum disorder (ASD) remain unclear, and clinical biomarkers are not yet available for ASD. Differences in dysregulated proteins in ASD have shown little reproducibility, which is partly due to ASD heterogeneity. Recent studies have demonstrated that subgrouping ASD cases based on clinical phenotypes is useful for identifying candidate genes that are dysregulated in ASD subgroups. However, this strategy has not been employed in proteome profiling analyses to identify ASD biomarker proteins for specific subgroups.
Methods
We therefore conducted a cluster analysis of the Autism Diagnostic Interview-Revised (ADI-R) scores from 85 individuals with ASD to predict subgroups and subsequently identified dysregulated genes by reanalyzing the transcriptome profiles of individuals with ASD and unaffected individuals. Proteome profiling of lymphoblastoid cell lines from these individuals was performed via 2D-gel electrophoresis, and then mass spectrometry. Disrupted proteins were identified and compared to the dysregulated transcripts and reported dysregulated proteins from previous proteome studies. Biological functions were predicted using the Ingenuity Pathway Analysis (IPA) program. Selected proteins were also analyzed by Western blotting.
Results
The cluster analysis of ADI-R data revealed four ASD subgroups, including ASD with severe language impairment, and transcriptome profiling identified dysregulated genes in each subgroup. Screening via proteome analysis revealed 82 altered proteins in the ASD subgroup with severe language impairment. Eighteen of these proteins were further identified by nano-LC-MS/MS. Among these proteins, fourteen were predicted by IPA to be associated with neurological functions and inflammation. Among these proteins, diazepam-binding inhibitor (DBI) protein was confirmed by Western blot analysis to be expressed at significantly decreased levels in the ASD subgroup with severe language impairment, and the DBI expression levels were correlated with the scores of several ADI-R items.
Conclusions
By subgrouping individuals with ASD based on clinical phenotypes, and then performing an integrated transcriptome-proteome analysis, we identified DBI as a novel candidate protein for ASD with severe language impairment. The mechanisms of this protein and its potential use as an ASD biomarker warrant further study.
Autism spectrum disorder (ASD) is a neurological and developmental condition that begins early in childhood and lasts throughout life. The epidemiology of ASD is continuously increasing all over the world with huge social and economical burdens. As the etiology of autism is not completely understood, there is still no medication available for the treatment of this disorder. However, some behavioral interventions are available to improve the core and associated symptoms of autism, particularly when initiated at an early stage. Thus, there is an increasing demand for finding biomarkers for ASD. Although diagnostic biomarkers have not yet been established, research efforts have been carried out in neuroimaging and biological analyses including genomics and gene testing, proteomics, metabolomics, transcriptomics, and studies of the immune system, inflammation, and microRNAs. Here, we will review the current progress in these fields and focus on new methods, developments, research strategies, and studies of blood-based biomarkers.
Proteomics is a powerful tool to study biological systems and is potentially useful in identifying biomarkers for clinical screening and diagnosis, for monitoring treatment, and for exploring pathogenetic mechanisms in autism. Unlike numerous other experimental approaches employed in autism research, there have been few proteomic-based analyses. Herein, we discuss the findings of studies regarding autism that utilized a proteomic approach and review key considerations in sample acquisition, processing, and analysis. Most proteomic studies on autism used blood or other peripheral tissues. Few studies used brain tissue, the main site of biological difference between persons with autism and others. The findings have varied and are not yet replicated. Some showed abnormalities of synaptic proteins or proteins of mitochondrial bioenergetics. Various abnormalities of proteins relating to immune processes and lipid metabolism have also been noted. Whether any of the proteomic differences between autism and control cases are primary or secondary phenomena is currently unclear. Consequently, no definitive biomarkers for autism have been identified, and the pathophysiological insights provided by proteomic studies to date are uncertain in the absence of replication. Based on this body of work and the challenges in using proteomics to study autism, we suggest considerations for future study design. These include attention to subject and specimen inclusion/exclusion criteria, attention to the state of specimens prior to proteomic analysis, and use of a replicate set of specimens. We end by discussing especially promising applications of proteomics in the study of autism pathobiology.
Breast Cancer (BC) remains a major cause of mortality, and early detection is considered important for reducing BC‐associated deaths. Early detection of BC is challenging in young women, due to the limitations of mammography on the dense breast tissue of young women. We recently reported results of a pilot proteomics study, using one‐dimensional polyacrylamide gel electrophoresis (1D‐PAGE) and mass spectrometry (MS) to investigate differences in milk proteins from women with and without BC. Here, we applied two‐dimensional polyacrylamide gel electrophoresis (2D‐PAGE) and MS to compare the protein pattern in milk from the breasts of a single woman who was diagnosed with BC in one breast 24 months after donating her milk. Statistically different gel spots were picked for protein digestion followed by nanoliquid chromatography tandem MS (nanoLC‐MS/MS) analysis. The upregulated proteins in BC versus control are alpha‐amylase, gelsolin isoform a precursor, alpha‐2‐glycoprotein 1 zinc isoform CRA_b partial, apoptosis‐inducing factor 2 and vitronectin. Several proteins were downregulated in the milk of the breast later diagnosed with cancer as compared to the milk from the healthy breast, including different isoforms of albumin, cholesterol esterase, different isoforms of lactoferrin, different proteins from the casein family and different isoforms of lysozyme. Results warrant further studies to determine the usefulness of these milk proteins for assessing risk and detecting occult disease.
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Purpose
: Autism spectrum disorder (ASD) is a neurological and developmental disorder that begins early in childhood and lasts throughout one's life. Early diagnosis is essential for ASD since early treatment can enable children with ASD to make significant gains in language and social skills, but remains challenging since there are currently no specific biomarkers of ASD. The study aimed to identify serum biomarkers for ASD.
Experimental design
: Serum of Han Chinese children with ASD (n = 68) and age‐matched healthy controls (n = 80) was analyzed using magnetic bead‐based separation combined with mass spectrum.
Results
: Eight potential ASD serum biomarker peaks (m/z: 3886.69, 7775.12, 2381.71, 6638.63, 3319.17, 894.34, 4968.59, and 5910.53) with higher expression in ASD group were further identified as peptide regions of Plasma Serine Protease Inhibitor Precursor (SERPINA5), Platelet Factor 4 (PF4), Fatty Acid Binding Protein 1(FABP1), Apolipoprotein C‐I Precursor (APOC1), Alpha‐fetoprotein Precursor (AFP), Carboxypeptidase B2 (CPB2), Trace Amine‐associated Receptor 6 (TAAR6) and Isoform1 of Fibrinogen Alpha Chain Precursor (FGA). The expression of identified proteins was validated by enzyme‐linked immunosorbent assay (ELISA).
Conclusions and medical relevance
: Our findings reveal the exceptional disease etiology of ASD from a serum proteomic perspective, and the identified proteins might be potential biomarkers for ASD diagnosis.
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Problem/Condition: Autism spectrum disorder (ASD). Period Covered: 2010. Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system in the United States that provides estimates of the prevalence of ASD and other characteristics among children aged 8 years whose parents or guardians live in 11 ADDM sites in the United States. ADDM surveillance is conducted in two phases. The first phase consists of screening and abstracting comprehensive evaluations performed by professional providers in the community. Multiple data sources for these evaluations include general pediatric health clinics and specialized programs for children with developmental disabilities. In addition, most ADDM Network sites also review and abstract records of children receiving special education services in public schools. The second phase involves review of all abstracted evaluations by trained clinicians to determine ASD surveillance case status. A child meets the surveillance case definition for ASD if a comprehensive evaluation of that child completed by a qualified professional describes behaviors consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (including atypical autism), or Asperger disorder. This report provides updated prevalence estimates for ASD from the 2010 surveillance year. In addition to prevalence estimates, characteristics of the population of children with ASD are described. Results: For 2010, the overall prevalence of ASD among the ADDM sites was 14.7 per 1,000 (one in 68) children aged 8 years. Overall ASD prevalence estimates varied among sites from 5.7 to 21.9 per 1,000 children aged 8 years. ASD prevalence estimates also varied by sex and racial/ethnic group. Approximately one in 42 boys and one in 189 girls living in the ADDM Network communities were identified as having ASD. Non-Hispanic white children were approximately 30% more likely to be identified with ASD than non-Hispanic black children and were almost 50% more likely to be identified with ASD than Hispanic children. Among the seven sites with sufficient data on intellectual ability, 31% of children with ASD were classified as having IQ scores in the range of intellectual disability (IQ <= 70), 23% in the borderline range (IQ = 71-85), and 46% in the average or above average range of intellectual ability (IQ > 85). The proportion of children classified in the range of intellectual disability differed by race/ethnicity. Approximately 48% of non-Hispanic black children with ASD were classified in the range of intellectual disability compared with 38% of Hispanic children and 25% of non-Hispanic white children. The median age of earliest known ASD diagnosis was 53 months and did not differ significantly by sex or race/ethnicity. Interpretation: These findings from CDC's ADDM Network, which are based on 2010 data reported from 11 sites, provide updated population-based estimates of the prevalence of ASD in multiple communities in the United States. Because the ADDM Network sites do not provide a representative sample of the entire United States, the combined prevalence estimates presented in this report cannot be generalized to all children aged 8 years in the United States population. Consistent with previous reports from the ADDM Network, findings from the 2010 surveillance year were marked by significant variations in ASD prevalence by geographic area, sex, race/ethnicity, and level of intellectual ability. The extent to which this variation might be attributable to diagnostic practices, underrecognition of ASD symptoms in some racial/ethnic groups, socioeconomic disparities in access to services, and regional differences in clinical or school-based practices that might influence the findings in this report is unclear. Public Health Action: ADDM Network investigators will continue to monitor the prevalence of ASD in select communities, with a focus on exploring changes within these communities that might affect both the observed prevalence of ASD and population-based characteristics of children identified with ASD. Although ASD is sometimes diagnosed by 2 years of age, the median age of the first ASD diagnosis remains older than age 4 years in the ADDM Network communities. Recommendations from the ADDM Network include enhancing strategies to address the need for 1) standardized, widely adopted measures to document ASD severity and functional limitations associated with ASD diagnosis; 2) improved recognition and documentation of symptoms of ASD, particularly among both boys and girls, children without intellectual disability, and children in all racial/ethnic groups; and 3) decreasing the age when children receive their first evaluation for and a diagnosis of ASD and are enrolled in community-based support systems.
Autism spectrum disorder (ASD) is a heterogeneous disease in which efforts to define subtypes behav-iorally have met with limited success. Hypothesiz-ing that genetically based subtype identification may prove more productive, we resequenced the ASD-associated gene CHD8 in 3,730 children with developmental delay or ASD. We identified a total of 15 independent mutations; no truncating events were identified in 8,792 controls, including 2,289 un-affected siblings. In addition to a high likelihood of an ASD diagnosis among patients bearing CHD8 muta-tions, characteristics enriched in this group included macrocephaly, distinct faces, and gastrointestinal complaints. chd8 disruption in zebrafish recapitu-lates features of the human phenotype, including increased head size as a result of expansion of the forebrain/midbrain and impairment of gastrointes-tinal motility due to a reduction in postmitotic enteric neurons. Our findings indicate that CHD8 disrup-tions define a distinct ASD subtype and reveal unex-pected comorbidities between brain development and enteric innervation. INTRODUCTION
Autism spectrum disorder (ASD) diagnosis is increasing, with 1/88 children believed to be affected by the disorder, with a most recent survey suggesting numbers as high as 1/50. Treatment and understanding of ASD causes is a pressing health concern. ASD protein biomarkers may provide clues about ASD cause. Protein biomarkers for ASDs could be used for ASD diagnosis, subtyping, treatment monitoring and identifying therapeutic targets. Here we analyzed the sera from 7 children with ASD and 7 matched controls using Tricine gel electrophoresis (Tricine-PAGE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Overall, we found increased levels of apolipoproteins (Apos) ApoA1 and ApoA4, involved in cholesterol metabolism and of serum paraoxanase/arylesterase 1 (PON1), involved in preventing oxidative damage, in the sera of children with ASD, compared with their matched controls. All three proteins are predicted to interact with each other and are parts of High Density Lipoproteins (HDLs). Further studies are needed to validate these findings in larger subject numbers.This article is protected by copyright. All rights reserved
Alzheimer's disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling.
Our approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (SR) based method followed by prioritization using clusters derived from PPI network. SR for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes.
With the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers then candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD.
The higher prevalence of Asperger Syndrome (AS) and other autism spectrum conditions in males has been known for many years. However, recent multiplex immunoassay profiling studies have shown that males and females with AS have distinct proteomic changes in serum.
Here, we analysed sera from adults diagnosed with AS (males = 14, females = 16) and controls (males = 13, females = 16) not on medication at the time of sample collection, using a combination of multiplex immunoassay and shotgun label-free liquid chromatography mass spectrometry (LC-MSE). The main objective was to identify sex-specific serum protein changes associated with AS.
Multiplex immunoassay profiling led to identification of 16 proteins that were significantly altered in AS individuals in a sex-specific manner. Three of these proteins were altered in females (ADIPO, IgA, APOA1), seven were changed in males (BMP6, CTGF, ICAM1, IL-12p70, IL-16, TF, TNF-alpha) and six were changed in both sexes but in opposite directions (CHGA, EPO, IL-3, TENA, PAP, SHBG). Shotgun LC-MSE profiling led to identification of 13 serum proteins which had significant sex-specific changes in the AS group and, of these, 12 were altered in females (APOC2, APOE, ARMC3, CLC4K, FETUB, GLCE, MRRP1, PTPA, RN149, TLE1, TRIPB, ZC3HE) and one protein was altered in males (RGPD4). The free androgen index in females with AS showed an increased ratio of 1.63 compared to controls.
Taken together, the serum multiplex immunoassay and shotgun LC-MSE profiling results indicate that adult females with AS had alterations in proteins involved mostly in lipid transport and metabolism pathways, while adult males with AS showed changes predominantly in inflammation signalling. These results provide further evidence that the search for biomarkers or novel drug targets in AS may require stratification into male and female subgroups, and could lead to the development of novel targeted treatment approaches.
The etiology and pathogenesis of many psychiatric disorders are unclear with many signaling pathways and complex interactions still unknown. Primary information provided from gene expression or brain activity imaging experiments is useful, but can have limitations. There is a current effort focusing on the discovery of diagnostic and prognostic proteomic potential biomarkers for psychiatric disorders. Despite this work, there is still no biological diagnostic test available for any mental disorder. Biomarkers may advance the care of psychiatric illnesses and have great potential to knowledge of psychiatric disorders but several drawbacks must be considered. Here, we describe the potential of proteomic biomarkers for better understanding and diagnosis of psychiatric disorders and current putative biomarkers for schizophrenia, depression, autism spectrum disorder and attention deficit/hyperactivity disorder.
Unlabelled:
Autism spectrum disorder (ASD) is a common and severe neuro-developmental disorder in early childhood which is defined by social and communication deficits and repetitive and stereotypic behaviours. The aetiology of ASD remains poorly understood. Susceptibility to development of ASD has significant environmental components, in addition to the profound genetic heritability. Few genes have been associated to the risk for ASD development. There is substantial evidence implicating chronic neurological inflammation and immune dysregulation leading to upregulation of inflammatory cytokines in the ASD brain, probably due to altered blood-brain barrier function. The immune system is characterized by excessive and skewed cytokine responses, modulated T cell reactivity, decreased regulation and production of immunosuppressive cytokines, modified NK function and increased autoantibody production.
Conclusion:
The perinatal environment generates vulnerability to chronic neuro-inflammation in the brain associated with profound modulation and dysregulation in the immune system leading to the rapid development of ASD in genetically susceptible children.
Autism spectrum disorders (ASD) are a heterogeneous group of disorders which have complex behavioural phenotypes. Although ASD is a highly heritable neuropsychiatric disorder, genetic research alone has not provided a profound understanding of the underlying causes. Recent developments using biochemical tools such as transcriptomics, proteomics and cellular models, will pave the way to gain new insights into the underlying pathological pathways. This review addresses the state-of-the-art in the search for molecular biomarkers for ASD. In particular, the most important findings in the biochemical field are highlighted and the need for establishing streamlined interaction between behavioural studies, genetics and proteomics is stressed. Eventually, these approaches will lead to suitable translational ASD models and, therefore, a better disease understanding which may facilitate novel drug discovery efforts in this challenging field.
Major salivary gland tumours are uncommon neoplasms of the head and neck. The increase of precise pre-operative diagnosis is crucial for their correct management and the identification of molecular markers would surely improve the required accuracy. In this study we performed a comparative proteomic analysis of fine needle aspiration fluids of the most frequent benign neoplasms of major salivary glands, namely pleomorphic adenoma and Warthin's tumour, in order to draw their proteomic profiles and to point out their significant features. Thirty-five patients submitted to parotidectomy were included in the study, 22 were identified to have pleomorphic adenoma and 14 Warthin's tumour. Fine needle aspiration samples were processed using a two-dimensional electrophoresis/mass spectrometry-based approach. A total of 26 differentially expressed proteins were identified. Ingenuity software was used to search the biological processes to which these proteins belong and to construct potential networks. Intriguingly, all Warthin's tumour up-regulated proteins such as Ig gamma-1 chain C region, Ig kappa chain C region and Ig alpha-1 chain C region and S100A9 were correlated to immunological and inflammatory diseases, while pleomorphic adenomas such as annexin A1, annexin A4, macrophage-capping protein, apolipoprotein E and alpha crystalline B chain were associated with cell death, apoptosis and tumorigenesis, showing different features of two benign tumours. Overall, our results shed new light on the potential usefulness of a proteomic approach to study parotid tumours and in particular up regulated proteins are able to discriminate two types of benign parotid lesions.
The search for molecules that can act as potential biomarkers is increasing in the scientific community, including in the field of psychiatry. The field of proteomics is evolving and its indispensability for identifying biomarkers is clear. Among proteomic tools, mass spectrometry is the core technique for qualitative and quantitative identification of protein markers. While significant progress has been made in the understanding of biomarkers for neurodegenerative diseases such as Alzheimer’s disease, multiple sclerosis and Parkinson’s disease, psychiatric disorders have not been as extensively investigated. Recent and successful applications of mass spectrometry-based proteomics in fields such as cardiovascular disease, cancer, infectious diseases and neurodegenerative disorders suggest a similar path for psychiatric disorders. In this brief review, we describe mass spectrometry and its use in psychiatric biomarker research and highlight some of the possible challenges of undertaking this type of work. Further, specific examples of candidate biomarkers are highlighted. A short comparison of proteomic with genomic methods for biomarker discovery research is presented. In summary, mass spectrometry-based techniques may greatly facilitate ongoing efforts to understand molecular mechanisms of psychiatric disorders.
Autism Spectrum Disorders (ASD) are a group of heterogeneous neurodevelopmental conditions presenting in early childhood with a prevalence ranging from 0.7% to 2.64%. Social interaction and communication skills are impaired and children often present with unusual repetitive behavior. The condition persists for life with major implications for the individual, the family and the entire health care system. While the etiology of ASD remains unknown, various clues suggest a possible association with altered immune responses and ASD. Inflammation in the brain and CNS has been reported by several groups with notable microglia activation and increased cytokine production in postmortem brain specimens of young and old individuals with ASD. Moreover several laboratories have isolated distinctive brain and CNS reactive antibodies from individuals with ASD. Large population based epidemiological studies have established a correlation between ASD and a family history of autoimmune diseases, associations with MHC complex haplotypes, and abnormal levels of various inflammatory cytokines and immunological markers in the blood. In addition, there is evidence that antibodies that are only present in some mothers of children with ASD bind to fetal brain proteins and may be a marker or risk factor for ASD. Studies involving the injection of these ASD specific maternal serum antibodies into pregnant mice during gestation, or gestational exposure of Rhesus monkeys to IgG subclass of these antibodies, have consistently elicited behavioral changes in offspring that have relevance to ASD. We will summarize the various types of studies associating ASD with the immune system, critically evaluate the quality of these studies, and attempt to integrate them in a way that clarifies the areas of immune and autoimmune phenomena in ASD research that will be important indicators for future research.
Autism spectrum disorders (ASDs) are neurodevelopmental in origin, affecting an estimated 1 in 88 children in the United States. We previously described ASD-specific maternal autoantibodies that recognize fetal brain antigens. Herein, we demonstrate that lactate dehydrogenase A and B (LDH), cypin, stress-induced phosphoprotein 1 (STIP1), collapsin response mediator proteins 1 and 2 (CRMP1, CRMP2) and Y-box-binding protein to comprise the seven primary antigens of maternal autoantibody-related (MAR) autism. Exclusive reactivity to specific antigen combinations was noted in 23% of mothers of ASD children and only 1% of controls. ASD children from mothers with specific reactivity to LDH, STIP1 and CRMP1 and/or cypin (7% vs 0% in controls; P<0.0002; odds ratios of 24.2 (95% confidence interval: 1.45-405)) had elevated stereotypical behaviors compared with ASD children from mothers lacking these antibodies. We describe the first panel of clinically significant biomarkers with over 99% specificity for autism risk thereby advancing our understanding of the etiologic mechanisms and therapeutic possibilities for MAR autism.
Tumor microenvironment plays very important roles in the carcinogenesis. A variety of stromal cells in the microenvironment have been modified to support the unique needs of the malignant state. This study was to discover stromal differentially expressed proteins (DEPs) that were involved in colon carcinoma carcinogenesis. Laser capture microdissection (LCM) was captured and isolated the stromal cells from colon adenocarcinoma (CAC) and non-neoplastic colon mucosa (NNCM) tissues, respectively. Seventy DEPs were identified between the pooled LCM-enriched CAC and NNCM stroma samples by iTRAQ-based quantitative proteomics. Gene Ontology (GO) relationship analysis revealed that DEPs were hierarchically grouped into 10 clusters, and were involved in multiple biological functions that were altered during carcinogenesis, including extracellular matrix organization, cytoskeleton, transport, metabolism, inflammatory response, protein polymerization, and cell motility. Pathway network analysis revealed 6 networks and 56 network eligible proteins with Ingenuity pathway analysis. Four significant networks functioned in digestive system development and its function, inflammatory disease, and developmental disorder. Eight DEPs (DCN, FN1, PKM2, HSP90B1, S100A9, MYH9, TUBB, and YWHAZ) were validated by Western blotting, and four DEPs (DCN, FN1, PKM2, and HSP90B1) were validated by immunohistochemical analysis. It is the first report of stromal DEPs between CAC and NNCM tissues. It will be helpful to recognize the roles of stromas in the colon carcinoma microenvironment, and improve the understanding of carcinogenesis in colon carcinoma. The present data suggest that DCN, FN1, PKM2, HSP90B1, S100A9, MYH9, TUBB, and YWHAZ might be the potential targets for colon cancer prevention and therapy.
Background:
Autism spectrum disorders (ASDs) are characterized by deficits in social communication and language and the presence of repetitive behaviors that affect as many as 1 in 50 US children. Perinatal stress and environmental factors appear to play a significant role in increasing the risk for ASDs. There is no definitive pathogenesis, which therefore significantly hinders the development of a cure.
Objective:
We aimed to identify publications using basic or clinical data that suggest a possible association between atopic symptoms and ASDs, as well as evidence of how such an association could lead to brain disease, that may explain the pathogenesis of ASD.
Methods:
PubMed was searched for articles published since 1995 that reported any association between autism and/or ASDs and any one of the following terms: allergy, atopy, brain, corticotropin-releasing hormone, cytokines, eczema, food allergy, food intolerance, gene mutation, inflammation, mast cells, mitochondria, neurotensin, phenotype, stress, subtype, or treatment.
Results:
Children with ASD respond disproportionally to stress and also present with food and skin allergies that involve mast cells. Brain mast cells are found primarily in the hypothalamus, which participates in the regulation of behavior and language. Corticotropin-releasing hormone is secreted from the hypothalamus under stress and, together with neurotensin, stimulates brain mast cells that could result in focal brain allergy and neurotoxicity. Neurotensin is significantly increased in serum of children with ASD and stimulates mast cell secretion of mitochondrial adenosine triphosphate and DNA, which is increased in these children; these mitochondrial components are misconstrued as innate pathogens, triggering an autoallergic response in the brain. Gene mutations associated with higher risk of ASD have been linked to reduction of the phosphatase and tensin homolog, which inhibits the mammalian target of rapamycin (mTOR). These same mutations also lead to mast cell activation and proliferation. Corticotropin-releasing hormone, neurotensin, and environmental toxins could further trigger the already activated mTOR, leading to superstimulation of brain mast cells in those areas responsible for ASD symptoms. Preliminary evidence indicates that the flavonoid luteolin is a stronger inhibitor of mTOR than rapamycin and is a potent mast cell blocker.
Conclusion:
Activation of brain mast cells by allergic, environmental, immune, neurohormonal, stress, and toxic triggers, especially in those areas associated with behavior and language, lead to focal brain allergies and subsequent focal encephalitis. This possibility is more likely in the subgroup of patients with ASD susceptibility genes that also involve mast cell activation.
Autism spectrum disorders (ASDs) are increasing in incidence but have an incompletely understood etiology. Tools for uncovering clues to the cause of ASDs and means for diagnoses are valuable to the field. Mass Spectrometry (MS) has been a useful method for evaluating differences between individuals with ASDs versus matched controls. Different biological substances can be evaluated using MS, including urine, blood, saliva, and hair. This technique has been used to evaluate relatively unsupported hypotheses based on introduction of exogenous factors, such as opiate and heavy metal excretion theories of ASDs. MS has also been used to support disturbances in serotonin-related molecules, which have been more consistently observed in ASDs. Serotonergic system markers, markers for oxidative stress, cholesterol system disturbances, peptide hypo-phosphorylation and methylation have been measured using MS in ASDs, although further analyses with larger numbers of subjects are needed (as well as consideration of behavioral data). Refinements in MS and data analysis are ongoing, allowing for the possibility that future studies examining body fluids and specimens from ASD subjects could continue to yield novel insights. This review summarizes MS investigations that have been conducted to study ASD to date and provides insight into future promising applications for this technique, with focus on proteomic studies.
Unlabelled:
In this study, we evaluated the reproducibility of abundant urine protein depletion by hexapeptide-based library beads and an antibody-based affinity column using the iTRAQ technique. The antibody-based affinity-depletion approach, which proved superior, was then applied in conjunction with iTRAQ to discover proteins that were differentially expressed between pooled urine samples from hernia and bladder cancer patients. Several proteins, including seven apolipoproteins, TIM, SAA4, and proEGF were further verified in 111 to 203 individual urine samples from patients with hernia, bladder cancer, or kidney cancer. Six apolipoproteins (APOA1, APOA2, APOB, APOC2, APOC3, and APOE) were able to differentiate bladder cancer from hernia. SAA4 was significantly increased in bladder cancer subgroups, whereas ProEGF was significantly decreased in bladder cancer subgroups. Additionally, the combination of SAA4 and ProEGF exhibited higher diagnostic capacity (AUC=0.80 and p<0.001) in discriminating bladder cancer from hernia than either marker alone. Using MetaCore software to interpret global changes of the urine proteome caused by bladder cancer, we found that the most notable alterations were in immune-response/alternative complement and blood-coagulation pathways. This study confirmed the clinical significance of the urine proteome in the development of non-invasive biomarkers for the detection of bladder cancer.
Biological significance:
In this study, we evaluated the reproducibility of abundant urine protein depletion by hexapeptide-based library beads and an antibody-based affinity column using the iTRAQ technique. The antibody-based affinity-depletion approach, which proved superior, was then applied in conjunction with iTRAQ to discover proteins that were differentially expressed between pooled urine samples from hernia and bladder cancer patients. Several proteins, including seven apolipoproteins, TIM, SAA4, and proEGF were further verified in 111 to 203 individual urine samples from patients with hernia, bladder cancer, or kidney cancer. SAA4 was significantly increased in bladder cancer subgroups, whereas ProEGF was significantly decreased in bladder cancer subgroups. Additionally, the combination of SAA4 and ProEGF exhibited higher diagnostic capacity in discriminating bladder cancer from hernia than either marker alone. A marker panel composed by two novel biomarker candidates, SAA4 and proEGF, was first discovered and verified successfully using Western blotting. To the best of our knowledge, the associations of urinary SAA4 and proEGF with bladder tumor and kidney cancer have not been mentioned before. In the present study, we discovered and verified SAA4 and proEGF as potential bladder cancer biomarker for the first time.
Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone
towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable
progress has been made—particularly for certain model organisms and functional systems. Currently, protein interactions and
associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized
pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality
data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored
and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version
9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information,
to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one
model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed
in their networks.
Tumor differentiation factor (TDF) is an under-investigated protein produced by the pituitary with no definitive function. TDF is secreted into the bloodstream and targets the breast and prostate, suggesting that it has an endocrine function. Initially, TDF was indirectly discovered based on the differentiation effect of alkaline pituitary extracts of the mammosomatotropic tumor MtTWlO on MTW9/PI rat mammary tumor cells. Years later, the cDNA clone responsible for this differentiation activity was isolated from a human pituitary cDNA library using expression cloning. The cDNA encoded a 108-amino-acid polypeptide that had differentiation activity on MCF7 breast cancer cells and on DU145 prostate cancer cells in vitro and in vivo. Recently, our group focused on identification of the TDF receptor (TDF-R). As potential TDF-R candidates, we identified the members of the Heat Shock 70-kDa family of proteins (HSP70) in both MCF7 and BT-549 human breast cancer cells (HBCC) and PC3, DU145, and LNCaP human prostate cancer cells (HPCC), but not in HeLa cells, NG108 neuroblastoma, or HDF-a and BLK CL.4 cells fibroblasts or fibroblast-like cells. Here we review the current advances on TDF, with particular focus on the structural investigation of its receptor and on its functional effects on breast and prostate cells.
Autism spectrum disorders (ASDs) are neurodevelopmental and behavioural syndromes affecting social orientation, behaviour, and communication that can be classified as developmental disorders. ASD is also associated with immune system abnormality. Immune system abnormalities may be caused partly by complement system factor I deficiency. Complement factor I is a serine protease present in human plasma that is involved in the degradation of complement protein C3b, which is a major opsonin of the complement system. Deficiency in factor I activity is associated with an increased incidence of infections in humans. In this paper, we show that the mean level of factor I activity in the ASD group is significantly higher than in the control group of typically developed and healthy children, suggesting that high activity of complement factor I might have an impact on the development of ASD.
The secretome represents the set of proteins secreted into the extracellular space of cells. These proteins have been shown to play a major role in cell-cell communication. For example, recent observations revealed the presence of diffusible factors with proliferative properties in the secretome of cancer cells. Thus, a qualitative and quantitative analysis of the secretome could lead to the identification of these factors and consequently to the development of new therapeutic strategies. Here, we provide an automated simple and effective strategy to identify novel targets in the secretome of specifically treated cells using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Furthermore, we explore the supportive role of mass spectrometry (MS) in the development of functional assays of identified secreted target molecules. Simplicity is achieved by growing cells in medium free of serum, which eliminates the need to remove the most abundant serum proteins and at the same time reduces disturbing matrix effects. Upon identification of these factors, their validation and characterization will follow. Moreover, this approach can also lead to the identification of proteins abnormally secreted, shed, or oversecreted by cells as response to a stimulus. Furthermore, we also discuss the problems that one may encounter. Finally, we discuss the broad application of automated MS-based proteomics, particularly in cancer research, highlighting new horizons for the use of MS.
Autism spectrum disorders (ASD) are classified as neurological developmental disorders. Several studies have been carried out to find a candidate biomarker linked to the development of these disorders, but up to date no reliable biomarker is available. Mass spectrometry techniques have been used for protein profiling of blood plasma of children with such disorders in order to identify proteins/peptides that may be used as biomarkers for detection of the disorders. Three differentially expressed peptides with mass-charge (m/z) values of 2020 ± 1, 1864 ± 1 and 1978 ± 1 Da in the heparin plasma of children with ASD that were significantly changed as compared with the peptide pattern of the non-ASD control group are reported here. This novel set of biomarkers allows for a reliable blood-based diagnostic tool that may be used in diagnosis and potentially, in prognosis of ASD.
It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes--so-called sporadic or simplex families--we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 677 individual exomes from 209 families. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected β-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.
