Andreas WindemuthCyclica, Inc.
Skills and Expertise
- Cambridge, Massachusetts, United States
- SVP & Chief Scientist
Jan 2011 - Feb 2015
Firefly BioWorks Inc.
- Cambridge, United States
- Chief Information Officer
Research Items (80)
Abstract Vascular endothelial growth factor A (VEGFA) dysfunction may contribute to a number of pathological processes that characterize psychotic disorders. However, the influence of VEGFA gene variants on clinical and neuroimaging phenotypes in psychotic disorders has yet to be shown. In the present study, we examined whether different VEGFA gene variants influence psychosis risk, symptom severity, cognition, and brain volume. The study group included 480 probands (Bipolar I disorder with psychosis, n = 205; Schizoaffective disorder, n = 112; Schizophrenia, n = 163) and 126 healthy controls that were recruited across six sites in the B-SNIP consortium. VEGFA variants identified for analysis (rs699947, rs833070, and rs2146323) were quantified via SNP chip array. We assessed symptoms and cognition using standardized clinical and neuropsychological batteries. The dorsolateral prefrontal cortex (DLPFC), medial temporal lobe, and hippocampal volumes were quantified using FreeSurfer. In our sample, VEGFA rs2146323 A- carriers showed reduced odds of being a proband (p = 0.037, OR = 0.65, 95% CI = 0.43–0.98) compared to noncarriers, but not for rs699947 or rs833070. In probands, rs2146323 A- carriers demonstrated fewer hallucinations (p = 0.035, Cohen’s d = 0.194), as well as significantly greater DLPFC (p
- Aug 2018
Obverse Cover: The cover image, by Steven V. Molinski et al., is based on the Research Article Comprehensive mapping of cystic fibrosis mutations to CFTR protein identifies mutation clusters and molecular docking predicts corrector binding site, DOI: 10.1002/prot.25496.
- Mar 2018
Cystic Fibrosis (CF) is caused by mutations in the CFTR gene, of which over 2000 have been reported to date. Mutations have yet to be analyzed in aggregate to assess their distribution across the tertiary structure of the CFTR protein, an approach that could provide valuable insights into the structure‐function relationship of CFTR. In addition, the binding site of Class I correctors (VX‐809, VX‐661, C18) is not well understood. In this study, exonic CFTR mutations and mutant allele frequencies described in three curated databases (ABCMdb, CFTR1 and CFTR2, comprising >130,000 data points) were mapped to two different structural models: a homology model of full‐length CFTR protein in the open‐channel state, and a cryo‐electron microscopy core‐structure of CFTR in the closed‐channel state. Accordingly, residue positions of six high‐frequency mutant CFTR alleles were found to spatially co‐localize in CFTR protein, and a significant cluster was identified at the NBD1:ICL4 interdomain interface. In addition, immunoblotting confirmed the approximate binding site of Class I correctors, demonstrating that these small molecules act via a similar mechanism in vitro, and in silico molecular docking generated binding poses for their complex with the cryo‐electron microscopy structure to suggest the putative corrector binding site is a multi‐domain pocket near residues F374‐L375. These results confirm the significance of interdomain interfaces as susceptible to disruptive mutation, and identify a putative corrector binding site. The structural pharmacogenomics approach of mapping mutation databases to protein models shows promise for facilitating drug discovery and personalized medicine for monogenetic diseases. This article is protected by copyright. All rights reserved.
Structure-based computational drug discovery efforts have traditionally focused on the structure of a single, well-known drug target. Important applications, such as target deconvolution and the analysis of polypharmacology, require proteome-scale molecular docking and have been inaccessible to structure-based in silico approaches. One important reason for this inaccessibility was that the structure of most proteins was not known. Lately, this 'structure gap' has been closing rapidly, and proteome-scale molecular docking seems within reach. Here, we survey the current state of structural coverage of the human genome and find that coverage is truly proteome-wide, both overall and in most pharmaceutically relevant categories of proteins. The time is right for structure-based approaches to target deconvolution and polypharmacology.
- Dec 2016
The investigational compound BIA 10-2474, designed as a long-acting and reversible inhibitor of fatty acid amide hydrolase for the treatment of neuropathic pain, led to the death of one participant and hospitalization of five others due to intracranial hemorrhage in a Phase I clinical trial. Putative off-target activities of BIA 10-2474 have been suggested to be major contributing factors to the observed neurotoxicity in humans, motivating our study's proteome-wide screening approach to investigate its polypharmacology. Accordingly, we performed an in silico screen against 80,923 protein structures reported in the Protein Data Bank. The resulting list of 284 unique human interactors was further refined using target-disease association analyses to a subset of proteins previously linked to neurological, intracranial, inflammatory, hemorrhagic or clotting processes and/or diseases. Eleven proteins were identified as potential targets of BIA 10-2474, and the two highest-scoring proteins, Factor VII and thrombin, both essential blood-clotting factors, were predicted to be inhibited by BIA 10-2474 and suggest a plausible mechanism of toxicity. Once this small molecule becomes commercially available, future studies will be conducted to evaluate the predicted inhibitory effect of BIA 10-2474 on blood clot formation specifically in the brain.
- Oct 2016
Background: Schizophrenia, schizoaffective disorder, and psychotic bipolar disorder overlap with regard to symptoms, structural and functional brain abnormalities, and genetic risk factors. Neurobiological pathways connecting genes to clinical phenotypes across the spectrum from schizophrenia to psychotic bipolar disorder remain largely unknown. Methods: We examined the relationship between structural brain changes and risk alleles across the psychosis spectrum in the multi-site Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) cohort. Regional MRI brain volumes were examined in 389 subjects with a psychotic disorder (139 schizophrenia, 90 schizoaffective disorder, and 160 psychotic bipolar disorder) and 123 healthy controls. 451,701 single-nucleotide polymorphisms were screened and processed using parallel independent component analysis (para-ICA) to assess associations between genes and structural brain abnormalities in probands. Results: 482 subjects were included after quality control (364 individuals with psychotic disorder and 118 healthy controls). Para-ICA identified four genetic components including several risk genes already known to contribute to schizophrenia and bipolar disorder and revealed three structural components that showed overlapping relationships with the disease risk genes across the three psychotic disorders. Functional ontologies representing these gene clusters included physiological pathways involved in brain development, synaptic transmission, and ion channel activity. Conclusions: Heritable brain structural findings such as reduced cortical thickness and surface area in probands across the psychosis spectrum were associated with somewhat distinct genes related to putative disease pathways implicated in psychotic disorders. This suggests that brain structural alterations might represent discrete psychosis intermediate phenotypes along common neurobiological pathways underlying disease expression across the psychosis spectrum.
- Jul 2016
To address the needs for circulating miRNA biomarker validation, we developed the Multiplexed Circulating microRNA assay. This assay enables the detection of up to 68 microRNA targets per sample in 96-well format with readout on standard flow cytometers and analysis with an included bioinformatics software package. The Circulating microRNA assay combines particle-based multiplexing, using patented Firefly hydrogel particles, with single-step RT-PCR signal amplification using universal primers. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are displayed and interpreted using our included Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data with only a few mouse clicks. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. These carefully curated panels include hemolysis markers to assess sample quality, as well as critical normalization factors. Here we present the data from several studies investigating circulating and tumor microRNA profiles using the Firefly Circulating microRNA Assay Fixed Panels. Together, this novel combination of bioinformatics tools and multiplexed, high-sensitivity assays enables rapid discovery and validation of microRNA biomarker signatures from fluid specimens. Citation Format: Jessica Tytell, Issac Stoner, Michael Tackett, Graeme Doran, Conor Rafferty, Andreas Windemuth, Daniel Pregibon. High-throughput,purification-free, multiplexed profiling of circulating miRNA for discovery,validation, and diagnostics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1082.
- Jun 2016
Statin responsiveness is an area of great research interest given the success of the drug class in the treatment of hypercholesterolemia and in primary and secondary prevention of cardiovascular disease. Interrogation of the patient's genome for gene variants will eventually guide anti-hyperlipidemic intervention. In this review, we discuss methodological approaches to discover genetic markers predictive of class-wide and drug-specific statin efficacy and safety. Notable pharmacogenetic findings are summarized from hypothesis-free genome wide and hypothesis-led candidate gene association studies. Physiogenomic models and clinical decision support systems will be required for DNA-guided statin therapy to reach practical use in medicine.
A revolution in our understanding of human health and disease has been launched by the sequencing of a prototypical human genome. To a large degree, this achievement represents the pinnacle of reductionist scientific thought, as having all genes dissected, one could in principle allow reconstitution of the organism. In contrast, the classical discipline of physiology has been dealing with systems from its very outset. Although clinically extraordinarily relevant, physiology remained an engineering embodiment of scientific thought distant from the molecular basis of function. Physiogenomics bridges the gap between the systems approach and the reductionist approach by using human variability in physiological process, either in health or disease, to drive their understanding at the genome level. Physiogenomics is particularly relevant to the phenotypes of complex diseases and the clustering of phenotypes into domains according to measurement technique, ranging from functional imaging and clinical scales to protein serology and gene expression.
- Mar 2016
To address the needs for circulating miRNA biomarker validation, we developed the Multiplexed Circulating microRNA assay. This assay enables the detection of up to 68 microRNA targets per sample in 96-well format with readout on standard flow cytometers and analysis with an included bioinformatics software package. The Circulating microRNA assay combines particle¬-based multiplexing, using patented Firefly hydrogel particles, with single¬ step RT-PCR signal amplification using universal primers. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target¬-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are displayed and interpreted using our included Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data with only a few mouse clicks. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. These carefully curated panels include hemolysis markers to assess sample quality, as well as critical normalization factors. Here we present the data from several studies investigating circulating and tumor microRNA profiles using the Firefly Circulating microRNA Assay Fixed Panels. Together, this novel combination of bioinformatics tools and multiplexed, high¬-sensitivity assays enables rapid discovery and validation of microRNA biomarker signatures from fluid specimens. Citation Format: Isaac Stoner, Michael Tackett, Conor Rafferty, Andreas Windemuth, Elnaz Atabakhsh, Jessica Tytell, Daniel Pregibon. High-throughput, purification-free, multiplexed profiling of circulating miRNA for discovery, validation, and diagnostics. [abstract]. In: Proceedings of the AACR Special Conference on Noncoding RNAs and Cancer: Mechanisms to Medicines ; 2015 Dec 4-7; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2016;76(6 Suppl):Abstract nr B30.
Objective: The complex molecular etiology of psychosis in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is not well defined, presumably due to their multifactorial genetic architecture. Neurobiological correlates of psychosis can be identified through genetic associations of intermediate phenotypes such as event-related potential (ERP) from auditory paired stimulus processing (APSP). Various ERP components of APSP are heritable and aberrant in SZ, PBP and their relatives, but their multivariate genetic factors are less explored. Methods: We investigated the multivariate polygenic association of ERP from 64-sensor auditory paired stimulus data in 149 SZ, 209 PBP probands, and 99 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Multivariate association of 64-channel APSP waveforms with a subset of 16 999 single nucleotide polymorphisms (SNPs) (reduced from 1 million SNP array) was examined using parallel independent component analysis (Para-ICA). Biological pathways associated with the genes were assessed using enrichment-based analysis tools. Results: Para-ICA identified 2 ERP components, of which one was significantly correlated with a genetic network comprising multiple linearly coupled gene variants that explained ~4% of the ERP phenotype variance. Enrichment analysis revealed epidermal growth factor, endocannabinoid signaling, glutamatergic synapse and maltohexaose transport associated with P2 component of the N1-P2 ERP waveform. This ERP component also showed deficits in SZ and PBP. Conclusions: Aberrant P2 component in psychosis was associated with gene networks regulating several fundamental biologic functions, either general or specific to nervous system development. The pathways and processes underlying the gene clusters play a crucial role in brain function, plausibly implicated in psychosis.
Schizophrenia (SZ) and psychotic bipolar disorder (PBP) are disabling psychiatric illnesses with complex and unclear etiologies. Electroencephalogram (EEG) oscillatory abnormalities in SZ and PBP probands are heritable and expressed in their relatives, but the neurobiology and genetic factors mediating these abnormalities in the psychosis dimension of either disorder are less explored. We examined the polygenic architecture of eyes-open resting state EEG frequency activity (intrinsic frequency) from 64 channels in 105 SZ, 145 PBP probands and 56 healthy controls (HCs) from the multisite BSNIP (Bipolar-Schizophrenia Network on Intermediate Phenotypes) study. One million single-nucleotide polymorphisms (SNPs) were derived from DNA. We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10 422 SNPs through novel multivariate association using parallel ICA (para-ICA). Genes contributing to the association were examined collectively using pathway analysis tools. Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis. Delta and theta abnormality was present in both SZ and PBP, while theta differed between the two disorders. Theta abnormalities were also mediated by gene clusters involved in glutamic acid pathways, cadherin and synaptic contact-based cell adhesion processes. Our data suggest plausible multifactorial genetic networks, including novel and several previously identified (DISC1) candidate risk genes, mediating low frequency delta and theta abnormalities in psychoses. The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development.
Objective: Biological risk factors underlying psychosis are poorly understood. Biological underpinnings of the dimension of psychosis can be derived using genetic associations with intermediate phenotypes such as subcomponents of auditory event-related potentials (ERPs). Various ERP subcomponent abnormalities in schizophrenia and psychotic bipolar disorder are heritable and are expressed in unaffected relatives, although studies investigating genetic contributions to ERP abnormalities are limited. The authors used a novel parallel independent component analysis (para-ICA) to determine which empirically derived gene clusters are associated with data-driven ERP subcomponents, assuming a complex etiology underlying psychosis. Method: The authors examined the multivariate polygenic association of ERP subcomponents from 64-channel auditory oddball data in 144 individuals with schizophrenia, 210 psychotic bipolar disorder probands, and 95 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Data were reduced by principal components analysis to two target and one standard ERP waveforms. Multivariate association of compressed ERP waveforms with a set of 20,329 single-nucleotide polymorphisms (SNPs) (reduced from a 1-million-SNP array) was examined using para-ICA. Genes associated with SNPs were further examined using pathway analysis tools. Results: Para-ICA identified four ERP components that were significantly correlated with three genetic components. Enrichment analysis revealed complement immune response pathway and multiple processes that significantly mediate ERP abnormalities in psychosis, including synaptic cell adhesion, axon guidance, and neurogenesis. Conclusions: This study identified three genetic components comprising multiple genes mediating ERP subcomponent abnormalities in schizophrenia and psychotic bipolar disorder. The data suggest a possible polygenic structure comprising genes influencing key neurodevelopmental processes, neural circuitry, and brain function mediating biological pathways plausibly associated with psychosis.
The brain's default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging-genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases.
Question - Are haplotypes or tag SNPs better for association studies?
Many genetic associations will be caused by mutations that are too rare to be listed as SNPs. These are likley to be more recent in origin than the SNPs, and therefore will be found only on a single haplotype. Only a SNP that is synonymous with that particular haplotype will be a good indicator of such associations. Often, such SNPs don't exist, meaning you will be better off with a haplotype approach, as the others have said.
Question - Permutation-based statistical tests for multiple hypotheses, one-tailed test vs two-tailed test?
You use the one-sided test if your hypothesis is one-sided, i.e. if the positive association would not make sense in your model. It sounds like you are looking for any associations, positive or negative, which would call for the two-sided test.
It is not good practice to pick your hypothesis based on the data, so picking a one-sided test because of an observed lack of positive associations is not well motivated. Doing the statistics in multiple different ways and then going with the method producing the most attractive results is similarly problematic, Technically, it incurs an additional multiple testing burden, counteracting any advantage you might hope to gain.
A good rule of thumb: If you find yourself tinkering with your statistical method to obtain significant results, whatever you have is tentative at best.
Question - How to validate the function of deep intronic SNPs?
One easy first step to consider is to see if the SNP falls into a conserved region. If it does, that immediately gives some validation to the finding, which is important because GWAS findings have a tendency to be false positives. The UCSC genome browser, I think, has easily accessed and well developed conservation scores.
Another thing to do would be to blast the vicinity of the SNP against the entire genome, to see if any known regions have matches. Perhaps you have discovered a new target for small RNA hybridization (microRNA and its cousins).
- Sep 2011
To illustrate the utility of CYP450 genotyping to guide clinical psychopharmacological treatment decisions and minimize or avoid harmful and costly adverse drug reactions (ADRs). DNA was extracted from a whole blood sample from the case study subject and tested for CYP450 gene polymorphisms in the CLIA certified Laboratory of Personalized Health at Genomas, Inc. Clinical data were obtained from patient records and clinician observations. We present a case in which the ascertainment of multiple CYP450 isoenzyme deficiencies resulted in a dramatic change in psychotropic treatment approach. Shortly after making these adjustments, the patient saw a significant improvement in most of her debilitating psychiatric symptoms. In complex cases, CYP450 DNA testing can guide pharmacotherapy by exposing innate hepatic metabolic deficiencies as a result of DNA polymorphism. In such cases, clinicians can favor treatments that target functional isoenzyme pathways rather than deficient or null pathways thus leading to decreased risk of ADRs and improved patient response.
- Aug 2011
The purpose of this study was to identify genetic variants predictive of cardiovascular risk factors in a psychiatric population treated with second generation antipsychotics (SGA). 924 patients undergoing treatment for severe mental illness at four US hospitals were genotyped at 1.2 million single nucleotide polymorphisms. Patients were assessed for fasting serum lipid (low density lipoprotein cholesterol [LDLc], high density lipoprotein cholesterol [HDLc], and triglycerides) and obesity phenotypes (body mass index, BMI). Thirteen candidate genes from previous studies of the same phenotypes in non-psychiatric populations were tested for association. We confirmed 8 of the 13 candidate genes at the 95% confidence level. An increased genetic effect size was observed for triglycerides in the psychiatric population compared to that in the cardiovascular population.
We aim to demonstrate clinical relevance and utility of four novel drug-metabolism indices derived from a combinatory (multigene) approach to CYP2C9, CYP2C19 and CYP2D6 allele scoring. Each index considers all three genes as complementary components of a liver enzyme drug metabolism system and uniquely benchmarks innate hepatic drug metabolism reserve or alteration through CYP450 combinatory genotype scores. A total of 1199 psychiatric referrals were genotyped for polymorphisms in the CYP2C9, CYP2C19 and CYP2D6 gene loci and were scored on each of the four indices. The data were used to create distributions and rankings of innate drug metabolism capacity to which individuals can be compared. Drug-specific indices are a combination of the drug metabolism indices with substrate-specific coefficients. The combinatory drug metabolism indices proved useful in positioning individuals relative to a population with regard to innate drug metabolism capacity prior to pharmacotherapy. Drug-specific indices generate pharmacogenetic guidance of immediate clinical relevance, and can be further modified to incorporate covariates in particular clinical cases. We believe that this combinatory approach represents an improvement over the current gene-by-gene reporting by providing greater scope while still allowing for the resolution of a single-gene index when needed. This method will result in novel clinical and research applications, facilitating the translation from pharmacogenomics to personalized medicine, particularly in psychiatry where many drugs are metabolized or activated by multiple CYP450 isoenzymes.
To investigate associations between novel human cytochrome P450 (CYP450) combinatory (multigene) and substrate-specific drug metabolism indices, and elements of metabolic syndrome, such as low density lipoprotein cholesterol (LDLc), high density lipoprotein cholesterol (HDLc), triglycerides and BMI, using physiogenomic analysis. CYP2C9, CYP2C19 and CYP2D6 genotypes and clinical data were obtained for 150 consecutive, consenting hospital admissions with a diagnosis of major depressive disorder and who were treated with psychotropic medications. Data analysis compared clinical measures of LDLc, HDLc, triglyceride and BMI with novel combinatory and substrate-specific CYP450 drug metabolism indices. We found that a greater metabolic reserve index score is related to lower LDLc and higher HDLc, and that a greater metabolic alteration index score corresponds with higher LDLc and lower HLDc values. We also discovered that the sertraline drug-specific indices correlated with cholesterol and triglyceride values. Overall, we demonstrated how a multigene approach to CYP450 genotype analysis yields more accurate and significant results than single-gene analyses. Ranking the individual with respect to the population represents a potential tool for assessing risk of dyslipidemia in major depressive disorder patients who are being treated with psychotropics. In addition, the drug-specific indices appear useful for modeling a variable of potential relevance to an individual's risk of drug-related dyslipidemia.
- Jul 2011
We investigated genetic variants predictive of muscular side effects in patients treated with statins. We utilized a physiogenomic approach to prototype a multi-gene panel correlated with statin-induced myalgia. Statin-induced myalgia occurs in ∼10% of lipid clinic outpatients. Its clinical manifestation may depend in part upon gene variation from patient to patient. We genotyped 793 patients (377 with myalgia and 416 without) undergoing statin therapy at four U.S. outpatient clinic sites to evaluate 31 candidate genes from the literature for their association with statin-induced common myalgia. Three previously hypothesized candidate genes were validated: COQ2 (rs4693570) encoding para-hydroxybenzoate-polyprenyltransferase, which participates in the biosynthesis of coenzyme Q10 (p<0.000041); ATP2B1 (rs17381194) which encodes a calcium transporting ATPase involved in calcium homeostasis (p<0.00079); and DMPK (rs672348) which encodes a protein kinase implicated in myotonic dystrophy (p<0.0016). The candidate genes COQ2, ATP2B1, and DMPK, representing pathways involved in myocellular energy transfer, calcium homeostasis, and myotonic dystonia, respectively, were validated as markers for the common myalgia observed in patients receiving statin therapy. The three genes integrated into a physiogenomic predictive system could be relevant to myalgia diagnosis and prognosis in clinical practice.
A case to illustrate the utility of genetic screening in warfarin (Coumadin) management is reported. A 45 year-old woman of Puerto Rican ancestry was admitted to the emergency room twice within one month with chest pain. She was diagnosed with congestive heart failure, which was stabilized both times. At her second release, warfarin therapy was initiated at 5 mg/ day to prevent thrombus formation and was lowered to 3.75 mg/day at day 7 by her primary physician. International Normalized Ratio (INR) test results in the follow-up period at days 1, 7, and 10 of warfarin therapy were 4.5, 6.5, and 7.3, respectively-far in excess of the therapeutic range, despite the lower dosage in effect from day 7 onward. The patient achieved target INR over the next 43 days after downward adjustment of the dose to a dose of 1.5 mg/day by trial and error. DNA-typing specific for the CYP2C9*2,*3,*4,*5,*6 alleles and seven variants in the VKORC1 gene, including the VKORC1-1639 G > A polymorphism, revealed the presence of combinatorial CYP2C9*2/*3 and VKORC1-1639 G/A genotypes in this patient. Entering the patient's demographic and genotype status data into independent algorithms available in the public domain to predict effective warfarin dose yielded predicted doses which ranged from 1.5 to 1.8 mg/day. Notably, the prediction of 1.5 mg/day, which was generated by the online resource www.warfarindosing.org, coincided with the patient's actual effective warfarin dose. We conclude that the rapid rise in INR observed upon the initiation of warfarin therapy and the final effective warfarin dose of 1.5 mg/day, are attributable in some part to the presence of two minor alleles in CYP2C9, which together significantly reduce warfarin metabolism. Warfarin genotyping can therefore inform the clinician of the predicted effective warfarin dose. The results highlight the potential for warfarin genetic testing to improve patient care.
- Oct 2010
Schizophrenia is a complex genetic disorder, with multiple putative risk genes and many reports of reduced cortical gray matter. Identifying the genetic loci contributing to these structural alterations in schizophrenia (and likely also to normal structural gray matter patterns) could aid understanding of schizophrenia's pathophysiology. We used structural parameters as potential intermediate illness markers to investigate genomic factors derived from single nucleotide polymorphism (SNP) arrays. We used research quality structural magnetic resonance imaging (sMRI) scans from European American subjects including 33 healthy control subjects and 18 schizophrenia patients. All subjects were genotyped for 367 SNPs. Linked sMRI and genetic (SNP) components were extracted to reveal relationships between brain structure and SNPs, using parallel independent component analysis, a novel multivariate approach that operates effectively in small sample sizes. We identified an sMRI component that significantly correlated with a genetic component (r = -.536, p < .00005); components also distinguished groups. In the sMRI component, schizophrenia gray matter deficits were in brain regions consistently implicated in previous reports, including frontal and temporal lobes and thalamus (p < .01). These deficits were related to SNPs from 16 genes, several previously associated with schizophrenia risk and/or involved in normal central nervous system development, including AKT, PI3K, SLC6A4, DRD2, CHRM2, and ADORA2A. Despite the small sample size, this novel analysis method identified an sMRI component including brain areas previously reported to be abnormal in schizophrenia and an associated genetic component containing several putative schizophrenia risk genes. Thus, we identified multiple genes potentially underlying specific structural brain abnormalities in schizophrenia.
- Sep 2010
Admixture is of great relevance to the clinical application of pharmacogenetics and personalized medicine, but unfortunately these studies have been scarce in Puerto Ricans. Besides, allele frequencies for clinically relevant genetic markers in warfarin response (i.e., CYP2C9 and VKORC1) have not yet been fully characterized in this population. Accordingly, this study is aimed at investigating whether a correlation between overall genetic similarity and CYP2C9 and/or VKORC1 genotypes could be established. 98 DNA samples from Puerto Ricans were genotyped for major CYP2C9 and VKORC1 polymorphisms and tested on a physiogenomic (PG)-array to infer population structure and admixture pattern. Analysis affirmed that Puerto Ricans are broadly admixed. A genetic distance dendrogram was constructed by clustering those subjects with similar genetic profiles. Individual VKORC1 and CYP2C9 genotypes were visually overlaid atop the three dendrogram sectors. Sector-1, representing Amerindian ancestry, showed higher VKORC1 -1639G>A variant frequency than the rest of the population (p=0.051). Although CYP2C9*3 allele frequencies matched the expected HapMap values, admixture may explain deviations from published findings regarding VKORC1 -1639G>A and CYP2C9*2 allele frequencies in sector-3. Results suggest that the observed inter-individual variations in ancestral contributions have significant implications for the way each Puerto Rican responds to warfarin therapy. Our findings provide valuable evidence on the importance of controlling for admixture in pharmacogenetic studies of Puerto Rican Hispanics.
Administered at maximal dosages, the most common statins--atorvastatin, simvastatin and rosuvastatin--lower low-density lipoprotein cholesterol (LDLC) by an average of 37-57% in patients with primary hypercholesterolemia. We hypothesized novel genetic underpinnings for variation in LDLC levels in the context of statin therapy. Genotyping of 384 SNPs in 202 volunteers from a lipid outpatient clinic was accomplished and LDLC levels obtained from chart records. The SNPs were distributed across 222 genes representing physiological pathways such as general metabolism, cholesterol biochemistry, cardiovascular function, inflammation, neurobiology and cell proliferation. We discovered significant associations with LDLC levels for the rs34274 SNP (p < 0.0002) and for rs2241220 (p < 0.008) in the acetyl-coenzyme A carboxylase beta (ACACB) gene. When corrected for multiple testing, the false-discovery rate associated with rs34274 was 0.076 (significance threshold: 0.10) and for rs2241220 the false-discovery rate was 0.93 (not significant). The acetyl coenzyme A carboxylase beta enzyme synthesizes malonyl coenzyme A, an essential substrate for hepatic fatty acid synthesis and an inhibitor of fatty acid oxidation. The SNPs were in weak linkage disequilibrium (D = 0.302). Minor alleles at these sites demonstrate opposing influences on LDLC; the C>T substitution at rs34724 is a risk marker and the C>T substitution at rs2241220 a protective marker for LDLC levels. These SNPs hypothetically influence enzymatic activity through different mechanisms, rs34274 through the PII promoter and rs2241220 via alteration of the protein's responsiveness to allosteric influence. Physiogenomic evidence suggests a novel link between LDLC levels and the regulation of fatty acid metabolism. The findings complement previously discovered novel SNP relationships to myalgia (pain) and myositis (serum creatine kinase activity). By genotyping for myositis, myalgia and LDLC levels, a physiogenomic model may be developed to help clinicians maximize effectiveness and minimize side effects in prescribing statins.
- Oct 2009
Acetyl-coenzyme A carboxylase alpha (ACACA) single-nucleotide polymorphism (SNP) (rs2229416) was significantly associated with hypertriglyceridemia, during exploration of antipsychotic direct effects on lipids. Neuropeptide Y (NPY) gene (rs1468271) and ACACB gene (rs2241220) SNPs were significantly associated with severe hypercholesterolemia. In the same sample (173 patients on olanzapine, quetiapine, chlorpromazine or mirtazapine [increasing the risk of hyperlipidemia] and 184 controls taking other antipsychotics), three (rs1266175, rs12453407 and rs9906543) of eight additional ACACA SNPs were significantly associated with hypertriglyceridemia in those taking drugs of interest, but not in controls. Five other ACACA SNPs, three additional NPY SNPs, and seven additional ACACB SNPs were not significant.
Polymorphisms in the cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) genes significantly alter the effective warfarin dose. We determined the frequencies of alleles, single carriers, and double carriers of single nucleotide polymorphisms (SNPs) in the CYP2C9 and VKORC1 genes in a Puerto Rican cohort and gauged the impact of these polymorphisms on warfarin dosage using a published algorithm. A total of 92 DNA samples were genotyped using Luminex x-MAP technology. The polymorphism frequencies were 6.52%, 5.43% and 28.8% for CYP2C9 *2, *3 and VKORC1-1639 C>A polymorphisms, respectively. The prevalence of combinatorial genotypes was 16% for carriers of both the CYP2C9 and VKORC1 polymorphisms, 9% for carriers of CYP2C9 polymorphisms, 35% for carriers of the VKORC1 polymorphism, and the remaining 40% were non-carriers for either gene. Based on a published warfarin dosing algorithm, single, double and triple carriers of functionally deficient polymorphisms predict reductions of 1.0-1.6, 2.0-2.9, and 2.9-3.7 mg/day, respectively, in warfarin dose. Overall, 60% of the population carried at least a single polymorphism predicting deficient warfarin metabolism or responsiveness and 13% were double carriers with polymorphisms in both genes studied. Combinatorial genotyping of CYP2C9 and VKORC1 can allow for individualized dosing of warfarin among patients with gene polymorphisms, potentially reducing the risk of stroke or bleeding.
Admixture in the population of the island of Puerto Rico is of general interest with regards to pharmacogenetics to develop comprehensive strategies for personalized healthcare in Latin Americans. This research was aimed at determining the frequencies of SNPs in key physiological, pharmacological and biochemical genes to infer population structure and ancestry in the Puerto Rican population. A noninterventional, cross-sectional, retrospective study design was implemented following a controlled, stratified-by-region, random sampling protocol. The sample was based on birthrates in each region of the island of Puerto Rico, according to the 2004 National Birth Registry. Genomic DNA samples from 100 newborns were obtained from the Puerto Rico Newborn Screening Program in dried-blood spot cards. Genotyping using a physiogenomic array was performed for 332 SNPs from 196 cardiometabolic and neuroendocrine genes. Population structure was examined using a Bayesian clustering approach as well as by allelic dissimilarity as a measure of allele sharing. The Puerto Rican sample was found to be broadly heterogeneous. We observed three main clusters in the population, which we hypothesize to reflect the historical admixture in the Puerto Rican population from Amerindian, African and European ancestors. We present evidence for this interpretation by comparing allele frequencies for the three clusters with those for the same SNPs available from the International HapMap project for Asian, African and European populations. Our results demonstrate that population analysis can be performed with a physiogenomic array of cardiometabolic and neuroendocrine genes to facilitate the translation of genome diversity into personalized medicine.
There is current interest in understanding genetic influences on both healthy and disordered brain function. We assessed brain function with functional magnetic resonance imaging (fMRI) data collected during an auditory oddball task--detecting an infrequent sound within a series of frequent sounds. Then, task-related imaging findings were utilized as potential intermediate phenotypes (endophenotypes) to investigate genomic factors derived from a single nucleotide polymorphism (SNP) array. Our target is the linkage of these genomic factors to normal/abnormal brain functionality. We explored parallel independent component analysis (paraICA) as a new method for analyzing multimodal data. The method was aimed to identify simultaneously independent components of each modality and the relationships between them. When 43 healthy controls and 20 schizophrenia patients, all Caucasian, were studied, we found a correlation of 0.38 between one fMRI component and one SNP component. This fMRI component consisted mainly of parietal lobe activations. The relevant SNP component was contributed to significantly by 10 SNPs located in genes, including those coding for the nicotinic alpha-7 cholinergic receptor, aromatic amino acid decarboxylase, disrupted in schizophrenia 1, among others. Both fMRI and SNP components showed significant differences in loading parameters between the schizophrenia and control groups (P = 0.0006 for the fMRI component; P = 0.001 for the SNP component). In summary, we constructed a framework to identify interactions between brain functional and genetic information; our findings provide a proof-of-concept that genomic SNP factors can be investigated by using endophenotypic imaging findings in a multivariate format.
Objective: This study compared the types and carrier prevalences of clinically significant DNA polymorphisms in the cytochrome P450 (CYP450) genes CYP2C9, CYP2C19 and CYP2D6 in major depressive disorder patients with a control group of nonpsychiatrically ill, medical outpatients. Method: We conducted a case-control study using 73 psychiatric outpatients diagnosed with depression and referred to a tertiary center, The Institute of Living (Hartford, CT, USA), for treatment resistance or intolerable side-effects to psychotropic drugs. The controls were 120 cardiovascular patients from Hartford Hospital being treated for dyslipidemia but otherwise healthy and not psychiatrically ill. DNA typing to detect polymorphisms in the genes CYP2C9, CYP2C19 and CYP2D6 was accomplished with the Tag-It™ mutation detection assay and the Luminex xMAP® system. Results: The percentage of individuals in psychiatric versus control groups with two wild-type alleles for CYP2C9, CYP2C19 and CYP2D6 genes, were 50 versus 74% (p < 0.001), 71 versus 73% (not statistically significant) and 36 versus 43% (trend, p < 0.2), respectively. Within the psychiatric population, 57% of individuals were carriers of non-wild-type alleles for 2-3 genes, compared with 36% in the control population (p < 0.0001). The balance, 43% in the psychiatric population and 64% in the control, were carriers of non-wild-type alleles for none or one gene. Conclusions: These findings reveal that clinically relevant CYP2C9 polymorphisms occur more frequently in depressed psychiatric patients than in nonpsychiatric controls. The same trend was found for polymorphisms in the CYP2D6 gene. We found a significant cumulative metabolic deficiency in the psychiatric population for combinations of the CYP2C9, CYP2C19 and CYP2D6 genes. The significant enrichment of CYP2C9-deficient alleles in the psychiatric population validates a previously reported association of this gene with the risk for depression disorders. The high prevalence of carriers with deficient and null alleles suggests that CYP450 DNA typing may play a role in the management of psychiatric patients at tertiary care institutions.
- Oct 2008
The thiazolidinediones (TZDs) improve tissue sensitivity to insulin in patients with type II diabetes, resulting in reduced levels of fasting blood glucose and glycated hemoglobin. However, TZDs unpredictably demonstrate adverse effects of increased body weight, fluid retention, and edema. The balance of efficacy and safety of TZD varies widely from patient to patient. Genetic variability may reveal pathophysiological pathways underlying weight gain associated with TZD therapy and due to adiposity and/or edema. We analyzed 384 single nucleotide polymorphisms (SNPs) from 222 cardiovascular and metabolic genes in 87 outpatients with type 2 diabetes receiving thiazolidinedione therapy. Physiogenomic analysis was used to discover associations with body mass index (BMI) and edema. The 5 most significant gene associations found between BMI and SNPs were ADORA1, adenosine A1 receptor (rs903361, p<0.0003), PKM2, pyruvate kinase-muscle (rs2856929, p<0.002); ADIPOR2, adiponectin receptor 2 (rs7975375, p<0.007); UCP2, uncoupling protein 2 (rs660339, p<0.008); and APOH, apolipoprotein H (rs8178847, p<0.010). For edema, the 5 most significant gene associations were NPY, neuropeptide Y (rs1468271, p<0.006); GYS1, glycogen synthase 1-muscle (rs2287754, p<0.013); CCL2, chemokine C-C motif ligand 2 (rs3760396, p<0.015); OLR1, oxidized LDL receptor 1 (rs2742115, p<0.015); and GHRH, growth hormone releasing hormone (rs6032470, p<0.023). After accounting for multiple comparisons, ADORA1 was significantly associated with BMI at a false discovery rate (FDR) of <10%. Physiogenomic associations were discovered suggesting mechanistic links between adenosine signaling and BMI, and between vascular permeability and drug-induced edema.
Warfarin is a well established oral anticoagulant for the treatment of thromboembolic disorders. Warfarin therapy is complicated by a narrow therapeutic index and marked inter-individual dose variability with therapeutic doses ranging from 1 mg to 10 mg/day. Recently genetic variation and resultant drug metabolizing polymorphisms have been found to contribute to warfarin dose variability with resultant hemorrhagic or thromboembolic complications. Cytochrome P4502C9 alters the rate of warfarin metabolism and clearance. A second enzyme, Vitamin K Epoxide Reductase Complex (VKORC) binds and reduces Vitamin K which is necessary for activation of clotting Factors II, VII, IX and X. The VKORC1 gene encodes for Vitamin K Epoxide Reductase Complex subunit 1, a key component of VKORC. The combination of physiologic factors (30%), CYP2C9 variations (20%) and VKORC1 variants (25%) accounts for approximately 75% of warfarin dose variability. This illustrative case report demonstrates the clinical importance of this new information. Clinicians need to incorporate these new genomic findings into appropriate management of warfarin dose anticoagulation.
The search for genetic factors associated with disease is complicated by the complexity of the biological pathways linking genotype and phenotype. This analytical complexity is particularly concerning in diseases historically lacking reliable diagnostic biological markers, such as schizophrenia and other mental disorders. We investigate the use of functional magnetic resonance imaging (fMRI) as an intermediate phenotype (endophenotype) to identify physiogenomic associations to schizophrenia. We screened 99 subjects, 30 subjects diagnosed with schizophrenia, 13 unaffected relatives of schizophrenia patients, and 56 unrelated controls, for gene polymorphisms associated with fMRI activation patterns at two locations in temporal and frontal lobes previously implied in schizophrenia. A total of 22 single nucleotide polymorphisms (SNPs) in 15 genes from the dopamine and serotonin neurotransmission pathways were genotyped in all subjects. We identified three SNPs in genes that are significantly associated with fMRI activity. SNPs of the dopamine beta-hydroxylase (DBH) gene and of the dopamine receptor D4 (DRD4) were associated with activity in the temporal and frontal lobes, respectively. One SNP of serotonin-3A receptor (HTR3A) was associated with temporal lobe activity. The results of this study support the physiogenomic analysis of neuroimaging data to discover associations between genotype and disease-related phenotypes.
Background: Polymorphisms in the cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) genes significantly alter the effective warfarin dose. The CYP2C9*2 (430C>T), CYP2C9*3 (1075A>C) and VKORC1 -1639 G>A polymorphisms affect warfarin dose through altered metabolism (CYP2C9) and sensitivity (VKORC1). Objective: We determined the frequencies of SNPs in the CYP2C9 and VKORC1 genes in a clinical outpatient population and the carrier prevalences for a variety of genotype combinations to gauge the impact of these polymorphisms on warfarin dosage using published algorithms. Method: A total of 127 patients from an outpatient clinic at Hartford Hospital (Hartford, CT, USA) were genotyped for five SNPs in the CYP2C9 gene and seven SNPs in the VKORC1 gene using Luminex® technology. Results: The polymorphism frequencies were 10.2, 7.9 and 37.4% for the functionally deficient CYP2C9*2, CYP2C9*3 and VKORC1 -1639 G>A polymorphisms, respectively. Combining prevalence of combinatorial genotypes, 18% were carriers of both CYP2C9 and VKORC1 polymorphisms, 13% were CYP2C9 polymorphism carriers only, 42.5% were VKORC1 carriers only, and the remaining 27% were noncarriers for either gene. Based on published warfarin dosing algorithms, carriers of 1, 2, 3 and 4 functionally deficient polymorphisms predict reductions of 1.0 to 1.6, 2.0 to 2.9, 2.9 to 3.7, and 3.6 to 4.4 mg/day, respectively, in warfarin dose. Conclusion: Overall, 73% of the population carried at least one polymorphism predicting deficient warfarin metabolism or responsiveness and 18% were carriers for polymorphisms in both genes studied. Combinatorial genotyping of CYP2C9 and VKORC1 can allow for individualized dosing of warfarin amongst patients with gene polymorphisms potentially reducing the risk of accentuated responses and bleeding.
Genetic factors that predict responses to diet may ultimately be used to individualize dietary recommendations. We used physiogenomics to explore associations among polymorphisms in candidate genes and changes in relative body fat (Delta%BF) to low fat and low carbohydrate diets. We assessed Delta%BF using dual energy X-ray absorptiometry (DXA) in 93 healthy adults who consumed a low carbohydrate diet (carbohydrate ~12% total energy) (LC diet) and in 70, a low fat diet (fat ~25% total energy) (LF diet). Fifty-three single nucleotide polymorphisms (SNPs) selected from 28 candidate genes involved in food intake, energy homeostasis, and adipocyte regulation were ranked according to probability of association with the change in %BF using multiple linear regression. Dieting reduced %BF by 3.0 +/- 2.6% (absolute units) for LC and 1.9 +/- 1.6% for LF (p < 0.01). SNPs in nine genes were significantly associated with Delta%BF, with four significant after correction for multiple statistical testing: rs322695 near the retinoic acid receptor beta (RARB) (p < 0.005), rs2838549 in the hepatic phosphofructokinase (PFKL), and rs3100722 in the histamine N-methyl transferase (HNMT) genes (both p < 0.041) due to LF; and the rs5950584 SNP in the angiotensin receptor Type II (AGTR2) gene due to LC (p < 0.021). Fat loss under LC and LF diet regimes appears to have distinct mechanisms, with PFKL and HNMT and RARB involved in fat restriction; and AGTR2 involved in carbohydrate restriction. These discoveries could provide clues to important physiologic mechanisms underlying the Delta%BF to low carbohydrate and low fat diets.
- Feb 2008
The goal of this study was to select some genes that may serve as good candidates for future studies of the direct effects (not explained by obesity) of some antipsychotics on hyperlipidemia. A search for single-nucleotide polymorphisms (SNPs) that may be associated with these direct effects was conducted. From a published cross-sectional sample, 357 patients on antipsychotics were genotyped using a DNA microarray with 384 SNPs. A total of 165 patients were taking olanzapine, quetiapine or chlorpromazine which may directly cause hypertriglyceridemia or hypercholesterolemia. Another 192 patients taking other antipsychotics were controls. A two-stage statistical analysis that included loglinear and logistic models was developed to select SNPs blindly. In a third stage, physiological knowledge was used to select promising SNPs. Known physiological mechanisms were supported for 3 associations found in patients taking olanzapine, quetiapine or chlorpromazine [acetyl-coenzyme A carboxylase alpha SNP (rs4072032) in the hypertriglyceridemia model, and for the neuropeptide Y (rs1468271) and ACCbeta, (rs2241220) in the hypercholesterolemia model]. These genes may be promising candidates for studies of the direct effects of some antipsychotics on hyperlipidemia.
- Sep 2007
We employed physiogenomic analyses to investigate the relationship between myalgia and selected polymorphisms in serotonergic genes, based on their involvement with pain perception and transduction of nociceptive stimuli. We screened 195 hypercholesterolemic, statin-treated patients, all of whom received either atorvastatin, simvastatin, or pravastatin. Patients were classified as having no myalgia, probable myalgia, or definite myalgia, and assigned a myalgia score of 0, 0.5, or 1, respectively. Fourteen single nucleotide polymorphisms (SNPs) were selected from candidates within the 5-HT receptor gene families [5a-hydroxytryptamine receptor genes (HTR) 1D, 2A, 2C, 3A, 3B, 5A, 6, 7] and the serotonin transporter gene (SLC6A4). SNPs in the HTR3B and HTR7 genes, rs2276307 and rs1935349, respectively, were significantly associated with the myalgia score. Individual differences in pain perception and nociception related to specific serotonergic gene variants may affect the development of myalgia in statin-treated patients.
Atypical antipsychotics induce pre-diabetic symptoms in some but not all patients, characterized most notably by elevated weight. The side effect profiles of the various drugs in the class differ, however, raising the possibility of drug-specific mechanisms for similar side effects. We used physiogenomic analysis, an approach previously employed to study the genetics of drug and diet response, to discover and compare genetic associations with weight profiles observed in patients treated with olanzapine and risperidone as an approach to unraveling contrasting mechanistic features of both drugs. A total of 29 single nucleotide polymorphisms (SNPs) were selected from 13 candidate genes relevant to two potential pharmacological axes of psychotropic-related weight profiles, appetite peptides and peripheral lipid homeostasis. We applied physiogenomic analysis to a cross-section of 67 and 101 patients being treated with olanzapine and risperidone, respectively, and assessed genetic associations with the weight profiles. Weight profiles in patients treated with olanzapine were significantly associated with SNPs in the genes for apolipoprotein E, apolipoprotein A4 and scavenger receptor class B, member 1. Weight profiles in patients treated with risperidone were significantly associated with SNPs in the genes for leptin receptor, neuropeptide Y receptor Y5 and paraoxonase 1. These results are consistent with contrasting mechanisms for the weight profile of patients treated with these drugs. Genes associated with olanzapine weight profiles may be related to peripheral lipid homeostatic axes, whereas those associated with risperidone's may be related to brain appetite peptide regulation. Future physiogenomic studies will include neurotransmitter receptor SNPs and validation in independent samples.
A 54-year-old woman presented with severe anxiety, multiple somatic complaints, medication intolerance and adverse drug reactions (ADRs) to numerous prescribed psychotropic medications. Multiple drug metabolizing deficiencies were suspected. Molecular analysis was performed for the CYP2 family of Cytochrome P450 (CYP450) drug metabolism isoenzymes by DNA typing CYP2D6, CYP2C9, and CYP2C19 genes. A multiple deficiency in CYP2 drug metabolism was discovered. The patient was a double carrier of null alleles for CYP2D6, a carrier of a null allele for CYP2C19 and a carrier of a deficient allele for CYP2C9. These alleles were confirmed by Mendelian inheritance in her nuclear family, where her brother had a similar multigene CYP2 deficiency. The patient improved clinically with discontinuation of psychotropic medications, suggesting that much of her symptomatology was drug-induced. DNA typing for multigene CYP2 deficiencies is diagnostically useful in individuals with histories of multiple ADRs, which could be avoided by DNA-guided individualized prescription.
Following a prior Kentucky clinical practice study on metabolic syndrome, serum glucose and lipid levels were used in a new sample to determine whether after correcting for confounding factors, olanzapine hyperlipidemia risk may be higher under naturalistic non-randomized treatment. Serum glucose, total cholesterol, HDL cholesterol and triglyceride levels were assessed in 360 patients with severe mental illnesses. The initial goal was to focus on olanzapine lipid profiles, but visual data inspection indicated that quetiapine needed attention as well. Patients were divided into 3 groups: 57 (16%) on olanzapine, 105 (29%) on quetiapine, and 198 (55%) on other antipsychotics (risperidone, ziprasidone, aripiprazole or typicals). HDL and glucose levels were not significantly different across the three antipsychotic groups. When compared with other antipsychotics, olanzapine patients had a borderline significantly higher mean total serum cholesterol level (178 vs. 192 mg/dl, p=0.06) and mean triglyceride level (172 vs. 202 mg/dl, p=0.06). These differences became significant (p=0.006 and 0.03) after correcting for confounders. Quetiapine appeared overprescribed in patients with metabolic syndrome complications. When compared with other antipsychotics, quetiapine patients had a significantly higher mean total serum cholesterol level (178 vs. 194 mg/dl, p=0.004) and mean triglyceride level (172 vs. 225 mg/dl, p<0.001). These differences were significant (p=0.02 and <0.001) after correcting for confounders. This study is consistent with emerging literature that suggests that some antipsychotics may have direct and immediate effects on lipid levels beyond obesity effects. The effect sizes of olanzapine and quetiapine on hyperlipidemia were about 0.40 in this naturalistic study.
There is current interest in understanding genetic influences on brain function in both the healthy and the disordered brain. Parallel independent component analysis, a new method for analyzing multimodal data, is proposed in this paper and applied to functional magnetic resonance imaging (fMRI) and a single nucleotide polymorphism (SNP) array. The method aims to identify the independent components of each modality and the relationship between the two modalities. We analyzed 92 participants, including 29 schizophrenia (SZ) patients, 13 unaffected SZ relatives, and 50 healthy controls. We found a correlation of 0.79 between one fMRI component and one SNP component. The fMRI component consists of activations in cingulate gyrus, multiple frontal gyri, and superior temporal gyrus. The related SNP component is contributed to significantly by 9 SNPs located in sets of genes, including those coding for apolipoprotein A-I, and C-III, malate dehydrogenase 1 and the gamma-aminobutyric acid alpha-2 receptor. A significant difference in the presences of this SNP component is found between the SZ group (SZ patients and their relatives) and the control group. In summary, we constructed a framework to identify the interactions between brain functional and genetic information; our findings provide new insight into understanding genetic influences on brain function in a common mental disorder.
An algorithm for the efficient calculation of macromolecular force fields on the Connection Machine is described. The full force field is separated into bond interactions and non-bonding interactions. Only the latter are implemented on the Connection Machine, the former, less computationally intensive tasks are performed by an existing, conventional molecular dynamics code on the front end. Parallelization of the evaluation of non-bonding interactions is achieved by the Replicated Systolic Loop algorithm introduced in this paper. The algorithm is a variant of the Systolic Loop scheme often used for the computation of 2-particle forces for the classical N-particle problem.
Many drugs are metabolized by highly polymorphic cytochrome P450 (CYP) enzymes. Among these enzymes, members of the CYP2 family coded by the CYP2D6, CYP2C9 and CYP2C19 genes are best amenable to the precise prediction of an individual's innate capacity to metabolize drugs by DNA typing of inherited null and deficient alleles. We determined the frequency of these alleles and the prevalence of their carriers in a New England, USA, tertiary care center to assess underlying population genetic features for the practice of personalized medicine. We determined that 54, 25 and 27% are carriers of at least one deficient or null allele for the CYP2D6, CYP2C9 and CYP2C19 genes, respectively. Furthermore, 6% of individuals are carriers of two null alleles for CYP2D6 and are predicted to have no biochemical activity for this isoenzyme. These results support the implementation of DNA typing of CYP2 genes to diagnose adverse drug reactions and to prevent a substantial number of patients being prescribed drugs they cannot adequately metabolize.
- Apr 2006
High density lipoprotein cholesterol (HDL-C) is a primary risk factor for cardiovascular disease. Apolipoprotein A-1 (apoA1) is the major HDL-associated apolipoprotein. The -75G/A single nucleotide polymorphism (SNP) in the apolipoprotein A1 gene (APOA1) promoter has been reported to be associated with HDL-C concentrations as well as HDL-C response to dietary changes in polyunsaturated fat intake. We examined the effect of this APOA1 SNP on exercise-induced changes in HDL subfraction distribution. From a cohort of healthy normolipidemic adults who volunteered for 6 months of supervised aerobic exercise, 75 subjects were genotyped for the -75G/A SNP. Of these, 53 subjects were G homozygotes (G/G) and 22 were A carriers (A/G and A/A). HDL subfractions were measured by nuclear magnetic resonance (NMR) spectroscopy by adding categories HDL-C 1+2 for the small subfraction, and HDL-C 3+4+5 for the large. The change in total HDL-C after exercise was 0.8+/-7.2 mg/dL (+1.7%), and was not statistically significant. HDL subfraction amounts also did not significantly change with exercise training in the total cohort or in G homozygotes or A carriers. The amount of the large HDL subfraction increased in the G homozygotes and decreased in the A carriers (mean+/-S.E.M., 1.8+/-6.6 mg/dL versus -6.1+/-2.3 mg/dL, p<0.0005). In contrast, the amount of the small HDL subfraction decreased in G homozygotes and increased in A carriers (-1.3+/-6.6 mg/dL versus 4.7+/-1.2 mg/dL, p<0.005). These results show that genetic variation at the APOA1 gene promoter is associated with HDL subfraction redistribution resulting from exercise training.
Diets that restrict carbohydrate (CHO) have proven to be a successful dietary treatment of obesity for many people, but the degree of weight loss varies across individuals. The extent to which genetic factors associate with the magnitude of weight loss induced by CHO restriction is unknown. We examined associations among polymorphisms in candidate genes and weight loss in order to understand the physiological factors influencing body weight responses to CHO restriction. We screened for genetic associations with weight loss in 86 healthy adults who were instructed to restrict CHO to a level that induced a small level of ketosis (CHO approximately 10% of total energy). A total of 27 single nucleotide polymorphisms (SNPs) were selected from 15 candidate genes involved in fat digestion/metabolism, intracellular glucose metabolism, lipoprotein remodeling, and appetite regulation. Multiple linear regression was used to rank the SNPs according to probability of association, and the most significant associations were analyzed in greater detail. Mean weight loss was 6.4 kg. SNPs in the gastric lipase (LIPF), hepatic glycogen synthase (GYS2), cholesteryl ester transfer protein (CETP) and galanin (GAL) genes were significantly associated with weight loss. A strong association between weight loss induced by dietary CHO restriction and variability in genes regulating fat digestion, hepatic glucose metabolism, intravascular lipoprotein remodeling, and appetite were detected. These discoveries could provide clues to important physiologic adaptations underlying the body mass response to CHO restriction.
Statins are highly effective at reducing coronary disease risk. The main side effects of these medications are a variety of skeletal muscle complaints ranging from mild myalgia to frank rhabdomyolysis. To search for physiologic factors possibly influencing statin muscle toxicity, we screened for genetic associations with serum creatine kinase (CK) levels in 102 patients receiving statin therapy for hypercholesteremia. A total of 19 single nucleotide polymorphism (SNPs) were selected from ten candidate genes involved in vascular homeostasis. Multiple linear regression was used to rank the SNPs according to probability of association, and the most significant associations were analyzed in greater detail. SNPs in the angiotensin II Type 1 receptor (AGTR1) and nitric oxide synthase 3 (NOS3) genes were significantly associated with CK activity. These results demonstrate a strong association between CK activity during statin treatment and variability in genes related to vascular function, and suggest that vascular smooth muscle function may contribute to the muscle side effects of statins.
Public health and medicine share a common objective of prolonging life. However, the means by which this can be attained have long repre-sented very different perspectives and strategies. Medicine has traditionally focused on treating patients who, by definition, are ill and in need of restoration to health, while public health seeks to reduce the number of individuals acquiring illness in the first place. Hence, medicine generally focuses on the needs of individuals in order to deliver the best treatment available to that person, taking into account their personal and clinical characteristics. On the other hand, public health focuses on the needs of the population as a whole, developing a health program that will serve the common good by reducing overall disease risk; with the understanding that a small minority may not realize the intended benefit. The two perspectives can be illustrated by the approaches for dealing with dental caries. A com-munity that adopts a public health approach to the problem might add fluoride to the water sup-ply, thus increasing the resistance of individuals to caries by making tooth enamel more resistant. Alternatively, the community may instead choose to provide its citizens with dental insurance, in which caries are treated once they develop. The former is certainly more cost effective from the perspective of the population, but the latter would avoid inducing any rare side effects that may result from the addition of something to the public water supply. Some individuals may have a gene or a lifestyle that makes them more resistant to the development of caries, so that they would person-ally receive little benefit from the addition of fluo-ride to the water, yet they may suffer some risk of harm from it. If it were possible to identify those individuals who would benefit most from a partic-ular form of treatment or disease prevention, then it may be possible to optimize the program as a whole, by avoiding side effects and increasing effi-ciency. In effect, this effort would bring together aspects of the medical and the public health per-spectives by personalizing the public health strate-gies, thus providing a method by which individuals can optimize their own health, and in the process benefit the population at large. In this report, the manner in which data from a variety of sources can be used to arrive at statistical models that may be used in prediction is consid-ered. First, the study designs that are employed, in addition to the behavior of the variables, are desci-bed. In addition, the basic structure of a general-ized linear model, indicating how this can be adapted in order to cover a wide variety of different types of data, is set out. These require specific ways for dealing with measurement types when the fac-tor is a response and when it is a predictor. Some of the issues involved in selecting prediction models and assessing their adequacy are also discussed.
- Jan 2005
We have investigated the association between APOE genotypes and C-reactive protein (CRP) levels in a cohort of approximately 600 individuals who were candidates for statin therapy. An association had been previously reported between the APOE3 allele and elevated CRP levels. That study only examined men. We have reproduced that association in men and have extended the finding to women. We also investigated the effect of the interaction between APOE genotype and hormone replacement therapy (HRT) status on CRP levels, adjusting for body mass index (BMI) and other covariates. BMI and HRT are also significant predictors of CRP, as previously reported. The effect of HRT is strong enough that the contribution of APOE genotype is no longer statistically significant among women on HRT. We also demonstrate that the presence or absence of the single SNP Cysl30Arg (which distinguishes APOE4 from APOE2 and APOE3) is sufficient to determine whether an individual is predisposed to higher or lower CRP levels. Essentially, the presence of one or two copies of APOE4 is associated with a reduction of CRP levels by approximately 34% relative to individuals with zero copies (1.73 mg/L for subjects with one or two copies versus 2.63 mg/L for subjects with zero copies of APOE4). We also tested previously reported associations between CRP levels and polymorphisms in the CRP and IL6 genes. These associations were not reproduced in our cohort.
The public SNP databases are an important resource for groups performing genetic association and linkage studies. Both academic and commercial groups are developing large numbers of genotyping assays for SNPs in candidate genes or spread across the genome. These databases now contain in excess of 6 million SNPs that have been generated using a large number of methods and cohorts. Today, however, only a small fraction of these SNPs are well characterized and validated. The latest release of dbSNP contains approximately 3.7 million non-redundant entries, only 0.5 million of which are validated, and 0.2 million of which have frequency information. Users of these databases have several common questions. How many of the SNPs are real? What is the frequency spectrum of the SNPs in these databases? What is the distribution picture of these SNPs across different ethnic and geographical populations? What fraction of the total number of SNPs is already captured by these databases? In order to address these questions, we compared the public SNPs against a well-characterized collection of gene-centric SNPs that we have developed. From this comparison, we find that > 50% of high frequency SNPs in the genome (> 20% minor allele frequency) have already been captured by these databases. The coverage drops dramatically below frequencies of 10%. At high frequencies, there is no sampling bias with respect to ethnicity or to regions of the genome. Finally, a relatively large fraction (> 40%) of SNPs in these databases were not seen in our study, which means that they are either of very low frequency, mismapped, or not polymorphic at all.
We derive and compare several estimates of the number of SNPs that would be required to form the basis of a complete haplotype survey of the human genome. Our estimates make use of reports published by Stephens et al. , Patil et al.  and Daly et al. . The estimated number of SNPs required for a genome-wide haplotype survey ranges from 180K (based on a European sample of 16 chromosomes) to 600K (based on an ethnically diverse sample of 164 chromosomes). We discuss the implications of using cohorts of different size and ethnic composition and the usefulness of public SNP databases for this effort. Finally, we estimate the experimental effort and cost required to complete a genome-wide haplotype survey.
Variation within genes has important implications for all biological traits. We identified 3899 single nucleotide polymorphisms (SNPs) that were present within 313 genes from 82 unrelated individuals of diverse ancestry, and we organized the SNPs into 4304 different haplotypes. Each gene had several variable SNPs and haplotypes that were present in all populations, as well as a number that were population-specific. Pairs of SNPs exhibited variability in the degree of linkage disequilibrium that was a function of their location within a gene, distance from each other, population distribution, and population frequency. Haplotypes generally had more information content (heterozygosity) than did individual SNPs. Our analysis of the pattern of variation strongly supports the recent expansion of the human population.
A variety of approaches have been proposed to find genetic markers that can be used in a clinical setting. Single nucleotide polymorphisms (SNPs) are the basis of the most commonly used approaches. Here we describe an approach using gene-based haplotypes, which are collections of SNPs located throughout the ftinctional regions of candidate genes, and organised as they occur separately on an individual's two chromosomes. The main point of this review is that the haplotype has greater power than any individual SNP to track an unobsenrved, but evolutionarily linked, variable site.
We describe an mRNA profiling technique for determining differential gene expression that utilizes, but does not require, prior knowledge of gene sequences. This method permits high-throughput reproducible detection of most expressed sequences with a sensitivity of greater than 1 part in 100,000. Gene identification by database query of a restriction endonuclease fingerprint, confirmed by competitive PCR using gene-specific oligonucleotides, facilitates gene discovery by minimizing isolation procedures. This process, called GeneCalling, was validated by analysis of the gene expression profiles of normal and hypertrophic rat hearts following in vivo pressure overload.
- Jun 1997
This paper describes a methodology to calculate the binding free energy (ΔG) of a protein-ligand complex using a continuum model of the solvent. A formal thermodynamic cycle is used to decompose the binding free energy into electrostatic and non-electrostatic contributions. In this cycle, the reactants are discharged in water, associated as purely nonpolar entities, and the final complex is then recharged. The total electrostatic free energies of the protein, the ligand, and the complex in water are calculated with the finite difference Poisson-Boltzmann (FDPB) method. The nonpolar (hydrophobic) binding free energy is calculated using a free energy-surface area relationship, with a single alkane/water surface tension coefficient (γaw). The loss in backbone and side-chain configurational entropy upon binding is estimated and added to the electrostatic and the nonpolar components of ΔG. The methodology is applied to the binding of the murine MHC class I protein H-2Kb with three distinct peptides, and to the human MHC class I protein HLA-A2 in complex with five different peptides. Despite significant differences in the amino acid sequences of the different peptides, the experimental binding free energy differences (ΔΔGexp) are quite small (
- Sep 1995
CCEMD (Center for Computational Engineering Molecular Dynamics) is a general purpose molecular dynamics program written in the C language, built on top of the MD program of Windemuth and Schulten. CCEMD can perform molecular dynamics, gradient minimization, genetic algorithm-based conformation searching, and ligand-protein docking. This report documents the algorithms used and provides a users` guide for the code.
- Jul 1995
We propose a fast implementation of the boundary element method for solving the Poisson equation, which approximately determines the electrostatic field around solvated molecules of arbitrary shape. The method presented uses computational resources of order O(N) only, where N is the number of elements representing the dielectric boundary at the molecular surface. The method is based on the Fast Multipole Algorithm by Rokhlin and Greengard, which is used to calculate the Coulombic interaction between surface elements in linear time. We calculate the solvation energies of a sphere, a small polar molecule, and a moderately sized protein. The values obtained by the boundary element method agree well with results from finite difference calculations and show a higher degree of consistency due to the absence of grid dependencies. The boundary element method can be taken to a much higher accuracy than is possible with finite difference methods and can therefore be used to verify their validity. © 1995 by John Wiley & Sons, Inc.
- Mar 1993
Retinal isomerization reactions, which are functionally important in the proton pump cycle of bacteriorhodopsin, were studied by molecular dynamics simulations performed on the complete protein. Retinal isomerizations were simulated in situ to account for the effects of the retinal-protein interactions. The protein structure employed was that described in Nonella et al. [Nonella, M., Windemuth, A., & Schulten, K. (1991) Photochem. Photobiol. 54, 937-948]. We investigated two mechanisms suggested previously for the proton pump cycle, the 13-cis isomerization model (C-T model) and the 13,14-dicis isomerization model. According to these models, retinal undergoes an all-trans-->13-cis or an all-trans-->13,14-dicis photoisomerization as the primary step of the pump cycle. From the simulations emerged a consistent picture of isomerization reactions and their control through the retinal-protein interactions which favors the 13,14-dicis isomerization model. Electrostatic interactions between the protonated Schiff base and its counterion are found to direct the stereochemistry of retinal in the photocycle: this and other interactions steer retinal toward the 13,14-dicis geometry in the primary photoreaction, toward the 13-cis geometry after its deprotonation, and to the all-trans isomeric form after its reprotonation. We also propose a catalytic mechanism involving hydrogen bonding of the Schiff base to main chain oxygen atoms of Val-49 and Thr-89 for the 13-cis-->all-trans thermal reisomerization of retinal. The all-trans-->13-cis primary photoreaction required by the "C-T" model was found to be inhibited by the Schiff base-counterion interaction, but the possibility of such a reaction can not be excluded. In order to investigate the "C-T" model, we enforced an all-trans-->13-cis photoisomerization in a simulation and monitored the subsequent protein conformational changes. The effects of internal water molecules on retinal isomerization reactions were studied by placing 16 water molecules in the proton conduction channel. The results indicate that water affects the nature of the Schiff base counterion and the nature of the primary photoreaction. Water chains, formed between positively and negatively charged protein groups in the proton conduction channel, are suggested to be involved in the reprotonation and deprotonation of retinal.
We have implemented the fast multipole algorithm (FMA) of Greengard and Rokhlin and incorporated it into the molecular dynamics program MD of Windemuth and Schulten, allowing rapid computation of the non-bonded forces acting in dynamical protein systems without truncation or other corruption of the Coulomb force. The resulting program speeds up simulations of protein systems with approximately 24000 atoms by up to an order of magnitude on a single workstation. Additionally, we have implemented a parallel version of the three-dimensional FMA code on a loosely coupled network of workstations, further reducing simulation times. Large (in both size of system and length of simulated time) protein molecular dynamics simulations are now possible on workstations rather than supercomputers, and very large protein computations are possible on clusters of workstations and parallel machines.
For the purpose of molecular dynamics simulations of large biopolymers we have developed a new method to accelerate the calculation of long-range pair interactions (e.g. Coulomb interaction). The algorithm introduces distance classes to schedule updates of non-bonding interactions and to avoid unnecessary computations of interactions between particles which are far apart. To minimize the error caused by the updating schedule, the Verlet integration scheme has been modified. The results of the method are compared to those of other approximation schemes as well as to results obtained by numerical integration without approximation. For simulation of a protein with 12 637 atoms our approximation scheme yields a reduction of computer time by a factor of seven. The approximation suggested can be implemented on sequential as well as on parallel computers. We describe an implementation on a (Transputer-based) MIMD machine with a systolic ring architecture.
- Feb 1991
Molecular dynamics simulations investigate local and global motion in molecules. Several parallel computing approaches have been taken to attack the most computationally expensive phase of molecular simulations, the evaluation of long range interactions. This paper develops a straightforward but effective algorithm for molecular dynamics simulations using the machine-independent parallel programming language, Linda. The algorithm was run both on a shared memory parallel computer and on a network of high performance Unix workstations. Performance benchmarks were performed on both systems using two proteins. This algorithm offers a portable cost-effective alternative for molecular dynamics simulations. In view of the increasing numbers of networked workstations, this approach could help make molecular dynamics simulations more easily accessible to the research community.
A two stage orbital launch system is proposed. The system can be constructed using commercially available tether materials. The lower tether is propelled by electric tow aircraft powered by grid electricity. The end of the lower tether is travelling at 3 km/s with a radius of 400km. The upper stage is an orbiting electrodynamic tether powered by solar electricity. The payload ascends the lower tether using hub mounted winches and then accelerates due to centripetal force. The payload transfers to the upper tether using a grappling mechanism and then accelerates to orbital velocity using momentum transfer.