Tommi Suvitaival

Tommi Suvitaival
  • Doctor of Science (Technology)
  • Researcher (Asst. Prof.-level) at Steno Diabetes Center

About

70
Publications
10,214
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1,220
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Introduction
I am a data scientist working at Steno Diabetes Center Copenhagen. My work is focused on the integration and analysis of molecular profiles of persons with diabetes. My particular focus is on blood metabolomics for clinical diabetes research. See my personal webpage at tommi-s.com for highlights from my research and for links to my other profiles.
Current institution
Steno Diabetes Center
Current position
  • Researcher (Asst. Prof.-level)

Publications

Publications (70)
Article
Introduction Metabolic responses to glucagon beyond the promotion of endogenous glucose production in type 1 diabetes remains poorly explored. Therefore, we aimed to investigate the metabolic responses to glucagon stimulation in type 1 diabetes and explore whether recent exposure to hypoglycemia would impact glucagon sensitivity. Research Design a...
Article
Aims: Heterogeneity in the rate of β-cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease-modifying clinical trials. Integrative analyses of baseline multi-omics data obtained after the diagnosis of type 1 diabetes may provide mechanistic insight into the diverse rat...
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Full-text available
Aims/hypothesis As a result of early loss of the glucagon response, adrenaline is the primary counter-regulatory hormone in type 1 diabetes. Diminished adrenaline responses to hypoglycaemia due to counter-regulatory failure are common in type 1 diabetes, and are probably induced by exposure to recurrent hypoglycaemia, however, the metabolic effects...
Article
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Background: Specific ceramides have been identified as risk markers for cardiovascular disease (CVD) years before onset of disease. Treatment with the glucagon-like peptide-1 receptor agonist (GLP-1RA) liraglutide has been shown to induce beneficial changes in the lipid profile and reduce the risk of CVD. Reducing lipotoxic lipids with an antidiab...
Article
Ceramides are lipid molecules involved in inflammation-related signaling. Recent studies have shown that higher amounts of specific circulating ceramides and their ratios are associated with future development of cardiovascular (CV) disease (CVD). We examined the associations between serum ceramide levels with CVD, kidney failure, and all-cause mor...
Article
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We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insuli...
Preprint
Full-text available
Background Heterogeneity in the rate of β-cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease-modifying clinical trials. Integrative analyses of complementary multi-omics data obtained after the diagnosis of T1D may provide mechanistic insight into the diverse rates...
Article
Background & aims: Alcohol disturbs hepatic lipid synthesis and transport, but the role of lipid dysfunction in alcohol-related liver disease (ALD) is unclear. In this biopsy-controlled, prospective, observational study, we characterized the liver and plasma lipidomes in patients with early ALD. Methods: We performed mass spectrometry-based lipi...
Preprint
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Background: Ceramides are lipid molecules involved in inflammation-related signaling. Recent studies have shown that higher amounts of specific circulating ceramides and ceramide ratios are associated with future development of cardiovascular (CV) disease (CVD). In persons with longstanding type 1 diabetes (T1D), we investigated if serum ceramide l...
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Background: Cardiovascular disease remains the leading cause of mortality in individuals with diabetes and improved understanding of its pathophysiology is needed. We investigated the association of a large panel of metabolites and molecular lipid species with future cardiovascular events in type 1 diabetes. Methods: The study included 669 indiv...
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Background Individuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facil...
Preprint
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Diabetic foot complications is a collective term used for the ailments of the foot that individuals with diabetes incur. The different entities of the term diabetic foot complications are closely linked to each other and several of the other complications of diabetes. Despite implementation of national and international preventive guidelines, diabe...
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Introduction Diabetic cardiovascular autonomic neuropathy (CAN) is associated with increased mortality and morbidity. To explore metabolic mechanisms associated with CAN we investigated associations between serum metabolites and CAN in persons with type 1 diabetes (T1D). Materials and Methods Cardiovascular reflex tests (CARTs) (heart rate respons...
Article
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Feces are the product of our diets and have been linked to diseases of the gut, including Chron’s disease and metabolic diseases such as diabetes. For screening metabolites in heterogeneous samples such as feces, it is necessary to use fast and reproducible analytical methods that maximize metabolite detection. As sample preparation is crucial to o...
Preprint
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(1) Background Feces are the product of our diets and have been linked to diseases of the gut, including Chron’s disease and metabolic diseases such as diabetes. For screening metabolites in heterogeneous samples such as feces, it is necessary to use fast and reproducible analytical methods that maximize metabolite detection. (2) Methods As sampl...
Preprint
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OBJECTIVE: Our aim was to apply state-of-the-art machine learning algorithms to predict the risk of future progression to diabetes complications, including diabetic kidney disease (≥30% decline in eGFR) and diabetic retinopathy (mild, moderate or severe). RESEARCH DESIGN AND METHODS: Using data in a cohort of 537 adults with type 1 diabetes we pred...
Article
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Aims/hypothesis Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic. Methods In three independent cohort...
Article
Full-text available
Introduction Treatment with glucagon-like peptide-1 receptor agonists (GLP-1 RAs) can reduce risk of cardiovascular disease (CVD) in persons living with type 2 diabetes, however the mechanisms explaining this cardiovascular benefit are still debated. We investigated changes in the plasma lipidome following treatment with the GLP-1 RA liraglutide....
Article
Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity a previous study clustered people with diabetes into five diabetes subtypes. The aim of the current study is to investigate the aetiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15...
Preprint
Full-text available
Background and aims Alcohol disturbs hepatic lipid synthesis and transport, but the role of lipid dysfunction in the severity of alcohol-related liver disease (ALD) is unclear. We therefore characterised the liver and plasma lipidome in a biopsy-controlled cohort of patients with early ALD. Methods We performed ultra-high-performance liquid chroma...
Article
Full-text available
Background and aim Genetic markers are established as predictive of type 1 diabetes, but unknown early life environment is believed to be involved. Umbilical cord blood may reflect perinatal metabolism and exposures. We studied whether selected polar metabolites in cord blood contribute to prediction of type 1 diabetes. Methods Using a targeted UH...
Article
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Background & Aims In experimental models, alcohol induces acute changes in lipid metabolism that cause hepatocyte lipoapoptosis and inflammation. Here we study human hepatic lipid turnover during controlled alcohol intoxication. Methods We studied 39 participants with three distinct hepatic phenotypes: alcohol-related liver disease (ALD), non-alco...
Preprint
Full-text available
We have deployed a multi-omics approach in large cohorts of patients with existing type 2 diabetes to identify biomarkers for disease progression across three molecular classes, metabolites, lipids and proteins. A Cox regression analysis for association with time to insulin requirement in 2,973 patients in the DCS, ANDIS and GoDARTS cohorts identif...
Preprint
Full-text available
Background and aim Genetic markers are established as predictive of type 1 diabetes, but unknown early life environment is believed to be involved. Umbilical cord blood may reflect perinatal metabolism and exposures. We studied whether selected polar metabolites in cord blood contribute to prediction of type 1 diabetes. Methods Using a targeted UHP...
Preprint
Full-text available
Background & Aims: In experimental models, alcohol induces acute changes in lipid metabolism that cause hepatocyte lipoapoptosis and inflammation. Here we study human hepatic lipid turnover during controlled alcohol intoxication. Methods: We studied 39 participants with three distinct hepatic phenotypes: alcohol-related liver disease (ALD), non-alc...
Article
Full-text available
Aims Lipid metabolism might be compromised in type 1 diabetes, and the understanding of lipid physiology is critically important. This study aimed to compare the change in plasma lipid concentrations during carbohydrate dietary changes in individuals with type 1 diabetes and identify links to early‐stage dyslipidaemia. We hypothesized that (1) the...
Presentation
Full-text available
A recent study evaluates the plasma lipidome and links the levels of several lipids with the risk of dyslipidemia and heart disease in patients with type 1 diabetes.
Preprint
Full-text available
Aims/hypothesis Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes (T2D). In the current study we replicate and cross-validate these T2D clusters in three large cohorts using readily measured variables in the clinic. Methods In this cross-sectional study, 15...
Article
Full-text available
Aims/hypothesis: Abnormal gut microbiota and blood metabolome profiles have been reported both in children and adults with uncomplicated type 1 diabetes as well as in adults with type 1 diabetes and advanced stages of diabetic nephropathy. In this study we aimed to investigate the gut microbiota and a panel of targeted plasma metabolites in indivi...
Article
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Introduction: Type 1 diabetes (T1D) is caused by the destruction of pancreatic islet beta cells resulting in total loss of insulin production. Recent studies have suggested that the destruction may be interrelated to plasma lipids. Objectives: Specifc lipids have previously been shown to be decreased in children who develop T1D before four years of...
Preprint
Aims/hypothesis: Lipid metabolism might be compromised in type 1 diabetes and the understanding of their physiology is critically important. This study aimed to compare the change in plasma lipid concentrations during carbohydrate dietary changes in individuals with type 1 diabetes and identify predictive biomarkers and early-stage pathophysiology...
Article
Full-text available
Purpose of Review: The underlying factors triggering a cascade of autoimmune response that leads to the death of pancreatic beta cells and type 1 diabetes are to large extent unknown. Aberrations in the lipid balance have been suggested, either as factors directly contributing to autoimmunity or as a reflection of external factors, such as the diet...
Article
Full-text available
Omics based methods may provide new markers associated to diabetic retinopathy (DR). We investigated a wide omics panel of metabolites and lipids related to DR in type 1 diabetes. Metabolomic analyses were performed using two-dimensional gas chromatography with time-of-flight mass spectrometry and lipidomic analyses utilizing an ultra-high-performa...
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Background and aims Adipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of person’s lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here, w...
Preprint
Full-text available
Lipidomics is one of the fastest-growing areas of molecular profiling in medicine. While increasing amounts of lipidomics data are generated, tools for analyzing and interpreting these data are not equally widely available. We present the lipidomeR -- a tool specifically designed for systematic interpretation of large lipidome-wide studies. The lip...
Article
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The current shortage of livers for transplantation has increased the use of marginal organs sourced from donation after circulatory death (DCD). However, these organs have a higher incidence of graft failure, and pre-transplant biomarkers which predict graft function and survival remain limited. Here, we aimed to find biomarkers of liver function b...
Article
Full-text available
The chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools. Frozen stool samples were collected from 10 healthy volunteers and cryogen...
Preprint
Full-text available
Background and aims: Adipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of person's lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here,...
Article
Full-text available
Background: Improved understanding of the pathophysiology causing diabetic kidney disease (DKD) is imperative. The aim of this study was to uncover associations between serum metabolites and renal outcomes. Methods: Non-targeted serum metabolomics analyses were performed in samples from 637 persons with type 1 diabetes using two-dimensional gas chr...
Article
Full-text available
There is an urgent need for a better molecular understanding of the pathophysiology underlying development and progression of diabetic nephropathy. The aim of the current study was to identify novel associations between serum lipidomics and diabetic nephropathy. Non-targeted serum lipidomic analyses were performed with mass spectrometry in 669 indi...
Article
Full-text available
Several small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities, and complications. Here, we report the development and validation of a novel, quantitative method for the determination of a selected panel of 34 metabolite biomarkers from human plasma. We selected a panel of me...
Preprint
Full-text available
Background & Aims: The current shortage of livers for transplantation has increased the use of organs sourced from donation after circulatory death (DCD). These organs are prone to higher incidence of graft failure, but the underlying mechanisms are largely unknown. Here we aimed to find biomarkers of liver function before transplantation to better...
Preprint
Full-text available
Introduction The chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools. Methods Frozen stool samples were collected from 10 healthy...
Preprint
Background Several small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities and complications. Here, we report the development and validation of a novel, quantitative, analytical method for use in the diabetes clinic. This method enables the determination of a selected panel of...
Article
Full-text available
Introduction: A critical and as-yet unmet need in Alzheimer's disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers. Methods: This study analy...
Article
Full-text available
Background: Lifestyle interventions have been shown to delay or prevent the onset of type 2 diabetes among high risk adults. A better understanding of the variability in physiological responses would support the matching of individuals with the best type of intervention in future prevention programmes, in order to optimize risk reduction. The purpo...
Article
Full-text available
Background The identification of early biomarkers of psychotic experiences (PEs) is of interest as early diagnosis and treatment of those at risk of future disorder is associated with improved outcomes. The current study investigated early lipidomic and coagulation pathway protein signatures of later PEs in subjects from the Avon Longitudinal Study...
Article
Full-text available
Background The molecular mechanisms mediating postnatal loss of cardiac regeneration in mammals are not fully understood. We aimed to provide an integrated resource of mRNA, protein, and metabolite changes in the neonatal heart for identification of metabolism‐related mechanisms associated with cardiac regeneration. Methods and Results Mouse ventr...
Article
Full-text available
Background Psychotic patients are at high risk for developing obesity, metabolic syndrome and type 2 diabetes. These metabolic co-morbidities are hypothesized to be related to both treatment side-effects as well as to metabolic changes occurring during the psychosis. Earlier metabolomics studies have shown that blood metabolite levels are predictiv...
Article
Full-text available
Background: There is a need for early markers to track and predict the development of type 2 diabetes mellitus (T2DM) from the state of normal glucose tolerance through prediabetes. In this study we tested whether the plasma molecular lipidome has biomarker potential to predicting the onset of T2DM. Methods: We applied global lipidomic profiling...
Article
Aim Metformin is the first-line treatment for Type 2 diabetes. However, not all people benefit from this drug. Our aim was to investigate the effects of metformin on the plasma metabolome and whether the pretreatment metabolite profile can predict HbA1c outcome. Methods Post hoc analysis of the Copenhagen Insulin and Metformin Therapy (CIMT) trial,...
Article
Full-text available
The identification of an early biomarker of psychotic disorder is important as early treatment is associated with improved patient outcome. Metabolomic and lipidomic approaches in combination with multivariate statistical analysis were applied to identify plasma alterations in children (age 11) (38 cases vs 67 controls) and adolescents (age 18) (36...
Article
Full-text available
Psychotic patients are at high risk for developing obesity, metabolic syndrome and type 2 diabetes. These metabolic co-morbidities are hypothesized to be related to both treatment side effects as well as to metabolic changes occurring during the psychosis. Earlier metabolomics studies have shown that blood metabolite levels are predictive of insuli...
Article
Full-text available
Motivation: Data analysis for metabolomics suffers from uncertainty because of the noisy measurement technology and the small sample size of experiments. Noise and the small sample size lead to a high probability of false findings. Further, individual compounds have natural variation between samples, which in many cases renders them unreliable as b...
Article
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We investigate the problem of detecting toxicogenomic associations that generalize across organisms, that is, statistical dependencies between transcriptional responses of multiple organisms and toxicological outcomes. We apply an interpretable probabilistic model to detect cross-organism toxicogenomic associations and propose an approach for drug...
Article
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Background Mass spectrometry-based metabolomic analysis depends upon the identification of spectral peaks by their mass and retention time. Statistical analysis that follows the identification currently relies on one main peak of each compound. However, a compound present in the sample typically produces several spectral peaks due to its isotopic p...
Conference Paper
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We present a Bayesian translational model for matching patterns in data sets which have neither co-occurring samples nor variables, but only a similar experiment design dividing the samples into two or more categories. The model estimates covariate effects related to this design and separates the factors that are shared across the data sets from th...
Article
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We present a Bayesian model for analysing the effect of multiple experimental factors in two-species studies without the requirement of a priori known match-ing. From model studies of human diseases, conducted using *omics technologies and various model organisms, the question emerges: is there something similar in the molecular responses of the di...
Article
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Translating potential disease biomarkers between multi-species 'omics' experiments is a new direction in biomedical research. The existing methods are limited to simple experimental setups such as basic healthy-diseased comparisons. Most of these methods also require an a priori matching of the variables (e.g., genes or metabolites) between the spe...
Conference Paper
Multivariate multi-way ANOVA-type models are the default tools for analyzing experimental data with multiple independent covariates. However, formulating standard multi-way models is not possible when the data comes from different sources or in cases where some covariates have (partly) unknown structure, such as time with unknown alignment. The “sm...
Article
Full-text available
Analysis of variance (ANOVA)-type methods are the default tool for the analysis of data with multiple covariates. These tools have been generalized to the multivariate analysis of high-throughput biological datasets, where the main challenge is the problem of small sample size and high dimensionality. However, the existing multi-way analysis method...
Article
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Lecture Notes in Computer Science Vol.6321, 538 - 553 Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2010. Barcelona, Spain, 20 - 24 Sept. 2010
Article
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We extend multi-way, multivariate ANOVA-type analysis to cases where one covariate is the view, with features of each view coming from different, high-dimensional domains. The different views are assumed to be connected by having paired samples; this is a common setup in recent bioinformatics experiments, of which we analyze metabolite profiles in...
Article
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We present a Bayesian model for two-way ANOVA-type analysis of high-dimensional, small sample-size datasets with highly correlated groups of variables. Modern cellular measurement methods are a main application area; typically the task is differential analysis between diseased and healthy samples, complicated by additional covariates requiring a mu...

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