Network reconstruction for trans acting genetic loci using multi-omics data and prior information.

BACKGROUND: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors used or have only been applied to model systems. In this study, we reconstruct the regulatory networks underlying trans-QTL hotspots using human cohort data and data-driven prior information. METHODS: We devised a new strategy to integrate QTL with human population scale multi-omics data. State-of-the art network inference methods including BDgraph and glasso were applied to these data. Comprehensive prior information to guide network inference was manually curated from large-scale biological databases. The inference approach was extensively benchmarked using simulated data and cross-cohort replication analyses. Best performing methods were subsequently applied to real-world human cohort data. RESULTS: Our benchmarks showed that prior-based strategies outperform methods without prior information in simulated data and show better replication across datasets. Application of our approach to human cohort data highlighted two novel regulatory networks related to schizophrenia and lean body mass for which we generated novel functional hypotheses. CONCLUSIONS: We demonstrate that existing biological knowledge can improve the integrative analysis of networks underlying trans associations and generate novel hypotheses about regulatory mechanisms.

Randomized test-treatment studies with an outlook on adaptive designs.

BACKGROUND: Diagnostic accuracy studies aim to examine the diagnostic accuracy of a new experimental test, but do not address the actual merit of the resulting diagnostic information to a patient in clinical practice. In order to assess the impact of diagnostic information on subsequent treatment strategies regarding patient-relevant outcomes, randomized test-treatment studies were introduced. Various designs for randomized test-treatment studies, including an evaluation of biomarkers as part of randomized biomarker-guided treatment studies, are suggested in the literature, but the nomenclature is not consistent. METHODS: The aim was to provide a clear description of the different study designs within a pre-specified framework, considering their underlying assumptions, advantages as well as limitations and derivation of effect sizes required for sample size calculations. Furthermore, an outlook on adaptive designs within randomized test-treatment studies is given. RESULTS: The need to integrate adaptive design procedures in randomized test-treatment studies is apparent. The derivation of effect sizes induces that sample size calculation will always be based on rather vague assumptions resulting in over- or underpowered study results. Therefore, it might be advantageous to conduct a sample size re-estimation based on a nuisance parameter during the ongoing trial. CONCLUSIONS: Due to their increased complexity, compared to common treatment trials, the implementation of randomized test-treatment studies poses practical challenges including a huge uncertainty regarding study parameters like the expected outcome in specific subgroups or disease prevalence which might affect the sample size calculation. Since research on adaptive designs within randomized test-treatment studies is limited so far, further research is recommended.

The Alzheimer's Association international guidelines for handling of cerebrospinal fluid for routine clinical measurements of amyloid ß and tau.

The core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers amyloid beta (Aß42 and Aß40), total tau, and phosphorylated tau, have been extensively clinically validated, with very high diagnostic performance for AD, including the early phases of the disease. However, between-center differences in pre-analytical procedures may contribute to variability in measurements across laboratories. To resolve this issue, a workgroup was led by the Alzheimer's Association with experts from both academia and industry. The aim of the group was to develop a simplified and standardized pre-analytical protocol for CSF collection and handling before analysis for routine clinical use, and ultimately to ensure high diagnostic performance and minimize patient misclassification rates. Widespread application of the protocol would help minimize variability in measurements, which would facilitate the implementation of unified cut-off levels across laboratories, and foster the use of CSF biomarkers in AD diagnostics for the benefit of the patients.

DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures.

BACKGROUND: The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances. RESULTS: We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10-10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations. CONCLUSION: Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.

Obesity Genes and Weight Loss During Lifestyle Intervention in Children With Obesity.

Importance: Genome-wide association studies have identified genetic loci influencing obesity risk in children. However, the importance of these loci in the associations with weight reduction through lifestyle interventions has not been investigated in large intervention trials. Objective: To evaluate the associations between various obesity susceptibility loci and changes in body weight in children during an in-hospital, lifestyle intervention program. Design, Setting, and Participants: Long-term Effects of Lifestyle Intervention in Obesity and Genetic Influence in Children (LOGIC), an interventional prospective cohort study, enrolled 1429 children with overweight or obesity to participate in an in-hospital lifestyle intervention program. Genotyping of 56 validated obesity single-nucleotide variants (SNVs) was performed, and the associations between the SNVs and body weight reduction during the intervention were evaluated using linear mixed-effects models for each SNV. The LOGIC study was conducted from January 6, 2006, to October 19, 2013; data analysis was performed from July 15, 2015, to November 6, 2016. Exposures: A 4- to 6-week standardized in-hospital lifestyle intervention program (daily physical activity, calorie-restricted diet, and behavioral therapy). Main Outcomes and Measures: The association between 56 obesity-relevant SNVs and changes in body weight and body mass index. Results: Of 1429 individuals enrolled in the LOGIC Study, 1198 individuals (mean [SD] age, 14.0 [2.2] years; 670 [56%] girls) were genotyped. A mean (SD) decrease was noted in body weight of -8.7 (3.6) kg (95% CI, -15.7 to -1.8 kg), and body mass index (calculated as weight in kilograms divided by height in meters squared) decreased by -3.3 (1.1) (95% CI, -5.4 to -1.1) (both P < .05). Five of 56 obesity SNVs were statistically significantly associated with a reduction of body weight or body mass index (all P < 8.93 × 10-4 corresponding to Bonferroni correction for 56 tests). Compared with homozygous participants without the risk allele, homozygous carriers of the rs7164727 (LOC100287559: 0.42 kg; 95% CI, 0.31-0.53 kg, P = 4.00 × 10-4) and rs12940622 (RPTOR: 0.35 kg; 95% CI, 0.18-0.52 kg; P = 1.86 × 10-5) risk alleles had a lower reduction of body weight, whereas carriers of the rs13201877 (IFNGR1: 0.65 kg; 95% CI, 0.51-0.79 kg; P = 2.39 × 10-5), rs10733682 (LMX1B: 0.45 kg; 95% CI, 0.27-0.63 kg; P = 6.37 × 10-4), and rs2836754 (ETS2: 0.56 kg; 95% CI, 0.38-0.74 kg; P = 1.51 × 10-4) risk alleles were associated with a greater reduction of body weight after adjustment for age and sex. Conclusions and Relevance: Genes appear to play a minor role in weight reduction by lifestyle in children with overweight or obesity. The findings suggest that environmental, social, and behavioral factors are more important to consider in obesity treatment strategies.

Pre-analytical protocol for measuring Alzheimer's disease biomarkers in fresh CSF.

INTRODUCTION: We aimed to establish a standardized, routine-use pre-analytical protocol for measuring Alzheimer's disease (AD) biomarkers in cerebrospinal fluid (CSF). METHODS: The effect of pre-analytical factors (sample collection/handling/storage/transportation) on biomarker levels was assessed using freshly collected CSF. Tube type/sterilization was assessed using previously frozen samples. A low-bind false-bottom tube (FBT, Sarstedt) was used for all experiments, except tube types/sterilization experiments. Biomarkers were measured using Elecsys CSF assays. RESULTS: Amyloid beta (Aß)1-42 levels varied by tube type, using a low-bind FBT reduced variation. Aß1-42 levels were higher with no mixing versus roller/inversion mixing. Aß1-42 levels were lower with horizontal versus upright transportation; this was resolved by maximal tube filling and storage at 2°C to 8°C. Aß1-40 levels were less strongly affected. Phospho-tau and total-tau levels were largely unaffected. DISCUSSION: We propose an easy-to-use, standardized, routine-use pre-analytical protocol, using low-bind FBTs, for measuring AD CSF biomarkers in clinical practice.

A genome-wide analysis of DNA methylation identifies a novel association signal for Lp(a) concentrations in the LPA promoter.

Lipoprotein(a) [Lp(a)] is a major cardiovascular risk factor, which is largely genetically determined by one major gene locus, the LPA gene. Many aspects of the transcriptional regulation of LPA are poorly understood and the role of epigenetics has not been addressed yet. Therefore, we conducted an epigenome-wide analysis of DNA methylation on Lp(a) levels in two population-based studies (total n = 2208). We identified a CpG site in the LPA promoter which was significantly associated with Lp(a) concentrations. Surprisingly, the identified CpG site was found to overlap the SNP rs76735376. We genotyped this SNP de-novo in three studies (total n = 7512). The minor allele of rs76735376 (1.1% minor allele frequency) was associated with increased Lp(a) values (p = 1.01e-59) and explained 3.5% of the variation of Lp(a). Statistical mediation analysis showed that the effect on Lp(a) is rather originating from the base change itself and is not mediated by DNA methylation levels. This finding is supported by eQTL data from 208 liver tissue samples from the GTEx project, which shows a significant association of the rs76735376 minor allele with increased LPA expression. To evaluate, whether the association signal at rs76735376 may actually be derived from a stronger eQTL signal in LD with this SNP, eQTL association results of all correlated SNPs (r2≥0.1) were integrated with genetic association results. This analysis pinpointed to rs10455872 as the potential trigger of the effect of rs76735376. Furthermore, both SNPs coincide with short apo(a) isoforms. Adjusting for both, rs10455872 and the apo(a) isoforms diminished the effect size of rs76735376 to 5.38 mg/dL (p = 0.0463). This indicates that the effect of rs76735376 can be explained by both an independent effect of the SNP and a strong correlation with rs10455872 and apo(a) isoforms.

Predicting clinical decline and conversion to Alzheimer's disease or dementia using novel Elecsys Aß(1-42), pTau and tTau CSF immunoassays.

We evaluated the performance of CSF biomarkers for predicting risk of clinical decline and conversion to dementia in non-demented patients with cognitive symptoms. CSF samples from patients in two multicentre longitudinal studies (ADNI, n = 619; BioFINDER, n = 431) were analysed. Aß(1-42), tTau and pTau CSF concentrations were measured using Elecsys CSF immunoassays, and tTau/Aß(1-42) and pTau/Aß(1-42) ratios calculated. Patients were classified as biomarker (BM)-positive or BM-negative at baseline. Ability of biomarkers to predict risk of clinical decline and conversion to AD/dementia was assessed using pre-established cut-offs for Aß(1-42) and ratios; tTau and pTau cut-offs were determined. BM-positive patients showed greater clinical decline than BM-negative patients, demonstrated by greater decreases in MMSE scores (all biomarkers: -2.10 to -0.70). Risk of conversion to AD/dementia was higher in BM-positive patients (HR: 1.67 to 11.48). Performance of Tau/Aß(1-42) ratios was superior to single biomarkers, and consistent even when using cut-offs derived in a different cohort. Optimal pTau and tTau cut-offs were approximately 27 pg/mL and 300 pg/mL in both BioFINDER and ADNI. Elecsys pTau/Aß(1-42) and tTau/Aß(1-42) are robust biomarkers for predicting risk of clinical decline and conversion to dementia in non-demented patients, and may support AD diagnosis in clinical practice.

Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

Epigenetic upregulation of FKBP5 by aging and stress contributes to NF-κB-driven inflammation and cardiovascular risk.

Aging and psychosocial stress are associated with increased inflammation and disease risk, but the underlying molecular mechanisms are unclear. Because both aging and stress are also associated with lasting epigenetic changes, a plausible hypothesis is that stress along the lifespan could confer disease risk through epigenetic effects on molecules involved in inflammatory processes. Here, by combining large-scale analyses in human cohorts with experiments in cells, we report that FKBP5, a protein implicated in stress physiology, contributes to these relations. Across independent human cohorts (total n > 3,000), aging synergized with stress-related phenotypes, measured with childhood trauma and major depression questionnaires, to epigenetically up-regulate FKBP5 expression. These age/stress-related epigenetic effects were recapitulated in a cellular model of replicative senescence, whereby we exposed replicating human fibroblasts to stress (glucocorticoid) hormones. Unbiased genome-wide analyses in human blood linked higher FKBP5 mRNA with a proinflammatory profile and altered NF-κB-related gene networks. Accordingly, experiments in immune cells showed that higher FKBP5 promotes inflammation by strengthening the interactions of NF-κB regulatory kinases, whereas opposing FKBP5 either by genetic deletion (CRISPR/Cas9-mediated) or selective pharmacological inhibition prevented the effects on NF-κB. Further, the age/stress-related epigenetic signature enhanced FKBP5 response to NF-κB through a positive feedback loop and was present in individuals with a history of acute myocardial infarction, a disease state linked to peripheral inflammation. These findings suggest that aging/stress-driven FKBP5-NF-κB signaling mediates inflammation, potentially contributing to cardiovascular risk, and may thus point to novel biomarker and treatment possibilities.

Diagnostic performance of Elecsys immunoassays for cerebrospinal fluid Alzheimer's disease biomarkers in a nonacademic, multicenter memory clinic cohort: The ABIDE project.

INTRODUCTION: We compared the automated Elecsys and manual Innotest immunoassays for cerebrospinal fluid (CSF) Alzheimer's disease biomarkers in a multicenter diagnostic setting. METHODS: We collected CSF samples from 137 participants in eight local memory clinics. Amyloid ß(1-42) (Aß42), total tau (t-tau), and phosphorylated tau (p-tau) were centrally analyzed with Innotest and Elecsys assays. Concordances between methods were assessed. RESULTS: Biomarker results strongly correlated between assays with Spearman's ρ 0.94 for Aß42, 0.98 for t-tau, and 0.98 for p-tau. Using Gaussian mixture modeling, cohort-specific cut-points were estimated at 1092 pg/mL for Aß42, 235 pg/mL for t-tau, and 24 pg/mL for p-tau. We found an excellent concordance of biomarker abnormality between assays of 97% for Aß42 and 96% for both t-tau and p-tau. DISCUSSION: The high concordances between Elecsys and Innotest in this nonacademic, multicenter cohort support the use of Elecsys for CSF Alzheimer's disease diagnostics and allow conversion of results between methods.

Derivation of cutoffs for the Elecsys® amyloid ß (1-42) assay in Alzheimer's disease.

INTRODUCTION: An Elecsys® Amyloid ß (Aß [1-42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. METHODS: Cerebrospinal fluid samples collected from patients with mild-to-moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aß (1-42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aß [1-42] and ratios with tau) were estimated by method comparison between AlzBio3 (n = 206), mixture modeling (n = 216), and concordance with florbetapir F 18 imaging-based classification (n = 75). RESULTS: A 1065-pg/mL (95% confidence interval: 985-1153) Elecsys® Aß (1-42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949-1205] pg/mL; prevalence weighted: 1172 [1081-1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998-1591] pg/mL; automated: 1198 [1051-1638] pg/mL). DISCUSSION: Based on three approaches, a 1100-pg/mL Elecsys® Aß (1-42) cutoff is suitable for clinical trials with similar populations and preanalytical handling.

Metastable DNA methylation sites associated with longitudinal lung function decline and aging in humans: an epigenome-wide study in the NAS and KORA cohorts.

DNA methylation is an epigenetic regulator of gene transcription, which has been found to be both metastable and variable within human cohort studies. Currently, few studies have been done to identify metastable DNA methylation biomarkers associated with longitudinal lung function decline in humans. The identification of such biomarkers is important for screening vulnerable populations. We hypothesized that quantifiable blood-based DNA methylation alterations would serve as metastable biomarkers of lung function decline and aging, which may help to discover new pathways and/or mechanisms related to pulmonary pathogenesis. Using linear mixed models, we performed an Epigenome Wide Association Study (EWAS) between DNA methylation at CpG dinucleotides and longitudinal lung function (FVC, FEV1, FEF25-75%) decline and aging with initial discovery in the Normative Aging Study, and replication in the Cooperative Health Research in the Region of Augsburg cohort. We identified two metastable epigenetic loci associated with either poor lung function and aging, cg05575921 (AHRR gene), or lung function independently of aging, cg06126421 (IER3 gene). These loci may inform basic mechanisms associated with pulmonary function, pathogenesis, and aging. Human epigenomic variation, may help explain features of lung function decline and related pathophysiology not attributable to DNA sequence alone, such as accelerated pulmonary decline in smokers, former smokers, and perhaps non-smokers. Our EWAS across two cohorts, therefore, will likely have implications for the human population, not just the elderly.

Prenatal Alcohol Exposure Is Associated With Adverse Cognitive Effects and Distinct Whole-Genome DNA Methylation Patterns in Primary School Children.

Prenatal alcohol exposure (PAE) is known to elicit a broad range of systemic effects, including neurophysiological alterations that result in adverse behavioral and cognitive outcomes. However, molecular pathways underlying these long-term intrauterine effects remain to be investigated. Here, we tested a hypothesis that PAE may lead to epigenetic alterations to the DNA resulting in attentional and cognitive alterations of the children. We report the results of the study that included 156 primary school children of the Franconian Cognition and Emotion Studies (FRANCES) cohort which were tested for an objective marker of PAE, ethyl glucuronide (EtG) in meconium at birth. Thirty-two newborns were found to be exposed to alcohol with EtG values above 30 ng/g (EtG+). Previously we described PAE being associated with lower IQ and smaller amplitude of the event-related potential component P3 in go trials (Go-P3), which indicates a reduced capacity of attentional resources. Whole-genome methylation analysis of the buccal cell DNA revealed 193 differentially methylated genes in children with positive meconium EtG, that were clustered into groups involved in epigenetic modifications, neurodegeneration, neurodevelopment, axon guidance and neuronal excitability. Furthermore, we detected mediation effects of the methylation changes in DPP10 and SLC16A9 genes on the EtG related cognitive and attention-related deficits. Our results suggest that system-wide epigenetic changes are involved in long-term effects of PAE. In particular, we show an epigenetic mediation of PAE effects on cognition and attention-related processes.

Cerebrospinal fluid biomarkers measured by Elecsys assays compared to amyloid imaging.

INTRODUCTION: Levels of amyloid ß peptide 42 (Aß42), total tau, and phosphorylated tau-181 are well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease, but variability in manual plate-based assays has limited their use. We examined the relationship between CSF biomarkers, as measured by a novel automated immunoassay platform, and amyloid positron emission tomography. METHODS: CSF samples from 200 individuals underwent separate analysis for Aß42, total tau, and phosphorylated tau-181 with automated Roche Elecsys assays. Aß40 was measured with a commercial plate-based assay. Positron emission tomography with Pittsburgh Compound B was performed less than 1 year from CSF collection. RESULTS: Ratios of CSF biomarkers (total tau/Aß42, phosphorylated tau-181/Aß42, and Aß42/Aß40) best discriminated Pittsburgh Compound B-positive from Pittsburgh Compound B-negative individuals. DISCUSSION: CSF biomarkers and amyloid positron emission tomography reflect different aspects of Alzheimer's disease brain pathology, and therefore, less-than-perfect correspondence is expected. Automated assays are likely to increase the utility of CSF biomarkers.

Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies.

BACKGROUND: Untargeted mass spectrometry (MS)-based metabolomics data often contain missing values that reduce statistical power and can introduce bias in biomedical studies. However, a systematic assessment of the various sources of missing values and strategies to handle these data has received little attention. Missing data can occur systematically, e.g. from run day-dependent effects due to limits of detection (LOD); or it can be random as, for instance, a consequence of sample preparation. METHODS: We investigated patterns of missing data in an MS-based metabolomics experiment of serum samples from the German KORA F4 cohort (n = 1750). We then evaluated 31 imputation methods in a simulation framework and biologically validated the results by applying all imputation approaches to real metabolomics data. We examined the ability of each method to reconstruct biochemical pathways from data-driven correlation networks, and the ability of the method to increase statistical power while preserving the strength of established metabolic quantitative trait loci. RESULTS: Run day-dependent LOD-based missing data accounts for most missing values in the metabolomics dataset. Although multiple imputation by chained equations performed well in many scenarios, it is computationally and statistically challenging. K-nearest neighbors (KNN) imputation on observations with variable pre-selection showed robust performance across all evaluation schemes and is computationally more tractable. CONCLUSION: Missing data in untargeted MS-based metabolomics data occur for various reasons. Based on our results, we recommend that KNN-based imputation is performed on observations with variable pre-selection since it showed robust results in all evaluation schemes.

Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study.

AIMS/HYPOTHESIS: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. METHODS: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case-control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. RESULTS: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p < 9.2 × 10-7). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10-3) and prevalent type 2 diabetes (ORVal_PC ae C32:2 2.64 [ß 0.97 ± 0.09], p = 1.0 × 10-27). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HRVal_PC ae C32:2 1.57 [ß 0.45 ± 0.06]; p = 1.3 × 10-15), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose). CONCLUSIONS/INTERPRETATION: In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.

Allele-specific methylation of type 1 diabetes susceptibility genes.

The susceptibility to autoimmune diseases is influenced by genes encoding major histocompatibility complex (MHC) proteins. By examining the epigenetic methylation maps of cord blood samples, we found marked differences in the methylation status of CpG sites within the MHC genes (cis-metQTLs) between carriers of the type 1 diabetes risk haplotypes HLA-DRB1*03-DQA1*0501-DQB1*0201 (DR3-DQ2) and HLA-DRB1*04-DQA1*0301-DQB1*0302 (DR4-DQ8). These differences were found in children and adults, and were accompanied by reduced HLA-DR protein expression in immune cells with the HLA-DR3-DQ2 haplotype. Extensive cis-metQTLs were identified in all 45 immune and non-immune type 1 diabetes susceptibility genes analyzed in this study. We observed and validated a novel association between the methylation status of CpG sites within the LDHC gene and the development of insulin autoantibodies in early childhood in children who are carriers of the highest type 1 diabetes risk genotype. Functionally relevant epigenetic changes in susceptibility genes may represent therapeutic targets for type 1 diabetes.

Long-Term Stability of Human Plasma Metabolites during Storage at -80 °C.

Prolonged storage of biospecimen can lead to artificially altered metabolite concentrations and thus bias data analysis in metabolomics experiments. To elucidate the potential impact of long-term storage on the metabolite profile, a pooled human plasma sample was aliquoted and stored at -80 °C. During a time period of five years, 1012 of the aliquots were measured with the Biocrates AbsoluteIDQ p180 targeted-metabolomics assay at 193 time points. Modeling the concentration courses over time revealed that 55 out of 111 metabolites remained stable. The statistically significantly changed metabolites showed on average an increase or decrease of +13.7% or -14.5%, respectively. In detail, increased concentration levels were observed for amino acids (mean: + 15.4%), the sum of hexoses (+7.9%), butyrylcarnitine (+9.4%), and some phospholipids mostly with chain lengths exceeding 40 carbon atoms (mean: +18.0%). Lipids tended to exhibit decreased concentration levels with the following mean concentration changes: acylcarnitines, -12.1%; lysophosphatidylcholines, -15.1%; diacyl-phosphatidylcholines, -17.0%; acyl-alkyl-phosphatidylcholines, -13.3%; sphingomyelins, -14.8%. We conclude that storage of plasma samples at -80 °C for up to five years can lead to altered concentration levels of amino acids, acylcarnitines, glycerophospholipids, sphingomyelins, and the sum of hexoses. These alterations must be considered when analyzing metabolomics data from long-term epidemiological studies.

Anxiety Associated Increased CpG Methylation in the Promoter of Asb1: A Translational Approach Evidenced by Epidemiological and Clinical Studies and a Murine Model.

Epigenetic regulation in anxiety is suggested, but evidence from large studies is needed. We conducted an epigenome-wide association study (EWAS) on anxiety in a population-based cohort and validated our finding in a clinical cohort as well as a murine model. In the KORA cohort, participants (n=1522, age 32-72 years) were administered the Generalized Anxiety Disorder (GAD-7) instrument, whole blood DNA methylation was measured (Illumina 450K BeadChip), and circulating levels of hs-CRP and IL-18 were assessed in the association between anxiety and methylation. DNA methylation was measured using the same instrument in a study of patients with anxiety disorders recruited at the Max Planck Institute of Psychiatry (MPIP, 131 non-medicated cases and 169 controls). To expand our mechanistic understanding, these findings were reverse translated in a mouse model of acute social defeat stress. In the KORA study, participants were classified according to mild, moderate, or severe levels of anxiety (29.4%/6.0%/1.5%, respectively). Severe anxiety was associated with 48.5% increased methylation at a single CpG site (cg12701571) located in the promoter of the gene encoding Asb1 (ß-coefficient=0.56 standard error (SE)=0.10, p (Bonferroni)=0.005), a protein hypothetically involved in regulation of cytokine signaling. An interaction between IL-18 and severe anxiety with methylation of this CpG cite showed a tendency towards significance in the total population (p=0.083) and a significant interaction among women (p=0.014). Methylation of the same CpG was positively associated with Panic and Agoraphobia scale (PAS) scores (ß=0.005, SE=0.002, p=0.021, n=131) among cases in the MPIP study. In a murine model of acute social defeat stress, Asb1 gene expression was significantly upregulated in a tissue-specific manner (p=0.006), which correlated with upregulation of the neuroimmunomodulating cytokine interleukin 1 beta. Our findings suggest epigenetic regulation of the stress-responsive Asb1 gene in anxiety-related phenotypes. Further studies are necessary to elucidate the causal direction of this association and the potential role of Asb1-mediated immune dysregulation in anxiety disorders.