Biological age captures a person’s age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers... Show moreBiological age captures a person’s age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment. Show less
Background: Thyroid hormones play a key role in differentiation and metabolism and are known regulators of gene expression through both genomic and epigenetic processes including DNA methylation.... Show moreBackground: Thyroid hormones play a key role in differentiation and metabolism and are known regulators of gene expression through both genomic and epigenetic processes including DNA methylation. The aim of this study was to examine associations between thyroid hormones and DNA methylation.Methods: We carried out a fixed-effect meta-analysis of epigenome-wide association study (EWAS) of blood DNA methylation sites from 8 cohorts from the ThyroidOmics Consortium, incorporating up to 7073 participants of both European and African ancestry, implementing a discovery and replication stage. Statistical analyses were conducted using normalized beta CpG values as dependent and log-transformed thyrotropin (TSH), free thyroxine, and free triiodothyronine levels, respectively, as independent variable in a linear model. The replicated findings were correlated with gene expression levels in whole blood and tested for causal influence of TSH and free thyroxine by two-sample Mendelian randomization (MR).Results: Epigenome-wide significant associations (p-value <1.1E-7) of three CpGs for free thyroxine, five for free triiodothyronine, and two for TSH concentrations were discovered and replicated (combined p-values = 1.5E-9 to 4.3E-28). The associations included CpG sites annotated to KLF9 (cg00049440) and DOT1L (cg04173586) that overlap with all three traits, consistent with hypothalamic-pituitary-thyroid axis physiology. Significant associations were also found for CpGs in FKBP5 for free thyroxine, and at CSNK1D/LINCO1970 and LRRC8D for free triiodothyronine. MR analyses supported a causal effect of thyroid status on DNA methylation of KLF9. DNA methylation of cg00049440 in KLF9 was inversely correlated with KLF9 gene expression in blood. The CpG at CSNK1D/LINC01970 overlapped with thyroid hormone receptor alpha binding peaks in liver cells. The total additive heritability of the methylation levels of the six significant CpG sites was between 25% and 57%. Significant methylation QTLs were identified for CpGs at KLF9, FKBP5, LRRC8D, and CSNK1D/LINC01970.Conclusions: We report novel associations between TSH, thyroid hormones, and blood-based DNA methylation. This study advances our understanding of thyroid hormone action particularly related to KLF9 and serves as a proof-of-concept that integrations of EWAS with other -omics data can provide a valuable tool for unraveling thyroid hormone signaling in humans by complementing and feeding classical in vitro and animal studies. Show less
Chronic inflammation, marked by C-reactive protein, has been associated with changes in methylation, but the causal relationship is unclear. Here, the authors perform a Epigenome-wide association... Show moreChronic inflammation, marked by C-reactive protein, has been associated with changes in methylation, but the causal relationship is unclear. Here, the authors perform a Epigenome-wide association meta-analysis for C-reactive protein levels and find that these methylation changes are likely the consequence of inflammation and could contribute to disease.We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD. Show less
Maas, S.C.E.; Vidaki, A.; Teumer, A.; Costeira, R.; Wilson, R.; Dongen, J. van; ... ; Kayser, M. 2021
Background Information on long-term alcohol consumption is relevant for medical and public health research, disease therapy, and other areas. Recently, DNA methylation-based inference of alcohol... Show moreBackground Information on long-term alcohol consumption is relevant for medical and public health research, disease therapy, and other areas. Recently, DNA methylation-based inference of alcohol consumption from blood was reported with high accuracy, but these results were based on employing the same dataset for model training and testing, which can lead to accuracy overestimation. Moreover, only subsets of alcohol consumption categories were used, which makes it impossible to extrapolate such models to the general population. By using data from eight population-based European cohorts (N = 4677), we internally and externally validated the previously reported biomarkers and models for epigenetic inference of alcohol consumption from blood and developed new models comprising all data from all categories. Results By employing data from six European cohorts (N = 2883), we empirically tested the reproducibility of the previously suggested biomarkers and prediction models via ten-fold internal cross-validation. In contrast to previous findings, all seven models based on 144-CpGs yielded lower mean AUCs compared to the models with less CpGs. For instance, the 144-CpG heavy versus non-drinkers model gave an AUC of 0.78 +/- 0.06, while the 5 and 23 CpG models achieved 0.83 +/- 0.05, respectively. The transportability of the models was empirically tested via external validation in three independent European cohorts (N = 1794), revealing high AUC variance between datasets within models. For instance, the 144-CpG heavy versus non-drinkers model yielded AUCs ranging from 0.60 to 0.84 between datasets. The newly developed models that considered data from all categories showed low AUCs but gave low AUC variation in the external validation. For instance, the 144-CpG heavy and at-risk versus light and non-drinkers model achieved AUCs of 0.67 +/- 0.02 in the internal cross-validation and 0.61-0.66 in the external validation datasets. Conclusions The outcomes of our internal and external validation demonstrate that the previously reported prediction models suffer from both overfitting and accuracy overestimation. Our results show that the previously proposed biomarkers are not yet sufficient for accurate and robust inference of alcohol consumption from blood. Overall, our findings imply that DNA methylation prediction biomarkers and models need to be improved considerably before epigenetic inference of alcohol consumption from blood can be considered for practical applications. Show less
Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100... Show moreOsteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation. Show less
Ruth, K.S.; Day, F.R.; Hussain, J.; Martinez-Marchal, A.; Aiken, C.E.; Azad, A.; ... ; 23 Me Res Team 2021
Reproductive longevity is essential for fertility and influences healthy ageing in women(1,2), but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here... Show moreReproductive longevity is essential for fertility and influences healthy ageing in women(1,2), but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause in approximately 200,000 women of European ancestry. These common alleles were associated with clinical extremes of age at natural menopause; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations(3). The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease. Show less
Houtman, E.; Almeida, R.C. de; Tuerlings, M.; Suchiman, H.E.D.; Broekhuis, D.; Nelissen, R.G.H.H.; ... ; Meulenbelt, I. 2021
Objective: We here aimed to characterize changes of Matrix Gla Protein (MGP) expression in relation to its recently identified OA risk allele rs1800801-T in OA cartilage, subchondral bone and human... Show moreObjective: We here aimed to characterize changes of Matrix Gla Protein (MGP) expression in relation to its recently identified OA risk allele rs1800801-T in OA cartilage, subchondral bone and human ex vivo osteochondral explants subjected to OA related stimuli. Given that MGP function depends on vitamin K bioavailability, we studied the effect of frequently prescribed vitamin K antagonist warfarin. Methods: Differential (allelic) mRNA expression of MGP was analyzed using RNA-sequencing data of human OA cartilage and subchondral bone. Human osteochondral explants were used to study exposures to interleukin one beta (IL-1b; inflammation), triiodothyronine (T3; Hypertrophy), warfarin, or 65% mechanical stress (65%MS) as function of rs1800801 genotypes. Results: We confirmed that the MGP risk allele rs1800801-T was associated with lower expression and that MGP was significantly upregulated in lesioned as compared to preserved OA tissues, mainly in risk allele carriers, in both cartilage and subchondral bone. Moreover, MGP expression was downregulated in response to OA like triggers in cartilage and subchondral bone and this effect might be reduced in carriers of the rs1800801-T risk allele. Finally, warfarin treatment in cartilage increased COL10A1 and reduced SOX9 and MMP3 expression and in subchondral bone reduced COL1A1 and POSTN expression. Discussion & conclusions: Our data highlights that the genetic risk allele lowers MGP expression and upon OA relevant triggers may hamper adequate dynamic changes in MGP expression, mainly in carti-lage. The determined direct negative effect of warfarin on human explant cultures functionally un-derscores the previously found association between vitamin K deficiency and OA. (c) 2021 The Authors. Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Show less
Background Despite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the... Show moreBackground Despite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the complexity of the different hand joints and heterogeneity of OA pathology.Methods We used data from the Rotterdam Study (RSI, RSII and RSIII) to create three hand OA phenotypes based on clustering patterns of radiographic OA severity to increase power in our modest discovery genome-wide association studies in the RS (n=8700), and sought replication in an independent cohort, the Framingham Heart Study (n=1203). We used multiple approaches that leverage different levels of information and functional data to further investigate the underlying biological mechanisms and candidate genes for replicated loci. We also attempted to replicate known OA loci at other joint sites, including the hips and knees.Results We found two novel genome-wide significant loci for OA in the thumb joints. We identified WNT9A as a possible novel causal gene involved in OA pathogenesis. Furthermore, several previously identified genetic loci for OA seem to confer risk for OA across multiple joints: TGFa, RUNX2, COL27A1, ASTN2, IL11 and GDF5 loci.Conclusions We identified a robust novel genetic locus for hand OA on chromosome 1, of which WNT9A is the most likely causal gene. In addition, multiple genetic loci were identified to be associated with OA across multiple joints. Our study confirms the potential for novel insight into the genetic architecture of OA by using biologically meaningful stratified phenotypes. Show less
Epigenetic programming is essential for lineage differentiation, embryogenesis and placentation in early pregnancy. In epigenetic association studies, DNA methylation is often examined in DNA... Show moreEpigenetic programming is essential for lineage differentiation, embryogenesis and placentation in early pregnancy. In epigenetic association studies, DNA methylation is often examined in DNA derived from white blood cells, although its validity to other tissues of interest remains questionable. Therefore, we investigated the tissue specificity of epigenome-wide DNA methylation in newborn and placental tissues. Umbilical cord white blood cells (UC-WBC, n = 25), umbilical cord blood mononuclear cells (UC-MNC, n = 10), human umbilical vein endothelial cells (HUVEC, n = 25) and placental tissue (n = 25) were obtained from 36 uncomplicated pregnancies. Genome-wide DNA methylation was measured by the Illumina HumanMethylation450K BeadChip. Using UC-WBC as a reference tissue, we identified 3595 HUVEC tissue-specific differentially methylated regions (tDMRs) and 11,938 placental tDMRs. Functional enrichment analysis showed that HUVEC and placental tDMRs were involved in embryogenesis, vascular development and regulation of gene expression. No tDMRs were identified in UC-MNC. In conclusion, the extensive amount of genome-wide HUVEC and placental tDMRs underlines the relevance of tissue-specific approaches in future epigenetic association studies, or the use of validated representative tissues for a certain disease of interest, if available. To this purpose, we herewith provide a relevant dataset of paired, tissue-specific, genome-wide methylation measurements in newborn tissues. Show less
Meessen, J.M.T.A.; Saberi-Hosnijeh, F.; Bomer, N.; Hollander, W. den; Bom, J.G. van der; Hilten, J.A. van; ... ; Meulenbelt, I. 2020
Higher body mass index (BMI) is associated with osteoarthritis (OA) in both weight-bearing and non-weight-bearing joints, suggesting a link between OA and poor metabolic health beyond mechanical... Show moreHigher body mass index (BMI) is associated with osteoarthritis (OA) in both weight-bearing and non-weight-bearing joints, suggesting a link between OA and poor metabolic health beyond mechanical loading. This risk may be influenced by systemic factors accompanying BMI. Fluctuations in concentrations of metabolites may mark or even contribute to development of OA. This study explores the association of metabolites with radiographic knee/hip OA prevalence and progression. A H-1-NMR-metabolomics assay was performed on plasma samples of 1564 cases for prevalent OA and 2,125 controls collected from the Rotterdam Study, CHECK, GARP/NORREF and LUMC-arthroplasty cohorts. OA prevalence and 5 to 10 year progression was assessed by means of Kellgren-Lawrence (KL) score and the OARSI-atlas. End-stage knee/hip OA (TJA) was defined as indication for arthroplasty surgery. Controls did not have OA at baseline or follow-up. Principal component analysis of 227 metabolites demonstrated 23 factors, of which 19 remained interpretable after quality-control. Associations of factor scores with OA definitions were investigated with logistic regression. Fatty acids chain length (FALen), which was included in two factors which associated with TJA, was individually associated with both overall OA as well as TJA. Increased Fatty Acid chain Length is associated with OA. Show less
Background DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes... Show moreBackground DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes that affect DNA methylation patterns in blood using large-scale population genomics data. Results By employing genetic instruments as causal anchors, we establish directed associations between gene expression and distant DNA methylation levels, while ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. The identified genes are enriched for transcription factors, of which many consistently increased or decreased DNA methylation levels at multiple CpG sites. In addition, we show that a substantial number of transcription factors affected DNA methylation at their experimentally determined binding sites. We also observe genes encoding proteins with heterogenous functions that have widespread effects on DNA methylation, e.g.,NFKBIE,CDCA7(L), andNLRC5, and for several examples, we suggest plausible mechanisms underlying their effect on DNA methylation. Conclusion We report hundreds of genes that affect DNA methylation and provide key insights in the principles underlying epigenetic regulation. Show less
Suratannon, N.; Wijck, R.T.A. van; Broer, L.; Xue, L.X.; Meurs, J.B.J. van; Barendregt, B.H.; ... ; South East Asia Primary Immunode 2020
Background: Genetic tests for primary immunodeficiency disorders (PIDs) are expensive, time-consuming, and not easily accessible in developing countries. Therefore, we studied the feasibility of a... Show moreBackground: Genetic tests for primary immunodeficiency disorders (PIDs) are expensive, time-consuming, and not easily accessible in developing countries. Therefore, we studied the feasibility of a customized single nucleotide variant (SNV) microarray that we developed to detect disease-causing variants and copy number variation (CNV) in patients with PIDs for only 40 Euros.Methods: Probes were custom-designed to genotype 9,415 variants of 277 PID-related genes, and were added to the genome-wide Illumina Global Screening Array (GSA). Data analysis of GSA was performed using Illumina GenomeStudio 2.0, Biodiscovery Nexus 10.0, and R-3.4.4 software. Validation of genotype calling was performed by comparing the GSA with whole-genome sequencing (WGS) data of 56 non-PID controls. DNA samples of 95 clinically diagnosed PID patients, of which 60 patients (63%) had a genetically established diagnosis (by Next-Generation Sequencing (NGS) PID panels or Sanger sequencing), were analyzed to test the performance of the GSA. The additional SNVs detected by GSA were validated by Sanger sequencing.Results: Genotype calling of the customized array had an accuracy rate of 99.7%. The sensitivity for detecting rare PID variants was high (87%). The single sample replication in two runs was high (94.9%). The customized GSA was able to generate a genetic diagnosis in 37 out of 95 patients (39%). These 37 patients included 29 patients in whom the genetic variants were confirmed by conventional methods (26 patients by SNV and 3 by CNV analysis), while in 8 patients a new genetic diagnosis was established (6 patients by SNV and 2 patients suspected for leukemia by CNV analysis). Twenty-eight patients could not be detected due to the limited coverage of the custom probes. However, the diagnostic yield can potentially be increased when newly updated variants are added.Conclusion: Our robust customized GSA seems to be a promising first-line rapid screening tool for PIDs at an affordable price, which opens opportunities for low-cost genetic testing in developing countries. The technique is scalable, allows numerous new genetic variants to be added, and offers the potential for genetic testing not only in PIDs, but also in many other genetic diseases. Show less
Radjabzadeh, D.; Boer, C.G.; Beth, S.A.; Wal, P. van der; Kiefte-De Jong, J.C.; Jansen, M.A.E.; ... ; Kraaij, R. 2020
The gut microbiota has been shown to play diverse roles in human health and disease although the underlying mechanisms have not yet been fully elucidated. Large cohort studies can provide further... Show moreThe gut microbiota has been shown to play diverse roles in human health and disease although the underlying mechanisms have not yet been fully elucidated. Large cohort studies can provide further understanding into inter-individual differences, with more precise characterization of the pathways by which the gut microbiota influences human physiology and disease processes. Here, we aimed to profile the stool microbiome of children and adults from two population-based cohort studies, comprising 2,111 children in the age-range of 9 to 12 years (the Generation R Study) and 1,427 adult individuals in the range of 46 to 88 years of age (the Rotterdam Study). For the two cohorts, 16S rRNA gene profile datasets derived from the Dutch population were generated. The comparison of the two cohorts showed that children had significantly lower gut microbiome diversity. Furthermore, we observed higher relative abundances of genus Bacteroides in children and higher relative abundances of genus Blautia in adults. Predicted functional metagenome analysis showed an overrepresentation of the glycan degradation pathways, riboflavin (vitamin B2), pyridoxine (vitamin B6) and folate (vitamin B9) biosynthesis pathways in children. In contrast, the gut microbiome of adults showed higher abundances of carbohydrate metabolism pathways, beta-lactam resistance, thiamine (vitamin B1) and pantothenic (vitamin B5) biosynthesis pathways. A predominance of catabolic pathways in children (valine, leucine and isoleucine degradation) as compared to biosynthetic pathways in adults (valine, leucine and isoleucine biosynthesis) suggests a functional microbiome switch to the latter in adult individuals. Overall, we identified compositional and functional differences in gut microbiome between children and adults in a population-based setting. These microbiome profiles can serve as reference for future studies on specific human disease susceptibility in childhood, adulthood and specific diseased populations. Show less
Rooij, J. van; Mandaviya, P.R.; Claringbould, A.; Felix, J.F.; Dongen, J. van; Jansen, R.; ... ; BIOS Consortium 2019
BackgroundA large number of analysis strategies are available for DNA methylation (DNAm) array and RNA-seq datasets, but it is unclear which strategies are best to use. We compare commonly used... Show moreBackgroundA large number of analysis strategies are available for DNA methylation (DNAm) array and RNA-seq datasets, but it is unclear which strategies are best to use. We compare commonly used strategies and report how they influence results in large cohort studies.ResultsWe tested the associations of DNAm and RNA expression with age, BMI, and smoking in four different cohorts (n =similar to 2900). By comparing strategies against the base model on the number and percentage of replicated CpGs for DNAm analyses or genes for RNA-seq analyses in a leave-one-out cohort replication approach, we find the choice of the normalization method and statistical test does not strongly influence the results for DNAm array data. However, adjusting for cell counts or hidden confounders substantially decreases the number of replicated CpGs for age and increases the number of replicated CpGs for BMI and smoking. For RNA-seq data, the choice of the normalization method, gene expression inclusion threshold, and statistical test does not strongly influence the results. Including five principal components or excluding correction of technical covariates or cell counts decreases the number of replicated genes.ConclusionsResults were not influenced by the normalization method or statistical test. However, the correction method for cell counts, technical covariates, principal components, and/or hidden confounders does influence the results. Show less
Inferring a person's smoking habit and history from blood is relevant for complementing or replacing self-reports in epidemiological and public health research, and for forensic applications.... Show moreInferring a person's smoking habit and history from blood is relevant for complementing or replacing self-reports in epidemiological and public health research, and for forensic applications. However, a finite DNA methylation marker set and a validated statistical model based on a large dataset are not yet available. Employing 14 epigenome-wide association studies for marker discovery, and using data from six population-based cohorts (N = 3764) for model building, we identified 13 CpGs most suitable for inferring smoking versus non-smoking status from blood with a cumulative Area Under the Curve (AUC) of 0.901. Internal fivefold cross-validation yielded an average AUC of 0.897 +/- 0.137, while external model validation in an independent population-based cohort (N = 1608) achieved an AUC of 0.911. These 13 CpGs also provided accurate inference of current (average AUC(crossvalidation) 0.925 +/- 0.021, AUC(externalvalidation)0.914), former (0.766 +/- 0.023, 0.699) and never smoking (0.830 +/- 0.019, 0.781) status, allowed inferring pack-years in current smokers (10 pack-years 0.800 +/- 0.068, 0.796; 15 pack-years 0.767 +/- 0.102, 0.752) and inferring smoking cessation time in former smokers (5 years 0.774 +/- 0.024, 0.760; 10 years 0.766 +/- 0.033, 0.764; 15 years 0.767 +/- 0.020, 0.754). Model application to children revealed highly accurate inference of the true non- smoking status (6 years of age: accuracy 0.994, N = 355; 10 years: 0.994, N = 309), suggesting prenatal and passive smoking exposure having no impact on model applications in adults. The finite set of DNA methylation markers allow accurate inference of smoking habit, with comparable accuracy as plasma cotinine use, and smoking history from blood, which we envision becoming useful in epidemiology and public health research, and in medical and forensic applications. Show less
Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential... Show moreDespite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D. Show less
Parmar, P.; Lowry, E.; Cugliari, G.; Suderman, M.; Wilson, R.; Karhunen, V.; ... ; GLOBAL Meth QTL 2018
