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Objectives Systemic Lupus Erythematosus is a complex autoimmune disease that leads to significant worsening of quality of life and mortality. Flares appear unpredictably during the disease course and therapies used are often only partially effective. These challenges are mainly due to the molecular heterogeneity of the disease, and in this context, personalized medicine-based approaches offer major promise. With this work we intended to advance in that direction by developing MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions. Methods Immunological gene-modules were used to represent the transcriptome of the patients. A dysregulation score for each gene-module was calculated at the patient level based on averaged z-scores. Almost 6100 Lupus and 750 healthy samples were used to analyze the association among dysregulation scores, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. Machine learning-based classification models were built to predict around 100 different clinical parameters based on personalized dysregulation scores. Results MyPROSLE allows to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. The combination of these modules revealed highly differentiated pathological mechanisms. We found that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Therefore, MyPROSLE may be used to accurately predict these clinical outcomes. Conclusions MyPROSLE (https://myprosle.genyo.es) allows molecular characterization of individual Lupus patients and it extracts key molecular information to support more precise therapeutic decisions., PID2020-119032RB-I00 supported by MCIN/AEI/10.13039/501100011033, FEDER and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 831434 (3TR), European Union’s Horizon 2020, EFPIA, FEDER/Junta de Andalucía-Consejer’a de Transformación Económica, Industria, Conocimiento y Universidades (grants P20_00335 and B-CTS-40-UGR20), ‘Consejería de Transformación Económica, Industria, Conocimiento y Universidades’ (CTEICU), European Union through the European Social Fund (ESF) named ‘Andalucía se mueve con Europa”, Andalusian ESF Operational Program 2014–2020, ISCIII CD18/00149, Ministerio de Universidades (Spain’s Government) and the European Union – NextGenerationEU

Objectives: We aimed at investigating the whole-blood transcriptome, expression quantitative trait loci (eQTLs), and levels of selected serological markers in patients with SLE versus healthy controls (HC) to gain insight into pathogenesis and identify drug targets. Methods: We analyzed differentially expressed genes (DEGs) and dysregulated gene modules in a cohort of 350 SLE patients and 497 HC from the European PRECISESADS project (NTC02890121), split into a discovery (60%) and a replication (40%) set. Replicated DEGs qualified for eQTL, pathway enrichment, regulatory network, and druggability analysis. For validation purposes, a separate gene module analysis was performed in an independent cohort (GSE88887). Results: Analysis of 521 replicated DEGs identified multiple enriched interferon signaling pathways through Reactome. Gene module analysis yielded 18 replicated gene modules in SLE patients, including 11 gene modules that were validated in GSE88887. Three distinct gene module clusters were defined i.e., “interferon/plasma cells”, “inflammation”, and “lymphocyte signaling”. Predominant downregulation of the lymphocyte signaling cluster denoted renal activity. By contrast, upregulation of interferon-related genes indicated hematological activity and vasculitis. Druggability analysis revealed several potential drugs interfering with dysregulated genes within the “interferon” and “PLK1 signaling events” modules. STAT1 was identified as the chief regulator in the most enriched signaling molecule network. Drugs annotated to 15 DEGs associated with cis-eQTLs included bortezomib for its ability to modulate CTSL activity. Belimumab was annotated to TNFSF13B (BAFF) and daratumumab was annotated to CD38 among the remaining replicated DEGs. Conclusions: Modulation of interferon, STAT1, PLK1, B and plasma cell signatures showed promise as viable approaches to treat SLE, pointing to their importance in SLE pathogenesis., The Swedish Rheumatism Association (R-941095), King Gustaf V’s 80-year Foundation (FAI-2020-0741), Swedish Society of Medicine (SLS-974449), Nyckelfonden (OLL-974804), Ulla and Roland Gustafsson Foundation (2021–26), Region Stockholm (FoUI-955483), Karolinska Institutet, Innovative Medicines Initiative (IMI) Joint Undertaking (JU) for the PRECISESADS project (grant number 115565), IMI 2 JU for the 3 TR project (grant number 831434), EU Horizon 2020

SARS-CoV-2 causes a severe inflammatory syndrome (COVID-19) leading, in many cases, to bilateral pneumonia, severe dyspnea and in ∼5% of these, death. DNA methylation is known to play an important role in the regulation of the immune processes behind COVID-19 progression, however it has not been studied in depth, yet. In this study, we aim to evaluate the implication of DNA methylation in COVID-19 progression by means of a genome-wide DNA methylation analysis combined with DNA genotyping. The results reveal the existence of epigenomic regulation of functional pathways associated with COVID-19 progression and mediated by genetic loci. We found an environmental trait-related signature that discriminates mild from severe cases, and regulates IL-6 expression via the transcription factor CEBP. The analyses suggest that an interaction between environmental contribution, genetics and epigenetics might be playing a role in triggering the cytokine storm described in the most severe cases., This work has been supported through Consejería de Transformación Económica, Industria, Conocimiento y Universidades of the regional government of Andalucía cofounded by the European Union through European Regional Development Fund (FEDER, CV20-10150), Consejo Superior de Investigaciones científicas (CSIC-COV19-016/202020E155) and Junta de Castilla y León (Proyectos COVID 07.04.467B04.74011.0 and IBGM excellence programme CLU-2029-02). G.B. is supported by the Instituto de Salud Carlos III (ISCIII, Spanish Health Ministry) through the Sara Borrell subprogram (CD18/00153).

SARS-CoV-2 infection can cause an inflammatory syndrome (COVID-19) leading, in many cases, to bilateral pneumonia, severe dyspnea, and in ~5% of these, death. DNAmethylation is known to play an important role in the regulation of the immune processes behind COVID-19 progression, however it has not been studied in depth. In this study, we aim to evaluate the implication of DNA methylation in COVID-19 progression by means of a genome-wide DNA methylation analysis combined with DNA genotyping. The results reveal the existence of epigenomic regulation of functional pathways associated with COVID-19 progression andmediated by genetic loci.We find an environmental trait-related signature that discriminatesmild from severe cases and regulates, among other cytokines, IL-6 expression via the transcription factor CEBP. The analyses suggest that an interaction between environmental contribution, genetics, and epigenetics might be playing a role in triggering the cytokine storm described in the most severe cases., Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades of the regional government of Andalucia, European Union through European Regional Development Fund CV20-10150, Consejo Superior de Investigaciones cientificas CSIC-COV19-016/202020E155, Junta de Castilla y Leon COVID 07.04.467B04.74011.0, Consejeria de Salud y Familias of the regional government of Andalucia PECOVID-0072-2020, Instituto de Salud Carlos III (ISCIII, Spanish Health Ministry) through the Sara Borrell subprogram CD18/00153, Programa Estrategico Instituto de Biologia y Genetica Molecular, IBGM excellence programme CLU-2029-02 CCVC8485

Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups., Abnormal blood lipid levels are important risk factors for cardiovascular and other various diseases. Here the authors conduct a large-scale multi-ethnic epigenome-wide association study combined with epigenetic (cis-QTL and eQTM) data, and identify CpG-lipid traits associations that are specific to or common across racial/ethnic groups.

OBJECTIVE: Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis. METHODS: Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time. RESULTS: Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient. CONCLUSION: Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases. ispartof: ARTHRITIS & RHEUMATOLOGY vol:73 issue:6 pages:1073-1085 ispartof: location:United States status: published

Primary Sjögren’s syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study we identified vast coordinated hypomethylation and overexpression effects, that also exhibit increased variability, in many already known IFN-regulated genes. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of novel genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified new genetic variants associated with SS that mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, DNA methylation, gene expression and SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population.

The interaction between genes and environment has a strong influence on gene regulation and the ultimate expression of our genes and proteins. The pathways through which these interactions occur require the activation of mechanisms that open or close chromatin, activate or deactivate promoters and enhancers, and suppress or promote the expression of genes. We describe those mechanisms and how we can make use of them to understand the pathogenesis of lupus; however, we take it a step further. Lupus heterogeneity is the result of gene–environment interaction, and there is no better way of understanding that heterogeneity than through the use of epigenetics and gene expression to define molecular differences between patients. Therefore we include a section that discusses studies aimed at stratifying lupus molecularly. Most of these studies have dealt with gene expression, but lately the integration of methylation and gene expression data has begun to shed light on the differences between patients with important clinical implications.

DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs. Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. Here we describe results of DNA methylation-quantitative trait loci (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTL of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We reveal that the genetic architecture of DNAm levels is highly polygenic and DNAm exhibits signatures of negative and positive natural selection. Using shared genetic control between distal DNAm sites we construct networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic factors are associated with both blood DNAm levels and complex diseases but in most cases these associations do not reflect causal relationships from DNAm to trait or vice versa indicating a more complex genotype-phenotype map than has previously been hypothesised.

Background Clinical heterogeneity, a hallmark of systemic autoimmune diseases (SADs) impedes early diagnosis and effective treatment, issues that may be addressed if patients could be grouped into a molecular defined stratification. Methods With the aim of reclassifying SADs independently of the clinical diagnoses, unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data of 918 patients with 7 SADs and 263 healthy controls was undertaken. An inception cohort prospectively followed for 6 and 14 months was studied to validate the results in early cases and analyze if cluster assignment was modified with time. Results Four clusters were identified Three aberrant clusters were ‘acute phase inflammatory’, ‘T cell immunity’, and ‘interferon’, each including all diagnoses, were defined by genetic, clinical, serological and cellular features. A fourth cluster showed no specific molecular pattern, to which 74% of healthy controls clustered with patients. The inception cohort showed that most patients were either assigned always to the same cluster or moved from the healthy-like cluster to a single aberrant cluster resembling the relapsing-remitting dynamic of these diseases, showing that single aberrant molecular signatures characterize each individual patient. Conclusions Patients with SADs share molecular signatures and can be therefore stratified into three disease clusters differentiating each patient into a specific molecular disease pathway. Such assignment is stable with time. These results have important implications for understanding disease progression and therapy design marking a paradigm shift in our view of SADs. Acknowledgment This work has been supported through a grant from the Innovative Medicines Initiative Joint Undertaking No. 115565 and in-kind and in-cash contributions from the EFPIA partners. G.B. is supported by the Instituto de Salud Carlos III (ISCIII, Spanish Health Ministry), through the Sara Borrell subprogram (CD18/00153). The authors would like to particularly express their gratitude to the patients, nurses and many others who helped directly or indirectly in the consecution of this study.

SUMMARYBackgroundClinical heterogeneity, a hallmark of systemic autoimmune diseases (SADs) impedes early diagnosis and effective treatment, issues that may be addressed if patients could be grouped into a molecular defined stratification.MethodsWith the aim of reclassifying SADs independently of the clinical diagnoses, unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data of 918 patients with 7 SADs and 263 healthy controls was undertaken. In addition, an inception cohort was prospectively followed for 6 and 14 months to validate the results and analyze if cluster assignment changed or not with time.ResultsFour clusters were identified. Three clusters were aberrant, representing ‘inflammatory’, ‘lymphoid’, and ‘interferon’ patterns each including all diagnoses and defined by genetic, clinical, serological and cellular features. A fourth cluster showed no specific molecular pattern and accumulated also healthy controls. An independent inception cohort showed that with time, the molecular clusters remain stable, showing that single aberrant molecular signatures characterize each individual patient.ConclusionsPatients with SADs can be jointly stratified into three stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of therapy non-responsiveness marking a paradigm shift in the view of SADs.

Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups.

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 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., Our understanding of the functional link between differential DNA methylation and type 2 diabetes and obesity remains limited. Here the authors present a blood-based EWAS of fasting glucose and insulin among 4808 non-diabetic Europeans and identify nine CpGs not previously implicated in glucose, insulin homeostasis and diabetes.

Background: Single variant approaches have been successful in identifying DNA methylation quantitative trait loci (mQTL), although as with complex traits they lack statistical power to identify effects from rare genetic variants. We have undertaken extensive analyses to identify regions of low frequency and rare variants that are associated with DNA methylation levels.Methods: We used repeated measurements of DNA methylation from five different life stages in human blood, taken from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Variants were collapsed across CpG islands and their flanking regions to identify variants collectively associated with methylation, where no single variant was individually responsible for the observed signal. All analyses were undertaken using the sequence kernel association test.Results: For loci where no individual variant mQTL was observed based on a single variant analysis, we identified 95 unique regions where the combined effect of low frequency variants (MAF≤5%) provided strong evidence of association with methylation. For loci where there was previous evidence of an individual variant mQTL, a further 3 regions provided evidence of association between multiple low frequency variants and methylation levels. Effects were observed consistently across 5 different time points in the lifecourse and evidence of replication in the TwinsUK and Exeter cohorts was also identified.Conclusion: We have demonstrated the potential of this novel approach to mQTL analysis by analysing the combined effect of multiple low frequency or rare variants. Future studies should benefit from applying this approach as a complementary follow up to single variant analyses.

Chronic obstructive pulmonary disease (COPD) is a major health burden in adults and cigarette smoking is considered the most important environmental risk factor of COPD. Chromosome 15q25.1 locus is associated with both COPD and smoking. Our study aims at understanding the mechanism underlying the association of chromosome 15q25.1 with COPD through epigenetic and transcriptional variation in a population-based setting. To assess if COPD-associated variants in 15q25.1 are methylation quantitative trait loci, epigenome-wide association analysis of four genetic variants, previously associated with COPD (P < 5 × 10-8) in the 15q25.1 locus (rs12914385:C>T-CHRNA3, rs8034191:T>C-HYKK, rs13180:C>T-IREB2 and rs8042238:C>T-IREB2), was performed in the Rotterdam study (n = 1489). All four variants were significantly associated (P < 1.4 × 10-6) with blood DNA methylation of IREB2, CHRNA3 and PSMA4, of which two, including IREB2 and PSMA4, were also differentially methylated in COPD cases and controls (P < 0.04). Further additive and multiplicative effects of smoking were evaluated and no significant effect was observed. To evaluate if these four genetic variants are expression quantitative trait loci, transcriptome-wide association analysis was performed in 1087 lung samples. All four variants were also significantly associated with differential expression of the IREB2 3'UTR in lung tissues (P < 5.4 × 10-95). We conclude that regulatory mechanisms affecting the expression of IREB2 gene, such as DNA methylation, may explain the association between genetic variants in chromosome 15q25.1 and COPD, largely independent of smoking.

Epigenetics is known to be an important mechanism in the pathogenesis of autoimmune diseases. Epigenetic variations can act as integrators of environmental and genetic exposures and propagate activated states in immune cells. Studying epigenetic alterations by means of genome-wide approaches promises to unravel novel molecular mechanisms related to disease etiology, disease progression, clinical manifestations and treatment responses. This paper reviews what we have learned in the last five years from epigenome-wide studies for three systemic autoimmune diseases, namely systemic lupus erythematosus, primary Sjogren's syndrome, and rheumatoid arthritis. We examine the degree of epigenetic sharing between different diseases and the possible mediating role of epigenetic associations in genetic and environmental risks. Finally, we also shed light into the use of epigenetic markers towards a better precision medicine regarding disease prediction, prevention and personalized treatment in systemic autoimmunity.

Santpere, Gabriel et al., We set out to investigate potential differences and similarities between the selective forces acting upon the coding and noncoding regions of five different sets of genes defined according to functional and evolutionary criteria: 1) two reference gene sets presenting accelerated and slow rates of protein evolution (the Complement and Actin pathways); 2) a set of genes with evidence of accelerated evolution in at least one of their introns; and 3) two gene sets related to neurological function (Parkinson’s and Alzheimer’s diseases). To that effect, we combine human–chimpanzee divergence patterns with polymorphism data obtained from target resequencing 20 central chimpanzees, our closest relatives with largest long-term effective population size. By using the distribution of fitness effect-alpha extension of the McDonald–Kreitman test, we reproduce inferences of rates of evolution previously based only on divergence data on both coding and intronic sequences and also obtain inferences for other classes of genomic elements (untranslated regions, promoters, and conserved noncoding sequences). Our results suggest that 1) the distribution of fitness effect-alpha method successfully helps distinguishing different scenarios of accelerated divergence (adaptation or relaxed selective constraints) and 2) the adaptive history of coding and noncoding sequences within the gene sets analyzed is decoupled., This work was supported by Ministerio de Ciencia e Innovación, Spain (SAF2011-29239 to E.B. and BFU2012-38236 to A.N.), Direcció General de Recerca, Generalitat de Catalunya (2014SGR1311 and 2014SGR866), the Spanish National Institute of Bioinfomatics of the Instituto de Salud Carlos III (PT13/0001/0026), and FEDER (Fondo Europeo de Desarrollo Regional)/FSE (Fondo Social Europeo).

Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are important biomarkers for disease development and progression. To gain insight into the genetic causes of variance in NLR and PLR in the general population, we conducted genome-wide association (GWA) analyses and estimated SNP heritability in a sample of 5901 related healthy Dutch individuals. GWA analyses identified a new genome-wide significant locus on the HBS1L-MYB intergenic region for PLR, which replicated in a sample of 2538 British twins. For platelet count, we replicated three known genome-wide significant loci in our cohort (at CCDC71L-PIK3CG, BAK1 and ARHGEF3). For neutrophil count, we replicated the PSMD3 locus. For the identified top SNPs, we found significant cis and trans expression quantitative trait loci effects for several loci involved in hematological and immunological pathways. Linkage Disequilibrium score (LD) regression analyses for PLR and NLR confirmed that both traits are heritable, with a polygenetic SNP heritability for PLR of 14.1%, and for NLR of 2.4%. Genetic correlations were present between ratios and the constituent counts, with the genetic correlation (r=0.45) of PLR with platelet count reaching statistical significance. In conclusion, we established that two important biomarkers have a significant heritable SNP component, and identified the first genome-wide locus for PLR.

© The Author 2017. Chronic obstructive pulmonary disease (COPD) is among the major health burdens in adults. While cigarette smoking is the leading risk factor, a growing number of genetic variations have been discovered to influence disease susceptibility. Epigenetic modifications may mediate the response of the genome to smoking and regulate gene expression. Chromosome 19q13.2 region is associated with both smoking and COPD, yet its functional role is unclear. Our study aimed to determine whether rs7937 (RAB4B, EGLN2), a top genetic variant in 19q13.2 region identified in genome-wide association studies of COPD, is associated with differential DNA methylation in blood (N=1490) and gene expression in blood (N=721) and lungs (N=1087). We combined genetic and epigenetic data from the Rotterdam Study (RS) to perform the epigenome-wide association analysis of rs7937. Further, we used genetic and transcriptomic data from blood (RS) and from lung tissue (Lung expression quantitative trait loci mapping study), to perform the transcriptome-wide association study of rs7937. Rs7937 was significantly (FDR < 0.05) and consistently associated with differential DNA methylation in blood at 4 CpG sites in cis, independent of smoking. One methylation site (cg11298343-EGLN2) was also associated with COPD (P=0.001). Additionally, rs7937 was associated with gene expression levels in blood in cis (EGLN2), 42% mediated through cg11298343, and in lung tissue, in cis and trans (NUMBL, EGLN2, DNMT3A, LOC101929709 and PAK2). Our results suggest that changes of DNA methylation and gene expression may be intermediate steps between genetic variants and COPD, but further causal studies in lung tissue should confirm this hypothesis.

Monozygotic (MZ) twins share the same STR profile, demonstrating a practical problem in forensic casework. DNA methylation has provided a suitable resource for MZ twin differentiation; however, studies addressing the forensic feasibility are lacking. Here, we investigated epigenetic MZ twin differentiation from blood under the forensic scenario comprising i) the discovery of candidate markers in reference-type blood DNA via genome-wide analysis, ii) the technical validation of candidate markers in reference-type blood DNA using a suitable targeted method, and iii) the analysis of the validated markers in trace-type DNA. Genome-wide methylation analysis in blood DNA from 10 MZ twin pairs resulted in 19 to 111 twin-differentially methylated sites (tDMSs) per pair with >0.3 twin-to-twin differences. Considering all top three candidate tDMSs across all pairs in the technical validation based on methylation-specific qPCR, 67.85% generated >0.1 twin-to-twin differences. Of the validated tDMSs, 68.4% showed >0.1 twin-to-twin differences with qPCR in trace-type DNA across 8 pairs. Using an updated marker selection strategy, 8 additional candidate tDMSs were obtained for an example MZ pair, of which 7 showed >0.1 twin-to-twin differences in both reference- and trace-type DNA. Lastly, we introduce a high-resolution melting curve analysis of the entire fragment that can complement the proposed approach. Overall, our study demonstrates the general feasibility of epigenetic twin differentiation in the forensic context and highlights that the number of informative tDMSs in the final trace DNA analysis is crucial, as some candidate markers identified in reference DNA were shown not informative in the trace DNA due to various, including technical, reasons. Future studies will need to address the optimal number of epigenetic markers required for reliable identification of MZ twin individuals including statistical considerations.

The work is supported by grants from Worldwide Cancer Research (14-1275), Fundació La Marató TV3 (201319-30), Spanish Ministerio de Economía y Competitividad (Plan Nacional I+D+i, SAF2013-46151-R; and International Cancer Genome Consortium for Chronic Lymphocytic Leukemia) co-financed by European Development Regional Fund “A way to achieve Europe” ERDF, through Instituto de Salud Carlos III (ISCIII); and Red Temática de Investigación del Cáncer (RTIC).

Epigenetics describes the study of cellular modifications that can modify the expression of genes without changing the DNA sequence. DNA methylation is one of the most stable and prevalent epigenetic mechanisms. Twin studies have been a valuable model for unraveling the genetic and epigenetic epidemiology of complex traits, and now offer a potential to dissect the factors that impact DNA methylation variability and its biomedical significance. The twin design specifically allows for the study of genetic, environmental and lifestyle factors, and their potential interactions, on epigenetic profiles. Furthermore, genetically identical twins offer a unique opportunity to assess nongenetic impacts on epigenetic profiles. Here, we summarize recent findings from twin studies of DNA methylation profiles across tissues, to define current knowledge regarding the genetic and nongenetic factors that influence epigenetic variation.

Monozygotic (MZ) twins are typically indistinguishable via forensic DNA profiling. Recently, we demonstrated that epigenetic differentiation of MZ twins is feasible; however, proportions of twin differentially methylated CpG sites (tDMSs) identified in reference-type blood DNA were not replicated in trace-type blood DNA. Here we investigated buccal swabs as typical forensic reference material, and saliva and cigarette butts as commonly encountered forensic trace materials. As an analog to a forensic case, we analyzed one MZ twin pair. Epigenome-wide microarray analysis in reference-type buccal DNA revealed 25 candidate tDMSs with >0.5 twin-to-twin differences. MethyLight quantitative PCR (qPCR) of 22 selected tDMSs in trace-type DNA revealed in saliva DNA that six tDMSs (27.3%) had >0.1 twin-to-twin differences, seven (31.8%) had smaller (

Engelken, Johannes et al., Extreme differences in allele frequency between West Africans and Eurasians were observed for a leucine-to-valine substitution (Leu372Val) in the human intestinal zinc uptake transporter, ZIP4, yet no further evidence was found for a selective sweep around the ZIP4 gene (SLC39A4). By interrogating allele frequencies in more than 100 diverse human populations and resequencing Neanderthal DNA, we confirmed the ancestral state of this locus and found a strong geographical gradient for the derived allele (Val372), with near fixation in West Africa. In extensive coalescent simulations, we show that the extreme differences in allele frequency, yet absence of a classical sweep signature, can be explained by the effect of a local recombination hotspot, together with directional selection favoring the Val372 allele in Sub-Saharan Africans. The possible functional effect of the Leu372Val substitution, together with two pathological mutations at the same codon (Leu372Pro and Leu372Arg) that cause acrodermatitis enteropathica (a disease phenotype characterized by extreme zinc deficiency), was investigated by transient overexpression of human ZIP4 protein in HeLa cells. Both acrodermatitis mutations cause absence of the ZIP4 transporter cell surface expression and nearly absent zinc uptake, while the Val372 variant displayed significantly reduced surface protein expression, reduced basal levels of intracellular zinc, and reduced zinc uptake in comparison with the Leu372 variant. We speculate that reduced zinc uptake by the ZIP4-derived Val372 isoform may act by starving certain pathogens of zinc, and hence may have been advantageous in Sub-Saharan Africa. Moreover, these functional results may indicate differences in zinc homeostasis among modern human populations with possible relevance for disease risk. © 2014 Engelken et al.

Cénit, M.C. et al., CD5 plays a crucial role in autoimmunity and is a well-established genetic risk factor of developing RA. Recently, evidence of positive selection has been provided for the CD5 Pro224-Val471 haplotype in East Asian populations. The aim of the present work was to further analyze the functional relevance of non-synonymous CD5 polymorphisms conforming the ancestral and the newly derived haplotypes (Pro224-Ala471 and Pro224-Val471, respectively) as well as to investigate the potential role of CD5 on the development of SLE and/or SLE nephritis, This work was supported by grants from the Spanish Ministerio de Economía y Competitividad [SAF2010-19717 to FL, SAF2009-11110 to JM, SAF2011-29239, and BFU2008-01046 to EB], Generalitat de Catalunya [2009SGR00252 to FL, and 2009SGR1101 to EB], Junta de Andalucía [CTS-4977], and Instituto de Salud Carlos III and Fondo Europeo de Desarrollo Regional/FEDER [RD12/0009/0004 to JM].

CD5 is a lymphocyte surface coreceptor of still incompletely understood function. Currently available information indicates that CD5 participates not only in cell-to-cell immune interactions through still poorly defined endogenous ligands expressed on hemopoietic and nonhemopoietic cells but also in recognition of exogenous and highly conserved microbial structures such as fungal β-glucans. Preceding single nucleotide polymorphism (SNP) data analysis provided evidence for a recent selective sweep in East Asia and suggested a nonsynonymous substitution at position 471 (A471V; rs2229177) of the cytoplasmatic region of the CD5 receptor as the most plausible target of selection. The present report further investigates the role of natural selection in the CD5 gene by a resequencing approach in 60 individuals representing populations from 3 different continents (20 Africans, 20 Europeans and 20 East Asians) and by functionally assaying the relevance of the A471V replacement on CD5 signaling. The high differentiation pattern found at the nonsynonymous A471V site together with the low diversity, most of the performed neutrality tests (Tajima's D, Fu and Li's F* and D*, and Fu's Fs) and the predominance of a major haplotype in East Asians strongly argue in favor of positive selection for the A471V site. Importantly, anti-CD5 monoclonal antibody cross-linking unveiled significant differences among A471V variants regarding the mitogen-activated protein kinase (MAPK) cascade activation on COS7 and on human peripheral blood mononuclear cells. Similar differences on MAPK activation and IL-8 cytokine release were also observed upon exposure of HEK293 cell transfectants expressing the A471V variants to Zymosan, a β-glucan-rich fungal particle. Taken together, the results provide evidence for the hypothesis of an adaptive role of the A471V substitution to environmental challenges, most likely infectious pathogens, in East Asian populations. © The Author 2011. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved., This research was supported by grants from the Spanish Ministerio de Ciencia e Innovación (BFU2008-01046/BMC to E.B. and SAF2007-62197 and SAF2010-19717 to F.L.); Generalitat de Catalunya (2009SGR1101); Spanish National Institute for Bioinformatics ( www.inb.org ); Fundación de Investigación y Pre- vención del SIDA en España (FIPSE 36-0773-09 to F.L.); Instituto de Salud Carlos III (Red Española de Investigación en Patología Infecciosa, RD06/0008/1013 to F.L.); Volkswagenstiftung Scholarship (I/85 198 to J.E.).

1 página.-- Póster presentado en el 5º European Workshop on Immune-Mediated Inflammatory Diseases celebrado en Sitges (Barcelona) del 1 al 3 de Diciembre de 2010.

BACKGROUND: Glycosylation is one of the most common post-translation modifications with large influences on protein structure and function. The effector function of immunoglobulin G (IgG) alters between pro- and anti-inflammatory, based on its glycosylation. IgG glycan synthesis is highly complex and dynamic.METHODS: With the use of two different analytical methods for assessing IgG glycosylation, we aim to elucidate the link between DNA methylation and glycosylation of IgG by means of epigenome-wide association studies. In total, 3000 individuals from 4 cohorts were analyzed.RESULTS: The overlap of the results from the two glycan measurement panels yielded DNA methylation of 7 CpG-sites on 5 genomic locations to be associated with IgG glycosylation: cg25189904 (chr.1, GNG12); cg05951221, cg21566642 and cg01940273 (chr.2, ALPPL2); cg05575921 (chr.5, AHRR); cg06126421 (6p21.33); and cg03636183 (chr.19, F2RL3). Mediation analyses with respect to smoking revealed that the effect of smoking on IgG glycosylation may be at least partially mediated via DNA methylation levels at these 7 CpG-sites.CONCLUSION: Our results suggest the presence of an indirect link between DNA methylation and IgG glycosylation that may in part capture environmental exposures.GENERAL SIGNIFICANCE: An epigenome-wide analysis conducted in four population-based cohorts revealed an association between DNA methylation and IgG glycosylation patterns. Presumably, DNA methylation mediates the effect of smoking on IgG glycosylation.

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of the functional relevance of the phenomenon remains limited. Because obesity is the main risk factor for T2D and a driver of methylation from previous study, we aimed to explore the effect of DNA methylation in the early phases of T2D pathology while accounting for body mass index (BMI). We performed a blood-based epigenome-wide association study (EWAS) of fasting glucose and insulin among 4,808 non-diabetic European individuals and replicated the findings in an independent sample consisting of 11,750 non-diabetic subjects. We integrated blood-based in silico cross-omics databases comprising genomics, epigenomics and transcriptomics collected by BIOS project of the Biobanking and BioMolecular resources Research Infrastructure of the Netherlands (BBMRI-NL), the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium, and the tissue-specific Genotype-Tissue Expression (GTEx) project. We identified and replicated nine novel differentially methylated sites in whole blood (P-value < 1.27 × 10-7): sites in LETM1, RBM20, IRS2, MAN2A2 genes and 1q25.3 region were associated with fasting insulin; sites in FCRL6, SLAMF1, APOBEC3H genes and 15q26.1 region were associated with fasting glucose. The association between SLAMF1, APOBEC3H and 15q26.1 methylation sites and glucose emerged only when accounted for BMI. Follow-up in silico cross-omics analyses indicate that the cis-acting meQTLs near SLAMF1 and SLAMF1 expression are involved in glucose level regulation. Moreover, our data suggest that differential methylation in FCRL6 may affect glucose level and the risk of T2D by regulating FCLR6 expression in the liver. In conclusion, the present study provided nine new DNA methylation sites associated with glycemia homeostasis and also provided new insights of glycemia related loci into the genetics, epigenetics and transcriptomics pathways based on the integration of cross-omics data in silico.