DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA(1c) levels:a systematic review and replication in a case-control sample of the Lifelines study

AIMS/HYPOTHESIS: Epigenetic mechanisms may play an important role in the aetiology of type 2 diabetes. Recent epigenome-wide association studies (EWASs) identified several DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels. Here we present a systematic review of these studies and attempt to replicate the CpG sites (CpGs) with the most significant associations from these EWASs in a case-control sample of the Lifelines study.METHODS: We performed a systematic literature search in PubMed and EMBASE for EWASs to test the association between DNA methylation and type 2 diabetes and/or glycaemic traits and reviewed the search results. For replication purposes we selected 100 unique CpGs identified in peripheral blood, pancreas, adipose tissue and liver from 15 EWASs, using study-specific Bonferroni-corrected significance thresholds. Methylation data (Illumina 450K array) in whole blood from 100 type 2 diabetic individuals and 100 control individuals from the Lifelines study were available. Multivariate linear models were used to examine the associations of the specific CpGs with type 2 diabetes and glycaemic traits.RESULTS: From the 52 CpGs identified in blood and selected for replication, 15 CpGs showed nominally significant associations with type 2 diabetes in the Lifelines sample (p &lt; 0.05). The results for five CpGs (in ABCG1, LOXL2, TXNIP, SLC1A5 and SREBF1) remained significant after a stringent multiple-testing correction (changes in methylation from -3% up to 3.6%, p &lt; 0.0009). All associations were directionally consistent with the original EWAS results. None of the selected CpGs from the tissue-specific EWASs were replicated in our methylation data from whole blood. We were also unable to replicate any of the CpGs associated with HbA1c levels in the healthy control individuals of our sample, while two CpGs (in ABCG1 and CCDC57) for fasting glucose were replicated at a nominal significance level (p &lt; 0.05).CONCLUSIONS/INTERPRETATION: A number of differentially methylated CpGs reported to be associated with type 2 diabetes in the EWAS literature were replicated in blood and show promise for clinical use as disease biomarkers. However, more prospective studies are needed to support the robustness of these findings.</p

Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression.

Recent developments in stem cell biology have enabled the study of cell fate decisions in early human development that are impossible to study in vivo. However, understanding how development varies across individuals and, in particular, the influence of common genetic variants during this process has not been characterised. Here, we exploit human iPS cell lines from 125 donors, a pooled experimental design, and single-cell RNA-sequencing to study population variation of endoderm differentiation. We identify molecular markers that are predictive of differentiation efficiency of individual lines, and utilise heterogeneity in the genetic background across individuals to map hundreds of expression quantitative trait loci that influence expression dynamically during differentiation and across cellular contexts

Intravascular Immune Surveillance by CXCR6(+) NKT Cells Patrolling Liver Sinusoids

We examined the in vivo behavior of liver natural killer T cells (NKT cells) by intravital fluorescence microscopic imaging of mice in which a green fluorescent protein cDNA was used to replace the gene encoding the chemokine receptor CXCR6. NKT cells, which account for most CXCR6(+) cells in liver, were found to crawl within hepatic sinusoids at 10–20 μm/min and to stop upon T cell antigen receptor activation. CXCR6-deficient mice exhibited a selective and severe reduction of CD1d-reactive NKT cells in the liver and decreased susceptibility to T-cell-dependent hepatitis. CXCL16, the cell surface ligand for CXCR6, is expressed on sinusoidal endothelial cells, and CXCR6 deficiency resulted in reduced survival, but not in altered speed or pattern of patrolling of NKT cells. Thus, NKT cells patrol liver sinusoids to provide intravascular immune surveillance, and CXCR6 contributes to liver-based immune responses by regulating their abundance

Single-cell Atlas of common variable immunodeficiency shows germinal center-associated epigenetic dysregulation in B-cell responses.

Common variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, displays impaired terminal B-cell differentiation and defective antibody responses. Incomplete genetic penetrance and ample phenotypic expressivity in CVID suggest the participation of additional pathogenic mechanisms. Monozygotic (MZ) twins discordant for CVID are uniquely valuable for studying the contribution of epigenetics to the disease. Here, we generate a single-cell epigenomics and transcriptomics census of naïve-to-memory B cell differentiation in a CVID-discordant MZ twin pair. Our analysis identifies DNA methylation, chromatin accessibility and transcriptional defects in memory B-cells mirroring defective cell-cell communication upon activation. These findings are validated in a cohort of CVID patients and healthy donors. Our findings provide a comprehensive multi-omics map of alterations in naïve-to-memory B-cell transition in CVID and indicate links between the epigenome and immune cell cross-talk. Our resource, publicly available at the Human Cell Atlas, gives insight into future diagnosis and treatments of CVID patients.We thank the CERCA Program/Generalitat de Catalunya and the Josep Carreras Foundation for institutional support. This publication is part of the Human Cell Atlas; www.humancellatlas.org/publications. This study was funded by: Spanish Ministry of Science and Innovation (grant number PID2020-117212RB-I00/AEI/10.13038/501100011033) (E.B.), Instituto de Salud Carlos III (ISCIII), Ref. AC18/00057, associated with i-PAD project (ERARE European Union program) (E.B.), the Jeffrey Modell Foundation (E.B.), Wellcome Sanger core funding (grant no. WT206194) (R.V.-T.), the Chan Zuckerberg Initiative (grant 2020-216799) (R.V.-T. and E.B.), an EMBO short-term fellowship (J.R.U.), Fondo de Investigación Sanitaria Instituto de Salud Carlos III (FIS PI16/01605) (L.P.-M.), the Spanish Ministry of Science, Innovation and Universities (SAF2017-89109-P; AEI/FEDER, UE) (H.H.), Instituto de Salud Carlos III, Ministry of Health (PI16/00759) and European Regional Development Fund-European Social Fund—FEDER-FSE) (C.R-G.), Grupo DISA (OA18/017) (C.R.-G.), the UK Biotechnology and Biological Sciences Research Council (BBS/E/B/000C0426) (G.K.) and Medical Research Council (MR/S000437/1) (G.K.). We are indebted to the donors for participating in this research. We thank Antonio Garcia-Gomez for graphical design support, Sarah Teichmann for her useful feedback, Hamish King for helping with single-cell germinal center dataset availability, Xi Chen for performing scATAC-seq analysis, Kirsty Ambridge and Elena Prigmore for their involvement in single-cell RNA library generation, Martin Prete for creating online visualizations for our cell atlas and Esther Castaño and Beatriz Barroso from CCiTUB Cytometry Unit for their support with single-cell sorting and Dr. Carla Gianelli and Dr. Rebeca Rodríguez Pena for the patient follow-up in the CVID cohort

Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2x)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted

Calling genotypes from public RNA-sequencing data enables identification of genetic variants that affect gene-expression levels

Background: RNA-sequencing (RNA-seq) is a powerful technique for the identification of genetic variants that affect gene-expression levels, either through expression quantitative trait locus (eQTL) mapping or through allele-specific expression (ASE) analysis. Given increasing numbers of RNA-seq samples in the public domain, we here studied to what extent eQTLs and ASE effects can be identified when using public RNA-seq data while deriving the genotypes from the RNA-sequencing reads themselves. Methods: We downloaded the raw reads for all available human RNA-seq datasets. Using these reads we performed gene expression quantification. All samples were jointly normalized and subjected to a strict quality control. We also derived genotypes using the RNA-seq reads and used imputation to infer non-coding variants. This allowed us to perform eQTL mapping and ASE analyses jointly on all samples that passed quality control. Our results were validated using samples for which DNA-seq genotypes were available. Results: 4,978 public human RNA-seq runs, representing many different tissues and cell-types, passed quality control. Even though these data originated from many different laboratories, samples reflecting the same cell type clustered together, suggesting that technical biases due to different sequencing protocols are limited. In a joint analysis on the 1,262 samples with high quality genotypes, we identified cis-eQTLs effects for 8,034 unique genes (at a false discovery rate Conclusions: By deriving and imputing genotypes from RNA-seq data, it is possible to identify both eQTLs and ASE effects. Given the exponential growth of the number of publicly available RNA-seq samples, we expect this approach will become especially relevant for studying the effects of tissue-specific and rare pathogenic genetic variants to aid clinical interpretation of exome and genome sequencing

Analysis of 1135 gut metagenomes identifies sex-specific resistome profiles

Published with license by Taylor & Francis Group, LLC. Several gastrointestinal diseases show a sex imbalance, although the underlying (patho)physiological mechanisms behind this are not well understood. The gut microbiome may be involved in this process, forming a complex interaction with host immune system, sex hormones, medication and other environmental factors. Here we performed sex-specific analyses of fecal microbiota composition in 1135 individuals from a population-based cohort. The overall gut microbiome composition of females and males was significantly different (p = 0.001), with females showing a greater microbial diversity (p = 0.009). After correcting for the effects of intrinsic factors, smoking, diet and medications, female hormonal factors such as the use of oral contraceptives and undergoing an ovariectomy were associated with microbial species and pathways. Females had a higher richness of antibiotic-resistance genes, with the most notable being resistance to the lincosamide nucleotidyltransferase (LNU) gene family. The higher abundance of resistance genes is consistent with the greater prescription of the Macrolide-Lincosamide-Streptogramin classes of antibiotics to females. Furthermore, we observed an increased resistance to aminoglycosides in females with self-reported irritable bowel syndrome. These results throw light upon the effects of common medications that are differentially prescribed between sexes and highlight the importance of sex-specific analysis when studying the gut microbiome and resistome

Publisher Correction: Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression.

An amendment to this paper has been published and can be accessed via a link at the top of the paper