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Age is among the main risk factors for cancer and any cancer study in adults is faced with an aging tissue and organism. Yet, pre-clinical studies are carried out using young mice and are not able address the impact of aging and associated comorbidities on disease biology and treatment outcomes. Here, we discuss the limitations of current mouse cancer models and suggest strategies for developing novel models to address these major gaps in knowledge and experimental approaches.

Pneumococcal infections cause serious illness and death among older adults. A capsular polysaccharide vaccine PPSV23 (Pneumovax®) and a conjugated polysaccharide vaccine PCV13 (Prevnar®) are used to prevent these infections, yet underlying responses, and baseline predictors remain unknown. We recruited and vaccinated 39 older adults (>60 years) with PPSV23 or PCV13. Both vaccines induced strong antibody responses at day 28 and similar plasmablast transcriptional signatures at day 10, however, their baseline predictors were distinct. Analyses of baseline flow cytometry and RNA-seq data (bulk and single cell) revealed a novel baseline phenotype that is specifically associated with weaker PCV13 responses, characterized by i) increased expression of cytotoxicity-associated genes and increased CD16+NK frequency; ii) increased Th17 and decreased Th1 cell frequency. Men were more likely to display this cytotoxic phenotype and mounted weaker responses to PCV13 than women. Baseline expression levels of a distinct gene set was predictive of PPSV23 responses. This first precision vaccinology study for pneumococcal vaccine responses of older adults uncovered novel and distinct baseline predictors that might transform vaccination strategies and initiate novel interventions.

Diverse mouse strains have different health and life spans, mimicking the diversity among humans. To capture conserved aging signatures, we studied long-lived C57BL/6J and short-lived NZO/HILtJ mouse strains by profiling transcriptomes and epigenomes of immune cells from peripheral blood and the spleen from young and old mice. Transcriptional activation of the AP-1 transcription factor complex, particularly Fos, Junb, and Jun genes, was the most significant and conserved aging signature across tissues and strains. ATAC-seq data analyses showed that the chromatin around these genes was more accessible with age and there were significantly more binding sites for these TFs with age across all studied tissues, targeting pro-inflammatory molecules including Il6. Age-related increases in binding sites of Jun/Fos factors were also conserved in human peripheral blood ATAC-seq data. Single-cell RNA-seq data from the mouse aging cell atlas Tabula Muris Senis showed that the expression of these genes increased with age in B, T, NK cells, and macrophages, with macrophages from old mice expressing these molecules more abundantly than other cells. Functional data showed that upon myeloid cell activation via poly(I:C), the levels of c-JUN protein and its binding activity increased more significantly in spleen cells from old mice compared to cells from young mice. In addition, upon activation, old cells produced more IL6 compared to young cells. In sum, we showed that the aging-related transcriptional activation of Jun/Fos members of the AP-1 complex is conserved across immune tissues and long- and short-living mouse strains, possibly contributing to increased inflammation with age.

Differences in immune function and responses contribute to health- and life-span disparities between sexes. However, the role of sex in immune system aging is not well understood. Here, we characterize peripheral blood mononuclear cells from 172 healthy adults 22–93 years of age using ATAC-seq, RNA-seq and flow cytometry. These data reveal a shared epigenomic signature of aging including declining naïve T cells and increasing monocyte and cytotoxic cell functions. These changes are greater in magnitude in men and accompanied by a male-specific decline in B-cell-specific loci. Interestingly, genomic differences between sexes increase after age 65, with men having higher innate and pro-inflammatory activity and lower adaptive activity. In a separate cohort (n=39) we studied how older adults respond to two available pneumococcal vaccines: T-dependent Prevnar and T-independent Pneumovax. How older adults respond to these vaccines at the molecular and cellular level, and whether there are pre-vaccination predictors for vaccine responsiveness, is poorly understood. To address this, we characterized serum antibody responses and peripheral blood leukocyte composition using flow cytometry and transcriptional profiles using RNA-seq, in healthy older adults before and after vaccination. The vaccines induced comparable serological responses and increases in the number of ICOS+ T follicular helper cells. A shared plasmablast transcriptional signature (IGHG2, IGHA1, IGHA2) was induced by both vaccines ten days after vaccination, which is distinct from influenza vaccine responses. Importantly, the pre-vaccination (baseline) ratio of Th1/Th17 cells predicted responsiveness to Prevnar but not to Pneumovax. Interestingly, women had higher levels of Th1/Th17; and responded stronger to Prevnar compared to men. This study uncovered how older adults respond to different pneumococcal vaccines and demonstrated the significance of considering biological sex and the immune cell composition for precision vaccinology.

Severe coronavirus disease 2019 (COVID-19) is characterized by systemic inflammation and can result in protracted symptoms. Robust systemic inflammation may trigger persistent changes in hematopoietic cells and innate immune memory through epigenetic mechanisms. We reveal that rare circulating hematopoietic stem and progenitor cells (HSPC), enriched from human blood, match the diversity of HSPC in bone marrow, enabling investigation of hematopoiesis and HSPC epigenomics. Following COVID-19, HSPC retain epigenomic alterations that are conveyed, through differentiation, to progeny innate immune cells. Epigenomic changes vary with disease severity, persist for months to a year, and are associated with increased myeloid cell differentiation and inflammatory or antiviral programs. Epigenetic reprogramming of HSPC may underly altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.One Sentence SummaryTranscriptomic and epigenomic analysis of blood reveal sustained changes in hematopoiesis and innate immunity after COVID-19.Graphical Abstract

Differences in immune function and responses contribute to health- and life-span disparities between sexes. However, the role of sex in immune system aging is not well understood. Here, we characterize peripheral blood mononuclear cells from 172 healthy adults 22–93 years of age using ATAC-seq, RNA-seq, and flow cytometry. These data reveal a shared epigenomic signature of aging including declining naïve T cell and increasing monocyte and cytotoxic cell functions. These changes are greater in magnitude in men and accompanied by a male-specific decline in B-cell specific loci. Age-related epigenomic changes first spike around late-thirties with similar timing and magnitude between sexes, whereas the second spike is earlier and stronger in men. Unexpectedly, genomic differences between sexes increase after age 65, with men having higher innate and pro-inflammatory activity and lower adaptive activity. Impact of age and sex on immune phenotypes can be visualized at https://immune-aging.jax.org to provide insights into future studies., Whether the immune system aging differs between men and women is barely known. Here the authors characterize gene expression, chromatin state and immune subset composition in the blood of healthy humans 22 to 93 years of age, uncovering shared as well as sex-unique alterations, and create a web resource to interactively explore the data.

Detecting multiplets in single nucleus (sn)ATAC-seq data is challenging due to data sparsity and limited dynamic range. AMULET (ATAC-seq MULtiplet Estimation Tool) enumerates regions with greater than two uniquely aligned reads across the genome to effectively detect multiplets. We evaluate the method by generating snATAC-seq data in the human blood and pancreatic islet samples. AMULET has high precision, estimated via donor-based multiplexing, and high recall, estimated via simulated multiplets, compared to alternatives and identifies multiplets most effectively when a certain read depth of 25K median valid reads per nucleus is achieved. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-021-02469-x.

Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies active cis-REs in a given cell type (including from single cells) by mapping accessible chromatin at base-pair resolution. However, these maps are not immediately useful for inferring specific functions of cis-REs. For this purpose, we developed a deep learning framework (CoRE-ATAC) with novel data encoders that integrate DNA sequence (reference or personal genotypes) with ATAC-seq cut sites and read pileups. CoRE-ATAC was trained on 4 cell types (n = 6 samples/replicates) and accurately predicted known cis-RE functions from 7 cell types (n = 40 samples) that were not used in model training (mean average precision = 0.80, mean F1 score = 0.70). CoRE-ATAC enhancer predictions from 19 human islet samples coincided with genetically modulated gain/loss of enhancer activity, which was confirmed by massively parallel reporter assays (MPRAs). Finally, CoRE-ATAC effectively inferred cis-RE function from aggregate single nucleus ATAC-seq (snATAC) data from human blood-derived immune cells that overlapped with known functional annotations in sorted immune cells, which established the efficacy of these models to study cis-RE functions of rare cells without the need for cell sorting. ATAC-seq maps from primary human cells reveal individual- and cell-specific variation in cis-RE activity. CoRE-ATAC increases the functional resolution of these maps, a critical step for studying regulatory disruptions behind diseases., Author summary Non-coding DNA sequences serve different functional roles to regulate gene expression. For these sequences to be active, they must be accessible for proteins to bind and carry out specific regulatory functions. Even so, mutations or other regulatory events may modulate their activity or regulatory function, making it critical to infer their function to understand their regulatory impact. Current sequencing technologies capture accessible sequences from low cell numbers, enabling the study of clinical samples. However, determining their functional role remains a challenge. For example, enhancers and insulators serve distinct regulatory functions, yet both fall in open chromatin regions and have similar genomic annotations (i.e., distance to transcription start site). Hence, alternative data sources and features (e.g., from DNA sequence or ATAC-seq data) must be integrated to distinguish them. Towards this goal, we developed CoRE-ATAC to infer whether open chromatin regions correspond to promoters, enhancers, or insulators. We demonstrate that CoRE-ATAC can infer regulatory functions in diverse cell types, capture activity differences modulated by genetic mutations, and can be applied to single cell ATAC-seq data to study rare cell populations. These inferences will further our understanding of how genes are regulated and how these regulatory mechanisms are disrupted with disease.

Increased inflammation with age (i.e., inflammaging) is a hallmark of aging conserved in human and mice, but the underlying mechanisms are poorly understood, partially because a systematic comparative study of mouse and human immune system aging is lacking. We uncovered epigenomic/transcriptomic signatures of aging in spleen and peripheral blood lymphocytes from young (3 months) and old (18 months) mice in two strains: C57BL/6J (long-lived) and NZO/HILtJ (short-lived) and compared these to the aging signatures of human peripheral blood cells. The most predominant and conserved genomic signature of aging in human and mice tissues studied here was the epigenetic activation of several AP-1 complex members (Fos, Fosl2, Junb, Jund). Footprinting analyses showed that these transcription factors ‘bind’ more frequently with age and target pro-inflammatory and effector molecules, including the pro-inflammatory Il6. Analysis of single cell RNA-seq data from the mouse aging cell atlas (Tabula Muris Senis) revealed that AP-1 activation with age is a common feature across all immune cell types within spleens, yet macrophages express these molecules more often than other cells. Functional assays confirmed that spleen cells from older animals have increased c-JUN protein binding and increased IL6 production upon myeloid cell activation using poly(I:C) via TLR3. Western blot data revealed that c-JUN activation with age is not post-transcriptional since its phosphorylation levels were similar between young and old mice. Together, these data established that Jun and Fos families in the AP-1 complex are transcriptionally activated with age and target pro-inflammatory molecules and aging-related increases in the binding of these proteins likely modulate increased inflammation with age.

Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) at >250 loci in the human genome to type 2 diabetes (T2D) risk. For each locus, identifying the functional variant(s) among multiple SNPs in high linkage disequilibrium is critical to understand molecular mechanisms underlying T2D genetic risk. Using massively parallel reporter assays (MPRA), we test the cis-regulatory effects of SNPs associated with T2D and altered in vivo islet chromatin accessibility in MIN6 β cells under steady state and pathophysiologic endoplasmic reticulum (ER) stress conditions. We identify 1,982/6,621 (29.9%) SNP-containing elements that activate transcription in MIN6 and 879 SNP alleles that modulate MPRA activity. Multiple T2D-associated SNPs alter the activity of short interspersed nuclear element (SINE)-containing elements that are strongly induced by ER stress. We identify 220 functional variants at 104 T2D association signals, narrowing 54 signals to a single candidate SNP. Together, this study identifies elements driving β cell steady state and ER stress-responsive transcriptional activation, nominates causal T2D SNPs, and uncovers potential roles for repetitive elements in β cell transcriptional stress response and T2D genetics., Identifying causal variants at GWAS loci is important to understand disease mechanisms. Here the authors use massively parallel reporter assays to identify type 2 diabetes-associated variants that alter cis-regulatory activity, narrowing in on the causal variants and genetic mechanisms behind the disease.

Summary Single-cell RNA-sequencing (scRNA-seq) technology enables studying gene expression programs from individual cells. However, these data are subject to diverse sources of variation, including ‘unwanted’ variation that needs to be removed in downstream analyses (e.g. batch effects) and ‘wanted’ or biological sources of variation (e.g. variation associated with a cell type) that needs to be precisely described. Surrogate variable analysis (SVA)-based algorithms, are commonly used for batch correction and more recently for studying ‘wanted’ variation in scRNA-seq data. However, interpreting whether these variables are biologically meaningful or stemming from technical reasons remains a challenge. To facilitate the interpretation of surrogate variables detected by algorithms including IA-SVA, SVA or ZINB-WaVE, we developed an R Shiny application [Visual Surrogate Variable Analysis (V-SVA)] that provides a web-browser interface for the identification and annotation of hidden sources of variation in scRNA-seq data. This interactive framework includes tools for discovery of genes associated with detected sources of variation, gene annotation using publicly available databases and gene sets, and data visualization using dimension reduction methods. Availability and implementation The V-SVA Shiny application is publicly hosted at https://vsva.jax.org/ and the source code is freely available at https://github.com/nlawlor/V-SVA. Contact leed13@miamioh.edu or duygu.ucar@jax.org Supplementary information Supplementary data are available at Bioinformatics online.

Varshney et al. directly compare five widely-used annotations of active regulatory elements: stretch, super, and typical enhancers; highoccupancy target (HOT) regions; and broad domains in four human cell types. Overall, their results suggest that current... Epigenomic signatures from histone marks and transcription factor (TF)-binding sites have been used to annotate putative gene regulatory regions. However, a direct comparison of these diverse annotations is missing, and it is unclear how genetic variation within these annotations affects gene expression. Here, we compare five widely used annotations of active regulatory elements that represent high densities of one or more relevant epigenomic marks—“super” and “typical” (nonsuper) enhancers, stretch enhancers, high-occupancy target (HOT) regions, and broad domains—across the four matched human cell types for which they are available. We observe that stretch and super enhancers cover cell type-specific enhancer “chromatin states,” whereas HOT regions and broad domains comprise more ubiquitous promoter states. Expression quantitative trait loci (eQTL) in stretch enhancers have significantly smaller effect sizes compared to those in HOT regions. Strikingly, chromatin accessibility QTL in stretch enhancers have significantly larger effect sizes compared to those in HOT regions. These observations suggest that stretch enhancers could harbor genetically primed chromatin to enable changes in TF binding, possibly to drive cell type-specific responses to environmental stimuli. Our results suggest that current eQTL studies are relatively underpowered or could lack the appropriate environmental context to detect genetic effects in the most cell type-specific “regulatory annotations,” which likely contributes to infrequent colocalization of eQTL with genome-wide association study signals.

Understanding the mechanisms underlying autoantibody development will accelerate therapeutic target identification in autoimmune diseases such as systemic lupus erythematosus (SLE)1. Follicular helper T cells (TFH cells) have long been implicated in SLE pathogenesis. Yet a fraction of autoantibodies in individuals with SLE are unmutated, supporting that autoreactive B cells also differentiate outside germinal centers2. Here, we describe a CXCR5-CXCR3+ programmed death 1 (PD1)hiCD4+ helper T cell population distinct from TFH cells and expanded in both SLE blood and the tubulointerstitial areas of individuals with proliferative lupus nephritis. These cells produce interleukin-10 (IL-10) and accumulate mitochondrial reactive oxygen species as the result of reverse electron transport fueled by succinate. Furthermore, they provide B cell help, independently of IL-21, through IL-10 and succinate. Similar cells are generated in vitro upon priming naive CD4+ T cells with plasmacytoid dendritic cells activated with oxidized mitochondrial DNA, a distinct class of interferogenic toll-like receptor 9 ligand3. Targeting this pathway might blunt the initiation and/or perpetuation of extrafollicular humoral responses in SLE.

SummaryATAC-seq is a frequently used assay to study chromatin accessibility levels. Differential chromatin accessibility analyses between biological groups and functional interpretation of these differential regions are essential in ATAC-seq data analyses. Although distinct methods and analyses pipelines are developed for this purpose, a stand-alone R package that combines state-of-the art differential and functional enrichment analyses pipelines is missing. To fill this gap, we developed cinaR (Chromatin Analyses in R), which is a single wrapper function and provides users with various data analyses and visualization options, including functional enrichment analyses with gene sets curated from multiple sources.Availability and implementationcinaR is an R/CRAN package which is under GPL-3 License and its source code is freely accessible at https://CRAN.R-project.org/package=cinaR.Gene sets are available at https://CRAN.R-project.org/package=cinaRgenesets.Bone marrow ATAC-seq data is available at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE165120Contactonur.karakaslar@jax.org or duygu.ucar@jax.org

Similar to other droplet-based single cell assays, single nucleus ATAC-seq (snATAC-seq) data harbor multiplets that confound downstream analyses. Detecting multiplets in snATAC-seq data is particularly challenging due to its sparsity and trinary nature (0 reads: closed chromatin, 1: open in one allele, 2: open in both alleles), yet offers a unique opportunity to infer multiplets when >2 uniquely aligned reads are observed at multiple loci. Here, we implemented the first read count-based multiplet detection method, ATAC-DoubletDetector, that detects multiplets independently of cell-type. Using PBMC and pancreatic islet datasets, ATAC-DoubletDetector captured simulated heterotypic multiplets (different cell-types) with ∼0.60 recall, showing ∼24% improvement over state of the art. ATAC-DoubletDetector detected homotypic multiplets with ∼0.61 recall, representing the first method to detect multiplets originating from the same cell type. Using our novel clustering-based algorithm, multiplets were annotated to their cellular origins with ∼85% accuracy. Application of ATAC-DoubletDetector will improve downstream analysis of snATAC-seq.

Immune cell activation assays have been widely used for immune monitoring and for understanding disease mechanisms. However, these assays are typically limited in scope. A holistic study of circulating immune cell responses to different activators is lacking. Here we developed a cost-effective high-throughput multiplexed single-cell RNA-seq combined with epitope tagging (CITE-seq) to determine how classic activators of T cells (anti-CD3 coupled with anti-CD28) or monocytes (LPS) alter the cell composition and transcriptional profiles of peripheral blood mononuclear cells (PBMCs) from healthy human donors. Anti-CD3/CD28 treatment activated all classes of lymphocytes either directly (T cells) or indirectly (B and NK cells) but reduced monocyte numbers. Activated T and NK cells expressed senescence and effector molecules, whereas activated B cells transcriptionally resembled autoimmune disease- or age-associated B cells (e.g., CD11c, T-bet). In contrast, LPS specifically targeted monocytes and induced two main states: early activation characterized by the expression of chemoattractants and a later pro-inflammatory state characterized by expression of effector molecules. These data provide a foundation for future immune activation studies with single cell technologies (https://czi-pbmc-cite-seq.jax.org/).Graphical abstract

Preeclampsia is a serious problem in pregnant women with high blood pressure, which can be fatal for both mother and newborn. Although the incidence of moderate and severe hyponatremia associated with preeclampsia has been reported in the literature in a small number, it is an important electrolyte disorder that may progress with high perinatal and maternal morbidity and mortality. Cases of preeclampsia complicated by severe hyponatremia have been reported much rarely. We present here a case with severe hyponatremia in preeclampsia and discuss shortly the pathogenesis and management of this rare complication.

While Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is disrupting lives across the globe for everyone, it has a more devastating impact on the health of older adults, especially that of older men. This pandemic has highlighted the crucial importance of considering an individual’s age and biological sex in the clinic in addition to other confounding diseases (Kuchel, G.A, J Am Geriatr Soc, 67, 203, 2019, Tannenbaum, C., Nature, 575 451-458, 2009) As an interdisciplinary team of scientists in immunology, hematology, genomics, bioinformatics, and geriatrics, we have been studying how age and sex shape the human immune system. Herein we reflect on how our recent findings on the alterations of the immune system in aging might contribute to our current understanding of COVID-19 infection rate and disease risk.

Ageing is associated with re-modelling of the immune system to enable the maintenance of life-long immunity. In the CD8(+) T cell compartment, ageing results in the expansion of highly-differentiated cells that exhibit characteristics of cellular senescence. Here we found that CD27(−)CD28(−)CD8(+) T lost the signalling activity of the T cell antigen receptor (TCR) and expressed a protein complex containing the agonistic NK receptor NKG2D and the NK adaptor molecule DAP12, which promoted cytotoxicity against cells that expressed NKG2D ligands. Immunoprecipitation and imaging cytometry indicated that the NKG2D-DAP12 complex was associated with sestrin 2. The genetic inhibition of sestrin 2 resulted in decreased expression of NKG2D and DAP12 and restored TCR signaling in senescent-like CD27(−)CD28(−)CD8(+) T cells. Therefore, during ageing, sestrins induces the reprogramming of non-proliferative senescent-like CD27(−)CD28(−)CD8(+) T cells to acquire a broad-spectrum, innate-like killing activity.

A major goal in functional genomics and complex disease genetics is to identify functional cis-regulatory elements (CREs) and single nucleotide polymorphisms (SNPs) altering CRE activity in disease-relevant cell types and environmental conditions. We tested >13,000 sequences containing each allele of 6,628 SNPs associated with altered in vivo chromatin accessibility in human islets and/or type 2 diabetes risk (T2D GWAS SNPs) for transcriptional activity in ß cell under steady state and endoplasmic reticulum (ER) stress conditions using the massively parallel reporter assay (MPRA). Approximately 30% (n=1,983) of putative CREs were active in at least one condition. SNP allelic effects on in vitro MPRA activity strongly correlated with their effects on in vivo islet chromatin accessibility (Pearson r=0.52), i.e., alleles associated with increased chromatin accessibility exhibited higher MPRA activity. Importantly, MPRA identified 220/2500 T2D GWAS SNPs, representing 104 distinct association signals, that significantly altered transcriptional activity in ß cells. This study has thus identified functional ß cell transcription-activating sequences with in vivo relevance, uncovered regulatory features that modulate transcriptional activity in ß cells under steady state and ER stress conditions, and substantially expanded the set of putative functional variants that modulate transcriptional activity in ß cells from thousands of genetically-linked T2D GWAS SNPs.

Enhancers are cis-acting sequences that regulate transcription rates of their target genes in a cell-specific manner and harbor disease-associated sequence variants in cognate cell types. Many complex diseases are associated with enhancer malfunction, necessitating the discovery and study of enhancers from clinical samples. Assay for Transposase Accessible Chromatin (ATAC-seq) technology can interrogate chromatin accessibility from small cell numbers and facilitate studying enhancers in pathologies. However, on average, ~35% of open chromatin regions (OCRs) from ATAC-seq samples map to enhancers. We developed a neural network-based model, Predicting Enhancers from ATAC-Seq data (PEAS), to effectively infer enhancers from clinical ATAC-seq samples by extracting ATAC-seq data features and integrating these with sequence-related features (e.g., GC ratio). PEAS recapitulated ChromHMM-defined enhancers in CD14+ monocytes, CD4+ T cells, GM12878, peripheral blood mononuclear cells, and pancreatic islets. PEAS models trained on these 5 cell types effectively predicted enhancers in four cell types that are not used in model training (EndoC-βH1, naïve CD8+ T, MCF7, and K562 cells). Finally, PEAS inferred individual-specific enhancers from 19 islet ATAC-seq samples and revealed variability in enhancer activity across individuals, including those driven by genetic differences. PEAS is an easy-to-use tool developed to study enhancers in pathologies by taking advantage of the increasing number of clinical epigenomes.

Type 2 diabetes (T2D) is a complex disorder in which both genetic and environmental risk factors contribute to islet dysfunction and failure. Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs), most of which are noncoding, in >200 loci to islet dysfunction and T2D. Identification of the putative causal variants and their target genes and whether they lead to gain or loss of function remains challenging. Here, we profiled chromatin accessibility in pancreatic islet samples from 19 genotyped individuals and identified 2,949 SNPs associated with in vivo cis-regulatory element use (i.e., chromatin accessibility quantitative trait loci [caQTL]). Among the caQTLs tested (n = 13) using luciferase reporter assays in MIN6 β-cells, more than half exhibited effects on enhancer activity that were consistent with in vivo chromatin accessibility changes. Importantly, islet caQTL analysis nominated putative causal SNPs in 13 T2D-associated GWAS loci, linking 7 and 6 T2D risk alleles, respectively, to gain or loss of in vivo chromatin accessibility. By investigating the effect of genetic variants on chromatin accessibility in islets, this study is an important step forward in translating T2D-associated GWAS SNP into functional molecular consequences.