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Nutritional disorders cause secondary osteoporosis as well as musculoskeletal metabolism dysfunction. The Christian Orthodox Church’s fasting in Mediterranean countries such Greece and Cyprus, or M.C.O.C. diet consists of self-restraint from food and/or food categories for 180 ± 19 days of total, especially of animal protein and dairy products. This case-control study attempts to investigate the effect of this fasting pattern on musculoskeletal metabolism and bone density. One hundred fasters (or M.C.O.C. diet followers; 68 women and 32 men, mean 59 ± 6.5) with 32 years average fasting time and 100 non-fasters (66 females and 34 males, mean 58.1 ± 6.8; the control group of Mediterranean diet followers) over the age of 50, including menopausal women, were interviewed, as well as physically and laboratory examined along with DEXA measurements of the L2-4 vertebrae and hips. Nutrition data gathered through a 3-day food record during a non-fasting period, while energy intakes calculated on a daily food consumption basis. Given the overall low incidence of osteoporosis in the Mediterranean diet, it appears to be more than three times higher than that of M.C.O.C. diet despite the periodic restriction of food intake of animal origin into a slightly hypothermic pattern, which in turn is characterized by increased consumption of multicolored vegetable foods. Abstinence from dairy products and meat does not adversely affect musculoskeletal metabolism or bone density. M.C.O.C. diet seems to be “healthy” eating habit for the musculoskeletal system, as future studies expected to confirm.

Aims/hypothesis It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes., Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

Funder: Universität des Saarlandes (1036), Background: Understanding the influence of genetic variants on DNA methylation is fundamental for the interpretation of epigenomic data in the context of disease. There is a need for systematic approaches not only for determining methylation quantitative trait loci (methQTL), but also for discriminating general from cell type-specific effects. Results: Here, we present a two-step computational framework MAGAR (https://bioconductor.org/packages/MAGAR), which fully supports the identification of methQTLs from matched genotyping and DNA methylation data, and additionally allows for illuminating cell type-specific methQTL effects. In a pilot analysis, we apply MAGAR on data in four tissues (ileum, rectum, T cells, B cells) from healthy individuals and demonstrate the discrimination of common from cell type-specific methQTLs. We experimentally validate both types of methQTLs in an independent data set comprising additional cell types and tissues. Finally, we validate selected methQTLs located in the PON1, ZNF155, and NRG2 genes by ultra-deep local sequencing. In line with previous reports, we find cell type-specific methQTLs to be preferentially located in enhancer elements. Conclusions: Our analysis demonstrates that a systematic analysis of methQTLs provides important new insights on the influences of genetic variants to cell type-specific epigenomic variation.

Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) often co-occur. Defining causal pathways underlying this relationship may help optimize the prevention and treatment of both diseases. Thus, we assessed the strength and magnitude of the putative causal pathways linking dysglycemia and fatty liver, using a combination of causal inference methods.Measures of glycemia, insulin dynamics, magnetic resonance imaging (MRI)-derived abdominal and liver fat content, serological biomarkers, lifestyle, and anthropometry were obtained in participants from the IMI DIRECT cohorts (n=795 with new onset T2D and 2234 individuals free from diabetes). UK Biobank (n=3641) was used for modelling and replication purposes. Bayesian networks were employed to infer causal pathways, with causal validation using two-sample Mendelian randomization.Bayesian networks fitted to IMI DIRECT data identified higher basal insulin secretion rate (BasalISR) and MRI-derived excess visceral fat (VAT) accumulation as the features of dysmetabolism most likely to cause liver fat accumulation; the unconditional probability of fatty liver (>5%) increased significantly when conditioning on high levels of BasalISR and VAT (by 23%, 32% respectively; 40% for both). Analyses in UK Biobank yielded comparable results. MR confirmed most causal pathways predicted by the Bayesian networks.Here, BasalISR had the highest causal effect on fatty liver predisposition, providing mechanistic evidence underpinning the established association of NAFLD and T2D. BasalISR may represent a pragmatic biomarker for NAFLD prediction in clinical practice.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.Analyses of expression profiles from whole blood of 31,684 individuals identify cis-expression quantitative trait loci (eQTL) effects for 88% of genes and trans-eQTL effects for 37% of trait-associated variants.

Vaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic. However, the emergence of vaccine-resistant strains may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic. To quantify and characterize the risk of such a scenario, we created a SIR-derived model with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. As expected, we found that a fast rate of vaccination decreases the probability of emergence of a resistant strain. Counterintuitively, when a relaxation of non-pharmaceutical interventions happened at a time when most individuals of the population have already been vaccinated the probability of emergence of a resistant strain was greatly increased. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. Our results suggest that policymakers and individuals should consider maintaining non-pharmaceutical interventions and transmission-reducing behaviours throughout the entire vaccination period.

Leydig cells (LC) are the main testicular androgen-producing cells. In eutherian mammals, two types of LCs emerge successively during testicular development, fetal Leydig cells (FLCs) and adult Leydig cells (ALCs). Both display significant differences in androgen production and regulation. Using bulk RNA sequencing, we compared the transcriptomes of both LC populations to characterise their specific transcriptional and functional features. Despite similar transcriptomic profiles, a quarter of the genes show significant variations in expression between FLCs and ALCs. Non-transcriptional events, such as alternative splicing was also observed, including a high rate of intron retention in FLCs compared to ALCs. The use of single-cell RNA sequencing data also allowed the identification of nine FLC-specific genes and 50 ALC-specific genes. Expression of the corticotropin-releasing hormone 1 (Crhr1) receptor and the ACTH receptor melanocortin type 2 receptor (Mc2r) specifically in FLCs suggests a dual regulation of steroidogenesis. The androstenedione synthesis by FLCs is stimulated by luteinizing hormone (LH), CRH and ACTH whereas the testosterone synthesis by ALCs is dependent exclusively on LH. Overall, our study provides a useful database to explore LC development and function.

Despite the importance of germ cell (GC) differentiation for sexual reproduction, the gene networks underlying their fate remain unclear. Here, we comprehensively characterize the gene expression dynamics during sex determination based on single-cell RNA sequencing of 14 914 XX and XY mouse GCs between embryonic days (E) 9.0 and 16.5. We found that XX and XY GCs diverge transcriptionally as early as E11.5 with upregulation of genes downstream of the bone morphogenic protein (BMP) and nodal/Activin pathways in XY and XX GCs, respectively. We also identified a sex-specific upregulation of genes associated with negative regulation of mRNA processing and an increase in intron retention consistent with a reduction in mRNA splicing in XY testicular GCs by E13.5. Using computational gene regulation network inference analysis, we identified sex-specific, sequential waves of putative key regulator genes during GC differentiation and revealed that the meiotic genes are regulated by positive and negative master modules acting in an antagonistic fashion. Finally, we found that rare adrenal GCs enter meiosis similarly to ovarian GCs but display altered expression of master genes controlling the female and male genetic programs, indicating that the somatic environment is important for GC function. Our data are available on a web platform and provide a molecular roadmap of GC sex determination at single-cell resolution, which will serve as a valuable resource for future studies of gonad development, function, and disease.

Lifestyle choices significantly influence mental health in later life. In this study we investigated the effects of the Christian Orthodox Church (COC) fasting diet, which includes long-term regular abstinence from animal-based products for half the calendar year, on cognitive function and emotional wellbeing of healthy adults. Two groups of fasting and non-fasting individuals were evaluated regarding their cognitive performance and the presence of anxiety and depression using the Mini Mental Examination Scale, the Hamilton Anxiety Scale, and the Geriatric Depression Scale (GDS), respectively. Data on physical activity, smoking, and vitamin levels were collected and correlated with mental health scoring. Negative binomial regression was performed to examine differences in the GDS scores between the two groups. Significantly lower levels of anxiety (7.48 ± 4.98 vs. 9.71 ± 5.25, p &lt, 0.001) and depression (2.24 ± 1.77 vs. 3.5 ± 2.52, 0.001), along with better cognitive function (29.15 ± 0.79 vs. 28.64 ± 1.27, 0.001), were noticed in fasting compared to non-fasting individuals. GDS score was 31% lower (Incidence Rate Ratio: 0.69, 95% Confidence Interval: 0.56–0.85) in the fasting group compared to the control, while vitamin and ferrum levels did not differ. The COC fasting diet was found to have an independent positive impact on cognition and mood in middle-aged and elderly individuals.

Individuals experiencing socioeconomic disadvantage in childhood have a higher rate of inflammation-related diseases decades later. Little is known about the mechanisms linking early life experiences to the functioning of the immune system in adulthood. To address this, we explore the relationship across social-to-biological layers of early life social exposures on levels of adulthood inflammation and the mediating role of gene regulatory mechanisms, epigenetic and transcriptomic profiling from blood, in 2,329 individuals from two European cohort studies. Consistently across both studies, we find transcriptional activity explains a substantive proportion (78% and 26%) of the estimated effect of early life disadvantaged social exposures on levels of adulthood inflammation. Furthermore, we show that mechanisms other than cis DNA methylation may regulate those transcriptional fingerprints. These results further our understanding of social-to-biological transitions by pinpointing the role of gene regulation that cannot fully be explained by differential cis DNA methylation.

OBJECTIVE We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), β-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression. RESULTS Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8–10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07–0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role. CONCLUSIONS Deteriorating insulin sensitivity and β-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, β-cell function, and insulin clearance may be relevant to prevent progression.

International audience; AIM: The worldwide increase in obesity and type 2 diabetes (T2D) represents a major health challenge. Chronically altered lipids induced by obesity further promote the development of T2D, and the accumulation of toxic lipid metabolites in serum and peripheral organs may contribute to the diabetic phenotype. METHODS: To better understand the complex metabolic pattern of lean and obese T2D and non-T2D individuals, we analysed the lipid profile of human serum, skeletal muscle and visceral adipose tissue of two cohorts by systematic mass spectrometry-based lipid analysis. RESULTS: Lipid homeostasis was strongly altered in a disease- and tissue-specific manner, allowing us to define T2D signatures associated with obesity from those that were obesity independent. Lipid changes encompassed lyso-, diacyl- and ether-phospholipids. Moreover, strong changes in sphingolipids included cytotoxic 1-deoxyceramide accumulation in a disease-specific manner in serum and visceral adipose tissue. The high amounts of non-canonical 1-deoxyceramide present in human adipose tissue most likely come from cell-autonomous synthesis because 1-deoxyceramide production increased upon differentiation to adipocytes in mouse cell culture experiments. CONCLUSION: Taken together, the observed lipidome changes in obesity and T2D will facilitate the identification of T2D patient subgroups and represent an important step towards personalized medicine in diabetes.

BackgroundThe rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D.MethodsClusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts.ResultsWe identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling.ConclusionsOur results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435).We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively.The TC and TC-PA models showed better fit than null models (TC: χThese analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.

A primary goal of human genetics is to identify DNA sequence variants that influence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition.

The Genotype-Tissue Expression (GTEx) project dissects how genetic variation affects gene expression and splicing. Some human genetic variants affect the amount of RNA produced and the splicing of gene transcripts, crucial steps in development and maintaining a healthy individual. However, some of these changes only occur in a small number of tissues within the body. The Genotype-Tissue Expression (GTEx) project has been expanded over time, and, looking at the final data in version 8, Aguet et al. present a deep characterization of genetic associations and gene expression and splicing in 838 individuals over 49 tissues (see the Perspective by Wilson). This large study was able to characterize the details underlying many aspects of gene expression and provides a resource with which to better understand the fundamental molecular mechanisms of how genetic variants affect gene regulation and complex traits in humans. Science, this issue p. 1318; see also p. 1298 The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues. We thank the donors and their families for their generous gifts of organ donation for transplantation and tissue donations for the GTEx research project; the Genomics Platform at the Broad Institute for data generation; J. Struewing for support and leadership of the GTEx project; M. Khan and C. Stolte for the illustrations in Fig. 1; and R. Do, D. Jordan, and M. Verbanck for providing GWAS pleiotropy scores. Funding: This work was supported by the Common Fund of the Office of the Director, U.S. National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, NIA, NIAID, and NINDS through NIH contracts HHSN261200800001E (Leidos Prime contract with NCI: A.M.S., D.E.T., N.V.R., J.A.M., L.S., M.E.B., L.Q., T.K., D.B., K.R., and A.U.), 10XS170 (NDRI: W.F.L., J.A.T., G.K., A.M., S.S., R.H., G.Wa., M.J., M.Wa., L.E.B., C.J., J.W., B.R., M.Hu., K.M., L.A.S., H.M.G., M.Mo., and L.K.B.), 10XS171 (Roswell Park Cancer Institute: B.A.F., M.T.M., E.K., B.M.G., K.D.R., and J.B.), 10X172 (Science Care Inc.), 12ST1039 (IDOX), 10ST1035 (Van Andel Institute: S.D.J., D.C.R., and D.R.V.), HHSN268201000029C (Broad Institute: F.A., G.G., K.G.A., A.V.S., X.Li., E.T., S.G., A.G., S.A., K.H.H., D.T.N., K.H., S.R.M., and J.L.N.), 5U41HG009494 (F.A., G.G., and K.G.A.), and through NIH grants R01 DA006227-17 (University of Miami Brain Bank: D.C.M. and D.A.D.), Supplement to University of Miami grant DA006227 (D.C.M. and D.A.D.), R01 MH090941 (University of Geneva), R01 MH090951 and R01 MH090937 (University of Chicago), R01 MH090936 (University of North Carolina–Chapel Hill), R01MH101814 (M.M.-A., V.W., S.B.M., R.G., E.T.D., D.G.-M., and A.V.), U01HG007593 (S.B.M.), R01MH101822 (C.D.B.), U01HG007598 (M.O. and B.E.S.), U01MH104393 (A.P.F.), extension H002371 to 5U41HG002371 (W.J.K.), as well as other funding sources: R01MH106842 (T.L., P.M., E.F., and P.J.H.), R01HL142028 (T.L., Si.Ka., and P.J.H.), R01GM122924 (T.L. and S.E.C.), R01MH107666 (H.K.I.), P30DK020595 (H.K.I.), UM1HG008901 (T.L.), R01GM124486 (T.L.), R01HG010067 (Y.Pa.), R01HG002585 (G.Wa. and M.St.), Gordon and Betty Moore Foundation GBMF 4559 (G.Wa. and M.St.), 1K99HG009916-01 (S.E.C.), R01HG006855 (Se.Ka. and R.E.H.), BIO2015-70777-P, Ministerio de Economia y Competitividad and FEDER funds (M.M.-A., V.W., R.G., and D.G.-M.), la Caixa Foundation ID 100010434 under agreement LCF/BQ/SO15/52260001 (D.G.-M.), NIH CTSA grant UL1TR002550-01 (P.M.), Marie-Skłodowska Curie fellowship H2020 Grant 706636 (S.K.-H.), R35HG010718 (E.R.G.), FPU15/03635, Ministerio de Educación, Cultura y Deporte (M.M.-A.),R01MH109905, 1R01HG010480 (A.Ba.), Searle Scholar Program (A.Ba.), R01HG008150 (S.B.M.), 5T32HG000044-22, NHGRI Institutional Training Grant in Genome Science (N.R.G.), EU IMI program (UE7-DIRECT-115317-1) (E.T.D. and A.V.), FNS funded project RNA1 (31003A_149984) (E.T.D. and A.V.), DK110919 (F.H.), F32HG009987 (F.H.), Massachusetts Lions Eye Research Fund Grant (A.R.H.), Wellcome grant WT108749/Z/15/Z (P.F.), and European Molecular Biology Laboratory (P.F. and D.Z.). Peer Reviewed "Article signat per 1 autors/es del BSC membres del THE GTEX CONSORTIUM: Marta Mele Messeguer"

BackgroundNon-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in type 2 diabetes (T2D) and beyond. Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and ultimately hepatocellular carcinomas.Methods and FindingsUtilizing the baseline data from the IMI DIRECT participants (n=1514) we sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. Multi-omic (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, and measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI image-derived liver fat content (ConclusionsWe have developed clinically useful liver fat prediction models (see:www.predictliverfat.org) and identified biological features that appear to affect liver fat accumulation.

Systemic Lupus Erythematosus (SLE) is the prototype of autoimmune diseases, characterized by extensive gene expression perturbations in peripheral blood immune cells. Circumstantial evidence suggests that these perturbations may be due to altered epigenetic profiles and chromatin accessibility but the relationship between transcriptional deregulation and genome organization remains largely unstudied. We developed a genomic approach that leverages patterns of gene coexpression from genome-wide transcriptome profiles in order to identify statistically robust Domains of Co-ordinated gene Expression (DCEs). By implementing this method on gene expression data from a large SLE patient cohort, we identify significant disease-associated alterations in gene co-regulation patterns, which also correlate with the SLE activity status. Low disease activity patient genomes are characterized by extensive fragmentation leading to DCEs of smaller size. High disease activity genomes display excessive spatial redistribution of co-expression domains with expanded and newly-appearing (emerged) DCEs. Fragmentation and redistribution of gene coexpression patterns correlate with SLE-implicated biological pathways and clinically relevant endophenotypes such as kidney involvement. Notably, genes lying at the boundaries of split DCEs of low activity genomes are enriched in the interferon and other SLE susceptibility signatures, suggesting the implication of DCE fragmentation at early disease stages. Interrogation of promoter-enhancer interactions from various immune cell subtypes shows that a significant percentage of nested connections are disrupted by a DCE split or depletion in SLE genomes. Collectively, our results underlining an important role for genome organization in shaping gene expression in SLE, could provide valuable insights into disease pathogenesis and the mechanisms underlying disease flares.SignificanceAlthough widespread gene expression changes have been reported in Systemic Lupus Erythematosus (SLE), attempts to link gene deregulation with genome structure have been lacking. Through a computational framework for the segmentation of gene expression data, we reveal extensive fragmentation and reorganization of gene co-regulation domains in SLE, that correlates with disease activity states. Gene co-expression domains pertaining to biological functions implicated in SLE such as the interferon pathway, are being disrupted in patients, while others associated to severe manifestations such as nephritis, emerge in previously uncorrelated regions of the genome. Our results support extensive genome re-organization underlying aberrant gene expression in SLE, which could assist in the early detection of disease flares in patients that are in remission.Graphical Abstract

Sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB) are the most frequent bariatric surgery procedures worldwide. In this prospective study, we examined the association of a genetic risk score (GRS) with loss of excess weight after bariatric surgery. A total of forty-seven morbidly obese Greek patients who underwent SG (81%) or RYGB were recruited, followed up for 2 years and genotyped. Weight loss after surgery was reported as the percentage of excess weight that was lost (%EWL) at 12 and 24 months after surgery. A GRS was constructed based on previously BMI- and WHR-related single nucleotide polymorphisms (SNPs) that were found significantly correlated with weight loss after bariatric surgery in our population. The level of post-surgery %EWL after 12 and 24 months was estimated through two multiple linear regression models that considered the effects of relevant genetic risk variants. The first proposed model suggested that the predictor variables of GRS, age, and BMI had a significant effect on %EWL12m. GRS was significantly associated with %EWL12m, indicating a 4.618% decrease of %EWL12m per score unit. The second model indicated a positive correlation between %EWL24m and %EWL12m, suggesting that while post-surgery weight loss increased during the first 12 months, an increase was expected in the next 12 months as well. GRS was also significantly associated with %EWL24m, indicating approximately 3% decrease of %EWL24m per score unit. GRS can be used in the future together with other preoperative parameters in order to predict the outcome of bariatric surgery.

Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues., Mechanistic inference following GWAS is hampered by the lack of tissue-specific transcriptomic resources. Here the authors combine genetic variants predisposing to type 2 diabetes with human pancreatic islet RNA-seq data. They identify 7741 islet expression quantitative trait loci (eQTLs), providing a resource for functional interpretation of association signals mapping to non-coding sequence.

Tissue cross-talk is emerging as a determinant way to coordinate the different organs implicated in glucose homeostasis. Among the inter-organ communication factors, muscle-secreted myokines can modulate the function and survival of pancreatic beta-cells. Using primary human myotubes from soleus, vastus lateralis and triceps brachii muscles, we report here that the impact of myokines on beta-cells depends on fiber types and their metabolic status. We show that Type I and type II primary myotubes present specific mRNA and myokine signatures as well as a different sensitivity to TNF-alpha induced insulin resistance. Finally, we show that angiogenin and osteoprotegerin are triceps specific myokines with beta-cell protective actions against proinflammatory cytokines. These results suggest that type I and type II muscles could impact insulin secretion and beta-cell mass differentially in type 2 diabetes through specific myokines secretion.

Gene expression changes with age have consequences for healthy aging and disease development. Here we investigate age-related changes in gene expression measured by RNA-seq in four tissues and the interplay between genotypes and age-related changes in expression. Using concurrently measured methylation array data from fat we also investigate the relationship between methylation, gene expression and age. We identified age-dependent changes in mean levels of gene expression in 5,631 genes and in splicing of 904 genes. Age related changes were widely shared across tissues, with up to 60% of age-related changes in expression and 47% on splicing in multi-exonic genes shared; amongst these we highlight effects on genes involved in diseases such as Alzheimer and cancer. We identified 137 genes with age-related changes in variance and 42 genes with age-dependent discordance between genetically identical individuals; implying the latter are driven by environmental effects. We also give four examples where genetic control of expression is affected by the aging process. Analysis of methylation observed a widespread and stronger effect of age on methylation than expression; however we did not find a strong relationship between age-related changes in both expression and methylation. In summary, we quantified aging affects in splicing, level and variance of gene expression, and show that these processes can be both environmentally and genetically influenced.

Genetic association mapping produces statistical links between phenotypes and genomic regions, but identifying causal variants remains difficult. Whole-genome sequencing (WGS) can help by providing complete knowledge of all genetic variants, but it is financially prohibitive for well-powered GWAS studies. We performed mapping of expression quantitative trait loci (eQTLs) with WGS and RNA-seq, and found that lead eQTL variants called with WGS were more likely to be causal. Through simulations, we derived properties of causal variants and used them to develop a method for identifying likely causal SNPs. We estimated that 25-70% of causal variants were located in open-chromatin regions, depending on the tissue and experiment. Finally, we identified a set of high-confidence causal variants and showed that these were more enriched in GWAS associations than other eQTLs. Of those, we found 65 associations with GWAS traits and provide examples in which genes implicated by expression are functionally validated as being relevant for complex traits.

The consistent detection and quantification of protein post-translational modifications (PTMs) across sample cohorts is an essential prerequisite for the functional analysis of biological processes. Data-independent acquisition (DIA), a bottom-up mass spectrometry based proteomic strategy, exemplified by SWATH-MS, provides complete precursor and fragment ion information of a sample and thus, in principle, the information to identify peptidoforms, the modified variants of a peptide. However, due to the convoluted structure of DIA data sets the confident and systematic identification and quantification of peptidoforms has remained challenging. Here we present IPF (Inference of PeptidoForms), a fully automated algorithm that uses spectral libraries to query, validate and quantify peptidoforms in DIA data sets. The method was developed on data acquired by SWATH-MS and benchmarked using a synthetic phosphopeptide reference data set and phosphopeptide-enriched samples. The data indicate that IPF reduced false site-localization by more than 7-fold in comparison to previous approaches, while recovering 85.4% of the true signals. IPF was applied to detect and quantify peptidoforms carrying ten different types of PTMs in DIA data acquired from more than 200 samples of undepleted blood plasma of a human twin cohort. The data approportioned, for the first time, the contribution of heritable, environmental and longitudinal effects on the observed quantitative variability of specific modifications in blood plasma of a human population.

Background Naevoid basal cell carcinoma syndrome (NBCCS) is an autosomal dominant genetic disorder. It is commonly caused by mutations in PTCH1 and chiefly characterized by multiple basal cell carcinomas (BCCs) developing prior to the age of 30 years. In rare cases NBCCS presents with a late onset of BCC development. Objective To investigate BCC tumorigenesis in two brothers, who showed characteristic features of NBCCS but developed their first BCCs only after 40 years of age. Two other siblings did not show signs of NBCCS. Results We obtained blood samples from four siblings and nine BCCs from the two brothers with NBCCS. Whole exome sequencing and RNA sequencing revealed Loss of Heterozygosity (LOH) of PTCH1 in eight out of nine tumors that consistently involved the same haplotype on chromosome 9. This haplotype contained a germinal splice-site mutation in PTCH1 (NM_001083605:exon9:c.763-6C>A). Analysis of germline DNA confirmed segregation of this mutation with the disease. All BCCs harbored additional somatic loss-of-function (LoF) mutations in the remaining PTCH1 allele which are not typically seen in other cases of NBCCS. This suggests a hypomorphic nature of the germinal PTCH1 mutation in this family. Furthermore, all BCCs had a similar tumor mutational burden (TMB) compared to BCCs of unrelated NBCCS patients while harboring a higher number of damaging PTCH1 mutations. Conclusions Our data suggests that a sequence of three genetic hits lead to the late development of BCCs in two brothers with NBCCS: a hypomorphic germline mutation, followed by somatic LOH and additional mutations that complete PTCH1 inactivation. These genetic events are in line with the late occurrence of the first BCC and with the higher number of damaging PTCH1 mutations compared to usual cases of NBCCS.

Aims/hypothesis Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). Methods From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6–24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. Results Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants’ clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m2; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants’ clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l. Conclusions/interpretation The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes. Electronic supplementary material The online version of this article (10.1007/s00125-019-4906-1) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Proper nutrition throughout childhood and adolescence is crucial for normal bone development. We investigated whether adherence to Christian Orthodox Church fasting is characterized by periodic avoidance of animal foods (including dairy products), since childhood affects stature or bone health in young adults. This cross-sectional study included 200 healthy men and women, aged 18-35, of whom 100 had been following religious fasting for a median of 14 years, starting at the age of 10, and 100 were non-fasters. Measurements included body height; bone mineral density and bone mineral content at the lumbar spine, right hip, left hip, right femoral neck, and left femoral neck; prevalence of bone fracture; serum biochemical parameters; food and nutrient intake; and physical activity and smoking habits. Fasters did not differ from non-fasters in anthropometric measures (including height), bone mineral density and content, or prevalence of low bone mineral density at any of the five sites measured; number of bone fractures; or serum calcium or 25-hydroxyvitamin D concentrations (P0.05). Fasters had lower daily calcium and protein intakes, as well as lower dairy consumption than non-fasters. Groups did not differ in physical activity, and fasters smoked less than non-fasters.Conclusion: Despite lower calcium intake and lower dairy product consumption, individuals adhering to religious fasting since childhood did not differ in height, bone mineral density and content, or prevalence of fractures from controls. Therefore, periodic abstention from dairy and, generally, animal products since childhood does not seem to compromise bone health in young adults.What is Known: • Bone health is an important determinant of overall health and longevity. • Proper nutrition throughout childhood and adolescence is crucial for normal bone development. • Adequate intake of dairy products is considered important due to their high calcium content.What is New: • Young adults with limited calcium intake and dairy product consumption, due to adherence to the fasting rules of the Christian Orthodox Church since childhood, do not differ in height or indices of bone health from non-fasting controls.

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

The circadian system plays an essential role in regulating the timing of human metabolism. Indeed, circadian misalignment is strongly associated with high rates of metabolic disorders. The properties of the circadian oscillator can be measured in cells cultured in vitro and these cellular rhythms are highly informative of the physiological circadian rhythm in vivo. We aimed to discover whether molecular properties of the circadian oscillator are altered as a result of type 2 diabetes. We assessed molecular clock properties in dermal fibroblasts established from skin biopsies taken from nine obese and eight non-obese individuals with type 2 diabetes and 11 non-diabetic control individuals. Following in vitro synchronisation, primary fibroblast cultures were subjected to continuous assessment of circadian bioluminescence profiles based on lentiviral luciferase reporters. We observed a significant inverse correlation (ρ = −0.592; p

Christian Orthodox Church (COC) fasting is characterized by periodic abstinence from animal foods (including dairy products). We found that, despite this, older individuals adhering to COC fasting for decades did not differ in bone mineral density, bone mineral content, or prevalence of osteoporosis at five sites from non-fasting controls.The present observational study investigated whether adherence to COC fasting, characterized by periodic abstinence from animal foods (including dairy products), affects bone health and the prevalence of osteoporosis in older individuals.Participants were 200 men and women, of whom 100 had been following the fasting rules of the COC for a median of 31 years and 100 were non-fasters, all aged 50 to 78 years. Participants underwent measurements of bone mineral density (BMD) and bone mineral content (BMC) at the lumbar spine, right hip, left hip, right femoral neck, and left femoral neck; completed a 3-day food intake record and food frequency questionnaire; and provided blood samples for biochemical measurements.Fasters did not differ from non-fasters in demographic characteristics, anthropometric measures, BMD, BMC, or prevalence of osteopenia or osteoporosis at any of the five sites measured (P 0.05). Fasters had lower daily calcium intake than non-fasters (median 532 vs 659 mg, P = 0.010), daily protein intake (0.67 vs 0.71 g/kg, P = 0.028), and consumption of dairy and soy products (10.3 vs 15.3 servings per week, P 0.001). Groups did not differ in serum calcium, vitamin D, or urea concentrations.Despite lower calcium intake and lower consumption of dairy and soy products, older individuals adhering to COC fasting did not differ in BMD, BMC, or prevalence of osteoporosis from controls. Thus, periodic abstinence from dairy and, generally, animal products does not seem to compromise bone health in older individuals.

Summary: Sex determination is a unique process that allows the study of multipotent progenitors and their acquisition of sex-specific fates during differentiation of the gonad into a testis or an ovary. Using time series single-cell RNA sequencing (scRNA-seq) on ovarian Nr5a1-GFP+ somatic cells during sex determination, we identified a single population of early progenitors giving rise to both pre-granulosa cells and potential steroidogenic precursor cells. By comparing time series single-cell RNA sequencing of XX and XY somatic cells, we provide evidence that gonadal supporting cells are specified from these early progenitors by a non-sex-specific transcriptomic program before pre-granulosa and Sertoli cells acquire their sex-specific identity. In XX and XY steroidogenic precursors, similar transcriptomic profiles underlie the acquisition of cell fate but with XX cells exhibiting a relative delay. Our data provide an important resource, at single-cell resolution, for further interrogation of the molecular and cellular basis of mammalian sex determination. : Using single-cell RNA sequencing of Nr5a1-expressing gonadal somatic cells during female and male sex determination, Stévant et al. deconvoluted the cell lineage specification process and sex-specific differentiation of both the supporting and the steroidogenic cell lineages at a transcriptomic level. Keywords: single-cell RNA-seq, sex determination, ovary, testis, granulosa cell, Sertoli cells, supporting cells, progenitors, differentiation, lineage specification, cell fate decision, gonad development, gene expression, transcriptomics

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci (cis-QTLs) for the majority of genes across a wide range of human tissues. However, the interpretation of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. Here, we map interactions between computational estimates of cell type abundance and genotype to identify cell type interaction QTLs for seven cell types and show that cell type interaction eQTLs provide finer resolution to tissue specificity than bulk tissuecis-eQTLs. Analyses of genetic associations to 87 complex traits show a contribution from cell type interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.One Sentence SummaryEstimated cell type abundances from bulk RNA-seq across tissues reveal the cellular specificity of quantitative trait loci.

The number of human genomes being genotyped or sequenced increases exponentially and efficient haplotype estimation methods able to handle this amount of data are now required. Here we present a method, SHAPEIT4, which substantially improves upon other methods to process large genotype and high coverage sequencing datasets. It notably exhibits sub-linear running times with sample size, provides highly accurate haplotypes and allows integrating external phasing information such as large reference panels of haplotypes, collections of pre-phased variants and long sequencing reads. We provide SHAPEIT4 in an open source format and demonstrate its performance in terms of accuracy and running times on two gold standard datasets: the UK Biobank data and the Genome In A Bottle., Haplotype information inferred by phasing is useful in genetic and genomic analysis. Here, the authors develop SHAPEIT4, a phasing method that exhibits sub-linear running time, provides accurate haplotypes and enables integration of external phasing information.

The number of human genomes being genotyped or sequenced increases exponentially and efficient haplotype estimation methods able to handle this amount of data are now required. Here, we present a new method, SHAPEIT4, which substantially improves upon other methods to process large genotype and high coverage sequencing datasets. It notably exhibits sub-linear scaling with sample size, provides highly accurate haplotypes and allows integrating external phasing information such as large reference panels of haplotypes, collections of pre-phased variants and long sequencing reads. We provide SHAPET4 in an open source format on https://odelaneau.github.io/shapeit4/ and demonstrate its performance in terms of accuracy and running times on two gold standard datasets: the UK Biobank data and the Genome In A Bottle.

Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.

Tracking neuronal transcriptional programs Early in brain development, cortical neurons are born near the ventricles, then migrate to their functional destinations. Telley et al. used a fluorescent labeling technique to see what transcripts characterize these earliest stages of neural development. Waves of transcriptional programs are initiated, then passed by as the neuron progresses from proliferative to migratory and finally to connectivity phases. Science , this issue p. 1443

Aim To determine the impact of a functional human islet clock on insulin secretion and gene transcription. Methods Efficient circadian clock disruption was achieved in human pancreatic islet cells by small interfering RNA mediated knockdown of CLOCK. Human islet secretory function was assessed in the presence or absence of a functional circadian clock by stimulated insulin secretion assays and by continuous around the clock monitoring of basal insulin secretion. Large scale transcription analysis was accomplished by RNA sequencing followed by quantitative RT PCR analysis of selected targets. Results Circadian clock disruption resulted in a significant decrease in both acute and chronic glucose stimulated insulin secretion. Moreover basal insulin secretion by human islet cells synchronized in vitro exhibited a circadian pattern which was perturbed upon clock disruption. RNA sequencing analysis suggested alterations in 352 transcript levels upon circadian clock disruption. Among them key regulators of the insulin secretion pathway (GNAQ ATP1A1 ATP5G2 KCNJ11) and transcripts required for granule maturation and release (VAMP3 STX6 SLC30A8) were affected. Conclusions Using our newly developed experimental approach for efficient clock disruption in human pancreatic islet cells we show for the first time that a functional ß cell clock is required for proper basal and stimulated insulin secretion. Moreover clock disruption has a profound impact on the human islet transcriptome in particular on the genes involved in insulin secretion.

Motivation: In order to discover quantitative trait loci, multi-dimensional genomic datasets combining DNA-seq and ChiP-/RNA-seq require methods that rapidly correlate tens of thousands of molecular phenotypes with millions of genetic variants while appropriately controlling for multiple testing. Results: We have developed FastQTL, a method that implements a popular cis-QTL mapping strategy in a user- and cluster-friendly tool. FastQTL also proposes an efficient permutation procedure to control for multiple testing. The outcome of permutations is modeled using beta distributions trained from a few permutations and from which adjusted P-values can be estimated at any level of significance with little computational cost. The Geuvadis & GTEx pilot datasets can be now easily analyzed an order of magnitude faster than previous approaches. Availability and implementation: Source code, binaries and comprehensive documentation of FastQTL are freely available to download at http://fastqtl.sourceforge.net/ Contact: emmanouil.dermitzakis@unige.ch or olivier.delaneau@unige.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Motivation Large genomic datasets combining genotype and sequence data, such as for expression quantitative trait loci (eQTL) detection, require perfect matching between both data types. Results We described here MBV (Match BAM to VCF); a method to quickly solve sample mislabeling and detect cross-sample contamination and PCR amplification bias. Availability and Implementation MBV is implemented in C ++ as an independent component of the QTLtools software package, the binary and source codes are freely available at https://qtltools.github.io/qtltools/. Supplementary information Supplementary data are available at Bioinformatics online.

Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from 12,627 genes across 32 normal human tissue types prepared by the GTEx project. Known and new tissue specific or enriched proteins (5,499) were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode highly tissue specific proteins. Discordance in the sites of RNA expression and protein detection also revealed potential sites of synthesis and action of protein signaling molecules. Overall, these results provide an extraordinary resource, and demonstrate that understanding protein levels can provide insights into metabolism, regulation, secretome, and human diseases.SummaryQuantitative proteome study of 32 human tissues and integrated analysis with transcriptome data revealed that understanding protein levels could provide in-depth knowledge to post transcriptional or translational regulations, human metabolism, secretome, and diseases.

SummaryWhile many disease-associated variants have been identified through genome-wide association studies, their downstream molecular consequences remain unclear.To identify these effects, we performedcis-andtrans-expressionquantitative trait locus (eQTL) analysis in blood from 31,684 individuals through the eQTLGen Consortium.We observed thatcis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting our ability to usecis-eQTLs to pinpoint causal genes within susceptibility loci.In contrast, trans-eQTLs (detected for 37% of 10,317 studied trait-associated variants) were more informative. Multiple unlinked variants, associated to the same complex trait, often converged on trans-genes that are known to play central roles in disease etiology.We observed the same when ascertaining the effect of polygenic scores calculated for 1,263 genome-wide association study (GWAS) traits. Expression levels of 13% of the studied genes correlated with polygenic scores, and many resulting genes are known to drive these traits.

We apply integrative approaches to expression quantitative loci (eQTLs) from 44 tissues from the Genotype-Tissue Expression project and genome-wide association study data. About 60% of known trait-associated loci are in linkage disequilibrium with a cis-eQTL, over half of which were not found in previous large-scale whole blood studies. Applying polygenic analyses to metabolic, cardiovascular, anthropometric, autoimmune, and neurodegenerative traits, we find that eQTLs are significantly enriched for trait associations in relevant pathogenic tissues and explain a substantial proportion of the heritability (40-80%). For most traits, tissue-shared eQTLs underlie a greater proportion of trait associations, although tissue-specific eQTLs have a greater contribution to some traits, such as blood pressure. By integrating information from biological pathways with eQTL target genes and applying a gene-based approach, we validate previously implicated causal genes and pathways, and propose new variant and gene associations for several complex traits, which we replicate in the UK BioBank and BioVU., National Institutes of Health (U.S.) (Contract HHSN268201000029C)

/SummaryBackground and aims:Understanding the aetiology, clinical presentation and prognosis of type 2 diabetes (T2D) and optimizing its treatment might be facilitated by biomarkers that help predict a person’s susceptibility to the risk factors that cause diabetes or its complications, or response to treatment. The IMI DIRECT (Diabetes Research on Patient Stratification) Study is a European Union (EU) Innovative Medicines Initiative (IMI) project that seeks to test these hypotheses in two recently established epidemiological cohorts. Here, we describe the characteristics of these cohorts at baseline and at the first main follow-up examination (18-months).Materials and methods:From a sampling-frame of 24,682 European-ancestry adults in whom detailed health information was available, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm and enrolled into a prospective cohort study (n=2127) undertaken at four study centres across Europe (Cohort 1: prediabetes). We also recruited people from clinical registries with recently diagnosed T2D (n=789) into a second cohort study (Cohort 2: diabetes). The two cohorts were studied in parallel with matched protocols. Endogenous insulin secretion and insulin sensitivity were modelled from frequently sampled 75g oral glucose tolerance (OGTT) in Cohort 1 and with mixed-meal tolerance tests (MMTT) in Cohort 2. Additional metabolic biochemistry was determined using blood samples taken when fasted and during the tolerance tests. Body composition was assessed using MRI and lifestyle measures through self-report and objective methods.Results:Using ADA-2011 glycaemic categories, 33% (n=693) of Cohort 1 (prediabetes) had normal glucose regulation (NGR), and 67% (n=1419) had impaired glucose regulation (IGR). 76% of the cohort was male, age=62(6.2) years; BMI=27.9(4.0) kg/m2; fasting glucose=5.7(0.6) mmol/l; 2-hr glucose=5.9(1.6) mmol/l [mean(SD)]. At follow-up, 18.6(1.4) months after baseline, fasting glucose=5.8(0.6) mmol/l; 2-hr OGTT glucose=6.1(1.7) mmol/l [mean(SD)]. In Cohort 2 (diabetes): 65% (n=508) were lifestyle treated (LS) and 35% (n=271) were lifestyle + metformin treated (LS+MET). 58% of the cohort was male, age=62(8.1) years; BMI=30.5(5.0) kg/m2; fasting glucose=7.2(1.4)mmol/l; 2-hr glucose=8.6(2.8) mmol/l [mean(SD)]. At follow-up, 18.2(0.6) months after baseline, fasting glucose=7.8(1.8) mmol/l; 2-hr MMTT glucose=9.5(3.3) mmol/l [mean(SD)].Conclusion:The epidemiological IMI DIRECT cohorts are the most intensely characterised prospective studies of glycaemic deterioration to date. Data from these cohorts help illustrate the heterogeneous characteristics of people at risk of or with T2D, highlighting the rationale for biomarker stratification of the disease - the primary objective of the IMI DIRECT consortium.Abbreviations:ASATAbdominal subcutaneous adipose tissueDIRECTDiabetes Research on Patient StratificationEUEuropean UnionMMTTMixed-meal tolerance testMRIMagnetic resonance imaginghpfVMHigh-pass filtered vector magnitudeIAATIntra-abdominal adipose tissueIGRImpaired glucose regulationIMIInnovative Medicines InitiativeMEmultiechoNGRNormal glucose regulationOGTTOral glucose tolerance testPAPhysical activityTAATTotal abdominal adipose tissueT2DType 2 Diabetes

Circadian regulation of transcriptional processes has a broad impact on cell metabolism. Here, we compared the diurnal transcriptome of human skeletal muscle conducted on serial muscle biopsies in vivo with profiles of human skeletal myotubes synchronized in vitro. More extensive rhythmic transcription was observed in human skeletal muscle compared to in vitro cell culture as a large part of the in vivo mRNA rhythmicity was lost in vitro. siRNA-mediated clock disruption in primary myotubes significantly affected the expression of ~8% of all genes, with impact on glucose homeostasis and lipid metabolism. Genes involved in GLUT4 expression, translocation and recycling were negatively affected, whereas lipid metabolic genes were altered to promote activation of lipid utilization. Moreover, basal and insulin-stimulated glucose uptake were significantly reduced upon CLOCK depletion. Our findings suggest an essential role for the circadian coordination of skeletal muscle glucose homeostasis and lipid metabolism in humans.

Summary: The gonad is a unique biological system for studying cell-fate decisions. However, major questions remain regarding the identity of somatic progenitor cells and the transcriptional events driving cell differentiation. Using time-series single-cell RNA sequencing on XY mouse gonads during sex determination, we identified a single population of somatic progenitor cells prior to sex determination. A subset of these progenitors differentiates into Sertoli cells, a process characterized by a highly dynamic genetic program consisting of sequential waves of gene expression. Another subset of multipotent cells maintains their progenitor state but undergoes significant transcriptional changes restricting their competence toward a steroidogenic fate required for the differentiation of fetal Leydig cells. Our findings confirm the presence of a unique multipotent progenitor population in the gonadal primordium that gives rise to both supporting and interstitial lineages. These also provide the most granular analysis of the transcriptional events occurring during testicular cell-fate commitment.

Microsatellite instability (MSI) leads to accumulation of an excessive number of mutations in the genome, mostly small insertions and deletions. MSI colorectal cancers (CRCs), however, also contain more point mutations than microsatellite-stable (MSS) tumors, yet they have not been as comprehensively studied. To identify candidate driver genes affected by point mutations in MSI CRC, we ranked genes based on mutation significance while correcting for replication timing and gene expression utilizing an algorithm, MutSigCV. Somatic point mutation data from the exome kit-targeted area from 24 exome-sequenced sporadic MSI CRCs and respective normals, and 12 whole-genome-sequenced sporadic MSI CRCs and respective normals were utilized. The top 73 genes were validated in 93 additional MSI CRCs. The MutSigCV ranking identified several well-established MSI CRC driver genes and provided additional evidence for previously proposed CRC candidate genes as well as shortlisted genes that have to our knowledge not been linked to CRC before. Two genes, SMARCB1 and STK38L, were also functionally scrutinized, providing evidence of a tumorigenic role, for SMARCB1 mutations in particular. © 2018 The Authors. Published under the terms of the CC BY 4.0 license

Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole-genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge. Unbiased CRISPR-Cas9 knockout and activation screens identified in total 79 genes within AI peaks regulating cell growth. Genetic and functional data implicate loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers., In this study the authors examine the allelic imbalance (AI) landscape of colorectal cancer, reporting loss of TP53 as a driver of AI. They use CRISPR-Cas9 screens to identify 79 genes (within AI regions) regulating cell growth and identify a network of transcription factors that may contribute to colorectal tumorigenesis.