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Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP's comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results.

Scalable sequence–function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.

Human large-scale genetic association studies have identified sequence variations at thousands of genetic risk loci that are more common in patients with diverse metabolic disease compared to healthy controls. While these genetic associations have been replicated in multiple large cohorts and sometimes can explain up to 50% of heritability, the molecular and cellular mechanisms affected by common genetic variation associated with metabolic disease remains mostly unknown. A variety of new genome-wide data types in conjunction with novel biostatistical and computational analytical methodologies and foundational experimental technologies are paving the way for a principled approach to systematic Variants – to – Function (V2F) studies for metabolic diseases, turning associated regions into causal variants, cell types and states of action, effector genes, and cellular and physiological mechanisms. Identification of new target genes and cellular programs for metabolic risk loci will improve mechanistic understanding of disease biology and identification of novel therapeutic strategies.

The obesity-linked FTO regulatory circuitry shows cross-species molecular, cellular, metabolic, and organismal conservation., Variants in FTO have the strongest association with obesity; however, it is still unclear how those noncoding variants mechanistically affect whole-body physiology. We engineered a deletion of the rs1421085 conserved cis-regulatory module (CRM) in mice and confirmed in vivo that the CRM modulates Irx3 and Irx5 gene expression and mitochondrial function in adipocytes. The CRM affects molecular and cellular phenotypes in an adipose depot–dependent manner and affects organismal phenotypes that are relevant for obesity, including decreased high-fat diet–induced weight gain, decreased whole-body fat mass, and decreased skin fat thickness. Last, we connected the CRM to a genetically determined effect on steroid patterns in males that was dependent on nutritional challenge and conserved across mice and humans. Together, our data establish cross-species conservation of the rs1421085 regulatory circuitry at the molecular, cellular, metabolic, and organismal level, revealing previously unknown contextual dependence of the variant’s action.

Obesity genes working together The biological causes of obesity are not well understood. Sobreira et al. examined the chromatin interactions between key genes in a locus known for its associations with obesity in human patients. In addition to directly interrogating the connections between these genes and examining the mechanisms that regulate their activity, the authors used mouse models to study the target genes' effects on both adipose tissue and brain cells that play a role in regulating dietary preferences. Science , abf1008, this issue p. 1085

Summary Skeletal and glycemic traits have shared etiology, but the underlying genetic factors remain largely unknown. To identify genetic loci that may have pleiotropic effects, we studied Genome-wide association studies (GWASs) for bone mineral density and glycemic traits and identified a bivariate risk locus at 3q21. Using sequence and epigenetic modeling, we prioritized an adenylate cyclase 5 (ADCY5) intronic causal variant, rs56371916. This SNP changes the binding affinity of SREBP1 and leads to differential ADCY5 gene expression, altering the chromatin landscape from poised to repressed. These alterations result in bone- and type 2 diabetes-relevant cell-autonomous changes in lipid metabolism in osteoblasts and adipocytes. We validated our findings by directly manipulating the regulator SREBP1, the target gene ADCY5, and the variant rs56371916, which together imply a novel link between fatty acid oxidation and osteoblast differentiation. Our work, by systematic functional dissection of pleiotropic GWAS loci, represents a framework to uncover biological mechanisms affecting pleiotropic traits., Graphical abstract, Highlights • 3q21 variants are associated with type 2 diabetes and increased bone mineral density • 3q21 variants affect chromatin accessibility in mesenchymal cells • rs56371916 is a 3q21 causal variant and ADCY5 its target in adipocytes and osteoblasts • ADCY5 and rs56371916 affect lipid oxidation processes in adipocytes and osteoblasts, Nasa Sinnott-Armstrong and colleagues identify a pleiotropic risk locus at 3q21 that is associated with type 2 diabetes (T2D) and greater bone mineral density (BMD) and its associated cell-autonomous mechanisms in adipocytes and osteoblasts. Together, these findings provide a possible explanation for the perplexing finding that individuals with T2D have higher BMD but greater susceptibility to bone fracture.

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the relationship between mean adipocyte area and obesity-related traits, and identify genetic factors associated with adipocyte cell size. To perform the first large-scale study of automatic adipocyte phenotyping using both histological and genetic data, we developed a deep learning-based method, the Adipocyte U-Net, to rapidly derive mean adipocyte area estimates from histology images. We validate our method using three state-of-the-art approaches; CellProfiler, Adiposoft and floating adipocytes fractions, all run blindly on two external cohorts. We observe high concordance between our method and the state-of-the-art approaches (Adipocyte U-net vs. CellProfiler: R2visceral = 0.94, P < 2.2 × 10−16, R2subcutaneous = 0.91, P < 2.2 × 10−16), and faster run times (10,000 images: 6mins vs 3.5hrs). We applied the Adipocyte U-Net to 4 cohorts with histology, genetic, and phenotypic data (total N = 820). After meta-analysis, we found that mean adipocyte area positively correlated with body mass index (BMI) (Psubq = 8.13 × 10−69, βsubq = 0.45; Pvisc = 2.5 × 10−55, βvisc = 0.49; average R2 across cohorts = 0.49) and that adipocytes in subcutaneous depots are larger than their visceral counterparts (Pmeta = 9.8 × 10−7). Lastly, we performed the largest GWAS and subsequent meta-analysis of mean adipocyte area and intra-individual adipocyte variation (N = 820). Despite having twice the number of samples than any similar study, we found no genome-wide significant associations, suggesting that larger sample sizes and a homogenous collection of adipose tissue are likely needed to identify robust genetic associations., Author summary Fundamental aspects of biology such as how the size or number of adipocytes relates to obesity and cardiometabolic health are still unanswered. To answer such questions, fast, accurate and automated measurements need to be acquired, free from human biases. Glastonbury et al., 2020 describe a novel machine learning method to perform rapid acquisition of adipocyte area estimates from histological imaging data. Using these imaging derived phenotypes, Glastonbury et al., 2020 assess the relationship between adipocyte size and a range of cardio-metabolic comorbidities, demonstrating that adipocyte size can vary depending on where adipose is stored throughout the body. By tying genetics with imaging data, Glastonbury et al., 2020 were able to demonstrate that previous findings associating adipocyte size with Type 2 Diabetes variants, are likely to be false positives. This study provides a means of being able to scale up GWAS type analyses to imaging derived phenotypes.

We have prioritised a single nucleotide polymorphism (SNP) rs2645294 as one candidate functional SNP in the TBX15-WARS2 waist-hip-ratio locus using posterior probability analysis. This SNP is located in the 3′ untranslated region of the WARS2 (tryptophanyl tRNA synthetase 2, mitochondrial) gene with which it has an expression quantitative trait in subcutaneous white adipose tissue. We show that transcripts of the WARS2 gene in a human white adipose cell line, heterozygous for the rs2645294 SNP, showed allelic imbalance. We tested whether the rs2645294 SNP altered WARS2 RNA stability using three different methods: actinomycin-D inhibition and RNA decay, mature and nascent RNA analysis and luciferase reporter assays. We found no evidence of a difference in RNA stability between the rs2645294 alleles indicating that the allelic expression imbalance was likely due to transcriptional regulation., Highlights • SNP rs2645294 was identified by PPA as one potential functional SNP for WHRadjBMI associated with the TBX15/WARS2 locus • SNP rs2645294 has an expression QTL for the WARS2 gene • Transcripts containing SNP rs2645294 showed allelic expression imbalance in a heterozygous human white adipose cell line • SNP rs2645294 was a potential WARS2 3’UTR gene regulatory SNP • No difference in allelic RNA stability was found, imbalance likely originating from transcriptional regulatory mechanisms

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of regulatory genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single or small sets of tissues. Here, we have reconstructed networks that capture a much more complete set of regulatory relationships, specifically including regulation of relative isoform abundance and splicing, and tissue-specific connections unique to each of a diverse set of tissues. Using the Genotype-Tissue Expression (GTEx) project v6 RNA-sequencing data across 44 tissues in 449 individuals, we evaluated shared and tissue-specific network relationships. First, we developed a framework called Transcriptome Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the complex interplay between the regulation of splicing and transcription. We built TWNs for sixteen tissues, and found that hubs with isoform node neighbors in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome, and providing a set of candidate shared and tissue-specific regulatory hub genes. Next, we used a Bayesian biclustering model that identifies network edges between genes with co-expression in a single tissue to reconstruct tissue-specific networks (TSNs) for 27 distinct GTEx tissues and for four subsets of related tissues. Using both TWNs and TSNs, we characterized gene co-expression patterns shared across tissues. Finally, we found genetic variants associated with multiple neighboring nodes in our networks, supporting the estimated network structures and identifying 33 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships between genes in the human transcriptome, including tissue-specificity of gene co-expression, regulation of splicing, and the coordinated impact of genetic variation on transcription.

Genome-wide epigenomic maps revealed millions of regions showing signatures of enhancers, promoters, and other gene-regulatory elements1. However, high-throughput experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited in their scale and length of regions tested. Here, we present a new method, HiDRA (High-Definition Reporter Assay), that overcomes these limitations by combining components of Sharpr-MPRA2 and STARR-Seq3 with genome-wide selection of accessible regions from ATAC-Seq4. We used HiDRA to test ~7 million DNA fragments preferentially selected from accessible chromatin in the GM12878 lymphoblastoid cell line. By design, accessibility-selected fragments were highly overlapping (up to 370 per region), enabling us to pinpoint driver regulatory nucleotides by exploiting subtle differences in reporter activity between partially-overlapping fragments, using a new machine learning model SHARPR2. Our resulting maps include ~65,000 regions showing significant enhancer function and enriched for endogenous active histone marks (including H3K9ac, H3K27ac), regulatory sequence motifs, and regions bound by immune regulators. Within them, we discover ~13,000 high-resolution driver elements enriched for regulatory motifs and evolutionarily-conservednucleotides, and help predict causal genetic variants underlying disease from genome-wide association studies. Overall, HiDRA provides a general, scalable, high-throughput, and high-resolution approach for experimental dissection of regulatory regions and driver nucleotides in the context of human biology and disease.

Genome-wide association studies identified numerous disease risk loci. Delineating molecular mechanisms influenced by cis-regulatory variants is essential to understand gene regulation and ultimately disease pathophysiology. Combining bioinformatics and public domain chromatin information with quantitative proteomics supports prediction of cis-regulatory variants and enabled identification of allele-dependent binding of both, transcription factors and coregulators at the type 2 diabetes associated PPARG locus. We found rs7647481A nonrisk allele binding of Yin Yang 1 (YY1), confirmed by allele-specific chromatin immunoprecipitation in primary adipocytes. Quantitative proteomics also found the coregulator RING1 and YY1 binding protein (RYBP) whose mRNA levels correlate with improved insulin sensitivity in primary adipose cells carrying the rs7647481A nonrisk allele. Our findings support a concept with diverse cis-regulatory variants contributing to disease pathophysiology at one locus. Proteome-wide identification of both, transcription factors and coregulators, can profoundly improve understanding of mechanisms underlying genetic associations.

Genome‐wide association studies (GWASs) have revealed numerous loci for areal bone mineral density (aBMD). We completed the first GWAS meta‐analysis (n = 15,275) of lumbar spine volumetric BMD (vBMD) measured by quantitative computed tomography (QCT), allowing for examination of the trabecular bone compartment. SNPs that were significantly associated with vBMD were also examined in two GWAS meta‐analyses to determine associations with morphometric vertebral fracture (n = 21,701) and clinical vertebral fracture (n = 5893). Expression quantitative trait locus (eQTL) analyses of iliac crest biopsies were performed in 84 postmenopausal women, and murine osteoblast expression of genes implicated by eQTL or by proximity to vBMD‐associated SNPs was examined. We identified significant vBMD associations with five loci, including: 1p36.12, containing WNT4 and ZBTB40 ; 8q24, containing TNFRSF11B ; and 13q14, containing AKAP11 and TNFSF11 . Two loci (5p13 and 1p36.12) also contained associations with radiographic and clinical vertebral fracture, respectively. In 5p13, rs2468531 (minor allele frequency [MAF] = 3%) was associated with higher vBMD (β = 0.22, p = 1.9 × 10–8) and decreased risk of radiographic vertebral fracture (odds ratio [OR] = 0.75; false discovery rate [FDR] p = 0.01). In 1p36.12, rs12742784 (MAF = 21%) was associated with higher vBMD (β = 0.09, p = 1.2 × 10–10) and decreased risk of clinical vertebral fracture (OR = 0.82; FDR p = 7.4 × 10–4). Both SNPs are noncoding and were associated with increased mRNA expression levels in human bone biopsies: rs2468531 with SLC1A3 (β = 0.28, FDR p = 0.01, involved in glutamate signaling and osteogenic response to mechanical loading) and rs12742784 with EPHB2 (β = 0.12, FDR p = 1.7 × 10–3, functions in bone‐related ephrin signaling). Both genes are expressed in murine osteoblasts. This is the first study to link SLC1A3 and EPHB2 to clinically relevant vertebral osteoporosis phenotypes. These results may help elucidate vertebral bone biology and novel approaches to reducing vertebral fracture incidence. © 2016 American Society for Bone and Mineral Research.

OBJECTIVE Adiponectin (APM1, ACDC) is an adipocyte-derived protein with downregulated expression in obesity and insulin-resistant states. Several potentially regulatory single nucleotide polymorphisms (SNPs) within the APM1 gene promoter region have been associated with circulating adiponectin levels. None of them have been functionally characterized in adiponectin-expressing cells. Hence, we investigated three SNPs (rs16861194, rs17300539, and rs266729) for their influence on adiponectin promoter activity and their association with circulating adiponectin levels. RESEARCH DESIGN AND METHODS Basal and rosiglitazone-induced promoter activity of different SNP combinations (haplotypes) was analyzed in 3T3-L1 adipocytes using luciferase reporter gene assays and DNA binding studies comparing all possible APM1 haplotypes. This functional approach was complemented with analysis of epidemiological population-based data of 1,692 participants of the MONICA/KORA S123 cohort and 696 participants from the KORA S4 cohort for SNP and haplotype association with circulating adiponectin levels. RESULTS Major to minor allele replacements of the three SNPs revealed significant effects on promoter activity in luciferase assays. Particularly, a minor variant in rs16861194 resulted in reduced basal and rosiglitazone-induced promoter activity and hypoadiponectinemia in the epidemiological datasets. The haplotype with the minor allele in all three SNPs showed a complete loss of promoter activity, and no subject carried this haplotype in either of the epidemiological samples (combined P value for statistically significant difference from a random sample was 0.006). CONCLUSIONS Our results clearly demonstrate that promoter variants associated with hypoadiponectinemia in humans substantially affect adiponectin promoter activity in adipocytes. Our combination of functional experiments with epidemiological data overcomes the drawback of each approach alone.

Background Genomewide association studies can be used to identify disease-relevant genomic regions, but interpretation of the data is challenging. The FTO region harbors the strongest genetic association with obesity, yet the mechanistic basis of this association remains elusive. Methods We examined epigenomic data, allelic activity, motif conservation, regulator expression, and gene coexpression patterns, with the aim of dissecting the regulatory circuitry and mechanistic basis of the association between the FTO region and obesity. We validated our predictions with the use of directed perturbations in samples from patients and from mice and with endogenous CRISPR-Cas9 genome editing in samples from patients. Results Our data indicate that the FTO allele associated with obesity represses mitochondrial thermogenesis in adipocyte precursor cells in a tissue-autonomous manner. The rs1421085 T-to-C single-nucleotide variant disrupts a conserved motif for the ARID5B repressor, which leads to derepression of a potent preadipocyte enhancer and a doubling of IRX3 and IRX5 expression during early adipocyte differentiation. This results in a cell-autonomous developmental shift from energy-dissipating beige (brite) adipocytes to energy-storing white adipocytes, with a reduction in mitochondrial thermogenesis by a factor of 5, as well as an increase in lipid storage. Inhibition of Irx3 in adipose tissue in mice reduced body weight and increased energy dissipation without a change in physical activity or appetite. Knockdown of IRX3 or IRX5 in primary adipocytes from participants with the risk allele restored thermogenesis, increasing it by a factor of 7, and overexpression of these genes had the opposite effect in adipocytes from nonrisk-allele carriers. Repair of the ARID5B motif by CRISPR-Cas9 editing of rs1421085 in primary adipocytes from a patient with the risk allele restored IRX3 and IRX5 repression, activated browning expression programs, and restored thermogenesis, increasing it by a factor of 7. Conclusions Our results point to a pathway for adipocyte thermogenesis regulation involving ARID5B, rs1421085, IRX3, and IRX5, which, when manipulated, had pronounced pro-obesity and anti-obesity effects. (Funded by the German Research Center for Environmental Health and others.).

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease., National Human Genome Research Institute (U.S.) (RC1HG005334), National Human Genome Research Institute (U.S.) (R01HG004037), National Human Genome Research Institute (U.S.) (R01HG004037-S1), National Human Genome Research Institute (U.S.) (RO1NS078839), National Science Foundation (U.S.) (CAREER Award 1254200)

SummaryGenome-wide association studies have revealed numerous risk loci associated with diverse diseases. However, identification of disease-causing variants within association loci remains a major challenge. Divergence in gene expression due to cis-regulatory variants in noncoding regions is central to disease susceptibility. We show that integrative computational analysis of phylogenetic conservation with a complexity assessment of co-occurring transcription factor binding sites (TFBS) can identify cis-regulatory variants and elucidate their mechanistic role in disease. Analysis of established type 2 diabetes risk loci revealed a striking clustering of distinct homeobox TFBS. We identified the PRRX1 homeobox factor as a repressor of PPARG2 expression in adipose cells and demonstrate its adverse effect on lipid metabolism and systemic insulin sensitivity, dependent on the rs4684847 risk allele that triggers PRRX1 binding. Thus, cross-species conservation analysis at the level of co-occurring TFBS provides a valuable contribution to the translation of genetic association signals to disease-related molecular mechanisms.

Background Type 2 immune responses directed by Th2 cells and characterized by the signature cytokines IL4, IL5, and IL13 play major pathogenic roles in atopic diseases. Single nucleotide polymorphisms in the human Th2 cytokine locus in particular in a locus control region within the DNA repair gene RAD50, containing several RAD50 DNase1-hypersensitive sites (RHS), have been robustly associated with atopic traits in genome-wide association studies (GWAS). Functional variants in IL13 have been intensely studied, whereas no causative variants for the IL13-independent RAD50 signal have been identified yet. This study aimed to characterize the functional impact of the atopy-associated polymorphism rs2240032 located in the human RHS7 on cis-regulatory activity and differential binding of transcription factors. Methods Differential transcription factor binding was analyzed by electrophoretic mobility shift assays (EMSAs) with Jurkat T-cell nuclear extracts. Identification of differentially binding factors was performed using mass spectrometry (LC-MS/MS). Reporter vector constructs carrying either the major or minor allele of rs2240032 were tested for regulating transcriptional activity in Jurkat and HeLa cells. Results The variant rs2240032 impacts transcriptional activity and allele-specific binding of SMAD3, SP1, and additional putative protein complex partners. We further demonstrate that rs2240032 is located in an RHS7 subunit which itself encompasses repressor activity and might be important for the fine-tuning of transcription regulation within this region. Conclusion The human RHS7 critically contributes to the regulation of gene transcription, and the common atopy-associated polymorphism rs2240032 impacts transcriptional activity and transcription factor binding.

This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported).-- et al., Genome-wide association studies (GWAS) identified the MEIS1 locus for Restless Legs Syndrome (RLS), but causal single nucleotide polymorphisms (SNPs) and their functional relevance remain unknown. This locus contains a large number of highly conserved noncoding regions (HCNRs) potentially functioning as cis-regulatory modules. We analyzed these HCNRs for allele-dependent enhancer activity in zebrafish and mice and found that the risk allele of the lead SNP rs12469063 reduces enhancer activity in the Meis1 expression domain of the murine embryonic ganglionic eminences (GE). CREB1 binds this enhancer and rs12469063 affects its binding in vitro. In addition, MEIS1 target genes suggest a role in the specification of neuronal progenitors in the GE, and heterozygous Meis1-deficient mice exhibit hyperactivity, resembling the RLS phenotype. Thus, in vivo and in vitro analysis of a common SNP with small effect size showed allele-dependent function in the prospective basal ganglia representing the first neurodevelopmental region implicated in RLS., The project was supported by Fritz-Thyssen-Stiftung, Cologne, Germany (10.09.2.146; 10.12.2.183), KKF-TUM (8766156), DAAD (0811963), and COST (“HOX and TALE homeoproteins in Development and Disease”). B.S. was partially supported by DFG grants (WI 1820/4-1; WI 1820/5-1) and a TUM-Excellence stipend. The KORA study was financed by the Helmholtz Zentrum München, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria. KORA research was supported within the Munich Center of Health Sciences (MC Health), Ludwig-Maximilians-Universität, as part of LMUinnovativ. J.L.G.-S. and F.C. acknowledge funding of the Spanish and the Andalusian Governments and the Feder program for grants (BFU2010-14839, BFU2009-07044, CSD2007-00008, and Proyectos de Excelencia CVI-3488 and CVI 2658). This work was funded in part by a grant from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD), to the German Mouse Clinic (Infrafrontier: 01KX1012), to the German Center for Neurodegenerative Diseases (DZNE), Germany; by the Initiative and Networking Fund of the Helmholtz Association in the framework of the Helmholtz Alliance for Mental Research in an Ageing Society (HA-215); and the Munich Cluster for Systems Neurology (EXC 1010 SyNergy) and its Collaborative Research Center (CRC) 870/2 “Assembly and Function of Neuronal Circuits.”

The transcriptional co-activator BOB.1/OBF.1 was originally identified in B cells and is constitutively expressed throughout B cell development. BOB.1/OBF.1 associates with the transcription factors Oct1 and Oct2, thereby enhancing octamer-dependent transcription. In contrast, in T cells, BOB.1/OBF.1 expression is inducible by treatment of cells with PMA/Ionomycin or by antigen receptor engagement, indicating a marked difference in the regulation of BOB.1/OBF.1 expression in B versus T cells. The molecular mechanisms underlying the differential expression of BOB.1/OBF.1 in T and B cells remain largely unknown. Therefore, the present study focuses on mechanisms controlling the transcriptional regulation of BOB.1/OBF.1 and Oct2 in T cells. We show that both calcineurin- and \(NF-\kappa B\)-inhibitors efficiently attenuate the expression of BOB.1/OBF.1 and Oct2 in T cells. In silico analyses of the BOB.1/OBF.1 promoter revealed the presence of previously unappreciated combined NFAT/\(NF-\kappa B\) sites. An array of genetic and biochemical analyses illustrates the involvement of the \(Ca^{2+}\)/calmodulin-dependent phosphatase calcineurin as well as NFAT and \(NF-\kappa B\) transcription factors in the transcriptional regulation of octamer-dependent transcription in T cells. Conclusively, impaired expression of BOB.1/OBF.1 and Oct2 and therefore a hampered octamer-dependent transcription may participate in T cell-mediated immunodeficiency caused by the deletion of NFAT or \(NF-\kappa B\) transcription factors.

A full list of authors and affiliations appears on page 5 of this article., The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF ≤ 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants, as well as rare, population-specific, coding variants. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD (rs11692564(T), MAF = 1.6%, replication effect size = +0.20 s.d., Pmeta = 2 × 10-14), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 × 10-11; ncases = 98,742 and ncontrols = 409,511). Using an En1cre/flox mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 × 10-11). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population., peer-reviewed

Aims/hypothesisPolymorphisms in the transcription factor 7-like 2 (TCF7L2) gene have been shown to display a powerful association with type 2 diabetes. The aim of the present study was to evaluate metabolic alterations in carriers of a common TCF7L2 risk variant.MethodsSeventeen non-diabetic subjects carrying the T risk allele at the rs7903146 TCF7L2 locus and 24 subjects carrying no risk allele were submitted to intravenous glucose tolerance test and euglycemic-hyperinsulinemic clamp. Plasma samples were analysed for concentrations of 163 metabolites through targeted mass spectrometry.ResultsTCF7L2 risk allele carriers had a reduced first-phase insulin response and normal insulin sensitivity. Under fasting conditions, carriers of TCF7L2 rs7903146 exhibited a non-significant increase of plasma sphingomyelins (SMs), phosphatidylcholines (PCs) and lysophosphatidylcholines (lysoPCs) species. A significant genotype effect was detected in response to challenge tests in 6 SMs (C16:0, C16:1, C18:0, C18:1, C24:0, C24:1), 5 hydroxy-SMs (C14:1, C16:1, C22:1, C22:2, C24:1), 4 lysoPCs (C14:0, C16:0, C16:1, C17:0), 3 diacyl-PCs (C28:1, C36:6, C40:4) and 4 long-chain acyl-alkyl-PCs (C40:2, C40:5, C44:5, C44:6).DiscussionPlasma metabolomic profiling identified alterations of phospholipid metabolism in response to challenge tests in subjects with TCF7L2 rs7903146 genotype. This may reflect a genotype-mediated link to early metabolic abnormalities prior to the development of disturbed glucose tolerance.

Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes., Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.