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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci ( P  < 5 × 10 −8 ), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis. A genome-wide association study and Metabochip meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis. Genetic correlates of obesity In the second of two Articles in this issue from the GIANT Consortium, Elizabeth Speliotes and collegues conducted a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), commonly used to define obesity and assess adiposity, to find 97 BMI-associated loci, of which 56 were novel. Many of these loci have significant effects on other metabolic phenotypes. The 97 loci account for about 2.7% of BMI variation, and genome-wide estimates suggest common variation accounts for more than 20% of BMI variation. Pathway analyses implicate the central nervous system in obesity susceptibility including synaptic function, glutamate signaling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury 1 – 4 . These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries 5 . Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction. A multi-ancestry meta-regression study analyses diverse genome-wide association studies and genome loci associated with tobacco and alcohol use.

Ali Gharavi and colleagues report a genome-wide association analysis of IgA nephropathy in over 20,000 individuals of European and East Asian ancestry. They identify genome-wide significant signals at three new loci near VAV3 , CARD9 and ITGAM - ITGAX and correlations between genetic risk and pathogen diversity. We performed a genome-wide association study (GWAS) of IgA nephropathy (IgAN), the most common form of glomerulonephritis, with discovery and follow-up in 20,612 individuals of European and East Asian ancestry. We identified six new genome-wide significant associations, four in ITGAM - ITGAX , VAV3 and CARD9 and two new independent signals at HLA-DQB1 and DEFA . We replicated the nine previously reported signals, including known SNPs in the HLA-DQB1 and DEFA loci. The cumulative burden of risk alleles is strongly associated with age at disease onset. Most loci are either directly associated with risk of inflammatory bowel disease (IBD) or maintenance of the intestinal epithelial barrier and response to mucosal pathogens. The geospatial distribution of risk alleles is highly suggestive of multi-locus adaptation, and genetic risk correlates strongly with variation in local pathogens, particularly helminth diversity, suggesting a possible role for host–intestinal pathogen interactions in shaping the genetic landscape of IgAN.

ObjectiveSystemic lupus erythematosus (SLE), an autoimmune disorder, has been associated with nearly 100 susceptibility loci. Nevertheless, these loci only partially explain SLE heritability and their putative causal variants are rarely prioritised, which make challenging to elucidate disease biology. To detect new SLE loci and causal variants, we performed the largest genome-wide meta-analysis for SLE in East Asian populations.MethodsWe newly genotyped 10 029 SLE cases and 180 167 controls and subsequently meta-analysed them jointly with 3348 SLE cases and 14 826 controls from published studies in East Asians. We further applied a Bayesian statistical approach to localise the putative causal variants for SLE associations.ResultsWe identified 113 genetic regions including 46 novel loci at genome-wide significance (p<5×10−8). Conditional analysis detected 233 association signals within these loci, which suggest widespread allelic heterogeneity. We detected genome-wide associations at six new missense variants. Bayesian statistical fine-mapping analysis prioritised the putative causal variants to a small set of variants (95% credible set size ≤10) for 28 association signals. We identified 110 putative causal variants with posterior probabilities ≥0.1 for 57 SLE loci, among which we prioritised 10 most likely putative causal variants (posterior probability ≥0.8). Linkage disequilibrium score regression detected genetic correlations for SLE with albumin/globulin ratio (rg=−0.242) and non-albumin protein (rg=0.238).ConclusionThis study reiterates the power of large-scale genome-wide meta-analysis for novel genetic discovery. These findings shed light on genetic and biological understandings of SLE.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures ( P  < 5 × 10 −8 ). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms. Genome-wide association meta-analyses of waist-to-hip ratio adjusted for body mass index in more than 224,000 individuals identify 49 loci, 33 of which are new and many showing significant sexual dimorphism with a stronger effect in women; pathway analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution. Cardiometabolic traits linked to body fat distribution In the first of a pair of Articles in this issue from the GIANT Consortium, genome-wide association meta-analyses of waist and hip circumference-related traits in more than 200,000 individuals have been used to identify 49 loci — 33 of them new — associated with waist-to-hip ratio adjusted for body mass index and an additional 19 loci associated with related waist and hip circumference measures. A subset of these loci shows significant sexual dimorphism, with many showing a stronger effect in women. Analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms and offer potential targets for interventions in the risks associated with abdominal fat accumulation.

Genome-wide association studies are used to identify common genetic variants that affect the structure of selected subcortical regions of the human brain; their identification provides insight into the causes of variability in brain development and may help to determine mechanisms of neuropsychiatric dysfunction. Genetic variants that alter brain development This genome-wide association study of 30,717 individuals identifies common genetic variants that affect the structure of selected subcortical regions of the brain known to be involved in functions associated with movement, learning, memory and motivation. The results provide insight into the causes of variability in human brain development and may help elucidate mechanisms of neuropsychiatric dysfunction. Of particular interest are six novel genetic loci influencing the volumes of the putamen, caudate nucleus and global head size. The highly complex structure of the human brain is strongly shaped by genetic influences 1 . Subcortical brain regions form circuits with cortical areas to coordinate movement 2 , learning, memory 3 and motivation 4 , and altered circuits can lead to abnormal behaviour and disease 2 . To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume 5 and intracranial volume 6 . These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10 −33 ; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Genetic variants located within the 12p13.33/RAD52 locus have been associated with lung squamous cell carcinoma (LUSC). Here, within 5,947 UADT cancers and 7,789 controls from 9 different studies, we found rs10849605, a common intronic variant in RAD52, to be also associated with upper aerodigestive tract (UADT) squamous cell carcinoma cases (OR = 1.09, 95% CI: 1.04-1.15, p = 6x10(-4)). We additionally identified rs10849605 as a RAD52 cis-eQTL inUADT(p = 1x10(-3)) and LUSC (p = 9x10(-4)) tumours, with the UADT/LUSC risk allele correlated with increased RAD52 expression levels. The 12p13.33 locus, encompassing rs10849605/RAD52, was identified as a significant somatic focal copy number amplification in UADT(n = 374, q-value = 0.075) and LUSC (n = 464, q-value = 0.007) tumors and correlated with higher RAD52 tumor expression levels (p = 6x10(-48) and p = 3x10(-29) in UADT and LUSC, respectively). In combination, these results implicate increased RAD52 expression in both genetic susceptibility and tumorigenesis of UADT and LUSC tumors.

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.

Microglia and central nervous system (CNS)-associated macrophages (CAMs), such as perivascular and meningeal macrophages, are implicated in virtually all diseases of the CNS. However, little is known about their cell-type-specific roles in the absence of suitable tools that would allow for functional discrimination between the ontogenetically closely related microglia and CAMs. To develop a new microglia gene targeting model, we first applied massively parallel single-cell analyses to compare microglia and CAM signatures during homeostasis and disease and identified hexosaminidase subunit beta ( Hexb) as a stably expressed microglia core gene, whereas other microglia core genes were substantially downregulated during pathologies. Next, we generated Hexb tdTomato mice to stably monitor microglia behavior in vivo. Finally, the Hexb locus was employed for tamoxifen-inducible Cre-mediated gene manipulation in microglia and for fate mapping of microglia but not CAMs. In sum, we provide valuable new genetic tools to specifically study microglia functions in the CNS. Microglia have key roles in central nervous system (CNS) disease and homeostasis but their study can be challenging. Prinz and colleagues identify hexosaminidase subunit beta ( Hexb ) to be specifically expressed by microglia and stable even under inflammatory conditions.

Chronic kidney disease (CKD) affects ~10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assemble genome-wide association studies of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals of diverse ancestry. We identify 127 distinct association signals with homogeneous effects on eGFR across ancestries and enrichment in genomic annotations including kidney-specific histone modifications. Fine-mapping reveals 40 high-confidence variants driving eGFR associations and highlights putative causal genes with cell-type specific expression in glomerulus, and in proximal and distal nephron. Mendelian randomisation supports causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure and hypertension. These results define novel molecular mechanisms and putative causal genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development. Estimated glomerular filtration rate (eGFR) is a measure of kidney function used to define chronic kidney disease. Here, Morris et al. perform trans-ethnic genome-wide meta-analyses for eGFR in 312,468 individuals and identify novel loci and downstream putative causal genes.