Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterisation of African genetic diversity is needed. The African Genome Variation Project (AGVP) provides a resource to help design, implement and interpret genomic studies in sub-Saharan Africa (SSA) and worldwide. The AGVP represents dense genotypes from 1,481 and whole genome sequences (WGS) from 320 individuals across SSA. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across SSA. We identify new loci under selection, including for malaria and hypertension. We show that modern imputation panels can identify association signals at highly differentiated loci across populations in SSA. Using WGS, we show further improvement in imputation accuracy supporting efforts for large-scale sequencing of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa, showing for the first time that such designs are feasible.

Objective To conduct a genome-wide association study (GWAS) of anorexia nervosa and to calculate genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Method Following uniform quality control and imputation using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, we performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression (LDSC) was used to calculate genome-wide common variant heritability [ hSNP2, partitioned heritability, and genetic correlations (rg)] between anorexia nervosa and other phenotypes. Results Results were obtained for 10,641,224 single nucleotide polymorphisms (SNPs) and insertion-deletion variants with minor allele frequency > 1% and imputation quality scores > 0.6. The hSNP2 of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. We identified one genome-wide significant locus on chromosome 12 (rs4622308, p=4.3×10−9) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high density lipoprotein (HDL) cholesterol, and significant negative genetic correlations between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes. Conclusions Anorexia nervosa is a complex heritable phenotype for which we have found the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. Our results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

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Back pain is a common and debilitating disorder with largely unknown underlying biology. Here we report a genome-wide association study of back pain using diagnoses assigned in clinical practice; dorsalgia (119,100 cases, 909,847 controls) and intervertebral disc disorder (IDD) (58,854 cases, 922,958 controls). We identify 41 variants at 33 loci. The most significant association (ORIDD = 0.92, P = 1.6 × 10−39; ORdorsalgia = 0.92, P = 7.2 × 10−15) is with a 3’UTR variant (rs1871452-T) in CHST3, encoding a sulfotransferase enzyme expressed in intervertebral discs. The largest effects on IDD are conferred by rare (MAF = 0.07 − 0.32%) loss-of-function (LoF) variants in SLC13A1, encoding a sodium-sulfate co-transporter (LoF burden OR = 1.44, P = 3.1 × 10−11); variants that also associate with reduced serum sulfate. Genes implicated by this study are involved in cartilage and bone biology, as well as neurological and inflammatory processes.

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Objectives Observational analyses suggest that high bone mineral density (BMD) is a risk factor for osteoarthritis (OA); it is unclear whether this represents a causal effect or shared aetiology and whether these relationships are body mass index (BMI)-independent. We performed bidirectional Mendelian randomization (MR) to uncover the causal pathways between BMD, BMI and OA. Methods One-sample (1S)MR estimates were generated by two-stage least-squares regression. Unweighted allele scores instrumented each exposure. Two-sample (2S)MR estimates were generated using inverse-variance weighted random-effects meta-analysis. Multivariable MR (MVMR), including BMD and BMI instruments in the same model, determined the BMI-independent causal pathway from BMD to OA. Latent causal variable (LCV) analysis, using weight-adjusted femoral neck (FN)–BMD and hip/knee OA summary statistics, determined whether genetic correlation explained the causal effect of BMD on OA. Results 1SMR provided strong evidence for a causal effect of BMD estimated from heel ultrasound (eBMD) on hip and knee OA {odds ratio [OR]hip = 1.28 [95% confidence interval (CI) = 1.05, 1.57], p = 0.02, ORknee = 1.40 [95% CI = 1.20, 1.63], p = 3 × 10–5, OR per standard deviation [SD] increase}. 2SMR effect sizes were consistent in direction. Results suggested that the causal pathways between eBMD and OA were bidirectional (βhip = 1.10 [95% CI = 0.36, 1.84], p = 0.003, βknee = 4.16 [95% CI = 2.74, 5.57], p = 8 × 10–9, β = SD increase per doubling in risk). MVMR identified a BMI-independent causal pathway between eBMD and hip/knee OA. LCV suggested that genetic correlation (i.e. shared genetic aetiology) did not fully explain the causal effects of BMD on hip/knee OA. Conclusions These results provide evidence for a BMI-independent causal effect of eBMD on OA. Despite evidence of bidirectional effects, the effect of BMD on OA did not appear to be fully explained by shared genetic aetiology, suggesting a direct action of bone on joint deterioration.

Anorexia nervosa (AN) is a serious eating disorder characterized by restriction of energy intake relative to requirements, resulting in abnormally low body weight. It has a lifetime prevalence of approximately 1%, disproportionately affects females 1,2 , and has no well replicated evidence of effective pharmacological or psychological treatments despite high morbidity and mortality 2 .Twin studies support a genetic basis for the observed aggregation of AN in families 3 , with heritability estimates of 48%-74% 4 . Although initial genome-wide association studies (GWASs) were underpowered 5,6 , evidence suggested that signals for AN would be detected with increased power 5 . We present a GWAS of 3,495 AN cases and 10,982 controls with one genome-wide significant locus (index variant rs4622308, p=4.3x10 -9 ) in a region (chr12: 56,372,482,185) which includes six genes. The SNP-chip heritability (h "#$ % ) of AN from these data is 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability stems from common genetic variation. Using these GWAS results, we also find significant positive genetic correlations with schizophrenia, neuroticism, educational attainment, and HDL cholesterol, and significant negative genetic correlations with body mass, insulin, glucose, and lipid phenotypes.Our results support the reconceptualization of AN as a disorder with both psychiatric and metabolic components.Following uniform quality control and imputation using the 1000 Genomes Project (phase 3) 7 in 12 anorexia nervosa (AN) case-control cohorts, we performed association analysis using an additive model on the dosage data for each cohort and an inverse-variance weighted metaanalysis across cohorts (see Supplementary Text for methods, quality control details and see Supplementary Table S1 for individual study details). Results were obtained for 10,641,224SNPs and insertion-deletion variants with minor allele frequency > 1% and imputation quality scores > 0.6 (see Supplementary Figure S1 for quantile-quantile plot). GWAS statistic inflation ( ) was 1.045, and the sample size adjusted '((( was 1.008, suggesting minimal inflation due to population stratification or other systematic biases.One locus achieved genome-wide significance for AN (Figure 1). Information for the top ten loci is given in Supplementary Table S2. The chromosome 12 (12q13.2) locus reported here is multigenic, overlaps six genes (IKZF4, RPS26, ERBB3, PA2G4, RPL41, and ZC3H10), and is located near six additional genes (ESYT1, SUOX, RAB5B, CDK2, PMEL, and DGKA).Supplementary Figure S2 provides a forest plot and information about effects across cohorts for the top SNP (rs4622308, P=4.3x10 -9 , OR (C allele) =1.2, SE=0.03, MAF cases =0.48, MAF controls =0.44), which were relatively consistent across cohorts. Results of conditional analyses are consistent with the existence of one signal at this locus (see Supplementary Figure S3). Several other immune-related phenotypes: vitiligo, alopecia areata, and asthma (see Supplementary Figure S4) have a...

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5x10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.