AIMS/HYPOTHESIS:Nearly 40% of African adults with type 2 diabetes are lean (BMI <25 kg/m2). Emerging evidence suggests that type 2 diabetes in African individuals who are lean may represent a distinct phenotype driven by impaired insulin secretion rather than insulin resistance, raising concerns about treatment mismatch and divergent disease outcomes. We examined complication profiles in Africans with type 2 diabetes who are lean vs overweight/obese. METHODS:We analysed harmonised, individual-level cross-sectional data from two large, well-characterised African cohorts (Africa America Diabetes Mellitus study, n=2790; Research on Obesity and Diabetes among African Migrants study, n=541; total n=3331) of adults with type 2 diabetes from Ghana, Nigeria and Kenya. Participants were classified as lean (BMI <25 kg/m2) or overweight/obese (BMI ≥25 kg/m2). Robust Poisson regression, adjusted for age, sex, education and treatment, assessed associations with retinopathy, chronic kidney disease, stroke, hypertension and 10-year cardiovascular disease risk. Cohort-specific estimates were pooled using random effects, followed by mediation analysis examining contributions of lifestyle and metabolic markers to observed differences. RESULTS:Type 2 diabetes in Africans who are lean was characterised by lower beta cell function and low insulin levels. Compared with individuals who are overweight/obese, adults who are lean showed a higher prevalence of retinopathy (pooled prevalence ratio [pPR] 1.36 [95% CI 1.13, 1.63]) and stroke (pPR 1.41 [95% CI 1.01, 1.99]), but lower hypertension (pPR 0.77 [95% CI 0.71, 0.85]) and 10-year cardiovascular disease risk (pPR 0.85 [95% CI 0.74, 0.97]). Chronic kidney disease prevalence did not differ between groups. Body fat percentage accounted for most differences (up to 92%). CONCLUSIONS/INTERPRETATION:Complication patterns in Africans with type 2 diabetes who are lean vs overweight/obese follow divergent paths. In Africa, where nearly 24 million people have type 2 diabetes, two-fifths of whom are lean, our findings add to growing evidence that lean type 2 diabetes may be a distinct phenotype, underscoring the urgent need for investigation into better-targeted management for this large, potentially mistreated, population.

Genetic predisposition and alcohol consumption are risk factors for increased blood pressure (BP), but their interactions influencing BP remain understudied. We conducted population-specific and cross-population meta-analyses of genome-wide gene-alcohol (GxAlc) interactions affecting BP in >1.1M individuals from multiple populations. We identified 46 GxAlc interaction loci for BP, including 21 from one-degree-of-freedom interaction tests (PGxAlc<5×10-8; or <0.05/Meff, Meff independent BP associations at P<10-5), and 25 from two-degree-of-freedom tests of main and interaction effects (PGxAlc<0.05/M2df, M2df independent 2df-associations at P2df<5×10-8), including 7 novel and 39 known BP loci. The 12q24 locus highlights the genetic effect of BRAP-rs11066001 on BP, being ~6 times larger in current drinkers than in non-drinkers. Gene prioritization with 46 GxAlc loci identified 15 genes with ≥3 lines of evidence (location, literature, druggability, functional/regulatory annotation, or pathway analyses). Several loci showed sex- and population-specific effects and revealed biological pathways of alcohol's influence on BP, suggesting mechanisms underlying alcohol-induced hypertension.

Evidence for a causal role of DNA methylation sites (CpGs) in type 2 diabetes and glycaemic traits is limited due to the cross-sectional nature of many epigenome-wide association studies (EWAS). In addition, epigenetic studies in West African populations are particularly sparse, despite the high and rising burden of type 2 diabetes in these populations. Hence, we aimed to identify CpGs causally associated with type 2 diabetes among West Africans by leveraging Mendelian randomisation (MR) analysis and longitudinal data. We used the Illumina EPIC DNA methylation array to profile the methylation of DNA extracted from white blood cells collected from 879 Ghanaian individuals (the Research on Obesity and Diabetes among African Migrants [RODAM] study) and 332 Nigerian individuals (the Africa America Diabetes Mellitus [AADM] study) who were not on glucose-lowering medication. We carried forwards CpGs identified in EWAS for type 2 diabetes and meta-analysed EWAS for HbA1c and homeostatic model assessment estimates of insulin sensitivity (HOMA-S) as exposures to two-sample MR analysis. Independent cis methylation quantitative trait loci (meQTLs) were calculated using methylation data from blood and primary hepatocytes and subsequently used as instrumental variables (SNP–exposure associations). Genome-wide association analyses for type 2 diabetes on 4120 participants from the AADM study were used to derive the SNP–outcome associations. Longitudinal trait data (n=138) and RNA-seq data (n=77 blood, 49 adipose, 55 muscle) available for a subset of Nigerians were used for follow-up analyses. We identified 28 CpGs associated with type 2 diabetes, 26 with HbA1c and three with HOMA-S (total CpGs: 57), of which 49 had meQTLs in blood (AADM study data) and four had meQTLs in primary hepatocytes from African American individuals. MR analysis provided evidence for causality for cg00036588 and cg16759041 in type 2 diabetes using blood and hepatocyte meQTLs, respectively. Longitudinal analyses showed an association between baseline methylation of these CpGs with HbA1c at follow-up. RNA-seq data revealed a cis correlation of cg00036588 with FAM83C (false discovery rate [FDR]=3.3 × 10–4) and EIF6 (FDR=0.13) in skeletal muscle. Our study identified two epigenetic markers as likely to be causal for type 2 diabetes in West African populations. In addition to enhancing our understanding of disease mechanisms, these CpGs with evidence of causal associations could be prioritised as potential biomarkers for early detection of disease or as drug development targets.

Kidney disease disproportionately affects populations of African ancestry, yet most genetic studies have focused on Europeans. Here, we present a three-stage genome-wide association study meta-analysis of estimated glomerular filtration rate in ~26,000 individuals across Eastern, Western, and Southern Africa and ~81,000 African-ancestry individuals in the diaspora. Continental African meta-analysis identifies four independent genome-wide significant loci, including two previously unreported loci. Pan-African meta-analysis identifies 19 independent loci, including three previously unreported loci. Fine-mapping reveals four loci with high causality probability, and phenome-wide analyses demonstrate pleiotropic effects on cardiometabolic and immunological traits. Notably, APOL1 high-risk variants strongly associated with kidney disease in African Americans show markedly lower frequency and attenuated effects in continental Africa, indicating potential distinct genetic architectures. Polygenic scores from genetically similar populations significantly outperformed those from distant cohorts. These findings demonstrate the necessity of conducting genomic research across diverse African populations to enable equitable health outcomes.

Gene-environment interactions may enhance our understanding of blood pressure (BP) biology. We conducted a meta-analysis of multi-population genome-wide association studies (GWASs) of BP traits accounting for gene-depressive symptomatology (DEPR) interactions. Our study included 564,680 adults from 67 cohorts and four population backgrounds: African (5%), Asian (7%), European (85%), and Hispanic (3%). We discovered seven previously unreported BP loci showing gene-DEPR interaction. These loci mapped to genes implicated in neurogenesis (TGFA and CASP3), lipid metabolism (ACSL1), neuronal apoptosis (CASP3), and synaptic activity (CNTN6 and DBI). We also showed evidence for gene-DEPR interaction at nine known BP loci, further suggesting links between mood disturbance and BP regulation. Of the 16 identified loci, 11 were derived from non-European populations. Post-GWAS analyses prioritized 36 genes, including genes involved in synaptic functions (DOCK4 and MAGI2) and neuronal signaling (CCK, UGDH, and SLC01A2). Integrative druggability analyses identified 11 druggable candidate gene targets linked to pathways involved in mood disorders as well as known anti-hypertensive drugs. Our findings emphasize the importance of considering gene-DEPR interactions on BP, particularly in non-European populations. Our prioritized genes and druggable targets highlight biological pathways connecting mood disorders and hypertension and suggest opportunities for BP drug repurposing and risk factor prevention, especially in individuals with DEPR.

Conventional genome-wide association studies (GWAS) are designed to assess the effect of a genetic locus on phenotypic mean by genotype. Such loci explain a proportion of phenotypic variance known as narrow-sense heritability. In contrast, variance quantitative trait loci (vQTL) are associated with the phenotypic variance by genotype. These loci explain an additional proportion of phenotypic variance and contribute to broad-sense heritability but not to narrow-sense heritability. Here, a genome-wide vQTL analysis in 22,805 African Americans yielded eight loci for body mass index (BMI). Of these loci, three were replicated in 6002 sub-Saharan Africans. No locus reached genome-wide significance using the standard additive model. Furthermore, no locus showed evidence for natural selection, haplotype effects, or gene × sex or gene × study interactions. Two loci showed evidence for an effect of locus-specific ancestry resulting from admixture and for a gene × gene interaction. One locus showed evidence for interaction with diastolic blood pressure, consistent with this vQTL capturing an unmodeled gene × covariate interaction. These analyses demonstrate that relevant BMI loci can be detected by evaluating vQTL and that these loci contribute to the underexplored broad-sense heritability for this trait.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which drove the 2019 coronavirus disease (COVID-19) pandemic, continues to engender inquiries into the role of host genetic factors in disease susceptibility. Despite the identification of over 1,000 genes potentially associated with SARS-CoV-2 and COVID-19, the mechanisms connecting genetic variants to phenotype remain elusive. To shed light on these mechanisms, we undertook an integrated analysis, merging data from whole genome association analyses of COVID-19 with methylome and transcriptomic. The study includes African American adults from the GENE-FORECAST study, encompassing 371 individuals with whole genome sequencing (WGS), 203 with DNA methylation, and 321 with RNA sequencing (RNA-Seq) of blood. About 53.3% of participants reported COVID-19. Significant loci associated with COVID-19 were examined within the framework of methylation quantitative trait loci (mQTL), which are located near the gene-of-orig (cis-mQTL) and expression quantitative trait loci (eQTL), which are located near the gene-of-origin (cis-eQTL), enabling analysis to assess mediators between genetic variants and COVID-19 status. Our analysis identified four intronic variants and confirmed a missense variant, rs1052067, in PMF1 associated with COVID-19. Causal mediation analysis revealed that the combination of genetic variants within PMF1, epigenomics, and transcriptomics mapped four pathways influencing COVID-19 status. These pathways include: rs9659072→DNAm at chr1:156285845 (annotated to TMEM79)→ENSG00000198715:13 (annotated to glycosylated lysosomal membrane protein, GLMP); rs12083543→DNAm at chr1:155951748 (ARHGEF2)→ENSG00000198715:13 (GLMP); rs1052067→DNAm at chr1:155951748 (ARHGEF2)→ENSG00000198715:13 (GLMP); rs1543294→ENSG00000198715:13 (GLMP)→DNAm at chr1:156077518 (MEX3A). Through integrated multiomics analyses, we identified genetic variants whose effects on COVID-19 susceptibility are mediated by changes in DNA methylation and mRNA expression. These findings offer insights into potential mechanistic pathways that merit further exploration.NEW & NOTEWORTHY The study investigates host genetic factors influencing COVID-19 susceptibility by integrating WGS, epigenomics, and transcriptomic data. It identified that PMF1 is linked to COVID-19. Mediation analysis revealed that genetic variants in PMF1 affect COVID-19 status via combinations of one transcript (annotated to GLMP) and three DNAm sites (annotated to ARHGEF2, TMEM79, MEX3A). The findings highlight the role of lysosomal pathways and transmembrane proteins in disease susceptibility, offering new insight into potential therapeutic targets for COVID-19.

Cigarette smoking influences blood pressure (BP) levels. Studying and accounting for potential gene-smoking interactions can help discover novel loci and provide insights into biological pathways for smoking-associated BP regulation. We conducted a genome-wide association meta-analysis involving 1,188,241 individuals from 66 studies in five ancestry groups, analyzing systolic BP, diastolic BP, and pulse pressure while considering interactions between genetic variants and three smoking exposures: smoking status, cigarettes per day, and pack years. These analyses identified twelve novel loci for BP at genome-wide significance ( P < 5 × 10 - 9 ), and highlighted biological processes including tight junction integrity, mitochondrial health, vascular relaxation, and endothelial function. In smoking status-stratified analyses, smoking modifies the genetic effect of six variants on BP. To prioritize likely causal, we developed and applied SuSiEgxe, a fine-mapping method based on a two-degree-of-freedom joint test using gene-environment interaction summary statistics. Fine-mapped loci uncovered immune-related pathway for smoking-associated BP regulation.

Liver enzymes are critical biomarkers of hepatic metabolism, injury, and systemic homeostasis. Their genetic architecture remains understudied in African-ancestry populations. We addressed this knowledge gap by conducting genome-wide analyses of four liver enzymes in over 55,000 individuals of African ancestry from six cohorts across sub-Saharan Africa, the United States, and the United Kingdom. We identified 31 significant loci, of which 14 were novel, including TMEM64 and CRYL1 for alkaline phosphatase, IMMP2L for alanine aminotransferase, and PDE4D for gamma-glutamyl transferase. Several novel variants exhibited high allele frequencies in African-ancestry populations but were rare or absent in other global populations. Functional annotation indicated that lead variants overlapped liver-active regulatory regions, histone marks, and hepatocyte eQTLs. Colocalization and enrichment analyses implicated pathways related to lipid and carbohydrate metabolism, glycosylation, and immune function. Our findings expand the catalog of genetic variants influencing liver enzymes and advance understanding of the biological mechanisms underlying liver function.

Background:Gene-environment interactions may enhance our understanding of hypertension. Our previous study highlighted the importance of considering psychosocial factors in gene discovery for blood pressure (BP) but was limited in statistical power and population diversity. To address these challenges, we conducted a multi-population genome-wide association study (GWAS) of BP accounting for gene-depressive symptomatology (DEPR) interactions in a larger and more diverse sample. Results:Our study included 564,680 adults aged 18 years or older from 67 cohorts and 4 population backgrounds (African (5%), Asian (7%), European (85%), and Hispanic (3%)). We discovered seven novel gene-DEPR interaction loci for BP traits. These loci mapped to genes implicated in neurogenesis (TGFA, CASP3), lipid metabolism (ACSL1), neuronal apoptosis (CASP3), and synaptic activity (CNTN6, DBI). We also identified evidence for gene-DEPR interaction at nine known BP loci, further suggesting links between mood disturbance and BP regulation. Of the 16 identified loci, 11 loci were derived from African, Asian, or Hispanic populations. Post-GWAS analyses prioritized 36 genes, including genes involved in synaptic functions (DOCK4, MAGI2) and neuronal signaling (CCK, UGDH, SLC01A2). Integrative druggability analyses identified 11 druggable candidate gene targets, including genes implicated in pathways linked to mood disorders as well as gene products targeted by known antihypertensive drugs. Conclusions:Our findings emphasize the importance of considering gene-DEPR interactions on BP, particularly in non-European populations. Our prioritized genes and druggable targets highlight biological pathways connecting mood disorders and hypertension and suggest opportunities for BP drug repurposing and risk factor prevention, especially in individuals with DEPR.

BACKGROUND:Developing countries face an "obesity epidemic," particularly affecting children and younger adults. While obesity is a known risk factor for 12 types of cancer, primarily affecting older populations, its impact on younger generations is understudied. METHODS:This study analyzed data from a population-based cancer registry covering 14.14 million individuals in China (2007-2021). We compared the incidence of obesity- and non-obesity-related cancers and applied an age-period-cohort model to estimate their impacts. FINDINGS:Among 651,342 cancer cases, 48.47% were obesity related. The age-standardized incidence rates (ASRs) of the 12 obesity-related cancers increased annually by 3.6% (p < 0.001), while ASRs for non-obesity-related cancers remained stable. Obesity-related cancers surged among younger adults, with rates rising across successive generations. The annual percentage of change decreased with age, from 15.28% for ages 25-29 years to 1.55% for ages 60-64 years. The incidence rate ratio for obesity-related cancer was higher in younger generations compared to those born in 1962-1966. We predict that the ASR for obesity-related cancers will nearly double in the next decade. CONCLUSIONS:The rising incidence of obesity-related cancers among young adults poses a significant public health concern. The increasing cancer burden underscores the need for targeted interventions to address the obesity epidemic. FUNDING:This work was supported by the National Natural Science Foundation of China (81930019, 82341076) to J.-K.Y.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized 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 cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

BackgroundSex is a crucial factor in the development, progression, and treatment of cancer, making it vital to examine cancer incidence trends by sex for effective prevention strategies. ObjectiveThis study aimed to assess the incidence of cancer in China between 2007 and 2021, with a focus on sex-based trends. MethodsA population-based cancer registry comprising 14.14 million individuals was maintained between 2007 and 2021 by the Beijing Municipal Health Big Data and Policy Research Center. The age-standardized rates (ASRs) of cancers were calculated using the Segi population. The average annual percentage of change (AAPC) was evaluated using the joinpoint regression model, while the Bayesian age-period-cohort model was used to predict cancer incidence in the next 10 years. ResultsFrom 2007 to 2021, the study included 651,342 incident patients with cancer, of whom 51.2% (n=333,577) were women. The incidence indicated by the ASR for all cancers combined was 200.8 per 100,000 for women and 184.4 per 100,000 for men. The increase in incidence indicated by AAPC for all malignancies combined significantly increased in women between 2007 and 2021 (AAPC=3.1%; P<.001), whereas it remained constant in men (AAPC=0.3%; P=.30). Although the overall incidence of all cancers indicated by AAPC increased in young men (AAPC=3.2%; P=.01), the greatest increase was observed among young women (AAPC=6.1%; P<.001). The incidence rate ratio for cancer in women increased among subsequent younger generations compared with patients born in the 1962-1966 cohort. The ASR in women will increase 1.6-fold over the next 10 years, with women having twice the incidence rate of men by 2031. ConclusionsThe rising incidence of cancer among women in China has become a growing concern, emphasizing the need for increased efforts in cancer prevention and early screening, especially among young women.

Objective: Understanding the genetic underpinnings of anthropometric traits in diverse populations is crucial for gaining insights into their biological mechanisms and potential implications for health. Methods: We conducted a genome-wide association study, meta-analysis, and gene set analysis of waist-hip ratio (WHR), WHR adjusted for BMI (WHRadjBMI), waist circumference, BMI, and height using the African Collaborative Center for Microbiome and Genomics Research (ACCME) cohort (n = similar to 11,000) for discovery and polygenic score target analyses and the Africa America Diabetes Mellitus (AADM) study (n = similar to 5200) for replication and polygenic score validation. We generated and compared polygenic scores from European, African, Afro-Caribbean, and multiethnic ancestry populations. Results: The top loci associated with each trait in the meta-analysis were in CD36 (rs3211826 [p = 5.90 x 10(-12)] for WHR and rs73709003 [p = 1.75 x 10(-13)] for WHRadjBMI), IFI27L1 (rs59775050 [p = 2.66 x 10(-08)] for waist circumference), INPP4B (rs2636629 [p = 1.44 x 10(-09)] for BMI), and HMGA1 (rs6937622 [p = 1.40 x 10(-15)] for height) gene regions. A novel variant rs7797157, near GNAT3, was also significantly associated with WHR (p = 2.50 x 10(-10)) and WHRadjBMI (p = 2.66 x 10(-11)). The ancestry-specific parameters for the best predictive polygenic scores were European ancestry (R-2 = 0.68%; p = 1.63 x 10(-16)) and multiethnic ancestry (R-2 = 0.06%; p = 1.29 x 10(-02)) for WHR; European ancestry (R-2 = 1.36%; p = 2.94 x 10(-31)) and multiethnic ancestry (R-2 = 1.12%; p = 3.52 x 10(-25)) for BMI; and European ancestry (R-2 = 3.16%; p = 2.95 x 10(-73)), African ancestry (R-2 = 4.16%; p = 1.75 x 10(-96)), and African and Afro-Caribbean ancestry (R-2 = 2.67%; p = 4.35 x 10(-62)) for height. Conclusions: The discovery of a novel locus for WHR and genetic signals for each trait and the assessment of polygenic score performance underscore the importance of conducting well-powered studies in diverse populations.

Background Type 2 diabetes (T2D) has reached epidemic proportions globally, including in Africa. However, molecular studies to understand the pathophysiology of T2D remain scarce outside Europe and North America. The aims of this study are to use an untargeted metabolomics approach to identify: (a) metabolites that are differentially expressed between individuals with and without T2D and (b) a metabolic signature associated with T2D in a population of Sub-Saharan Africa (SSA). Methods A total of 580 adult Nigerians from the Africa America Diabetes Mellitus (AADM) study were studied. The discovery study included 310 individuals (210 without T2D, 100 with T2D). Metabolites in plasma were assessed by reverse phase, ultra-performance liquid chromatography and mass spectrometry (RP)/UPLC-MS/MS methods on the Metabolon Platform. Welch’s two-sample t-test was used to identify differentially expressed metabolites (DEMs), followed by the construction of a biomarker panel using a random forest (RF) algorithm. The biomarker panel was evaluated in a replication sample of 270 individuals (110 without T2D and 160 with T2D) from the same study. Results Untargeted metabolomic analyses revealed 280 DEMs between individuals with and without T2D. The DEMs predominantly belonged to the lipid (51%, 142/280), amino acid (21%, 59/280), xenobiotics (13%, 35/280), carbohydrate (4%, 10/280) and nucleotide (4%, 10/280) super pathways. At the sub-pathway level, glycolysis, free fatty acid, bile metabolism, and branched chain amino acid catabolism were altered in T2D individuals. A 10-metabolite biomarker panel including glucose, gluconate, mannose, mannonate, 1,5-anhydroglucitol, fructose, fructosyl-lysine, 1-carboxylethylleucine, metformin, and methyl-glucopyranoside predicted T2D with an area under the curve (AUC) of 0.924 (95% CI: 0.845–0.966) and a predicted accuracy of 89.3%. The panel was validated with a similar AUC (0.935, 95% CI 0.906–0.958) in the replication cohort. The 10 metabolites in the biomarker panel correlated significantly with several T2D-related glycemic indices, including Hba1C, insulin resistance (HOMA-IR), and diabetes duration. Conclusions We demonstrate that metabolomic dysregulation associated with T2D in Nigerians affects multiple processes, including glycolysis, free fatty acid and bile metabolism, and branched chain amino acid catabolism. Our study replicated previous findings in other populations and identified a metabolic signature that could be used as a biomarker panel of T2D risk and glycemic control thus enhancing our knowledge of molecular pathophysiologic changes in T2D. The metabolomics dataset generated in this study represents an invaluable addition to publicly available multi-omics data on understudied African ancestry populations.

Background: Kidney disease is more prevalent in populations of African ancestry, yet most genome-wide association studies (GWAS) for kidney function markers have been performed in Europeans. To discover additional loci in individuals of African ancestry, we assembled 10 GWASs of the estimated glomerular filtration rate (eGFR) across diverse African regions, including ~26,000 individuals as part of the newly established KidneyGenAfricaconsortium. Additional GWASs of eGFR in ~81,000 African-ancestry individuals in the diaspora were aggregated from the Million Veteran Program (MVP), UK Biobank (UKBB), and the Chronic Kidney Disease Genetics (CKDGen) Consortium. Methods: We performed a three-stage GWAS meta-analysis: (1) Three regional meta-analyses in eastern, western, and southern Africa; (2) a continental African meta-analysis; and (3) a pan-African meta-analysis pooling continental and diaspora studies. We performed fine-mapping, colocalization, functional annotation using MAGMA/FUMA, and a phenome-wide association study (PheWAS). We investigated the role of APOL1 haplotypes in low eGFR in continental Africa. Polygenic scores (PGSs) were estimated from regional, continental, pan-African, and multi-ancestry meta-analyses in a Malawi MEIRU cohort divided into testing and validation sets. Results: The regional meta-analyses identified 28 genome-wide significant loci, including 5 novel loci at FAM72C, LOC645752, OPRM1, KLH1, and LAMA4. The pan-African meta-analysis detected 20 independent loci, including four novel loci (ARG1, OR52H1, TRIM69, and SQRDL). Our fine-mappingidentified four loci with a posterior probability of causality > 0.99. Colocalization recapitulated known eGFR-related genes, and PheWAS showed a pleiotropic profile for 23 of the identified loci, particularly with cardiometabolic, immunological, dermatological, nutritional, and psychiatric traits. The overall APOL1high-risk haplotype frequency in continental Africa was 5%, significantly lower than the approximately 13% observed in African Americans. Notably, we found a limited association between APOL1 variants and low eGFR in continental Africa, which contrasts with the strong APOL1 association with chronic kidney disease observed in African Americans, highlighting distinct genetic risk profiles for kidney disease between African populations and African Americans. PGSs derived from southern African datasets outperformed those from other regional, continental, and multi-ancestry-derived PGSs in the Malawi cohort. Conclusion: We identified novel loci associated with eGFR in individuals of African ancestry from the largest GWAS of eGFR conducted in Africa to date. We observed potential distinct genetic factors that may influence eGFR in continental Africans and African Americans. This suggests that other genetic factors may play a more significant role in eGFR risk among continental Africans. PGSs derived from close genetic distance with discovery cohorts performed better than PGSs derived from other regions, including multi-ancestry data.

The vast majority of human populations and individuals have mixed ancestry. Consequently, adjustment for locus-specific ancestry is essential for genetic association studies. To empower association studies for all populations, it is necessary to integrate effects of locus-specific ancestry and genotype. We developed a joint test of ancestry and association that can be performed with summary statistics, is independent of study design, can take advantage of locus-specific ancestry effects to boost power in association testing, and can utilize association effects to fine map admixture peaks. We illustrate the test using the association between serum triglycerides and LPL. By combining data from African Americans, European Americans, and West Africans, we identify three conditionally independent variants with varying amounts of ancestrally differentiated allele frequencies. Using out-of-sample data, we demonstrate improved prediction achievable by accounting for multiple causal variants and locus-specific ancestry effects at a single locus.

AIMS:Reports have suggested that COVID-19 vaccination may cause Type 1 diabetes (T1D), particularly fulminant T1D (FT1D). This study aimed to investigate the incidence of T1D in a general population of China, where>90% of the people have received three injections of inactivated SARS-Cov-2 vaccines in 2021.METHODS:A population-based registry of T1D was performed using data from the Beijing Municipal Health Commission Information Center. Annual incidence rates were calculated by age group and gender, and annual percentage changes were assessed using Joinpoint regression.RESULTS:The study included 14.14 million registered residents, and 7,697 people with newly diagnosed T1D were identified from 2007 to 2021. T1D incidence increased from 2.77 in 2007 to 3.84 per 100,000 persons in 2021. However, T1D incidence was stable from 2019 to 2021, and the incidence rate did not increase when people were vaccinated in January-December 2021. The incidence of FT1D did not increase from 2015 to 2021.CONCLUSIONS:The findings suggest that COVID-19 vaccination did not increase the onset of T1D or have a significant impact on T1D pathogenesis, at least not on a large scale.

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.