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Hepatitis C virus (HCV) infects an estimated 3% of the global population with the majority of individuals (75-85%) failing to clear the virus without treatment, leading to chronic liver disease. Individuals of African descent have lower rates of clearance compared with individuals of European descent and this is not fully explained by social and environmental factors. This suggests that differences in genetic background may contribute to this difference in clinical outcome following HCV infection. Using 473 individuals and 792,721 single-nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS), we estimated local African ancestry across the genome. Using admixture mapping and logistic regression, we identified two regions of interest associated with spontaneous clearance of HCV (15q24, 20p12). A genome-wide significant variant was identified on chromosome 15 at the imputed SNP, rs55817928 (P=6.18 × 10(-8)) between the genes SCAPER and RCN. Each additional copy of the African ancestral C allele is associated with 2.4 times the odds of spontaneous clearance. Conditional analysis using this SNP in the logistic regression model explained one-third of the local ancestry association. Additionally, signals of selection in this area suggest positive selection due to some ancestral pathogen or environmental pressure in African, but not in European populations.

Gene-environment interactions (G × E), the interplay of genetic variation with environmental factors, have a pivotal impact on human complex traits and diseases. Statistically, G × E can be assessed by determining the deviation from expectation of predictive models based solely on the phenotypic effects of genetics or environmental exposures. Despite the unprecedented, widespread and diverse use of G × E analytical frameworks, heterogeneity in their application and reporting hinders their applicability in public health. In this Review, we discuss study design considerations as well as G × E analytical frameworks to assess polygenic liability dependent on the environment, to identify specific genetic variants exhibiting G × E, and to characterize environmental context for these dynamics. We conclude with recommendations to address the most common challenges and pitfalls in the conceptualization, methodology and reporting of G × E studies, as well as future directions., (© 2024. Springer Nature Limited.)

Genetic variation that influences gene expression and splicing is a key source of phenotypic diversity 1-5 . Although invaluable, studies investigating these links in humans have been strongly biased towards participants of European ancestries, which constrains generalizability and hinders evolutionary research. Here to address these limitations, we developed MAGE, an open-access RNA sequencing dataset of lymphoblastoid cell lines from 731 individuals from the 1000 Genomes Project 6 , spread across 5 continental groups and 26 populations. Most variation in gene expression (92%) and splicing (95%) was distributed within versus between populations, which mirrored the variation in DNA sequence. We mapped associations between genetic variants and expression and splicing of nearby genes (cis-expression quantitative trait loci (eQTLs) and cis-splicing QTLs (sQTLs), respectively). We identified more than 15,000 putatively causal eQTLs and more than 16,000 putatively causal sQTLs that are enriched for relevant epigenomic signatures. These include 1,310 eQTLs and 1,657 sQTLs that are largely private to underrepresented populations. Our data further indicate that the magnitude and direction of causal eQTL effects are highly consistent across populations. Moreover, the apparent 'population-specific' effects observed in previous studies were largely driven by low resolution or additional independent eQTLs of the same genes that were not detected. Together, our study expands our understanding of human gene expression diversity and provides an inclusive resource for studying the evolution and function of human genomes., (© 2024. The Author(s).)

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Nearly 300 million individuals live with chronic hepatitis B virus (HBV) infection (CHB), for which no curative therapy is available. As viral diversity is associated with pathogenesis and immunological control of infection, improved methods to characterize this diversity could aid drug development efforts. Conventionally, viral sequencing data are mapped/aligned to a reference genome, and only the aligned sequences are retained for analysis. Thus, reference selection is critical, yet selecting the most representative reference a priori remains difficult. We investigate an alternative pangenome approach which can combine multiple reference sequences into a graph which can be used during alignment. Using simulated short-read sequencing data generated from publicly available HBV genomes and real sequencing data from an individual living with CHB, we demonstrate alignment to a phylogenetically representative 'genome graph' can improve alignment, avoid issues of reference ambiguity, and facilitate the construction of sample-specific consensus sequences more genetically similar to the individual's infection. Graph-based methods can, therefore, improve efforts to characterize the genetics of viral pathogens, including HBV, and have broader implications in host-pathogen research., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Duchen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Astroviral infections commonly cause acute nonbacterial gastroenteritis in children globally. However, these infections often go undiagnosed outside of research settings. There is no treatment available for astrovirus, and Astroviridae strain diversity presents a challenge to potential vaccine development., Methods: To address our hypothesis that host genetic risk factors are associated with astrovirus disease susceptibility, we performed a genome-wide association study of astrovirus infection in the first year of life from children enrolled in 2 Bangladeshi birth cohorts., Results: We identified a novel region on chromosome 1 near the loricrin gene ( LOR ) associated with astrovirus diarrheal infection (rs75437404; meta-analysis P = 8.82 × 10 -9 ; A allele odds ratio, 2.71) and on chromosome 10 near the prolactin releasing hormone receptor gene ( PRLHR ) (rs75935441; meta-analysis P = 1.33 × 10 -8 ; C allele odds ratio, 4.17). The prolactin-releasing peptide has been shown to influence feeding patterns and energy balance in mice. In addition, several single-nucleotide polymorphisms in the chromosome 1 locus have previously been associated with expression of innate immune system genes PGLYRP4, S100A9, and S100A12 ., Conclusions: This study identified 2 significant host genetic regions that may influence astrovirus diarrhea susceptibility and should be considered in further studies., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Polygenic scores (PGSs) aggregate the effects of variants across the genome to estimate genetic liability, but have lower performance in external study populations. A new study by Ding et al. has applied a novel framework to estimate the individual-level predictive accuracy of PGSs, and demonstrates that performance reduction occurs linearly with genetic distance., Competing Interests: Declaration of interests The author declares no conflicts of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Sickle cell trait affects approximately 8% of Black individuals in the United States, along with many other individuals with ancestry from malaria-endemic regions worldwide. While traditionally considered a benign condition, recent evidence suggests that sickle cell trait is associated with lower eGFR and higher risk of kidney diseases, including kidney failure. The mechanisms underlying these associations remain poorly understood. We used proteomic profiling to gain insight into the pathobiology of sickle cell trait., Methods: We measured proteomics ( N =1285 proteins assayed by Olink Explore) using baseline plasma samples from 592 Black participants with sickle cell trait and 1:1 age-matched Black participants without sickle cell trait from the prospective Women's Health Initiative cohort. Age-adjusted linear regression was used to assess the association between protein levels and sickle cell trait., Results: In age-adjusted models, 35 proteins were significantly associated with sickle cell trait after correction for multiple testing. Several of the sickle cell trait-protein associations were replicated in Black participants from two independent cohorts (Atherosclerosis Risk in Communities study and Jackson Heart Study) assayed using an orthogonal aptamer-based proteomic platform (SomaScan). Many of the validated sickle cell trait-associated proteins are known biomarkers of kidney function or injury ( e.g. , hepatitis A virus cellular receptor 1 [HAVCR1]/kidney injury molecule-1 [KIM-1], uromodulin [UMOD], ephrins), related to red cell physiology or hemolysis (erythropoietin [EPO], heme oxygenase 1 [HMOX1], and α -hemoglobin stabilizing protein) and/or inflammation (fractalkine, C-C motif chemokine ligand 2/monocyte chemoattractant protein-1 [MCP-1], and urokinase plasminogen activator surface receptor [PLAUR]). A protein risk score constructed from the top sickle cell trait-associated biomarkers was associated with incident kidney failure among those with sickle cell trait during Women's Health Initiative follow-up (odds ratio, 1.32; 95% confidence interval, 1.10 to 1.58)., Conclusions: We identified and replicated the association of sickle cell trait with a number of plasma proteins related to hemolysis, kidney injury, and inflammation., (Copyright © 2023 by the American Society of Nephrology.)

Background: Diarrhea is the second leading cause of death in children under 5 years old worldwide. Known diarrhea risk factors include sanitation, water sources, and pathogens but do not fully explain the heterogeneity in frequency and duration of diarrhea in young children. We evaluated the role of host genetics in diarrhea., Methods: Using 3 well-characterized birth cohorts from an impoverished area of Dhaka, Bangladesh, we compared infants with no diarrhea in the first year of life to those with an abundance, measured by either frequency or duration. We performed a genome-wide association analysis for each cohort under an additive model and then meta-analyzed across the studies., Results: For diarrhea frequency, we identified 2 genome-wide significant loci associated with not having any diarrhea, on chromosome 21 within the noncoding RNA AP000959 (C allele odds ratio [OR] = 0.31, P = 4.01 × 10-8), and on chromosome 8 within SAMD12 (T allele OR = 0.35, P = 4.74 × 10-7). For duration of diarrhea, we identified 2 loci associated with no diarrhea, including the same locus on chromosome 21 (C allele OR = 0.31, P = 1.59 × 10-8) and another locus on chromosome 17 near WSCD1 (C allele OR = 0.35, P = 1.09 × 10-7)., Conclusions: These loci are in or near genes involved in enteric nervous system development and intestinal inflammation and may be potential targets for diarrhea therapeutics., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Latin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories and complex trait architectures remain hidden owing to insufficient data 1 . To fill this gap, the Mexican Biobank project genotyped 6,057 individuals from 898 rural and urban localities across all 32 states in Mexico at a resolution of 1.8 million genome-wide markers with linked complex trait and disease information creating a valuable nationwide genotype-phenotype database. Here, using ancestry deconvolution and inference of identity-by-descent segments, we inferred ancestral population sizes across Mesoamerican regions over time, unravelling Indigenous, colonial and postcolonial demographic dynamics 2-6 . We observed variation in runs of homozygosity among genomic regions with different ancestries reflecting distinct demographic histories and, in turn, different distributions of rare deleterious variants. We conducted genome-wide association studies (GWAS) for 22 complex traits and found that several traits are better predicted using the Mexican Biobank GWAS compared to the UK Biobank GWAS 7,8 . We identified genetic and environmental factors associating with trait variation, such as the length of the genome in runs of homozygosity as a predictor for body mass index, triglycerides, glucose and height. This study provides insights into the genetic histories of individuals in Mexico and dissects their complex trait architectures, both crucial for making precision and preventive medicine initiatives accessible worldwide., (© 2023. The Author(s).)

Peripheral artery disease (PAD) is a form of atherosclerotic cardiovascular disease, affecting ∼8 million Americans, and is known to have racial and ethnic disparities. PAD has been reported to have a significantly higher prevalence in African Americans (AAs) compared to non-Hispanic European Americans (EAs). Hispanic/Latinos (HLs) have been reported to have lower or similar rates of PAD compared to EAs, despite having a paradoxically high burden of PAD risk factors; however, recent work suggests prevalence may differ between sub-groups. Here, we examined a large cohort of diverse adults in the Bio Me biobank in New York City. We observed the prevalence of PAD at 1.7% in EAs vs. 8.5% and 9.4% in AAs and HLs, respectively, and among HL sub-groups, the prevalence was found at 11.4% and 11.5% in Puerto Rican and Dominican populations, respectively. Follow-up analysis that adjusted for common risk factors demonstrated that Dominicans had the highest increased risk for PAD relative to EAs [OR = 3.15 (95% CI 2.33-4.25), p < 6.44 × 10 -14 ]. To investigate whether genetic factors may explain this increased risk, we performed admixture mapping by testing the association between local ancestry and PAD in Dominican Bio Me participants (N = 1,813) separately from European, African, and Native American (NAT) continental ancestry tracts. The top association with PAD was an NAT ancestry tract at chromosome 2q35 [OR = 1.96 (SE = 0.16), p < 2.75 × 10 -05 ) with 22.6% vs. 12.9% PAD prevalence in heterozygous NAT tract carriers versus non-carriers, respectively. Fine-mapping at this locus implicated tag SNP rs78529201 located within a long intergenic non-coding RNA (lincRNA) LINC00607 , a gene expression regulator of key genes related to thrombosis and extracellular remodeling of endothelial cells, suggesting a putative link of the 2q35 locus to PAD etiology. Efforts to reproduce the signal in other Hispanic cohorts were unsuccessful. In summary, we showed how leveraging health system data helped understand nuances of PAD risk across HL sub-groups and admixture mapping approaches elucidated a putative risk locus in a Dominican population., Competing Interests: EK received personal fees from Illumina, 23andMe, Allelica, and Regeneron Pharmaceuticals, received research funding from Allelica, and serves as a scientific advisory board member for Encompass Bio, Foresite Labs, and Galateo Bio. NA-H is an employee and equity holder of 23andMe; serves as a scientific advisory board member for Allelica; received personal fees from Genentech, Allelica, and 23andMe; received research funding from Akcea; and was previously employed by Regeneron Pharmaceuticals. ES is an employee of Calico Life Sciences LLC. SA received consulting fees from Variant Bio and Biogen Inc. CG owns stock in 23andMe and serves as an advisory board member for Encompass Bio. DK serve as scientific advisor to Bitterroot Bio, Inc. SMD receives research support from RenalytixAI and Novo Nordisk, outside the scope of the current research. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cullina, Wojcik, Shemirani, Klarin, Gorman, Sorokin, Gignoux, Belbin, Pyarajan, Asgari, Tsao, Damrauer, Abul-Husn and Kenny.)

Individuals of admixed ancestries (for example, African Americans) inherit a mosaic of ancestry segments (local ancestry) originating from multiple continental ancestral populations. This offers the unique opportunity of investigating the similarity of genetic effects on traits across ancestries within the same population. Here we introduce an approach to estimate correlation of causal genetic effects (r admix ) across local ancestries and analyze 38 complex traits in African-European admixed individuals (N = 53,001) to observe very high correlations (meta-analysis r admix  = 0.95, 95% credible interval 0.93-0.97), much higher than correlation of causal effects across continental ancestries. We replicate our results using regression-based methods from marginal genome-wide association study summary statistics. We also report realistic scenarios where regression-based methods yield inflated heterogeneity-by-ancestry due to ancestry-specific tagging of causal effects, and/or polygenicity. Our results motivate genetic analyses that assume minimal heterogeneity in causal effects by ancestry, with implications for the inclusion of ancestry-diverse individuals in studies., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Genome-wide association studies (GWASs) have been performed to identify host genetic factors for a range of phenotypes, including for infectious diseases. The use of population-based common control subjects from biobanks and extensive consortia is a valuable resource to increase sample sizes in the identification of associated loci with minimal additional expense. Non-differential misclassification of the outcome has been reported when the control subjects are not well characterized, which often attenuates the true effect size. However, for infectious diseases the comparison of affected subjects to population-based common control subjects regardless of pathogen exposure can also result in selection bias. Through simulated comparisons of pathogen-exposed cases and population-based common control subjects, we demonstrate that not accounting for pathogen exposure can result in biased effect estimates and spurious genome-wide significant signals. Further, the observed association can be distorted depending upon strength of the association between a locus and pathogen exposure and the prevalence of pathogen exposure. We also used a real data example from the hepatitis C virus (HCV) genetic consortium comparing HCV spontaneous clearance to persistent infection with both well-characterized control subjects and population-based common control subjects from the UK Biobank. We find biased effect estimates for known HCV clearance-associated loci and potentially spurious HCV clearance associations. These findings suggest that the choice of control subjects is especially important for infectious diseases or outcomes that are conditional upon environmental exposures., Competing Interests: Declaration of interests All authors declare no competing interests., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Genome-wide association studies (GWASs) can require immense sample sizes to identify variants associated with human health across the frequency spectrum. As the Global Biobank Meta-analysis Initiative (GBMI), Zhou et al. describe a collaborative network across 23 biobanks and 2.2 million participants to address challenges of underrepresentation of diversity in genomic research., Competing Interests: Declaration of interests The author declares no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Genome-wide association studies using large-scale genome and exome sequencing data have become increasingly valuable in identifying associations between genetic variants and disease, transforming basic research and translational medicine. However, this progress has not been equally shared across all people and conditions, in part due to limited resources. Leveraging publicly available sequencing data as external common controls, rather than sequencing new controls for every study, can better allocate resources by augmenting control sample sizes or providing controls where none existed. However, common control studies must be carefully planned and executed as even small differences in sample ascertainment and processing can result in substantial bias. Here, we discuss challenges and opportunities for the robust use of common controls in high-throughput sequencing studies, including study design, quality control and statistical approaches. Thoughtful generation and use of large and valuable genetic sequencing data sets will enable investigation of a broader and more representative set of conditions, environments and genetic ancestries than otherwise possible., (© 2022. Springer Nature Limited.)

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Diarrhea is responsible for the deaths of more than 500,000 children each year, many of whom reside in low-to-middle-income countries (LMICs). Additionally, children with multiple diarrheal infections early in life have increased growth stunting and malnutrition and decreased vaccine efficacy. Two bacteria that contribute to the burden of diarrhea are Campylobacter jejuni and Campylobacter coli, both are endemic in Bangladesh. However, not all children that are exposed to these pathogens, including Campylobacter, will experience diarrhea. We hypothesized that host genetics may influence susceptibility to Campylobacter infections and performed a genome-wide association study in 534 children from two independent birth cohorts in Dhaka, Bangladesh. Infants were monitored for diarrhea for the first 2 years of life and only defined as controls if all diarrheal samples in the first year were negative for Campylobacter jejuni / C. coli. Each cohort was analyzed separately under an additive model and adjusted for length-for-age z-scores at birth and 12 months, sex, water treatment, and ancestry. In a fixed effect inverse-variance weighted meta-analysis of these two cohorts, we identified a genome-wide significant region on chromosome 8 in intron 4 of the rho guanine nucleotide exchange factor 10 gene ( ARHGEF10 ). Individuals with the G allele (rs13281104) had a 2-fold lower risk of having a Campylobacter-associated diarrheal episode than individuals with the A allele (OR 0.41, 95% CI 0.29 to 0.58, P = 3.6 × 10 -7 ). This SNP is associated with decreased expression of the neighboring gene, CLN8 , which may be involved in the transport of the cytolethal distending toxin produced by Campylobacter. IMPORTANCE Children in low-to-middle-income countries often suffer from multiple enteric infections in their first few years of life, many of which have the potential for long-lasting effects. These children are already likely to be malnourished and underweight, and chronic intestinal disturbances exacerbate these conditions. Despite public health interventions aimed at improving water, sanitation, and hygiene, enteric infections are still a leading cause of death for children under five. Previous work has included transmission dynamics, pathogen characteristics, and evaluation of interventions. Here, we examined the role of host genetic variation in susceptibility to diarrhea-associated Campylobacter infection. In our meta-analysis of two independent birth cohorts from Dhaka, Bangladesh, we found that children carrying a specific genetic variant (rs13281104, in an intron of ARHGEF10 ) were half as likely to have a diarrhea-associated Campylobacter infection in their first year of life. This protective effect may be achieved by decreasing gene expression and thereby impacting host-pathogen interactions and host immune response.

Preeclampsia is a multi-organ complication of pregnancy characterized by sudden hypertension and proteinuria that is among the leading causes of preterm delivery and maternal morbidity and mortality worldwide. The heterogeneity of preeclampsia poses a challenge for understanding its etiology and molecular basis. Intriguingly, risk for the condition increases in high-altitude regions such as the Peruvian Andes. To investigate the genetic basis of preeclampsia in a population living at high altitude, we characterized genome-wide variation in a cohort of preeclamptic and healthy Andean families (n = 883) from Puno, Peru, a city located above 3,800 meters of altitude. Our study collected genomic DNA and medical records from case-control trios and duos in local hospital settings. We generated genotype data for 439,314 SNPs, determined global ancestry patterns, and mapped associations between genetic variants and preeclampsia phenotypes. A transmission disequilibrium test (TDT) revealed variants near genes of biological importance for placental and blood vessel function. The top candidate region was found on chromosome 13 of the fetal genome and contains clotting factor genes PROZ, F7, and F10. These findings provide supporting evidence that common genetic variants within coagulation genes play an important role in preeclampsia. A selection scan revealed a potential adaptive signal around the ADAM12 locus on chromosome 10, implicated in pregnancy disorders. Our discovery of an association in a functional pathway relevant to pregnancy physiology in an understudied population of Native American origin demonstrates the increased power of family-based study design and underscores the importance of conducting genetic research in diverse populations., Competing Interests: Declaration of interests J.W.C. is currently a full-time employee at Genentech, Inc. and hold stocks in Roche Holding AG., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Throughout human evolutionary history, large-scale migrations have led to intermixing (i.e., admixture) between previously separated human groups. Although classical and recent work have shown that studying admixture can yield novel historical insights, the extent to which this process contributed to adaptation remains underexplored. Here, we introduce a novel statistical model, specific to admixed populations, that identifies loci under selection while determining whether the selection likely occurred post-admixture or prior to admixture in one of the ancestral source populations. Through extensive simulations, we show that this method is able to detect selection, even in recently formed admixed populations, and to accurately differentiate between selection occurring in the ancestral or admixed population. We apply this method to genome-wide SNP data of ∼4,000 individuals in five admixed Latin American cohorts from Brazil, Chile, Colombia, Mexico, and Peru. Our approach replicates previous reports of selection in the human leukocyte antigen region that are consistent with selection post-admixture. We also report novel signals of selection in genomic regions spanning 47 genes, reinforcing many of these signals with an alternative, commonly used local-ancestry-inference approach. These signals include several genes involved in immunity, which may reflect responses to endemic pathogens of the Americas and to the challenge of infectious disease brought by European contact. In addition, some of the strongest signals inferred to be under selection in the Native American ancestral groups of modern Latin Americans overlap with genes implicated in energy metabolism phenotypes, plausibly reflecting adaptations to novel dietary sources available in the Americas., (© The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

One mechanism by which genetic factors influence complex traits and diseases is altering gene expression. Direct measurement of gene expression in relevant tissues is rarely tenable; however, genetically regulated gene expression (GReX) can be estimated using prediction models derived from large multi-omic datasets. These approaches have led to the discovery of many gene-trait associations, but whether models derived from predominantly European ancestry (EA) reference panels can map novel associations in ancestrally diverse populations remains unclear. We applied PrediXcan to impute GReX in 51,520 ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) participants (35% African American, 45% Hispanic/Latino, 10% Asian, and 7% Hawaiian) across 25 key cardiometabolic traits and relevant tissues to identify 102 novel associations. We then compared associations in PAGE to those in a random subset of 50,000 White British participants from UK Biobank (UKBB 50k ) for height and body mass index (BMI). We identified 517 associations across 47 tissues in PAGE but not UKBB 50k , demonstrating the importance of diverse samples in identifying trait-associated GReX. We observed that variants used in PrediXcan models were either more or less differentiated across continental-level populations than matched-control variants depending on the specific population reflecting sampling bias. Additionally, variants from identified genes specific to either PAGE or UKBB 50k analyses were more ancestrally differentiated than those in genes detected in both analyses, underlining the value of population-specific discoveries. This suggests that while EA-derived transcriptome imputation models can identify new associations in non-EA populations, models derived from closely matched reference panels may yield further insights. Our findings call for more diversity in reference datasets of tissue-specific gene expression., Competing Interests: Declaration of interests E.E.K. has received speaker honoraria from Illumina, 23andMe, and Regeneron Pharmaceuticals and serves as a scientific board member for Galateo Bio., (Copyright © 2022 American Society of Human Genetics. All rights reserved.)

Aims/hypothesis: Type 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA 1c , that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA 1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study., Methods: We conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA 1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci., Results: Four novel associations were identified (p < 5 × 10 -9 ), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis., Conclusions/interpretation: Our findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations., Data Availability: Full summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics )., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Spontaneous clearance of acute hepatitis C virus (HCV) infection is associated with single nucleotide polymorphisms (SNPs) on the MHC class II. We fine-mapped the MHC region in European (n = 1,600; 594 HCV clearance/1,006 HCV persistence) and African (n = 1,869; 340 HCV clearance/1,529 HCV persistence) ancestry individuals and evaluated HCV peptide binding affinity of classical alleles. In both populations, HLA-DQβ1Leu26 (p value Meta = 1.24 × 10 -14 ) located in pocket 4 was negatively associated with HCV spontaneous clearance and HLA-DQβ1Pro55 (p value Meta = 8.23 × 10 -11 ) located in the peptide binding region was positively associated, independently of HLA-DQβ1Leu26. These two amino acids are not in linkage disequilibrium (r 2 < 0.1) and explain the SNPs and classical allele associations represented by rs2647011, rs9274711, HLA-DQB1 ∗ 03:01, and HLA-DRB1 ∗ 01:01. Additionally, HCV persistence classical alleles tagged by HLA-DQβ1Leu26 had fewer HCV binding epitopes and lower predicted binding affinities compared to clearance alleles (geometric mean of combined IC 50 nM of persistence versus clearance; 2,321 nM versus 761.7 nM, p value = 1.35 × 10 -38 ). In summary, MHC class II fine-mapping revealed key amino acids in HLA-DQβ1 explaining allelic and SNP associations with HCV outcomes. This mechanistic advance in understanding of natural recovery and immunogenetics of HCV might set the stage for much needed enhancement and design of vaccine to promote spontaneous clearance of HCV infection., Competing Interests: Declaration of interests J.C.P. has received research grant support to her institution from Gilead Sciences, Merck, and Abbvie and has served on an advisory board for Gilead Sciences and Theratechnolgies. S.H.M. have received speaker fees from Gilead Sciences not related to this work. A.H.K. serves on the Data Monitoring Committee for Kintor Pharmaceutical., (Copyright © 2022. Published by Elsevier Inc.)

Background: Spontaneous clearance of acute hepatitis C virus (HCV) infection is more common in women than in men, independent of known risk factors., Methods: To identify sex-specific genetic loci, we studied 4423 HCV-infected individuals (2903 male, 1520 female) of European, African, and Hispanic ancestry. We performed autosomal, and X chromosome sex-stratified and combined association analyses in each ancestry group., Results: A male-specific region near the adenosine diphosphate-ribosylation factor-like 5B (ARL5B) gene was identified. Individuals with the C allele of rs76398191 were about 30% more likely to have chronic HCV infection than individuals with the T allele (OR, 0.69; P = 1.98 × 10-07), and this was not seen in females. The ARL5B gene encodes an interferon-stimulated gene that inhibits immune response to double-stranded RNA viruses. We also identified suggestive associations near septin 6 and ribosomal protein L39 genes on the X chromosome. In box sexes, allele G of rs12852885 was associated with a 40% increase in HCV clearance compared with the A allele (OR, 1.4; P = 2.46 × 10-06). Septin 6 facilitates HCV replication via interaction with the HCV NS5b protein, and ribosomal protein L39 acts as an HCV core interactor., Conclusions: These novel gene associations support differential mechanisms of HCV clearance between the sexes and provide biological targets for treatment or vaccine development., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: Circulating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented., Results: We performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations., Conclusions: Our results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.

Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens and environmental factors impacting specific sub-populations. Here, we propose a framework for repurposing data from electronic health records (EHRs) in concert with genomic data to explore the demographic ties that can impact disease burdens. Using data from a diverse biobank in New York City, we identified 17 communities sharing recent genetic ancestry. We observed 1,177 health outcomes that were statistically associated with a specific group and demonstrated significant differences in the segregation of genetic variants contributing to Mendelian diseases. We also demonstrated that fine-scale population structure can impact the prediction of complex disease risk within groups. This work reinforces the utility of linking genomic data to EHRs and provides a framework toward fine-scale monitoring of population health., Competing Interests: Declaration of interests N.S.A.-H. was previously employed by Regeneron Pharmaceuticals and has received a speaker honorarium from Genentech. E.E.K. has received speaker honoraria from Illumina and Regeneron Pharmaceuticals. S.W. is currently employed at Tempus. A.M. is currently employed at Regeneron. E.P.S. is currently employed at Calico. D.S.P. is currently employed at Ancestry. A.A. is currently employed at 23&Me. The remaining authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

Objective: Pediatric acute-onset neuropsychiatric syndrome (PANS) is a complex neuropsychiatric syndrome characterized by an abrupt onset of obsessive-compulsive symptoms and/or severe eating restrictions, along with at least two concomitant debilitating cognitive, behavioral, or neurological symptoms. A wide range of pharmacological interventions along with behavioral and environmental modifications, and psychotherapies have been adopted to treat symptoms and underlying etiologies. Our goal was to develop a data-driven approach to identify treatment patterns in this cohort., Materials and Methods: In this cohort study, we extracted medical prescription histories from electronic health records. We developed a modified dynamic programming approach to perform global alignment of those medication histories. Our approach is unique since it considers time gaps in prescription patterns as part of the similarity strategy., Results: This study included 43 consecutive new-onset pre-pubertal patients who had at least 3 clinic visits. Our algorithm identified six clusters with distinct medication usage history which may represent clinician's practice of treating PANS of different severities and etiologies i.e., two most severe groups requiring high dose intravenous steroids; two arthritic or inflammatory groups requiring prolonged nonsteroidal anti-inflammatory drug (NSAID); and two mild relapsing/remitting group treated with a short course of NSAID. The psychometric scores as outcomes in each cluster generally improved within the first two years., Discussion and Conclusion: Our algorithm shows potential to improve our knowledge of treatment patterns in the PANS cohort, while helping clinicians understand how patients respond to a combination of drugs., (Copyright © 2020. Published by Elsevier Inc.)

Clearance of acute infection with hepatitis C virus (HCV) is associated with the chr19q13.13 region containing the rs368234815 (TT/ΔG) polymorphism. We fine-mapped this region to detect possible causal variants that may contribute to HCV clearance. First, we performed sequencing of IFNL1-IFNL4 region in 64 individuals sampled according to rs368234815 genotype: TT/clearance (N = 16) and ΔG/persistent (N = 15) (genotype-outcome concordant) or TT/persistent (N = 19) and ΔG/clearance (N = 14) (discordant). 25 SNPs had a difference in counts of alternative allele >5 between clearance and persistence individuals. Then, we evaluated those markers in an association analysis of HCV clearance conditioning on rs368234815 in two groups of European (692 clearance/1 025 persistence) and African ancestry (320 clearance/1 515 persistence) individuals. 10/25 variants were associated (P < 0.05) in the conditioned analysis leaded by rs4803221 (P value = 4.9 × 10 -04 ) and rs8099917 (P value = 5.5 × 10 -04 ). In the European ancestry group, individuals with the haplotype rs368234815ΔG/rs4803221C were 1.7× more likely to clear than those with the rs368234815ΔG/rs4803221G haplotype (P value = 3.6 × 10 -05 ). For another nearby SNP, the haplotype of rs368234815ΔG/rs8099917T was associated with HCV clearance compared to rs368234815ΔG/rs8099917G (OR: 1.6, P value = 1.8 × 10 -04 ). We identified four possible causal variants: rs368234815, rs12982533, rs10612351 and rs4803221. Our results suggest a main signal of association represented by rs368234815, with contributions from rs4803221, and/or nearby SNPs including rs8099917.

Background: We examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci., Methods: We decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15% Black; 30% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test., Results: We identified 6 novels ( CD36, PITX2, EMB, ZNF592, YPEL2 , and BC043580 ) and 87 known loci (adaptive sum of powered score test P <5×10 -9 ). Lead single-nucleotide polymorphism rs3211938 at CD36 was common in Blacks (minor allele frequency=10%), near monomorphic in European Americans, and had effects on the QT interval and TP segment that ranked among the largest reported to date for common variants. The other 5 novel loci were observed when evaluating the contiguous but not the composite electrocardiographic traits. Combined phenotype testing did not identify novel electrocardiographic loci unapparent using traditional univariate approaches, although this approach did assist with the characterization of known loci., Conclusions: Despite including one-third as many participants as published electrocardiographic trait genome-wide association studies, our study identified 6 novel loci, emphasizing the importance of ancestral diversity and phenotype resolution in this era of ever-growing genome-wide association studies.

The possibility of voyaging contact between prehistoric Polynesian and Native American populations has long intrigued researchers. Proponents have pointed to the existence of New World crops, such as the sweet potato and bottle gourd, in the Polynesian archaeological record, but nowhere else outside the pre-Columbian Americas 1-6 , while critics have argued that these botanical dispersals need not have been human mediated 7 . The Norwegian explorer Thor Heyerdahl controversially suggested that prehistoric South American populations had an important role in the settlement of east Polynesia and particularly of Easter Island (Rapa Nui) 2 . Several limited molecular genetic studies have reached opposing conclusions, and the possibility continues to be as hotly contested today as it was when first suggested 8-12 . Here we analyse genome-wide variation in individuals from islands across Polynesia for signs of Native American admixture, analysing 807 individuals from 17 island populations and 15 Pacific coast Native American groups. We find conclusive evidence for prehistoric contact of Polynesian individuals with Native American individuals (around AD 1200) contemporaneous with the settlement of remote Oceania 13-15 . Our analyses suggest strongly that a single contact event occurred in eastern Polynesia, before the settlement of Rapa Nui, between Polynesian individuals and a Native American group most closely related to the indigenous inhabitants of present-day Colombia.

Genome-wide association studies have revolutionized our understanding of the genetic underpinnings of cardiometabolic disease. Yet, the inadequate representation of individuals of diverse ancestral backgrounds in these studies may undercut their ultimate potential for both public health and precision medicine. The goal of this review is to describe the imperativeness of studying the populations who are most affected by cardiometabolic disease, to the aim of better understanding the genetic underpinnings of the disease. We support this premise by describing the current variation in the global burden of cardiometabolic disease and emphasize the importance of building a globally and ancestrally representative genetics evidence base for the identification of population-specific variants, fine-mapping, and polygenic risk score estimation. We discuss the important ethical, legal, and social implications of increasing ancestral diversity in genetic studies of cardiometabolic disease and the challenges that arise from the (1) lack of diversity in current reference populations and available analytic samples and the (2) unequal generation of health-associated genomic data and their prediction accuracies. Despite these challenges, we conclude that additional, unprecedented opportunities lie ahead for public health genomics and the realization of precision medicine, provided that the gap in diversity can be systematically addressed. Achieving this goal will require concerted efforts by social, academic, professional and regulatory stakeholders and communities, and these efforts must be based on principles of equity and social justice.

Background & Aims: The Ile138Met variant (rs738409) in the PNPLA3 gene has the largest effect on non-alcoholic fatty liver disease (NAFLD), increasing the risk of progression to severe forms of liver disease. It remains unknown if the variant plays a role in age of NAFLD onset. We aimed to determine if rs738409 impacts on the age of NAFLD diagnosis., Methods: We applied a novel natural language processing (NLP) algorithm to a longitudinal electronic health records (EHR) dataset of >27,000 individuals with genetic data from a multi-ethnic biobank, defining NAFLD cases (n = 1,703) and confirming controls (n = 8,119). We conducted i) a survival analysis to determine if age at diagnosis differed by rs738409 genotype, ii) a receiver operating characteristics analysis to assess the utility of the rs738409 genotype in discriminating NAFLD cases from controls, and iii) a phenome-wide association study (PheWAS) between rs738409 and 10,095 EHR-derived disease diagnoses., Results: The PNPLA3 G risk allele was associated with: i) earlier age of NAFLD diagnosis, with the strongest effect in Hispanics (hazard ratio 1.33; 95% CI 1.15-1.53; p <0.0001) among whom a NAFLD diagnosis was 15% more likely in risk allele carriers vs. non-carriers; ii) increased NAFLD risk (odds ratio 1.61; 95% CI 1.349-1.73; p <0.0001), with the strongest effect among Hispanics (odds ratio 1.43; 95% CI 1.28-1.59; p <0.0001); iii) additional liver diseases in a PheWAS (p <4.95 × 10 -6 ) where the risk variant also associated with earlier age of diagnosis., Conclusion: Given the role of the rs738409 in NAFLD diagnosis age, our results suggest that stratifying risk within populations known to have an enhanced risk of liver disease, such as Hispanic carriers of the rs738409 variant, would be effective in earlier identification of those who would benefit most from early NAFLD prevention and treatment strategies., Lay Summary: Despite clear associations between the PNPLA3 rs738409 variant and elevated risk of progression from non-alcoholic fatty liver disease (NAFLD) to more severe forms of liver disease, it remains unknown if PNPLA3 rs738409 plays a role in the age of NAFLD onset. Herein, we found that this risk variant is associated with an earlier age of NAFLD and other liver disease diagnoses; an observation most pronounced in Hispanic Americans. We conclude that PNPLA3 rs738409 could be used to better understand liver disease risk within vulnerable populations and identify patients that may benefit from early prevention strategies., Competing Interests: Conflict of interest The authors declare no conflicts of interest that pertain to this work. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2020 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Background: Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population., Results: We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP., Conclusion: This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations.

Diarrhea is a major cause of both morbidity and mortality worldwide, especially among young children. Cryptosporidiosis is a leading cause of diarrhea in children, particularly in South Asia and sub-Saharan Africa, where it is responsible for over 200,000 deaths per year. Beyond the initial clinical presentation of diarrhea, it is associated with long-term sequelae such as malnutrition and neurocognitive developmental deficits. Risk factors include poverty and overcrowding, and yet not all children with these risk factors and exposure are infected, nor do all infected children develop symptomatic disease. One potential risk factor to explain these differences is their human genome. To identify genetic variants associated with symptomatic cryptosporidiosis, we conducted a genome-wide association study (GWAS) examining 6.5 million single nucleotide polymorphisms (SNPs) in 873 children from three independent cohorts in Dhaka, Bangladesh, namely, the Dhaka Birth Cohort (DBC), the Performance of Rotavirus and Oral Polio Vaccines in Developing Countries (PROVIDE) study, and the Cryptosporidiosis Birth Cohort (CBC). Associations were estimated separately for each cohort under an additive model, adjusting for length-for-age Z-score at 12 months of age, the first two principal components to account for population substructure, and genotyping batch. The strongest meta-analytic association was with rs58296998 ( P  = 3.73 × 10 -8 ), an intronic SNP and expression quantitative trait locus (eQTL) of protein kinase C alpha ( PRKCA ). Each additional risk allele conferred 2.4 times the odds of Cryptosporidium -associated diarrhea in the first year of life. This genetic association suggests a role for protein kinase C alpha in pediatric cryptosporidiosis and warrants further investigation. IMPORTANCE Globally, diarrhea remains one of the major causes of pediatric morbidity and mortality. The initial symptoms of diarrhea can often lead to long-term consequences for the health of young children, such as malnutrition and neurocognitive developmental deficits. Despite many children having similar exposures to infectious causes of diarrhea, not all develop symptomatic disease, indicating a possible role for human genetic variation. Here, we conducted a genetic study of susceptibility to symptomatic disease associated with Cryptosporidium infection (a leading cause of diarrhea) in three independent cohorts of infants from Dhaka, Bangladesh. We identified a genetic variant within protein kinase C alpha ( PRKCA ) associated with higher risk of cryptosporidiosis in the first year of life. These results indicate a role for human genetics in susceptibility to cryptosporidiosis and warrant further research to elucidate the mechanism., (Copyright © 2020 Wojcik et al.)

The past decade has seen a technological revolution in human genetics that has empowered population-level investigations into genetic associations with phenotypes. Although these discoveries rely on genetic variation across individuals, association studies have overwhelmingly been performed in populations of European descent. In this review, we describe limitations faced by single-population studies and provide an overview of strategies to improve global representation in existing data sets and future human genomics research via diversity-focused, multiethnic studies. We highlight the successes of individual studies and meta-analysis consortia that have provided unique knowledge. Additionally, we outline the approach taken by the Population Architecture Using Genomics and Epidemiology (PAGE) study to develop best practices for performing genetic epidemiology in multiethnic contexts. Finally, we discuss how limiting investigations to single populations impairs findings in the clinical domain for both rare-variant identification and genetic risk prediction.

Background: African Americans (AAs) and Hispanic/Latinos (HLs) have higher risk of obesity than European Americans, possibly due to differences in environment and lifestyle, but also reflecting differences in genetic background., Objective: To gain insight into factors contributing to BMI (in kg/m2) and obesity risk (BMI ≥ 30) among ancestry groups, we investigate the role of self-reported ancestry, proportion of genetic African ancestry, and country of birth in 6368 self-identified AA and 7569 HL participants of the New York-based BioMe Biobank., Methods: AAs and HLs are admixed populations that trace their genetic ancestry to the Americas, Africa, and Europe. The proportion of African ancestry (PAA), quantified using ADMIXTURE, was higher among self-reported AA (median: 87%; IQR: 79-92%) than among HL (26%; 15-41%) participants. Approximately 18% of AA and 59% of HL participants were non-US-born., Results: Because of significant differences between sexes (PPAA*sex interaction = 4.8 × 10-22), we considered women and men separately. Among women, country of birth and genetic ancestry contributed independently to BMI. US-born women had a BMI 1.99 higher than those born abroad (P = 7.7 × 10-25). Every 10% increase in PAA was associated with a BMI 0.29 higher (P = 7.1 × 10-10). After accounting for PAA and country of birth, the contribution of self-reported ancestry was small (P = 0.046). The contribution of PAA to higher BMI was significantly more pronounced among US-born (0.35/10%PAA, P = 0.003) than among non-US-born (0.26/10%PAA, P = 0.01) women (PPAA*sex interaction = 0.004). In contrast, among men, only US-born status influenced BMI. US-born men had a BMI 1.33 higher than non-US-born men, whereas PAA and self-reported ancestry were not associated with BMI. Associations with obesity risk were similar to those observed for BMI., Conclusions: Being US-born is associated with a substantially higher BMI and risk of obesity in both men and women. Genetic ancestry, but not self-reported ancestry, is associated with obesity susceptibility, but only among US-born women in this New York-based population., (Copyright © American Society for Nutrition 2019.)

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry 1-3 . In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific 4-10 . Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations 11,12 . Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions 13 -the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

The varying frequencies of pharmacogenetic alleles among populations have important implications for the impact of these alleles in different populations. Current population grouping methods to communicate these patterns are insufficient as they are inconsistent and fail to reflect the global distribution of genetic variability. To facilitate and standardize the reporting of variability in pharmacogenetic allele frequencies, we present seven geographically defined groups: American, Central/South Asian, East Asian, European, Near Eastern, Oceanian, and Sub-Saharan African, and two admixed groups: African American/Afro-Caribbean and Latino. These nine groups are defined by global autosomal genetic structure and based on data from large-scale sequencing initiatives. We recognize that broadly grouping global populations is an oversimplification of human diversity and does not capture complex social and cultural identity. However, these groups meet a key need in pharmacogenetics research by enabling consistent communication of the scale of variability in global allele frequencies and are now used by Pharmacogenomics Knowledgebase (PharmGKB)., (© 2018 The Authors Clinical Pharmacology & Therapeutics © 2018 American Society for Clinical Pharmacology and Therapeutics.)

Background & Aims: Spontaneous clearance of hepatitis C virus (HCV) occurs in approximately 30% of infected persons and less often in populations of African ancestry. Variants in major histocompatibility complex (MHC) and in interferon lambda genes are associated with spontaneous HCV clearance, but there have been few studies of these variants in persons of African ancestry. We performed a dense multi-ancestry genome-wide association study of spontaneous clearance of HCV, focusing on individuals of African ancestry., Methods: We performed genotype analyses of 4423 people from 3 ancestry groups: 2201 persons of African ancestry (445 with HCV clearance and 1756 with HCV persistence), 1739 persons of European ancestry (701 with HCV clearance and 1036 with HCV persistence), and 486 multi-ancestry Hispanic persons (173 with HCV clearance and 313 with HCV persistence). Samples were genotyped using Illumina (San Diego, CA) arrays and statistically imputed to the 1000 Genomes Project. For each ancestry group, the association of single-nucleotide polymorphisms with HCV clearance was tested by log-additive analysis, and then a meta-analysis was performed., Results: In the meta-analysis, significant associations with HCV clearance were confirmed at the interferon lambda gene locus IFNL4-IFNL3 (19q13.2) (P = 5.99 × 10 -50 ) and the MHC locus 6p21.32 (P = 1.15 × 10 -21 ). We also associated HCV clearance with polymorphisms in the G-protein-coupled receptor 158 gene (GPR158) at 10p12.1 (P = 1.80 × 10 -07 ). These 3 loci had independent, additive effects of HCV clearance, and account for 6.8% and 5.9% of the variance of HCV clearance in persons of European and African ancestry, respectively. Persons of African or European ancestry carrying all 6 variants were 24-fold and 11-fold, respectively, more likely to clear HCV infection compared with individuals carrying none or 1 of the clearance-associated variants., Conclusions: In a meta-analysis of data from 3 studies, we found variants in MHC genes, IFNL4-IFNL3, and GPR158 to increase odds of HCV clearance in patients of European and African ancestry. These findings could increase our understanding of immune response to and clearance of HCV infection., (Copyright © 2019. Published by Elsevier Inc.)

The emergence of very large cohorts in genomic research has facilitated a focus on genotype-imputation strategies to power rare variant association. These strategies have benefited from improvements in imputation methods and association tests, however little attention has been paid to ways in which array design can increase rare variant association power. Therefore, we developed a novel framework to select tag SNPs using the reference panel of 26 populations from Phase 3 of the 1000 Genomes Project. We evaluate tag SNP performance via mean imputed r 2 at untyped sites using leave-one-out internal validation and standard imputation methods, rather than pairwise linkage disequilibrium. Moving beyond pairwise metrics allows us to account for haplotype diversity across the genome for improve imputation accuracy and demonstrates population-specific biases from pairwise estimates. We also examine array design strategies that contrast multi-ethnic cohorts vs. single populations, and show a boost in performance for the former can be obtained by prioritizing tag SNPs that contribute information across multiple populations simultaneously. Using our framework, we demonstrate increased imputation accuracy for rare variants (frequency < 1%) by 0.5-3.1% for an array of one million sites and 0.7-7.1% for an array of 500,000 sites, depending on the population. Finally, we show how recent explosive growth in non-African populations means tag SNPs capture on average 30% fewer other variants than in African populations. The unified framework presented here will enable investigators to make informed decisions for the design of new arrays, and help empower the next phase of rare variant association for global health., (Copyright © 2018 Wojcik et al.)

Entamoeba histolytica is the etiologic agent of amebic dysentery, though clinical manifestation of infection is highly variable ranging from subclinical colonization to invasive disease. We hypothesize that host genetics contribute to the variable outcomes of E. histolytica infection; thus, we conducted a genome-wide association study (GWAS) in two independent birth cohorts of Bangladeshi infants monitored for susceptibility to E. histolytica disease in the first year of life. Children with at least one diarrheal episode positive for E. histolytica (cases) were compared to children with no detectable E. histolytica infection in the same time frame (controls). Meta-analyses under a fixed-effect inverse variance weighting model identified multiple variants in a region of chromosome 10 containing loci associated with symptomatic E. histolytica infection. An intergenic insertion between CREM and CCNY (rs58000832) achieved genome-wide significance ( P value from meta-analysis [ P meta ] = 6.05 × 10 -9 ), and each additional risk allele of rs58000832 conferred 2.42 increased odds of a diarrhea-associated E. histolytica infection. The most strongly associated single nucleotide polymorphism (SNP) within a gene was in an intron of CREM (rs58468612; P meta = 8.94 × 10 -8 ), which has been implicated as a susceptibility locus for inflammatory bowel disease (IBD). Gene expression resources suggest associated loci are related to the lower expression of CREM Increased CREM expression is also observed in early E. histolytica infection. Further, CREM - / - mice were more susceptible to E. histolytica amebic colitis. These genetic associations reinforce the pathological similarities observed in gut inflammation between E. histolytica infection and IBD. IMPORTANCE Diarrhea is the second leading cause of death for children globally, causing 760,000 deaths each year in children less than 5 years old. Amebic dysentery contributes significantly to this burden, especially in developing countries. The identification of host factors that control or enable enteric pathogens has the potential to transform our understanding of disease predisposition, outcomes, and treatments. Our discovery of the transcriptional regulator cAMP-responsive element modulator (CREM) as a genetic modifier of susceptibility to amebic disease has implications for understanding the pathogenesis of other diarrheal infections. Further, emerging evidence for CREM in IBD susceptibility suggests that CREM is a critical regulator of enteric inflammation and may have broad therapeutic potential as a drug target across intestinal inflammatory diseases., (Copyright © 2018 Wojcik et al.)