While respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma share many risk factors, most studies investigate them in isolation and in predominantly European-ancestry populations. Here, we conducted the most powerful multi-trait and multi-ancestry genetic analysis of respiratory diseases and auxiliary traits to date, identifying 25 new loci associated with lung function in individuals of East Asian ancestry. Using these results, we developed PRSxtra (cross-trait and cross-ancestry), a multi-trait and multi-ancestry polygenic risk score (PRS) approach that leverages shared components of heritable risk via pleiotropic effects. PRSxtra significantly improved the prediction of asthma, COPD and lung cancer compared to trait- and ancestry-matched PRSs in a multi-ancestry cohort from the All of Us Research Program, especially in diverse populations. Our results present a new framework for multi-trait and multi-ancestry studies of respiratory diseases to improve genetic discovery and polygenic prediction. Multi-trait genome-wide analyses identify variants associated with comorbid lung diseases. Polygenic scores leveraging shared components of heritable risk improve prediction of asthma, chronic obstructive pulmonary disease and lung cancer in a multi-ancestry cohort.

Recent studies have demonstrated that polygenic risk scores (PRS) trained on multi-ancestry data can improve prediction accuracy in groups historically underrepresented in genomic studies, but the availability of linked health and genetic data from large-scale diverse cohorts representative of a wide spectrum of human diversity remains limited. To address this need, the All of Us research program (AoU) generated whole-genome sequences of 245,388 individuals (release v7) who collectively reflect the diversity of the USA. Leveraging this resource and another widely-used population-scale biobank, the UK Biobank (UKB) with a half million participants, we developed PRS trained on multi-ancestry and multi-biobank data with up to ~750,000 participants for 32 common, complex traits and diseases across a range of genetic architectures. We then evaluated effects of ancestry, PRS methodology, and genetic architecture on PRS accuracy across a held out subset of ancestrally diverse AoU participants. Overall, we found that the increased diversity of AoU significantly improved PRS performance in some participants in AoU, especially underrepresented individuals, across multiple phenotypes. Notably, maximizing sample size by combining discovery data across AoU and UKB is not the optimal approach for predicting some phenotypes particularly in African ancestry populations; rather, using data from only AoU for these traits resulted in the greatest accuracy. This was especially true for less polygenic traits with large ancestry-enriched effects, and larger heritability estimates in African ancestry populations, such as neutrophil count (R 2: 0.055 vs. 0.035 using AoU vs. cross-biobank meta-analysis, respectively, because of e.g. DARC). Lastly, we calculated individual-level PRS accuracies rather than grouping by continental ancestry, a critical step towards interpretability in precision medicine. Individualized PRS accuracy decays linearly as a function of ancestry divergence, but the slope was smaller using multi-ancestry GWAS compared to using European GWAS. Our results highlight the potential of biobanks with more balanced representations of human diversity to facilitate more accurate PRS for the individuals least represented in genomic studies.

Genome-wide association studies (GWAS) have predominantly focused on European ancestry populations, limiting biological discoveries across diverse populations. Here we report GWAS findings from 153,950 individuals across 36 quantitative traits in the Korean Cancer Prevention Study-II (KCPS2) Biobank. We discovered 301 previously unreported genetic loci in KCPS2, including an association between thyroid-stimulating hormone and CD36. Meta-analysis with the Korean Genome and Epidemiology Study, Biobank Japan, Taiwan Biobank, and UK Biobank identified 4588 loci that were not significant in any contributing GWAS. We describe differences in genetic architectures across these East Asian and European samples. We also highlight East Asian specific associations, including a known pleiotropic missense variant in ALDH2, which fine-mapping identified as a likely causal variant for multiple traits. Our findings provide insights into the genetic architecture of complex traits in East Asian populations and highlight how broadening the population diversity of GWAS samples can aid discovery.

IntroductionIn the dynamic landscape of healthcare, pharmacists play a critical role in ensuring the well-being of communities, and having solid professional organisations to support pharmacists is essential in crucial activities, including continuing education, advocacy and establishing service standards. Eight pharmacy organisations play vital roles in representing pharmacists in various sectors and collectively contribute to developing, regulating, and promoting the pharmacy profession in Australia. However, a notable lack of female representation in these organisations' leadership roles has led to an increased focus on gender balance and equity.ObjectiveTo determine if the gender distribution in pharmacy leadership aligns with the pharmacy workforce in Australia (64% women) and how it has changed in the five years since our last study on the issue.SettingAustralia.MethodEight key Australian pharmacy organisations were identified. The website for each organisation was accessed, and data were recorded for their 2023 boards/committees/councils based on annual reports. Data recorded include name, number of males, number of females, and the gender of the president/chair of each board/committee/council.ResultsData were obtained for 340 separate professional committee members from the eight organisations (including state/territory branches) in 2023. Gender balance in pharmacy organisations has increased significantly since 2018, with women's representation in leadership positions now at 58% (47% 2018).ConclusionGender equity within Australian pharmacy professional organisations has significantly progressed.

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

Food literacy is a growing area of interest given its potential to support healthy and sustainable diets. Most existing food literacy measures focus on nutrition and food skills but fail to address food systems and socio-environmental aspects of food literacy. Further, measures developed and tested in the Canadian context are lacking. The objective of this project was to develop and test the validity and reliability of a brief self-administered measure, in French and English, designed to assess multiple dimensions of food literacy among adults living in Canada. The 23-item Canadian Food Literacy Measure was developed through an iterative process that included assessment of face and content validity through expert review (n=20) and cognitive interviews (n=20), and construct validity and reliability, i.e., internal consistency through an online survey (n=154). The results indicate that the measure is well understood by both English- and French-speaking adults. The measure’s construct validity is demonstrated by the observed differences in total scores in hypothesized directions by gender (p=0.003), age (p=0.007), education level (p=0.002), health literacy (p<0.001) and smoking status (p=0.001) and the significant positive correlation (r = 0.29; p=0.002) between total scores and fruit and vegetable intake. The measure also has high internal consistency with a Cronbach’s coefficient alpha of 0.80. This measure can be used in surveillance studies to provide insight into the food literacy of adults living in Canada and in epidemiologic research that aims to explore how food literacy is associated with a variety of health outcomes.

Background Alcohol use disorder (AUD) is a chronic psychiatric illness with high morbidity and mortality globally. Previous studies have largely focused on individuals of European ancestry from high-income countries. In this study, we examine the genetic architecture and polygenic prediction of AUD in a unique community-based sample of 10,032 admixed individuals from the Chitwan Valley Family Study in Nepal. Methods We applied a genome-based restricted maximum likelihood framework to estimate the narrow-sense heritability of AUD using the Genome-wide Complex Trait Analysis (GCTA) software applied to a sample of related individuals in Nepal. Subsequently, we performed a generalized linear mixed model GWAS on AUD with sex, age, ethnicity, and 20 PCs as fixed effect covariates. Finally, we used PRS-CS to calculate polygenic risk scores (PRS) from GWAS summary statistics for problematic alcohol use among individuals in the Million Veteran Program. To account for population structure and relatedness, we fitted a series of sequential mixed models using GCTA to assess incremental improvements in phenotypic variance explained (R2) by covariates including PRS. Results In the study population, 596 (5.94%) individuals met lifetime diagnostic criteria for AUD, with the majority of cases (565, 94.80%) being males. AUD risk was associated with male sex (β=3.23, P=7.15 × 10^-68), higher age (β=0.025, P=4.1 × 10^-14), and childhood exposure to potentially traumatic events (β=0.81, P=6.06 × 10^-16). The heritability of AUD was 0.079 (se=0.015, p=1.07 × 10^-17) on the observed scale. We identified a novel locus on chromosome 4 with the lead SNP chr4:144995070:A:C (P=1.18 × 10^-08) residing within GYPB, a gene coding for red blood cell antigens. PRS was significantly associated with increased risk of AUD (P=2.53 × 10^-3), with individuals in the top decile of PRS having an odds ratio of 1.495 (P=1.09 × 10^-3) for AUD. In the full sample, the incremental R2 of PRS on the liability scale was 0.003 (SE=0.001, 95% CI 0.0006–0.0046) compared to covariates alone. In the male subsample (N=4,517), the incremental R2 of PRS was 0.003 (SE=0.001, 95% CI 0.0009–0.0052). Discussion We conducted the first genetic study of alcohol use in a unique and ancestrally diverse cohort from the Chitwan Valley in Nepal. We found evidence of substantial genetic basis for AUD in this population, although the estimated heritability is notably lower than previous estimates from European ancestry samples. We identify a novel locus with preliminary evidence for association with AUD and find PRS to have modest predictive utility. Our results reveal new insights into the genetic architecture of this unique sample and highlight the necessity to study under-represented groups in genomic research to ensure equitable translation of research findings across global populations.

Biobanks have emerged as valuable resources for studying behavioural and social genomics, but are not representative of global populations. Thus, current research findings do not generalize, and exacerbate knowledge and health inequalities. We call on researchers, publishers and funders to address barriers to biobank diversity.

Abstract Evidence for adaptation of human skin color to regional ultraviolet radiation suggests shared and distinct genetic variants across populations. However, skin color evolution and genetics in East Asians are understudied. We quantified skin color in 48,433 East Asians using image analysis and identified associated genetic variants and potential causal genes for skin color as well as their polygenic interplay with sun exposure. This genome-wide association study (GWAS) identified 12 known and 11 previously unreported loci and SNP-based heritability was 23–24%. Potential causal genes were determined through the identification of nonsynonymous variants, colocalization with gene expression in skin tissues, and expression levels in melanocytes. Genomic loci associated with pigmentation in East Asians substantially diverged from European populations, and we detected signatures of polygenic adaptation. This large GWAS for objectively quantified skin color in an East Asian population improves understanding of the genetic architecture and polygenic adaptation of skin color and prioritizes potential causal genes.

Importance Psychological distress is characterized by anxiety and depressive symptoms. Although prior research has investigated the occurrence and factors associated with psychological distress in low- and middle-income countries, including those in Africa, these studies' findings are not very generalizable and have focused on different kinds of population groups. Objective To investigate the prevalence and characteristics (sociodemographic, psychosocial, and clinical) associated with psychological distress among African participants. Design, setting, and participants This case-control study analyzed data of participants in the Neuropsychiatric Genetics in African Populations-Psychosis (NeuroGAP-Psychosis) study, which recruited from general outpatient clinics in Eastern (Uganda, Kenya, and Ethiopia) and Southern (South Africa) Africa. Individuals who participated in the control group of NeuroGAP-Psychosis from 2018 to 2023 were analyzed as part of this study. Data were analyzed from May 2023 to January 2024. Main outcomes and measures The prevalence of psychological distress was determined using the Kessler Psychological Distress Scale (K10), which measures distress on a scale of 10 to 50, with higher scores indicating more distress. Participants from the NeuroGAP-Psychosis study were categorized into cases as mild (score of 20-24), moderate (score of 25-29), and severe (score of 30-50), and participants with scores less than 20 were considered controls. Factors that were associated with psychological distress were examined using binomial logistic regression. Results From the data on 21 308 participants, the mean (SD) age was 36.5 (11.8) years, and 12 096 participants (56.8%) were male. The majority of the participants were married or cohabiting (10 279 participants [48.2%]), most had attained secondary education as their highest form of learning (9133 participants [42.9%]), and most lived with their families (17 231 participants [80.9%]). The prevalence of mild, moderate, and severe psychological distress was 4.2% (869 participants), 1.5% (308 participants), and 0.8% (170 participants), respectively. There were 19 961 participants (93.7%) who served as controls. Binomial logistic regression analyses indicated that the independent associations of psychological distress were experience of traumatic events, substance use (alcohol, tobacco, or cannabis), the physical comorbidity of arthritis, chronic neck or back pain, and frequent or severe headaches. Conclusions and relevance In this case-control study among ethnically diverse African participants, psychological distress was associated with traumatic stress, substance use, and physical symptoms. These findings were observed to be consistent with previous research that emphasizes the importance of traumatic events as a factor associated with risk for psychopathology and notes the frequent co-occurrence of conditions such as physical symptoms, depression, and anxiety.

ABSTRACTPolygenic risk scores (PRS) are an emerging tool to predict the clinical phenotypes and outcomes of individuals. Validation and transferability of existing PRS across independent datasets and diverse ancestries are limited, which hinders the practical utility and exacerbates health disparities. We propose PRSmix, a framework that evaluates and leverages the PRS corpus of a target trait to improve prediction accuracy, and PRSmix+, which incorporates genetically correlated traits to better capture the human genetic architecture. We applied PRSmix to 47 and 32 diseases/traits in European and South Asian ancestries, respectively. PRSmix demonstrated a mean prediction accuracy improvement of 1.20-fold (95% CI: [1.10; 1.3]; P-value = 9.17 × 10−5) and 1.19-fold (95% CI: [1.11; 1.27]; P-value = 1.92 × 10−6), and PRSmix+ improved the prediction accuracy by 1.72-fold (95% CI: [1.40; 2.04]; P-value = 7.58 × 10−6) and 1.42-fold (95% CI: [1.25; 1.59]; P-value = 8.01 × 10−7) in European and South Asian ancestries, respectively. Compared to the previously established cross-trait-combination method with scores from pre-defined correlated traits, we demonstrated that our method can improve prediction accuracy for coronary artery disease up to 3.27-fold (95% CI: [2.1; 4.44]; P-value after FDR correction = 2.6 × 10−4). Our method provides a comprehensive framework to benchmark and leverage the combined power of PRS for maximal performance in a desired target population.

Primary open -angle glaucoma (POAG), a leading cause of irreversible blindness globally, shows disparity in prevalence and manifestations across ancestries. We perform meta -analysis across 15 biobanks (of the Global Biobank Meta -analysis Initiative) (n = 1,487,441: cases = 26,848) and merge with previous multiancestry studies, with the combined dataset representing the largest and most diverse POAG study to date (n = 1,478,037: cases = 46,325) and identify 17 novel significant loci, 5 of which were ancestry specific. Gene -enrichment and transcriptome-wide association analyses implicate vascular and cancer genes, a fifth of which are primary ciliary related. We perform an extensive statistical analysis of SIX6 and CDKN2B-AS1 loci in human GTEx data and across large electronic health records showing interaction between SIX6 gene and causal variants in the chr9p21.3 locus, with expression effect on CDKN2A/B. Our results suggest that some POAG risk variants may be ancestry specific, sex specific, or both, and support the contribution of genes involved in programmed cell death in POAG pathogenesis.

The quality improvement study examines the use of risk-adaptive adjuvant radiotherapy in women with non–mismatch repair deficiency endometrial cancer.

Large biobanks, such as the UK Biobank (UKB), enable massive phenome by genome-wide association studies that elucidate genetic etiology of complex traits. However, individuals from diverse genetic ancestry groups are often excluded from association analyses due to concerns about population structure introducing false positive associations. Here, we generate mixed model associations and meta-analyses across genetic ancestry groups, inclusive of a larger fraction of the UKB than previous efforts, to produce freely-available summary statistics for 7,271 traits. We build a quality control and analysis framework informed by genetic architecture. Overall, we identify 14,676 significant loci in the meta-analysis that were not found in the European genetic ancestry group alone, including novel associations for example between CAMK2D and triglycerides. We also highlight associations from ancestry-enriched variation, including a known pleiotropic missense variant in G6PD associated with several biomarker traits. We release these results publicly alongside FAQs that describe caveats for interpretation of results, enhancing available resources for interpretation of risk variants across diverse populations. ### Competing Interest Statement K.J.K. is a consultant for Tome Biosciences, AlloDx, and Vor Biosciences, and a member of the scientific advisory board of Nurture Genomics. M.J.D is a founder of Maze Therapeutics. B.M.N. is a member of the scientific advisory board at Deep Genomics and Neumora. ### Funding Statement This work was supported by the Novo Nordisk Foundation (NNF21SA0072102), NIH grants R37MH107649, R00MH117229, K01MH121659, F31HL167378, and F30AG074507, and BroadIgnite funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study used data from the UK Biobank. UK Biobank has approval from the North West Multi-centre Research Ethics Committee (MREC) as a Research Tissue Bank (RTB) approval. This approval means that researchers do not require separate ethical clearance and can operate under the RTB approval. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data are available at https://pan.ukbb.broadinstitute.org/, and sample metadata is available in the UK Biobank showcase under return number 2442: https://biobank.ndph.ox.ac.uk/ukb/dset.cgi?id=2442.

Background:The Populations Underrepresented in Mental illness Association Studies (PUMAS) project is attempting to remediate the historical underrepresentation of African and Latin American populations in psychiatric genetics through large-scale genetic association studies of individuals diagnosed with a serious mental illness [SMI, including schizophrenia (SCZ), schizoaffective disorder (SZA) bipolar disorder (BP), and severe major depressive disorder (MDD)] and matched controls. Given growing evidence indicating substantial symptomatic and genetic overlap between these diagnoses, we sought to enable transdiagnostic genetic analyses of PUMAS data by conducting phenotype alignment and harmonization for 89,320 participants (48,165 cases and 41,155 controls) from four cohorts, each of which used different ascertainment and assessment methods: PAISA n=9,105; PUMAS-LATAM n=14,638; NGAP n=42,953 and GPC n=22,624. As we describe here, these efforts have yielded harmonized datasets enabling us to analyze PUMAS genetic variation data at three levels: SMI overall, diagnoses, and individual symptoms. Methods:In aligning item-level phenotypes obtained from 14 different clinical instruments, we incorporated content, branching nature, and time frame for each phenotype; standardized diagnoses; and selected 19 core SMI item-level phenotypes for analyses. The harmonization was evaluated in PUMAS cases using multiple correspondence analysis (MCA), co-occurrence analyses, and item-level endorsement. Outcomes:We mapped >6,895 item-level phenotypes in the aggregated PUMAS data, in which SCZ (44.97%) and severe BP (BP-I, 31.53%) were the most common diagnoses. Twelve of the 19 core item-level phenotypes occurred at frequencies of > 10% across all diagnoses, indicating their potential utility for transdiagnostic genetic analyses. MCA of the 14 phenotypes that were present for all cohorts revealed consistency across cohorts, and placed MDD and SCZ into separate clusters, while other diagnoses showed no significant phenotypic clustering. Interpretation:Our alignment strategy effectively aggregated extensive phenotypic data obtained using diverse assessment tools. The MCA yielded dimensional scores which we will use for genetic analyses along with the item level phenotypes. After successful harmonization, residual phenotypic heterogeneity between cohorts reflects differences in branching structure of diagnostic instruments, recruitment strategies, and symptom interpretation (due to cultural variation).

Summary Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic study of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. Availability and implementation Admix-kit package is open-source and available at https://github.com/KangchengHou/admix-kit . Additionally, users can use the pipeline designed for admixed genotype simulation available at https://github.com/UW-GAC/admix-kit_workflow .