Populations Of European Ancestry Research Articles

A multi-trait GWAS identifies novel genes influencing albuminuria.

Albuminuria is common and associated with increased risks of end-stage kidney disease and cardiovascular diseases, yet its underlying mechanism remains obscure. Previous genome-wide association studies (GWAS) for albuminuria did not consider gene pleiotropy and primarily focused on European ancestry populations. This study adopted a multi-trait analysis of GWAS (MTAG) approach to jointly analyze two vital kidney traits, estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR) to identify and prioritize the genes associated with UACR. Data from the Taiwan Biobank from 2012 to 2023 were analyzed. GWAS of UACR and eGFR were performed separately and the summary statistics from these GWAS were jointly analyzed using MTAG. The polygenic risk scores (PRS) of UACR were constructed for validation. The UACR-associated loci were further fine-mapped and prioritized based on their deleteriousness, eQTL associations, and relatedness to Mendelian kidney diseases. MTAG analysis of the UACR revealed 15 genetic loci, including 12 novel loci. The PRS for UACR was significantly associated with urinary albumin level (P<0.001) and microalbuminuria (P=0.001 ∼ 0.045). A list of priority genes was generated. Twelve genes with high priority included the albumin endocytic receptor gene LRP2 and ciliary genes IFT172. The findings of this multi-trait GWAS suggest that primary cilia play a role in sensing mechanical stimuli, leading to albumin endocytosis. The priority list of genes warrants further translational investigation to reduce albuminuria.

Large-scale alternative polyadenylation-wide association studies to identify putative cancer susceptibility genes.

Alternative polyadenylation (APA) modulates mRNA processing in the 3' untranslated regions (3' UTR), affecting mRNA stability and translation efficiency. Research into genetically regulated APA has the potential to provide insights into cancer risk. Herein, we conducted large alternative polyadenylation-wide association studies (APA-WAS) to investigate associations of APA levels with cancer risk. Genetic models were built to predict APA levels in multiple tissues using genotype and RNA-sequencing data from 1,337 samples from the Genotype-Tissue Expression Project. Associations of genetically predicted APA levels with cancer risk were assessed by applying the prediction models to data from large genome-wide association studies of six common cancers among European-ancestry populations, including breast, ovary, prostate, colorectum, lung, and pancreas. A total of 58 risk genes (corresponding to 76 APA sites) were associated with at least one type of cancer, including 25 genes previously not linked to cancer susceptibility. Of the identified risk APAs, 97.4% and 26.3% were supported by 3' UTR APA quantitative trait loci and co-localization analyses, respectively. Luciferase reporter assays for four selected putative regulatory 3' UTR variants demonstrated that the risk alleles of 3' UTR variants, rs324015 (STAT6), rs2280503 (DIP2B), rs1128450 (FBXO38), and rs145220637 (LDHA), significantly increased the post-transcriptional activities of their target genes compared to reference alleles. Furthermore, knockdown of the target genes confirmed their ability to promote proliferation and migration. Overall, this study provides insights into the role of APA in the genetic susceptibility to common cancers.

Genetic association and transferability for urinary albumin-creatinine ratio as a marker of kidney disease in four Sub-Saharan African populations and non-continental individuals of African ancestry

BackgroundGenome-wide association studies (GWAS) have predominantly focused on populations of European and Asian ancestry, limiting our understanding of genetic factors influencing kidney disease in Sub-Saharan African (SSA) populations. This study presents the largest GWAS for urinary albumin-to-creatinine ratio (UACR) in SSA individuals, including 8,970 participants living in different African regions and an additional 9,705 non-resident individuals of African ancestry from the UK Biobank and African American cohorts.MethodsUrine biomarkers and genotype data were obtained from two SSA cohorts (AWI-Gen and ARK), and two non-resident African-ancestry studies (UK Biobank and CKD-Gen Consortium). Association testing and meta-analyses were conducted, with subsequent fine-mapping, conditional analyses, and replication studies. Polygenic scores (PGS) were assessed for transferability across populations.ResultsTwo genome-wide significant (P &amp;lt; 5 × 10−8) UACR-associated loci were identified, one in the BMP6 region on chromosome 6, in the meta-analysis of resident African individuals, and another in the HBB region on chromosome 11 in the meta-analysis of non-resident SSA individuals, as well as the combined meta-analysis of all studies. Replication of previous significant results confirmed associations in known UACR-associated regions, including THB53, GATM, and ARL15. PGS estimated using previous studies from European ancestry, African ancestry, and multi-ancestry cohorts exhibited limited transferability of PGS across populations, with less than 1% of observed variance explained.ConclusionThis study contributes novel insights into the genetic architecture of kidney disease in SSA populations, emphasizing the need for conducting genetic research in diverse cohorts. The identified loci provide a foundation for future investigations into the genetic susceptibility to chronic kidney disease in underrepresented African populations Additionally, there is a need to develop integrated scores using multi-omics data and risk factors specific to the African context to improve the accuracy of predicting disease outcomes.

Association among attention-deficit hyperactivity disorder, restless legs syndrome, and peripheral iron status: a two-sample Mendelian randomization study.

Epidemiological evidence indicates a high correlation and comorbidity between Attention Deficit Hyperactivity Disorder (ADHD) and Restless Legs Syndrome (RLS). We aimed to investigate the causal relationship and shared genetic architecture between ADHD and RLS, as well as explore potential causal associations between both disorders and peripheral iron status. We performed two-sample Mendelian randomization (MR) analyses using summary statistics from genome-wide meta-analyses of ADHD, RLS, and peripheral iron status (serum iron, ferritin, transferrin saturation, and total iron binding capacity). Additionally, we employed linkage disequilibrium score regression (LDSC) to assess genetic correlations between ADHD and RLS using genetic data. Our MR results supports a causal effect from ADHD (as exposure) to RLS (as outcome) (inverse variance weighted OR = 1.20, 95% CI: 1.08-1.34, p = 0.001). Conversely, we found no a causal association from RLS to ADHD (inverse variance weighted OR = 1.04, 95% CI: 0.99-1.09, p = 0.11). LDSC analysis did not detect a significant genetic correlation between RLS and ADHD (Rg = 0.3, SE = 0.16, p = 0.068). Furthermore, no evidence supported a causal relationship between peripheral iron deficiency and the RLS or ADHD onset. However, RLS may have been associated with a genetic predisposition to reduced serum ferritin levels (OR = 1.20, 95% CI: 1.00-1.04, p = 0.047). This study suggests that ADHD is an independent risk factor for RLS, while RLS may confer a genetic predisposition to reduced serum ferritin levels. The GWAS summary data utilized originated from populations of European ancestry, limiting the generalizability of conclusions to other populations. The potential co-occurrence of RLS in individuals with ADHD should be considered during diagnosis and treatment. Moreover, iron supplementation may be beneficial for alleviating RLS symptoms.

Abstract PO1-15-04: Young Black Women With Triple-Negative Breast Cancer Molecular Subtypes: Population-Specific Patterns and Batch Effect Considerations

Abstract Introduction: While triple-negative breast cancer (TNBC) molecular subtypes have been associated with biological differences and clinical outcomes, studies have overwhelmingly been conducted in populations of European or Asian ancestry. Data collected across diverse populations is required to better leverage clinical directions from translational studies in TNBC. Through females recruited through the Black Women: Etiology and Survival of Triple-Negative Breast Cancers (BEST) study, we sought to characterize subtypes and explore associations. Methods: Our study included Black women diagnosed with early-stage (I-III) invasive TNBC at &amp;lt; = age 50 from 2005 to 2016, with recruitment from Florida and Tennessee state cancer registries. Germline DNA, tumor RNA, clinical outcomes, and risk factor data were collected. TNBC status in the BEST study was based on immunohistochemistry from pathology reports, cancer registry data, and self-reported data. Analyses on banked tumor samples, extracted at multiple time points, were conducted through PAM50 (Nanostring) and whole-transcriptome RNA-seq. TNBC subtype was assessed using TNBCtype-4 (Lehmann et al. 2016). Sources of batch effect were evaluated using PCA and corrected via limma. Genetic ancestry based on OncoArray or MEGA genotyping data was inferred using 1000Genomes continental reference samples. Immune cell characterization was performed via CIBERSORT and ESTIMATE. Statistical significance in comparing differences across subtypes was assessed via Chi-square test. Kaplan-Meier estimates and log-rank test were used for survival analysis. Results: RNA-seq from 114 self-reported Black females with TNBC was analyzed. TNBC subtype distribution in the BEST study cohort included 31.6% basal-like 1 (BL1), 28.9% basal-like 2 (BL2), 16.7% luminal androgen receptor (LAR), and 21.9% mesenchymal (M). While results were largely consistent with prior studies in patients of European or East Asian ancestry, a higher percentage of BL2 subtype was observed (28.9% vs. 21.0%, p=0.053). Based on PAM50 subtyping, 100% of tumors with BL1 and M were basal, whereas 68.8% of LAR and 86.7% of BL2 subtypes were basal. Tumors without subtype decreased from 9.8% to 1.1% after batch correcting for location at which RNA was extracted (Moffitt vs. Vanderbilt) and time between RNA banking and sequencing. All TNBC subtypes in this population demonstrated monocyte/activated dendritic cell predominance, with no significant subtype-specific associations with immune cell patterns. A lower relative proportion of M subtype was found in tumors from BRCA1/2 carriers, but this was not statistically significant due to the small number of carriers (8% vs. 18%; p=0.22). With a median follow-up time of 9 years, there was no significant difference in 10-year overall survival by TNBC subtype (p=0.18). However, patients with M subtype appeared to have worse survival relative to other subtypes combined (p=0.036). Conclusion: Our study is among the largest to date that interrogates TNBC subtypes and associated molecular/clinical data in self-reported Black females with invasive breast cancer. Our findings suggest that established TNBC subtyping can be applied in patients of African ancestry. Furthermore, data to correct for lab-based confounders remains critical; in this study, it enabled us to use many samples that could not be subtyped initially. Several population-specific patterns were observed, including no difference in 10-year overall survival across TNBC subtypes (consistent with prior data), but worse initial outcomes in M subtype; a preliminary association between BRCA1/2 carriers and non-M subtypes (in contrast to prior data); and no significant difference in immune cell distributions (in contrast to prior data mainly from patients of European ancestry). Studies of associations between TNBC subtypes, additional clinical data, and treatment data (type and response rates) are ongoing. Citation Format: Padma Rajagopal, Sonya Reid, Run Fan, Lindsay Venton, Anne Weidner, Mya Roberson, Susan Vadaparampil, Xuefeng Wang, Sean Yoder, Marilin Rosa, Jibril Hirbo, Jennifer Whisenant, Jennifer Pietenpol, Fei Ye, Tuya Pal, Brian Lehmann. Young Black Women With Triple-Negative Breast Cancer Molecular Subtypes: Population-Specific Patterns and Batch Effect Considerations [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-15-04.

Abstract PO2-08-03: Developing a polygenic risk score for precision prevention of estrogen receptor-positive (ER+)/HER2- breast cancer in Brazilian women

Abstract Polygenic risk scores (PRS) quantify the genetic risk of diseases based on risk alleles in genomic loci identified in genome-wide association studies (GWAS). As individuals of European ancestry are overrepresented in GWAS, PRS performance may vary in individuals of different ancestries. Brazil is the largest and most populated country in Latin America, with around 43% of admixed individuals, and data on breast cancer PRS performance for this population is lacking. We aimed to evaluate the performance of a breast cancer PRS with 313 SNPs generated with Europeans in Brazilian population. In this case-control study, we expect to include 1000 women age &amp;gt;= 18 years old with current or previous diagnosis of ER+/HER2- breast cancer. Germline DNA samples are genotyped with Illumina Infinium Global Screening Array-24 v3.0 chip. Controls are healthy woman previously genotyped with Global Screening Array-24 v1.0 chip. We selected the 313 SNPs PRS for ER+/HER2- breast cancer from PGS Catalog for evaluation. Quality control, imputation, PRS calculation and statistical analysis were performed in PLINK v2.0, Michigan server, PGS Catalog and R, respectively. We present the preliminary results for 1347 women (504 cases and 843 controls) included until March of 2023. After quality control and imputation, we calculated PRS for 1212 subjects (475 cases and 737 controls). Out of 313 SNPs, 211 were validated in our samples. For ER+/HER2- breast cancer, the odds ratio per SD of the 211-variant PRS (PRS211) was 1.363 (95% confidence interval [CI]: 1.211 to 1.537). Compared with women with average risk (40th-60th PRS percentile), women in the top 10% of PRS211 had a 1.623-fold increased risk (95% CI: 1.047 to 2.522). The area under the receiver operating characteristic curve of 0.581. Our preliminary results indicate that a PRS derived from European-ancestry population correlates with ER+/HER2- breast cancer in admixed Brazilian population, although with attenuated performance. Further work is needed to better characterize PRS risk stratification in admixed populations. Citation Format: Marina Candido Visontai Cormedi, Álison Luís Eburnêo Pereira, Fernanda Borchers Coeli-Lacchini, Sabrina Baroni, Lívia Mara Torres Bueno, Evelyn Ayumi Onga, Victor Girelli Piloto De Oliveira, Fabiana De Oliveira Buono, Aline Fares, Tatiana Strava Correa, Iasmin Alves Chirichela, Fernanda Peria, Romulado Barroso-Sousa, Rodrigo Santa Cruz Guindalini, Taisa Manuela Bonfim Machado Lopes, Rosimeire Aparecida Roela, Maria Aparecida Azevedo Koike Folgueira, Daniel Guimarães Tiezzi, Leandro Machado Colli, Liane Rapatoni. Developing a polygenic risk score for precision prevention of estrogen receptor-positive (ER+)/HER2- breast cancer in Brazilian women [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-08-03.

Mendelian randomization identifies causal effects of major depressive disorder on accelerated aging

BackgroundEvidence links major depressive disorder (MDD) with aging, but it's unclear if MDD accelerates aging and what factors mediate this transition. MethodsTwo-sample Mendelian randomization (MR) analyses were applied to estimate the causal association between MDD and frailty index (FI), telomere length (TL), and appendicular lean mass (ALM) from available genome-wide association studies in populations of European ancestry. Furthermore, we conducted mediation MR analyses to assess the mediating effects of 31 lifestyle factors or diseases on the causal relationship between MDD and aging. ResultsMDD was significantly causally associated with increased FI (βIVW = 0.23, 95 % CI = 0.18 to 0.28, p = 1.20 × 10−17), shorter TL (βIVW = −0.04, 95 % CI = −0.07 to −0.01, p = 0.01), and decreased ALM (βIVW = −0.07, 95 % CI = −0.11 to −0.03, p = 3.54 × 10−4). The mediation analysis through two-step MR revealed smoking initiation (9.09 %), hypertension (6.67 %) and heart failure (5.36 %) mediated the causal effect of MDD on FI. Additionally, alcohol use disorders and alcohol dependence on the causal relationship between MDD and TL were found to be 17.52 % and 17.13 % respectively. LimitationsConfounding, statistical power, and Euro-centric focus limit generalization. ConclusionOverall, individuals with MDD may be at a higher risk of experiencing premature aging, and this risk is partially influenced by the pathways involving smoking, alcohol use, and cardiovascular health. It underscores the importance of early intervention and comprehensive health management in individuals with MDD to promote healthy aging and overall well-being.

Genetic Complexities of Cerebral Small Vessel Disease, Blood Pressure, and Dementia.

Vascular disease is a treatable contributor to dementia risk, but the role of specific markers remains unclear, making prevention strategies uncertain. To investigate the causal association between white matter hyperintensity (WMH) burden, clinical stroke, blood pressure (BP), and dementia risk, while accounting for potential epidemiologic biases. This study first examined the association of genetically determined WMH burden, stroke, and BP levels with Alzheimer disease (AD) in a 2-sample mendelian randomization (2SMR) framework. Second, using population-based studies (1979-2018) with prospective dementia surveillance, the genetic association of WMH, stroke, and BP with incident all-cause dementia was examined. Data analysis was performed from July 26, 2020, through July 24, 2022. Genetically determined WMH burden and BP levels, as well as genetic liability to stroke derived from genome-wide association studies (GWASs) in European ancestry populations. The association of genetic instruments for WMH, stroke, and BP with dementia was studied using GWASs of AD (defined clinically and additionally meta-analyzed including both clinically diagnosed AD and AD defined based on parental history [AD-meta]) for 2SMR and incident all-cause dementia for longitudinal analyses. In 2SMR (summary statistics-based) analyses using AD GWASs with up to 75 024 AD cases (mean [SD] age at AD onset, 75.5 [4.4] years; 56.9% women), larger WMH burden showed evidence for a causal association with increased risk of AD (odds ratio [OR], 1.43; 95% CI, 1.10-1.86; P = .007, per unit increase in WMH risk alleles) and AD-meta (OR, 1.19; 95% CI, 1.06-1.34; P = .008), after accounting for pulse pressure for the former. Blood pressure traits showed evidence for a protective association with AD, with evidence for confounding by shared genetic instruments. In the longitudinal (individual-level data) analyses involving 10 699 incident all-cause dementia cases (mean [SD] age at dementia diagnosis, 74.4 [9.1] years; 55.4% women), no significant association was observed between larger WMH burden and incident all-cause dementia (hazard ratio [HR], 1.02; 95% CI, 1.00-1.04; P = .07). Although all exposures were associated with mortality, with the strongest association observed for systolic BP (HR, 1.04; 95% CI, 1.03-1.06; P = 1.9 × 10-14), there was no evidence for selective survival bias during follow-up using illness-death models. In secondary analyses using polygenic scores, the association of genetic liability to stroke, but not genetically determined WMH, with dementia outcomes was attenuated after adjusting for interim stroke. These findings suggest that WMH is a primary vascular factor associated with dementia risk, emphasizing its significance in preventive strategies for dementia. Future studies are warranted to examine whether this finding can be generalized to non-European populations.

Genetic correlation and causal associations between psychiatric disorders and lung cancer risk

BackgroundPatients with certain psychiatric disorders have increased lung cancer incidence. However, establishing a causal relationship through traditional epidemiological methods poses challenges. MethodsAvailable summary statistics of genome-wide association studies of cigarette smoking, lung cancer, and eight psychiatric disorders, including attention deficit/hyperactivity disorder (ADHD), autism, depression, major depressive disorder, bipolar disorder, insomnia, neuroticism, and schizophrenia (range N: 46,350-1,331,010) were leveraged to estimate genetic correlations using Linkage Disequilibrium Score Regression and assess causal effect of each psychiatric disorder on lung cancer using two-sample Mendelian randomization (MR) models, comprising inverse-variance weighted (IVW), weighted median, MR-Egger, pleiotropy residual sum and outlier testing (MR-PRESSO), and a constrained maximum likelihood approach (cML-MR). ResultsSignificant positive correlations were observed between each psychiatric disorder and both smoking and lung cancer (all FDR < 0.05), except for the correlation between autism and lung cancer. Both univariable and the cML-MA MR analyses demonstrated that liability to schizophrenia, depression, ADHD, or insomnia was associated with an increased risk of overall lung cancer. Genetic liability to insomnia was linked specifically to squamous cell carcinoma (SCC), while genetic liability to ADHD was associated with an elevated risk of both SCC and small cell lung cancer (all P < 0.05). The later was further supported by multivariable MR analyses, which accounted for smoking. LimitationsParticipants were constrained to European ancestry populations. Causal estimates from binary psychiatric disorders may be biased. ConclusionOur findings suggest appropriate management of several psychiatric disorders, particularly ADHD, may potentially reduce the risk of developing lung cancer.

Multi-trait GWAS for diverse ancestries: mapping the knowledge gap

BackgroundApproximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores.MethodsHere, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits across five ancestries (European (EUR), admixed American (AMR), African (AFR), East Asian (EAS), and South-East Asian (SAS)).ResultsWe detected 367 new genome-wide significant associations in non-European populations (15 in Admixed American (AMR), 72 in African (AFR) and 280 in East Asian (EAS)). New associations detected represent 5%, 17% and 13% of associations in the AFR, AMR and EAS populations, respectively. Overall, multi-trait testing increases the replication of European associated loci in non-European ancestry by 15%. Pleiotropic effects were highly similar at significant loci across ancestries (e.g. the mean correlation between multi-trait genetic effects of EUR and EAS ancestries was 0.88). For hematological traits, strong discrepancies in multi-trait genetic effects are tied to known evolutionary divergences: the ARKC1 loci, which is adaptive to overcome p.vivax induced malaria.ConclusionsMulti-trait GWAS can be a valuable tool to narrow the genetic knowledge gap between European and non-European populations.

An ensemble penalized regression method for multi-ancestry polygenic risk prediction

Great efforts are being made to develop advanced polygenic risk scores (PRS) to improve the prediction of complex traits and diseases. However, most existing PRS are primarily trained on European ancestry populations, limiting their transferability to non-European populations. In this article, we propose a novel method for generating multi-ancestry Polygenic Risk scOres based on enSemble of PEnalized Regression models (PROSPER). PROSPER integrates genome-wide association studies (GWAS) summary statistics from diverse populations to develop ancestry-specific PRS with improved predictive power for minority populations. The method uses a combination of L1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{{{{{\\mathscr{L}}}}}}}_{1}$$\\end{document} (lasso) and L2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{{{{{\\mathscr{L}}}}}}}_{2}$$\\end{document} (ridge) penalty functions, a parsimonious specification of the penalty parameters across populations, and an ensemble step to combine PRS generated across different penalty parameters. We evaluate the performance of PROSPER and other existing methods on large-scale simulated and real datasets, including those from 23andMe Inc., the Global Lipids Genetics Consortium, and All of Us. Results show that PROSPER can substantially improve multi-ancestry polygenic prediction compared to alternative methods across a wide variety of genetic architectures. In real data analyses, for example, PROSPER increased out-of-sample prediction R2 for continuous traits by an average of 70% compared to a state-of-the-art Bayesian method (PRS-CSx) in the African ancestry population. Further, PROSPER is computationally highly scalable for the analysis of large SNP contents and many diverse populations.

Genetic susceptibility of urolithiasis: comprehensive results from genome-wide analysis.

The pathogenesis of urolithiasis is multi-factorial and genetic factors have been shown to play a significant role in the development of urolithiasis. We tried to apply genome-wide Mendelian randomization (MR) analysis and figure out reliable gene susceptibility of urolithiasis from the largest samples to date in two independent genome-wide association studies (GWAS) database of European ancestry. We extracted summary statistics of expression quantitative trait locus (eQTL) from eQTLGen consortium. Urolithiasis phenotype information was obtained from both FinnGen Biobank and UK Biobank. Multiple two-sample MR analysis with a Bonferroni-corrected P threshold (P < 2.5e-06) was conducted. The primary endpoint was the causal effect calculated by random-effect inverse variance weighted (IVW) method. Sensitivity analysis, volcano plots, scatter plots, and regional plots were also performed and visualized. After multiple MR tests between 19942 eQTLs and urolithiasis phenotype from both cohorts, 30 common eQTLs with consistent effect size direction were found to be causally associated with urolithiasis risk. Finally only one gene (LMAN2) was simultaneously identified among all top significant eQTLs from both FinnGen Biobank (beta = 0.6758, se = 0.0327, P = 6.775e-95) and UK Biobank (beta = 0.0044, se = 0.0009, P = 2.417e-06). We also found that LMAN2 was with the largest beta effect size on urolithiasis phenotype from the two cohorts. We for the first time implemented genome-wide MR analysis to investigate the genetic susceptibility of urolithiasis in general population of European ancestry. Our results provided novel insights into common genetic variants of urinary stone disease, which was of great help to subsequent researches.

Imputation accuracy across global human populations

Genotype imputation is now fundamental for genome-wide association studies but lacks fairness due to the underrepresentation of references from non-European ancestries. The state-of-the-art imputation reference panel released by the Trans-Omics for Precision Medicine (TOPMed) initiative improved the imputation of admixed African-ancestry and Hispanic/Latino samples, but imputation for populations primarily residing outside of North America may still fall short in performance due to persisting underrepresentation. To illustrate this point, we imputed the genotypes of over 43,000 individuals across 123 populations around the world and identified numerous populations where imputation accuracy paled in comparison to that of European-ancestry populations. For instance, the mean imputation r-squared (Rsq) for variants with minor allele frequencies between 1% and 5% in Saudi Arabians (n= 1,061), Vietnamese (n= 1,264), Thai (n= 2,435), and Papua New Guineans (n= 776) were 0.79, 0.78, 0.76, and 0.62, respectively, compared to 0.90-0.93 for comparable European populations matched in sample size and SNP array content. Outside of Africa and Latin America, Rsq appeared to decrease as genetic distances to European-ancestry reference increased, as predicted. Using sequencing data as ground truth, we also showed that Rsq may over-estimate imputation accuracy for non-European populations more than European populations, suggesting further disparity in accuracy between populations. Using 1,496 sequenced individuals from Taiwan Biobank as a second reference panel to TOPMed, we also assessed a strategy to improve imputation for non-European populations with meta-imputation, but this design did not improve accuracy across frequency spectra. Taken together, our analyses suggest that we must ultimately strive to increase diversity and size to promote equity within genetics research.

Abstract 6614: Integrating single-cell RNA-seq and large genome-wide association study data to identify colorectal cancer cell-of-origin populations

Abstract Background: Single-cell RNA sequencing (scRNA-seq) enables the precise identification of distinct cell populations and the measurement of gene expression within each population. Recently, integrating scRNA-seq and genome-wide association study (GWAS) data has shown promise in identifying cell-of-origin populations in human diseases. Colorectal cancer (CRC) progresses through a phenotypic continuum from normal colon to adenoma, and ultimately CRC. However, the specific disease cell-of-origin populations underlying each stage of CRC development at a single-cell resolution have not been well studied. Additionally, while transcriptome-wide association studies (TWAS) have identified more than 200 putative risk genes in CRC, the precise disease cell-of-origin populations associated with these genes remain elusive. Materials and methods: We analyzed scRNA-seq datasets from 31 normal colon, 8 colon serrated polyps, and 15 conventional adenoma tissues of individuals participated the Colorectal Molecular Atlas Project (COLON MAP). We next conducted an integrative analysis of the aforementioned scRNA-seq data, with extensive epigenomics data and summary statistics from a large CRC GWAS conducted among European ancestry populations (78,473 CRC cases and 107,143 controls) using single-cell disease relevance score (scDRS), to investigate cell-of-origin populations underlying the CRC development. We conducted correlation analysis between gene expression and individual cell risk scores derived from scDRS. Additionally, we performed differential expression analysis comparing disease cell-of-origin populations with other cell populations at each stage. Results: We identified multiple cell-of-origin populations associated with CRC, including absorptive cells (ABS) (P &amp;lt; 1 × 10-4) and goblet cells (GOB) (P &amp;lt; 7 × 10-3) in the normal colon, ABS (P &amp;lt; 2 × 10-3), enteroendocrine cells (EE) (P &amp;lt; 0.04), and serrated-specific cells (SSC) (P &amp;lt; 1 × 10-4) in serrated polyps, and ABS (P &amp;lt; 9 × 10-3) and SSC (P &amp;lt; 6 × 10-4) in adenomas. Among the previously reported 205 risk genes from TWAS, a majority show high correlations of their expressions with the risk scores of the single cells (median value R2 = 0.07, 0.14, 0.137 at normal colon, serrated polyps, adenoma, respectively). Moreover, 57 of these TWAS-reported genes (27.8% of 205 genes) exhibited evidence of differential expression in disease cell-of-origin populations compared to other cell populations at a nominal p-value &amp;lt; 0.05 in at least one stage (Binomial test, P &amp;lt; 0.01 for all). Conclusion: This study reveals the cell-of-origin populations that influence the development of CRC, and provides evidence of the role of risk genes in these populations. These findings are crucial for identifying causal genes and understanding the cellular mechanisms that drive the biology and etiology of CRC. Citation Format: Chao Li, Zhishan Chen, Qing Li, Jungyoon Choi, Quanhu Sheng, Wanqing Wen, Xiang Shu, Xiao-ou Shu, Jirong Long, Qiuyin Cai, Bhuminder Singh, Martha J. Shrubsole, Ken Lau, Wei Zheng, Xingyi Guo. Integrating single-cell RNA-seq and large genome-wide association study data to identify colorectal cancer cell-of-origin populations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6614.

A genome-wide cross-trait analysis identifies shared loci and causal relationships of obesity and lipidemic traits with psoriasis.

Obesity and dyslipidemia, major global health concerns, have been linked to psoriasis, but previous studies faced methodological limitations and their shared genetic basis remains unclear. This study examines various obesity-related and lipidemic traits as potential contributors to psoriasis development, aiming to clarify their genetic associations and potential causal links. Summary statistics from genome-wide association studies (GWAS) conducted for obesity-related traits (body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-hip ratio adjusted for the body mass index (WHRadjBMI)) and lipidemic traits (high-density lipoprotein (HDL), LDL, triglyceride (TG), total Cholesterol (TC), apolipoprotein A1 (apoA1), apolipoprotein B (apoB), and apolipoprotein E (apoE)) and psoriasis, all in populations of European ancestry, were used. We quantified genetic correlations, identified shared loci and explored causal relationship across traits. We found positive genetic correlation between BMI and psoriasis (rg=0.22, p=2.44×10-18), and between WHR and psoriasis (rg=0.19, p=1.41×10-12). We further found the positive genetic correlation between psoriasis and WHRadjBMI(rg=0.07, p=1.81×10-2) the genetic correlation, in while the effect of BMI was controlled for. We identified 14 shared loci underlying psoriasis and obesity-related traits and 43 shared loci between psoriasis and lipidemic traits via cross-trait meta-analysis. Mendelian randomization (MR) supported the causal roles of BMI (IVW OR=1.483, 95%CI=1.333-1.649), WHR (IVW OR=1.393, 95%CI=1.207-1.608) and WHRadjBMI (IVW OR=1.18, 95%CI=1.047-1.329) in psoriasis, but not observe any significant association between lipidemic traits and the risk of psoriasis. Genetic predisposition to psoriasis did not appear to affect the risk of obesity and lipidemic traits. An intrinsic link between obesity-related traits and psoriasis has been demonstrated. The genetic correlation and causal role of obesity-related traits in psoriasis highlight the significance of weight management in both the prevention and treatment of this condition.

Shared genetic architecture between periodontal disease and type 2 diabetes: a large scale genome-wide cross-trait analysis.

To investigate the relationship between abnormal glucose metabolism, type 2 diabetes (T2D), and periodontal disease (PER) independent of Body Mass Index (BMI), we employed a genome-wide cross-trait approach to clarify the association. Our study utilized the most extensive genome-wide association studies conducted for populations of European ancestry, including PER, T2D, fasting glucose, fasting insulin, 2-hour glucose after an oral glucose challenge, HOMA-β, HOMA-IR (unadjusted or adjusted for BMI) and HbA1c. With this approach, we were able to identify pleiotropic loci, establish expression-trait associations, and quantify global and local genetic correlations. There was a significant positive global genetic correlation between T2D (rg = 0.261, p = 2.65 × 10-13), HbA1c (rg = 0.182, p = 4.14 × 10-6) and PER, as well as for T2D independent of BMI (rg = 0.158, p = 2.34 × 10-6). A significant local genetic correlation was also observed between PER and glycemic traits or T2D. We also identified 62 independent pleiotropic loci that impact both PER and glycemic traits, including T2D. Nine significant pathways were identified between the shared genes between T2D, glycemic traits and PER. Genetically liability of HOMA-βadjBMI was causally associated with the risk of PER. Our research has revealed a genetic link between T2D, glycemic traits, and PER that is influenced by biological pleiotropy. Notably, some of these links are not related to BMI. Our research highlights an underlying link between patients with T2D and PER, regardless of their BMI.

A multi-ancestry genome-wide association study in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease caused by destruction of the pancreatic β-cells. Genome-wide association (GWAS) and fine mapping studies have been conducted mainly in European ancestry (EUR) populations. We performed a multi-ancestry GWAS to identify SNPs and HLA alleles associated with T1D risk and age at onset. EUR families (N = 3223), and unrelated individuals of African (AFR, N = 891) and admixed (Hispanic/Latino) ancestry (AMR, N = 308) were genotyped using the Illumina HumanCoreExome BeadArray, with imputation to the TOPMed reference panel. The Multi-Ethnic HLA reference panel was utilized to impute HLA alleles and amino acid residues. Logistic mixed models (T1D risk) and frailty models (age at onset) were used for analysis. In GWAS meta-analysis, seven loci were associated with T1D risk at genome-wide significance: PTPN22, HLA-DQA1, IL2RA, RNLS, INS, IKZF4-RPS26-ERBB3, and SH2B3, with four associated with T1D age at onset (PTPN22, HLA-DQB1, INS, and ERBB3). AFR and AMR meta-analysis revealed NRP1 as associated with T1D risk and age at onset, although NRP1 variants were not associated in EUR ancestry. In contrast, the PTPN22 variant was significantly associated with risk only in EUR ancestry. HLA alleles and haplotypes most significantly associated with T1D risk in AFR and AMR ancestry differed from that seen in EUR ancestry; in addition, the HLA-DRB1*08:02-DQA1*04:01-DQB1*04:02 haplotype was 'protective' in AMR while HLA-DRB1*08:01-DQA1*04:01-DQB1*04:02 haplotype was 'risk' in EUR ancestry, differing only at HLA-DRB1*08. These results suggest that much larger sample sizes in non-EUR populations are required to capture novel loci associated with T1D risk.

Fetal genetically determined birth weight plays a causal role in earlier puberty timing: evidence from human genetic studies.

Does fetal genetically determined birth weight associate with the timing of puberty? Lower fetal genetically determined birth weight was causally associated with an earlier onset of puberty, independent of the indirect effects of the maternal intrauterine environment. Previous Mendelian randomization (MR) studies have indicated a potential causal link between birth weight, childhood BMI, and the onset of puberty. However, they did not distinguish between genetic variants that have a direct impact on birth weight through the fetal genome (referred to as fetal genetic effects) and those that influence birth weight indirectly by affecting the intrauterine environment (known as maternal genetic effects). It is crucial to emphasize that previous studies were limited because they did not account for the potential bias caused by unaddressed correlations between maternal and fetal genetic effects. Additionally, the proportion of birth weight variation explained by the fetal genome is considerably larger than that of the maternal genome. We performed two-sample MR analyses to investigate the causal effect of fetal genetically determined birth weight on puberty timing using summary data from large-scale genome-wide association studies (GWASs) in individuals of European ancestry. From the two most recent GWASs specifically centered on birth weight, which included 406 063 individuals and 423 683 individuals (63 365 trios) respectively, we identified genetic variants associated with fetal genetically determined birth weight, while adjusting for maternal genetic effects. We identified genetic variants associated with childhood BMI from an independent GWAS involving 21 309 European participants. On this basis, we employed two-sample MR techniques to examine the possible causal effects of fetal genetically determined birth weight on puberty timing using a large-scale GWAS of puberty timing (including 179 117 females of European ancestry). Furthermore, we employed advanced analytical methods, specifically MR mediation and MR-Cluster, to enhance our comprehension of the causal relationship between birth weight determined by fetal genetics and the timing of puberty. We also explored the pathways through which childhood BMI might act as a mediator in this relationship. In the univariable MR analysis, a one SD decrease in fetal genetically determined birth weight (∼ 418 g) was associated with a 0.16 (95% CI [0.07-0.26]) years earlier onset of puberty. The multivariable MR analysis including fetal genetically determined birth weight and childhood BMI in relation to puberty timing provided compelling evidence that birth weight had a direct influence on the timing of puberty. Lower birth weight (one SD) was associated with an earlier onset of puberty, with a difference of 0.23 (95% CI [0.05-0.42]) years. We found little evidence to support a mediating role of childhood BMI between birth weight and puberty timing (-0.07 years, 95% CI [-0.20 to 0.06]). Our data came from European ancestry populations, which may restrict the generalizability of our results to other populations. Moreover, our analysis could not investigate potential non-linear relationships between birth weight and puberty timing due to limitations in genetic summary data. Findings from this study suggested that low birth weight, determined by the fetal genome, contributes to early puberty, and offered supporting evidence to enhance comprehension of the fetal origins of disease hypothesis. C.Z. was funded by the Sichuan Province Science and Technology Program [grant number 2021JDR0189]. J.Z. was supported by grants from the National Natural Science Foundation of China [grant number 82373588]. No other authors declare any sources of funding. The authors have no conflicts of interest. N/A.

Independent associations of education, intelligence, and cognition with gastrointestinal diseases and the mediating effects of risk factors: a Mendelian randomization study.

Education, intelligence and cognition affect occupational performance and socioeconomic status and may influence virous diseases development. However, the impact of these factors on gastrointestinal diseases and their mediating risk factors remains unclear. We utilized genome-wide association studies from European ancestry populations to perform two-sample Mendelian randomization analyses, aiming to estimate genetic instruments associated with education, intelligence, or cognition in relation to 24 gastrointestinal diseases Subsequently, we evaluated 14 potential mediators of this association and calculated the corresponding mediated proportions through two-step Mendelian randomization analyses. As the dominant factor in gastrointestinal diseases, education had a statistically significant association with 2 gastrointestinal diseases (acute pancreatitis, gastroesophageal reflux) and a suggestive association with 6 diseases (cirrhosis, alcoholic liver disease, cholecystitis, cholelithiasis, chronic gastritis and gastric ulcer). Of the 14 mediators, smoking and adiposity traits played a major role in mediating the effects. The study demonstrated the causal, independent impact of education on specific gastrointestinal diseases. Smoking and adiposity traits emerged as primary mediators, illuminating potential avenues for targeted interventions for prevention of them.

Parkinson Disease Genetics Extended to African and Hispanic Ancestries in the VA Million Veteran Program.

Nearly all genetic analyses of Parkinson disease (PD) have been in populations of European ancestry. We sought to test the ability of a machine learning method to extract accurate PD diagnoses from an electronic medical record (EMR) system, to see whether genetic variants identified in European populations generalize to individuals of African and Hispanic ancestries, and to compare the rates of PD across ancestries. A machine learning method using natural language processing was applied to EMRs of US veterans participating in the VA Million Veteran Program (MVP) to identify individuals with PD. These putative cases were vetted via blind chart review by a movement disorder specialist. A polygenic risk score (PRS) of 90 established genetic variants whose genotypes were imputed from a customized Axiom Biobank Array was evaluated in different case groups. The EMR prediction scores had a distinct trimodal distribution, with 97% of the high group and only 30% of the middle group having a credible diagnosis of PD. Using the 3,542 cases from the high group matched 4:1 to controls, the PRS was highly predictive in individuals of European ancestry (n = 3,137 cases; OR = 1.82; p = 8.01E-48), and nearly identical effect sizes were seen in individuals of African (n = 184; OR = 2.07; p = 3.4E-4) and Hispanic ancestries (n = 221; OR = 2.13; p = 3.9E-6). The PRS was much less predictive for the 2,757 European ancestry cases who had an ICD code for PD but for whom the machine learning method had a lower confidence in their diagnosis. No novel ancestry-specific genetic variants were identified. Individuals with African ancestry had one-quarter the rate of PD compared with European or Hispanic ancestries aged 60-70 years and one half the rate in the 70-80 years age range. African American cases had a higher proportion of their DNA originating in Europe compared with African American controls. Machine learning can reliably classify PD using data from a large EMR. Larger studies of non-European populations are required to confirm the generalizability of PD risk variants identified in populations of European ancestry and the increased risk coming from a higher proportion of European DNA in African Americans.