Ancestry Populations Research Articles

Refining the genetic risk of breast cancer with rare haplotypes and pattern mining.

Hundreds of common variants have been found to confer small but significant differences in breast cancer risk, supporting the widely accepted polygenic model of inherited predisposition. Using a novel closed-pattern mining algorithm, we provide evidence that rare haplotypes may refine the association of breast cancer risk with common germline alleles. Our method, called Chromosome Overlap, consists in iteratively pairing chromosomes from affected individuals and looking for noncontiguous patterns of shared alleles. We applied Chromosome Overlap to haplotypes of genotyped SNPs from female breast cancer cases from the UK Biobank at four loci containing common breast cancer-risk SNPs. We found two rare (frequency <0.1%) haplotypes bearing a GWAS hit at 11q13 (hazard ratio = 4.21 and 16.7) which replicated in an independent, European ancestry population at P < 0.05, and another at 22q12 (frequency <0.2%, hazard ratio = 2.58) which expanded the risk pool to noncarriers of a GWAS hit. These results suggest that rare haplotypes (or mutations) may underlie the "synthetic association" of breast cancer risk with at least some common variants.

Patrilocality and hunter-gatherer-related ancestry of populations in East-Central Europe during the Middle Bronze Age

The demographic history of East-Central Europe after the Neolithic period remains poorly explored, despite this region being on the confluence of various ecological zones and cultural entities. Here, the descendants of societies associated with steppe pastoralists form Early Bronze Age were followed by Middle Bronze Age populations displaying unique characteristics. Particularly, the predominance of collective burials, the scale of which, was previously seen only in the Neolithic. The extent to which this re-emergence of older traditions is a result of genetic shift or social changes in the MBA is a subject of debate. Here by analysing 91 newly generated genomes from Bronze Age individuals from present Poland and Ukraine, we discovered that Middle Bronze Age populations were formed by an additional admixture event involving a population with relatively high proportions of genetic component associated with European hunter-gatherers and that their social structure was based on, primarily patrilocal, multigenerational kin-groups.

Exploring the legacy of African and Indigenous Caribbean admixture in Puerto Rico.

From an anthropological genetic perspective, little is known about the ethnogenesis of African descendants in Puerto Rico. Furthermore, historical interactions between Indigenous Caribbean and African descendant peoples that may be reflected in the ancestry of contemporary populations are understudied. Given this dearth of genetic research and the precedence for Afro-Indigenous interactions documented by historical, archeological, and other lines of evidence, we sought to assess the biogeographic origins of African descendant Puerto Ricans and to query the potential for Indigenous ancestry within this community. Saliva samples were collected from 58 self-identified African descendant Puerto Ricans residing in Puerto Rico. We sequenced whole mitochondrial genomes and genotyped Y chromosome haplogroups for each male individual (n = 25). Summary statistics, comparative analyses, and network analysis were used to assess diversity and variation in haplogroup distribution between the sample and comparative populations. As indicated by mitochondrial haplogroups, 66% had African, 5% had European, and 29% had Indigenous American matrilines. Along the Y chromosome, 52% had African, 28% had Western European, 16% had Eurasian, and, notably, 4% had Indigenous American patrilines. Both mitochondrial and Y chromosome haplogroup frequencies were significantly different from several comparative populations. Biogeographic origins are consistent with historical accounts of African, Indigenous American, and European ancestry. However, this first report of Indigenous American paternal ancestry in Puerto Rico suggests distinctive features within African descendant communities on the island. Future studies expanding sampling and incorporating higher resolution genetic markers are necessary to more fully understand African descendant history in Puerto Rico.

BMI and well-being in people of East Asian and European ancestry: a Mendelian randomisation study

Previous studies have linked higher body mass index (BMI) to lower subjective well-being in adult European ancestry populations. However, our understanding of these relationships across different populations is limited. Here, we investigated the association between BMI and well-being in people of (a) East Asian and (b) European ancestry in the China Kadoorie Biobank (CKB) and UK Biobank (UKB), respectively. Mendelian randomisation (MR) methods were used to test the relationship between BMI with (a) health satisfaction and (b) life satisfaction. One-sample MR enabled us to test effects in men and women separately and to test the role of cultural contexts by stratifying our analyses by urban and rural home location in both China and the UK. Further, we implemented a control function method to test the linearity of the BMI-well-being relationship. We found evidence of different associations between BMI and well-being in individuals of East Asian versus European ancestry. For example, a genetically instrumented higher BMI tentatively associated with higher health satisfaction in people of East Asian ancestry, especially in females (ß: 0.041, 95% CI: 0.002, 0.081). In contrast, there was a robust inverse association between higher genetically instrumented BMI and health satisfaction in all European ancestry UKB participants (ß: −0.183, 95% CI: −0.200, −0.165, Pdifference < 1.00E−15). We also showed the importance of considering non-linear relationships in the MR framework by providing evidence of non-linear relationships between BMI and health and life satisfaction. Overall, our study suggests potential setting-specific causality in the relationship between BMI and subjective well-being, with robust differences observed between East Asians and Europeans when considering very similar outcomes. We highlight the importance of (a) considering potential non-linear relationships in causal analyses and (b) testing causal relationships in different populations, as the casual nature of relationships, especially relationships influenced by social processes, may be setting-specific.

O-306 Genome-wide association meta-analysis supports the association between MUC1 and ectopic pregnancy

Abstract Study question Can we identify genetic variants associated with ectopic pregnancy by undertaking the first genome-wide association study leveraging two large-scale biobank initiatives? Summary answer We identified two novel genome-wide significant associations with ectopic pregnancy, highlighting MUC1 as the most plausible affected gene. What is known already Ectopic pregnancy is an important cause of maternal morbidity and mortality worldwide. Despite being a common early pregnancy complication, the genetic predisposition to this condition remains understudied and no large scale genetic studies have been performed so far. Study design, size, duration A GWAS meta-analysis including 7,070 women with ectopic pregnancy and 248,810 controls from Estonian Biobank and the FinnGen study. Several post-GWAS analysis were conducted to characterise the genetic signals, as well as to analyse the genetic and phenotypic relationships with the condition. Participants/materials, setting, methods We identified ectopic pregnancy cases from national registers by ICD codes (ICD-10 O00), and all remaining women were considered controls. Main results and the role of chance We identified two genome-wide significant loci on chromosomes 1 (rs4971091, p = 5.32x10-9 ) and 10 (rs11598956, p = 2.41x10-8 ). Follow-up analyses propose MUC1, an epithelial glycoprotein with an important role in barrier function, as the most likely candidate for the association on chromosome 1. We also characterise the phenotypic and genetic correlations with other phenotypes, identifying a genetic correlation with smoking and diseases of the (genito)urinary and gastrointestinal system, and phenotypic correlations with various reproductive health diagnoses, reflecting the previously known epidemiological associations. Limitations, reasons for caution The main limitation is that the findings apply to European-based ancestry populations and we only captured maternal genomes. Wider implications of the findings This study encourages the use of large scale genetic datasets to unravel genetic factors linked to ectopic pregnancy, which is difficult to study in experimental settings. Increased sample size might bring additional genetic factors associating with ectopic pregnancy and inform its heritability. Trial registration number not applicable

Evaluation of SNPs associated with mammographic density in European women with mammographic density in Asian women from South-East Asia.

Mammographic density (MD), after accounting for age and body mass index (BMI), is a strong heritable risk factor for breast cancer. Genome-wide association studies (GWAS) have identified 64 SNPs in 55 independent loci associated with MD in women of European ancestry. Their associations with MD in Asian women, however, are largely unknown. Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls. Of the 61 SNPs available in our data, 21 were associated with MD at a nominal threshold of P value < 0.05, all in consistent directions with those reported in European ancestry populations. Of the remaining 40 variants with a P-value of association > 0.05, 29 variants showed consistent directions of association as those previously reported. We found that nine of the 21 MD-associated SNPs in this study were also associated with breast cancer risk in Asian women (P < 0.05), seven of which showed a direction of associations that was consistent with that reported for MD. Our study confirms the associations of 21 SNPs (19/55 or 34.5% out of all known MD loci identified in women of European ancestry) with area and/or volumetric densities in Asian women, and further supports the evidence of a shared genetic basis through common genetic variants for MD and breast cancer risk.

Applications of genomic research in pediatric endocrine diseases.

Recent advances in molecular genetics have advanced our understanding of the molecular mechanisms involved in pediatric endocrine disorders and now play a major role in mainstream medical practice. The spectrum of endocrine genetic disorders has 2 extremes: Mendelian and polygenic. Mendelian or monogenic diseases are caused by rare variants of a single gene, each of which exerts a strong effect on disease risk. Polygenic diseases or common traits are caused by the combined effects of multiple genetic variants in conjunction with environmental and lifestyle factors. Testing for a single gene is preferable if the disease is phenotypically and/or geneically homogeneous. Next-generation sequencing (NGS) can be applied to phenotypically and genetically heterogeneous conditions. Genome-wide association studies (GWASs) have examined genetic variants across the entire genome in a large number of individuals who have been matched for population ancestry and assessed for a disease or trait of interest. Common endocrine diseases or traits, such as type 2 diabetes mellitus, obesity, height, and pubertal timing, result from the combined effects of multiple variants in various genes that are frequently found in the general population, each of which contributes a small individual effect. Isolated founder mutations can result from a true founder effect or an extreme reduction in population size. Studies of founder mutations offer powerful advantages for efficiently localizing the genes that underlie Mendelian disorders. The Korean population has settled in the Korean peninsula for thousands of years, and several recurrent mutations have been identified as founder mutations. The application of molecular technology has increased our understanding of endocrine diseases, which have impacted on the practice of pediatric endocrinology related to diagnosis and genetic counseling. This review focuses on the application of genomic research to pediatric endocrine diseases using GWASs and NGS technology for diagnosis and treatment.

A scoping review of smoking cessation pharmacogenetic studies to advance future research across racial, ethnic, and ancestral populations.

Abstinence rates among smokers attempting to quit remain low despite the wide availability and accessibility of pharmacological smoking cessation treatments. In addition, the prevalence of cessation attempts and abstinence differs by individual-level social factors such as race and ethnicity. Clinical treatment of nicotine dependence also continues to be challenged by individual-level variability in effectiveness to promote abstinence. The use of tailored smoking cessation strategies that incorporate information on individual-level social and genetic factors hold promise, although additional pharmacogenomic knowledge is still needed. In particular, genetic variants associated with pharmacological responses to smoking cessation treatment have generally been conducted in populations with participants that self-identify as White race or who are determined to be of European genetic ancestry. These results may not adequately capture the variability across all smokers as a result of understudied differences in allele frequencies across genetic ancestry populations. This suggests that much of the current pharmacogenetic study results for smoking cessation may not apply to all populations. Therefore, clinical application of pharmacogenetic results may exacerbate health inequities by racial and ethnic groups. This scoping review examines the extent to which racial, ethnic, and ancestral groups that experience differences in smoking rates and smoking cessation are represented in the existing body of published pharmacogenetic studies of smoking cessation. We will summarize results by race, ethnicity, and ancestry across pharmacological treatments and study designs. We will also explore current opportunities and challenges in conducting pharmacogenomic research on smoking cessation that encourages greater participant diversity, including practical barriers to clinical utilization of pharmacological smoking cessation treatment and clinical implementation of pharmacogenetic knowledge.

Large scale proteomic studies create novel privacy considerations

Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to link SomaScan 1.3K proteomes to genomes for 2812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We correctly linked 90–95% of proteomes to their correct genome and for 95–99% we identify the 1% most likely links. The linking accuracy in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. We also linked proteomes-to-proteomes and used the proteome only to determine features such as sex, ancestry, and first-degree relatives. When serial proteomes are available, the linking algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

Drivers of genomic landscapes of differentiation across a Populus divergence gradient.

Speciation, the continuous process by which new species form, is often investigated by looking at the variation of nucleotide diversity and differentiation across the genome (hereafter genomic landscapes). A key challenge lies in how to determine the main evolutionary forces at play shaping these patterns. One promising strategy, albeit little used to date, is to comparatively investigate these genomic landscapes as progression through time by using a series of species pairs along a divergence gradient. Here, we resequenced 201 whole-genomes from eight closely related Populus species, with pairs of species at different stages along the divergence gradient to learn more about speciation processes. Using population structure and ancestry analyses, we document extensive introgression between some species pairs, especially those with parapatric distributions. We further investigate genomic landscapes, focusing on within-species (i.e. nucleotide diversity and recombination rate) and among-species (i.e. relative and absolute divergence) summary statistics of diversity and divergence. We observe relatively conserved patterns of genomic divergence across species pairs. Independent of the stage across the divergence gradient, we find support for signatures of linked selection (i.e. the interaction between natural selection and genetic linkage) in shaping these genomic landscapes, along with gene flow and standing genetic variation. We highlight the importance of investigating genomic patterns on multiple species across a divergence gradient and discuss prospects to better understand the evolutionary forces shaping the genomic landscapes of diversity and differentiation.

Pathogenic germline variants in patients with endometrial cancer across diverse ancestries.

5596 Background: Racial/ethnic disparities in outcomes exist in endometrial cancer (EC), particularly amongst self-reported Black compared to Non-Hispanic White (NH-White) patients. However, the contribution of differences in germline pathogenic variants (gPV) and genetics care to disparities is unknown. We seek to describe the spectrum of gPV in unselected patients with EC by ancestry to characterize variations and describe any differences in subsequent genetic counseling follow-up. Methods: Germline assessment of ≥76 cancer predisposition genes was performed in patients with EC undergoing clinical tumor-normal MSK-IMPACT sequencing from 1/1/15-6/30/21. Self-reported data on race/ethnicity and Ashkenazi Jewish (AJ) ancestry were used to classify patients into mutually exclusive ancestry groups: AJ, Asian, Black, Hispanic, NH-White, or Unknown. Genetic ancestry was inferred from MSK-IMPACT, and those with single population ancestral fraction &gt;0.8 were assigned to African (AFR), European (EUR), East Asian (EAS), Native American (NAM), South Asian (SAS), and AJ (ASJ) ancestry populations or considered admixed (Mixed). Clinicopathologic variables were reported using summary statistics and compared by ancestry using non-parametric tests. Results: Among 1,625 patients with EC, self-reported ancestry [202 AJ (12.4%), 124 (7.6%) Asian, 171 Black (10.5%), 124 Hispanic (7.6%), 927 NH-White (57.1%), and 77 missing (4.7%)] correlated with genetic ancestry. In those identifying as Black, 122 (71%) had &gt;80% African ancestry, 45 (26%) were considered Mixed, and 4 (3%) had missing data. We observed gPV in 216 (13.3%) patients (73 high, 36 moderate and 107 low/uncertain penetrance), with 15 patients having &gt;1 gPV. Rates of gPV varied significantly by self-reported ancestry [AJ: 40 (19.8%), Asian: 15 (12.1%), Black: 12 (7.0%), Hispanic: 15 (12.1%), NH-White: 129 (13.9%), Missing: 5; p=0.009] and genetic ancestry [AFR: 9 (6.4%), AJ: 53 (19.3%), EAS: 9 (11.0%), EUR: 112 (13.3%), NAM: 2 (40%), SAS: 7(20%), Mixed: 17 (8.6%), Missing: 7; p&lt;0.001]. Self-reported Black patients had the lowest rate with 13 gPV observed in 12 patients (7.0%); 5 gPV had biallelic inactivation within the tumor (2 MSH2, 1 MSH6, 1 BRCA2 and 1 FANCA). Biallelic inactivation was observed in 70 (32%) patients overall with highest rates in Black (42%), Asian (40%), AFR (67%) and SAS (71%) populations. In those with new gPV (n=114), 102 (89%) overall were seen in genetics clinic for follow-up care, with the lowest rates in patients identifying as Black (75%) and of AFR ancestry (67%). Conclusions: Although rates of gPV varied by ancestry, they are drivers of disease in all populations, emphasizing the importance of germline assessment in EC. Differences in gPV and subsequent genetics care may contribute to racial/ethnic disparities in outcomes in EC by affecting treatment and cancer prevention and should be studied further.

Trans-ethnic polygenic risk scores for body mass index: An international hundred K+ cohorts consortium study.

While polygenic risk scores hold significant promise in estimating an individual's risk of developing a complex trait such as obesity, their application in the clinic has, to date, been limited by a lack of data from non-European populations. As a collaboration model of the International Hundred K+ Cohorts Consortium (IHCC), we endeavored to develop a globally applicable trans-ethnic PRS for body mass index (BMI) through this relatively new international effort. The polygenic risk score (PRS) model was developed, trained and tested at the Center for Applied Genomics (CAG) of The Children's Hospital of Philadelphia (CHOP) based on a BMI meta-analysis from the GIANT consortium. The validated PRS models were subsequently disseminated to the participating sites. Scores were generated by each site locally on their cohorts and summary statistics returned to CAG for final analysis. We show that in the absence of a well powered trans-ethnic GWAS from which to derive marker SNPs and effect estimates for PRS, trans-ethnic scores can be generated from European ancestry GWAS using Bayesian approaches such as LDpred, by adjusting the summary statistics using trans-ethnic linkage disequilibrium reference panels. The ported trans-ethnic scores outperform population specific-PRS across all non-European ancestry populations investigated including East Asians and three-way admixed Brazilian cohort. Here we show that for a truly polygenic trait such as BMI adjusting the summary statistics of a well powered European ancestry study using trans-ethnic LD reference results in a score that is predictive across a range of ancestries including East Asians and three-way admixed Brazilians.

Sex modifies the effect of genetic risk scores for polycystic ovary syndrome on metabolic phenotypes.

Females with polycystic ovary syndrome (PCOS), the most common endocrine disorder in women, have an increased risk of developing cardiometabolic disorders such as insulin resistance, obesity, and type 2 diabetes (T2D). While only diagnosable in females, males with a family history of PCOS can also exhibit a poor cardiometabolic profile. Therefore, we aimed to elucidate the role of sex in the cardiometabolic comorbidities observed in PCOS by conducting bidirectional genetic risk score analyses in both sexes. We first conducted a phenome-wide association study (PheWAS) using PCOS polygenic risk scores (PCOSPRS) to identify potential pleiotropic effects of PCOSPRS across 1,380 medical conditions recorded in the Vanderbilt University Medical Center electronic health record (EHR) database, in females and males. After adjusting for age and genetic ancestry, we found that European (EUR)-ancestry males with higher PCOSPRS were significantly more likely to develop hypertensive diseases than females at the same level of genetic risk. We performed the same analysis in an African (AFR)-ancestry population, but observed no significant associations, likely due to poor trans-ancestry performance of the PRS. Based on observed significant associations in the EUR-ancestry population, we then tested whether the PRS for comorbid conditions (e.g., T2D, body mass index (BMI), hypertension, etc.) also increased the odds of a PCOS diagnosis. Only BMIPRS and T2DPRS were significantly associated with a PCOS diagnosis in EUR-ancestry females. We then further adjusted the T2DPRS for measured BMI and BMIresidual (regressed on the BMIPRS and enriched for the environmental contribution to BMI). Results demonstrated that genetically regulated BMI primarily accounted for the relationship between T2DPRS and PCOS. Overall, our findings show that the genetic architecture of PCOS has distinct sex differences in associations with genetically correlated cardiometabolic traits. It is possible that the cardiometabolic comorbidities observed in PCOS are primarily explained by their shared genetic risk factors, which can be further influenced by biological variables including sex and BMI.

Genome-Wide Association Study of Breast Density among Women of African Ancestry.

Breast density, the amount of fibroglandular versus fatty tissue in the breast, is a strong breast cancer risk factor. Understanding genetic factors associated with breast density may help in clarifying mechanisms by which breast density increases cancer risk. To date, 50 genetic loci have been associated with breast density, however, these studies were performed among predominantly European ancestry populations. We utilized a cohort of women aged 40-85 years who underwent screening mammography and had genetic information available from the Penn Medicine BioBank to conduct a Genome-Wide Association Study (GWAS) of breast density among 1323 women of African ancestry. For each mammogram, the publicly available "LIBRA" software was used to quantify dense area and area percent density. We identified 34 significant loci associated with dense area and area percent density, with the strongest signals in GACAT3, CTNNA3, HSD17B6, UGDH, TAAR8, ARHGAP10, BOD1L2, and NR3C2. There was significant overlap between previously identified breast cancer SNPs and SNPs identified as associated with breast density. Our results highlight the importance of breast density GWAS among diverse populations, including African ancestry populations. They may provide novel insights into genetic factors associated with breast density and help in elucidating mechanisms by which density increases breast cancer risk.

Sex differences in the genetics of sarcoidosis across European and African ancestry populations.

Sex differences in the susceptibility of sarcoidosis are unknown. The study aims to identify sex-dependent genetic variations in two clinical sarcoidosis phenotypes: Löfgren's syndrome (LS) and non-Löfgren's syndrome (non-LS). A meta-analysis of genome-wide association studies was conducted on Europeans and African Americans, totaling 10,103 individuals from three population-based cohorts, Sweden (n = 3,843), Germany (n = 3,342), and the United States (n = 2,918), followed by an SNP lookup in the UK Biobank (UKB, n = 387,945). A genome-wide association study based on Immunochip data consisting of 141,000 single nucleotide polymorphisms (SNPs) was conducted in the sex groups. The association test was based on logistic regression using the additive model in LS and non-LS sex groups independently. Additionally, gene-based analysis, gene expression, expression quantitative trait loci (eQTL) mapping, and pathway analysis were performed to discover functionally relevant mechanisms related to sarcoidosis and biological sex. We identified sex-dependent genetic variations in LS and non-LS sex groups. Genetic findings in LS sex groups were explicitly located in the extended Major Histocompatibility Complex (xMHC). In non-LS, genetic differences in the sex groups were primarily located in the MHC class II subregion and ANXA11. Gene-based analysis and eQTL enrichment revealed distinct sex-specific gene expression patterns in various tissues and immune cell types. In LS sex groups, a pathway map related to antigen presentation machinery by IFN-gamma. In non-LS, pathway maps related to immune response lectin-induced complement pathway in males and related to maturation and migration of dendritic cells in skin sensitization in females were identified. Our findings provide new evidence for a sex bias underlying sarcoidosis genetic architecture, particularly in clinical phenotypes LS and non-LS. Biological sex likely plays a role in disease mechanisms in sarcoidosis.

Interethnic Differences in Bladder Cancer Incidence and the Association between Type 2 Diabetes and Bladder Cancer in the Multiethnic Cohort Study.

Research on the association between type 2 diabetes (T2D) and bladder cancer (BCA) risk among non-European ancestry populations is sparse to nonexistent, and most prior studies rely on a single baseline assessment of T2D status. We estimated the T2D-BCA association using the Multiethnic Cohort Study of 185,059 men and women in California and Hawaii. Participants were African American, European American, Japanese American, Latin American, and Native Hawaiian, ages 45-75 years at enrollment (1993-1996). T2D was assessed by self-report at baseline, follow-up surveys, and Medicare claims. Cases were identified using Surveillance, Epidemiology and End Results Program cancer registries through 2016. Associations were estimated by race/ethnicity using Cox proportional hazards regression. Adjusted attributable fractions (AAF) and cumulative absolute risk of bladder cancer were estimated across groups. Over an average 19.7 years of follow-up 1,890 incident bladder cancer cases were diagnosed. Time-varying T2D was associated with bladder cancer in the multiethnic sample (HR = 1.17; 95% confidence interval, 1.05-1.30); however, the HR did not differ by race/ethnicity (P = 0.85). The AAF was 4.2% in the multiethnic sample and largest among Native Hawaiians (9.8%). Absolute risk of bladder cancer among European Americans without T2D was higher than all other groups with T2D. T2D is significantly associated with bladder cancer risk in a multiethnic sample. Those with T2D have higher incidence of bladder cancer, regardless of racial/ethnic group. Reducing T2D prevalence could substantially lower bladder cancer incidence among Native Hawaiians due to T2D being more common in this group. High absolute risk of bladder cancer among European Americans, regardless of T2D status, indicates that elevated bladder cancer risk in this group may be due to factors other than T2D. Future studies must explore reasons for this difference in incidence.

Comparative evaluation of the MAPlex, Precision ID Ancestry Panel, and VISAGE Basic Tool for biogeographical ancestry inference

Biogeographical ancestry (BGA) inference from ancestry-informative markers (AIMs) has strong potential to support forensic investigations. Over the past two decades, several forensic panels composed of AIMs have been developed to predict ancestry at a continental scale. These panels typically comprise fewer than 200 AIMs and have been designed and tested with a limited set of populations. How well these panels recover patterns of genetic diversity relative to larger sets of markers, and how accurately they infer ancestry of individuals and populations not included in their design remains poorly understood. The lack of comparative studies addressing these aspects makes the selection of appropriate panels for forensic laboratories difficult. In this study, the model-based genetic clustering tool STRUCTURE was used to compare three popular forensic BGA panels: MAPlex, Precision ID Ancestry Panel (PIDAP), and VISAGE Basic Tool (VISAGE BT) relative to a genome-wide reference set of 10k SNPs. The genotypes for all these markers were obtained for a comprehensive set of 3957 individuals from 228 worldwide human populations. Our results indicate that at the broad continental scale (K=6) typically examined in forensic studies, all forensic panels produced similar genetic structure patterns compared to the reference set (G'≈90%) and had high classification performance across all regions (average AUC-PR > 97%). However, at K=7 and K=8, the forensic panels displayed some region-specific clustering deviations from the reference set, particularly in Europe and the region of East and South-East Asia, which may be attributed to differences in the design of the respective panels. Overall, the panel with the most consistent performance in all regions was VISAGE BT with an average weighted AUC̅W score of 96.26% across the three scales of geographical resolution investigated.

CE-454029-2 THE UTILITY OF MACHINE LEARNING TOOLS IN REDUCING VUS IN ARRHYTHMIA GENES FOR INDIVIDUALS FROM UNDERREPRESENTED POPULATIONS COMPARED TO WELL STUDIED POPULATIONS

Classifying missense variants is often challenging due to limited pathogenicity evidence. Consequently, many remain categorized as variants of uncertain significance (VUS). VUS are at the core of healthcare disparities, as individuals from underrepresented race, ethnicity and ancestry (REA) populations are more likely to receive a VUS result. To improve VUS interpretation, we designed machine learning (ML), gene-specific algorithms utilizing public genomic, protein, and population data. To evaluate ML utility in arrhythmia genetic testing across REA groups. From 1/1-11/15/22, various ML algorithms were validated at Invitae, using existing models such as SpliceAI and developing our own by leveraging gnomAD, AlphaFold, and others. ML evidence was incorporated into Sherloc, a semi-quantitative ACMG/AMP-based variant interpretation framework. Only evidence that met a negative or positive predictive value >80% was incorporated. At least one evidence model was available for 42 arrhythmia genes. Variant classifications impacted by ML were evaluated, stratified by REA groups. Out of 2,715 US-based individuals that underwent arrhythmia panel testing, 1,303 (48%) had ML evidence applied to at least one variant and 796 (29%) were from an underrepresented group. Models contributed to classifying at least one benign/likely benign (B/LB) variant in 840 (31%) and at least one pathogenic/likely pathogenic (P/LP) variant in 43 (1.6%) individuals. A higher percentage of Asian (42%), Black (38%), and Hispanic (35%) individuals had an ML-dependent definitive classification (P/LP or B/LB) relative to White (30%) individuals (p <0.03). The average amount of benign or pathogenic ML evidence applied per reclassified variant was similar across populations, showing that the models contributed comparably across REA groups. By leveraging publicly available datasets to create gene-specific ML algorithms for variant interpretation, the resultant evidence impacted a significant number of individuals who had arrhythmia genetic testing. For those with at least one variant with ML evidence applied, 67% would have otherwise received a VUS result. Additionally, ML appears to provide more definitive variant classifications for underrepresented individuals. ML can assess factors in ways that are agnostic to population ancestry and, when appropriately implemented, can narrow the VUS gap rates across REA groups.

The impact of machine learning models in reducing variants of uncertain significance for individuals from underrepresented populations who are undergoing testing for inborn errors of immunity

The classification of missense variants is challenging due to limited evidence. Consequently, many remain categorized as variants of uncertain significance (VUS). VUS are at the core of healthcare disparities, as individuals from race, ethnicity and ancestry (REA) populations underrepresented in large genomic databases and medical literature receive VUS more often. To generate definitive genetic results more equitably across REA groups, we sought to develop gene-specific machine learning (ML) models and evaluate their utility in genetic testing for inborn errors of immunity (IEI).From 1/1/2022 to 11/15/2022, gene-specific ML algorithms were validated and integrated at Invitae. We incorporated existing models such as SpliceAI, and developed our own by leveraging large datasets including gnomAD, AlphaFold protein structures, and others, to model variant effects. Evidence from these ML models were incorporated into Sherloc, a semi-quantitative variant interpretation framework based on ACMG/AMP guidelines. Only evidence that met a negative or positive predictive value >80% was incorporated during variant interpretation. At least 1 validated model was available for 232 genes during the study period. VUS reduction was calculated, stratified by REA groups.Of 19 784 US based individuals who underwent multi-gene panel testing for IEI, ~16 900 (85%) had ML evidence applied to at least one variant, and ~5700 (29%) individuals were from an underrepresented REA group. Models contributed to the classification of at least 1 benign/likely benign variant in ~10 300 (52%) individuals and at least 1 pathogenic/likely pathogenic variant in ~210 (1%) individuals. A higher percentage of Black (67%), Asian (56%) and Hispanic (60%) individuals had a definitive classification (P/LP or B/LB) that was dependent on ML evidence compared to White (51%) individuals by one-tailed, two-sample proportion test (p <0.03). The average amount of benign or pathogenic ML evidence applied per reclassified variant by Sherloc was similar across populations. Among individuals who had at least 1 variant with ML evidence applied, over 60% would have received a VUS variant without this evidence. ML modeling has demonstrated utility during clinical variant interpretation for IEI, particularly in underrepresented populations.

PIK3R3 is a candidate regulator of platelet count in people of Bangladeshi ancestry

BackgroundBlood platelets are mediators of atherothrombotic disease and are regulated by complex sets of genes. Association studies in European ancestry populations have already detected informative platelet regulatory loci. Studies in other ancestries can potentially reveal new associations because of different allele frequencies, linkage structures, and variant effects. ObjectivesTo reveal new regulatory genes for platelet count (PLT). MethodsGenome-wide association studies (GWAS) were performed in 20,218 Bangladeshi and 9198 Pakistani individuals from the Genes & Health study. Loci significantly associated with PLT underwent fine-mapping to identify candidate genes. ResultsOf 1588 significantly associated variants (P < 5 × 10−8) at 20 loci in the Bangladeshi analysis, most replicated findings in prior transancestry GWAS and in the Pakistani analysis. However, the Bangladeshi locus defined by rs946528 (chr1:46019890) did not associate with PLT in the Pakistani analysis but was in the same linkage disequilibrium block (r2 ≥ 0.5) as PLT-associated variants in prior East Asian GWAS. The single independent association signal was refined to a 95% credible set of 343 variants spanning 8 coding genes. Functional annotation, mapping to megakaryocyte regulatory regions, and colocalization with blood expression quantitative trait loci identified the likely mediator of the PLT phenotype to be PIK3R3 encoding a regulator of phosphoinositol 3-kinase (PI3K). ConclusionAbnormal PI3K activity in the vessel wall is already implicated in the pathogenesis of atherothrombosis. Our identification of a new association between PIK3R3 and PLT provides further mechanistic insights into the contribution of the PI3K pathway to platelet biology.