Diverse Ancestral Backgrounds Research Articles

Methodologies underpinning polygenic risk scores estimation: a comprehensive overview.

Polygenic risk scores (PRS) have emerged as a promising tool for predicting disease risk and treatment outcomes using genomic data. Thousands of genome-wide association studies (GWAS), primarily involving populations of European ancestry, have supported the development of PRS models. However, these models have not been adequately evaluated in non-European populations, raising concerns about their clinical validity and predictive power across diverse groups. Addressing this issue requires developing novel risk prediction frameworks that leverage genetic characteristics across diverse populations, considering host-microbiome interactions and a broad range of health measures. One of the key aspects in evaluating PRS is understanding the strengths and limitations of various methods for constructing them. In this review, we analyze strengths and limitations of different methods for constructing PRS, including traditional weighted approaches and new methods such as Bayesian and Frequentist penalized regression approaches. Finally, we summarize recent advances in PRS calculation methods development, and highlight key areas for future research, including development of models robust across diverse populations by underlining the complex interplay between genetic variants across diverse ancestral backgrounds in disease risk as well as treatment response prediction. PRS hold great promise for improving disease risk prediction and personalized medicine; therefore, their implementation must be guided by careful consideration of their limitations, biases, and ethical implications to ensure that they are used in a fair, equitable, and responsible manner.

Ancestral Diversity in Pharmacogenomics Affects Treatment for Hispanic/Latine Populations With Inflammatory Bowel Disease

Background and AimsThe prevalence of inflammatory bowel disease (IBD) among Hispanic/Latine communities is increasing. Pharmacogenomic studies reveal genetic markers that influence treatment decisions. The aim of our study was to examine the frequency and impact of genetic polymorphisms on thiopurine-associated leukopenia (NUDT15, TPMT) and anti-TNF immunogenicity (HLA-DQA1*05) in a cohort of Hispanic patients of diverse ancestral backgrounds. MethodsWe performed a multicenter, retrospective cohort study comprised of 2225 Hispanic participants. We measured the frequency of variation affecting drug response in NUDT15, TPMT, and HLA-DQA1*05, their ancestral origin (European, African, or Amerindian), and the rate of development of myelosuppression and immunogenicity to thiopurines and anti-TNFs, respectively, in exposed patients. ResultsNUDT15 and TPMT variants were rare, except for rs116855232 in NUDT15 which was common only in alleles of Amerindian origin. All NUDT15 variant alleles were inherited on an Amerindian haplotype, and among the Amerindian allele subset, the variant frequency of NUDT15*4 (rs147390019) was a remarkable 23% in patients with leukopenia but only 3% in patients without leukopenia. HLA-DQA1*05 and its European tagging variant rs2097432 were common in alleles from all ancestral origins and demonstrated association with immunogenicity to anti-TNFs. However, rs2097432 was only correlated with HLA-DQA1*05 in the European allele subset. ConclusionThese findings indicate that NUDT15 testing should become standard clinical practice before prescribing thiopurines in individuals with Amerindian ancestry, including Hispanic individuals. Additionally, rs2097432 should not be used as a surrogate for HLA-DQA1*05 testing for diverse populations. Ultimately, incorporating ancestry in personalized therapeutic approaches is important for treatment of Hispanic patients with IBD.

GWAS breakthroughs: mapping the journey from one locus to 393 significant CAD associations.

Coronary artery disease (CAD) poses a substantial threat to global health, leading to significant morbidity and mortality worldwide. It has a significant genetic component that has been studied through genome-wide association studies (GWAS) over the past 17 years. These studies have made progress with larger sample sizes, diverse ancestral backgrounds, and the discovery of multiple genomic regions related to CAD risk. In this review, we provide a comprehensive overview of CAD GWAS, including information about the genetic makeup of the disease and the importance of ethnic diversity in these studies. We also discuss challenges of identifying causal genes and variants within GWAS loci with a focus on non-coding regions. Additionally, we highlight tissues and cell types relevant to CAD, and discuss clinical implications of GWAS findings including polygenic risk scores, sex-specific differences in CAD genetics, ethnical aspects of personalized interventions, and GWAS guided drug development.

The impact of clinical genome sequencing in a global population with suspected rare genetic disease

There is mounting evidence of the value of clinical genome sequencing (cGS) in individuals with suspected rare genetic disease (RGD), but cGS performance and impact on clinical care in a diverse population drawn from both high-income countries (HICs) and low- and middle-income countries (LMICs) has not been investigated. The iHope program, a philanthropic cGS initiative, established a network of 24 clinical sites in eight countries through which it provided cGS to individuals with signs or symptoms of an RGD and constrained access to molecular testing. A total of 1,004 individuals (median age, 6.5 years; 53.5% male) with diverse ancestral backgrounds (51.8% non-majority European) were assessed from June 2016 to September 2021. The diagnostic yield of cGS was 41.4% (416/1,004), with individuals from LMIC sites 1.7 times more likely to receive a positive test result compared to HIC sites (LMIC 56.5% [195/345] vs. HIC 33.5% [221/659], OR 2.6, 95% CI 1.9-3.4, p<0.0001). A change in diagnostic evaluation occurred in 76.9% (514/668) of individuals. Change of management, inclusive of specialty referrals, imaging and testing, therapeutic interventions, and palliative care, was reported in 41.4% (285/694) of individuals, which increased to 69.2% (480/694) when genetic counseling and avoidance of additional testing were also included. Individuals from LMIC sites were as likely as their HIC counterparts to experience a change in diagnostic evaluation (OR 6.1, 95% CI 1.1-∞, p= 0.05) and change of management (OR 0.9, 95% CI 0.5-1.3, p= 0.49). Increased access to genomic testing may support diagnostic equity and the reduction of global health care disparities.

Mendelian randomization analysis of atopic dermatitis and esophageal cancer in East Asian and European populations

BackgroundEmerging observational studies showed an association between atopic dermatitis (AD) and gastrointestinal cancers. However, it remains unclear whether this association is causal, particularly in the case of cancers like esophageal cancer, which exhibit ancestral genetic traits. MethodsTo assess the potential causal relationship between AD and esophageal cancer across diverse ancestral backgrounds, we conducted a 2-sample Mendelian randomization study. Independent genetic instruments for AD from the FinnGen consortium (N case = 7024 and N control = 198 740), BioBank Japan (N case = 2385 and N control = 209 651) and Early Genetics and Lifecourse Epidemiology (EAGLE) eczema consortium (N case = 18 900 and N control = 84 166, without the 23andMe study) were used to investigate the association with esophageal cancer in the UK Biobank study (N case = 740 and N control = 372 016) and BioBank Japan esophageal cancer sample (N case = 1300 and N control = 197 045). ResultsWhen esophageal cancer extracted from East Asian ancestry was used as a outcome factor, AD data extracted from BioBank Japan (OR = 0.90, 95% CI: 0.83–0.98), FinnGen consortium (OR = 0.86, 95% CI: 0.77–0.96), and EAGLE consortium (OR = 0.92, 95% CI: 0.81–1.06) were negatively associated with esophageal cancer susceptibility. However, AD as a whole did not show an association with esophageal cancer from European ancestry. ConclusionThis study provides support for a causal relationship between AD and esophageal cancer in East Asian populations but not between AD and esophageal cancer from European ancestry. The specific associations between esophageal cancer and AD appear to exhibit significant disparities between the East Asian and European regions.

Abstract PR015: Evaluation of genetic ancestry as a covariable in gene expression analysis for chemotherapy response in Colombian breast cancer women

Abstract Breast cancer (BC) is a public health concern in Colombia that presents admixture of indigenous American (IA), European and African American (AA) ancestries. These differences could be affecting prognosis and neoadjuvant chemotherapy (NAC) response. This study aims to identify gene expression profiles associated with non-response to NAC in Colombian women diagnosed with invasive BC, including genetic ancestry as a covariable. An integrative transcriptome analysis was conducted on 87 samples of BC female patients belonging to Colombian NCI population and candidates for NAC. Patients either responded or did not respond to NAC. To estimate genetic ancestry, genotyping of 106 ancestry informative markers was performed from non-tumoral DNA. Molecular intrinsic subtypes were classified into four groups: All luminal, LuminalBHer2+/-, LuminalBHer2+ &amp; HER2 enriched, and TNBC+Her2-enriched. Two analyses were performed: differential gene expression comparing RNA-Seq data from different molecular subtype grouping, and enrichment analysis comparing baseline vs follow-up samples from non-responders, as well as baseline samples from non-responders vs responders. All analyses were performed comparing ancestry as a covariable in differential expression model. Responders and nonresponders showed distinct gene signatures in all categories. Sample distribution shown 8% AA, 59% IA and 32% European ancestry. Subtype grouping with ancestry as a covariable found 4 differential expressed genes (DEG) across nonresponders and baseline analyses for all samples (CPNE9, GTSF1, NORAD, PPP1R35) associated with cell differentiation pathways. 1 luminal DEG (CGB3), 20 DEG for LuminalBHer2+/-, 202 DEGs for LuminalBHer2+ &amp; HER2 enriched, and 7 DEGs for TNBC+Her2-enriched (AKR1E2, CEACAM6, IRS4,LIGO, MICU2, NPAS2 and STATH). Among these groups, enrichment pathways included positive regulation of cell migration, cell-cell adhesion, cellular response to hormone stimulus. We found a notable increase in differential gene expression as the proportion of IA genetic ancestry becomes greater. Genetic ancestry effect might indicate a connection between heterozygosity and genetic variance. We contrasted our results to other studies performed in other Latin American cohorts. Overall, our findings reveal a significant gene signature between responders and non-responders across subtype grouping. Our previous findings identified different sets of genes among this subtype grouping suggesting that genetic ancestry affects the gene signatures and as it's already reported, treatment response. Our results emphasizes the significance of assessing gene expression in heterogeneous populations with diverse ancestral backgrounds like Colombia, as a means to facilitate novel findings and alleviate disparities. Overexpression of these genes provides a potential to predict therapy response, alerting clinicians about patients who may not benefit from NAC. Citation Format: Hedda Michelle Guevara-Nieto, Rafael Santiago Parra-Medina, Juan Carlos Mejia Henao, Jone Garai, Jovanny Zabaleta, Liliana Lopez-Kleine, Alba Lucia Combita. Evaluation of genetic ancestry as a covariable in gene expression analysis for chemotherapy response in Colombian breast cancer women [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr PR015.

Polygenic risk score calibration and association with breast cancer in diverse ancestries.

10505 Background: Polygenic risk scores (PRS) have been shown to substantially improve breast cancer (BC) risk prediction when incorporated into traditional risk assessment models. However, PRS developed primarily in women of European ancestry have shown poor performance when applied to non-European populations. We previously described development and validation of a multiple-ancestry PRS (MA-PRS) that is based on individual ancestral genetic composition. MA-PRS has been incorporated into the Tyrer-Cuzick model for use in clinical practice and has been shown to provide independent value to the model. Here, we describe performance of the MA-PRS in a large cohort of women from diverse ancestral backgrounds. Methods: The study cohort included 203,586 patients who were referred for hereditary cancer testing and negative for pathogenic variants in genes associated with BC. MA-PRS was calculated as previously described based on 149 SNPs (93 BC and 56 ancestry-informative). Association of MA-PRS with invasive BC status (affected vs unaffected) was analyzed using logistic regression adjusted for personal and family cancer history, age, and ancestry. Calibration was assessed by examining the MA-PRS distribution within unaffected patients, and through goodness-of-fit tests. All analyses were conducted within the full cohort and within ancestral subpopulations. Odds ratios (ORs) are reported per standard deviation. Results: One-fifth (43,782/203,586, 21.5%) of patients were diagnosed with invasive BC, and 60,657 (29.8%) of patients reported BC in a first degree relative. The MA-PRS distribution was centered around zero among unaffected patients overall and within each subpopulation. MA-PRS significantly improved BC risk prediction over clinical factors in the full cohort (OR = 1.43, 95% CI:1.41-1.44) and within each ancestral subpopulation (Table). The strongest associations were observed in Ashkenazi Jewish (OR = 1.56, 95% CI:1.39-1.76) and South Asian (OR = 1.49,95% CI: 1.23-1.81) populations. The top decile of the MA-PRS consistently identified patients with two-fold increased risk of developing BC. Goodness-of-fit tests showed that the MA-PRS was well calibrated and predicted BC risk accurately in the tails of the distribution for both European and non-European women. Conclusions: The breast cancer MA-PRS based on genetic ancestral composition is well-calibrated and strongly associated with BC in all tested ancestral populations. Incorporation of PRS adds independent information to risk models and supports equitable access to personalized BC risk management. [Table: see text]

ADAMS project: a genetic Association study in individuals from Diverse Ancestral backgrounds with Multiple Sclerosis based in the UK

PurposeGenetic studies of multiple sclerosis (MS) susceptibility and severity have focused on populations of European ancestry. Studying MS genetics in other ancestral groups is necessary to determine the generalisability of...

Trans-ancestry, Bayesian meta-analysis discovers 20 novel risk loci for inflammatory bowel disease in an African American, East Asian and European cohort.

Inflammatory bowel disease (IBD) is an immune-mediated chronic intestinal disorder with major phenotypes: ulcerative colitis (UC) and Crohn's disease (CD). Multiple studies have identified over 240 IBD susceptibility loci. However, most studies have centered on European (EUR) and East Asian (EAS) populations. The prevalence of IBD in non-EUR, including African Americans (AAs), has risen in recent years. Here we present the first attempt to identify loci in AAs using a trans-ancestry Bayesian approach (MANTRA) accounting for heterogeneity between diverse ancestries while allowing for the similarity between closely related populations. We meta-analyzed genome-wide association studies (GWAS) and Immunochip data from a 2015 EUR meta-analysis of 38 155 IBD cases and 48 485 controls and EAS Immunochip study of 2824 IBD cases and 3719 controls, and our recent AA IBD GWAS of 2345 cases and 5002 controls. Across the major IBD phenotypes, we found significant evidence for 92% of 205 loci lead SNPs from the 2015 meta-analysis, but also for three IBD loci only established in latter studies. We detected 20 novel loci, all containing immunity-related genes or genes with other evidence for IBD or immune-mediated disease relevance: PLEKHG5;TNFSFR25 (encoding death receptor 3, receptor for TNFSF15 gene product TL1A), XKR6, ELMO1, BC021024;PI4KB;PSMD4 and APLP1 for IBD; AUTS2, XKR6, OSER1, TET2;AK094561, BCAP29 and APLP1 for CD; and GABBR1;MOG, DQ570892, SPDEF;ILRUN, SMARCE1;CCR7;KRT222;KRT24;KRT25, ANKS1A;TCP11, IL7, LRRC18;WDFY4, XKR6 and TNFSF4 for UC. Our study highlights the value of combining low-powered genomic studies from understudied populations of diverse ancestral backgrounds together with a high-powered study to enable novel locus discovery, including potentially important therapeutic IBD gene targets.

Why We Swab: A library of stories in stem cell donation.

Stories are powerful in their ability to disseminate information in a meaningful way. We hypothesized that a stem cell donation story library optimized for social media could support the education and recruitment of committed unrelated hematopoietic stem cell donors from needed demographic groups. We developed Why We Swab, a library of stories on stem cell donation (facebook.com/WhyWeSwab; instagram.com/WhyWeSwab; twitter.com/WhyWeSwab), and evaluated its impact across social and traditional media as well as on eligible potential donors' knowledge and attitudes towards donation. As of December 2021, the library included 28 story arcs featuring 45 storytellers from diverse ancestral backgrounds, including 8 donor-recipient stories. Overall, the stories reached >92,000 people across social media. Notably, stories were republished by 18 print/ broadcast media outlets in Canada and by major medical organizations. A series of stories shown to 33 eligible potential donors improved mean total scores on a donation knowledge test (64% to 85%, p < 0.001), reduced mean ambivalence scale scores (3.85 to 2.70, p < 0.001), and improved participants' willingness to register as donors (45% to 73%, p < 0.005). Data are also shown demonstrating that stakeholders valued the library and that its deployment was associated with improved donor recruitment outcomes in Canada. Why We Swab is accessible and relevant to a wide audience, including stem cell donor registries and recruitment organizations seeking to improve their recruitment efforts as well as to blood and organ & tissue donation organizations who can adapt the Why We Swab model to their audiences.

MP05-06 GENETIC ANALYSIS OF KIDNEY STONE DISEASE IN A MULTI-ETHNIC COHORT: INSIGHTS FROM GENOME-WIDE AND PHENOME-WIDE ASSOCIATION STUDIES

You have accessJournal of UrologyCME1 May 2022MP05-06 GENETIC ANALYSIS OF KIDNEY STONE DISEASE IN A MULTI-ETHNIC COHORT: INSIGHTS FROM GENOME-WIDE AND PHENOME-WIDE ASSOCIATION STUDIES Parth Patel, Vidhya Venkateswaran, Bogdan Pasanuic, and Kymora Scotland Parth PatelParth Patel More articles by this author , Vidhya VenkateswaranVidhya Venkateswaran More articles by this author , Bogdan PasanuicBogdan Pasanuic More articles by this author , and Kymora ScotlandKymora Scotland More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002522.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Nephrolithiasis, a common global ailment with significant clinical and economic health burden, has demonstrated heritability up to 56%. Various single nucleotide polymorphisms (SNPs) have been implicated in the development of kidney stone disease. Existing literature regarding this association is primarily in the form of genome-wide association studies or based on geographically limited samples. This genome- and phenome-wide association study aimed to evaluate the link between SNPs and kidney stone disease in a database of patients representing diverse ancestral backgrounds. METHODS: We retrospectively studied our repository of more than 27000 genotyped patients and their de-identified electronic health records. ICD-10 codes were aggregated to provide clinically meaningful groupings called phecodes. Genome-wide association testing was performed between all genotyped SNPs and phecodes associated with urolithiasis. We also tested the association between selected SNPs from our genome-wide association analysis and 1330 phecodes in the biobank to ascertain other phenotypic associations. RESULTS: The ancestry breakdown of these patients was 72.8% European, 16.3% Admixed American, 7.41% Eastern Asian, and 3.45% African. The lead SNPs from the trans-ancestry meta-analysis were rs2263090 and rs79616469 with p-values approaching genome-wide significance threshold of 5e-08 (Figure 1). In the phenome-wide association analysis, SNP rs2263090 showed associations with other kidney-related traits such as hematuria in EUR (Figure 2). CONCLUSIONS: While numerous polymorphisms have been associated with kidney stone disease, our genome-wide and phenome-wide association studies suggest that their phenotypic expression may not be equal across genetic ancestral groupings. This promotes the concept that inheritable causes of nephrolithiasis are likely polygenic and their expression multifactorial, and much still remains to be learned about the molecular basis of kidney stone formation. Source of Funding: N/A © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e69 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Parth Patel More articles by this author Vidhya Venkateswaran More articles by this author Bogdan Pasanuic More articles by this author Kymora Scotland More articles by this author Expand All Advertisement PDF DownloadLoading ...

Genetics of Type 2 Diabetes: Implications from Large-Scale Studies.

Purpose of ReviewType 2 diabetes (T2D) is a multifactorial, heritable syndrome characterized by dysregulated glucose homeostasis that results from impaired insulin secretion and insulin resistance. Genetic association studies have successfully identified hundreds of T2D risk loci implicating many genes in disease pathogenesis. In this review, we provide an overview of the recent T2D genetic studies from the past 3 years with particular focus on the effects of sample size and ancestral diversity on genetic discovery as well as discuss recent work on the use and limitations of genetic risk scores (GRS) for T2D risk prediction.Recent FindingsRecent large-scale, multi-ancestry genetic studies of T2D have identified over 500 novel risk loci. The genetic variants (i.e., single nucleotide polymorphisms (SNPs)) marking these novel loci in general have smaller effect sizes than previously discovered loci. Inclusion of samples from diverse ancestral backgrounds shows a few ancestry specific loci marked by common variants, but overall, the majority of loci discovered are common across ancestries. Inclusion of common variant GRS, even with hundreds of loci, does not substantially increase T2D risk prediction over standard clinical risk factors such as age and family history.SummaryCommon variant association studies of T2D have now identified over 700 T2D risk loci, half of which have been discovered in the past 3 years. These recent studies demonstrate that inclusion of ancestrally diverse samples can enhance locus discovery and improve accuracy of GRS for T2D risk prediction. GRS based on common variants, however, only minimally enhances risk prediction over standard clinical risk factors.

It's time to incorporate diversity into our basic science and disease models.

To address health disparities and facilitate increasingly personalized treatments, we need to develop new models for basic and disease research that reflect diverse ancestral backgrounds and sex, and ensure that diverse populations are included among donors and research participants.

Patient-Reported Outcome Information Collected from Lupus Patients Using a Mobile Application: Compliance and Validation.

ObjectivePatient‐reported outcomes (PROs) can provide critical information concerning the impact of a disease on an individual. Mobile technology to collect PRO data in an electronic format (ePRO) allows for frequent assessment in the person's regular environment. The goal of this study was to assess the compliance with a phone application (app) and validate ePRO information in individuals with systemic lupus erythematosus (SLE).MethodsA smartphone app that collects ePRO data from various clinical instruments was developed. Information was collected by both an ePRO and a paper‐administered instrument as part of a multicenter randomized interventional clinical trial of patients meeting American College of Rheumatology (ACR) criteria for the classification of SLE. To determine agreement between PRO information collected in the different formats, intraclass correlation coefficients (ICCs), paired Student's t tests, and Bland–Altman plots were evaluated. Compliance and Cronbach's alpha were also assessed as a measure of survey reliability.ResultsFor the 62 subjects from diverse ancestral backgrounds, compliance with ePRO completion was high (more than 75%). Cronbach alpha values for PROs indicated moderate to high survey reliability. The vast majority (73.4%) of ICC values were indicative of good to excellent reliability between measurement methods. Bland–Altman plots verified method agreement, and 87% of pairwise t tests yielded an insignificant difference between information collected with the different administration methods.ConclusionThe excellent compliance and the high level of consistency between data collected by paper and that collected by electronic methods indicate that the app provides a reliable means of cataloging real‐time changes in PROs in SLE patients.

Integrated multi-omic analyses reveals clinical relevance of endometrial cancer cell line models

<h3>Objectives:</h3> Endometrial cancer (EC) cell lines models established from diverse ancestral backgrounds and reflective of <i>in situ</i> disease characteristics are necessary to support preclinical investigations with broad generalizability. We performed multi-omic analyses of EC cell line models established from women representing diverse ancestries and compared these with clinical and molecular profiling data from the TCGA UCEC patient cohort to assess the relevance of models to <i>in situ</i> clinical and molecular disease characteristics. <h3>Methods:</h3> Whole genome sequencing (WGS), transcriptome (RNAseq) and proteome (LC-MS/MS and RPPA) analyses were performed for primary cell line models established from endometrioid EC patients (NCI-EC1, ACI-80, ACI-181, ACI-52, ACI-61 and ACI-68) as well as commercial EC models (MFE-296, SNG-M, HEC1A, RL95-2, Ishikawa, AN3-CA, KLE). Microsatellite instability (MSI) was determined from WGS data using MSISensor2 and standard ancestry estimates by comparison with reference populations from the 1000 Genomes Project. Hierarchical cluster analyses was performed using Pvclust and differential analyses using LIMMA. TCGA UCEC clinical and transcriptome data (n=371 patients) were downloaded from the TCGA UCEC manuscript supplement or cbioportal.org and odds ratio significance was assessed using Fisher's exact test (p<0.05). <h3>Results:</h3> EC cell line models are MSI-high except ACI-61, ACI-68 and KLE cells which are microsatellite stable. Standard ancestry estimates showed most cell lines are from women of European ancestry except Ishikawa, HEC1A and SNG-M which are of East Asian ancestry and NCI-EC1, ACI-181 and ACI-80 which are of African ancestry. Unsupervised hierarchical analysis of proteome data revealed distinct clusters comprising MFE-296, AN3-CA, ACI-68, ACI-61, NCI-EC1 cells (cluster 1) and ACI-80, ACI-52, HEC1A, SNG-M, RL95-2, KLE, ACI-181 and Ishikawa cells (cluster 2). Differential analyses showed elevated levels of mesenchymal markers (eg, vimentin) and lower levels of epithelial markers (eg, E-cadherin) in cluster 1 versus 2 cells. Correlation of transcript-level data with TCGA UCEC patients showed all cell lines are significantly correlated with endometrioid versus mixed/ uterine serous carcinoma tumors except NCI-EC1, ACI-52, HEC1A and KLE cells. Most cell lines significantly correlated with MSI-H patient tumors and largely trended as being correlated with tumors harboring high mutational loads, except ACI-68 and KLE cells. Cluster 2 cell lines are largely correlated with tumors exhibiting low somatic copy-number alterations except KLE, Ishikawa and HEC1A cells and are significantly correlated with tumors classified as hormonal versus mitotic or immunoreactive molecular subtypes except KLE cells. <h3>Conclusions:</h3> We describe EC cell line models established from women of diverse patient ancestries including those from women of African descent (i.e. NCI-EC1, ACI-181 and ACI-80 cells) that represent novel preclinical resources to investigate ancestry-linked molecular alterations underlying racial disparities between European and African-American women diagnosed with EC. We further define EC cell line models correlating with endometrioid tumors that exhibit more epithelial-like (elevation of E-Cadherin) as well as hormonal characteristics that will benefit preclinical investigations of endometrioid EC disease biology.

Integrative genomic analyses identify susceptibility genes underlying COVID-19 hospitalization

Despite rapid progress in characterizing the role of host genetics in SARS-Cov-2 infection, there is limited understanding of genes and pathways that contribute to COVID-19. Here, we integrate a genome-wide association study of COVID-19 hospitalization (7,885 cases and 961,804 controls from COVID-19 Host Genetics Initiative) with mRNA expression, splicing, and protein levels (n = 18,502). We identify 27 genes related to inflammation and coagulation pathways whose genetically predicted expression was associated with COVID-19 hospitalization. We functionally characterize the 27 genes using phenome- and laboratory-wide association scans in Vanderbilt Biobank (n = 85,460) and identified coagulation-related clinical symptoms, immunologic, and blood-cell-related biomarkers. We replicate these findings across trans-ethnic studies and observed consistent effects in individuals of diverse ancestral backgrounds in Vanderbilt Biobank, pan-UK Biobank, and Biobank Japan. Our study highlights and reconfirms putative causal genes impacting COVID-19 severity and symptomology through the host inflammatory response.

Increased APOE ε4 expression is associated with the difference in Alzheimer's disease risk from diverse ancestral backgrounds.

Apolipoprotein E (APOE) ε4 confers less risk for Alzheimer's disease (AD) in carriers with African local genomic ancestry (ALA) than APOE ε4 carriers with European local ancestry (ELA). Cell type specific transcriptional variation between the two local ancestries (LAs) could contribute to this disease risk differences. Single-nucleus RNA sequencing was performed on frozen frontal cortex of homozygous APOE ε4/ε4 AD patients: seven with ELA, four with ALA. A total of 60,908 nuclei were sequenced. Within the LA region (chr19:44-46Mb), APOE was the gene most differentially expressed, with ELA carriers having significantly more expression (overall P<1.8E-317 ) in 24 of 32 cell clusters. The transcriptome of one astrocyte cluster, with high APOE ε4 expression and specific to ELA, is suggestive of A1 reactive astrocytes. AD patients with ELA expressed significantly greater levels of APOE than ALA APOE ε4 carriers. These differences in APOE expression could contribute to the reduced risk for AD seen in African APOE ε4 carriers.

Characterization of genetic and phenotypic heterogeneity of obstructive sleep apnea using electronic health records

BackgroundObstructive sleep apnea (OSA) is defined by frequent episodes of reduced or complete cessation of airflow during sleep and is linked to negative health outcomes. Understanding the genetic factors influencing expression of OSA may lead to new treatment strategies. Electronic health records (EHRs) can be leveraged to both validate previously reported OSA-associated genomic variation and detect novel relationships between these variants and comorbidities.MethodsWe identified candidate single nucleotide polymorphisms (SNPs) via systematic literature review of existing research. Using datasets available at Geisinger (n = 39,407) and Vanderbilt University Medical Center (n = 24,084), we evaluated associations between 40 previously implicated SNPs and OSA diagnosis, defined using clinical codes. We also evaluated associations between these SNPs and OSA severity measures obtained from sleep reports at Geisinger (n = 6571). Finally, we used a phenome-wide association study approach to help reveal pleiotropic genetic effects between OSA candidate SNPs and other clinical codes and laboratory values available in the EHR.ResultsMost previously reported OSA candidate SNPs showed minimal to no evidence for associations with OSA diagnosis or severity in the EHR-derived datasets. Three SNPs in LEPR, MMP-9, and GABBR1 validated for an association with OSA diagnosis in European Americans; the SNP in GABBR1 was associated following meta-analysis of results from both clinical populations. The GABBR1 and LEPR SNPs, and one additional SNP, were associated with OSA severity measures in European Americans from Geisinger. Three additional candidate OSA SNPs were not associated with OSA-related traits but instead with hyperlipidemia and autoimmune diseases of the thyroid.ConclusionsTo our knowledge, this is one of the largest candidate gene studies and one of the first phenome-wide association studies of OSA genomic variation. Results validate genetic associates with OSA in the LEPR, MMP-9 and GABBR1 genes, but suggest that the majority of previously identified genetic associations with OSA may be false positives. Phenome-wide analyses provide evidence of mediated pleiotropy. Future well-powered genome-wide association analyses of OSA risk and severity across populations with diverse ancestral backgrounds are needed. The comprehensive nature of the analyses represents a platform for informing future work focused on understanding how genetic data can be useful to informing treatment of OSA and related comorbidities.

Importance of Genetic Studies of Cardiometabolic Disease in Diverse Populations.

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

Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores

BackgroundInherited susceptibility to common, complex diseases may be caused by rare, pathogenic variants (“monogenic”) or by the cumulative effect of numerous common variants (“polygenic”). Comprehensive genome interpretation should enable assessment for both monogenic and polygenic components of inherited risk. The traditional approach requires two distinct genetic testing technologies—high coverage sequencing of known genes to detect monogenic variants and a genome-wide genotyping array followed by imputation to calculate genome-wide polygenic scores (GPSs). We assessed the feasibility and accuracy of using low coverage whole genome sequencing (lcWGS) as an alternative to genotyping arrays to calculate GPSs.MethodsFirst, we performed downsampling and imputation of WGS data from ten individuals to assess concordance with known genotypes. Second, we assessed the correlation between GPSs for 3 common diseases—coronary artery disease (CAD), breast cancer (BC), and atrial fibrillation (AF)—calculated using lcWGS and genotyping array in 184 samples. Third, we assessed concordance of lcWGS-based genotype calls and GPS calculation in 120 individuals with known genotypes, selected to reflect diverse ancestral backgrounds. Fourth, we assessed the relationship between GPSs calculated using lcWGS and disease phenotypes in a cohort of 11,502 individuals of European ancestry.ResultsWe found imputation accuracy r2 values of greater than 0.90 for all ten samples—including those of African and Ashkenazi Jewish ancestry—with lcWGS data at 0.5×. GPSs calculated using lcWGS and genotyping array followed by imputation in 184 individuals were highly correlated for each of the 3 common diseases (r2 = 0.93–0.97) with similar score distributions. Using lcWGS data from 120 individuals of diverse ancestral backgrounds, we found similar results with respect to imputation accuracy and GPS correlations. Finally, we calculated GPSs for CAD, BC, and AF using lcWGS in 11,502 individuals of European ancestry, confirming odds ratios per standard deviation increment ranging 1.28 to 1.59, consistent with previous studies.ConclusionslcWGS is an alternative technology to genotyping arrays for common genetic variant assessment and GPS calculation. lcWGS provides comparable imputation accuracy while also overcoming the ascertainment bias inherent to variant selection in genotyping array design.