Search

Sex differences in Parkinson Disease (PD) risk are well-known. However, it is still unclear the role of sex chromosomes in the development and progression of PD. We performed the first X-chromosome Wide Association Study (XWAS) for PD risk in Latin American individuals. We used data from three admixed cohorts: (i) Latin American Research consortium on the GEnetics of Parkinson’s Disease (n=1,504) as discover cohort and (ii) Latino cohort from International Parkinson Disease Genomics Consortium (n = 155) and (iii) Bambui Aging cohort (n= 1,442) as replication cohorts. After developing a X-chromosome framework specifically designed for admixed populations, we identified eight linkage disequilibrium regions associated with PD. We fully replicated one of these regions (top variant rs525496; discovery OR [95%CI]: 0.60 [0.478 - 0.77], p = 3.13 ×10-5; replication OR: 0.60 [0.37-0.98], p = 0.04). rs525496 is an expression quantitative trait loci for several genes expressed in brain tissues, includingRAB9B, H2BFM, TSMB15BandGLRA4. We also replicated a previous XWAS finding (rs28602900), showing that this variant is associated with PD in non-European populations. Our results reinforce the importance of including X-chromosome and diverse populations in genetic studies.

ImportanceDisparities in survival exist between non-Hispanic Black (hereafter, Black) and non-Hispanic White (hereafter, White) patients with uterine cancer.ObjectiveTo investigate factors associated with racial disparities in survival between Black and White patients with uterine cancer.Design, Setting, and PatientsThis cohort study used data from the National Cancer Database on 274 838 Black and White patients who received a diagnosis of uterine cancer from January 1, 2004, to December 31, 2017, with follow-up through December 2020. Statistical analysis was performed in July 2022.Main Outcomes and MeasuresOverall survival by self-reported race and evaluation of explanatory study factors associated with hazard ratio (HR) reduction for Black vs White patients. A propensity scoring approach was applied sequentially to balance racial differences in demographic characteristics, comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, and treatment.ResultsThe study included 32 230 Black female patients (mean [SD] age at diagnosis, 63.8 [10.0] years) and 242 608 White female patients (mean [SD] age at diagnosis, 63.5 [10.5] years) and had a median follow-up of 74.0 months (range, 43.5-113.8 months). Black patients were more likely than White patients to have low income (44.1% vs 14.0%), be uninsured (5.7% vs 2.6%), present with nonendometrioid histologic characteristics (46.1% vs 21.6%), have an advanced disease stage (34.1% vs 19.8%), receive first-line chemotherapy (33.8% vs 18.2%), and have worse 5-year survival (58.6% vs 78.5%). Among patients who received a diagnosis at younger than 65 years of age, the HR for death for Black vs White patients was 2.43 (95% CI, 2.34-2.52) in a baseline demographic-adjusted model and 1.29 (95% CI, 1.23-1.35) after balancing other factors. Comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, treatment, and unexplained factors accounted for 0.8%, 7.2%, 11.5%, 53.1%, 5.8%, 1.2%, and 20.4%, respectively, of the excess relative risk (ERR) among the younger Black vs White patients. Among patients 65 years or older, the HR for death for Black vs White patients was 1.87 (95% CI, 1.81-1.93) in the baseline model and 1.14 (95% CI, 1.09-1.19) after balancing other factors. Comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, treatment, and unexplained factors accounted for 3.0%, 7.5%, 0.0%, 56.2%, 10.6%, 6.9%, and 15.8%, respectively, of the ERR among Black vs White patients aged 65 years or older.Conclusions and RelevanceThis study suggests that histologic subtype was the dominant factor associated with racial survival disparity among patients with uterine cancer, while insurance status represented the main modifiable factor for women younger than 65 years. Additional studies of interactions between biology and social determinants of health are merited.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%., The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

Significance There are multiple archaeological debates regarding early Samoan population history. Here, we add genetic data to this discussion, which supports an initial small population size at the founding of the Samoan islands. We also indicate a major demographic change approximately 1,000 y ago that mirrors the archaeological record. In addition, we demonstrate the utility of rare genetic variants in identifying sparse population structure. These genetic results help establish a detailed demographic model for the Samoan population, which will aid in future studies of Oceanic populations for both history and disease., Archaeological studies estimate the initial settlement of Samoa at 2,750 to 2,880 y ago and identify only limited settlement and human modification to the landscape until about 1,000 to 1,500 y ago. At this point, a complex history of migration is thought to have begun with the arrival of people sharing ancestry with Near Oceanic groups (i.e., Austronesian-speaking and Papuan-speaking groups), and was then followed by the arrival of non-Oceanic groups during European colonialism. However, the specifics of this peopling are not entirely clear from the archaeological and anthropological records, and is therefore a focus of continued debate. To shed additional light on the Samoan population history that this peopling reflects, we employ a population genetic approach to analyze 1,197 Samoan high-coverage whole genomes. We identify population splits between the major Samoan islands and detect asymmetrical gene flow to the capital city. We also find an extreme bottleneck until about 1,000 y ago, which is followed by distinct expansions across the islands and subsequent bottlenecks consistent with European colonization. These results provide for an increased understanding of Samoan population history and the dynamics that inform it, and also demonstrate how rapid demographic processes can shape modern genomes.

BackgroundLarge-scale Parkinson’s disease (PD) genome-wide association studies (GWAS) and meta-analyses have, until recently, only been conducted on subjects with European-ancestry. Consequently, polygenic risk scores (PRS) constructed using PD GWAS data are likely to be less predictive when applied to non-European cohorts.MethodsUsing GWAS data from Nalls et al. 2019, we constructed a PD PRS for a Latino PD cohort (LARGE-PD) and tested it for association with PD status. We validated the PRS performance through testing the PD PRS in an independent cohort of Latino PD patients and by repeating the PRS analysis in LARGE-PD with the addition of 440 external Peruvian controls. To explore the global distribution of PD PRS, we utilized 1000 Genomes Project (1KGP) and Peruvian Genome Project (PGP) data to estimate PD risk allele frequencies. We also tested SNCA haplotypes for association with PD risk using logistic regression in LARGE-PD and a European-ancestry PD cohort from the International Parkinson Disease Genomics Consortium (IPDGC).ResultsThe GWAS-significant PD PRS had an area under the receiver-operator curve (AUC) of 0.668 (95% CI: 0.640-0.695) and explained 2.2% of the phenotypic variance on the liability scale in LARGE-PD. The inclusion of external Peruvian data as controls mitigated this result, dropping the AUC 0.632 (95% CI: 0.607-0.657). In 1KGP Latinos, we found the PD PRS to exhibit a bias by ancestry. At the SNCA locus, haplotypes differ by ancestry. Ancestry-specific SNCA haplotypes were associated with PD status in both LARGE-PD and the IPDGC cohort (p-value < 0.05). Apart from rs356182, these haplotypes share as little as 14% of their variants.ConclusionThe PD PRS has potential for PD risk prediction in Latinos, but variability caused by admixture patterns and bias in the PD PRS calculated using only European-ancestry data limits its utility. The inclusion of diverse subjects can help elucidate PD risk loci and improve risk prediction in non-European cohorts. In the case of the SNCA locus, by leveraging a Latino cohort, we provide orthogonal evidence for rs356182 causality.

Human diets in developed countries such as the US have changed dramatically over the past 75 years, leading to increased obesity, inflammation, and cardiometabolic dysfunction. Evidence over the past decade indicates that the interaction of genetic variation with changes in the intake of 18-carbon essential dietary omega-6 (n-6) and omega-3 (n-3) polyunsaturated fatty acids (PUFA), linoleic acid (LA) and α-linolenic acid (ALA), respectively, has impacted numerous molecular and clinical phenotypes. Interactions are particularly relevant with the

The current search for host-susceptibility variants for COVID-19 contrasts with the fact that the study of the genetic architecture of Severe Acute Respiratory Syndrome (SARS) has been neglected. For human/SARS-CoV-2 interactome genes ACE2, TMPRSS2 and BSG, there is only one convincing evidence of association in Asians with influenza-induced SARS for TMPRSS2-rs2070788, tag-SNP of the eQTL rs383510. This case illustrates the importance of population genetics and of sequencing data in the design of genetic association studies in different human populations: the high linkage disequilibrium (LD) between rs2070788 and rs383510 is Asian-specific. Leveraging on a combination of genotyping and sequencing data for Native Americans (neglected in genetic studies), we show that while their frequencies of the Asian tag-SNP rs2070788 is, surprisingly, the highest worldwide, it is not in LD with the eQTL rs383510, that therefore, should be directly genotyped in genetic association studies of SARS in populations with Native American ancestry.

Long chain polyunsaturated fatty acids (LC-PUFAs) have critical signaling roles that regulate dyslipidemia and inflammation. Genetic variation in the FADS gene cluster accounts for a large portion of interindividual differences in circulating and tissue levels of LC-PUFAs, with the genotypes most strongly predictive of low LC-PUFA levels at strikingly higher frequencies in Amerind ancestry populations. In this study, we examined relationships between genetic ancestry and FADS variation in 1102 Hispanic American participants from the Multi-Ethnic Study of Atherosclerosis. We demonstrate strong negative associations between Amerind genetic ancestry and LC-PUFA levels. The FADS rs174537 single nucleotide polymorphism (SNP) accounted for much of the AI ancestry effect on LC-PUFAs, especially for low levels of n-3 LC-PUFAs. Rs174537 was also strongly associated with several metabolic, inflammatory and anthropomorphic traits including circulating triglycerides (TGs) and E-selectin in MESA Hispanics. Our study demonstrates that Amerind ancestry provides a useful and readily available tool to identify individuals most likely to have FADS-related n-3 LC-PUFA deficiencies and associated cardiovascular risk., Yang et al. examine whether genetic ancestry is associated with genetic variation in fatty acid desaturases and plasma phospholipid levels of long chain polyunsaturated fatty acids (LC-PUFAs) in Hispanic Americans. They find strong associations between Amerind genetic ancestry and LC-PUFA levels; and report that the well-known FADS rs174537 variant was associated with several metabolic, inflammatory and anthropomorphic traits including circulating triglycerides.

OBJECTIVE This work was undertaken in order to identify Parkinson's disease (PD) risk variants in a Latino cohort, to describe the overlap in the genetic architecture of PD in Latinos compared to European-ancestry subjects, and to increase the diversity in PD genome-wide association (GWAS) data. METHODS We genotyped and imputed 1,497 PD cases and controls recruited from nine clinical sites across South America. We performed a GWAS using logistic mixed models; variants with a p-value

Background Although cell lines are an essential resource for studying cancer biology, many are of unknown ancestral origin, and their use may not be optimal for evaluating the biology of all patient populations. Methods An admixture analysis was performed using genome‐wide chip data from the Catalogue of Somatic Mutations in Cancer (COSMIC) Cell Lines Project to calculate genetic ancestry estimates for 1018 cancer cell lines. After stratifying the analyses by tissue and histology types, linear models were used to evaluate the influence of ancestry on gene expression and somatic mutation frequency. Results For the 701 cell lines with unreported ancestry, 215 were of East Asian origin, 30 were of African or African American origin, and 453 were of European origin. Notable imbalances were observed in ancestral representation across tissue type, with the majority of analyzed tissue types having few cell lines of African American ancestral origin, and with Hispanic and South Asian ancestry being almost entirely absent across all cell lines. In evaluating gene expression across these cell lines, expression levels of the genes neurobeachin line 1 (NBEAL1), solute carrier family 6 member 19 (SLC6A19), HEAT repeat containing 6 (HEATR6), and epithelial cell transforming 2 like (ECT2L) were associated with ancestry. Significant differences were also observed in the proportions of somatic mutation types across cell lines with varying ancestral proportions. Conclusions By estimating genetic ancestry for 1018 cancer cell lines, the authors have produced a resource that cancer researchers can use to ensure that their cell lines are ancestrally representative of the populations they intend to affect. Furthermore, the novel ancestry‐specific signal identified underscores the importance of ancestral awareness when studying cancer., Preclinical cancer cell line research is often conducted without an awareness of ancestral background, which results in incongruities between the genetic backgrounds of used cell lines and the patient populations they are intended to represent. By calculating genetic ancestry for 1018 common cancer cell lines and identifying ancestry‐specific expression and somatic mutation patterns, the importance of ancestral awareness is emphasized, and a resource is provided that can be used by cancer researchers to ensure that their cell lines are ancestrally representative of the populations they aim to impact.

Background: Uterine serous carcinomas (USC) comprise 10-15% of all uterine cancers, but are responsible for approximately 40% of all deaths due to the disease. African American women have the highest incidence of and mortality from USC of any racial or ethnic group. Assessment of racial differences in driver mutation frequency may partially explain the survival disparity, and identification of novel alterations may provide avenues for targeted treatment. Methods: Two academic hospitals in Detroit, Michigan identified 125 women who had surgical treatment for USC and formalin fixed, paraffin-embedded tissue available for whole exome sequencing (WES). Detailed clinical and pathological data were also available, including long-term follow up. WES was performed using Illumina’s NovaSeq 6000 platform and data were processed via the Genome Analysis Toolkit (GATK), with additional filtering to account for excess artifacts resulting from formalin fixation. Functional mutations were determined by ANNOVAR and the ClinVar database, while putative driver mutations were identified via the IntOGen pipeline. Percentages were used to describe the proportion of tumors harboring a gene mutation, and the Fisher’s exact test was used to test for statistically significant differences in African American (AA) versus non-Hispanic white (NHW) mutation frequencies. Results: The majority of tumors were from AA women (n=87, 69.6%), with the remaining from NHW women (n=38, 30.4%). The overall mutational burden in tumors from AA women was similar to tumors from NHW women (median=122 and 166.5, respectively, p-value=0.12).TP53 was the most frequently mutated, with 77% of tumors from AA women and 65.8% of tumors from NHW women harboring a mutation (p-value=0.20), followed by PPP2R1A (AA=19.5%, NHW=28.9%, p-value=0.25) and PIK3CA (AA=13.8%, NHW=23.7%, p-value=0.20). Of the 66 driver genes in uterine cancer identified from IntOGen, only 3 differed significantly by race: ARID1A (AA=5.7%, NHW=28.9%; p-value=0.001), PTEN (AA=1.1%, NHW=15.8%; p-value=0.003) and FGFR2 (AA=0%, NHW=7.9%, p-value=0.02). Examination of genes with mutational frequencies ≥10% in AA or NHW tumors and with significant differences in mutation distribution by race (n=96) identified an additional 10 genes with mutations that are considered drivers in other cancer types that have not been described in uterine cancers. Conclusions: There are potential driver mutations undescribed in USC that are clinically important in other cancers. Additionally, we noted several differences in the mutation frequency by race which highlights the importance of including racially diverse samples in research, particularly AA women who have the largest burden of USC. Defining the somatic landscape of USC will lead to identification of actionable molecular targets, which will ultimately improve the prognosis of this aggressive subtype. Citation Format: Michele L. Cote, Greg Dyson, Douglas Craig, Julie J. Ruterbusch, Julie Boerner, Mohamed A. Elshaikh, Thomas P. Conrads, Nicholas W. Bateman, George L. Maxwell, Kathleen M. Darcy, Sasha Makohon-Moores, Timothy D. O'Connor, Hassan Abdallah, Logan Corey, Mira Kheil, Rouba Ali-Fehmi. Whole exome sequencing of uterine serous carcinomas reveals racial differences in known and novel driver mutations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 750.

Hispanic populations have higher rates of obesity, elevated triglycerides, and a greater prevalence of diabetes. Long chain polyunsaturated fatty acids (LC-PUFAs) and LC-PUFA metabolites have critical signaling roles that regulate dyslipidemia and inflammation. Genetic variation in the FADS cluster accounts for a large part of the interindividual differences in circulating and tissue levels of LC-PUFAs, with the genotypes most strongly predictive of low LC-PUFA levels at strikingly higher frequencies in Amerind (AI) ancestry populations. In this study, we examined relationships between genetic ancestry and FADS variation, plasma phospholipid levels of LC-PUFAs, anthropometric measures, and circulating metabolic and inflammatory biomarkers in 1,102 Hispanic American participants, representing six distinct ancestry populations from the Multi-Ethnic Study of Atherosclerosis. We demonstrate strong negative associations between AI genetic ancestry and LC-PUFA levels. The FADS rs174537 single nucleotide polymorphism (SNP) accounted for much of the AI ancestry effect on LC-PUFAs, especially for low levels of n-3 LC-PUFAs. Rs174537 was also strongly associated with several metabolic, inflammatory and anthropomorphic traits including circulating triglycerides (TGs) and E-selectin in MESA Hispanics. We further replicated the association with circulating TGs in two additional Hispanic cohorts: the Hispanic Community Health Study/Study of Latinos and the Arizona Insulin Resistance Registry. Our study demonstrates that Amerind ancestry provides a useful and readily available tool to identify individuals most likely to have FADS-related n-3 LC-PUFA deficiencies and associated cardiovascular risk.

Objectives: To investigate racial differences in uterine cancer histology in non-Hispanic Back (NHB) and non-Hispanic White (NHW) women with one or more cancer diagnoses as an extension of prior studies that excluded cases with multiple malignancies. Download : Download high-res image (552KB) Download : Download full-size image Methods: Women in the 18-region Surveillance, Epidemiology and End Results registry with an invasive uterine cancer diagnosed between 1975 and 2015 as a first or second of multiple malignancies relative a single malignancy were evaluated. Median age at diagnosis was compared using Wilcoxon test. Proportions between histologic and racial groups were compared using Chi-square test. Age-adjusted odds ratio (AOR) and 95% confidence interval (CI) for each high-risk uterine cancer histology were calculated for NHBs vs NHWs. Results: There were 237,823 with an invasive uterine cancer including 177,869 as a single diagnosis, 29,594 as a first of multiple malignancies and 30,380 as a second of multiple malignancies. The distribution of NHBs by the setting of the uterine cancer diagnosis was 10.1% as a single malignancy, 6.7% as a first of multiple malignancies and 8.5% as second of multiple malignancies. The median age for the uterine cancer diagnosis in NHBs vs NHWs was 3 vs 5 years younger when identified as a single or first malignancy compared with as a second malignancy, respectively (Table 1). The proportion of both NHBs and NHWs with grade 3 endometrioid cancer, serous cancer and carcinosarcoma was consistently higher in both NHBs and NHWs when diagnosed as a second malignancy compared with a single or first malignancy (P Conclusions: Racial differences in uterine serous cancer, clear cell cancer, carcinosarcoma and leiomyosarcoma but not in grade 3 endometrioid cancer were smaller in women with a prior cancer diagnosis and may reflect the impact of factors including ancestral admixture, germline vs. somatic alterations, genetic modifiers, epigenetic regulators, exposure to prior cancer treatment, cancer screening and social health determinants.

Deep proteogenomic analyses of diverse populations will improve our understanding of molecular drivers of disease, such as those underlying uterine neoplasms which exhibit marked racial disparities. The characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step towards investigating relationships linking patient ancestry with the proteome, genome and disease pathogenesis. We selected 1,037 nonsynonymous single nucleotide polymorphisms (nsSNPs) encoding missense amino acid substitutions occurring within putative tryptic peptides exhibiting high allele frequencies (≥ 50%) in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs) and investigated these in cell line models and tissues of uterine neoplasms collected from women representing diverse ancestries. We quantified 62 pAIMs in total across >100 patient-derived samples by multiplexed, quantitative proteomic analyses. Our analyses of endometrial cancer cell lines established from European (n=7), African (n=3), and East Asian (n=3) women resulted in the quantitation of 43 pAIMs that significantly correlated with population-level allele frequencies consistent with global ancestry estimates defined by genotype analyses. We next investigated uterine leiomyoma (ULM) tissues from self-described African-American (n=31) and European-American (n=35) women and quantified 33 pAIMs that correlated with patient race. We validated 10 of these in an independent cohort of ULM tissues collected from women determined to be of European (n=16) and African (n=11) ancestry by genotype analyses. This validated subset was predominated by candidates of undetermined clinical significance (ClinVar) and included a substitution in GC vitamin D-binding protein, i.e. (D451E, rs7041), that exhibits a higher allele frequency in European (58%) versus African (7.3%) populations and correlates with altered GC protein and vitamin D levels. Comparison of cell line and tissue analyses revealed co-quantitation of pAIMs encoded within Protein-L-isoaspartate(D-aspartate) O-methyltransferase (V178I, >80% AF in African and East Asians), Serine/threonine-protein phosphatase CPPED1 (A19D, >75% AF in Africans) and AH receptor-interacting protein (Q228K, >99% AF in European and East Asians). We further assessed the performance of pAIMs to determine patient ancestry in silico relative to standard genotype estimates by random sampling analyses and find that as few as 20 population-specific pAIMs can determine ancestry proportions similarly to >260K SNPs (R2=0.9905). These efforts have quantified and validated pAIMs in diverse uterine neoplasms that represent a foundational set of ancestry-linked variant peptides observable by multiplexed proteomics and provides proof of concept that estimates of European, African and East Asian ancestry can be determined from routine proteomic analysis of disease-relevant patient cell lines and tissues. This work will support ongoing efforts focused on linking the proteome and genome with patient ancestry to better understand relationships with disease mechanisms driving racial disparities in the pathogenesis of uterine neoplasms.

To date, over 90 Parkinson’s disease (PD) risk variants have been reported from genome-wide association studies (GWAS). However, these GWAS efforts have been limited to individuals of European and East Asian ancestry. We performed the first GWAS of Latino PD patients from South America, comparing 807 cases against 690 controls followed by association testing of suggestive loci in a replication cohort of 1,234 cases and 439,522 controls. We demonstrated that SNCA plays a significant role in PD etiology in a Latino cohort and identified a suggestive locus near NRROS on chromosome 3 that appeared to be driven by Peruvian subjects. We also characterized the overlap of PD genetic architecture between Europeans and Latinos with a replication of significant variants identified by Nalls et al. in their 2019 GWAS1, finding 80% concordance in direction of effect. We then leveraged the population history of Latinos via admixture mapping, identifying a significant locus on chromosome 14 in a joint test of ancestries, driven by the Native American ancestral background, and a significant locus on chromosome 6 in our test of African ancestry, containing the genes STXBP6 and RPS6KA2, respectively. Ultimately, our work reflects the most comprehensive characterization of PD genetic architecture in Latinos to date.

Background and Purpose: The genetic contribution to ischemic stroke may include rare- or low-frequency variants of high-penetrance and large-effect sizes. Analyses focusing on early-onset disease, an extreme-phenotype, and on the exome, the protein-coding portion of genes, may increase the likelihood of identifying such rare functional variants. To evaluate this hypothesis, we implemented a 2-stage discovery and replication design, and then addressed whether the identified variants also associated with older-onset disease. Methods: Discovery was performed in UMD-GEOS Study (University of Maryland-Genetics of Early-Onset Stroke), a biracial population-based study of first-ever ischemic stroke cases 15 to 49 years of age (n=723) and nonstroke controls (n=726). All participants had prior GWAS (Genome Wide Association Study) and underwent Illumina exome-chip genotyping. Logistic-regression was performed to test single-variant associations with all-ischemic stroke and TOAST (Trial of ORG 10172 in Acute Stroke Treatment) subtypes in Whites and Blacks. Population level results were combined using meta-analysis. Gene-based aggregation testing and meta-analysis were performed using seqMeta. Covariates included age and gender, and principal-components for population structure. Pathway analyses were performed across all nominally associated genes for each stroke outcome. Replication was attempted through lookups in a previously reported meta-analysis of early-onset stroke and a large-scale stroke genetics study consisting of primarily older-onset cases. Results: Gene burden tests identified a significant association with NAT10 in small-vessel stroke ( P =3.79×10 − 6 ). Pathway analysis of the top 517 genes ( P P −7 ), several were near, including an intronic variant in LEXM (rs7549251; P =4.08×10 − 7 ) and an exonic variant in TRAPPC11 (rs67383011; P =5.19×10 − 6 ). Conclusions: Exome-based analysis in the setting of early-onset stroke is a promising strategy for identifying novel genetic risk variants, loci, and pathways.

Background: Parkinson's disease is the second most common neurodegenerative disorder and affects people from all ethnic backgrounds, yet little is known about the genetics of Parkinson's disease in non-European populations. In addition, the overall identification of copy number variants at a genome-wide level has been understudied in Parkinson's disease patients. Objectives: To understand the genome-wide burden of copy number variants in Latinos and its association with Parkinson's disease. Methods: We used genome-wide genotyping data from 747 Parkinson's disease patients and 632 ancestry matched controls from the Latin American Research Consortium on the Genetics of Parkinson's disease. Results: Genome-wide copy number burden analysis showed no difference between patients vs. controls, whereas patients were significantly enriched for copy number variants overlapping known Parkinson's disease genes compared to controls (Odds Ratio: 3.97 [1.69 - 10.5], P = 0.018). PARK2 showed the strongest copy number burden, with 20 copy number variant carriers. These patients presented an earlier age of disease onset compared to patients with other copy number variants (median age at onset: 31 years vs. 57 years, P = 7.46 x 10-7). Conclusions: We found that Parkinson's disease patients are significantly enriched with copy number variants affecting known Parkinson's disease genes. We also identified that out of 250 patients with early-onset disease, 5.6% carried a copy number variant on PARK2 in our cohort. Our study is the first to analyze genome-wide copy number variants association in Latino Parkinson's disease patients and provides insights about this complex disease in this understudied population.

MotivationThe global human population has experienced an explosive growth from a few million to roughly 7 billion people in the last 10,000 years. Accompanying this growth has been the accumulation of rare variants that can inform our understanding of human evolutionary history. Common variants have primarily been used to infer the structure of the human population and relatedness between two individuals. However, with the increasing abundance of rare variants observed in large-scale projects, such as Trans-Omics for Precision Medicine (TOPMed), the use of rare variants to decipher cryptic relatedness and fine-scale population structure can be beneficial to the study of population demographics and association studies. Identity-by-descent (IBD) is an important framework used for identifying these relationships. IBD segments are broken down by recombination over time, such that longer shared haplotypes give strong evidence of recent relatedness while shorter shared haplotypes are indicative of more distant relationships. Current methods to identify IBD accurately detect only long segments (> 2cM) found in related individuals.AlgorithmWe describe a metric that leverages rare-variants shared between individuals to improve the detection of short IBD segments. We computed IBD segments using existing methods implemented inRefined IBDwhere we enrich the signal using our metric that facilitates the detection of short IBD segments (ResultsTo test our new metric, we simulated datasets involving populations with varying divergent time-scales. We show that rare-variant IBD identifies shorter segments with greater confidence and enables the detection of older divergence between populations. As an example, we applied our metric to the Old-Order Amish cohort with known genealogies dating 14 generations back to validate its ability to detect genetic relatedness between distant relatives. This analysis shows that our method increases the accuracy of identifying shorter segments that in turn capture distant relationships.ConclusionsWe describe a method to enrich the detection of short IBD segments using rare-variant sharing within IBD segments. Leveraging rare-variant sharing improves the information content of short IBD segments better than common variants alone. We validated the method in both simulated and empirical datasets. This method can benefit association analyses, IBD mapping analyses, and demographic inferences.

Western South America was one of the worldwide cradles of civilization. The well known Inca Empire was the tip of the iceberg of a cultural and biological evolutionary process that started 14-11 thousand years ago. Genetic data from 18 Peruvian populations reveal that: (1) The between-population homogenization of the central-southern Andes and its differentiation with respect to Amazonian populations of similar latitudes do not extend northward. Instead, longitudinal gene flow between the northern coast of Peru, Andes and Amazonia accompanied cultural and socioeconomic interactions revealed by archeological studies. This pattern recapitulates the environmental and cultural differentiation between the fertile north, where altitudes are lower; and the arid south, where the Andes are higher, acting as a genetic barrier between the sharply different environments of the Andes and Amazonia (2). The genetic homogenization between the populations of the arid Andes is not only due to migration during the Inca Empire or the subsequent colonial period. It started at least during the earlier expansion of the pre-Inca Wari Empire (600-1000 YBP) (3) This demographic history allowed for cases of positive natural selection in the high and arid Andes vs. the low Amazon tropical forest: in the Andes, HAND2-AS1 (heart and neural crest derivatives expressed 2 antisense RNA1, related with cardiovascular function) and DUOX2 (dual oxidase 2, related to thyroid function and innate immunity) genes; in the Amazon, the gene encoding for the CD45 protein, essential for antigen recognition by T/B lymphocytes in viral-host interaction, consistent with the host-virus arms race hypothesis.

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains h 2 ), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.

Mechanistic processes underlying human germline mutations remain largely unknown. Variation in mutation rate and spectra along the genome is informative about the biological mechanisms. We statistically decompose this variation into separate processes using a blind source separation technique. The analysis of a large-scale whole genome sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. Seven of these processes lend themselves to a biological interpretation. One process is driven by bulky DNA lesions that resolve asymmetrically with respect to transcription and replication. Two processes independently track direction of replication fork and replication timing. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions. We also demonstrate that a recently discovered mutagenic process specific to oocytes can be localized solely from population sequencing data. This process is spread across all chromosomes and is highly asymmetric with respect to the direction of transcription, suggesting a major role of DNA damage.

Liquid biopsy, or the capacity to non-invasively isolate and analyze plasma tumor DNA (ptDNA) using blood samples, represents an important tool for modern oncology that enables increasingly safe, personalized and robust cancer diagnosis and treatment. Here, we review advances in the development and implementation of liquid biopsy approaches, and we focus on the capacity of liquid biopsy to non-invasively detect oncological disease and enhance early detection strategies. In addition to noting the distinctions between mutation targeted and mutation agnostic approaches, we discuss the potential for genomic analysis and longitudinal testing to identify somatic lesions early, and to guide intervention at more manageable disease stages.

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans., Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

Objectives: Endometrial cancer (EC) cell lines models established from diverse ancestral backgrounds and reflective of in situ 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 in situ clinical and molecular disease characteristics. Methods: 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 Results: 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. Conclusions: 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.

Intellectual disability (ID) is a clinically and genetically heterogeneous disorder, affecting 1–3% of the general population. Although research into the genetic causes of ID has recently gained momentum, identification of pathogenic mutations that cause autosomal recessive ID (ARID) has lagged behind, predominantly due to non-availability of sizeable families. Here we present the results of exome sequencing in 121 large consanguineous Pakistani ID families. In 60 families, we identified homozygous or compound heterozygous DNA variants in a single gene, 30 affecting reported ID genes and 30 affecting novel candidate ID genes. Potential pathogenicity of these alleles was supported by co-segregation with the phenotype, low frequency in control populations and the application of stringent bioinformatics analyses. In another eight families segregation of multiple pathogenic variants was observed, affecting 19 genes that were either known or are novel candidates for ID. Transcriptome profiles of normal human brain tissues showed that the novel candidate ID genes formed a network significantly enriched for transcriptional co-expression (P<0.0001) in the frontal cortex during fetal development and in the temporal–parietal and sub-cortex during infancy through adulthood. In addition, proteins encoded by 12 novel ID genes directly interact with previously reported ID proteins in six known pathways essential for cognitive function (P<0.0001). These results suggest that disruptions of temporal parietal and sub-cortical neurogenesis during infancy are critical to the pathophysiology of ID. These findings further expand the existing repertoire of genes involved in ARID, and provide new insights into the molecular mechanisms and the transcriptome map of ID.

Motivation Variant calling from next-generation sequencing (NGS) data is susceptible to false positive calls due to sequencing, mapping and other errors. To better distinguish true from false positive calls, we present a method that uses genotype array data from the sequenced samples, rather than public data such as HapMap or dbSNP, to train an accurate classifier using Random Forests. We demonstrate our method on a set of variant calls obtained from 642 African-ancestry genomes from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA), sequenced to high depth (30X). Results We have applied our classifier to compare call sets generated with different calling methods, including both single-sample and multi-sample callers. At a False Positive Rate of 5%, our method determines true positive rates of 97.5%, 95% and 99% on variant calls obtained using Illuminas single-sample caller CASAVA, Real Time Genomics multisample variant caller, and the GATK UnifiedGenotyper, respectively. Since NGS sequencing data may be accompanied by genotype data for the same samples, either collected concurrent to sequencing or from a previous study, our method can be trained on each dataset to provide a more accurate computational validation of site calls compared to generic methods. Moreover, our method allows for adjustment based on allele frequency (e.g. a different set of criteria to determine quality for rare versus common variants) and thereby provides insight into sequencing characteristics that indicate call quality for variants of different frequencies. Availability and Implementation Code is available on Github at: https://github.com/suyashss/variant_validation Supplementary information Supplementary data are available at Bioinformatics online.

Admixed populations are a resource to study the global genetic architecture of complex phenotypes, which is critical, considering that non-European populations are severely under-represented in genomic studies. Leveraging admixture in Brazilians, whose chromosomes are mosaics of fragments of Native American, European and African origins, we used genome-wide data to perform admixture mapping/fine-mapping of Body Mass Index (BMI) in three population-based cohorts from Northeast (Salvador), Southeast (Bambuí) and South (Pelotas) of the country. We found significant associations with African-associated alleles in children from Salvador (PALD1 and ZMIZ1 genes), and in young adults from Pelotas (NOD2 and MTUS2 genes). More importantly, in Pelotas, rs114066381, mapped in a potential regulatory region, is significantly associated only in females (p= 2.76 e-06). This variant is very rare in Europeans but with frequencies of ~3% in West Africa, and has a strong female-specific effect (95%CI: 2.32-5.65 kg/m2 per each A allele). We confirmed this sex-specific association and replicated its strong effect for an adjusted fat-mass index in the same Pelotas cohort, and for BMI in another Brazilian cohort from São Paulo (Southeast Brazil). A meta-analysis confirmed the significant association. Remarkably, we observed that while the frequency of rs114066381-A allele ranges from 0.8 to 2.1% in the studied populations, it attains ~9% among morbidly obese women from Pelotas, São Paulo, and Bambuí. The effect size of rs114066381 is at least five-times the effect size of the FTO SNPs rs9939609 and rs1558902, already emblematic for their high effects, and for which we replicated associations in Pelotas. We demonstrate how, after a decade of GWAS mostly performed in European-ancestry populations, non-European and admixed populations are a source of new relevant phenotype-associated genetic variants.

Motivation Identifying the genes regulated by a given transcription factor (TF) (its ‘target genes’) is a key step in developing a comprehensive understanding of gene regulation. Previously, we developed a method (CisMapper) for predicting the target genes of a TF based solely on the correlation between a histone modification at the TF’s binding site and the expression of the gene across a set of tissues or cell lines. That approach is limited to organisms for which extensive histone and expression data are available, and does not explicitly incorporate the genomic distance between the TF and the gene. Results We present the T-Gene algorithm, which overcomes these limitations. It can be used to predict which genes are most likely to be regulated by a TF, and which of the TF’s binding sites are most likely involved in regulating particular genes. T-Gene calculates a novel score that combines distance and histone/expression correlation, and we show that this score accurately predicts when a regulatory element bound by a TF is in contact with a gene’s promoter, achieving median precision above 60%. T-Gene is easy to use via its web server or as a command-line tool, and can also make accurate predictions (median precision above 40%) based on distance alone when extensive histone/expression data is not available for the organism. T-Gene provides an estimate of the statistical significance of each of its predictions. Availability and implementation The T-Gene web server, source code, histone/expression data and genome annotation files are provided at http://meme-suite.org. Supplementary information Supplementary data are available at Bioinformatics online.

Author(s): Daya, Michelle; Rafaels, Nicholas; Brunetti, Tonya M; Chavan, Sameer; Levin, Albert M; Shetty, Aniket; Gignoux, Christopher R; Boorgula, Meher Preethi; Wojcik, Genevieve; Campbell, Monica; Vergara, Candelaria; Torgerson, Dara G; Ortega, Victor E; Doumatey, Ayo; Johnston, Henry Richard; Acevedo, Nathalie; Araujo, Maria Ilma; Avila, Pedro C; Belbin, Gillian; Bleecker, Eugene; Bustamante, Carlos; Caraballo, Luis; Cruz, Alvaro; Dunston, Georgia M; Eng, Celeste; Faruque, Mezbah U; Ferguson, Trevor S; Figueiredo, Camila; Ford, Jean G; Gan, Weiniu; Gourraud, Pierre-Antoine; Hansel, Nadia N; Hernandez, Ryan D; Herrera-Paz, Edwin Francisco; Jimenez, Silvia; Kenny, Eimear E; Knight-Madden, Jennifer; Kumar, Rajesh; Lange, Leslie A; Lange, Ethan M; Lizee, Antoine; Maul, Pissamai; Maul, Trevor; Mayorga, Alvaro; Meyers, Deborah; Nicolae, Dan L; O'Connor, Timothy D; Oliveira, Ricardo Riccio; Olopade, Christopher O; Olopade, Olufunmilayo; Qin, Zhaohui S; Rotimi, Charles; Vince, Nicolas; Watson, Harold; Wilks, Rainford J; Wilson, James G; Salzberg, Steven; Ober, Carole; Burchard, Esteban G; Williams, L Keoki; Beaty, Terri H; Taub, Margaret A; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen C; CAAPA | Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Comparative analyses suggest that the MHC was derived from a prevertebrate “primordial immune complex” (PIC). PIC duplicated twice in the well-studied two rounds of genome-wide duplications (2R) early in vertebrate evolution, generating four MHC paralogous regions (predominantly on human chromosomes [chr] 1, 6, 9, 19). Examining chiefly the amphibian Xenopus laevis, but also other vertebrates, we identified their MHC paralogues and mapped MHC class I, AgR, and “framework” genes. Most class I genes mapped to MHC paralogues, but a cluster of Xenopus MHC class Ib genes (xnc), which previously was mapped outside of the MHC paralogues, was surrounded by genes syntenic to mammalian CD1 genes, a region previously proposed as an MHC paralogue on human chr 1. Thus, this gene block is instead the result of a translocation that we call the translocated part of the MHC paralogous region (MHCtrans). Analyses of Xenopus class I genes, as well as MHCtrans, suggest that class I arose at 1R on the chr 6/19 ancestor. Of great interest are nonrearranging AgR-like genes mapping to three MHC paralogues; thus, PIC clearly contained several AgR precursor loci, predating MHC class I/II. However, all rearranging AgR genes were found on paralogues derived from the chr 19 precursor, suggesting that invasion of a variable (V) exon by the RAG transposon occurred after 2R. We propose models for the evolutionary history of MHC/TCR/Ig and speculate on the dichotomy between the jawless (lamprey and hagfish) and jawed vertebrate adaptive immune systems, as we found genes related to variable lymphocyte receptors also map to MHC paralogues.

Summary paragraphThe Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency

On average, Peruvian individuals are among the shortest in the world1. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru. In an ethnically diverse group of Peruvian individuals, the population-specific, missense variant in FBN1 (E1297G) is associated with lower height and shows evidence of positive selection within the Peruvian population.

de novoMutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) program, we directly estimate and analyze DNM counts, rates, and spectra from 1,465 trios across an array of diverse human populations. Using the resulting call set of 86,865 single nucleotide DNMs, we find a significant positive correlation between local recombination rate and local DNM rate, which together can explain up to 35.5% of the genome-wide variation in population level rare genetic variation from 41K unrelated TOPMed samples. While genome-wide heterozygosity does correlate weakly with DNM count, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, interestingly, we do find significantly fewer DNMs in Amish individuals compared with other Europeans, even after accounting for parental age and sequencing center. Specifically, we find significant reductions in the number of T→C mutations in the Amish, which seems to underpin their overall reduction in DNMs. Finally, we calculate near-zero estimates of narrow sense heritability (h2), which suggest that variation in DNM rate is significantly shaped by non-additive genetic effects and/or the environment, and that a less mutagenic environment may be responsible for the reduced DNM rate in the Amish.SignificanceHere we provide one of the largest and most diverse humande novomutation (DNM) call sets to date, and use it to quantify the genome-wide relationship between local mutation rate and population-level rare genetic variation. While we demonstrate that the human single nucleotide mutation rate is similar across numerous human ancestries and populations, we also discover a reduced mutation rate in the Amish founder population, which shows that mutation rates can shift rapidly. Finally, we find that variation in mutation rates is not heritable, which suggests that the environment may influence mutation rates more significantly than previously realized.