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Grinde KE, Browning BL, Reiner AP, Thornton TA, Browning SR. Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.02.587682. [PMID: 38617337 PMCID: PMC11014513 DOI: 10.1101/2024.04.02.587682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/24/2024]
Abstract
Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.
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Affiliation(s)
- Kelsey E. Grinde
- Department of Mathematics, Statistics, and Computer Science, Macalester College, Saint Paul, Minnesota, 55105, USA
| | - Brian L. Browning
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington, 98195, USA
| | - Alexander P. Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, 98109, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, 98195, USA
| | - Timothy A. Thornton
- Regeneron Genetics Center, Tarrytown, New York, 10591, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, 98195, USA
| | - Sharon R. Browning
- Department of Biostatistics, University of Washington, Seattle, Washington, 98195, USA
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2
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Chan TF, Rui X, Conti DV, Fornage M, Graff M, Haessler J, Haiman C, Highland HM, Jung SY, Kenny EE, Kooperberg C, Le Marchand L, North KE, Tao R, Wojcik G, Gignoux CR, Chiang CWK, Mancuso N. Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics. Am J Hum Genet 2023; 110:1853-1862. [PMID: 37875120 PMCID: PMC10645552 DOI: 10.1016/j.ajhg.2023.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 10/26/2023] Open
Abstract
The heritability explained by local ancestry markers in an admixed population (hγ2) provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of hγ2 can be susceptible to biases due to population structure in ancestral populations. Here, we present heritability estimation from admixture mapping summary statistics (HAMSTA), an approach that uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA hγ2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of ∼5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe hˆγ2 in the 20 phenotypes range from 0.0025 to 0.033 (mean hˆγ2 = 0.012 ± 9.2 × 10-4), which translates to hˆ2 ranging from 0.062 to 0.85 (mean hˆ2 = 0.30 ± 0.023). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 ± 0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies.
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Affiliation(s)
- Tsz Fung Chan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Xinyue Rui
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - David V Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Myriam Fornage
- Brown Foundation Institute for Molecular Medicine, The University of Texas Health Science Center, Houston, TX, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Christopher Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Heather M Highland
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Su Yon Jung
- Translational Sciences Section, School of Nursing, Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Genevieve Wojcik
- Department of Epidemiology, Bloomberg School of Public Health, John Hopkins University, Baltimore, MD, USA
| | - Christopher R Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
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3
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Tan T, Atkinson EG. Strategies for the Genomic Analysis of Admixed Populations. Annu Rev Biomed Data Sci 2023; 6:105-127. [PMID: 37127050 PMCID: PMC10871708 DOI: 10.1146/annurev-biodatasci-020722-014310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.
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Affiliation(s)
- Taotao Tan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA;
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA;
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4
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Cullina S, Wojcik GL, Shemirani R, Klarin D, Gorman BR, Sorokin EP, Gignoux CR, Belbin GM, Pyarajan S, Asgari S, Tsao PS, Damrauer SM, Abul-Husn NS, Kenny EE. Admixture mapping of peripheral artery disease in a Dominican population reveals a putative risk locus on 2q35. Front Genet 2023; 14:1181167. [PMID: 37600667 PMCID: PMC10432698 DOI: 10.3389/fgene.2023.1181167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 07/10/2023] [Indexed: 08/22/2023] Open
Abstract
Peripheral artery disease (PAD) is a form of atherosclerotic cardiovascular disease, affecting ∼8 million Americans, and is known to have racial and ethnic disparities. PAD has been reported to have a significantly higher prevalence in African Americans (AAs) compared to non-Hispanic European Americans (EAs). Hispanic/Latinos (HLs) have been reported to have lower or similar rates of PAD compared to EAs, despite having a paradoxically high burden of PAD risk factors; however, recent work suggests prevalence may differ between sub-groups. Here, we examined a large cohort of diverse adults in the BioMe biobank in New York City. We observed the prevalence of PAD at 1.7% in EAs vs. 8.5% and 9.4% in AAs and HLs, respectively, and among HL sub-groups, the prevalence was found at 11.4% and 11.5% in Puerto Rican and Dominican populations, respectively. Follow-up analysis that adjusted for common risk factors demonstrated that Dominicans had the highest increased risk for PAD relative to EAs [OR = 3.15 (95% CI 2.33-4.25), p < 6.44 × 10-14]. To investigate whether genetic factors may explain this increased risk, we performed admixture mapping by testing the association between local ancestry and PAD in Dominican BioMe participants (N = 1,813) separately from European, African, and Native American (NAT) continental ancestry tracts. The top association with PAD was an NAT ancestry tract at chromosome 2q35 [OR = 1.96 (SE = 0.16), p < 2.75 × 10-05) with 22.6% vs. 12.9% PAD prevalence in heterozygous NAT tract carriers versus non-carriers, respectively. Fine-mapping at this locus implicated tag SNP rs78529201 located within a long intergenic non-coding RNA (lincRNA) LINC00607, a gene expression regulator of key genes related to thrombosis and extracellular remodeling of endothelial cells, suggesting a putative link of the 2q35 locus to PAD etiology. Efforts to reproduce the signal in other Hispanic cohorts were unsuccessful. In summary, we showed how leveraging health system data helped understand nuances of PAD risk across HL sub-groups and admixture mapping approaches elucidated a putative risk locus in a Dominican population.
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Affiliation(s)
- Sinead Cullina
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Genevieve L. Wojcik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Ruhollah Shemirani
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Derek Klarin
- VA Palo Alto Healthcare System, Palo Alto, CA, United States
- Division of Vascular Surgery, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Bryan R. Gorman
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, United States
- Booz Allen Hamilton, McLean, VA, United States
| | - Elena P. Sorokin
- Department of Genetics, Stanford University, Stanford, CA, United States
| | - Christopher R. Gignoux
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Colorado Center for Personalized Medicine, Aurora, CO, United States
| | - Gillian M. Belbin
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Saiju Pyarajan
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Brigham Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Samira Asgari
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Philip S. Tsao
- VA Palo Alto Healthcare System, Palo Alto, CA, United States
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, United States
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Noura S. Abul-Husn
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Eimear E. Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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Rajabli F, Tosto G, Hamilton-Nelson KL, Kunkle BW, Vardarajan BN, Naj A, Whitehead PG, Gardner OK, Bush WS, Sariya S, Mayeux RP, Farrer LA, Cuccaro ML, Vance JM, Griswold AJ, Schellenberg GD, Haines JL, Byrd GS, Reitz C, Beecham GW, Pericak-Vance MA, Martin ER. Admixture mapping identifies novel Alzheimer's disease risk regions in African Americans. Alzheimers Dement 2023; 19:2538-2548. [PMID: 36539198 PMCID: PMC10272044 DOI: 10.1002/alz.12865] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 08/09/2022] [Accepted: 08/17/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND This study used admixture mapping to prioritize the genetic regions associated with Alzheimer's disease (AD) in African American (AA) individuals, followed by ancestry-aware regression analysis to fine-map the prioritized regions. METHODS We analyzed 10,271 individuals from 17 different AA datasets. We performed admixture mapping and meta-analyzed the results. We then used regression analysis, adjusting for local ancestry main effects and interactions with genotype, to refine the regions identified from admixture mapping. Finally, we leveraged in silico annotation and differential gene expression data to prioritize AD-related variants and genes. RESULTS Admixture mapping identified two genome-wide significant loci on chromosomes 17p13.2 (p = 2.2 × 10-5 ) and 18q21.33 (p = 1.2 × 10-5 ). Our fine mapping of the chromosome 17p13.2 and 18q21.33 regions revealed several interesting genes such as the MINK1, KIF1C, and BCL2. DISCUSSION Our ancestry-aware regression approach showed that AA individuals have a lower risk of AD if they inherited African ancestry admixture block at the 17p13.2 locus. HIGHLIGHTS We identified two genome-wide significant admixture mapping signals: on chromosomes 17p13.2 and 18q21.33, which are novel in African American (AA) populations. Our ancestry-aware regression approach showed that AA individuals have a lower risk of Alzheimer's disease (AD) if they inherited African ancestry admixture block at the 17p13.2 locus. We found that the overall proportion of African ancestry does not differ between the cases and controls that suggest African genetic ancestry alone is not likely to explain the AD prevalence difference between AA and non-Hispanic White populations.
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Affiliation(s)
- Farid Rajabli
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Giuseppe Tosto
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Kara L. Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Brian W. Kunkle
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Badri N. Vardarajan
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Adam Naj
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PE, USA
| | - Patrice G. Whitehead
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Olivia K. Gardner
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - William S. Bush
- Department of Population & Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Sanjeev Sariya
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Richard P. Mayeux
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Lindsay A. Farrer
- Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Epidemiology, and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jeffrey M. Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Anthony J. Griswold
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Gerard D. Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PE, USA
| | - Jonathan L. Haines
- Department of Population & Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Goldie S. Byrd
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Christiane Reitz
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Gary W. Beecham
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Eden R. Martin
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
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Gautam Y, Caldwell J, Kottyan L, Chehade M, Dellon ES, Rothenberg ME, Mersha TB. Genome-wide admixture and association analysis identifies African ancestry-specific risk loci of eosinophilic esophagitis in African Americans. J Allergy Clin Immunol 2023; 151:1337-1350. [PMID: 36400179 PMCID: PMC10164699 DOI: 10.1016/j.jaci.2022.09.040] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 09/17/2022] [Accepted: 09/28/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Eosinophilic esophagitis (EoE), a chronic allergic inflammatory disease, is linked to multiple genetic risk factors, but studies have focused on populations of European ancestry. Few studies have assessed Black or African American (AA) populations for loci involved in EoE susceptibility. OBJECTIVE We performed admixture mapping (AM) and genome-wide association study (GWAS) of EoE using participants from AA populations. METHODS We conducted AM and GWAS of EoE using 137 EoE cases and 1465 healthy controls from the AA population. Samples were genotyped using molecular evolutionary genetics analysis (MEGA). Genotype imputation was carried out with the Consortium on Asthma Among African-Ancestry Populations in the Americas (CAAPA) reference panel using the Michigan Imputation Server. Global and local ancestry inference was carried out, followed by fine mapping and RNA sequencing. After quality control filtering, over 6,000,000 variants were tested by logistic regression adjusted for sex, age, and global ancestry. RESULTS The global African ancestry proportion was found to be significantly lower among cases than controls (0.751 vs 0.786, P = .012). Case-only AM identified 3 significant loci (9p13.3, 12q24.22-23, and 15q11.2) associated with EoE, of which 12q24.22-23 and 9p13.3 were further replicated in the case-control analysis, with associations observed with African ancestry. Fine mapping and multiomic functional annotations prioritized the variants rs11068264 (FBXW8) and rs7307331 (VSIG10) at 12q24.23 and rs2297879 (ARHGEF39) at 9p13.3. GWAS identified 1 genome-wide significant locus at chromosome 1p22.3 (rs17131726, DDAH1) and 10 other suggestive loci. Most GWAS variants were low-frequency African ancestry-specific variants. RNA sequencing revealed that esophageal DDAH1 and VSIG10 were downregulated and ARHGEF39 upregulated among EoE cases. CONCLUSIONS GWAS and AM for EoE in AA revealed that African ancestry-specific genetic susceptibility loci exist at 1p22.3, 9p13.3, and 12q24.23, providing evidence of ancestry-specific inheritance of EoE. More independent genetic studies of different ancestries for EoE are needed.
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Affiliation(s)
- Yadu Gautam
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio
| | - Julie Caldwell
- Division of Allergy and Immunology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio
| | - Leah Kottyan
- Division of Allergy and Immunology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio
| | - Mirna Chehade
- Mount Sinai Center for Eosinophilic Disorders, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Evan S Dellon
- Center for Esophageal Diseases and Swallowing, Division of Gastroenterology and Hepatology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Marc E Rothenberg
- Division of Allergy and Immunology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio
| | - Tesfaye B Mersha
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio.
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7
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Chan TF, Rui X, Conti DV, Fornage M, Graff M, Haessler J, Haiman C, Highland HM, Jung SY, Kenny E, Kooperberg C, Marchland LL, North KE, Tao R, Wojcik G, Gignoux CR, Chiang CWK, Mancuso N. Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.10.536252. [PMID: 37131817 PMCID: PMC10153181 DOI: 10.1101/2023.04.10.536252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The heritability explained by local ancestry markers in an admixed population h γ 2 provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of h γ 2 can be susceptible to biases due to population structure in ancestral populations. Here, we present a novel approach, Heritability estimation from Admixture Mapping Summary STAtistics (HAMSTA), which uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA h γ 2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of ~5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe h ˆ γ 2 in the 20 phenotypes range from 0.0025 to 0.033 (mean h ˆ γ 2 = 0.012 + / - 9.2 × 10 - 4 ), which translates to h ˆ 2 ranging from 0.062 to 0.85 (mean h ˆ 2 = 0.30 + / - 0.023 ). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 +/- 0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies.
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Affiliation(s)
- Tsz Fung Chan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Xinyue Rui
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - David V Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Myriam Fornage
- Brown Foundation Institute for Molecular Medicine, The University of Texas Health Science Center, Houston, TX, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Christopher Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Heather M Highland
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Su Yon Jung
- Translational Sciences Section, School of Nursing, Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Eimear Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Loic Le Marchland
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Genevieve Wojcik
- Department of Epidemiology, Bloomberg School of Public Health, John Hopkins University, Baltimore, MD, USA
| | - Christopher R Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
- Department of Quantitative and Computational Biology, University of Southern California
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
- Department of Quantitative and Computational Biology, University of Southern California
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8
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Cullina S, Wojcik GL, Shemirani R, Klarin D, Gorman BR, Sorokin EP, Gignoux CR, Belbin GM, Pyarajan S, Asgari S, Tsao PS, Damrauer SM, Abul-Husn NS, Kenny EE. Admixture Mapping of Peripheral Artery Disease in a Dominican Population Reveals a Novel Risk Locus on 2q35. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.27.23287788. [PMID: 37034679 PMCID: PMC10081406 DOI: 10.1101/2023.03.27.23287788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Peripheral artery disease (PAD) is a form of atherosclerotic cardiovascular disease, affecting ∼8 million Americans, and is known to have racial and ethnic disparities. PAD has been reported to have significantly higher prevalence in African Americans (AAs) compared to non-Hispanic European Americans (EAs). Hispanic/Latinos (HLs) have been reported to have lower or similar rates of PAD compared to EAs, despite having a paradoxically high burden of PAD risk factors, however recent work suggests prevalence may differ between sub-groups. Here we examined a large cohort of diverse adults in the Bio Me biobank in New York City (NYC). We observed the prevalence of PAD at 1.7% in EAs vs 8.5% and 9.4% in AAs and HLs, respectively; and among HL sub-groups, at 11.4% and 11.5% in Puerto Rican and Dominican populations, respectively. Follow-up analysis that adjusted for common risk factors demonstrated that Dominicans had the highest increased risk for PAD relative to EAs (OR=3.15 (95% CI 2.33-4.25), P <6.44×10 -14 ). To investigate whether genetic factors may explain this increased risk, we performed admixture mapping by testing the association between local ancestry (LA) and PAD in Dominican Bio Me participants (N=1,940) separately for European (EUR), African (AFR) and Native American (NAT) continental ancestry tracts. We identified a NAT ancestry tract at chromosome 2q35 that was significantly associated with PAD (OR=2.05 (95% CI 1.51-2.78), P <4.06×10 -6 ) with 22.5% vs 12.5% PAD prevalence in heterozygous NAT tract carriers versus non-carriers, respectively. Fine-mapping at this locus implicated tag SNP rs78529201 located within a long intergenic non-coding RNA (lincRNA) LINC00607 , a gene expression regulator of key genes related to thrombosis and extracellular remodeling of endothelial cells, suggesting a putative link of the 2q35 locus to PAD etiology. In summary, we showed how leveraging health systems data helped understand nuances of PAD risk across HL sub-groups and admixture mapping approaches elucidated a novel risk locus in a Dominican population.
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9
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Barragan FA, Mills LJ, Raduski AR, Marcotte EL, Grinde KE, Spector LG, Williams LA. Genetic ancestry, differential gene expression, and survival in pediatric B-cell acute lymphoblastic leukemia. Cancer Med 2023; 12:4761-4772. [PMID: 36127808 PMCID: PMC9972134 DOI: 10.1002/cam4.5266] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 08/23/2022] [Accepted: 09/01/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Black children have lower incidence yet worse survival than White and Latinx children with B-cell acute lymphoblastic leukemia (B-ALL). It is unclear how reported race/ethnicity (RRE) is associated with death in B-ALL after accounting for differentially expressed genes associated with genetic ancestry. METHODS Using Phase 1 and 2 NCI TARGET B-ALL cases (N = 273; RRE-Black = 21, RRE-White = 162, RRE-Latinx = 69, RRE-Other = 9, RRE-Unknown = 12), we estimated proportions of African (AFR), European (EUR), and Amerindian (AMR) genetic ancestry. We estimated hazard ratios (HR) and 95% confidence intervals (95% CI) between ancestry and death while adjusting for RRE and clinical measures. We identified genes associated with genetic ancestry and adjusted for them in RRE and death associations. RESULTS Genetic ancestry varied within RRE (RRE-Black, AFR proportion: Mean: 78.5%, Range: 38.2%-93.6%; RRE-White, EUR proportion: Mean: 94%, Range: 1.6%-99.9%; RRE-Latinx, AMR proportion: Mean: 52.0%, Range: 1.2%-98.7%). We identified 10, 1, and 6 differentially expressed genes (padjusted <0.05) associated with AFR, AMR, and EUR ancestry proportion, respectively. We found AMR and AFR ancestry were statistically significantly associated with death (AMR each 10% HR: 1.05, 95% CI: 1.03-1.17, AFR each 10% increase HR: 1.03, 95% CI:1.01-1.19). RRE differences in the risk of death were larger in magnitude upon adjustment for genes associated with genetic ancestry for RRE-Black, but not RRE-Latinx children (RRE-Black HR: 3.35, 95% CI: 1.31, 8.53; RRE-Latinx HR: 1.47, 0.88-2.45). CONCLUSIONS Our work highlights B-ALL survival differences by RRE after adjusting for ancestry differentially expressed genes suggesting other factors impacting survival are important.
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Affiliation(s)
- Freddy A Barragan
- Department of Mathematics, Statistics, and Computer Science, Macalester College, St. Paul, Minnesota, USA.,Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Lauren J Mills
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Andrew R Raduski
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Erin L Marcotte
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA.,Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
| | - Kelsey E Grinde
- Department of Mathematics, Statistics, and Computer Science, Macalester College, St. Paul, Minnesota, USA
| | - Logan G Spector
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA.,Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
| | - Lindsay A Williams
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA.,Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
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10
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Li S, Chiang CWK, Myint SS, Arroyo K, Chan TF, Morimoto L, Metayer C, de Smith AJ, Walsh KM, Wiemels JL. Localized variation in ancestral admixture identifies pilocytic astrocytoma risk loci among Latino children. PLoS Genet 2022; 18:e1010388. [PMID: 36070312 PMCID: PMC9484652 DOI: 10.1371/journal.pgen.1010388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 09/19/2022] [Accepted: 08/21/2022] [Indexed: 11/18/2022] Open
Abstract
Background Pilocytic astrocytoma (PA) is the most common pediatric brain tumor. PA has at least a 50% higher incidence in populations of European ancestry compared to other ancestral groups, which may be due in part to genetic differences. Methods We first compared the global proportions of European, African, and Amerindian ancestries in 301 PA cases and 1185 controls of self-identified Latino ethnicity from the California Biobank. We then conducted admixture mapping analysis to assess PA risk with local ancestry. Results We found PA cases had a significantly higher proportion of global European ancestry than controls (case median = 0.55, control median = 0.51, P value = 3.5x10-3). Admixture mapping identified 13 SNPs in the 6q14.3 region (SNX14) contributing to risk, as well as three other peaks approaching significance on chromosomes 7, 10 and 13. Downstream fine mapping in these regions revealed several SNPs potentially contributing to childhood PA risk. Conclusions There is a significant difference in genomic ancestry associated with Latino PA risk and several genomic loci potentially mediating this risk. Childhood brain tumors are among the most prevalent and lethal childhood cancers. Despite this, the epidemiology as well as genetic risks are not well defined. For example, children of European ancestry have a higher risk of contracting pilocytic astrocytoma (PA) compared to other ancestries, but the genetic or environmental basis for this is unknown. Latino children are a mixture of multiple ancestries including European, African, and Native American. Using a group of Californian Latino children, we show that the risk of PA increases when a Latino child has a higher proportion of European ancestry. This global ancestry difference shows that germline genetic risk alleles contribute to a higher PA risk in children of European descendent. Moreover, this ancestral risk is localized to specific regions of the genome, especially in Chromosome 6 near the SNX14 gene, which is associated with cancer-related growth signaling pathway described by MAPK/ERK. This result brings us one step closer to understanding the etiology of this common childhood brain tumor.
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Affiliation(s)
- Shaobo Li
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
| | - Charleston W. K. Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, United States of America
| | - Swe Swe Myint
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
| | - Katti Arroyo
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
| | - Tsz Fung Chan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
| | - Libby Morimoto
- School of Public Health, University of California Berkeley, Berkeley, California, United States of America
| | - Catherine Metayer
- School of Public Health, University of California Berkeley, Berkeley, California, United States of America
| | - Adam J. de Smith
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
| | - Kyle M. Walsh
- Division of Neuro-Epidemiology, Department of Neurosurgery, Duke University, Durham, North Carolina, United States of America
- * E-mail: (KMW); (JLW)
| | - Joseph L. Wiemels
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America
- * E-mail: (KMW); (JLW)
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11
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Horimoto AR, Xue D, Cai J, Lash JP, Daviglus ML, Franceschini N, Thornton TA. Genome-Wide Admixture Mapping of Estimated Glomerular Filtration Rate and Chronic Kidney Disease Identifies European and African Ancestry-of-Origin Loci in Hispanic and Latino Individuals in the United States. J Am Soc Nephrol 2022; 33:77-87. [PMID: 34670813 PMCID: PMC8763178 DOI: 10.1681/asn.2021050617] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 09/08/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Admixture mapping is a powerful approach for gene mapping of complex traits that leverages the diverse genetic ancestry in populations with recent admixture, such as Hispanic or Latino individuals in the United States. These individuals have an increased risk of CKD. METHODS We performed genome-wide admixture mapping for both CKD and eGFR in a sample of 12,601 participants from the Hispanic Community Health Study/Study of Latinos, with validation in a sample of 8191 Black participants from the Women's Health Initiative (WHI). We also compared the findings with those from a conventional genome-wide association study. RESULTS Three novel ancestry-of-origin loci were identified on chromosomes 2, 14, and 15 for CKD and eGFR. The chromosome 2 locus comprises two European ancestry regions encompassing the FSHR and NRXN1 genes, with European ancestry at this locus associated with increased CKD risk. The chromosome 14 locus, found within the DLK1-DIO3 imprinted domain, was associated with lower eGFR and driven by European ancestry. The eGFR-associated locus on chromosome 15 included intronic variants of RYR3 and was within an African-specific genomic region associated with higher eGFR. The genome-wide association study failed to identify significant associations in these regions. We validated the chromosome 14 and 15 loci associated with eGFR in the WHI Black participants. CONCLUSIONS This study provides evidence of shared ancestry-specific genomic regions influencing eGFR in Hispanic or Latino individuals and Black individuals and illustrates the potential for leveraging genetic ancestry in recently admixed populations for the discovery of novel candidate loci for kidney phenotypes.
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Affiliation(s)
| | - Diane Xue
- Institute for Public Health Genetics, University of Washington, Seattle, Washington
| | - Jianwen Cai
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| | - James P. Lash
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Martha L. Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, Illinois
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, Washington,Department of Statistics, University of Washington, Seattle, Washington
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12
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Swart Y, Uren C, van Helden PD, Hoal EG, Möller M. Local Ancestry Adjusted Allelic Association Analysis Robustly Captures Tuberculosis Susceptibility Loci. Front Genet 2021; 12:716558. [PMID: 34721521 PMCID: PMC8554120 DOI: 10.3389/fgene.2021.716558] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 10/01/2021] [Indexed: 11/13/2022] Open
Abstract
Pulmonary tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease. The risk of developing active TB is in part determined by host genetic factors. Most genetic studies investigating TB susceptibility fail to replicate association signals particularly across diverse populations. South African populations arose because of multi-wave genetic admixture from the indigenous KhoeSan, Bantu-speaking Africans, Europeans, Southeast Asian-and East Asian populations. This has led to complex genetic admixture with heterogenous patterns of linkage disequilibrium and associated traits. As a result, precise estimation of both global and local ancestry is required to prevent both false positive and false-negative associations. Here, 820 individuals from South Africa were genotyped on the SNP-dense Illumina Multi-Ethnic Genotyping Array (∼1.7M SNPs) followed by local and global ancestry inference using RFMix. Local ancestry adjusted allelic association (LAAA) models were utilized owing to the extensive genetic heterogeneity present in this population. Hence, an interaction term, comprising the identification of the minor allele that corresponds to the ancestry present at the specific locus under investigation, was included as a covariate. One SNP (rs28647531) located on chromosome 4q22 was significantly associated with TB susceptibility and displayed a SNP minor allelic effect (G allele, frequency = 0.204) whilst correcting for local ancestry for Bantu-speaking African ancestry (p-value = 5.518 × 10-7; OR = 3.065; SE = 0.224). Although no other variants passed the significant threshold, clear differences were observed between the lead variants identified for each ancestry. Furthermore, the LAAA model robustly captured the source of association signals in multi-way admixed individuals from South Africa and allowed the identification of ancestry-specific disease risk alleles associated with TB susceptibility that have previously been missed.
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Affiliation(s)
- Yolandi Swart
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Caitlin Uren
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Paul D van Helden
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Eileen G Hoal
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Marlo Möller
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
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13
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Casares-Marfil D, Guillen-Guio B, Lorenzo-Salazar JM, Rodríguez-Pérez H, Kerick M, Jaimes-Campos MA, Díaz ML, Estupiñán E, Echeverría LE, González CI, Martin J, Flores C, Acosta-Herrera M. Admixture mapping analysis reveals differential genetic ancestry associated with Chagas disease susceptibility in the Colombian population. Hum Mol Genet 2021; 30:2503-2512. [PMID: 34302177 PMCID: PMC8643504 DOI: 10.1093/hmg/ddab213] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 01/02/2023] Open
Abstract
Chagas disease is an infection caused by the parasite Trypanosoma cruzi, endemic in Latino America. Leveraging the three-way admixture between Native American (AMR), European (EUR) and African (AFR) populations in Latin Americans, we aimed to better understand the genetic basis of Chagas disease by performing an admixture mapping study in a Colombian population. A two-stage study was conducted, and subjects were classified as seropositive and seronegative for T. cruzi. In stage 1, global and local ancestries were estimated using reference data from the 1000 Genomes Project (1KGP) and local ancestry associations were performed by logistic regression models. The AMR ancestry showed a protective association with Chagas disease within the Major Histocompatibility Complex region (OR = 0.74, 95%CI = 0.66-0.83, lowest p-value = 4.53x10-8). The fine mapping assessment on imputed genotypes combining data from stage 1 and 2 from an independent Colombian cohort, revealed nominally associated variants in high linkage disequilibrium with the top signal (rs2032134, OR = 0.93, 95%CI = 0.90-0.97, p-value = 3.54x10-4) in the previously associated locus. To assess ancestry-specific adaptive signals, a selective sweep scan in an AMR reference population from 1KGP together with an in silico functional analysis highlighted the Tripartite Motif family and the Human Leukocyte Antigen (HLA) genes, with crucial role in the immune response against pathogens. Furthermore, these analyses emphasized the macrophages, neutrophils, and eosinophils, as key players in the defense against T. cruzi. This first admixture mapping study in Chagas disease provided novel insights underlying the host immune response in the pathogenesis of this neglected disease.
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Affiliation(s)
| | - Beatriz Guillen-Guio
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Jose M Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Héctor Rodríguez-Pérez
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Martin Kerick
- Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain
| | - Mayra A Jaimes-Campos
- Grupo de Inmunología y Epidemiología Molecular, Escuela de Microbiología, Universidad Industrial de Santander, Bucaramanga, Colombia
| | - Martha L Díaz
- Grupo de Inmunología y Epidemiología Molecular, Escuela de Microbiología, Universidad Industrial de Santander, Bucaramanga, Colombia
| | - Elkyn Estupiñán
- Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain.,Grupo de Inmunología y Epidemiología Molecular, Escuela de Microbiología, Universidad Industrial de Santander, Bucaramanga, Colombia
| | - Luis E Echeverría
- Heart Failure and Heart Transplant Clinic, Fundación Cardiovascular de Colombia, Floridablanca, Colombia
| | - Clara I González
- Grupo de Inmunología y Epidemiología Molecular, Escuela de Microbiología, Universidad Industrial de Santander, Bucaramanga, Colombia
| | - Javier Martin
- Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain
| | - Carlos Flores
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain.,Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
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14
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Horimoto ARVR, Xue D, Thornton TA, Blue EE. Admixture mapping reveals the association between Native American ancestry at 3q13.11 and reduced risk of Alzheimer's disease in Caribbean Hispanics. Alzheimers Res Ther 2021; 13:122. [PMID: 34217363 PMCID: PMC8254995 DOI: 10.1186/s13195-021-00866-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/20/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND Genetic studies have primarily been conducted in European ancestry populations, identifying dozens of loci associated with late-onset Alzheimer's disease (AD). However, much of AD's heritability remains unexplained; as the prevalence of AD varies across populations, the genetic architecture of the disease may also vary by population with the presence of novel variants or loci. METHODS We conducted genome-wide analyses of AD in a sample of 2565 Caribbean Hispanics to better understand the genetic contribution to AD in this population. Statistical analysis included both admixture mapping and association testing. Evidence for differential gene expression within regions of interest was collected from independent transcriptomic studies comparing AD cases and controls in samples with primarily European ancestry. RESULTS Our genome-wide association study of AD identified no loci reaching genome-wide significance. However, a genome-wide admixture mapping analysis that tests for association between a haplotype's ancestral origin and AD status detected a genome-wide significant association with chromosome 3q13.11 (103.7-107.7Mb, P = 8.76E-07), driven by a protective effect conferred by the Native American ancestry (OR = 0.58, 95%CI = 0.47-0.73). Within this region, two variants were significantly associated with AD after accounting for the number of independent tests (rs12494162, P = 2.33E-06; rs1731642, P = 6.36E-05). The significant admixture mapping signal is composed of 15 haplotype blocks spanning 5 protein-coding genes (ALCAM, BBX, CBLB, CCDC54, CD47) and four brain-derived topologically associated domains, and includes markers significantly associated with the expression of ALCAM, BBX, CBLB, and CD47 in the brain. ALCAM and BBX were also significantly differentially expressed in the brain between AD cases and controls with European ancestry. CONCLUSION These results provide multiethnic evidence for a relationship between AD and multiple genes at 3q13.11 and illustrate the utility of leveraging genetic ancestry diversity via admixture mapping for new insights into AD.
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Affiliation(s)
| | - Diane Xue
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Elizabeth E Blue
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA.
- Division of Medical Genetics, University of Washington, BOX 357720, Seattle, WA, 98195-7720, USA.
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15
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Sun H, Lin M, Russell EM, Minster RL, Chan TF, Dinh BL, Naseri T, Reupena MS, Lum-Jones A, Cheng I, Wilkens LR, Le Marchand L, Haiman CA, Chiang CWK. The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians. PLoS Genet 2021; 17:e1009273. [PMID: 33571193 PMCID: PMC7877570 DOI: 10.1371/journal.pgen.1009273] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 11/18/2020] [Indexed: 12/17/2022] Open
Abstract
Epidemiological studies of obesity, Type-2 diabetes (T2D), cardiovascular diseases and several common cancers have revealed an increased risk in Native Hawaiians compared to European- or Asian-Americans living in the Hawaiian islands. However, there remains a gap in our understanding of the genetic factors that affect the health of Native Hawaiians. To fill this gap, we studied the genetic risk factors at both the chromosomal and sub-chromosomal scales using genome-wide SNP array data on ~4,000 Native Hawaiians from the Multiethnic Cohort. We estimated the genomic proportion of Native Hawaiian ancestry ("global ancestry," which we presumed to be Polynesian in origin), as well as this ancestral component along each chromosome ("local ancestry") and tested their respective association with binary and quantitative cardiometabolic traits. After attempting to adjust for non-genetic covariates evaluated through questionnaires, we found that per 10% increase in global Polynesian genetic ancestry, there is a respective 8.6%, and 11.0% increase in the odds of being diabetic (P = 1.65×10-4) and having heart failure (P = 2.18×10-4), as well as a 0.059 s.d. increase in BMI (P = 1.04×10-10). When testing the association of local Polynesian ancestry with risk of disease or biomarkers, we identified a chr6 region associated with T2D. This association was driven by an uniquely prevalent variant in Polynesian ancestry individuals. However, we could not replicate this finding in an independent Polynesian cohort from Samoa due to the small sample size of the replication cohort. In conclusion, we showed that Polynesian ancestry, which likely capture both genetic and lifestyle risk factors, is associated with an increased risk of obesity, Type-2 diabetes, and heart failure, and that larger cohorts of Polynesian ancestry individuals will be needed to replicate the putative association on chr6 with T2D.
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Affiliation(s)
- Hanxiao Sun
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Meng Lin
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Emily M. Russell
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Ryan L. Minster
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Tsz Fung Chan
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Bryan L. Dinh
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, United States of America
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia, Samoa
| | | | - Annette Lum-Jones
- Epidemiology Program, University of Hawai‘i Cancer Center, University of Hawai‘i, Manoa, Honolulu, Hawaii, United States of America
| | | | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America
| | - Lynne R. Wilkens
- Epidemiology Program, University of Hawai‘i Cancer Center, University of Hawai‘i, Manoa, Honolulu, Hawaii, United States of America
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawai‘i Cancer Center, University of Hawai‘i, Manoa, Honolulu, Hawaii, United States of America
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Charleston W. K. Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, United States of America
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Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium. EBioMedicine 2021; 63:103157. [PMID: 33418499 PMCID: PMC7804602 DOI: 10.1016/j.ebiom.2020.103157] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 11/10/2020] [Accepted: 11/18/2020] [Indexed: 01/05/2023] Open
Abstract
Background Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants. Methods We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity. Findings When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10−11; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10−9; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10−9). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10−9, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10−9, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants. Interpretation This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.
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Strauss M, Casares-Marfil D, Alcaraz A, Palma-Vega M, Bosch-Nicolau P, Lo Presti MS, Molina I, González CI, Martín J, Acosta-Herrera M. Lack of Association of IL6 polymorphism with the susceptibility to Chagas disease in Latin American populations. Acta Trop 2020; 210:105546. [PMID: 32492396 DOI: 10.1016/j.actatropica.2020.105546] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 05/04/2020] [Accepted: 05/16/2020] [Indexed: 11/26/2022]
Abstract
The aim of the present study was to analyze IL6 rs1800795 genetic variant in the susceptibility to Trypanosoma cruzi infection and in the development of chronic Chagas cardiomyopathy (CCC), in five independent Latin American cohorts. A total of 3,087 individuals from Latin American countries (Argentina, Bolivia, Peru, and two cohorts from Colombia) were studied. In all cohorts, patients were classified as seropositive for T. cruzi antigens (n= 1,963) and seronegative (n= 1,124). Based on clinical evaluation, the seropositive patients, were classified as CCC (n= 900) and asymptomatic (n= 1,063). No statistically significant differences in the frequency of IL6 rs1800795 between seropositive and seronegative, or between CCC and asymptomatic patients, were found. Furthermore, after the meta-analysis no statistically significant differences were observed. Our results do not support a contribution of IL6 rs1800795 genetic variant in the susceptibility to the infection and the development of chronic Chagas cardiomyopathy in the studied populations.
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Affiliation(s)
- Mariana Strauss
- Centro de Estudios e Investigación de la Enfermedad de Chagas y Leishmaniasis, FCM, INICSA-CONICET-UNC, Córdoba, Argentina.
| | - Desiré Casares-Marfil
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, PTS Granada, Granada, España.
| | - Alexia Alcaraz
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, PTS Granada, Granada, España
| | - Miriam Palma-Vega
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, PTS Granada, Granada, España
| | - Pau Bosch-Nicolau
- Unidad de Medicina Tropical y Salud Internacional Hospital UniversitariValld'Hebron, PROSICS, Barcelona, España
| | - María Silvina Lo Presti
- Centro de Estudios e Investigación de la Enfermedad de Chagas y Leishmaniasis, FCM, INICSA-CONICET-UNC, Córdoba, Argentina
| | - Israel Molina
- Unidad de Medicina Tropical y Salud Internacional Hospital UniversitariValld'Hebron, PROSICS, Barcelona, España
| | | | - Javier Martín
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, PTS Granada, Granada, España
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Calfee E, Agra MN, Palacio MA, Ramírez SR, Coop G. Selection and hybridization shaped the rapid spread of African honey bee ancestry in the Americas. PLoS Genet 2020; 16:e1009038. [PMID: 33075065 PMCID: PMC7595643 DOI: 10.1371/journal.pgen.1009038] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 10/29/2020] [Accepted: 08/09/2020] [Indexed: 02/07/2023] Open
Abstract
Recent biological invasions offer 'natural' laboratories to understand the genetics and ecology of adaptation, hybridization, and range limits. One of the most impressive and well-documented biological invasions of the 20th century began in 1957 when Apis mellifera scutellata honey bees swarmed out of managed experimental colonies in Brazil. This newly-imported subspecies, native to southern and eastern Africa, both hybridized with and out-competed previously-introduced European honey bee subspecies. Populations of scutellata-European hybrid honey bees rapidly expanded and spread across much of the Americas in less than 50 years. We use broad geographic sampling and whole genome sequencing of over 300 bees to map the distribution of scutellata ancestry where the northern and southern invasions have presently stalled, forming replicated hybrid zones with European bee populations in California and Argentina. California is much farther from Brazil, yet these hybrid zones occur at very similar latitudes, consistent with the invasion having reached a climate barrier. At these range limits, we observe genome-wide clines for scutellata ancestry, and parallel clines for wing length that span hundreds of kilometers, supporting a smooth transition from climates favoring scutellata-European hybrid bees to climates where they cannot survive winter. We find no large effect loci maintaining exceptionally steep ancestry transitions. Instead, we find most individual loci have concordant ancestry clines across South America, with a build-up of somewhat steeper clines in regions of the genome with low recombination rates, consistent with many loci of small effect contributing to climate-associated fitness trade-offs. Additionally, we find no substantial reductions in genetic diversity associated with rapid expansions nor complete dropout of scutellata ancestry at any individual loci on either continent, which suggests that the competitive fitness advantage of scutellata ancestry at lower latitudes has a polygenic basis and that scutellata-European hybrid bees maintained large population sizes during their invasion. To test for parallel selection across continents, we develop a null model that accounts for drift in ancestry frequencies during the rapid expansion. We identify several peaks within a larger genomic region where selection has pushed scutellata ancestry to high frequency hundreds of kilometers past the present cline centers in both North and South America and that may underlie high-fitness traits driving the invasion.
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Affiliation(s)
- Erin Calfee
- Center for Population Biology, University of California, Davis, California, United States of America
- Department of Evolution and Ecology, University of California, Davis, California, United States of America
| | | | - María Alejandra Palacio
- Instituto Nacional de Tecnología Agropecuaria (INTA), Balcarce, Argentina
- Facultad de Ciencias Agrarias, Universidad de Mar del Plata, Balcarce, Argentina
| | - Santiago R. Ramírez
- Center for Population Biology, University of California, Davis, California, United States of America
- Department of Evolution and Ecology, University of California, Davis, California, United States of America
| | - Graham Coop
- Center for Population Biology, University of California, Davis, California, United States of America
- Department of Evolution and Ecology, University of California, Davis, California, United States of America
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Raffield LM, Lu AT, Szeto MD, Little A, Grinde KE, Shaw J, Auer PL, Cushman M, Horvath S, Irvin MR, Lange EM, Lange LA, Nickerson DA, Thornton TA, Wilson JG, Wheeler MM, Zakai NA, Reiner AP. Coagulation factor VIII: Relationship to cardiovascular disease risk and whole genome sequence and epigenome-wide analysis in African Americans. J Thromb Haemost 2020; 18:1335-1347. [PMID: 31985870 PMCID: PMC7274883 DOI: 10.1111/jth.14741] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 01/02/2020] [Accepted: 01/21/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Prospective studies have suggested higher factor VIII (FVIII) levels are an independent risk factor for coronary heart disease (CHD) and stroke. However, limited information, including on genetic and epigenetic contributors to FVIII variation, is available specifically among African Americans (AAs), who have higher FVIII levels than Europeans. OBJECTIVES We measured FVIII levels in ~3400 AAs from the community-based Jackson Heart Study and assessed genetic, epigenetic, and epidemiological correlates of FVIII, as well as incident cardiovascular disease (CVD) associations. METHODS We assessed cross-sectional associations of FVIII with CVD risk factors as well as incident CHD, stroke, heart failure, and mortality associations. We additionally assessed associations with TOPMed whole genome sequencing data and an epigenome-wide methylation array. RESULTS Our results confirmed associations between FVIII and risk of incident CHD events and total mortality in AAs; mortality associations were largely independent of traditional risk factors. We also demonstrate an association of FVIII with incident heart failure, independent of B-type natriuretic peptide. Two genomic regions were strongly associated with FVIII (ABO and VWF). The index variant at VWF is specific to individuals of African descent and is distinct from the previously reported European VWF association signal. Epigenome-wide association analysis showed significant FVIII associations with several CpG sites in the ABO region. However, after adjusting for ABO genetic variants, ABO CpG sites were not significant. CONCLUSIONS Larger sample sizes of AAs will be required to discover additional genetic and epigenetic contributors to FVIII phenotypic variation, which may have consequences for CVD health disparities.
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Affiliation(s)
- Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Mindy D Szeto
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, Colorado
| | - Amarise Little
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Kelsey E Grinde
- Department of Mathematics, Statistics, and Computer Science, Macalester College, St. Paul, Minnesota
| | - Jessica Shaw
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, Colorado
| | - Paul L Auer
- Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont
- Department of Pathology & Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, California
- Department of Biostatistics, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham (UAB) School of Public Health, Birmingham, Alabama
| | - Ethan M Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, Colorado
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, Colorado
| | | | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi
| | | | - Neil A Zakai
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont
- Department of Pathology & Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, Washington
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Strauss M, Acosta-Herrera M, Alcaraz A, Casares-Marfil D, Bosch-Nicolau P, Lo Presti MS, Molina I, González CI, Martín J. Association of IL18 genetic polymorphisms with Chagas disease in Latin American populations. PLoS Negl Trop Dis 2019; 13:e0007859. [PMID: 31751351 PMCID: PMC6894881 DOI: 10.1371/journal.pntd.0007859] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 12/05/2019] [Accepted: 10/21/2019] [Indexed: 12/14/2022] Open
Abstract
Host genetic factors have been suggested to play an important role in the susceptibility to Chagas disease. Given the influence of interleukin 18 (IL-18) in the development of the disease, in the present study, we analyzed three IL18 genetic variants (rs2043055, rs1946518, rs360719) regarding the predisposition to Trypanosoma cruzi infection and the development of chronic Chagas cardiomyopathy (CCC), in different Latin America populations. Genetic data of 3,608 patients from Colombia, Bolivia, Argentina, and Brazil were meta-analyzed to validate previous findings with increased statistical power. Seropositive and seronegative individuals were compared for T. cruzi infection susceptibility. In the Colombian cohort, the allelic frequencies of the three variants showed a significant association, with adjustment for sex and age, and also after applying multiple testing adjustments. Among the Colombian and Argentinean cohorts, rs360719 showed a significant genetic effect in a fixed-effects meta-analysis after a Bonferroni correction (OR: 0.76, CI: 0.66-0.89, P = 0.001). For CCC, the rs2043055 showed an association with protection from cardiomyopathy in the Colombian cohort (OR: 0.79, CI: 0.64-0.99, P = 0.037), with adjustment for sex and age, and after applying multiple testing adjustments. The meta-analysis of the CCC vs. asymptomatic patients from the four cohorts showed no evidence of association. In conclusion, our results validated the association found previously in the Colombian cohort suggesting that IL18 rs360719 plays an important role in the susceptibility to T. cruzi infection and no evidence of association was found between the IL18 genetic variants and CCC in the Latin American population studied.
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Affiliation(s)
- Mariana Strauss
- Centro de Estudios e Investigación de la Enfermedad de Chagas y Leishmaniasis, FCM, INICSA-CONICET-UNC, Córdoba, Argentina
| | | | - Alexia Alcaraz
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, PTS Granada, Granada, España
| | - Desiré Casares-Marfil
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, PTS Granada, Granada, España
| | - Pau Bosch-Nicolau
- Unidad de Medicina Tropical y Salud Internacional Hospital Universitari Vall d'Hebron, PROSICS, Barcelona, España
| | - María Silvina Lo Presti
- Centro de Estudios e Investigación de la Enfermedad de Chagas y Leishmaniasis, FCM, INICSA-CONICET-UNC, Córdoba, Argentina
| | - Israel Molina
- Unidad de Medicina Tropical y Salud Internacional Hospital Universitari Vall d'Hebron, PROSICS, Barcelona, España
| | | | - Javier Martín
- Instituto de Parasitología y Biomedicina López-Neyra, IPBLN-CSIC, PTS Granada, Granada, España
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