1
|
Yang X, Cheng B, Cheng S, Liu L, Pan C, Meng P, Li C, Chen Y, Zhang J, Zhang H, Zhang Z, Wen Y, Jia Y, Liu H, Zhang F. A genome-wide association study identifies candidate genes for sleep disturbances in depressed individuals. Hum Genomics 2024; 18:51. [PMID: 38778419 PMCID: PMC11110369 DOI: 10.1186/s40246-024-00609-5] [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: 10/06/2023] [Accepted: 04/15/2024] [Indexed: 05/25/2024] Open
Abstract
OBJECTIVE This study aimed to identify candidate loci and genes related to sleep disturbances in depressed individuals and clarify the co-occurrence of sleep disturbances and depression from the genetic perspective. METHODS The study subjects (including 58,256 self-reported depressed individuals and 6,576 participants with PHQ-9 score ≥ 10, respectively) were collected from the UK Biobank, which were determined based on the Patient Health Questionnaire (PHQ-9) and self-reported depression status, respectively. Sleep related traits included chronotype, insomnia, snoring and daytime dozing. Genome-wide association studies (GWASs) of sleep related traits in depressed individuals were conducted by PLINK 2.0 adjusting age, sex, Townsend deprivation index and 10 principal components as covariates. The CAUSALdb database was used to explore the mental traits associated with the candidate genes identified by the GWAS. RESULTS GWAS detected 15 loci significantly associated with chronotype in the subjects with self-reported depression, such as rs12736689 at RNASEL (P = 1.00 × 10- 09), rs509476 at RGS16 (P = 1.58 × 10- 09) and rs1006751 at RFX4 (P = 1.54 × 10- 08). 9 candidate loci were identified in the subjects with PHQ-9 ≥ 10, of which 2 loci were associated with insomnia such as rs115379847 at EVC2 (P = 3.50 × 10- 08), and 7 loci were associated with daytime dozing, such as rs140876133 at SMYD3 (P = 3.88 × 10- 08) and rs139156969 at ROBO2 (P = 3.58 × 10- 08). Multiple identified genes, such as RNASEL, RGS16, RFX4 and ROBO2 were reported to be associated with chronotype, depression or cognition in previous studies. CONCLUSION Our study identified several candidate genes related to sleep disturbances in depressed individuals, which provided new clues for understanding the biological mechanism underlying the co-occurrence of depression and sleep disorders.
Collapse
Affiliation(s)
- Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Chun'e Li
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yujing Chen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Jingxi Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Huijie Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Zhen Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Huan Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
| |
Collapse
|
2
|
Winkler SS, Tian C, Casablanca Y, Bateman NW, Jokajtys S, Kucera CW, Tarney CM, Chan JK, Richardson MT, Kapp DS, Liao CI, Hamilton CA, Leath CA, Reddy M, Cote ML, O'Connor TD, Jones NL, Rocconi RP, Powell MA, Farley J, Shriver CD, Conrads TP, Phippen NT, Maxwell GL, Darcy KM. Racial, ethnic and country of origin disparities in aggressive endometrial cancer histologic subtypes. Gynecol Oncol 2024; 184:31-42. [PMID: 38277919 DOI: 10.1016/j.ygyno.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/22/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024]
Abstract
OBJECTIVE This study investigated the risk of an aggressive endometrial cancer (EC) diagnosis by race, ethnicity, and country of origin to further elucidate histologic disparities in non-Hispanic Black (NHB), Hispanic, Asian/Pacific Islander (API), American Indian/Alaskan Native (AIAN) vs. non-Hispanic White (NHW) patients, particularly in Hispanic or API subgroups. METHODS Patient diagnosed between 2004 and 2020 with low grade (LG)-endometrioid endometrial cancer (ECC) or an aggressive EC including grade 3 EEC, serous carcinoma, clear cell carcinoma, mixed epithelial carcinoma, or carcinosarcoma in the National Cancer Database were studied. The odds ratio (OR) and 95% confidence interval (CI) for diagnosis of an aggressive EC histology was estimated using logistic modeling. RESULTS There were 343,868 NHW, 48,897 NHB, 30,013 Hispanic, 15,015 API and 1646 AIAN patients. The OR (95% CI) for an aggressive EC diagnosis was 3.07 (3.01-3.13) for NHB, 1.08 (1.06-1.11) for Hispanic, 1.17 (1.13-1.21) for API and 1.07 (0.96-1.19) for AIAN, relative to NHW patients. Subset analyses by country of origin illustrated the diversity in the OR for an aggressive EC diagnosis among Hispanic (1.18 for Mexican to 1.87 for Dominican), Asian (1.14 Asian Indian-Pakistani to 1.48 Korean) and Pacific Islander (1.00 for Hawaiian to 1.33 for Samoan) descendants. Hispanic, API and AIAN patients were diagnosed 5-years younger that NHW patients, and the risk for an aggressive EC histology were all significantly higher than NHW patients after correcting for age. Insurance status was another independent risk factor for aggressive histology. CONCLUSIONS Risk of an aggressive EC diagnosis varied by race, ethnicity, and country of origin. NHB patients had the highest risk, followed by Dominican, South/Central American, Cuban, Korean, Thai, Vietnamese, and Filipino descendants.
Collapse
Affiliation(s)
- Stuart S Winkler
- Division of Gynecologic Oncology, Department of Gynecologic Surgery and Obstetrics, Brooke Army Medical Center, San Antonio, TX, USA
| | - Chunqiao Tian
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD, USA
| | - Yovanni Casablanca
- Division of Gynecologic Oncology, Levine Cancer Institute, Atrium Health, Charlotte, NC, USA
| | - Nicholas W Bateman
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD, USA
| | - Suzanne Jokajtys
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Calen W Kucera
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Christopher M Tarney
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - John K Chan
- Palo Alto Medical Foundation, California Pacific Medical Center, Sutter Health, San Francisco, CA, USA
| | - Michael T Richardson
- Department of Obstetrics and Gynecology, University of California, Los Angeles School of Medicine, Los Angeles, CA. USA
| | - Daniel S Kapp
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | - Cheng-I Liao
- Division of Obstetrics and Gynecology, Pingtung Veterans General Hospital, Pingtung, Taiwan
| | - Chad A Hamilton
- Gynecologic Oncology Section, Women's Services and The Ochsner Cancer Institute, Ochsner Health, New Orleans, LA, USA
| | - Charles A Leath
- Division of Gynecologic Oncology, University of Alabama at Birmingham, O'Neal Comprehensive Cancer Center, Birmingham, AL, USA
| | - Megan Reddy
- California Pacific Medical Center, San Francisco, CA, USA
| | - Michele L Cote
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indiana University, Indianapolis, IN, USA
| | - Timothy D O'Connor
- Institute for Genome Sciences, Department of Medicine, Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, MD, USA
| | - Nathaniel L Jones
- Division of Gynecologic Oncology, Mitchell Cancer Institute, University of South Alabama, Mobile, AL, USA
| | - Rodney P Rocconi
- Division of Gynecologic Oncology, Cancer Center & Research Institute, The University of Mississippi Medical Center, Jackson, MS, USA
| | - Matthew A Powell
- Division of Gynecologic Oncology, Siteman Cancer Center, Washington University, St Louis, MO, USA
| | - John Farley
- Division of Gynecologic Oncology, Center for Women's Health, Cancer Institute, Dignity Health St. Joseph's Hospital and Medical Center, Phoenix, AZ, USA
| | - Craig D Shriver
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Thomas P Conrads
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Women's Health Integrated Research Center, Women's Service Line, Inova Health System, Falls Church, VA, USA
| | - Neil T Phippen
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - G Larry Maxwell
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Women's Health Integrated Research Center, Women's Service Line, Inova Health System, Falls Church, VA, USA
| | - Kathleen M Darcy
- Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, MD, USA; The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD, USA.
| |
Collapse
|
3
|
Joshi PH, Marcovina S, Orroth K, López JAG, Kent ST, Kaplan R, Swett K, Sotres-Alvarez D, Thyagarajan B, Slipczuk L, Sofer T, Daviglus ML, Talavera GA, Schneiderman N, Rodriguez CJ. Heterogeneity of Lipoprotein(a) Levels Among Hispanic or Latino Individuals Residing in the US. JAMA Cardiol 2023; 8:691-696. [PMID: 37223894 PMCID: PMC10209825 DOI: 10.1001/jamacardio.2023.1134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 03/29/2023] [Indexed: 05/25/2023]
Abstract
Importance Lipoprotein(a) (Lp[a]) is a genetically determined risk-enhancing factor for atherosclerotic cardiovascular disease (ASCVD). The Lp(a) distribution among the diverse Hispanic or Latino community residing in the US has not been previously described, to the authors' knowledge. Objective To determine the distribution of Lp(a) levels across a large cohort of diverse Hispanic or Latino adults living in the US and by key demographic groups. Design, Setting, and Participants The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a prospective, population-based, cohort study of diverse Hispanic or Latino adults living in the US. At screening, participants aged 18 to 74 years were recruited between 2008 and 2011 from 4 US metropolitan areas (Bronx, New York; Chicago, Illinois; Miami, Florida; San Diego, California). HCHS/SOL included 16 415 noninstitutionalized adults recruited through probability sampling of randomly selected households. The study population represents Hispanic or Latino participants from diverse self-identified geographic and cultural backgrounds: Central American, Cuban, Dominican, Mexican, Puerto Rican, and South American. This study evaluated a subset of HCHS/SOL participants who underwent Lp(a) measurement. Sampling weights and surveys methods were used to account for HCHS/SOL sampling design. Data for this study were analyzed from April 2021 to April 2023. Exposure Lp(a) molar concentration was measured by a particle-enhanced turbidimetric assay with minimized sensitivity to apolipoprotein(a) size variation. Main Outcome and Measure Lp(a) quintiles were compared using analysis of variance among key demographic groups, including self-identified Hispanic or Latino background. Median percentage genetic ancestry (Amerindian, European, West African) were compared across Lp(a) quintiles. Results Lp(a) molar concentration was measured in 16 117 participants (mean [SD] age, 41 [14.8] years; 9680 female [52%]; 1704 Central American [7.7%], 2313 Cuban [21.1%], 1436 Dominican [10.3%], 6395 Mexican [39.1%], 2652 Puerto Rican [16.6%], 1051 South American [5.1%]). Median (IQR) Lp(a) level was 19.7 (7.4-59.7) nmol/L. Across Hispanic or Latino background groups, there was significant heterogeneity in median Lp(a) levels ranging from 12 to 41 nmol/L in those reporting a Mexican vs Dominican background. Median (IQR) West African genetic ancestry was lowest in the first quintile of Lp(a) level and highest in the fifth quintile (5.5% [3.4%-12.9%] and 12.1% [5.0%-32.5%]; respectively; P < .001), whereas the converse was seen for Amerindian ancestry (32.8% [9.9%-53.2%] and 10.7% [4.9%-30.7%], respectively; P < .001). Conclusions and Relevance Results of this cohort study suggest that differences in Lp(a) level distribution across the diverse US Hispanic or Latino population may carry important implications for the use of Lp(a) level in ASCVD risk assessment for this group. Cardiovascular outcomes data are needed to better understand the clinical impact of differences in Lp(a) levels by Hispanic or Latino background.
Collapse
Affiliation(s)
- Parag H. Joshi
- Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas
| | | | - Kate Orroth
- Center for Observational Research, Amgen Inc, Thousand Oaks, California
| | | | - Shia T. Kent
- Center for Observational Research, Amgen Inc, Thousand Oaks, California
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, New York
| | - Katrina Swett
- Department of Medicine (Cardiology), Albert Einstein College of Medicine, New York, New York
| | | | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Leandro Slipczuk
- Department of Medicine (Cardiology), Albert Einstein College of Medicine, New York, New York
| | - Tamar Sofer
- Department of Biostatistics, Harvard Medical School, Boston, Massachusetts
| | | | | | | | - Carlos J. Rodriguez
- Department of Medicine (Cardiology), Albert Einstein College of Medicine, New York, New York
| |
Collapse
|
4
|
Khan AT, Gogarten SM, McHugh CP, Stilp AM, Sofer T, Bowers ML, Wong Q, Cupples LA, Hidalgo B, Johnson AD, McDonald MLN, McGarvey ST, Taylor MR, Fullerton SM, Conomos MP, Nelson SC. Recommendations on the use and reporting of race, ethnicity, and ancestry in genetic research: Experiences from the NHLBI TOPMed program. CELL GENOMICS 2022; 2:100155. [PMID: 36119389 PMCID: PMC9481067 DOI: 10.1016/j.xgen.2022.100155] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
How race, ethnicity, and ancestry are used in genomic research has wide-ranging implications for how research is translated into clinical care and incorporated into public understanding. Correlation between race and genetic ancestry contributes to unresolved complexity for the scientific community, as illustrated by heterogeneous definitions and applications of these variables. Here, we offer commentary and recommendations on the use of race, ethnicity, and ancestry across the arc of genetic research, including data harmonization, analysis, and reporting. While informed by our experiences as researchers affiliated with the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, these recommendations are applicable to basic and translational genomic research in diverse populations with genome-wide data. Moving forward, considerable collaborative effort will be required to ensure that race, ethnicity, and ancestry are described and used appropriately to generate scientific knowledge that yields broad and equitable benefit.
Collapse
Affiliation(s)
- Alyna T. Khan
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | | | - Caitlin P. McHugh
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Tamar Sofer
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Michael L. Bowers
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Quenna Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Bertha Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Andrew D. Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Merry-Lynn N. McDonald
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Stephen T. McGarvey
- Department of Epidemiology and International Health Institute, Brown University School of Public Health, Providence, RI, USA
- Department of Anthropology, Brown University, Providence, RI, USA
| | - Matthew R.G. Taylor
- Department of Medicine, Adult Medical Genetics Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | | | - Sarah C. Nelson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| |
Collapse
|
5
|
Chew NW, Chong B, Ng CH, Kong G, Chin YH, Xiao W, Lee M, Dan YY, Muthiah MD, Foo R. The genetic interactions between non-alcoholic fatty liver disease and cardiovascular diseases. Front Genet 2022; 13:971484. [PMID: 36035124 PMCID: PMC9399730 DOI: 10.3389/fgene.2022.971484] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 07/19/2022] [Indexed: 12/03/2022] Open
Abstract
The ongoing debate on whether non-alcoholic fatty liver disease (NAFLD) is an active contributor or an innocent bystander in the development of cardiovascular disease (CVD) has sparked interests in understanding the common mediators between the two biologically distinct entities. This comprehensive review identifies and curates genetic studies of NAFLD overlapping with CVD, and describes the colinear as well as opposing correlations between genetic associations for the two diseases. Here, CVD described in relation to NAFLD are coronary artery disease, cardiomyopathy and atrial fibrillation. Unique findings of this review included certain NAFLD susceptibility genes that possessed cardioprotective properties. Moreover, the complex interactions of genetic and environmental risk factors shed light on the disparity in genetic influence on NAFLD and its incident CVD. This serves to unravel NAFLD-mediated pathways in order to reduce CVD events, and helps identify targeted treatment strategies, develop polygenic risk scores to improve risk prediction and personalise disease prevention.
Collapse
Affiliation(s)
- Nicholas W.S. Chew
- Department of Cardiology, National University Heart Centre, Singapore, Singapore
- *Correspondence: Nicholas W.S. Chew, ; Roger Foo,
| | - Bryan Chong
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Cheng Han Ng
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Gwyneth Kong
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Yip Han Chin
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Wang Xiao
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Cardiovascular Disease Translational Research Programme, National University Health Systems, Singapore, Singapore
- Genome Institute of Singapore, Agency of Science Technology and Research, Bipolis way, Singapore
| | - Mick Lee
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Cardiovascular Disease Translational Research Programme, National University Health Systems, Singapore, Singapore
- Genome Institute of Singapore, Agency of Science Technology and Research, Bipolis way, Singapore
| | - Yock Young Dan
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, Singapore, Singapore
- National University Centre for Organ Transplantation, National University Health System, Singapore, Singapore
| | - Mark D. Muthiah
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, Singapore, Singapore
- National University Centre for Organ Transplantation, National University Health System, Singapore, Singapore
| | - Roger Foo
- Department of Cardiology, National University Heart Centre, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Cardiovascular Disease Translational Research Programme, National University Health Systems, Singapore, Singapore
- Genome Institute of Singapore, Agency of Science Technology and Research, Bipolis way, Singapore
- *Correspondence: Nicholas W.S. Chew, ; Roger Foo,
| |
Collapse
|
6
|
Hsu YW, Wong HSC, Huang WC, Yeh YH, Hsiao CD, Chang WC, Hsieh SL. Human rs75776403 polymorphism links differential phenotypic and clinical outcomes to a CLEC18A p.T151M-driven multiomics. J Biomed Sci 2022; 29:43. [PMID: 35717171 PMCID: PMC9206359 DOI: 10.1186/s12929-022-00822-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 06/03/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Human traits, diseases susceptibility, and clinical outcomes vary hugely among individuals. Despite a fundamental understanding of genetic (or environmental) contributions, the detailed mechanisms of how genetic variation impacts molecular or cellular behaviours of a gene, and subsequently leads to such variability remain poorly understood. METHODS Here, in addition to phenome-wide correlations, we leveraged multiomics to exploit mechanistic links, from genetic polymorphism to protein structural or functional changes and a cross-omics perturbation landscape of a germline variant. RESULTS We identified a missense cis-acting expression quantitative trait locus in CLEC18A (rs75776403) in which the altered residue (T151→M151) disrupts the lipid-binding ability of the protein domain. The altered allele carriage led to a metabolic and proliferative shift, as well as immune deactivation, therefore determines human anthropometrics (body height), kidney, and hematological traits. CONCLUSIONS Collectively, we uncovered genetic pleiotropy in human complex traits and diseases via CLEC18A rs75776403-regulated pathways.
Collapse
Affiliation(s)
- Yu-Wen Hsu
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei, Taiwan
| | - Henry Sung-Ching Wong
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan
| | - Wan-Chen Huang
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei, Taiwan.,Institute of Medical Device and Imaging, National Taiwan University, Taipei, Taiwan
| | - Yi-Hung Yeh
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | | | - Wei-Chiao Chang
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan. .,Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan. .,Integrative Research Center in Critical Care, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.
| | - Shie-Liang Hsieh
- Genomics Research Center, Academia Sinica, Taipei, Taiwan. .,Institute of Clinical Medicine, National Yang Ming Chiao Tung University School of Medicine, Taipei, Taiwan. .,Department of Medical Research and Education, Taipei Veterans General Hospital, Taipei, Taiwan. .,Graduate of Institute of Cancer Biology and Drug Discovery, Taipei Medical University, Taipei, Taiwan.
| |
Collapse
|
7
|
Fernández-Rhodes L, Graff M, Buchanan VL, Justice AE, Highland HM, Guo X, Zhu W, Chen HH, Young KL, Adhikari K, Palmer ND, Below JE, Bradfield J, Pereira AC, Glover L, Kim D, Lilly AG, Shrestha P, Thomas AG, Zhang X, Chen M, Chiang CW, Pulit S, Horimoto A, Krieger JE, Guindo-Martínez M, Preuss M, Schumann C, Smit RA, Torres-Mejía G, Acuña-Alonzo V, Bedoya G, Bortolini MC, Canizales-Quinteros S, Gallo C, González-José R, Poletti G, Rothhammer F, Hakonarson H, Igo R, Adler SG, Iyengar SK, Nicholas SB, Gogarten SM, Isasi CR, Papnicolaou G, Stilp AM, Qi Q, Kho M, Smith JA, Langefeld CD, Wagenknecht L, Mckean-Cowdin R, Gao XR, Nousome D, Conti DV, Feng Y, Allison MA, Arzumanyan Z, Buchanan TA, Ida Chen YD, Genter PM, Goodarzi MO, Hai Y, Hsueh W, Ipp E, Kandeel FR, Lam K, Li X, Nadler JL, Raffel LJ, Roll K, Sandow K, Tan J, Taylor KD, Xiang AH, Yao J, Audirac-Chalifour A, de Jesus Peralta Romero J, Hartwig F, Horta B, Blangero J, Curran JE, Duggirala R, Lehman DE, Puppala S, Fejerman L, John EM, Aguilar-Salinas C, Burtt NP, Florez JC, García-Ortíz H, González-Villalpando C, Mercader J, Orozco L, Tusié-Luna T, Blanco E, Gahagan S, Cox NJ, Hanis C, Butte NF, Cole SA, Comuzzie AG, Voruganti VS, Rohde R, Wang Y, Sofer T, Ziv E, Grant SF, Ruiz-Linares A, Rotter JI, Haiman CA, Parra EJ, Cruz M, Loos RJ, North KE. Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium. HGG ADVANCES 2022; 3:100099. [PMID: 35399580 PMCID: PMC8990175 DOI: 10.1016/j.xhgg.2022.100099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 03/06/2022] [Indexed: 02/05/2023] Open
Abstract
Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.
Collapse
Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Biobehavioral Health, Pennsylvania State University, 219 Biobehavioral Health Building, University Park, PA 16802, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Victoria L. Buchanan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Anne E. Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, PA 17822, USA
| | - Heather M. Highland
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Wanying Zhu
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Kristin L. Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, MK7 6AA Milton Keynes, UK
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Jennifer E. Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jonathan Bradfield
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alexandre C. Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - LáShauntá Glover
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Daeeun Kim
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Adam G. Lilly
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Poojan Shrestha
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Alvin G. Thomas
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xinruo Zhang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Minhui Chen
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Charleston W.K. Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90007, USA
| | - Sara Pulit
- Vertex Pharmaceuticals, W2 6BD Oxford, UK
| | - Andrea Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - Jose E. Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - Marta Guindo-Martínez
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Novo Nordisk Center for Basic Metabolic Research, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Michael Preuss
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Claudia Schumann
- Hasso Plattner Institute, University of Potsdam, Digital Health Center, 14482 Potsdam, Germany
| | - Roelof A.J. Smit
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gabriela Torres-Mejía
- Department of Research in Cardiovascular Diseases, Diabetes Mellitus, and Cancer, Population Health Research Center, National Institute of Public Health, Cuernavaca, Morelos 62100, Mexico
| | | | - Gabriel Bedoya
- Molecular Genetics Investigation Group, University of Antioquia, Medellín 1226, Colombia
| | - Maria-Cátira Bortolini
- Department of Genetics, Federal University of Rio Grande do Sul, Porto Alegre 90040-060, Brazil
| | - Samuel Canizales-Quinteros
- Population Genomics Applied to Health Unit, The National Institute of Genomic Medicine and the Faculty of Chemistry at the National Autonomous University of Mexico, Mexico City 04510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | - Rolando González-José
- Patagonian Institute of the Social and Human Sciences, Patagonian National Center, Puerto Madryn U9120, Argentina
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | | | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Robert Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Sharon G. Adler
- Division of Nephrology and Hypertension, Harbor-University of California Los Angeles Medical Center, Torrance, CA 90502, USA
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Susanne B. Nicholas
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA
| | | | - Carmen R. Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | | | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Carl D. Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Lynne Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Roberta Mckean-Cowdin
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Xiaoyi Raymond Gao
- Department of Ophthalmology and Visual Sciences, Department of Biomedical Informatics, Division of Human Genetics, The Ohio State University, Columbus, OH 43210, USA
| | - Darryl Nousome
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - David V. Conti
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Ye Feng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Matthew A. Allison
- Department of Family Medicine, University of California, San Diego, CA 92161, USA
| | - Zorayr Arzumanyan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Thomas A. Buchanan
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Pauline M. Genter
- Department of Medicine, Division of Endocrinology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Yang Hai
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Willa Hsueh
- Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA
| | - Eli Ipp
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA
- Department of Medicine, Division of Endocrinology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Fouad R. Kandeel
- Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Kelvin Lam
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Jerry L. Nadler
- Department of Pharmacology at New York Medical College School of Medicine, Valhalla, NY 10595, USA
| | - Leslie J. Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, CA 92697, USA
| | - Kathryn Roll
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Kevin Sandow
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Anny H. Xiang
- Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, CA 91101, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Astride Audirac-Chalifour
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Jose de Jesus Peralta Romero
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Fernando Hartwig
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - Bernando Horta
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Donna E. Lehman
- Department of Medicine, School of Medicine, University of Texas Health San Antonio, San Antonio, TX 78229, USA
| | - Sobha Puppala
- Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27109, USA
| | - Laura Fejerman
- Department of Public Health Sciences, School of Medicine, and the Comprehensive Cancer Center, University of California Davis, Davis, CA 95616, USA
| | - Esther M. John
- Departments of Epidemiology & Population Health and Medicine-Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Carlos Aguilar-Salinas
- Division of Nutrition, Salvador Zubirán National Institute of Health Sciences and Nutrition, Mexico City 14080, Mexico
| | - Noël P. Burtt
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Jose C. Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Humberto García-Ortíz
- Laboratory of Immunogenomics and Metabolic Diseases, National Institute of Genomic Medicine, Mexico City 14610, Mexico
| | - Clicerio González-Villalpando
- Center for Diabetes Studies, Research Unit for Diabetes and Cardiovascular Risk, Center for Population Health Studies, National Institute of Public Health, Mexico City 14080, Mexico
| | - Josep Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Lorena Orozco
- Laboratory of Immunogenomics and Metabolic Diseases, National Institute of Genomic Medicine, Mexico City 14610, Mexico
| | - Teresa Tusié-Luna
- Molecular Biology and Medical Genomics Unity, Institute of Biomedical Research, The National Autonomous University of Mexico and the Salvador Zubirán National Institute of Health Sciences and Nutrition, Mexico City 14080, Mexico
| | - Estela Blanco
- Center for Community Health, Division of Academic General Pediatrics, University of California at San Diego, San Diego, CA 92093, USA
| | - Sheila Gahagan
- Center for Community Health, Division of Academic General Pediatrics, University of California at San Diego, San Diego, CA 92093, USA
| | - Nancy J. Cox
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Craig Hanis
- University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Nancy F. Butte
- United States Department of Agriculture, Agricultural Research Service, The Children’s Nutrition Research Center, and the Department Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Shelley A. Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | | | - V. Saroja Voruganti
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yujie Wang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tamar Sofer
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, Helen Diller Family Comprehensive Cancer Center, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94115, USA
| | - Struan F.A. Grant
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Andres Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai 200438, China
- Department of Genetics, Evolution and Environment, and Genetics Institute of the University College London, London WC1E 6BT, UK
- Laboratory of Biocultural Anthropology, Law, Ethics, and Health, Aix-Marseille University, Marseille 13385, France
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto- Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Ruth J.F. Loos
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| |
Collapse
|
8
|
Levine DA, Gross AL, Briceño EM, Tilton N, Whitney R, Han D, Giordani BJ, Sussman JB, Hayward RA, Burke JF, Elkind MS, Moran AE, Tom S, Gottesman RF, Gaskin DJ, Sidney S, Yaffe K, Sacco RL, Heckbert SR, Hughes TM, Lopez OL, Allen NB, Galecki AT. Blood Pressure and Later-Life Cognition in Hispanic and White Adults (BP-COG): A Pooled Cohort Analysis of ARIC, CARDIA, CHS, FOS, MESA, and NOMAS. J Alzheimers Dis 2022; 89:1103-1117. [PMID: 35964190 PMCID: PMC10041434 DOI: 10.3233/jad-220366] [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] [Accepted: 07/23/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Ethnic differences in cognitive decline have been reported. Whether they can be explained by differences in systolic blood pressure (SBP) is uncertain. OBJECTIVE Determine whether cumulative mean SBP levels explain differences in cognitive decline between Hispanic and White individuals. METHODS Pooled cohort study of individual participant data from six cohorts (1971-2017). The present study reports results on SBP and cognition among Hispanic and White individuals. Outcomes were changes in global cognition (GC) (primary), executive function (EF) (secondary), and memory standardized as t-scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1 SD difference in cognition. Median follow-up was 7.7 (Q1-Q3, 5.2-20.1) years. RESULTS We included 24,570 participants free of stroke and dementia: 2,475 Hispanic individuals (median age, cumulative mean SBP at first cognitive assessment, 67 years, 132.5 mmHg; 40.8% men) and 22,095 White individuals (60 years,134 mmHg; 47.3% men). Hispanic individuals had slower declines in GC, EF, and memory than White individuals when all six cohorts were examined. Two cohorts recruited Hispanic individuals by design. In a sensitivity analysis, Hispanic individuals in these cohorts had faster decline in GC, similar decline in EF, and slower decline in memory than White individuals. Higher time-varying cumulative mean SBP was associated with faster declines in GC, EF, and memory in all analyses. After adjusting for time-varying cumulative mean SBP, differences in cognitive slopes between Hispanic and White individuals did not change. CONCLUSION We found no evidence that cumulative mean SBP differences explained differences in cognitive decline between Hispanic and White individuals.
Collapse
Affiliation(s)
- Deborah A. Levine
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
- Department of Neurology and Stroke Program, University of Michigan, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA
| | - Alden L. Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School Public Health, Baltimore, MD, USA
| | - Emily M. Briceño
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
- Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Tilton
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
| | - Rachael Whitney
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
| | - Dehua Han
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
| | - Bruno J. Giordani
- Department of Psychiatry & Michigan Alzheimer’s Disease Center, University of Michigan, Ann Arbor, MI, USA
| | - Jeremy B. Sussman
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA
- VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Rodney A. Hayward
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA
- VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - James F. Burke
- Department of Neurology and Stroke Program, University of Michigan, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA
- VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Mitchell S.V. Elkind
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Andrew E. Moran
- Department of Medicine, Division of General Medicine, Columbia University, New York, NY, USA
| | - Sarah Tom
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Rebecca F. Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD, USA
| | - Darrell J. Gaskin
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Stephen Sidney
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Kristine Yaffe
- Departments of Psychiatry, Neurology and Epidemiology, University of California, San Francisco, San Francisco, CA, USA
| | - Ralph L. Sacco
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Susan R. Heckbert
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Timothy M. Hughes
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Norrina Bai Allen
- Department of Internal Medicine, Northwestern University, Chicago, IL, USA
| | - Andrzej T. Galecki
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| |
Collapse
|
9
|
Shi H, Ossip DJ, Mayo NL, Lopez DA, Block RC, Post WS, Bertoni AG, Ding J, Chen S, Yan C, Xie Z, Hoeschele I, Liu Y, Li D. Role of DNA methylation on the association between physical activity and cardiovascular diseases: results from the longitudinal multi-ethnic study of atherosclerosis (MESA) cohort. BMC Genomics 2021; 22:790. [PMID: 34732130 PMCID: PMC8567593 DOI: 10.1186/s12864-021-08108-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 10/14/2021] [Indexed: 12/03/2022] Open
Abstract
Background The complexity of physical activity (PA) and DNA methylation interaction in the development of cardiovascular disease (CVD) is rarely simultaneously investigated in one study. We examined the role of DNA methylation on the association between PA and CVD. Results The Multi-Ethnic Study of Atherosclerosis (MESA) cohort Exam 5 data with 1065 participants free of CVD were used for final analysis. The quartile categorical total PA variable was created by activity intensity (METs/week). During a median follow-up of 4.0 years, 69 participants developed CVD. Illumina HumanMethylation450 BeadChip was used to provide genome-wide DNA methylation profiles in purified human monocytes (CD14+). We identified 23 candidate DNA methylation loci to be associated with both PA and CVD. We used the structural equation modeling (SEM) approach to test the complex relationships among multiple variables and the roles of mediators. Three of the 23 identified loci (corresponding to genes VPS13D, PIK3CD and VPS45) remained as significant mediators in the final SEM model along with other covariates. Bridged by the three genes, the 2nd PA quartile (β = − 0.959; 95%CI: − 1.554 to − 0.449) and the 3rd PA quartile (β = − 0.944; 95%CI: − 1.628 to − 0.413) showed the greatest inverse associations with CVD development, while the 4th PA quartile had a relatively weaker inverse association (β = − 0.355; 95%CI: − 0.713 to − 0.124). Conclusions The current study is among the first to simultaneously examine the relationships among PA, DNA methylation, and CVD in a large cohort with long-term exposure. We identified three DNA methylation loci bridged the association between PA and CVD. The function of the identified genes warrants further investigation in the pathogenesis of CVD. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08108-w.
Collapse
Affiliation(s)
- Hangchuan Shi
- Department of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, 14642-0708, USA.,Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Deborah J Ossip
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Nicole L Mayo
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Daniel A Lopez
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Robert C Block
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Alain G Bertoni
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Jingzhong Ding
- Department of Medicine, Wake Forest Baptist Medical Center, Winston-Salem, NC, 27157, USA
| | - Si Chen
- Aab Cardiovascular Research Institute, University of Rochester, School of Medicine and Dentistry, Rochester, NY, 14642, USA.,Department of Pharmacology and Physiology, University of Rochester, School of Medicine and Dentistry, Rochester, NY, 14642, USA
| | - Chen Yan
- Aab Cardiovascular Research Institute, University of Rochester, School of Medicine and Dentistry, Rochester, NY, 14642, USA.,Department of Pharmacology and Physiology, University of Rochester, School of Medicine and Dentistry, Rochester, NY, 14642, USA
| | - Zidian Xie
- Department of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, 14642-0708, USA
| | - Ina Hoeschele
- Department of Statistics, Fralin Life Sciences Institute at Virginia Tech, Blacksburg, VA, 24061, USA
| | - Yongmei Liu
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, 27701, USA.
| | - Dongmei Li
- Department of Clinical and Translational Research, University of Rochester Medical Center, Rochester, NY, 14642-0708, USA.
| |
Collapse
|
10
|
Herrando‐Pérez S, Tobler R, Huber CD. smartsnp
, an
r
package for fast multivariate analyses of big genomic data. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13684] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Salvador Herrando‐Pérez
- Australian Centre for Ancient DNA School of Biological Sciences The University of Adelaide Adelaide SA Australia
- Department of Biogeography and Global Change Museo Nacional de Ciencias NaturalesSpanish National Research Council (CSIC) Madrid Spain
| | - Raymond Tobler
- Australian Centre for Ancient DNA School of Biological Sciences The University of Adelaide Adelaide SA Australia
- Evolution of Cultural Diversity Initiative Australian National University Canberra ACT Australia
| | - Christian D. Huber
- Australian Centre for Ancient DNA School of Biological Sciences The University of Adelaide Adelaide SA Australia
- Department of Biology The Pennsylvania State University University Park PA USA
| |
Collapse
|
11
|
Zhang X, Zhang B, Zhang C, Sun G, Sun X. Current Progress in Delineating the Roles of Pseudokinase TRIB1 in Controlling Human Diseases. J Cancer 2021; 12:6012-6020. [PMID: 34539875 PMCID: PMC8425202 DOI: 10.7150/jca.51627] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 08/10/2021] [Indexed: 12/15/2022] Open
Abstract
Tribbles homolog 1 (TRIB1) is a member of the tribbles family of pseudoprotein kinases and is widely expressed in numerous tissues, such as bone marrow, skeletal muscle, liver, heart, and adipose tissue. It is closely associated with acute myeloid leukemia, prostate cancer, and tumor drug resistance, and can interfere with the hematopoietic stem cell cycle, promote tumor cell proliferation, and inhibit apoptosis. Recent studies have shown that TRIB1 can regulate acute and chronic inflammation by affecting the secretion of inflammatory factors, which is closely related to the occurrence of hyperlipidemia and cardiovascular diseases. Given the important biological functions of TRIB1, the reviews published till now are not sufficiently comprehensive. Therefore, this paper reviews the progress in TRIB1 research aimed at exploring its roles in cancer, hyperlipidemia, and cardiovascular disease, and providing a theoretical basis for further studies on the biological roles of TRIB1.
Collapse
Affiliation(s)
- Xuelian Zhang
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100193, China.,Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing 100193, China.,Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing 100193, China.,Key Laboratory of efficacy evaluation of Chinese Medicine against Glyeolipid Metabolism Disorder Disease, State Administration of Traditional Chinese Medicine, Beijing 100193, China
| | - Bin Zhang
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100193, China.,Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing 100193, China.,Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing 100193, China.,Key Laboratory of efficacy evaluation of Chinese Medicine against Glyeolipid Metabolism Disorder Disease, State Administration of Traditional Chinese Medicine, Beijing 100193, China
| | - Chenyang Zhang
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100193, China.,Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing 100193, China.,Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing 100193, China.,Key Laboratory of efficacy evaluation of Chinese Medicine against Glyeolipid Metabolism Disorder Disease, State Administration of Traditional Chinese Medicine, Beijing 100193, China
| | - Guibo Sun
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100193, China.,Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing 100193, China.,Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing 100193, China.,Key Laboratory of efficacy evaluation of Chinese Medicine against Glyeolipid Metabolism Disorder Disease, State Administration of Traditional Chinese Medicine, Beijing 100193, China
| | - Xiaobo Sun
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100193, China.,Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing 100193, China.,Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing 100193, China.,Key Laboratory of efficacy evaluation of Chinese Medicine against Glyeolipid Metabolism Disorder Disease, State Administration of Traditional Chinese Medicine, Beijing 100193, China
| |
Collapse
|
12
|
Impact of Amerind ancestry and FADS genetic variation on omega-3 deficiency and cardiometabolic traits in Hispanic populations. Commun Biol 2021; 4:918. [PMID: 34321601 PMCID: PMC8319323 DOI: 10.1038/s42003-021-02431-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 06/22/2021] [Indexed: 12/31/2022] Open
Abstract
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.
Collapse
|
13
|
Osibogun O, Ogunmoroti O, Mathews L, Okunrintemi V, Tibuakuu M, Michos ED. Greater Acculturation is Associated With Poorer Cardiovascular Health in the Multi-Ethnic Study of Atherosclerosis. J Am Heart Assoc 2021; 10:e019828. [PMID: 33834848 PMCID: PMC8174160 DOI: 10.1161/jaha.120.019828] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Background Greater acculturation is associated with increased risk of cardiovascular disease. However, little is known about the association between acculturation and ideal cardiovascular health (CVH) as measured by the American Heart Association's 7 CVH metrics. We investigated the association between acculturation and ideal CVH among a multi-ethnic cohort of US adults free of clinical cardiovascular disease at baseline. Methods and Results This was a cross-sectional analysis of 6506 men and women aged 45 to 84 years of 4 races/ethnicities. We examined measures of acculturation(birthplace, language spoken at home, and years lived in the United States [foreign-born participants]) by CVH score. Scores of 0 to 8 indicate inadequate, 9 to 10 average and 11 to 14 optimal CVH. We used multivariable regression to examine associations between acculturation and CVH, adjusting for age, sex, race/ethnicity, education, income and health insurance. The mean (SD) age was 62 (10) years, 53% were women, 39% non-Hispanic White-, 26% non-Hispanic Black-, 12% Chinese- and 22% Hispanic-Americans. US-born participants had lower odds of optimal CVH (odds ratio [OR]: 0.63 [0.50-0.79], P<0.001) compared with foreign-born participants. Participants who spoke Chinese and other foreign languages at home had greater odds of optimal CVH compared with those who spoke English (1.91 [1.08-3.36], P=0.03; and 1.65 [1.04-2.63], P=0.03, respectively). Foreign-born participants who lived the longest in the United States had lower odds of optimal CVH (0.62 [0.43-0.91], P=0.02). Conclusions Greater US acculturation was associated with poorer CVH. This finding suggests that the promotion of ideal CVH should be encouraged among immigrant populations since more years lived in the United States was associated with poorer CVH.
Collapse
Affiliation(s)
- Olatokunbo Osibogun
- Department of Epidemiology Robert Stempel College of Public Health and Social Work Florida International University Miami FL
| | - Oluseye Ogunmoroti
- Ciccarone Center for the Prevention of Cardiovascular Disease Johns Hopkins University School of Medicine Baltimore MD.,Division of Cardiology Johns Hopkins University School of Medicine Baltimore MD
| | - Lena Mathews
- Ciccarone Center for the Prevention of Cardiovascular Disease Johns Hopkins University School of Medicine Baltimore MD.,Division of Cardiology Johns Hopkins University School of Medicine Baltimore MD
| | | | - Martin Tibuakuu
- Ciccarone Center for the Prevention of Cardiovascular Disease Johns Hopkins University School of Medicine Baltimore MD.,Division of Cardiology Johns Hopkins University School of Medicine Baltimore MD
| | - Erin D Michos
- Ciccarone Center for the Prevention of Cardiovascular Disease Johns Hopkins University School of Medicine Baltimore MD.,Division of Cardiology Johns Hopkins University School of Medicine Baltimore MD
| |
Collapse
|
14
|
Nahin RL. Pain Prevalence, Chronicity and Impact Within Subpopulations Based on Both Hispanic Ancestry and Race: United States, 2010-2017. THE JOURNAL OF PAIN 2021; 22:826-851. [PMID: 33636375 DOI: 10.1016/j.jpain.2021.02.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 01/22/2021] [Accepted: 02/09/2021] [Indexed: 12/15/2022]
Abstract
We provide national surveillance estimates of pain chronicity, severity and impact in adult subpopulations defined by both Hispanic Ancestry and Race. Data are from 144,434 adults who completed validated questionnaires in the 2010-2017 National Health Interview Survey asking about pain status within the last 3 (N = 84,664) or 6 months (N = 59,770). Multivariable logistic regression was used to assess the relationship between pain and ethnicity/race. Compared to White Puerto Rican participants, White participants with Central/South American and Mexican ancestry had reduced odds of reporting Category 3-4 pain and High-Impact Chronic Pain (HICP), while those of Cuban ancestry had reduced odds of only HICP - eg, White participants with Mexican ancestry had 32% lower odds of having Category 3-4 pain and 50% lower odds of having HICP. While no differences were seen between White Puerto Rican and White Non-Hispanic participants for Category 3-4 pain, White Non-Hispanics had 40% lower odds of reporting HICP. Asian Non-Hispanic and Black Non-Hispanic participants had significantly lower odds of reporting Category 3-4 pain and HICP compared to White Puerto Rican participants, eg, Black Non-Hispanic participants had 26% lower odds off having Category 3-4 pain and 42% lower odds of having HICP. Perspective: By examining pain status in discrete demographic groups based on Hispanic Ancestry and Race, this report further documents substantial difference in health status among underserved populations and provides a baseline for continuing surveillance research on pain, with the eventual goal of eliminating disparities in pain assessment and treatment.
Collapse
Affiliation(s)
- Richard L Nahin
- National Center for Complementary and Integrative Health, National Institutes of Health, Bethesda, Maryland.
| |
Collapse
|
15
|
Hsu S, Hoofnagle AN, Gupta DK, Gutierrez OM, Peralta CA, Shea S, Allen NB, Burke G, Michos ED, Ix JH, Siscovick D, Psaty BM, Watson KE, Kestenbaum B, de Boer IH, Robinson-Cohen C. Race, Ancestry, and Vitamin D Metabolism: The Multi-Ethnic Study of Atherosclerosis. J Clin Endocrinol Metab 2020; 105:dgaa612. [PMID: 32869845 PMCID: PMC7526733 DOI: 10.1210/clinem/dgaa612] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 08/27/2020] [Indexed: 02/06/2023]
Abstract
CONTEXT A comprehensive characterization of racial/ethnic variations in vitamin D metabolism markers may improve our understanding of differences in bone and mineral homeostasis and the risk of vitamin D-related diseases. OBJECTIVE Describe racial/ethnic differences in vitamin D metabolism markers and their associations with genetic ancestry. DESIGN, SETTING, PARTICIPANTS In a cross-sectional study within the Multi-Ethnic Study of Atherosclerosis (MESA), we compared a comprehensive panel of vitamin D metabolism markers across self-reported racial/ethnic groups of Black (N = 1759), White (N = 2507), Chinese (N = 788), and Hispanic (N = 1411). We evaluated associations of proportion African and European ancestry with this panel of markers in Black and Hispanic participants using ancestry informative markers. Latent class analysis evaluated associations between patterns of vitamin D measurements with race/ethnicity. RESULTS Compared with Black participants, White participants had significantly higher serum concentrations of 25-hydroxyvitamin D and fibroblast growth factor-23; lower concentrations of parathyroid hormone and 1,25-dihydroxyvitamin D; circulating vitamin D metabolite ratios suggesting lower CYP27B1 and higher CYP24A1 activity; higher urinary concentrations of calcium and phosphorus with higher urinary fractional excretion of phosphorus; and differences in vitamin D binding globulin haplotypes. Higher percent European ancestry was associated with higher 25-hydroxyvitamin D and lower parathyroid hormone concentrations among Black and Hispanic participants. Latent classes defined by vitamin D measurements reflected these patterns and differed significantly by race/ethnicity and ancestry. CONCLUSIONS Markers of vitamin D metabolism vary significantly by race/ethnicity, may serve to maintain bone and mineral homeostasis across ranges of 25-hydroxyvitamin D production, and be attributable, at least partly, to genetic ancestry.
Collapse
Affiliation(s)
- Simon Hsu
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine, University of Washington, Seattle, Washington
| | - Deepak K Gupta
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Orlando M Gutierrez
- Division of Nephrology, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Carmen A Peralta
- Cricket Health, Inc., San Francisco, California
- The Kidney Health Research Collaborative, San Francisco, California
- University of California, San Francisco, San Francisco, California
| | - Steven Shea
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Norrina B Allen
- Department of Internal Medicine, Northwestern University, Chicago, Illinois
| | - Gregory Burke
- Division of Public Health Sciences Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Erin D Michos
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Joachim H Ix
- Nephrology Section, Veterans Affairs San Diego Healthcare System, San Diego, California
- Division of Nephrology-Hypertension, University of California, San Diego, San Diego, California
| | | | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington, Seattle, Washington
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Karol E Watson
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Bryan Kestenbaum
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Ian H de Boer
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Cassianne Robinson-Cohen
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, Tennessee
| |
Collapse
|
16
|
Zhou Y, Browning BL, Browning SR. Population-Specific Recombination Maps from Segments of Identity by Descent. Am J Hum Genet 2020; 107:137-148. [PMID: 32533945 PMCID: PMC7332656 DOI: 10.1016/j.ajhg.2020.05.016] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 05/20/2020] [Indexed: 12/26/2022] Open
Abstract
Recombination rates vary significantly across the genome, and estimates of recombination rates are needed for downstream analyses such as haplotype phasing and genotype imputation. Existing methods for recombination rate estimation are limited by insufficient amounts of informative genetic data or by high computational cost. We present a method and software, called IBDrecomb, for using segments of identity by descent to infer recombination rates. IBDrecomb can be applied to sequenced population cohorts to obtain high-resolution, population-specific recombination maps. In simulated admixed data, IBDrecomb obtains higher accuracy than admixture-based estimation of recombination rates. When applied to 2,500 simulated individuals, IBDrecomb obtains similar accuracy to a linkage-disequilibrium (LD)-based method applied to 96 individuals (the largest number for which computation is tractable). Compared to LD-based maps, our IBD-based maps have the advantage of estimating recombination rates in the recent past rather than the distant past. We used IBDrecomb to generate new recombination maps for European Americans and for African Americans from TOPMed sequence data from the Framingham Heart Study (1,626 unrelated individuals) and the Jackson Heart Study (2,046 unrelated individuals), and we compare them to LD-based, admixture-based, and family-based maps.
Collapse
Affiliation(s)
- Ying Zhou
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
| | - Brian L Browning
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
| |
Collapse
|
17
|
Differentiation of Hispanic biogeographic ancestry with 80 ancestry informative markers. Sci Rep 2020; 10:7745. [PMID: 32385290 PMCID: PMC7210943 DOI: 10.1038/s41598-020-64245-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 04/03/2020] [Indexed: 11/09/2022] Open
Abstract
Ancestry informative single nucleotide polymorphisms (SNPs) can identify biogeographic ancestry (BGA); however, population substructure and relatively recent admixture can make differentiation difficult in heterogeneous Hispanic populations. Utilizing unrelated individuals from the Genomic Origins and Admixture in Latinos dataset (GOAL, n = 160), we designed an 80 SNP panel (Setser80) that accurately depicts BGA through STRUCTURE and PCA. We compared our Setser80 to the Seldin and Kidd panels via resampling simulations, which models data based on allele frequencies. We incorporated Admixed American 1000 Genomes populations (1000 G, n = 347), into a combined populations dataset to determine robustness. Using multinomial logistic regression (MLR), we compared the 3 panels on the combined dataset and found overall MLR classification accuracies: 93.2% Setser80, 87.9% Seldin panel, 71.4% Kidd panel. Naïve Bayesian classification had similar results on the combined dataset: 91.5% Setser80, 84.7% Seldin panel, 71.1% Kidd panel. Although Peru and Mexico were absent from panel design, we achieved high classification accuracy on the combined populations for Peru (MLR = 100%, naïve Bayes = 98%), and Mexico (MLR = 90%, naïve Bayes = 83.4%) as evidence of the portability of the Setser80. Our results indicate the Setser80 SNP panel can reliably classify BGA for individuals of presumed Hispanic origin.
Collapse
|
18
|
Hatchell KE, Lu Q, Mares JA, Michos ED, Wood AC, Engelman CD. Multi-ethnic analysis shows genetic risk and environmental predictors interact to influence 25(OH)D concentration and optimal vitamin D intake. Genet Epidemiol 2019; 44:208-217. [PMID: 31830327 DOI: 10.1002/gepi.22272] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Revised: 11/27/2019] [Accepted: 11/27/2019] [Indexed: 12/30/2022]
Abstract
25-Hydroxyvitamin D (25(OH)D) concentration is a complex trait with genetic and environmental predictors that may determine how much vitamin D exposure is required to reach optimal concentration. Interactions between continuous measures of a polygenic score (PGS) and vitamin D intake (PGS*intake) or available ultraviolet (UV) radiation (PGS*UV) were evaluated in individuals of African (n = 1,099) or European (n = 8,569) ancestries. Interaction terms and joint effects (main and interaction terms) were tested using one-degree of freedom (1-DF) and 2-DF models, respectively. Models controlled for age, sex, body mass index, cohort, and dietary intake/available UV. In addition, in participants achieving Institute of Medicine (IOM) vitamin D intake recommendations, 25(OH)D was evaluated by level PGS. The 2-DF PGS*intake, 1-DF PGS*UV, and 2-DF PGS*UV results were statistically significant in participants of European ancestry (p = 3.3 × 10-18 , p = 2.1 × 10-2 , and p = 2.4 × 10-19 , respectively), but not in those of African ancestry. In European-ancestry participants reaching IOM vitamin D intake guidelines, the percent of participants achieving adequate 25(OH)D ( >20 ng/ml) increased as genetic risk decreased (72% vs. 89% in highest vs. lowest risk; p = .018). Available UV radiation and vitamin D intake interact with genetics to influence 25(OH)D. Individuals with higher genetic risk may require more vitamin D exposure to maintain optimal 25(OH)D concentrations.
Collapse
Affiliation(s)
- Kathryn E Hatchell
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Julie A Mares
- Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, Wisconsin
| | - Erin D Michos
- Department of Cardiology, Ciccarone Center for the Prevention of Cardiovascular Disease, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Alexis C Wood
- Children's Nutrition Research Center, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas
| | - Corinne D Engelman
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| |
Collapse
|
19
|
Differential admixture, human leukocyte antigen diversity, and hematopoietic cell transplantation in Latin America: challenges and opportunities. Bone Marrow Transplant 2019; 55:496-504. [DOI: 10.1038/s41409-019-0737-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 10/21/2019] [Accepted: 10/22/2019] [Indexed: 12/31/2022]
|
20
|
Hatchell KE, Lu Q, Hebbring SJ, Michos ED, Wood AC, Engelman CD. Ancestry-specific polygenic scores and SNP heritability of 25(OH)D in African- and European-ancestry populations. Hum Genet 2019; 138:1155-1169. [PMID: 31342140 PMCID: PMC7041489 DOI: 10.1007/s00439-019-02049-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Accepted: 07/21/2019] [Indexed: 02/07/2023]
Abstract
Vitamin D inadequacy, assessed by 25-hydroxyvitamin D [25(OH)D], affects around 50% of adults in the United States and is associated with numerous adverse health outcomes. Blood 25(OH)D concentrations are influenced by genetic factors that may determine how much vitamin D intake is required to reach optimal 25(OH)D. Despite large genome-wide association studies (GWASs), only a small portion of the genetic factors contributing to differences in 25(OH)D has been discovered. Therefore, knowledge of a fuller set of genetic factors could be useful for risk prediction of 25(OH)D inadequacy, personalized vitamin D supplementation, and prevention of downstream morbidity and mortality. Using PRSice and weights from published African- and European-ancestry GWAS summary statistics, ancestry-specific polygenic scores (PGSs) were created to capture a more complete set of genetic factors in those of European (n = 9569) or African ancestry (n = 2761) from three cohort studies. The PGS for African ancestry was derived using all input SNPs (a p value cutoff of 1.0) and had an R2 of 0.3%; for European ancestry, the optimal PGS used a p value cutoff of 3.5 × 10-4 in the target/tuning dataset and had an R2 of 1.0% in the validation cohort. Those with highest genetic risk had 25(OH)D that was 2.8-3.0 ng/mL lower than those with lowest genetic risk (p = 0.0463-3.2 × 10-13), requiring an additional 467-500 IU of vitamin D intake to maintain equivalent 25(OH)D. PGSs are a powerful predictive tool that could be leveraged for personalized vitamin D supplementation to prevent the negative downstream effects of 25(OH)D inadequacy.
Collapse
Affiliation(s)
- Kathryn E Hatchell
- Department of Population Health Sciences, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, 53706, USA.
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, 53706, USA
| | - Scott J Hebbring
- Center for Human Genetics, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA
| | - Erin D Michos
- Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Alexis C Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Corinne D Engelman
- Department of Population Health Sciences, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, 53706, USA
| |
Collapse
|
21
|
Genetic Similarity Assessment of Twin-Family Populations by Custom-Designed Genotyping Array. Twin Res Hum Genet 2019; 22:210-219. [PMID: 31379313 DOI: 10.1017/thg.2019.41] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Twin registries often take part in large collaborative projects and are major contributors to genome-wide association (GWA) meta-analysis studies. In this article, we describe genotyping of twin-family populations from Australia, the Midwestern USA (Avera Twin Register), the Netherlands (Netherlands Twin Register), as well as a sample of mothers of twins from Nigeria to assess the extent, if any, of genetic differences between them. Genotyping in all cohorts was done using a custom-designed Illumina Global Screening Array (GSA), optimized to improve imputation quality for population-specific GWA studies. We investigated the degree of genetic similarity between the populations using several measures of population variation with genotype data generated from the GSA. Visualization of principal component analysis (PCA) revealed that the Australian, Dutch and Midwestern American populations exhibit negligible interpopulation stratification when compared to each other, to a reference European population and to globally distant populations. Estimations of fixation indices (FST values) between the Australian, Midwestern American and Netherlands populations suggest minimal genetic differentiation compared to the estimates between each population and a genetically distinct cohort (i.e., samples from Nigeria genotyped on GSA). Thus, results from this study demonstrate that genotype data from the Australian, Dutch and Midwestern American twin-family populations can be reasonably combined for joint-genetic analysis.
Collapse
|
22
|
Interventions to Reduce Ethnic and Racial Disparities in Dyslipidemia Management. CURRENT TREATMENT OPTIONS IN CARDIOVASCULAR MEDICINE 2019; 21:24. [DOI: 10.1007/s11936-019-0725-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
|
23
|
De T, Park CS, Perera MA. Cardiovascular Pharmacogenomics: Does It Matter If You're Black or White? Annu Rev Pharmacol Toxicol 2018; 59:577-603. [PMID: 30296897 DOI: 10.1146/annurev-pharmtox-010818-021154] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Race and ancestry have long been associated with differential risk and outcomes to disease as well as responses to medications. These differences in drug response are multifactorial with some portion associated with genomic variation. The field of pharmacogenomics aims to predict drug response in patients prior to medication administration and to uncover the biological underpinnings of drug response. The field of human genetics has long recognized that genetic variation differs in frequency between ancestral populations, with some single nucleotide polymorphisms found solely in one population. Thus far, most pharmacogenomic studies have focused on individuals of European and East Asian ancestry, resulting in a substantial disparity in the clinical utility of genetic prediction for drug response in US minority populations. In this review, we discuss the genetic factors that underlie variability to drug response and known pharmacogenomic associations and how these differ between populations, with an emphasis on the current knowledge in cardiovascular pharmacogenomics.
Collapse
Affiliation(s)
- Tanima De
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, USA;
| | - C Sehwan Park
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, USA;
| | - Minoli A Perera
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, USA;
| |
Collapse
|
24
|
He Z, Lee S, Zhang M, Smith JA, Guo X, Palmas W, Kardia SL, Ionita-Laza I, Mukherjee B. Rare-variant association tests in longitudinal studies, with an application to the Multi-Ethnic Study of Atherosclerosis (MESA). Genet Epidemiol 2017; 41:801-810. [PMID: 29076270 PMCID: PMC5696115 DOI: 10.1002/gepi.22081] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 08/24/2017] [Accepted: 08/24/2017] [Indexed: 11/09/2022]
Abstract
Over the past few years, an increasing number of studies have identified rare variants that contribute to trait heritability. Due to the extreme rarity of some individual variants, gene-based association tests have been proposed to aggregate the genetic variants within a gene, pathway, or specific genomic region as opposed to a one-at-a-time single variant analysis. In addition, in longitudinal studies, statistical power to detect disease susceptibility rare variants can be improved through jointly testing repeatedly measured outcomes, which better describes the temporal development of the trait of interest. However, usual sandwich/model-based inference for sequencing studies with longitudinal outcomes and rare variants can produce deflated/inflated type I error rate without further corrections. In this paper, we develop a group of tests for rare-variant association based on outcomes with repeated measures. We propose new perturbation methods such that the type I error rate of the new tests is not only robust to misspecification of within-subject correlation, but also significantly improved for variants with extreme rarity in a study with small or moderate sample size. Through extensive simulation studies, we illustrate that substantially higher power can be achieved by utilizing longitudinal outcomes and our proposed finite sample adjustment. We illustrate our methods using data from the Multi-Ethnic Study of Atherosclerosis for exploring association of repeated measures of blood pressure with rare and common variants based on exome sequencing data on 6,361 individuals.
Collapse
Affiliation(s)
- Zihuai He
- Department of Biostatistics, Columbia University, New York, NY 10032
| | - Seunggeun Lee
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109
| | - Min Zhang
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109
| | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48109
| | - Xiuqing Guo
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90509
| | - Walter Palmas
- Department of Medicine, Columbia University, New York, NY 10032
| | | | | | - Bhramar Mukherjee
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109
| |
Collapse
|
25
|
Seyerle AA, Lin HJ, Gogarten SM, Stilp A, Méndez Giráldez R, Soliman E, Baldassari A, Graff M, Heckbert S, Kerr KF, Kooperberg C, Rodriguez C, Guo X, Yao J, Sotoodehnia N, Taylor KD, Whitsel EA, Rotter JI, Laurie CC, Avery CL. Genome-wide association study of PR interval in Hispanics/Latinos identifies novel locus at ID2. Heart 2017; 104:904-911. [PMID: 29127183 DOI: 10.1136/heartjnl-2017-312045] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 10/10/2017] [Accepted: 10/16/2017] [Indexed: 01/12/2023] Open
Abstract
OBJECTIVE PR interval (PR) is a heritable electrocardiographic measure of atrial and atrioventricular nodal conduction. Changes in PR duration may be associated with atrial fibrillation, heart failure and all-cause mortality. Hispanic/Latino populations have high burdens of cardiovascular morbidity and mortality, are highly admixed and represent exceptional opportunities for novel locus identification. However, they remain chronically understudied. We present the first genome-wide association study (GWAS) of PR in 14 756 participants of Hispanic/Latino ancestry from three studies. METHODS Study-specific summary results of the association between 1000 Genomes Phase 1 imputed single-nucleotide polymorphisms (SNPs) and PR assumed an additive genetic model and were adjusted for global ancestry, study centre/region and clinical covariates. Results were combined using fixed-effects, inverse variance weighted meta-analysis. Sequential conditional analyses were used to identify independent signals. Replication of novel loci was performed in populations of Asian, African and European descent. ENCODE and RoadMap data were used to annotate results. RESULTS We identified a novel genome-wide association (P<5×10-8) with PR at ID2 (rs6730558), which replicated in Asian and European populations (P<0.017). Additionally, we generalised 10 previously identified PR loci to Hispanics/Latinos. Bioinformatics annotation provided evidence for regulatory function in cardiac tissue. Further, for six loci that generalised, the Hispanic/Latino index SNP was genome-wide significant and identical to (or in high linkage disequilibrium with) the previously identified GWAS lead SNP. CONCLUSIONS Our results suggest that genetic determinants of PR are consistent across race/ethnicity, but extending studies to admixed populations can identify novel associations, underscoring the importance of conducting genetic studies in diverse populations.
Collapse
Affiliation(s)
- Amanda A Seyerle
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Henry J Lin
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, USA.,Department of Pediatrics, Division of Medical Genetics, Harbor-UCLA Medical Center, Torrance, California, USA
| | | | - Adrienne Stilp
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Raul Méndez Giráldez
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Elsayed Soliman
- Division of Public Health Sciences, Wake Forest School of Medicine, Epidemiology Cardiology Research Center (EPICARE), Winston-Salem, North Carolina, USA.,Department of Medicine, Section of Cardiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Antoine Baldassari
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Susan Heckbert
- Department of Epidemiology, University of Washington, Seattle, Washington, USA.,Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, USA
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Carlos Rodriguez
- Department of Medicine, Section of Cardiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, USA.,Department of Pediatrics, Division of Medical Genetics, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, USA.,Department of Pediatrics, Division of Medical Genetics, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, USA.,Division of Cardiology, University of Washington, Seattle, Washington, USA
| | - Kent D Taylor
- Division of Genomic Outcomes and Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Eric A Whitsel
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, USA.,Department of Pediatrics, Division of Medical Genetics, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Christy L Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| |
Collapse
|
26
|
Gupta DK, Daniels LB, Cheng S, deFilippi CR, Criqui MH, Maisel AS, Lima JA, Bahrami H, Greenland P, Cushman M, Tracy R, Siscovick D, Bertoni AG, Cannone V, Burnett JC, Carr JJ, Wang TJ. Differences in Natriuretic Peptide Levels by Race/Ethnicity (From the Multi-Ethnic Study of Atherosclerosis). Am J Cardiol 2017; 120:1008-1015. [PMID: 28750825 DOI: 10.1016/j.amjcard.2017.06.030] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 05/19/2017] [Accepted: 06/05/2017] [Indexed: 02/02/2023]
Abstract
Natriuretic peptides (NP) are cardiac-derived hormones with favorable cardiometabolic actions. Low NP levels are associated with increased risks of hypertension and diabetes mellitus, conditions with variable prevalence by race and ethnicity. Heritable factors underlie a significant proportion of the interindividual variation in NP concentrations, but the specific influences of race and ancestry are unknown. In 5597 individuals (40% white, 24% black, 23% Hispanic, and 13% Chinese) without prevalent cardiovascular disease at baseline in the Multi-Ethnic Study of Atherosclerosis, multivariable linear regression and restricted cubic splines were used to estimate differences in serum N-terminal pro B-type natriuretic peptide (NT-proBNP) levels according to, ethnicity, and ancestry. Ancestry was determined using genetic ancestry informative markers. NT-proBNP concentrations differed significantly by race and ethnicity (black, median 43 pg/ml [interquartile range 17 to 94], Chinese 43 [17 to 90], Hispanic 53 [23 to 107], white 68 [34 to 136]; p = 0.0001). In multivariable models, NT-proBNP was 44% lower (95% confidence interval -48 to -40) in black and 46% lower (-50 to -41) in Chinese, compared with white individuals. Hispanic individuals had intermediate concentrations. Self-identified blacks and Hispanics were the most genetically admixed. Among self-identified black individuals, a 20% increase in genetic European ancestry was associated with 12% higher (1% to 23%) NT-proBNP. Among Hispanic individuals, genetic European and African ancestry were positively and negatively associated with NT-proBNP levels, respectively. In conclusion, NT-proBNP levels differ according to race and ethnicity, with the lowest concentrations in black and Chinese individuals. Racial and ethnic differences in NT-proBNP may have a genetic basis, with European and African ancestry associated with higher and lower NT-proBNP concentrations, respectively.
Collapse
|
27
|
Jain D, Hodonsky CJ, Schick UM, Morrison JV, Minnerath S, Brown L, Schurmann C, Liu Y, Auer PL, Laurie CA, Taylor KD, Browning BL, Papanicolaou G, Browning SR, Loos RJF, North KE, Thyagarajan B, Laurie CC, Thornton TA, Sofer T, Reiner AP. Genome-wide association of white blood cell counts in Hispanic/Latino Americans: the Hispanic Community Health Study/Study of Latinos. Hum Mol Genet 2017; 26:1193-1204. [PMID: 28158719 DOI: 10.1093/hmg/ddx024] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Accepted: 01/11/2017] [Indexed: 12/13/2022] Open
Abstract
Circulating white blood cell (WBC) counts (neutrophils, monocytes, lymphocytes, eosinophils, basophils) differ by ethnicity. The genetic factors underlying basal WBC traits in Hispanics/Latinos are unknown. We performed a genome-wide association study of total WBC and differential counts in a large, ethnically diverse US population sample of Hispanics/Latinos ascertained by the Hispanic Community Health Study and Study of Latinos (HCHS/SOL). We demonstrate that several previously known WBC-associated genetic loci (e.g. the African Duffy antigen receptor for chemokines null variant for neutrophil count) are generalizable to WBC traits in Hispanics/Latinos. We identified and replicated common and rare germ-line variants at FLT3 (a gene often somatically mutated in leukemia) associated with monocyte count. The common FLT3 variant rs76428106 has a large allele frequency differential between African and non-African populations. We also identified several novel genetic loci involving or regulating hematopoietic transcription factors (CEBPE-SLC7A7, CEBPA and CRBN-TRNT1) associated with basophil count. The minor allele of the CEBPE variant associated with lower basophil count has been previously associated with Amerindian ancestry and higher risk of acute lymphoblastic leukemia in Hispanics. Together, these data suggest that germline genetic variation affecting transcriptional and signaling pathways that underlie WBC development and lineage specification can contribute to inter-individual as well as ethnic differences in peripheral blood cell counts (normal hematopoiesis) in addition to susceptibility to leukemia (malignant hematopoiesis).
Collapse
Affiliation(s)
- Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Chani J Hodonsky
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC 27514, USA
| | - Ursula M Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA
| | - Jean V Morrison
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sharon Minnerath
- Department of Lab Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Lisa Brown
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yongmei Liu
- Department of Epidemiology and Prevention, School of Medicine, Wake Forest University, Winston-Salem, NC 27101, USA
| | - Paul L Auer
- Department of Biostatistics, Joseph J. Zilber School of Public Health, University of Wisconsin Milwaukee, Milwaukee, WI 53201, USA
| | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences at Harbor-UCLA Medical Center, Torrance, CA 90502, USA.,Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Brian L Browning
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - George Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung and Blood Institute, Bethesda, MD 20824, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC 27514, USA.,Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Bharat Thyagarajan
- Department of Lab Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA
| |
Collapse
|
28
|
Qureshi WT, Kaplan RC, Swett K, Burke G, Daviglus M, Jung M, Talavera GA, Chirinos DA, Reina SA, Davis S, Rodriguez CJ. American College of Cardiology/American Heart Association (ACC/AHA) Class I Guidelines for the Treatment of Cholesterol to Reduce Atherosclerotic Cardiovascular Risk: Implications for US Hispanics/Latinos Based on Findings From the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). J Am Heart Assoc 2017; 6:JAHA.116.005045. [PMID: 28495699 PMCID: PMC5524073 DOI: 10.1161/jaha.116.005045] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background The prevalence estimates of statin eligibility among Hispanic/Latinos living in the United States under the new 2013 American College of Cardiology/American Heart Association (ACC/AHA) cholesterol treatment guidelines are not known. Methods and Results We estimated prevalence of statin eligibility under 2013 ACC/AHA and 3rd National Cholesterol Education Program Adult Treatment Panel (NCEP/ATP III) guidelines among Hispanic Community Health Study/Study of Latinos (n=16 415; mean age 41 years, 40% males) by using sampling weights calibrated to the 2010 US census. We examined the characteristics of Hispanic/Latinos treated and not treated with statins under both guidelines. We also redetermined the statin‐therapy eligibility by using black risk estimates for Dominicans, Cubans, Puerto Ricans, and Central Americans. Compared with NCEP/ATP III guidelines, statin eligibility increased from 15.9% (95% CI 15.0–16.7%) to 26.9% (95% CI 25.7–28.0%) under the 2013 ACC/AHA guidelines. This was mainly driven by the ≥7.5% atherosclerotic cardiovascular disease risk criteria (prevalence 13.9% [95% CI 13.0–14.7%]). Of the participants eligible for statin eligibility under NCEP/ATP III and ACC/AHA guidelines, only 28.2% (95% CI 26.3–30.0%) and 20.6% (95% CI 19.4–21.9%) were taking statins, respectively. Statin‐eligible participants who were not taking statins had a higher prevalence of cardiovascular risk factors compared with statin‐eligible participants who were taking statins. There was no significant increase in statin eligibility when atherosclerotic cardiovascular disease risk was calculated by using black estimates instead of recommended white estimates (increase by 1.4%, P=0.12) for Hispanic/Latinos. Conclusions The eligibility of statin therapy increased consistently across all Hispanic/Latinos subgroups under the 2013 ACC/AHA guidelines and therefore will potentially increase the number of undertreated Hispanic/Latinos in the United States.
Collapse
Affiliation(s)
- Waqas T Qureshi
- Division of Cardiology, Department of Internal Medicine, Wake Forest School of Medicine, Winston Salem, NC
| | - Robert C Kaplan
- Division of Cardiology, Department of Internal Medicine, Albert Einstein College of Medicine, New York, NY
| | - Katrina Swett
- Division of Cardiology, Department of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC
| | - Gregory Burke
- Division of Cardiology, Department of Internal Medicine, Albert Einstein College of Medicine, New York, NY
| | - Martha Daviglus
- Division of Cardiology, Department of Internal Medicine, Northwestern University, Chicago, IL
| | | | | | | | | | - Sonia Davis
- University of North Carolina, Chapel Hill, NC
| | - Carlos J Rodriguez
- Division of Cardiology, Department of Internal Medicine, Wake Forest School of Medicine, Winston Salem, NC.,Division of Cardiology, Department of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC
| |
Collapse
|
29
|
Avery CL, Wassel CL, Richard MA, Highland HM, Bien S, Zubair N, Soliman EZ, Fornage M, Bielinski SJ, Tao R, Seyerle AA, Shah SJ, Lloyd-Jones DM, Buyske S, Rotter JI, Post WS, Rich SS, Hindorff LA, Jeff JM, Shohet RV, Sotoodehnia N, Lin DY, Whitsel EA, Peters U, Haiman CA, Crawford DC, Kooperberg C, North KE. Fine mapping of QT interval regions in global populations refines previously identified QT interval loci and identifies signals unique to African and Hispanic descent populations. Heart Rhythm 2017; 14:572-580. [PMID: 27988371 PMCID: PMC5448160 DOI: 10.1016/j.hrthm.2016.12.021] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Indexed: 11/27/2022]
Abstract
BACKGROUND The electrocardiographically measured QT interval (QT) is heritable and its prolongation is an established risk factor for several cardiovascular diseases. Yet, most QT genetic studies have been performed in European ancestral populations, possibly reducing their global relevance. OBJECTIVE To leverage diversity and improve biological insight, we fine mapped 16 of the 35 previously identified QT loci (46%) in populations of African American (n = 12,410) and Hispanic/Latino (n = 14,837) ancestry. METHODS Racial/ethnic-specific multiple linear regression analyses adjusted for heart rate and clinical covariates were examined separately and in combination after inverse-variance weighted trans-ethnic meta-analysis. RESULTS The 16 fine-mapped QT loci included on the Illumina Metabochip represented 21 independent signals, of which 16 (76%) were significantly (P-value≤9.1×10-5) associated with QT. Through sequential conditional analysis we also identified three trans-ethnic novel SNPs at ATP1B1, SCN5A-SCN10A, and KCNQ1 and three Hispanic/Latino-specific novel SNPs at NOS1AP and SCN5A-SCN10A (two novel SNPs) with evidence of associations with QT independent of previous identified GWAS lead SNPs. Linkage disequilibrium patterns helped to narrow the region likely to contain the functional variants at several loci, including NOS1AP, USP50-TRPM7, and PRKCA, although intervals surrounding SLC35F1-PLN and CNOT1 remained broad in size (>100 kb). Finally, bioinformatics-based functional characterization suggested a regulatory function in cardiac tissues for the majority of independent signals that generalized and the novel SNPs. CONCLUSION Our findings suggest that a majority of identified SNPs implicate gene regulatory dysfunction in QT prolongation, that the same loci influence variation in QT across global populations, and that additional, novel, population-specific QT signals exist.
Collapse
Affiliation(s)
| | - Christina L Wassel
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Vermont, Burlington, Vermont
| | - Melissa A Richard
- Institute of Molecular Medicine and; Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas
| | | | - Stephanie Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Niha Zubair
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Elsayed Z Soliman
- Department of Epidemiology and Prevention, Epidemiological Cardiology Research Center and; Department of Internal Medicine, Section on Cardiology, Wake Forest School of Medicine, Winston Salem, North Carolina
| | - Myriam Fornage
- Institute of Molecular Medicine and; Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas
| | - Suzette J Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | | | | | - Sanjiv J Shah
- Department of Preventive Medicine and; Department of Medicine, Northwestern University Feinberg School of Medicine and
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine and; Department of Medicine, Northwestern University Feinberg School of Medicine and
| | - Steven Buyske
- Department of Statistics and Biostatistics and; Department of Genetics, Rutgers University, Piscataway, New Jersey
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California
| | - Wendy S Post
- Department of Medicine and; Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - Lucia A Hindorff
- National Institutes of Health, National Human Genome Research Institute, Office of Population Genomics, Bethesda, Maryland
| | - Janina M Jeff
- Genetics and Genomic Sciences, The Charles Bronfman Institute for Personalized Medicine, The Center for Statistical Genetics, and The Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Ralph V Shohet
- Center for Cardiovascular Research, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, Washington
| | | | | | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine and; Norris Comprehensive Cancer Center, University of Southern California, Pasadena, California
| | - Dana C Crawford
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Kari E North
- Department of Epidemiology; Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| |
Collapse
|
30
|
Han E, Carbonetto P, Curtis RE, Wang Y, Granka JM, Byrnes J, Noto K, Kermany AR, Myres NM, Barber MJ, Rand KA, Song S, Roman T, Battat E, Elyashiv E, Guturu H, Hong EL, Chahine KG, Ball CA. Clustering of 770,000 genomes reveals post-colonial population structure of North America. Nat Commun 2017; 8:14238. [PMID: 28169989 PMCID: PMC5309710 DOI: 10.1038/ncomms14238] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Accepted: 12/12/2016] [Indexed: 02/06/2023] Open
Abstract
Despite strides in characterizing human history from genetic polymorphism data, progress in identifying genetic signatures of recent demography has been limited. Here we identify very recent fine-scale population structure in North America from a network of over 500 million genetic (identity-by-descent, IBD) connections among 770,000 genotyped individuals of US origin. We detect densely connected clusters within the network and annotate these clusters using a database of over 20 million genealogical records. Recent population patterns captured by IBD clustering include immigrants such as Scandinavians and French Canadians; groups with continental admixture such as Puerto Ricans; settlers such as the Amish and Appalachians who experienced geographic or cultural isolation; and broad historical trends, including reduced north-south gene flow. Our results yield a detailed historical portrait of North America after European settlement and support substantial genetic heterogeneity in the United States beyond that uncovered by previous studies.
Collapse
Affiliation(s)
- Eunjung Han
- AncestryDNA, San Francisco, California 94107, USA
| | | | | | - Yong Wang
- AncestryDNA, San Francisco, California 94107, USA
| | | | - Jake Byrnes
- AncestryDNA, San Francisco, California 94107, USA
| | - Keith Noto
- AncestryDNA, San Francisco, California 94107, USA
| | | | | | | | | | - Shiya Song
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Theodore Roman
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Erin Battat
- W.E.B. Du Bois Research Institute, Hutchins Center for African and African American Research, Harvard University, Cambridge, Massachusetts 02138, USA
| | | | | | | | | | | |
Collapse
|
31
|
Brown LA, Sofer T, Stilp AM, Baier LJ, Kramer HJ, Masindova I, Levy D, Hanson RL, Moncrieft AE, Redline S, Rosas SE, Lash JP, Cai J, Laurie CC, Browning S, Thornton T, Franceschini N. Admixture Mapping Identifies an Amerindian Ancestry Locus Associated with Albuminuria in Hispanics in the United States. J Am Soc Nephrol 2017; 28:2211-2220. [PMID: 28137830 DOI: 10.1681/asn.2016091010] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2016] [Accepted: 12/29/2016] [Indexed: 11/03/2022] Open
Abstract
Increased urine albumin excretion is highly prevalent in Hispanics/Latinos. Previous studies have found an association between urine albumin excretion and Amerindian ancestry in Hispanic/Latino populations. Admixture between racial/ethnic groups creates long-range linkage disequilibrium between variants with different allelic frequencies in the founding populations and it can be used to localize genes. Hispanic/Latino genomes are an admixture of European, African, and Amerindian ancestries. We leveraged this admixture to identify associations between urine albumin excretion (urine albumin-to-creatinine ratio [UACR]) and genomic regions harboring variants with highly differentiated allele frequencies among the ancestral populations. Admixture mapping analysis of 12,212 Hispanic Community Health Study/Study of Latinos participants, using a linear mixed model, identified three novel genome-wide significant signals on chromosomes 2, 11, and 16. The admixture mapping signal identified on chromosome 2, spanning q11.2-14.1 and not previously reported for UACR, is driven by a difference between Amerindian ancestry and the other two ancestries (P<5.7 × 10-5). Within this locus, two common variants located at the proapoptotic BCL2L11 gene associated with UACR: rs116907128 (allele frequency =0.14; P=1.5 × 10-7) and rs586283 (C allele frequency =0.35; P=4.2 × 10-7). In a secondary analysis, rs116907128 accounted for most of the admixture mapping signal observed in the region. The rs116907128 variant is common among full-heritage Pima Indians (A allele frequency =0.54) but is monomorphic in the 1000 Genomes European and African populations. In a replication analysis using a sample of full-heritage Pima Indians, rs116907128 significantly associated with UACR (P=0.01; n=1568). Our findings provide evidence for the presence of Amerindian-specific variants influencing the variation of urine albumin excretion in Hispanics/Latinos.
Collapse
Affiliation(s)
- Lisa A Brown
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Tamar Sofer
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Leslie J Baier
- Epidemiology and Clinical Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona
| | - Holly J Kramer
- Department of Public Health Sciences and Medicine, Division of Nephrology and Hypertension, Loyola University Chicago, Maywood, Illinois
| | - Ivica Masindova
- Epidemiology and Clinical Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona
| | - Daniel Levy
- The Framingham Heart Study, Framingham, Massachusetts, and Population Sciences Branch, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, Maryland
| | - Robert L Hanson
- Epidemiology and Clinical Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona
| | | | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Sylvia E Rosas
- Department of Medicine, Division of Nephrology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - James P Lash
- Department of Medicine, Division of Nephrology and Institute for Minority Health Research, University of Illinois at Chicago, Chicago, Illinois
| | - Jianwen Cai
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; and
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Sharon Browning
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Timothy Thornton
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| |
Collapse
|
32
|
Fahrenkrog AM, Neves LG, Resende MFR, Vazquez AI, de Los Campos G, Dervinis C, Sykes R, Davis M, Davenport R, Barbazuk WB, Kirst M. Genome-wide association study reveals putative regulators of bioenergy traits in Populus deltoides. THE NEW PHYTOLOGIST 2017; 213:799-811. [PMID: 27596807 DOI: 10.1111/nph.14154] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Accepted: 07/13/2016] [Indexed: 05/18/2023]
Abstract
Genome-wide association studies (GWAS) have been used extensively to dissect the genetic regulation of complex traits in plants. These studies have focused largely on the analysis of common genetic variants despite the abundance of rare polymorphisms in several species, and their potential role in trait variation. Here, we conducted the first GWAS in Populus deltoides, a genetically diverse keystone forest species in North America and an important short rotation woody crop for the bioenergy industry. We searched for associations between eight growth and wood composition traits, and common and low-frequency single-nucleotide polymorphisms detected by targeted resequencing of 18 153 genes in a population of 391 unrelated individuals. To increase power to detect associations with low-frequency variants, multiple-marker association tests were used in combination with single-marker association tests. Significant associations were discovered for all phenotypes and are indicative that low-frequency polymorphisms contribute to phenotypic variance of several bioenergy traits. Our results suggest that both common and low-frequency variants need to be considered for a comprehensive understanding of the genetic regulation of complex traits, particularly in species that carry large numbers of rare polymorphisms. These polymorphisms may be critical for the development of specialized plant feedstocks for bioenergy.
Collapse
Affiliation(s)
- Annette M Fahrenkrog
- School of Forest Resources and Conservation, University of Florida, PO Box 110410, Gainesville, FL, 32611, USA
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, PO Box 110690, Gainesville, FL, 32610, USA
| | - Leandro G Neves
- School of Forest Resources and Conservation, University of Florida, PO Box 110410, Gainesville, FL, 32611, USA
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, PO Box 110690, Gainesville, FL, 32610, USA
| | - Márcio F R Resende
- School of Forest Resources and Conservation, University of Florida, PO Box 110410, Gainesville, FL, 32611, USA
- Genetics and Genomics Graduate Program, University of Florida, PO Box 103610, Gainesville, FL, 32610, USA
| | - Ana I Vazquez
- Department of Epidemiology and Biostatistics, Michigan State University, 909 Fee Road, East Lansing, MI, 48824, USA
| | - Gustavo de Los Campos
- Department of Epidemiology and Biostatistics, Michigan State University, 909 Fee Road, East Lansing, MI, 48824, USA
- Statistics Department, Michigan State University, 619 Red Cedar Road, MI, 48824, USA
| | - Christopher Dervinis
- School of Forest Resources and Conservation, University of Florida, PO Box 110410, Gainesville, FL, 32611, USA
| | - Robert Sykes
- National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA
| | - Mark Davis
- National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA
| | - Ruth Davenport
- Biology Department, University of Florida, PO Box 118525, Gainesville, FL, 32611, USA
| | - William B Barbazuk
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, PO Box 110690, Gainesville, FL, 32610, USA
- Biology Department, University of Florida, PO Box 118525, Gainesville, FL, 32611, USA
- University of Florida Genetics Institute, University of Florida, PO Box 103610, Gainesville, FL, 32611, USA
| | - Matias Kirst
- School of Forest Resources and Conservation, University of Florida, PO Box 110410, Gainesville, FL, 32611, USA
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, PO Box 110690, Gainesville, FL, 32610, USA
- University of Florida Genetics Institute, University of Florida, PO Box 103610, Gainesville, FL, 32611, USA
| |
Collapse
|
33
|
Kramer HJ, Stilp AM, Laurie CC, Reiner AP, Lash J, Daviglus ML, Rosas SE, Ricardo AC, Tayo BO, Flessner MF, Kerr KF, Peralta C, Durazo-Arvizu R, Conomos M, Thornton T, Rotter J, Taylor KD, Cai J, Eckfeldt J, Chen H, Papanicolau G, Franceschini N. African Ancestry-Specific Alleles and Kidney Disease Risk in Hispanics/Latinos. J Am Soc Nephrol 2016; 28:915-922. [PMID: 27650483 DOI: 10.1681/asn.2016030357] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2016] [Accepted: 07/26/2016] [Indexed: 12/15/2022] Open
Abstract
African ancestry alleles may contribute to CKD among Hispanics/Latinos, but whether associations differ by Hispanic/Latino background remains unknown. We examined the association of CKD measures with African ancestry-specific APOL1 alleles that were directly genotyped and sickle cell trait (hemoglobin subunit β gene [HBB] variant) on the basis of imputation in 12,226 adult Hispanics/Latinos grouped according to Caribbean or Mainland background. We also performed an unbiased genome-wide association scan of urine albumin-to-creatinine ratios. Overall, 41.4% of participants were male, 44.6% of participants had a Caribbean background, and the mean age of all participants was 46.1 years. The Caribbean background group, compared with the Mainland background group, had a higher frequency of two APOL1 alleles (1.0% versus 0.1%) and the HBB variant (2.0% versus 0.7%). In the Caribbean background group, presence of APOL1 alleles (2 versus 0/1 copies) or the HBB variant (1 versus 0 copies) were significantly associated with albuminuria (odds ratio [OR], 3.2; 95% confidence interval [95% CI], 1.7 to 6.1; and OR, 2.6; 95% CI, 1.8 to 3.8, respectively) and albuminuria and/or eGFR<60 ml/min per 1.73 m2 (OR, 2.9; 95% CI, 1.5 to 5.4; and OR, 2.4; 95% CI, 1.7 to 3.5, respectively). The urine albumin-to-creatinine ratio genome-wide association scan identified associations with the HBB variant among all participants, with the strongest association in the Caribbean background group (P=3.1×10-10 versus P=9.3×10-3 for the Mainland background group). In conclusion, African-specific alleles associate with CKD in Hispanics/Latinos, but allele frequency varies by Hispanic/Latino background/ancestry.
Collapse
Affiliation(s)
- Holly J Kramer
- Department of Public Health Sciences and Medicine, and.,Division of Nephrology and Hypertension, Loyola University Chicago, Maywood, Illinois
| | | | | | - Alex P Reiner
- Fred Hutchinson Cancer Research Center, Division of Public Health Science, University of Washington School of Public Health, Seattle, Washington
| | - James Lash
- Division of Nephrology, Department of Medicine, and.,Institute for Minority Health Research, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Martha L Daviglus
- Institute for Minority Health Research, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Sylvia E Rosas
- Division of Nephrology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Ana C Ricardo
- Division of Nephrology, Department of Medicine, and.,Institute for Minority Health Research, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | | | - Michael F Flessner
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | | | - Carmen Peralta
- Division of Nephrology, Department of Medicine, University of California, San Francisco, California
| | | | | | | | - Jerome Rotter
- Institute for Translational Genomics and Population Sciences Los Angeles, Biomedical Research Institute and Department of Pediatrics, Harbor-University of California at Los Angeles Medical Center, Torrance, California
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences Los Angeles, Biomedical Research Institute and Department of Pediatrics, Harbor-University of California at Los Angeles Medical Center, Torrance, California
| | - Jainwen Cai
- Collaborative Studies Coordinating Center, Department of Biostatistics, and
| | - John Eckfeldt
- Advanced Research and Diagnostics Laboratories, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota; and
| | - Han Chen
- Department of Biostatistics, and
| | - George Papanicolau
- Epidemiology Branch, National Heart, Lung, and Blood Institute, Bethesda, Maryland
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina;
| |
Collapse
|
34
|
Nelson SC, Stilp AM, Papanicolaou GJ, Taylor KD, Rotter JI, Thornton TA, Laurie CC. Improved imputation accuracy in Hispanic/Latino populations with larger and more diverse reference panels: applications in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Hum Mol Genet 2016; 25:3245-3254. [PMID: 27346520 PMCID: PMC5179925 DOI: 10.1093/hmg/ddw174] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Revised: 04/04/2016] [Accepted: 06/01/2016] [Indexed: 12/15/2022] Open
Abstract
Imputation is commonly used in genome-wide association studies to expand the set of genetic variants available for analysis. Larger and more diverse reference panels, such as the final Phase 3 of the 1000 Genomes Project, hold promise for improving imputation accuracy in genetically diverse populations such as Hispanics/Latinos in the USA. Here, we sought to empirically evaluate imputation accuracy when imputing to a 1000 Genomes Phase 3 versus a Phase 1 reference, using participants from the Hispanic Community Health Study/Study of Latinos. Our assessments included calculating the correlation between imputed and observed allelic dosage in a subset of samples genotyped on a supplemental array. We observed that the Phase 3 reference yielded higher accuracy at rare variants, but that the two reference panels were comparable at common variants. At a sample level, the Phase 3 reference improved imputation accuracy in Hispanic/Latino samples from the Caribbean more than for Mainland samples, which we attribute primarily to the additional reference panel samples available in Phase 3. We conclude that a 1000 Genomes Project Phase 3 reference panel can yield improved imputation accuracy compared with Phase 1, particularly for rare variants and for samples of certain genetic ancestry compositions. Our findings can inform imputation design for other genome-wide association studies of participants with diverse ancestries, especially as larger and more diverse reference panels continue to become available.
Collapse
Affiliation(s)
- Sarah C Nelson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | | | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research, Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research, Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| |
Collapse
|
35
|
Detecting Heterogeneity in Population Structure Across the Genome in Admixed Populations. Genetics 2016; 204:43-56. [PMID: 27440868 DOI: 10.1534/genetics.115.184184] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Accepted: 06/11/2016] [Indexed: 11/18/2022] Open
Abstract
The genetic structure of human populations is often characterized by aggregating measures of ancestry across the autosomal chromosomes. While it may be reasonable to assume that population structure patterns are similar genome-wide in relatively homogeneous populations, this assumption may not be appropriate for admixed populations, such as Hispanics and African-Americans, with recent ancestry from two or more continents. Recent studies have suggested that systematic ancestry differences can arise at genomic locations in admixed populations as a result of selection and nonrandom mating. Here, we propose a method, which we refer to as the chromosomal ancestry differences (CAnD) test, for detecting heterogeneity in population structure across the genome. CAnD can incorporate either local or chromosome-wide ancestry inferred from SNP genotype data to identify chromosomes harboring genomic regions with ancestry contributions that are significantly different than expected. In simulation studies with real genotype data from phase III of the HapMap Project, we demonstrate the validity and power of CAnD. We apply CAnD to the HapMap Mexican-American (MXL) and African-American (ASW) population samples; in this analysis the software RFMix is used to infer local ancestry at genomic regions, assuming admixing from Europeans, West Africans, and Native Americans. The CAnD test provides strong evidence of heterogeneity in population structure across the genome in the MXL sample ([Formula: see text]), which is largely driven by elevated Native American ancestry and deficit of European ancestry on the X chromosomes. Among the ASW, all chromosomes are largely African derived and no heterogeneity in population structure is detected in this sample.
Collapse
|
36
|
Oetjens MT, Brown-Gentry K, Goodloe R, Dilks HH, Crawford DC. Population Stratification in the Context of Diverse Epidemiologic Surveys Sans Genome-Wide Data. Front Genet 2016; 7:76. [PMID: 27200085 PMCID: PMC4858524 DOI: 10.3389/fgene.2016.00076] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2015] [Accepted: 04/18/2016] [Indexed: 01/01/2023] Open
Abstract
Population stratification or confounding by genetic ancestry is a potential cause of false associations in genetic association studies. Estimation of and adjustment for genetic ancestry has become common practice thanks in part to the availability of ancestry informative markers on genome-wide association study (GWAS) arrays. While array data is now widespread, these data are not ubiquitous as several large epidemiologic and clinic-based studies lack genome-wide data. One such large epidemiologic-based study lacking genome-wide data accessible to investigators is the National Health and Nutrition Examination Surveys (NHANES), population-based cross-sectional surveys of Americans linked to demographic, health, and lifestyle data conducted by the Centers for Disease Control and Prevention. DNA samples (n = 14,998) were extracted from biospecimens from consented NHANES participants between 1991-1994 (NHANES III, phase 2) and 1999-2002 and represent three major self-identified racial/ethnic groups: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We as the Epidemiologic Architecture for Genes Linked to Environment study genotyped candidate gene and GWAS-identified index variants in NHANES as part of the larger Population Architecture using Genomics and Epidemiology I study for collaborative genetic association studies. To enable basic quality control such as estimation of genetic ancestry to control for population stratification in NHANES san genome-wide data, we outline here strategies that use limited genetic data to identify the markers optimal for characterizing genetic ancestry. From among 411 and 295 autosomal SNPs available in NHANES III and NHANES 1999-2002, we demonstrate that markers with ancestry information can be identified to estimate global ancestry. Despite limited resolution, global genetic ancestry is highly correlated with self-identified race for the majority of participants, although less so for ethnicity. Overall, the strategies outlined here for a large epidemiologic study can be applied to other datasets accessible for genotype-phenotype studies but are sans genome-wide data.
Collapse
Affiliation(s)
- Matthew T. Oetjens
- Center for Human Genetics Research Vanderbilt University, NashvilleTN, USA
| | | | - Robert Goodloe
- Center for Human Genetics Research Vanderbilt University, NashvilleTN, USA
| | | | - Dana C. Crawford
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, ClevelandOH, USA
| |
Collapse
|
37
|
Morrison J, Laurie CC, Marazita ML, Sanders AE, Offenbacher S, Salazar CR, Conomos MP, Thornton T, Jain D, Laurie CA, Kerr KF, Papanicolaou G, Taylor K, Kaste LM, Beck JD, Shaffer JR. Genome-wide association study of dental caries in the Hispanic Communities Health Study/Study of Latinos (HCHS/SOL). Hum Mol Genet 2016; 25:807-16. [PMID: 26662797 PMCID: PMC4743689 DOI: 10.1093/hmg/ddv506] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 11/11/2015] [Accepted: 12/07/2015] [Indexed: 12/11/2022] Open
Abstract
Dental caries is the most common chronic disease worldwide, and exhibits profound disparities in the USA with racial and ethnic minorities experiencing disproportionate disease burden. Though heritable, the specific genes influencing risk of dental caries remain largely unknown. Therefore, we performed genome-wide association scans (GWASs) for dental caries in a population-based cohort of 12 000 Hispanic/Latino participants aged 18-74 years from the HCHS/SOL. Intra-oral examinations were used to generate two common indices of dental caries experience which were tested for association with 27.7 M genotyped or imputed single-nucleotide polymorphisms separately in the six ancestry groups. A mixed-models approach was used, which adjusted for age, sex, recruitment site, five principal components of ancestry and additional features of the sampling design. Meta-analyses were used to combine GWAS results across ancestry groups. Heritability estimates ranged from 20-53% in the six ancestry groups. The most significant association observed via meta-analysis for both phenotypes was in the region of the NAMPT gene (rs190395159; P-value = 6 × 10(-10)), which is involved in many biological processes including periodontal healing. Another significant association was observed for rs72626594 (P-value = 3 × 10(-8)) downstream of BMP7, a tooth development gene. Other associations were observed in genes lacking known or plausible roles in dental caries. In conclusion, this was the largest GWAS of dental caries, to date and was the first to target Hispanic/Latino populations. Understanding the factors influencing dental caries susceptibility may lead to improvements in prediction, prevention and disease management, which may ultimately reduce the disparities in oral health across racial, ethnic and socioeconomic strata.
Collapse
Affiliation(s)
- Jean Morrison
- Department of Biostatistics, University of Washington, Seattle, WA 98077, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98077, USA
| | - Mary L Marazita
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, 130 De Soto Street, Pittsburgh, PA 15261, USA, Department of Oral Biology, School of Dental Medicine, Center for Craniofacial and Dental Genetics and Department of Psychiatry, Clinical and Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | | | - Steven Offenbacher
- Department of Periodontology, Center for Oral and Systemic Diseases, School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Christian R Salazar
- Department of Epidemiology and Department of Population Health, Albert Einstein College of Medicine and Montefiore Medical Center, New York City, NY 10461, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98077, USA
| | - Timothy Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98077, USA
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA 98077, USA
| | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98077, USA
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, WA 98077, USA
| | | | - Kent Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute Harbor-UCLA Medical Center, Torrance, CA 90502, USA and
| | - Linda M Kaste
- College of Dentistry and School of Public Health, University of Illinois at Chicago, Chicago, IL 60162, USA
| | | | - John R Shaffer
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, 130 De Soto Street, Pittsburgh, PA 15261, USA,
| |
Collapse
|
38
|
Schick UM, Jain D, Hodonsky CJ, Morrison JV, Davis JP, Brown L, Sofer T, Conomos MP, Schurmann C, McHugh CP, Nelson SC, Vadlamudi S, Stilp A, Plantinga A, Baier L, Bien SA, Gogarten SM, Laurie CA, Taylor KD, Liu Y, Auer PL, Franceschini N, Szpiro A, Rice K, Kerr KF, Rotter JI, Hanson RL, Papanicolaou G, Rich SS, Loos RJF, Browning BL, Browning SR, Weir BS, Laurie CC, Mohlke KL, North KE, Thornton TA, Reiner AP. Genome-wide Association Study of Platelet Count Identifies Ancestry-Specific Loci in Hispanic/Latino Americans. Am J Hum Genet 2016; 98:229-42. [PMID: 26805783 PMCID: PMC4746331 DOI: 10.1016/j.ajhg.2015.12.003] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 12/07/2015] [Indexed: 12/23/2022] Open
Abstract
Platelets play an essential role in hemostasis and thrombosis. We performed a genome-wide association study of platelet count in 12,491 participants of the Hispanic Community Health Study/Study of Latinos by using a mixed-model method that accounts for admixture and family relationships. We discovered and replicated associations with five genes (ACTN1, ETV7, GABBR1-MOG, MEF2C, and ZBTB9-BAK1). Our strongest association was with Amerindian-specific variant rs117672662 (p value = 1.16 × 10(-28)) in ACTN1, a gene implicated in congenital macrothrombocytopenia. rs117672662 exhibited allelic differences in transcriptional activity and protein binding in hematopoietic cells. Our results underscore the value of diverse populations to extend insights into the allelic architecture of complex traits.
Collapse
Affiliation(s)
- Ursula M Schick
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Chani J Hodonsky
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Jean V Morrison
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - James P Davis
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Lisa Brown
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Claudia Schurmann
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Caitlin P McHugh
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sarah C Nelson
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | | | - Adrienne Stilp
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Anna Plantinga
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Leslie Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, NIH, 445 North 5(th) Street, Phoenix, AZ 85004, USA
| | - Stephanie A Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA
| | | | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA; Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Yongmei Liu
- School of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA
| | - Paul L Auer
- Joseph J. Zilber School of Public Health, University of Wisconsin Milwaukee, Milwaukee, WI 53201, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Adam Szpiro
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Ken Rice
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, NIH, 445 North 5(th) Street, Phoenix, AZ 85004, USA
| | - George Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Division of Endocrinology, Department of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Brian L Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Bruce S Weir
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA.
| |
Collapse
|
39
|
Conomos MP, Reiner AP, Weir BS, Thornton TA. Model-free Estimation of Recent Genetic Relatedness. Am J Hum Genet 2016; 98:127-48. [PMID: 26748516 PMCID: PMC4716688 DOI: 10.1016/j.ajhg.2015.11.022] [Citation(s) in RCA: 220] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2015] [Accepted: 11/24/2015] [Indexed: 12/14/2022] Open
Abstract
Genealogical inference from genetic data is essential for a variety of applications in human genetics. In genome-wide and sequencing association studies, for example, accurate inference on both recent genetic relatedness, such as family structure, and more distant genetic relatedness, such as population structure, is necessary for protection against spurious associations. Distinguishing familial relatedness from population structure with genotype data, however, is difficult because both manifest as genetic similarity through the sharing of alleles. Existing approaches for inference on recent genetic relatedness have limitations in the presence of population structure, where they either (1) make strong and simplifying assumptions about population structure, which are often untenable, or (2) require correct specification of and appropriate reference population panels for the ancestries in the sample, which might be unknown or not well defined. Here, we propose PC-Relate, a model-free approach for estimating commonly used measures of recent genetic relatedness, such as kinship coefficients and IBD sharing probabilities, in the presence of unspecified structure. PC-Relate uses principal components calculated from genome-screen data to partition genetic correlations among sampled individuals due to the sharing of recent ancestors and more distant common ancestry into two separate components, without requiring specification of the ancestral populations or reference population panels. In simulation studies with population structure, including admixture, we demonstrate that PC-Relate provides accurate estimates of genetic relatedness and improved relationship classification over widely used approaches. We further demonstrate the utility of PC-Relate in applications to three ancestrally diverse samples that vary in both size and genealogical complexity.
Collapse
Affiliation(s)
- Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Bruce S Weir
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
| |
Collapse
|
40
|
Genetic Diversity and Association Studies in US Hispanic/Latino Populations: Applications in the Hispanic Community Health Study/Study of Latinos. Am J Hum Genet 2016; 98:165-84. [PMID: 26748518 DOI: 10.1016/j.ajhg.2015.12.001] [Citation(s) in RCA: 217] [Impact Index Per Article: 27.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Accepted: 12/02/2015] [Indexed: 12/20/2022] Open
Abstract
US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a "genetic-analysis group" variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness.
Collapse
|
41
|
Loh PR, Bhatia G, Gusev A, Finucane HK, Bulik-Sullivan BK, Pollack SJ, de Candia TR, Lee SH, Wray NR, Kendler KS, O’Donovan MC, Neale BM, Patterson N, Price AL. Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis. Nat Genet 2015; 47:1385-92. [PMID: 26523775 PMCID: PMC4666835 DOI: 10.1038/ng.3431] [Citation(s) in RCA: 283] [Impact Index Per Article: 31.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2015] [Accepted: 10/02/2015] [Indexed: 12/15/2022]
Abstract
Heritability analyses of genome-wide association study (GWAS) cohorts have yielded important insights into complex disease architecture, and increasing sample sizes hold the promise of further discoveries. Here we analyze the genetic architectures of schizophrenia in 49,806 samples from the PGC and nine complex diseases in 54,734 samples from the GERA cohort. For schizophrenia, we infer an overwhelmingly polygenic disease architecture in which ≥71% of 1-Mb genomic regions harbor ≥1 variant influencing schizophrenia risk. We also observe significant enrichment of heritability in GC-rich regions and in higher-frequency SNPs for both schizophrenia and GERA diseases. In bivariate analyses, we observe significant genetic correlations (ranging from 0.18 to 0.85) for several pairs of GERA diseases; genetic correlations were on average 1.3 tunes stronger than the correlations of overall disease liabilities. To accomplish these analyses, we developed a fast algorithm for multicomponent, multi-trait variance-components analysis that overcomes prior computational barriers that made such analyses intractable at this scale.
Collapse
Affiliation(s)
- Po-Ru Loh
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Gaurav Bhatia
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Alexander Gusev
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Hilary K Finucane
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Brendan K Bulik-Sullivan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Samuela J Pollack
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | | | - Teresa R de Candia
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, United States
| | - Sang Hong Lee
- The Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
- School of Environmental and Rural Science, University of New England, Armidale, New South Wales, Australia
| | - Naomi R Wray
- The Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Kenneth S Kendler
- Department of Psychiatry and Human Genetics, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Michael C O’Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Benjamin M Neale
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Nick Patterson
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| |
Collapse
|
42
|
A minimum set of ancestry informative markers for determining admixture proportions in a mixed American population: the Brazilian set. Eur J Hum Genet 2015; 24:725-31. [PMID: 26395555 DOI: 10.1038/ejhg.2015.187] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Accepted: 07/12/2015] [Indexed: 11/08/2022] Open
Abstract
The Brazilian population is considered to be highly admixed. The main contributing ancestral populations were European and African, with Amerindians contributing to a lesser extent. The aims of this study were to provide a resource for determining and quantifying individual continental ancestry using the smallest number of SNPs possible, thus allowing for a cost- and time-efficient strategy for genomic ancestry determination. We identified and validated a minimum set of 192 ancestry informative markers (AIMs) for the genetic ancestry determination of Brazilian populations. These markers were selected on the basis of their distribution throughout the human genome, and their capacity of being genotyped on widely available commercial platforms. We analyzed genotyping data from 6487 individuals belonging to three Brazilian cohorts. Estimates of individual admixture using this 192 AIM panels were highly correlated with estimates using ~370 000 genome-wide SNPs: 91%, 92%, and 74% of, respectively, African, European, and Native American ancestry components. Besides that, 192 AIMs are well distributed among populations from these ancestral continents, allowing greater freedom in future studies with this panel regarding the choice of reference populations. We also observed that genetic ancestry inferred by AIMs provides similar association results to the one obtained using ancestry inferred by genomic data (370 K SNPs) in a simple regression model with rs1426654, related to skin pigmentation, genotypes as dependent variable. In conclusion, these markers can be used to identify and accurately quantify ancestry of Latin Americans or US Hispanics/Latino individuals, in particular in the context of fine-mapping strategies that require the quantification of continental ancestry in thousands of individuals.
Collapse
|
43
|
Prospective association of a genetic risk score and lifestyle intervention with cardiovascular morbidity and mortality among individuals with type 2 diabetes: the Look AHEAD randomised controlled trial. Diabetologia 2015; 58:1803-13. [PMID: 25972230 PMCID: PMC4507276 DOI: 10.1007/s00125-015-3610-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2014] [Accepted: 04/07/2015] [Indexed: 02/07/2023]
Abstract
AIMS/HYPOTHESIS Both obesity and genetics contribute to cardiovascular disease (CVD). We examined whether a genetic risk score (GRS) prospectively predicted cardiovascular morbidity and mortality among overweight/obese individuals with type 2 diabetes and whether behavioural weight loss could diminish this association. METHODS Look AHEAD (Action for Health in Diabetes) is a randomised controlled trial to determine the effects of intensive lifestyle intervention (ILI), including weight loss and physical activity, relative to diabetes support and education, on cardiovascular outcomes among overweight/obese individuals with type 2 diabetes. Of the participants, 4,016 provided consent for genetic analyses and had DNA samples passing quality control procedures. These secondary data analyses focused on whether a GRS derived from 153 single nucleotide polymorphisms (SNPs) associated with coronary artery disease in the most recent genome-wide association study predicted cardiovascular morbidity and mortality over a median of 9.6 years of follow-up, and whether ILI would diminish this association. RESULTS The GRS significantly predicted the primary composite endpoint of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalisation for angina in the full sample (HR, 95% CI per 1 SD increase in GRS: 1.19 [1.10, 1.28]) and among individuals with no known history of CVD at baseline (HR 1.18 [95% CI 1.07, 1.30]). In no case did ILI significantly alter this association. CONCLUSIONS/INTERPRETATION A GRS comprised of SNPs significantly predicts cardiovascular morbidity and mortality over 9.6 years of follow-up in Look AHEAD. Lifestyle intervention did not alter the genetic association. CLINICAL TRIAL REGISTRATION NCT00017953; NCT01270763.
Collapse
|
44
|
Moradi H, Abhari P, Streja E, Kashyap ML, Shah G, Gillen D, Pahl MV, Vaziri ND, Kalantar-Zadeh K. Association of serum lipids with outcomes in Hispanic hemodialysis patients of the West versus East Coasts of the United States. Am J Nephrol 2015; 41:284-95. [PMID: 26044456 DOI: 10.1159/000381991] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Accepted: 03/25/2015] [Indexed: 12/24/2022]
Abstract
BACKGROUND Paradoxical associations exist between serum lipid levels and mortality in patients on maintenance hemodialysis (MHD) including those of Hispanic origin. However, there are significant racial and ethnic variations in patients of 'Hispanic' background. We hypothesized that clinically meaningful differences existed in the association between lipids and survival in Hispanic MHD patients on the West versus East Coast. METHODS We examined the survival impact of serum lipids in a 2-year cohort of 15,109 MHD patients of Hispanic origin being treated in California, Texas, representing the West versus New York, New Jersey and Florida representing the East Coast, using Cox models with various degrees of adjustments. RESULTS The association of serum total and HDL cholesterol with mortality follows a U-shaped pattern in Hispanic patients residing in the West. This is in contrast to Hispanic patients in the East Coast whose survival seems to improve with increasing total and HDL cholesterol levels. Elevated serum LDL levels in Hispanic patients on the West Coast are associated with a significant increase in mortality, while this association is not observed in patients residing on the East Coast. CONCLUSIONS Substantial differences exist in the association of serum lipids with mortality in MHD patients of Hispanic background depending on whether they reside on the West or East Coast of the United States. These geographical variances most likely reflect ethnic, racial and genetic distinctions, which are usually ignored. Future studies should take into account these critical variations in a population of patients who make up a significant portion of our society.
Collapse
Affiliation(s)
- Hamid Moradi
- Division of Nephrology and Hypertension, University of California Irvine School of Medicine, Orange, Calif., USA
| | | | | | | | | | | | | | | | | |
Collapse
|
45
|
Onengut-Gumuscu S, Chen WM, Burren O, Cooper NJ, Quinlan AR, Mychaleckyj JC, Farber E, Bonnie JK, Szpak M, Schofield E, Achuthan P, Guo H, Fortune MD, Stevens H, Walker NM, Ward LD, Kundaje A, Kellis M, Daly MJ, Barrett JC, Cooper JD, Deloukas P, Todd JA, Wallace C, Concannon P, Rich SS. Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers. Nat Genet 2015; 47:381-6. [PMID: 25751624 PMCID: PMC4380767 DOI: 10.1038/ng.3245] [Citation(s) in RCA: 469] [Impact Index Per Article: 52.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2014] [Accepted: 02/13/2015] [Indexed: 02/06/2023]
Abstract
Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10(-8)). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34(+) stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal.
Collapse
Affiliation(s)
- Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Medicine, Division of Endocrinology, University of Virginia, Charlottesville, VA, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA, USA
| | - Oliver Burren
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Nick J. Cooper
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Aaron R. Quinlan
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA, USA
| | - Josyf C. Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA, USA
| | - Emily Farber
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jessica K. Bonnie
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Michal Szpak
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Ellen Schofield
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Premanand Achuthan
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Hui Guo
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Mary D. Fortune
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Helen Stevens
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Neil M. Walker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Luke D. Ward
- Department of Computer Science, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anshul Kundaje
- Department of Computer Science, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA. Department of Genetics, Stanford University, Stanford, CA, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Manolis Kellis
- Department of Computer Science, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark J. Daly
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Jason D. Cooper
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | | | | | - John A. Todd
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
| | - Chris Wallace
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, NIHR Biomedical Research Centre, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY, UK
- MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, CB2 0SR, Cambridge, United Kingdom
| | - Patrick Concannon
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA, USA
| |
Collapse
|
46
|
Haberstick BC, Smolen A, Williams RB, Bishop GD, Foshee VA, Thornberry TP, Conger R, Siegler IC, Zhang X, Boardman JD, Frajzyngier Z, Stallings MC, Brent Donnellan M, Halpern CT, Harris KM. Population frequencies of the Triallelic 5HTTLPR in six Ethnicially diverse samples from North America, Southeast Asia, and Africa. Behav Genet 2015; 45:255-61. [PMID: 25564228 PMCID: PMC4348250 DOI: 10.1007/s10519-014-9703-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2014] [Accepted: 12/20/2014] [Indexed: 12/16/2022]
Abstract
Genetic differences between populations are potentially an important contributor to health disparities around the globe. As differences in gene frequencies influence study design, it is important to have a thorough understanding of the natural variation of the genetic variant(s) of interest. Along these lines, we characterized the variation of the 5HTTLPR and rs25531 polymorphisms in six samples from North America, Southeast Asia, and Africa (Cameroon) that differ in their racial and ethnic composition. Allele and genotype frequencies were determined for 24,066 participants. Results indicated higher frequencies of the rs25531 G-allele among Black and African populations as compared with White, Hispanic and Asian populations. Further, we observed a greater number of 'extra-long' ('XL') 5HTTLPR alleles than have previously been reported. Extra-long alleles occurred almost entirely among Asian, Black and Non-White Hispanic populations as compared with White and Native American populations where they were completely absent. Lastly, when considered jointly, we observed between sample differences in the genotype frequencies within racial and ethnic populations. Taken together, these data underscore the importance of characterizing the L-G allele to avoid misclassification of participants by genotype and for further studies of the impact XL alleles may have on the transcriptional efficiency of SLC6A4.
Collapse
Affiliation(s)
- Brett C Haberstick
- Institute for Behavioral Genetics, University of Colorado Boulder, Campus Box 447, Boulder, CO, 80309-0447, USA,
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
47
|
Rodriguez CJ, Soliman EZ, Alonso A, Swett K, Okin PM, Goff DC, Heckbert SR. Atrial fibrillation incidence and risk factors in relation to race-ethnicity and the population attributable fraction of atrial fibrillation risk factors: the Multi-Ethnic Study of Atherosclerosis. Ann Epidemiol 2015; 25:71-6, 76.e1. [PMID: 25523897 PMCID: PMC4559265 DOI: 10.1016/j.annepidem.2014.11.024] [Citation(s) in RCA: 127] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2014] [Revised: 11/06/2014] [Accepted: 11/14/2014] [Indexed: 10/24/2022]
Abstract
PURPOSE We studied incident atrial fibrillation (AF) in the prospective community-based Multi-Ethnic Study of Atherosclerosis (MESA). Reportedly, non-Hispanic blacks (NHBs) have a lower AF burden compared with their non-Hispanic white (NHW) counterparts. Information on the epidemiology of AF in Hispanic and Asian populations is much more limited. METHODS We excluded participants with a history of AF at enrollment. A total of 6721 MESA participants were monitored for the first AF event ascertained according to hospital discharge International Classification of Diseases, Ninth Revision, codes. Age- and sex-adjusted incidence rates (IRs) of AF were calculated per 1000 person-years of observation. IR ratios were calculated using NHWs as the reference group. Age- and sex-adjusted population attributable fractions (PAFs) of established modifiable AF risk factors were ascertained. RESULTS In the MESA cohort, 47.2% was male; at baseline, 25.7% had hypertension; 12.5% had diabetes. Three hundred five incident hospitalized AF events occurred over a mean follow-up of 7.3 years. Age- and sex-adjusted IRs and IR ratios showed that overall AF incidence was significantly lower among Hispanics, NHBs and Chinese compared with NHWs (all P < .001). Among participants 65 years of age or greater, Hispanics, Chinese, and blacks had significantly lower AF incidence than NHWs (all P ≤ .01), but IRs were similar among participants under age 65 years. The PAF for smoking was 27% among NHBs but lower among other race-ethnic groups. Among NHWs, the PAF for hypertension was 22.2%, but this was higher among NHBs (33.1%), Chinese (46.3%), and Hispanics (43.9%). CONCLUSIONS Overall, the incidence of hospitalized AF was significantly lower in Hispanics, NHBs, and Chinese than in NHWs. A larger proportion of AF events appear to be attributable to hypertension among nonwhite populations compared with NHWs.
Collapse
Affiliation(s)
- Carlos J Rodriguez
- Department of Medicine, Wake Forest University School of Medicine, Winston Salem, NC; Department of Epidemiology & Prevention, Wake Forest University School of Medicine, Winston Salem, NC.
| | - Elsayed Z Soliman
- Department of Medicine, Wake Forest University School of Medicine, Winston Salem, NC; Department of Epidemiology & Prevention, Wake Forest University School of Medicine, Winston Salem, NC
| | - Alvaro Alonso
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis
| | - Katrina Swett
- Department of Medicine, Wake Forest University School of Medicine, Winston Salem, NC; Department of Epidemiology & Prevention, Wake Forest University School of Medicine, Winston Salem, NC
| | - Peter M Okin
- Department of Medicine, Weill-Cornell School of Medicine, New York, NY
| | - David C Goff
- Department of Epidemiology, Colorado School of Public Health, Aurora
| | | |
Collapse
|
48
|
Immunogenetic influences on acquisition of HIV-1 infection: consensus findings from two African cohorts point to an enhancer element in IL19 (1q32.2). Genes Immun 2015; 16:213-20. [PMID: 25633979 PMCID: PMC4409473 DOI: 10.1038/gene.2014.84] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2014] [Revised: 12/19/2014] [Accepted: 12/19/2014] [Indexed: 12/12/2022]
Abstract
Numerous reports have suggested that immunogenetic factors may influence HIV-1 acquisition, yet replicated findings that translate between study cohorts remain elusive. Our work aimed to test several hypotheses about genetic variants within the IL10-IL24 gene cluster that encodes interleukin (IL)-10, IL-19, IL-20, and IL-24. In aggregated data from 515 Rwandans and 762 Zambians with up to 12 years of follow-up, 190 single nucleotide polymorphisms (SNPs) passed quality control procedures. When HIV-1-exposed seronegative subjects (n = 486) were compared with newly seroconverted individuals (n = 313) and seroprevalent subjects (n = 478) who were already infected at enrollment, rs12407485 (G>A) in IL19 showed a robust association signal in adjusted logistic regression models (odds ratio = 0.64, P = 1.7 × 10−4, and q = 0.033). Sensitivity analyses demonstrated that (i) results from both cohorts and subgroups within each cohort were highly consistent; (ii) verification of HIV-1 infection status after enrollment was critical; and (iii) supporting evidence was readily obtained from Cox proportional hazards models. Data from public databases indicate that rs12407485 is part of an enhancer element for three transcription factors. Overall, these findings suggest that molecular features at the IL19 locus may modestly alter the establishment of HIV-1 infection.
Collapse
|
49
|
Ramamoorthy A, Pacanowski MA, Bull J, Zhang L. Racial/ethnic differences in drug disposition and response: Review of recently approved drugs. Clin Pharmacol Ther 2015; 97:263-73. [DOI: 10.1002/cpt.61] [Citation(s) in RCA: 173] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2014] [Revised: 12/01/2014] [Accepted: 12/06/2014] [Indexed: 01/09/2023]
Affiliation(s)
- A Ramamoorthy
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration; Silver Spring Maryland USA
| | - MA Pacanowski
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration; Silver Spring Maryland USA
| | - J Bull
- Office of Minority Health, Office of the Commissioner, US Food and Drug Administration; Silver Spring Maryland USA
| | - L Zhang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration; Silver Spring Maryland USA
| |
Collapse
|
50
|
Rodriguez CJ, Daviglus ML, Swett K, González HM, Gallo LC, Wassertheil-Smoller S, Giachello AL, Teng Y, Schneiderman N, Talavera GA, Kaplan RC. Dyslipidemia patterns among Hispanics/Latinos of diverse background in the United States. Am J Med 2014; 127:1186-94.e1. [PMID: 25195188 PMCID: PMC4551715 DOI: 10.1016/j.amjmed.2014.07.026] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2014] [Revised: 07/10/2014] [Accepted: 07/11/2014] [Indexed: 11/19/2022]
Abstract
BACKGROUND The prevalence and determinants of dyslipidemia patterns among Hispanics/Latinos are not well known. METHODS Lipid and lipoprotein data were used from the Hispanic Community Health Study/Study of Latinos—a population-based cohort of 16,415 US Hispanic/Latinos ages 18-74 years. National Cholesterol Education Program cutoffs were employed. Differences in demographics, lifestyle factors, and biological and acculturation characteristics were compared among those with and without dyslipidemia. RESULTS Mean age was 41.1 years, and 47.9% were male. The overall prevalence of any dyslipidemia was 65.0%. The prevalence of elevated low-density lipoprotein cholesterol was 36.0%, and highest among Cubans (44.5%; P < .001). Low high-density lipoprotein cholesterol (HDL-C) was present in 41.4% and did not significantly differ across Hispanic background groups (P = .09). High triglycerides were seen in 14.8% of Hispanics/Latinos, most commonly among Central Americans (18.3%; P < .001). Elevated non-HDL-C was seen in 34.7%, with the highest prevalence among Cubans (43.3%; P < .001). Dominicans consistently had a lower prevalence of most types of dyslipidemia. In multivariate analyses, the presence of any dyslipidemia was associated with increasing age, body mass index, and low physical activity. Older age, female sex, diabetes, low physical activity, and alcohol use were associated with specific dyslipidemia types. Spanish-language preference and lower educational status were associated with higher dyslipidemia prevalence. CONCLUSION Dyslipidemia is highly prevalent among US Hispanics/Latinos; Cubans seem particularly at risk. Determinants of dyslipidemia varied across Hispanic backgrounds, with socioeconomic status and acculturation having a significant effect on dyslipidemia prevalence. This information can help guide public health measures to prevent disparities among the US Hispanic/Latino population.
Collapse
Affiliation(s)
- Carlos J Rodriguez
- Department of Medicine and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC.
| | | | - Katrina Swett
- Department of Medicine and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC
| | | | | | | | | | - Yanping Teng
- Departments of Biostatistics, University of North Carolina, Chapel Hill
| | | | - Gregory A Talavera
- Graduate School of Public Health, San Diego State University, San Diego, Calif
| | - Robert C Kaplan
- Department of Epidemiology and Community Health, Albert Einstein School of Medicine, New York, NY
| |
Collapse
|