1
|
Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North KE, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, Raffield LM. Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium. Hum Mol Genet 2024; 33:1429-1441. [PMID: 38747556 PMCID: PMC11305684 DOI: 10.1093/hmg/ddae050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 01/31/2024] [Accepted: 03/11/2024] [Indexed: 05/28/2024] Open
Abstract
Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38 465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program (with varying sample size by trait, where the minimum sample size was n = 737 for MMP-1). We identified 22 distinct single-variant associations across 6 traits-E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin-that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
Collapse
Affiliation(s)
- Min-Zhi Jiang
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
| | - Sheila M Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, United States
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, United States
| | - Xihao Li
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
- Department of Biostatistics, 135 Dauer Drive, 4115D McGavran-Greenberg Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, United States
| | - Adrienne Stilp
- Department of Biostatistics, 4333 Brooklyn Ave NE, University of Washington, Seattle, WA 98105, United States
| | - Erin Buth
- Department of Biostatistics, 4333 Brooklyn Ave NE, University of Washington, Seattle, WA 98105, United States
| | - Fei Fei Wang
- Department of Biostatistics, 4333 Brooklyn Ave NE, University of Washington, Seattle, WA 98105, United States
| | - Regina Manansala
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO) WHO Collaborating Centre, University of Antwerp, Campus Drie Eiken - Building S; Universiteitsplein 1 2610 Antwerpen, Belgium
| | - Stephanie M Gogarten
- Department of Biostatistics, 4333 Brooklyn Ave NE, University of Washington, Seattle, WA 98105, United States
| | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, 5268 Renmin Street, Changchun, JL 130024, China
| | - Linda M Polfus
- Advanced Analytics, Ambry Genetics, 1 Enterprise, Aliso Viejo, CA 92656, United States
| | - Shabnam Salimi
- Department of Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine, 655 W. Baltimore Street, Baltimore, MD 21201, United States
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA 98195, United States
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, 420 Delaware Street SE, Minneapolis, MN 55455, United States
| | - Lisa R Yanek
- Department of Medicine, General Internal Medicine, Johns Hopkins University School of Medicine, 1830 E Monument St Rm 8024, Baltimore, MD 21287, United States
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT 05446, United States
| | - Russell P Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT 05446, United States
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, 200 Jeanette Lancaster Way, Charlottesville, VA 22903, United States
| | - 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, 1124 W. Carson Street, Torrance, CA 90502, United States
| | - Braxton D Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD 21201, United States
| | - Joshua P Lewis
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD 21201, United States
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA 98195, United States
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA 98101, United States
| | - Katherine A Pratte
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, 1400 Jackson Street, Denver, CO 80206, United States
| | - Edwin K Silverman
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, United States
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC 27599, United States
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC 27599, United States
| | - Rasika A Mathias
- Department of Medicine, Allergy and Clinical Immunology, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Cir JHAAC Room 3B53, Baltimore, MD 21287, United States
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287, United States
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA 01655, United States
| | - Biqi Wang
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA 01655, United States
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS 39213, United States
| | - Arnita F Norwood
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS 39213, United States
| | - Richard A Gibbs
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, WA 98109, United States
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, WA 98109, United States
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, WA 98109, United States
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 2001 McGill College Avenue, Montreal, QC H3A 1G1, Canada
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, United States
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N Lake Shore Drive, Chicago, IL 60611, United States
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, 1825 Pressler Street, Houston, TX 77030, United States
| | - Emelia J Benjamin
- Department of Medicine, Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, 72 East Newton Street, Boston, MA 02118, United States
- Department of Epidemiology, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, United States
- Boston University and National Heart, Lung, and Blood Institute’s Framingham Heart Study, 73 Mount Wayte Ave #2, Framingham, MA 01702, United States
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA 98105, United States
| | - Russell P Bowler
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, 1400 Jackson Street, Denver, CO 80206, United States
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, United States
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
| | | |
Collapse
|
2
|
Yu Z, Coorens THH, Uddin MM, Ardlie KG, Lennon N, Natarajan P. Genetic variation across and within individuals. Nat Rev Genet 2024; 25:548-562. [PMID: 38548833 DOI: 10.1038/s41576-024-00709-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2024] [Indexed: 04/12/2024]
Abstract
Germline variation and somatic mutation are intricately connected and together shape human traits and disease risks. Germline variants are present from conception, but they vary between individuals and accumulate over generations. By contrast, somatic mutations accumulate throughout life in a mosaic manner within an individual due to intrinsic and extrinsic sources of mutations and selection pressures acting on cells. Recent advancements, such as improved detection methods and increased resources for association studies, have drastically expanded our ability to investigate germline and somatic genetic variation and compare underlying mutational processes. A better understanding of the similarities and differences in the types, rates and patterns of germline and somatic variants, as well as their interplay, will help elucidate the mechanisms underlying their distinct yet interlinked roles in human health and biology.
Collapse
Affiliation(s)
- Zhi Yu
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - Md Mesbah Uddin
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - Niall Lennon
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Pradeep Natarajan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
3
|
Niewold TB, Aksentijevich I, Gorevic PD, Gibson G, Yao Q. Genetically transitional disease: conceptual understanding and applicability to rheumatic disease. Nat Rev Rheumatol 2024; 20:301-310. [PMID: 38418715 DOI: 10.1038/s41584-024-01086-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/19/2024] [Indexed: 03/02/2024]
Abstract
In genomic medicine, the concept of genetically transitional disease (GTD) refers to cases in which gene mutation is necessary but not sufficient to cause disease. In this Perspective, we apply this novel concept to rheumatic diseases, which have been linked to hundreds of genetic variants via association studies. These variants are in the 'grey zone' between monogenic variants with large effect sizes and common susceptibility alleles with small effect sizes. Among genes associated with rare autoinflammatory diseases, many low-frequency and/or low-penetrance variants are known to increase susceptibility to systemic inflammation. In autoimmune diseases, hundreds of HLA and non-HLA genetic variants have been revealed to be modest- to moderate-risk alleles. These diseases can be reclassified as GTDs. The same concept could apply to many other human diseases. GTD could improve the reporting of genetic testing results, diagnostic yields, genetic counselling and selection of therapy, as well as facilitating research using a novel approach to human genetic diseases.
Collapse
Affiliation(s)
- Timothy B Niewold
- Department of Rheumatology, Hospital for Special Surgery, New York, NY, USA
| | - Ivona Aksentijevich
- Inflammatory Disease Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peter D Gorevic
- Division of Rheumatology, Allergy and Immunology, Stony Brook University Renaissance School of Medicine, Stony Brook, NY, USA
| | - Greg Gibson
- Center for Integrative Genomics, School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Qingping Yao
- Division of Rheumatology, Allergy and Immunology, Stony Brook University Renaissance School of Medicine, Stony Brook, NY, USA.
| |
Collapse
|
4
|
Alireza Z, Maleeha M, Kaikkonen M, Fortino V. Enhancing prediction accuracy of coronary artery disease through machine learning-driven genomic variant selection. J Transl Med 2024; 22:356. [PMID: 38627847 PMCID: PMC11020205 DOI: 10.1186/s12967-024-05090-1] [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: 09/12/2023] [Accepted: 03/14/2024] [Indexed: 04/19/2024] Open
Abstract
Machine learning (ML) methods are increasingly becoming crucial in genome-wide association studies for identifying key genetic variants or SNPs that statistical methods might overlook. Statistical methods predominantly identify SNPs with notable effect sizes by conducting association tests on individual genetic variants, one at a time, to determine their relationship with the target phenotype. These genetic variants are then used to create polygenic risk scores (PRSs), estimating an individual's genetic risk for complex diseases like cancer or cardiovascular disorders. Unlike traditional methods, ML algorithms can identify groups of low-risk genetic variants that improve prediction accuracy when combined in a mathematical model. However, the application of ML strategies requires addressing the feature selection challenge to prevent overfitting. Moreover, ensuring the ML model depends on a concise set of genomic variants enhances its clinical applicability, where testing is feasible for only a limited number of SNPs. In this study, we introduce a robust pipeline that applies ML algorithms in combination with feature selection (ML-FS algorithms), aimed at identifying the most significant genomic variants associated with the coronary artery disease (CAD) phenotype. The proposed computational approach was tested on individuals from the UK Biobank, differentiating between CAD and non-CAD individuals within this extensive cohort, and benchmarked against standard PRS-based methodologies like LDpred2 and Lassosum. Our strategy incorporates cross-validation to ensure a more robust evaluation of genomic variant-based prediction models. This method is commonly applied in machine learning strategies but has often been neglected in previous studies assessing the predictive performance of polygenic risk scores. Our results demonstrate that the ML-FS algorithm can identify panels with as few as 50 genetic markers that can achieve approximately 80% accuracy when used in combination with known risk factors. The modest increase in accuracy over PRS performances is noteworthy, especially considering that PRS models incorporate a substantially larger number of genetic variants. This extensive variant selection can pose practical challenges in clinical settings. Additionally, the proposed approach revealed novel CAD-genetic variant associations.
Collapse
Affiliation(s)
- Z Alireza
- Institute of Biomedicine, University of Eastern Finland, 70210, Kuopio, Finland
| | - M Maleeha
- Institute of Biomedicine, University of Eastern Finland, 70210, Kuopio, Finland
| | - M Kaikkonen
- A.I.Virtanen Institute, University of Eastern Finland, 70210, Kuopio, Finland
| | - V Fortino
- Institute of Biomedicine, University of Eastern Finland, 70210, Kuopio, Finland.
| |
Collapse
|
5
|
Bick AG, Metcalf GA, Mayo KR, Lichtenstein L, Rura S, Carroll RJ, Musick A, Linder JE, Jordan IK, Nagar SD, Sharma S, Meller R, Basford M, Boerwinkle E, Cicek MS, Doheny KF, Eichler EE, Gabriel S, Gibbs RA, Glazer D, Harris PA, Jarvik GP, Philippakis A, Rehm HL, Roden DM, Thibodeau SN, Topper S, Blegen AL, Wirkus SJ, Wagner VA, Meyer JG, Cicek MS, Muzny DM, Venner E, Mawhinney MZ, Griffith SML, Hsu E, Ling H, Adams MK, Walker K, Hu J, Doddapaneni H, Kovar CL, Murugan M, Dugan S, Khan Z, Boerwinkle E, Lennon NJ, Austin-Tse C, Banks E, Gatzen M, Gupta N, Henricks E, Larsson K, McDonough S, Harrison SM, Kachulis C, Lebo MS, Neben CL, Steeves M, Zhou AY, Smith JD, Frazar CD, Davis CP, Patterson KE, Wheeler MM, McGee S, Lockwood CM, Shirts BH, Pritchard CC, Murray ML, Vasta V, Leistritz D, Richardson MA, Buchan JG, Radhakrishnan A, Krumm N, Ehmen BW, Schwartz S, Aster MMT, Cibulskis K, Haessly A, Asch R, Cremer A, Degatano K, Shergill A, Gauthier LD, Lee SK, Hatcher A, Grant GB, Brandt GR, Covarrubias M, Banks E, Able A, Green AE, Carroll RJ, Zhang J, Condon HR, Wang Y, Dillon MK, Albach CH, Baalawi W, Choi SH, Wang X, Rosenthal EA, Ramirez AH, Lim S, Nambiar S, Ozenberger B, Wise AL, Lunt C, Ginsburg GS, Denny JC. Genomic data in the All of Us Research Program. Nature 2024; 627:340-346. [PMID: 38374255 PMCID: PMC10937371 DOI: 10.1038/s41586-023-06957-x] [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: 07/22/2022] [Accepted: 12/08/2023] [Indexed: 02/21/2024]
Abstract
Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics1-4. The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health5,6. Here we describe the programme's genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.
Collapse
|
6
|
Gao Z, Pu C, Lin L, Ou Q, Quan H. Genome-wide association study of blood lipid levels in Southern Han Chinese adults with prediabetes. Front Endocrinol (Lausanne) 2024; 14:1334893. [PMID: 38371897 PMCID: PMC10869499 DOI: 10.3389/fendo.2023.1334893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 12/22/2023] [Indexed: 02/20/2024] Open
Abstract
Background Dyslipidemia is highly prevalent among individuals with prediabetes, further exacerbating their cardiovascular risk. However, the genetic determinants underlying diabetic dyslipidemia in Southern Han Chinese remain largely unexplored. Methods We performed a genome-wide association study (GWAS) of blood lipid traits in 451 Southern Han Chinese adults with prediabetes. Fasting plasma lipids, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were assayed. Genotyping was conducted using the Precision Medicine Diversity Array and Gene Titan platform, followed by genotype imputation using IMPUTE2 with the 1000 Genomes Project (Phase 3, Southern Han Chinese) as reference. Single nucleotide polymorphisms (SNPs) associated with lipid levels were identified using mixed linear regression, with adjustment for covariates. Results We identified 58, 215, 74 and 81 novel SNPs associated with TG, TC, HDL-C and LDL-C levels, respectively (P < 5×10-5). Several implicated loci were located in or near genes involved in lipid metabolism, including SRD5A2, PCSK7, PITPNC1, IRX3, BPI, and LBP. Pathway enrichment analysis highlighted lipid metabolism and insulin secretion. Conclusion This first GWAS of dyslipidemia in Southern Han Chinese with prediabetes identified novel genetic variants associated with lipid traits. Our findings provide new insights into genetic mechanisms underlying heightened cardiovascular risk in the prediabetic stage. Functional characterization of implicated loci is warranted.
Collapse
Affiliation(s)
- Zhenshu Gao
- Department of Endocrinology, Hainan Affiliated Hospital of Hainan Medical University, Hainan General Hospital, Haikou, China
| | - Changchun Pu
- Department of Endocrinology, Hainan Affiliated Hospital of Hainan Medical University, Hainan General Hospital, Haikou, China
| | - Leweihua Lin
- Department of Endocrinology, Hainan General Hospital, Haikou, China
| | - Qianying Ou
- Department of Endocrinology, Hainan General Hospital, Haikou, China
| | - Huibiao Quan
- Department of Endocrinology, Hainan General Hospital, Haikou, China
| |
Collapse
|
7
|
Xu LL, Zhou XJ, Zhang H. An Update on the Genetics of IgA Nephropathy. J Clin Med 2023; 13:123. [PMID: 38202130 PMCID: PMC10780034 DOI: 10.3390/jcm13010123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 12/15/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024] Open
Abstract
Immunoglobulin A (IgA) nephropathy (IgAN), the most common form of glomerulonephritis, is one of the leading causes of end-stage kidney disease (ESKD). It is widely believed that genetic factors play a significant role in the development of IgAN. Previous studies of IgAN have provided important insights to unravel the genetic architecture of IgAN and its potential pathogenic mechanisms. The genome-wide association studies (GWASs) together have identified over 30 risk loci for IgAN, which emphasizes the importance of IgA production and regulation in the pathogenesis of IgAN. Follow-up fine-mapping studies help to elucidate the candidate causal variant and the potential pathogenic molecular pathway and provide new potential therapeutic targets. With the rapid development of next-generation sequencing technologies, linkage studies based on whole-genome sequencing (WGS)/whole-exome sequencing (WES) also identify rare variants associated with IgAN, accounting for some of the missing heritability. The complexity of pathogenesis and phenotypic variability may be better understood by integrating genetics, epigenetics, and environment. We have compiled a review summarizing the latest advancements in genetic studies on IgAN. We similarly summarized relevant studies examining the involvement of epigenetics in the pathogenesis of IgAN. Future directions and challenges in this field are also proposed.
Collapse
Affiliation(s)
- Lin-Lin Xu
- Renal Division, Peking University First Hospital, Beijing 100034, China; (L.-L.X.); (H.Z.)
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing 100034, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing 100034, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing 100034, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing 100034, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100034, China
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Beijing 100034, China; (L.-L.X.); (H.Z.)
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing 100034, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing 100034, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing 100034, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing 100034, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100034, China
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Beijing 100034, China; (L.-L.X.); (H.Z.)
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing 100034, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing 100034, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing 100034, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing 100034, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100034, China
| |
Collapse
|
8
|
de Vries PS, Conomos MP, Singh K, Nicholson CJ, Jain D, Hasbani NR, Jiang W, Lee S, Lino Cardenas CL, Lutz SM, Wong D, Guo X, Yao J, Young EP, Tcheandjieu C, Hilliard AT, Bis JC, Bielak LF, Brown MR, Musharoff S, Clarke SL, Terry JG, Palmer ND, Yanek LR, Xu H, Heard-Costa N, Wessel J, Selvaraj MS, Li RH, Sun X, Turner AW, Stilp AM, Khan A, Newman AB, Rasheed A, Freedman BI, Kral BG, McHugh CP, Hodonsky C, Saleheen D, Herrington DM, Jacobs DR, Nickerson DA, Boerwinkle E, Wang FF, Heiss G, Jun G, Kinney GL, Sigurslid HH, Doddapaneni H, Hall IM, Bensenor IM, Broome J, Crapo JD, Wilson JG, Smith JA, Blangero J, Vargas JD, Mosquera JV, Smith JD, Viaud-Martinez KA, Ryan KA, Young KA, Taylor KD, Lange LA, Emery LS, Bittencourt MS, Budoff MJ, Montasser ME, Yu M, Mahaney MC, Mahamdeh MS, Fornage M, Franceschini N, Lotufo PA, Natarajan P, Wong Q, Mathias RA, Gibbs RA, Do R, Mehran R, Tracy RP, Kim RW, Nelson SC, Damrauer SM, Kardia SL, Rich SS, Fuster V, Napolioni V, Zhao W, Tian W, Yin X, Min YI, Manning AK, Peloso G, Kelly TN, O’Donnell CJ, Morrison AC, Curran JE, Zapol WM, Bowden DW, Becker LC, Correa A, Mitchell BD, Psaty BM, Carr JJ, Pereira AC, Assimes TL, Stitziel NO, Hokanson JE, Laurie CA, Rotter JI, Vasan RS, Post WS, Peyser PA, Miller CL, Malhotra R. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification. NATURE CARDIOVASCULAR RESEARCH 2023; 2:1159-1172. [PMID: 38817323 PMCID: PMC11138106 DOI: 10.1038/s44161-023-00375-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 10/25/2023] [Indexed: 06/01/2024]
Abstract
Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC (ARSE and MMP16), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease.
Collapse
Affiliation(s)
- Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Matthew P. Conomos
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Kuldeep Singh
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Christopher J. Nicholson
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Deepti Jain
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Natalie R. Hasbani
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Wanlin Jiang
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Sujin Lee
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Christian L Lino Cardenas
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Sharon M. Lutz
- PRecisiOn Medicine Translational Research (PROMoTeR)
Center, Department of Population Medicine, Harvard Medical School and Harvard
Pilgrim Health Care Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of
Public Health, Boston, MA, USA
| | - Doris Wong
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, 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, 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, USA
| | - Erica P. Young
- Cardiovascular Division, Department of Internal Medicine,
Washington University School of Medicine, St. Louis, MO, USA
| | - Catherine Tcheandjieu
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, USA
| | - Austin T. Hilliard
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Palo Alto Veterans Institute for Research, Palo Alto, CA,
USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of
Medicine, University of Washington, Seattle, WA, USA
| | - Lawrence F. Bielak
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Michael R. Brown
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Shaila Musharoff
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Genetics, Stanford University School of
Medicine, Stanford, CA, USA
| | - Shoa L. Clarke
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, USA
| | - James G. Terry
- Department of Radiology, Vanderbilt Translational and
Clinical Cardiovascular Research Center, Vanderbilt University Medical Center,
Nashville, TN, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of
Medicine, Winston-Salem, NC, USA
| | - Lisa R. Yanek
- Division of General Internal Medicine, Department of
Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition,
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD,
USA
| | - Nancy Heard-Costa
- Boston University School of Medicine, Boston, MA,
USA
- Boston University and National Heart, Lung, and Blood
Institute’s Framingham Heart Study, Framingham, MA, USA
| | - Jennifer Wessel
- Department of Epidemiology, Fairbanks School of Public
Health, Indiana University, Indianapolis, IN, USA
- Diabetes Translational Research Center, Indiana
University, Indianapolis, IN, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic
Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad
Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston,
MA, USA
| | - Rebecca H. Li
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Xiao Sun
- School of Public Health and Tropical Medicine, Department
of Epidemiology, Tulane University, New Orleans, LA, USA
- College of Medicine, Department of Medicine, Division of
Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Adam W. Turner
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Adrienne M. Stilp
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Alyna Khan
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Anne B. Newman
- Department of Epidemiology, Graduate School of Public
Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Asif Rasheed
- Center For Non-Communicable Diseases, Karachi,
Pakistan
| | - Barry I Freedman
- Section on Nephrology, Department of Internal Medicine,
Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Brian G. Kral
- Division of Cardiology, Department of Medicine, Johns
Hopkins University School of Medicine, Baltimore, MD, USA
| | - Caitlin P. McHugh
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Chani Hodonsky
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Danish Saleheen
- Center For Non-Communicable Diseases, Karachi,
Pakistan
- Department of Medicine, Columbia University Irving
Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving
Medical Center, New York, NY, USA
| | - David M. Herrington
- Department of Internal Medicine, Section of
Cardiovascular Medicine, Wake Forest School of Medicine, Winston-Salem, NC,
USA
| | - David R. Jacobs
- Division of Epidemiology and Community Health, University
of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Deborah A. Nickerson
- Department of Genome Sciences, University of Washington,
Seattle, WA, USA
- Northwest Genomics Center, University of Washington,
Seattle, WA, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of
Medicine, Houston, TX, USA
| | - Fei Fei Wang
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Gerardo Heiss
- Department of Epidemiology, Gillings School of Global
Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Goo Jun
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Greg L. Kinney
- Department of Epidemiology, Colorado School of Public
Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Haakon H. Sigurslid
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | | | - Ira M. Hall
- Yale Center for Genomic Health, Yale School of Medicine,
New Haven, CT, USA
| | - Isabela M. Bensenor
- Center for Clinical and Epidemiological Research,
University Hospital, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Jai Broome
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - James D. Crapo
- Department of Medicine, National Jewish Health, Denver,
CO, USA
| | - James G. Wilson
- Division of Cardiology, Beth Israel Deaconess Medical
Center, Boston, MA, USA
| | - Jennifer A. Smith
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research,
University of Michigan, Ann Arbor, MI, USA
| | - John Blangero
- Department of Human Genetics, University of Texas Rio
Grande Valley School of Medicine, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of
Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Jose D. Vargas
- Medstar Heart and Vascular Institute, Medstar Georgetown
University Hospital, Washington, DC, USA
| | - Jose Verdezoto Mosquera
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Joshua D. Smith
- Department of Genome Sciences, University of Washington,
Seattle, WA, USA
- Northwest Genomics Center, University of Washington,
Seattle, WA, USA
| | | | - Kathleen A. Ryan
- Division of Endocrinology, Diabetes and Nutrition,
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD,
USA
| | - Kendra A. Young
- Department of Epidemiology, Colorado School of Public
Health, University of Colorado Anschutz Medical Campus, Aurora, CO, 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, USA
| | - Leslie A. Lange
- Department of Medicine, University of Colorado Denver,
Anschutz Medical Campus, Aurora, CO, USA
| | - Leslie S. Emery
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Marcio S. Bittencourt
- Center for Clinical and Epidemiological Research,
University Hospital, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Matthew J. Budoff
- Department of Medicine, The Lundquist Institute for
Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - May E. Montasser
- Division of Endocrinology, Diabetes and Nutrition,
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD,
USA
| | - Miao Yu
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Michael C. Mahaney
- Department of Human Genetics, University of Texas Rio
Grande Valley School of Medicine, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of
Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Mohammed S Mahamdeh
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
- Institute of Molecular Medicine, McGovern Medical School,
The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global
Public health, University of North Carolina, Chapel Hill, NC, USA
| | - Paulo A. Lotufo
- Center for Clinical and Epidemiological Research,
University Hospital, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic
Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad
Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston,
MA, USA
| | - Quenna Wong
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Rasika A. Mathias
- Division of General Internal Medicine, Department of
Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Allergy and Clinical Immunology, Department
of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of
Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor
College of Medicine, Houston, TX, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine,
Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School
of Medicine at Mount Sinai, New York, NY, USA
| | - Roxana Mehran
- Icahn School of Medicine at Mount Sinai, New York, NY,
USA
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine, Robert
Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA
| | | | - Sarah C. Nelson
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center,
Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine,
University of Pennsylvania, Philadelphia, PA, USA
| | - Sharon L.R. Kardia
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Valentin Fuster
- Centro Nacional de Investigaciones Cardiovasculares
Carlos III, Madrid, Spain
- Mount Sinai Heart Center, New York, NY, USA
| | - Valerio Napolioni
- Genomic And Molecular Epidemiology (GAME) Lab, School of
Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Wei Zhao
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Wenjie Tian
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Xianyong Yin
- Department of Biostatistics and Center for Statistical
Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Yuan-I Min
- Jackson Heart Study, Department of Medicine, University
of Mississippi Medical Center, Jackson, MS, USA
| | - Alisa K. Manning
- Clinical and Translation Epidemiology Unit, Department of
Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical and Population
Genetics, Broad Institute, Cambridge, MA, USA
| | - Gina Peloso
- Department of Biostatistics, Boston University School of
Public Health, Boston, MA, USA
| | - Tanika N. Kelly
- College of Medicine, Department of Medicine, Division of
Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Christopher J. O’Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women’s Hospital,
Boston, MA, USA
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne E. Curran
- Department of Human Genetics, University of Texas Rio
Grande Valley School of Medicine, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of
Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Warren M. Zapol
- Department of Anesthesia, Critical Care and Pain Medicine
at Massachusetts General Hospital, Boston, MA, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest School of
Medicine, Winston-Salem, NC, USA
| | - Lewis C. Becker
- Division of Cardiology, Department of Medicine, Johns
Hopkins University School of Medicine, Baltimore, MD, USA
| | - Adolfo Correa
- Jackson Heart Study, Department of Medicine, University
of Mississippi Medical Center, Jackson, MS, USA
- Department of Population Health Science, University of
Mississippi Medical Center, Jackson, MS, USA
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition,
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD,
USA
- Geriatrics Research and Education Clinical Center,
Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of
Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington,
Seattle, WA, USA
- Department of Health Services, University of Washington,
Seattle, WA, USA
| | - John Jeffrey Carr
- Department of Radiology, Vanderbilt Translational and
Clinical Cardiovascular Research Center, Vanderbilt University Medical Center,
Nashville, TN, USA
| | - Alexandre C. Pereira
- Department of Genetics, Harvard Medical School, Boston,
MA, USA
- Laboratory of Genetics and Molecular Cardiology, Heart
Institute, University of São Paulo, São Paulo, Brazil
| | - Themistocles L. Assimes
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, USA
| | - Nathan O. Stitziel
- Cardiovascular Division, Department of Internal Medicine,
Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of
Medicine, St. Louis, MO, USA
- McDonnell Genome Institute, Washington University School
of Medicine, St. Louis, MO, USA
| | - John E. Hokanson
- Department of Epidemiology, Colorado School of Public
Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Cecelia A. Laurie
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - 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, USA
| | - Ramachandran S. Vasan
- Boston University and National Heart, Lung, and Blood
Institute’s Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Boston University School of
Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of
Public Health, Boston, MA, USA
| | - Wendy S. Post
- Division of Cardiology, Department of Medicine, Johns
Hopkins University School of Medicine, Baltimore, MD, USA
| | - Patricia A. Peyser
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Clint L. Miller
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Rajeev Malhotra
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| |
Collapse
|
9
|
Radhika A, Burgula S, Badapanda C, Hussain T, Naushad SM. Elucidation of genetic determinants of dyslipidaemia using a global screening array for the early detection of coronary artery disease. Mamm Genome 2023; 34:632-643. [PMID: 37668737 DOI: 10.1007/s00335-023-10017-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 08/16/2023] [Indexed: 09/06/2023]
Abstract
Dyslipidemia is a major risk factor for the development of coronary artery disease (CAD). Understanding the genetic determinants of dyslipidemia can provide valuable information on the pathogenesis of CAD and aid in the development of early detection strategies. In this study, we used a Global Screening Array (GSA) to elucidate the genetic factors associated with dyslipidemia and their potential role in the prediction of CAD. We conducted a GSA-based association study in 265 subjects to identify the genetic loci associated with dyslipidemia traits using Multiple Linear Regression (MLR) and Logistic Regression (LR), Classification and Regression Tree (CART), and Manhattan plots. We identified an association between dyslipidemia and variants identified in genes such as JCAD, GLIS3, CD38, FN1, CELSR2, MTNR1B, GIPR, DYM, APOB, APOE, ADCY5. The MLR models explained 62%, 71%, and 81% of the variability in HDL, LDL, and triglycerides, respectively. The Area Under the Curve (AUC) values in the LR models of HDL, LDL, and triglycerides were 1.00, 0.94, and 0.95, respectively. CART models identified novel gene-gene interactions influencing the risk for dyslipidemia. To conclude, we have identified the association of 12 SNVs with dyslipidemia and demonstrated their clinical utility in four different models such as MLR, LR, CART, and Manhattan plots. The identified genetic variants and associated pathways shed light on the underlying biology of dyslipidemia and offer potential avenues for precision medicine strategies in the management of CAD.
Collapse
Affiliation(s)
- Ananthaneni Radhika
- Genomics Division, Yoda Lifeline Diagnostics Pvt Ltd, 6-3-862/A, Lal Bungalow Add On, Ameerpet, Hyderabad, 500016, India
- Department of Microbiology, Osmania University, Taranaka, Hyderabad, 500007, India
| | - Sandeepta Burgula
- Department of Microbiology, Osmania University, Taranaka, Hyderabad, 500007, India.
| | - Chandan Badapanda
- Genomics Division, Yoda Lifeline Diagnostics Pvt Ltd, 6-3-862/A, Lal Bungalow Add On, Ameerpet, Hyderabad, 500016, India
| | - Tajamul Hussain
- Research Chair for Biomedical Applications of Nanomaterials, Biochemistry Department, College of Science, King Saud University, 11451, Riyadh, Saudi Arabia
- Center of Excellence in Biotechnology Research, King Saud University, 11451, Riyadh, Saudi Arabia
| | - Shaik Mohammad Naushad
- Genomics Division, Yoda Lifeline Diagnostics Pvt Ltd, 6-3-862/A, Lal Bungalow Add On, Ameerpet, Hyderabad, 500016, India.
| |
Collapse
|
10
|
Yu C, Bakshi A, Watts GF, Renton AE, Fulton‐Howard B, Goate AM, Natarajan P, Chasman DI, Robman L, Woods RL, Guymer R, Wolfe R, Thao LTP, McNeil JJ, Tonkin AM, Nicholls SJ, Lacaze P. Genome-Wide Association Study of Cardiovascular Resilience Identifies Protective Variation in the CETP Gene. J Am Heart Assoc 2023; 12:e031459. [PMID: 37929782 PMCID: PMC10727421 DOI: 10.1161/jaha.123.031459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/05/2023] [Indexed: 11/07/2023]
Abstract
Background The risk of atherosclerotic cardiovascular disease (ASCVD) increases sharply with age. Some older individuals, however, remain unaffected despite high predicted risk. These individuals may carry cardioprotective genetic variants that contribute to resilience. Our aim was to assess whether asymptomatic older individuals without prevalent ASCVD carry cardioprotective genetic variants that contribute to ASCVD resilience. Methods and Results We performed a genome-wide association study using a 10-year predicted ASCVD risk score as a quantitative trait, calculated only in asymptomatic older individuals aged ≥70 years without prevalent ASCVD. Our discovery genome-wide association study of N=12 031 ASCVD event-free individuals from the ASPREE (Aspirin in Reducing Events in the Elderly) trial identified 2 independent variants, rs9939224 (P<5×10-8) and rs56156922 (P<10-6), in the CETP (cholesteryl ester transfer protein) gene. The CETP gene is a regulator of plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and lipoprotein(a) levels, and it is a therapeutic drug target. The associations were replicated in the UK Biobank (subpopulation of N=13 888 individuals aged ≥69 years without prevalent ASCVD). Carriers of the identified CETP variants (versus noncarriers) had higher plasma high-density lipoprotein cholesterol levels, lower plasma low-density lipoprotein cholesterol levels, and reduced risk of incident ASCVD events during follow-up. Expression quantitative trait loci analysis predicted the identified CETP variants reduce CETP gene expression across various tissues. Previously reported associations between genetic CETP inhibition and increased risk of age-related macular degeneration were not observed among the 3917 ASPREE trial participants with retinal imaging and genetic data available. Conclusions Common genetic variants in the CETP gene region are associated with cardiovascular resilience during aging. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT01038583.
Collapse
Affiliation(s)
- Chenglong Yu
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
| | - Andrew Bakshi
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
| | - Gerald F. Watts
- School of MedicineUniversity of Western AustraliaPerthWAAustralia
- Lipid Disorders Clinic, Cardiometabolic Service, Department of CardiologyRoyal Perth HospitalPerthWAAustralia
| | - Alan E. Renton
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNY
| | - Brian Fulton‐Howard
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNY
| | - Alison M. Goate
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNY
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMA
- Program in Population and Medical Genetics and the Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMA
- Department of MedicineHarvard Medical SchoolBostonMA
| | - Daniel I. Chasman
- Preventive Medicine Division, Brigham and Women’s HospitalHarvard Medical SchoolBostonMA
| | - Liubov Robman
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
- Centre for Eye Research AustraliaThe University of Melbourne, Royal Victorian Eye and Ear HospitalMelbourneVICAustralia
| | - Robyn L. Woods
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
| | - Robyn Guymer
- Centre for Eye Research AustraliaThe University of Melbourne, Royal Victorian Eye and Ear HospitalMelbourneVICAustralia
| | - Rory Wolfe
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
| | - Le Thi Phuong Thao
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
| | - John J. McNeil
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
| | - Andrew M. Tonkin
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
| | - Stephen J. Nicholls
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
- Monash Cardiovascular Research Centre, Victorian Heart InstituteMonash UniversityClaytonVICAustralia
| | - Paul Lacaze
- School of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia
| |
Collapse
|
11
|
Li X, Chen H, Selvaraj MS, Van Buren E, Zhou H, Wang Y, Sun R, McCaw ZR, Yu Z, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Brody JA, Cade BE, Carson AP, Carlson JC, Chami N, Chen YDI, Curran JE, de Vries PS, Fornage M, Franceschini N, Freedman BI, Gu C, Heard-Costa NL, He J, Hou L, Hung YJ, Irvin MR, Kaplan RC, Kardia SL, Kelly T, Konigsberg I, Kooperberg C, Kral BG, Li C, Loos RJ, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Palmer ND, Peyser PA, Psaty BM, Raffield LM, Redline S, Reiner AP, Rich SS, Sitlani CM, Smith JA, Taylor KD, Tiwari H, Vasan RS, Wang Z, Yanek LR, Yu B, Rice KM, Rotter JI, Peloso GM, Natarajan P, Li Z, Liu Z, Lin X. A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.30.564764. [PMID: 37961350 PMCID: PMC10634938 DOI: 10.1101/2023.10.30.564764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of NIPSNAP3A and an intergenic region on chromosome 1.
Collapse
Affiliation(s)
- Xihao Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Margaret Sunitha Selvaraj
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Hufeng Zhou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ryan Sun
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Zachary R. McCaw
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zhi Yu
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Donna K. Arnett
- Provost Office, University of South Carolina, Columbia, SC, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Brian E. Cade
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jenna C. Carlson
- Department of Human Genetics and Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nathalie Chami
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 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, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, the University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Barry I. Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Charles Gu
- Division of Biology & Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Nancy L. Heard-Costa
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Yi-Jen Hung
- Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Marguerite R. Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Tanika Kelly
- Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Iain Konigsberg
- Department of Biomedical Informatics, University of Colorado, Aurora, CO, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G. Kral
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michael C. Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Lisa W. Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A. Mathias
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan L. Minster
- Department of Human Genetics and Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - May E. Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Departments of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Alexander P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Departments of Epidemiology, University of Washington, Seattle, WA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Colleen M. Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 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, USA
| | - Hemant Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham, MA, USA
- Department of Quantitative and Qualitative Health Sciences, UT Health San Antonio School of Public Health, San Antonia, TX, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa R. Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Kenneth M. Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - 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, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Pradeep Natarajan
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zhonghua Liu
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
| |
Collapse
|
12
|
Kalnina I, Gudra D, Silamikelis I, Viksne K, Roga A, Skinderskis E, Fridmanis D, Klovins J. Variations in the Relative Abundance of Gut Bacteria Correlate with Lipid Profiles in Healthy Adults. Microorganisms 2023; 11:2656. [PMID: 38004667 PMCID: PMC10673050 DOI: 10.3390/microorganisms11112656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/04/2023] [Accepted: 10/26/2023] [Indexed: 11/26/2023] Open
Abstract
The gut microbiome is a versatile system regulating numerous aspects of host metabolism. Among other traits, variations in the composition of gut microbial communities are related to blood lipid patterns and hyperlipidaemia, yet inconsistent association patterns exist. This study aims to assess the relationships between the composition of the gut microbiome and variations in lipid profiles among healthy adults. This study used data and samples from 23 adult participants of a previously conducted dietary intervention study. Circulating lipid measurements and whole-metagenome sequences of the gut microbiome were derived from 180 blood and faecal samples collected from eight visits distributed across an 11-week study. Lipid-related variables explained approximately 4.5% of the variation in gut microbiome compositions, with higher effects observed for total cholesterol and high-density lipoproteins. Species from the genera Odoribacter, Anaerostipes, and Parabacteroides correlated with increased serum lipid levels, whereas probiotic species like Akkermansia muciniphila were more abundant among participants with healthier blood lipid profiles. An inverse correlation with serum cholesterol was also observed for Massilistercora timonensis, a player in regulating lipid turnover. The observed correlation patterns add to the growing evidence supporting the role of the gut microbiome as an essential regulator of host lipid metabolism.
Collapse
Affiliation(s)
- Ineta Kalnina
- Latvian Biomedical Research and Study Centre 1, LV-1067 Riga, Latvia
| | | | | | | | | | | | | | | |
Collapse
|
13
|
Wang Y, Selvaraj MS, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Cade BE, Carlson JC, Carson AP, Chen YDI, Curran JE, de Vries PS, Dutcher SK, Ellinor PT, Floyd JS, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, Guo X, He J, Heard-Costa N, Hildalgo B, Hou L, Irvin MR, Joehanes R, Kaplan RC, Kardia SL, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJ, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Murabito JM, Naseri T, O'Connell JR, Palmer ND, Preuss MH, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Ruepena MS, Sheu WHH, Smith JA, Smith A, Tiwari HK, Tsai MY, Viaud-Martinez KA, Wang Z, Yanek LR, Zhao W, Rotter JI, Lin X, Natarajan P, Peloso GM. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study. Am J Hum Genet 2023; 110:1704-1717. [PMID: 37802043 PMCID: PMC10577076 DOI: 10.1016/j.ajhg.2023.09.003] [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: 06/22/2023] [Revised: 09/01/2023] [Accepted: 09/01/2023] [Indexed: 10/08/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.
Collapse
Affiliation(s)
- Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Xihao Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jacob A Holdcraft
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donna K Arnett
- Provost Office, University of South Carolina, Columbia, SC, USA; Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, SC, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Brian E Cade
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jenna C Carlson
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 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, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Susan K Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | | | - Richard A Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, 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, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA; Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bertha Hildalgo
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sharon Lr Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Tanika N Kelly
- Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Ryan Kim
- Psomagen, Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Changwei Li
- Tulane University Translational Science Institute, New Orleans, LA, USA; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
| | - Don Lloyd-Jone
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Ruth Jf Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; NNF Center for Basic Metabolic Research, University of Copenhagen, Cophenhagen, Denmark
| | - Michael C Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Lisa W Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan L Minster
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - May E Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne M Murabito
- Framingham Heart Study, Framingham, MA, USA; Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Take Naseri
- Naseri & Associates Public Health Consultancy Firm and Family Health Clinic, Apia, Samoa; International Health Institute, School of Public Health, Brown University, Providence, RI, USA
| | - Jeffrey R O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | - Wayne H-H Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institute (NHRI), Miaoli County, Taiwan
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Albert Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama, Birmingham, AL, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - 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, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
| |
Collapse
|
14
|
Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North K, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, Raffield LM. Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.10.555215. [PMID: 37745480 PMCID: PMC10515765 DOI: 10.1101/2023.09.10.555215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
Collapse
Affiliation(s)
- Min-Zhi Jiang
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
| | - Sheila M. Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Xihao Li
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Adrienne Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Erin Buth
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Fei Fei Wang
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Regina Manansala
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO) WHO Collaborating Centre, University of Antwerp, Antwerp, BE
| | | | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, 130024, China
| | - Linda M. Polfus
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, 90033, USA
| | - Shabnam Salimi
- Department of Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Lisa R. Yanek
- Department of Medicine, General Internal Medicine, Johns Hopkins University School of Medicine, 1830 E Monument St Rm 8024, Baltimore, MD, 21287, USA
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Russell P. Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, 200 Jeanette Lancaster Way, Charlottesville, VA, 22903, USA
| | - 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, 1124 W. Carson Street, Torrance, CA, 90502, USA
| | - Braxton D. Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Joshua P. Lewis
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA, 98101, USA
| | - Katherine A. Pratte
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Edwin K. Silverman
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kari North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Rasika A. Mathias
- Department of Medicine, Allergy and Clinical Immunology, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Cir JHAAC Room 3B53, Baltimore, MD, 21287, USA
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - Biqi Wang
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Arnita F. Norwood
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Richard A. Gibbs
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, H3A 1G1, Canada
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Emelia J. Benjamin
- Department of Medicine, Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, 01702, USA
| | - Alexander P. Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98105, USA
| | - Russell P. Bowler
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Paul L. Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
| | | |
Collapse
|
15
|
Deflaux N, Selvaraj MS, Condon HR, Mayo K, Haidermota S, Basford MA, Lunt C, Philippakis AA, Roden DM, Denny JC, Musick A, Collins R, Allen N, Effingham M, Glazer D, Natarajan P, Bick AG. Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis. Nat Commun 2023; 14:5419. [PMID: 37669985 PMCID: PMC10480504 DOI: 10.1038/s41467-023-41185-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 08/24/2023] [Indexed: 09/07/2023] Open
Abstract
Recently, large scale genomic projects such as All of Us and the UK Biobank have introduced a new research paradigm where data are stored centrally in cloud-based Trusted Research Environments (TREs). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conduct a Genome-Wide Association Study of standard lipid measures using two approaches: meta-analysis and pooled analysis. Comparison of full summary data from both approaches with an external study shows strong correlation of known loci with lipid levels (R2 ~ 83-97%). Importantly, 90 variants meet the significance threshold only in the meta-analysis and 64 variants are significant only in pooled analysis, with approximately 20% of variants in each of those groups being most prevalent in non-European, non-Asian ancestry individuals. These findings have important implications, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.
Collapse
Affiliation(s)
| | - Margaret Sunitha Selvaraj
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Henry Robert Condon
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kelsey Mayo
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sara Haidermota
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Melissa A Basford
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Chris Lunt
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | | | - Dan M Roden
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Joshua C Denny
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Anjene Musick
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Rory Collins
- Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK
- UK Biobank, Cheadle, Stockport, UK
| | - Naomi Allen
- Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK
- UK Biobank, Cheadle, Stockport, UK
| | | | | | - Pradeep Natarajan
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Alexander G Bick
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
| |
Collapse
|
16
|
McCaw ZR, O'Dushlaine C, Somineni H, Bereket M, Klein C, Karaletsos T, Casale FP, Koller D, Soare TW. An allelic-series rare-variant association test for candidate-gene discovery. Am J Hum Genet 2023; 110:1330-1342. [PMID: 37494930 PMCID: PMC10432147 DOI: 10.1016/j.ajhg.2023.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/30/2023] [Accepted: 07/01/2023] [Indexed: 07/28/2023] Open
Abstract
Allelic series are of candidate therapeutic interest because of the existence of a dose-response relationship between the functionality of a gene and the degree or severity of a phenotype. We define an allelic series as a collection of variants in which increasingly deleterious mutations lead to increasingly large phenotypic effects, and we have developed a gene-based rare-variant association test specifically targeted to identifying genes containing allelic series. Building on the well-known burden test and sequence kernel association test (SKAT), we specify a variety of association models covering different genetic architectures and integrate these into a Coding-Variant Allelic-Series Test (COAST). Through extensive simulations, we confirm that COAST maintains the type I error and improves the power when the pattern of coding-variant effect sizes increases monotonically with mutational severity. We applied COAST to identify allelic-series genes for four circulating-lipid traits and five cell-count traits among 145,735 subjects with available whole-exome sequencing data from the UK Biobank. Compared with optimal SKAT (SKAT-O), COAST identified 29% more Bonferroni-significant associations with circulating-lipid traits, on average, and 82% more with cell-count traits. All of the gene-trait associations identified by COAST have corroborating evidence either from rare-variant associations in the full cohort (Genebass, n = 400,000) or from common-variant associations in the GWAS Catalog. In addition to detecting many gene-trait associations present in Genebass by using only a fraction (36.9%) of the sample, COAST detects associations, such as that between ANGPTL4 and triglycerides, that are absent from Genebass but that have clear common-variant support.
Collapse
Affiliation(s)
| | | | | | | | | | | | - Francesco Paolo Casale
- Institute of AI for Health, Helmholtz Munich, Neuherberg, Germany; Helmholtz Pioneer Campus, Helmholtz Munich, Neuherberg, Germany; School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | | | | |
Collapse
|
17
|
Kasahara K, Kerby RL, Zhang Q, Pradhan M, Mehrabian M, Lusis AJ, Bergström G, Bäckhed F, Rey FE. Gut bacterial metabolism contributes to host global purine homeostasis. Cell Host Microbe 2023; 31:1038-1053.e10. [PMID: 37279756 PMCID: PMC10311284 DOI: 10.1016/j.chom.2023.05.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/25/2023] [Accepted: 05/10/2023] [Indexed: 06/08/2023]
Abstract
The microbes and microbial pathways that influence host inflammatory disease progression remain largely undefined. Here, we show that variation in atherosclerosis burden is partially driven by gut microbiota and is associated with circulating levels of uric acid (UA) in mice and humans. We identify gut bacterial taxa spanning multiple phyla, including Bacillota, Fusobacteriota, and Pseudomonadota, that use multiple purines, including UA as carbon and energy sources anaerobically. We identify a gene cluster that encodes key steps of anaerobic purine degradation and that is widely distributed among gut-dwelling bacteria. Furthermore, we show that colonization of gnotobiotic mice with purine-degrading bacteria modulates levels of UA and other purines in the gut and systemically. Thus, gut microbes are important drivers of host global purine homeostasis and serum UA levels, and gut bacterial catabolism of purines may represent a mechanism by which gut bacteria influence health.
Collapse
Affiliation(s)
- Kazuyuki Kasahara
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Robert L Kerby
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Qijun Zhang
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Meenakshi Pradhan
- Department of Molecular and Clinical Medicine, Wallenberg Laboratory, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Margarete Mehrabian
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Aldons J Lusis
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Göran Bergström
- Department of Molecular and Clinical Medicine, Wallenberg Laboratory, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden; Region Västra Götaland, Sahlgrenska University Hospital, Department of Clinical Physiology, Gothenburg, Sweden
| | - Fredrik Bäckhed
- Department of Molecular and Clinical Medicine, Wallenberg Laboratory, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden; Region Västra Götaland, Sahlgrenska University Hospital, Department of Clinical Physiology, Gothenburg, Sweden; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Federico E Rey
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA.
| |
Collapse
|
18
|
Bocher O, Willer CJ, Zeggini E. Unravelling the genetic architecture of human complex traits through whole genome sequencing. Nat Commun 2023; 14:3520. [PMID: 37316478 DOI: 10.1038/s41467-023-39259-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 06/06/2023] [Indexed: 06/16/2023] Open
Affiliation(s)
- Ozvan Bocher
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Computational Medicine and Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Ismaninger Str. 22, 81675, Munich, Germany.
| |
Collapse
|
19
|
Calling and Phasing of Single-Nucleotide and Structural Variants of the LDLR Gene Using Oxford Nanopore MinION. Int J Mol Sci 2023; 24:ijms24054471. [PMID: 36901902 PMCID: PMC10003201 DOI: 10.3390/ijms24054471] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/27/2023] [Accepted: 02/22/2023] [Indexed: 03/12/2023] Open
Abstract
The LDLR locus has clinical significance for lipid metabolism, Mendelian familial hypercholesterolemia (FH), and common lipid metabolism-related diseases (coronary artery disease and Alzheimer's disease), but its intronic and structural variants are underinvestigated. The aim of this study was to design and validate a method for nearly complete sequencing of the LDLR gene using long-read Oxford Nanopore sequencing technology (ONT). Five PCR amplicons from LDLR of three patients with compound heterozygous FH were analyzed. We used standard workflows of EPI2ME Labs for variant calling. All rare missense and small deletion variants detected previously by massively parallel sequencing and Sanger sequencing were identified using ONT. One patient had a 6976 bp deletion (exons 15 and 16) that was detected by ONT with precisely located breakpoints between AluY and AluSx1. Trans-heterozygous associations between mutation c.530C>T and c.1054T>C, c.2141-966_2390-330del, and c.1327T>C, and between mutations c.1246C>T and c.940+3_940+6del of LDLR, were confirmed. We demonstrated the ability of ONT to phase variants, thereby enabling haplotype assignment for LDLR with personalized resolution. The ONT-based method was able to detect exonic variants with the additional benefit of intronic analysis in one run. This method can serve as an efficient and cost-effective tool for diagnosing FH and conducting research on extended LDLR haplotype reconstruction.
Collapse
|
20
|
Rethy L, Khan SS. Primary prevention of heart failure: targeting dyslipidemia and atherosclerotic pathways. Eur J Prev Cardiol 2023:zwad044. [PMID: 36804691 DOI: 10.1093/eurjpc/zwad044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 02/07/2023] [Indexed: 02/22/2023]
Affiliation(s)
- Leah Rethy
- University of Pennsylvania Perelman School of Medicine, Department of Medicine, Philadelphia, PA
| | - Sadiya S Khan
- Northwestern University Feinberg School of Medicine, Department of Medicine, Chicago, IL
| |
Collapse
|
21
|
Genetic Heterogeneity of Familial Hypercholesterolemia: Repercussions for Molecular Diagnosis. Int J Mol Sci 2023; 24:ijms24043224. [PMID: 36834635 PMCID: PMC9961636 DOI: 10.3390/ijms24043224] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/02/2023] [Accepted: 02/03/2023] [Indexed: 02/10/2023] Open
Abstract
Genetics of Familial Hypercholesterolemia (FH) is ascribable to pathogenic variants in genes encoding proteins leading to an impaired LDL uptake by the LDL receptor (LDLR). Two forms of the disease are possible, heterozygous (HeFH) and homozygous (HoFH), caused by one or two pathogenic variants, respectively, in the three main genes that are responsible for the autosomal dominant disease: LDLR, APOB and PCSK9 genes. The HeFH is the most common genetic disease in humans, being the prevalence about 1:300. Variants in the LDLRAP1 gene causes FH with a recessive inheritance and a specific APOE variant was described as causative of FH, contributing to increase FH genetic heterogeneity. In addition, variants in genes causing other dyslipidemias showing phenotypes overlapping with FH may mimic FH in patients without causative variants (FH-phenocopies; ABCG5, ABCG8, CYP27A1 and LIPA genes) or act as phenotype modifiers in patients with a pathogenic variant in a causative gene. The presence of several common variants was also considered a genetic basis of FH and several polygenic risk scores (PRS) have been described. The presence of a variant in modifier genes or high PRS in HeFH further exacerbates the phenotype, partially justifying its variability among patients. This review aims to report the updates on the genetic and molecular bases of FH with their implication for molecular diagnosis.
Collapse
|