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Fernández-Gallego N, Castillo-González R, Moreno-Serna L, García-Cívico AJ, Sánchez-Martínez E, López-Sanz C, Fontes AL, Pimentel LL, Gradillas A, Obeso D, Neuhaus R, Ramírez-Huesca M, Ruiz-Fernández I, Nuñez-Borque E, Carrasco YR, Ibáñez B, Martín P, Blanco C, Barbas C, Barber D, Rodríguez-Alcalá LM, Villaseñor A, Esteban V, Sánchez-Madrid F, Jiménez-Saiz R. Allergic inflammation triggers dyslipidemia via IgG signalling. Allergy 2024; 79:2680-2699. [PMID: 38864116 DOI: 10.1111/all.16187] [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: 09/14/2023] [Revised: 05/02/2024] [Accepted: 05/04/2024] [Indexed: 06/13/2024]
Abstract
BACKGROUND Allergic diseases begin early in life and are often chronic, thus creating an inflammatory environment that may precede or exacerbate other pathologies. In this regard, allergy has been associated to metabolic disorders and with a higher risk of cardiovascular disease, but the underlying mechanisms remain incompletely understood. METHODS We used a murine model of allergy and atherosclerosis, different diets and sensitization methods, and cell-depleting strategies to ascertain the contribution of acute and late phase inflammation to dyslipidemia. Untargeted lipidomic analyses were applied to define the lipid fingerprint of allergic inflammation at different phases of allergic pathology. Expression of genes related to lipid metabolism was assessed in liver and adipose tissue at different times post-allergen challenge. Also, changes in serum triglycerides (TGs) were evaluated in a group of 59 patients ≥14 days after the onset of an allergic reaction. RESULTS We found that allergic inflammation induces a unique lipid signature that is characterized by increased serum TGs and changes in the expression of genes related to lipid metabolism in liver and adipose tissue. Alterations in blood TGs following an allergic reaction are independent of T-cell-driven late phase inflammation. On the contrary, the IgG-mediated alternative pathway of anaphylaxis is sufficient to induce a TG increase and a unique lipid profile. Lastly, we demonstrated an increase in serum TGs in 59 patients after undergoing an allergic reaction. CONCLUSION Overall, this study reveals that IgG-mediated allergic inflammation regulates lipid metabolism.
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Affiliation(s)
- Nieves Fernández-Gallego
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- Department of Immunology, Instituto de Investigación Sanitaria Hospital Universitario de La Princesa (IIS-Princesa), Universidad Autónoma de Madrid (UAM), Madrid, Spain
| | - Raquel Castillo-González
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- Department of Immunology, Ophthalmology and Ear, Nose and Throat (ENT), Universidad Complutense de Madrid, Madrid, Spain
| | - Lucía Moreno-Serna
- Department of Immunology, Instituto de Investigación Sanitaria Hospital Universitario de La Princesa (IIS-Princesa), Universidad Autónoma de Madrid (UAM), Madrid, Spain
| | - Antonio J García-Cívico
- Department of Basic Medical Sciences, Faculty of Medicine, Instituto de Medicina Molecular Aplicada (IMMA), Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
- Centro de Metabolómica y Bioanálisis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Elisa Sánchez-Martínez
- Department of Immunology, Instituto de Investigación Sanitaria Hospital Universitario de La Princesa (IIS-Princesa), Universidad Autónoma de Madrid (UAM), Madrid, Spain
| | - Celia López-Sanz
- Department of Immunology, Instituto de Investigación Sanitaria Hospital Universitario de La Princesa (IIS-Princesa), Universidad Autónoma de Madrid (UAM), Madrid, Spain
| | - Ana Luiza Fontes
- CBQF-Centro de Biotecnologia e Química Fina-Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Porto, Portugal
| | - Lígia L Pimentel
- CBQF-Centro de Biotecnologia e Química Fina-Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Porto, Portugal
| | - Ana Gradillas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - David Obeso
- Department of Basic Medical Sciences, Faculty of Medicine, Instituto de Medicina Molecular Aplicada (IMMA), Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
- Centro de Metabolómica y Bioanálisis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - René Neuhaus
- Department of Basic Medical Sciences, Faculty of Medicine, Instituto de Medicina Molecular Aplicada (IMMA), Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
- Centro de Metabolómica y Bioanálisis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | | | | | - Emilio Nuñez-Borque
- Department of Allergy and Immunology, Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Universidad Autónoma de Madrid (UAM), Madrid, Spain
| | - Yolanda R Carrasco
- Department of Immunology and Oncology, Centro Nacional de Biotecnología (CNB)-CSIC, Madrid, Spain
| | - Borja Ibáñez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- Department of Cardiology, Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Madrid, Spain
- CIBER de Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
| | - Pilar Martín
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- CIBER de Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
| | - Carlos Blanco
- Department of Allergy, Instituto de Investigación Sanitaria Hospital Universitario de La Princesa (IIS-Princesa), Madrid, Spain
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Domingo Barber
- Department of Basic Medical Sciences, Faculty of Medicine, Instituto de Medicina Molecular Aplicada (IMMA), Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Luis M Rodríguez-Alcalá
- CBQF-Centro de Biotecnologia e Química Fina-Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Porto, Portugal
| | - Alma Villaseñor
- Department of Basic Medical Sciences, Faculty of Medicine, Instituto de Medicina Molecular Aplicada (IMMA), Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
- Centro de Metabolómica y Bioanálisis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Vanesa Esteban
- Department of Allergy and Immunology, Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Universidad Autónoma de Madrid (UAM), Madrid, Spain
- Faculty of Medicine and Biomedicine, Universidad Alfonso X El Sabio, Madrid, Spain
| | - Francisco Sánchez-Madrid
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- Department of Immunology, Instituto de Investigación Sanitaria Hospital Universitario de La Princesa (IIS-Princesa), Universidad Autónoma de Madrid (UAM), Madrid, Spain
- CIBER de Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
| | - Rodrigo Jiménez-Saiz
- Department of Immunology, Instituto de Investigación Sanitaria Hospital Universitario de La Princesa (IIS-Princesa), Universidad Autónoma de Madrid (UAM), Madrid, Spain
- Department of Immunology and Oncology, Centro Nacional de Biotecnología (CNB)-CSIC, Madrid, Spain
- Department of Medicine, McMaster Immunology Research Centre (MIRC), Schroeder Allergy and Immunology Research Institute (SAIRI), McMaster University, Hamilton, Ontario, Canada
- Faculty of Experimental Sciences, Universidad Francisco de Vitoria (UFV), Madrid, Spain
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Liu Z, Zhou Y, Jin M, Liu S, Liu S, Yang K, Li H, Luo S, Jureti S, Wei M, Fu Z. Association of HMGCR rs17671591 and rs3761740 with lipidemia and statin response in Uyghurs and Han Chinese. PeerJ 2024; 12:e18144. [PMID: 39351366 PMCID: PMC11441381 DOI: 10.7717/peerj.18144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 08/30/2024] [Indexed: 10/04/2024] Open
Abstract
Background Dyslipidemia plays a very important role in the occurrence and development of cardiovascular disease (CVD). Genetic factors, including single nucleotide polymorphisms (SNPs), are one of the main risks of dyslipidemia. 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) is not only the rate-limiting enzyme step of endogenous cholesterol production, but also the therapeutic target of statins. Methods We investigated 405 Han Chinese and 373 Uyghur people who took statins for a period of time, recorded their blood lipid levels and baseline data before and after oral statin administration, and extracted DNA from each subject for SNP typing of HMGCR rs17671591 and rs3761740. The effects of HMGCR rs17671591 and rs3761740 on lipid levels and the effect of statins on lipid lowering in Han Chinese and Uyghur ethnic groups were studied. Results In this study, for rs17671591, the CC vs. TT+CT model was significantly correlated with the level of LDL-C before oral statin in the Uyghur population, but there were no correlations between rs17671591 and the level of blood lipid before oral statin in the Han population. The CC vs. TT+CT and CT vs. CC+TT models were significantly correlated with the level of LDL-C after oral statin in the Uyghur population. There was no significant correlation between rs3761740 with blood lipids before and after oral statin in the Han population. For rs3761740, before oral statin, the CC vs. AA+CA model was significantly correlated with the level of LDL-C, and the CA vs. CC+AA model was significantly correlated with the level of total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), and non-high density lipoprotein cholesterol (HDL-C) in the Uyghur population. After oral statin, the CC vs. AA+CA and CA vs. CC+AA models were significantly correlated with the level of TC, LDL-C, and apolipoprotein (APOB), and the C vs. A model was significantly correlated with the level of TC, triglyceride (TG), LDL-C, and APOB in the Uyghur population. Particularly, the CT vs. CC+TT model of rs17671591 was significantly correlated with the changes of LDL-C after oral statin in the Uyghur population. In this study, we also explored the association of rs17671591 and rs3761740 with the rate of dyslipidemia as a reference. Conclusion We found that HMGCR rs3761740 was correlated with the levels of TC, LDL-C, and non-HDL-C before and after oral statin in Uyghurs, but not with blood lipid levels in the Han population. In the Uyghur population, HMGCR rs17671591 was associated with the level of LDL-C before and after oral statin, and also affected the changes of LDL-C after oral statin.
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Affiliation(s)
- Ziyang Liu
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
- Xinjiang Medical University, Urumqi, Xinjiang, China
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Yang Zhou
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Menglong Jin
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Shuai Liu
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Sen Liu
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Kai Yang
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Huayin Li
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Sifu Luo
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Subinuer Jureti
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Mengwei Wei
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Zhenyan Fu
- The First Affiliated Hospital, Xinjiang Medical University, Urumqi, Xinjiang, China
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Koyama S, Yu Z, Choi SH, Jurgens SJ, Selvaraj MS, Klarin D, Huffman JE, Clarke SL, Trinh MN, Ravi A, Dron JS, Spinks C, Surakka I, Bhatnagar A, Lannery K, Hornsby W, Damrauer SM, Chang KM, Lynch JA, Assimes TL, Tsao PS, Rader DJ, Cho K, Peloso GM, Ellinor PT, Sun YV, Wilson PWF, Program MV, Natarajan P. Exome wide association study for blood lipids in 1,158,017 individuals from diverse populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.17.24313718. [PMID: 39371182 PMCID: PMC11451673 DOI: 10.1101/2024.09.17.24313718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
Abstract
Rare coding alleles play crucial roles in the molecular diagnosis of genetic diseases. However, the systemic identification of these alleles has been challenging due to their scarcity in the general population. Here, we discovered and characterized rare coding alleles contributing to genetic dyslipidemia, a principal risk for coronary artery disease, among over a million individuals combining three large contemporary genetic datasets (the Million Veteran Program, n = 634,535, UK Biobank, n = 431,178, and the All of Us Research Program, n = 92,304) totaling 1,158,017 multi-ancestral individuals. Unlike previous rare variant studies in lipids, this study included 238,243 individuals (20.6%) from non-European-like populations. Testing 2,997,401 rare coding variants from diverse backgrounds, we identified 800 exome-wide significant associations across 209 genes including 176 predicted loss of function and 624 missense variants. Among these exome-wide associations, 130 associations were driven by non-European-like populations. Associated alleles are highly enriched in functional variant classes, showed significant additive and recessive associations, exhibited similar effects across populations, and resolved pathogenicity for variants enriched in African or South-Asian populations. Furthermore, we identified 5 lipid-related genes associated with coronary artery disease (RORC, CFAP65, GTF2E2, PLCB3, and ZNF117). Among them, RORC is a potentially novel therapeutic target through the down regulation of LDLC by its silencing. This study provides resources and insights for understanding causal mechanisms, quantifying the expressivity of rare coding alleles, and identifying novel drug targets across diverse populations.
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Affiliation(s)
- Satoshi Koyama
- VA Boston Healthcare System, Boston, MA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Zhi Yu
- VA Boston Healthcare System, Boston, MA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Seung Hoan Choi
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Sean J. Jurgens
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
- Department of Experimental Cardiology, Heart Center, Heart Failure and Arrhythmias, Amsterdam UMC location University of Amsterdam, Amsterdam, Netherlands
| | - Margaret Sunitha Selvaraj
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Derek Klarin
- VA Palo Alto Healthcare System, Palo Alto, CA
- Department of Surgery, Stanford University School of Medicine, Stanford, CA
| | | | - Shoa L. Clarke
- VA Palo Alto Healthcare System, Palo Alto, CA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA
| | - Michael N. Trinh
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Akshaya Ravi
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Jacqueline S. Dron
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Catherine Spinks
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Ida Surakka
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA
| | - Aarushi Bhatnagar
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Kim Lannery
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Whitney Hornsby
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
- University of Pennsylvania, Philadelphia, PA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
- University of Pennsylvania, Philadelphia, PA
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT
- College of Nursing and Health Sciences, University of Massachusetts, Boston, MA
| | - Themistocles L. Assimes
- VA Palo Alto Healthcare System, Palo Alto, CA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA
| | - Philip S. Tsao
- VA Palo Alto Healthcare System, Palo Alto, CA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA
| | | | - Kelly Cho
- VA Boston Healthcare System, Boston, MA
- Massachusetts General Brigham, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Gina M. Peloso
- VA Boston Healthcare System, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Patrick T. Ellinor
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Yan V. Sun
- VA Atlanta Healthcare System, Decatur, GA
- Department of Epidemiology and Global Health, Emory University Rollins School of Public Health, Atlanta, GA
- Emory University School of Medicine, Atlanta, GA
| | - Peter WF. Wilson
- VA Atlanta Healthcare System, Decatur, GA
- Emory University School of Medicine, Atlanta, GA
| | | | - Pradeep Natarajan
- VA Boston Healthcare System, Boston, MA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
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Noordam R, Wang W, Nagarajan P, Wang H, Brown MR, Bentley AR, Hui Q, Kraja AT, Morrison JL, O'Connel JR, Lee S, Schwander K, Bartz TM, de las Fuentes L, Feitosa MF, Guo X, Hanfei X, Harris SE, Huang Z, Kals M, Lefevre C, Mangino M, Milaneschi Y, van der Most P, Pacheco NL, Palmer ND, Rao V, Rauramaa R, Sun Q, Tabara Y, Vojinovic D, Wang Y, Weiss S, Yang Q, Zhao W, Zhu W, Abu Yusuf Ansari M, Aschard H, Anugu P, Assimes TL, Attia J, Baker LD, Ballantyne C, Bazzano L, Boerwinkle E, Cade B, Chen HH, Chen W, Ida Chen YD, Chen Z, Cho K, De Anda-Duran I, Dimitrov L, Do A, Edwards T, Faquih T, Hingorani A, Fisher-Hoch SP, Gaziano JM, Gharib SA, Giri A, Ghanbari M, Grabe HJ, Graff M, Gu CC, He J, Heikkinen S, Hixson J, Ho YL, Hood MM, Houghton SC, Karvonen-Gutierrez CA, Kawaguchi T, Kilpeläinen TO, Komulainen P, Lin HJ, Linchangco GV, Luik AI, Ma J, Meigs JB, McCormick JB, Menni C, Nolte IM, Norris JM, Petty LE, Polikowsky HG, Raffield LM, Rich SS, Riha RL, Russ TC, Ruiz-Narvaez EA, Sitlani CM, Smith JA, Snieder H, Sofer T, Shen B, Tang J, Taylor KD, Teder-Laving M, Triatin R, Tsai MY, Völzke H, Westerman KE, Xia R, Yao J, Young KL, Zhang R, Zonderman AB, Zhu X, Below JE, Cox SR, Evans M, Fornage M, Fox ER, Franceschini N, Harlow SD, Holliday E, Ikram MA, Kelly T, Lakka TA, Lawlor DA, Li C, Liu CT, Mägi R, Manning AK, Matsuda F, Morrison AC, Nauck M, North KE, Penninx BW, Province MA, Psaty BM, Rotter JI, Spector TD, Wagenknecht LE, Willems van Dijk K, Study LC, Jaquish CE, Wilson PW, Peyser PA, Munroe PB, de Vries PS, Gauderman WJ, Sun YV, Chen H, Miller CL, Winkler TW, Rao DC, Redline S, van Heemst D. A Large-Scale Genome-Wide Gene-Sleep Interaction Study in 732,564 Participants Identifies Lipid Loci Explaining Sleep-Associated Lipid Disturbances. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.02.24312466. [PMID: 39281768 PMCID: PMC11398441 DOI: 10.1101/2024.09.02.24312466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify novel genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. We collected data from 55 cohorts with a combined sample size of 732,564 participants (87% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for the one-degree of freedom tests of interaction and two-degree of freedom joint tests of the main and interaction effect. In the cross-population meta-analyses, the one-degree of freedom variant-sleep interaction test identified 10 loci (P int <5.0e-9) not previously observed for lipids. Of interest, the ASPH locus (TG, LTST) is a target for aspartic and succinic acid metabolism previously shown to improve sleep and cardiovascular risk. The two-degree of freedom analyses identified an additional 7 loci that showed evidence for variant-sleep interaction (P joint <5.0e-9 in combination with P int <6.6e-6). Of these, the SLC8A1 locus (TG, STST) has been considered a potential treatment target for reduction of ischemic damage after acute myocardial infarction. Collectively, the 17 (9 with STST; 8 with LTST) loci identified in this large-scale initiative provides evidence into the biomolecular mechanisms underpinning sleep-duration-associated changes in lipid levels. The identified druggable targets may contribute to the development of novel therapies for dyslipidemia in people with sleep disturbances.
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5
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Bleich D, Biggs ML, Gardin JM, Lyles M, Siscovick DS, Mukamal KJ. Phenotyping lipid profiles in type 2 diabetes: Risk association and outcomes from the Cardiovascular Health Study. Am J Prev Cardiol 2024; 19:100725. [PMID: 39286650 PMCID: PMC11402907 DOI: 10.1016/j.ajpc.2024.100725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 08/16/2024] [Accepted: 08/17/2024] [Indexed: 09/19/2024] Open
Abstract
Aims To determine whether discrete lipid profiles (refer to as lipid phenotyping) can be used to stratify cardiovascular risk in individuals with type 2 diabetes. Methods and results Cardiovascular Health Study participants with diabetes and fasting lipid profiles at baseline (n = 866) were categorized separately by level of LDL cholesterol and HDL-C/Triglyceride (Tg) profiles (low Tg/high HDL-C; high Tg/low HDL-C; high Tg only or low HDL-C only). We performed Cox multivariate regression analysis to assess the risk of CVD mortality, incident myocardial infarction (MI), heart failure (HF), stroke, and composite MACE (MI, HF, stroke, and CVD mortality) associated with each lipid category. We also calculated risk estimates for MACE using lipid measures as continuous variables. In the fully adjusted model, the high triglyceride plus low HDL-C cholesterol phenotype demonstrated risk that was at least as high as the highest LDL-C sub-group phenotype for CVD mortality (Hazard ratio {HR} 1.58 vs 1.48), MI (HR 1.53 vs 1.58), HF (HR 1.47 vs 1.20), stroke (HR 2.02 vs 1.43), and MACE (HR 1.58 vs 1.38). When modeled continuously, the HR per SD for MACE was 1.12 (p = 0.03) for LDL-C and 1.19-1.20 (p < 0.001) for triglycerides or remnant cholesterol. Conclusions Participants with the high triglyceride/low HDL-C phenotype had equivalent or higher CVD risk than those with the high LDL-C phenotype. Further studies are necessary to determine whether lipid phenotyping accounts for the substantial CVD risk not explained by LDL cholesterol among individuals with type 2 diabetes.
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Affiliation(s)
- David Bleich
- Division of Endocrinology, Diabetes, & Metabolism, Rutgers New Jersey Medical School, 185 South Orange Avenue, MSB I-588, Newark, NJ 07103, United States
| | - Mary L Biggs
- University of Washington School of Medicine, Seattle, WA, United States
| | - Julius M Gardin
- Division of Endocrinology, Diabetes, & Metabolism, Rutgers New Jersey Medical School, 185 South Orange Avenue, MSB I-588, Newark, NJ 07103, United States
| | - Mary Lyles
- Wake Forest School of Medicine, Winston-Salem, NC, United States
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Zubirán R, Cruz-Bautista I, Aguilar-Salinas CA. Interaction Between Primary Hyperlipidemias and Type 2 Diabetes: Therapeutic Implications. Diabetes Ther 2024; 15:1979-2000. [PMID: 39080218 PMCID: PMC11330433 DOI: 10.1007/s13300-024-01626-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 07/10/2024] [Indexed: 08/18/2024] Open
Abstract
There is a gap of knowledge about the clinical and pathophysiological implications resulting from the interaction between primary hyperlipidemias and type 2 diabetes (T2D). Most of the existing evidence comes from sub-analyses of cohorts; scant information derives from randomized clinical trials. The expected clinical implications of T2D in patients with primary hyperlipidemias is an escalation of their already high cardiovascular risk. There is a need to accurately identify patients with this dual burden and to adequately prescribe lipid-lowering therapies, with the current advancements in newer therapeutic options. This review provides an update on the interactions of primary hyperlipidemias, such as familial combined hyperlipidemia, familial hypercholesterolemia, multifactorial chylomicronemia, lipoprotein (a), and type 2 diabetes.
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Affiliation(s)
- Rafael Zubirán
- Lipoprotein Metabolism Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ivette Cruz-Bautista
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico
| | - Carlos A Aguilar-Salinas
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico.
- Dirección de Investigación, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.
- Tecnológico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Mexico City, Mexico.
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7
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Mao G, Xu W, Wan L, Wang H, Xu S, Zhang L, Li S, Zhang J, Lai Z, Lan Y, Liu J. Unveiling the bioinformatic genes and their involved regulatory mechanisms in type 2 diabetes combined with osteoarthritis. Front Immunol 2024; 15:1353915. [PMID: 39176085 PMCID: PMC11338775 DOI: 10.3389/fimmu.2024.1353915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 07/24/2024] [Indexed: 08/24/2024] Open
Abstract
Background Type 2 Diabetes Mellitus (T2D) and Osteoarthritis (OA) are both prevalent diseases that significantly impact the health of patients. Increasing evidence suggests that there is a big correlation between T2D and OA, but the molecular mechanisms remain elusive. The aims of this study are to investigate the shared biomarkers and potential molecular mechanisms in T2D combined with OA. Methods T2D and OA-related differentially expressed genes (DEGs) were identified via bioinformatic analysis on Gene Expression Omnibus (GEO) datasets GSE26168 and GSE114007 respectively. Subsequently, extensive target prediction and network analysis were finished with Gene Ontology (GO), protein-protein interaction (PPI), and pathway enrichment with DEGs. The transcription factors (TFs) and miRNAs coupled in co-expressed DEGs involved in T2D and OA were predicted as well. The key genes expressed both in the clinical tissues of T2D and OA were detected with western blot and qRT-PCR assay. Finally, the most promising candidate compounds were predicted with the Drug-Gene Interaction Database (DGIdb) and molecular docking. Results In this study, 209 shared DEGs between T2D and OA were identified. Functional analysis disclosed that these DEGs are predominantly related to ossification, regulation of leukocyte migration, extracellular matrix (ECM) structural constituents, PI3K/AKT, and Wnt signaling pathways. Further analysis via Protein-Protein Interaction (PPI) analysis and validation with external datasets emphasized MMP9 and ANGPTL4 as crucial genes in both T2D and OA. Our findings were validated through qRT-PCR and Western blot analyses, which indicated high expression levels of these pivotal genes in T2D, OA, and T2D combined with OA cases. Additionally, the analysis of Transcription Factors (TFs)-miRNA interactions identified 7 TFs and one miRNA that jointly regulate these important genes. The Receiver Operating characteristic (ROC) analysis demonstrated the significant diagnostic potential of MMP9 and ANGPTL4.Moreover, we identified raloxifene, ezetimibe, and S-3304 as promising agents for patients with both T2D and OA. Conclusion This study uncovers the shared signaling pathways, biomarkers, potential therapeutics, and diagnostic models for individuals suffering from both T2D and OA. These findings not only present novel perspectives on the complex interplay between T2D and OA but also hold significant promise for improving the clinical management and prognosis of patients with this concurrent condition.
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Affiliation(s)
- Guangming Mao
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Wenhao Xu
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Lingli Wan
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Hongpin Wang
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Shutao Xu
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Liangming Zhang
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Shiyang Li
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
- Department of Pharmacy, Dali University, Dali, China
| | - Jifa Zhang
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Zhongming Lai
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Yuping Lan
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, China
| | - Jianhui Liu
- College of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, China
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8
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Fan W, Bradford TM, Török NJ. Metabolic dysfunction-associated liver disease and diabetes: Matrix remodeling, fibrosis, and therapeutic implications. Ann N Y Acad Sci 2024; 1538:21-33. [PMID: 38996214 DOI: 10.1111/nyas.15184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/14/2024]
Abstract
Metabolic dysfunction-associated liver disease (MASLD) and steatohepatitis (MASH) are becoming the most common causes of chronic liver disease in the United States and worldwide due to the obesity and diabetes epidemics. It is estimated that by 2030 close to 100 million people might be affected and patients with type 2 diabetes are especially at high risk. Twenty to 30% of patients with MASLD can progress to MASH, which is characterized by steatosis, necroinflammation, hepatocyte ballooning, and in advanced cases, fibrosis progressing to cirrhosis. Clinically, it is recognized that disease progression in diabetic patients is accelerated and the role of various genetic and epigenetic factors, as well as cell-matrix interactions in fibrosis and stromal remodeling, have recently been recognized. While there has been great progress in drug development and clinical trials for MASLD/MASH, the complexity of these pathways highlights the need to improve diagnosis/early detection and develop more successful antifibrotic therapies that not only prevent but reverse fibrosis.
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Affiliation(s)
- Weiguo Fan
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA
- Palo Alto VA Medical Center, Palo Alto, California, USA
| | - Toby M Bradford
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA
| | - Natalie J Török
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA
- Palo Alto VA Medical Center, Palo Alto, California, USA
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Hydes TJ, Kennedy OJ, Glyn-Owen K, Buchanan R, Parkes J, Cuthbertson DJ, Roderick P, Byrne CD. Liver Fibrosis Assessed Via Noninvasive Tests Is Associated With Incident Heart Failure in a General Population Cohort. Clin Gastroenterol Hepatol 2024; 22:1657-1667. [PMID: 38723982 DOI: 10.1016/j.cgh.2024.03.045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 03/06/2024] [Accepted: 03/22/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND & AIMS The aim of this study was to determine whether liver fibrosis is associated with heart failure in a general population cohort, and if genetic polymorphisms (PNPLA3 rs738409; TM6SF2 rs58542926), linked to increased risk of liver fibrosis and decreased risk of coronary artery disease, modify this association. METHODS Using UK Biobank data, we prospectively examined the relationship between noninvasive fibrosis markers (nonalcoholic fatty liver disease [NAFLD] fibrosis score [NFS], Fibrosis-4 [FIB-4] and aspartate transaminase [AST] to platelet ratio index [APRI]) and incident hospitalization/death from heart failure (n = 413,860). Cox-regression estimated hazard ratios (HRs) for incident heart failure. Effects of PNPLA3 and TM6SF2 on the association between liver fibrosis and heart failure were estimated by stratifying for genotype and testing for an interaction between genotype and liver fibrosis using a likelihood ratio test. RESULTS A total of 12,527 incident cases of heart failure occurred over a median of 10.7 years. Liver fibrosis was associated with an increased risk of hospitalization or death from heart failure (multivariable adjusted high-risk NFS score HR, 1.59; 95% confidence interval [CI],1.47-1.76; P < .0001; FIB-4 HR, 1.69; 95% CI, 1.55-1.84; P < .0001; APRI HR, 1.85; 95% CI, 1.56-2.19; P < .0001; combined fibrosis scores HR, 1.90; 95% CI, 1.44-2.49; P < .0001). These associations persisted for people with metabolic dysfunction-associated steatotic liver disease (MASLD), MASLD with alcohol consumption (Met-ALD), and harmful alcohol consumption. PNPLA3 rs738409 GG and TM6SF2 rs58542926 TT did not attenuate the positive association between fibrosis markers and heart failure. For PNPLA3, a statistically significant interaction was found between PNPLA3 rs738409, FIB-4, APRI score, and heart failure. CONCLUSION In the general population, serum markers of liver fibrosis are associated with increased hospitalization/death from heart failure. Genetic polymorphisms associated with liver fibrosis were not positively associated with elevated heart failure risk.
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Affiliation(s)
- Theresa J Hydes
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom; University Hospital Aintree, Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom; Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, United Kingdom.
| | - Oliver J Kennedy
- Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Kate Glyn-Owen
- Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Ryan Buchanan
- Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, United Kingdom; Southampton National Institute for Health and Care Research, Biomedical Research Centre, University Hospital Southampton, Southamptom, United Kingdom
| | - Julie Parkes
- Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Daniel J Cuthbertson
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom; University Hospital Aintree, Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom; Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, United Kingdom
| | - Paul Roderick
- Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Christopher D Byrne
- Southampton National Institute for Health and Care Research, Biomedical Research Centre, University Hospital Southampton, Southamptom, United Kingdom; Nutrition and Metabolism, Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
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Civeira F, Martín C, Cenarro A. APOE and familial hypercholesterolemia. Curr Opin Lipidol 2024; 35:195-199. [PMID: 38640077 DOI: 10.1097/mol.0000000000000937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Abstract
PURPOSE OF REVIEW Autosomal dominant hypercholesterolemia is a common cause of cardiovascular disease. In addition to the classic genes that cause hypercholesterolemia, LDLR, APOB and PCSK9 , a new locus has emerged as a candidate to be the cause of this hyperlipidemia, the p.(Leu167del) mutation in the APOE gene. RECENT FINDINGS Various studies have demonstrated the involvement of the p.(Leu167del) mutation in the APOE gene in hypercholesterolemia: Studies of family segregation, lipoprotein composition by ultracentrifugation and proteomic techniques, and functional studies of VLDL-carrying p.(Leu167del) internalization with cell cultures have demonstrated the role of this mutation in the cause of hypercholesterolemia. The phenotype of individuals carrying the p.(Leu167del) in APOE is indistinguishable from familial hypercholesterolemia individuals with mutations in the classic genes. However, a better response to lipid-lowering treatment has been demonstrated in these APOE mutation carrier individuals. SUMMARY Therefore, APOE gene should be considered a candidate locus along with LDLR, APOB , and PCSK9 to be investigated in the genetic diagnosis of familial hypercholesterolemia.
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Affiliation(s)
- Fernando Civeira
- Hospital Universitario Miguel Servet, IIS Aragón, CIBERCV
- Universidad de Zaragoza, Zaragoza
| | - César Martín
- Biofisika Institute (UPV/EHU, CSIC), University of the Basque Country, Leioa
- Department of Biochemistry and Molecular Biology, UPV/EHU, University of the Basque Country, Bilbao
| | - Ana Cenarro
- Hospital Universitario Miguel Servet, IIS Aragón, CIBERCV
- Instituto Aragonés de Ciencias de la Salud (IACS), Zaragoza, Spain
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Wang Z, Zhang J, Jiao F, Wu Y, Han L, Jiang G. Genetic association analyses highlight apolipoprotein B as a determinant of chronic kidney disease in patients with type 2 diabetes. J Clin Lipidol 2024:S1933-2874(24)00213-7. [PMID: 39278771 DOI: 10.1016/j.jacl.2024.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 07/05/2024] [Accepted: 07/10/2024] [Indexed: 09/18/2024]
Abstract
BACKGROUND Blood lipid levels were associated with chronic kidney disease (CKD) in patients with type 2 diabetes (T2D), but the genetic basis and causal nature remains unclear. OBJECTIVE This study aimed to investigate the relationships of lipids and their fractions with CKD in patients with T2D. METHODS Our prospective analysis involved 8,607 White participants with T2D but no CKD at baseline from the UK Biobank. Five common lipid traits were included as exposures. Weighted genetic risk scores (GRSs) for these lipid traits were developed. The causal associations between lipid traits, as well as lipid fractions, and CKD were explored using linear or nonlinear Mendelian randomization (MR). The 10-year predicted probabilities of CKD were evaluated via integrating MR and Cox models. RESUTLS Higher GRS of apolipoprotein B (ApoB) was associated with an increased CKD risk (HR[95 % CI]:1.07[1.02,1.13] per SD;P = 0.008) after adjusting for potential confounders. Linear MR indicated a positive association between genetically predicted ApoB levels and CKD (HR[95 % CI]:1.53[1.12,2.09];P = 0.008), but no evidence of associations was found between other lipid traits and CKD in T2D. Regarding 12 ApoB-contained lipid fractions, a significant causal association was found between medium very-low-density lipoprotein particles and CKD (HR[95 % CI]:1.16[1.02,1.32];P = 0.020). Nonlinear MR did not support nonlinearity in these causal associations. The 10-year probability curve showed that ApoB levels was positively associated with the risk of CKD in patients with T2D. CONCLUSION Lower ApoB levels were causally associated with a reduced risk of CKD in patients with T2D, positioning ApoB as a potential therapeutic target for CKD prevention in this population.
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Affiliation(s)
- Zhenqian Wang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China (Drs Wang, Zhang, Jiang); School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China (Drs Wang, Zhang, Jiang)
| | - Jiaying Zhang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China (Drs Wang, Zhang, Jiang); School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China (Drs Wang, Zhang, Jiang)
| | - Feng Jiao
- Guangzhou Centre for Applied Mathematics, Guangzhou University, Guangzhou, China (Dr Jiao)
| | - Yueheng Wu
- Medical Research Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China (Dr Wu)
| | - Liyuan Han
- Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China (Dr Han)
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China (Drs Wang, Zhang, Jiang); School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China (Drs Wang, Zhang, Jiang); Shenzhen Key Laboratory of Pathogenic Microbes and Biosafety, Shenzhen, Guangdong, China (Dr Jiang).
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12
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Hao QY, Zeng YH, Lin Y, Guo JB, Li SC, Yang PZ, Gao JW, Li ZH. Observational and genetic association of non-alcoholic fatty liver disease and calcific aortic valve disease. Front Endocrinol (Lausanne) 2024; 15:1421642. [PMID: 39045267 PMCID: PMC11263017 DOI: 10.3389/fendo.2024.1421642] [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: 04/22/2024] [Accepted: 06/25/2024] [Indexed: 07/25/2024] Open
Abstract
Background Non-alcoholic fatty liver disease (NAFLD) has emerged as a predominant driver of chronic liver disease globally and is associated with increased cardiovascular disease morbidity and mortality. However, the association between NAFLD and calcific aortic valve disease remains unclear. We aimed to prospectively investigate the association between NAFLD and incident aortic valve calcification (AVC), as well as its genetic relationship with incident calcific aortic valve stenosis (CAVS). Methods A post hoc analysis was conducted on 4226 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) database. We employed the adjusted Cox models to assess the observational association between NAFLD and incident AVC. Additionally, we conducted two-sample Mendelian randomization (MR) analyses to investigate the genetic association between genetically predicted NAFLD and calcific aortic valve stenosis (CAVS), a severe form of CAVD. We repeated the MR analyses by excluding NAFLD susceptibility genes linked to impaired very low-density lipoprotein (VLDL) secretion. Results After adjustment for potential risk factors, participants with NAFLD had a hazard ratio of 1.58 (95% CI: 1.03-2.43) for incident AVC compared to those without NAFLD. After excluding genes associated with impaired VLDL secretion, the MR analyses consistently showed the significant associations between genetically predicted NAFLD and CAVS for 3 traits: chronic elevation of alanine aminotransferase (odds ratio = 1.13 [95% CI: 1.01-1.25]), imaging-based NAFLD (odds ratio = 2.81 [95% CI: 1.66-4.76]), and biopsy-confirmed NAFLD (odds ratio = 1.12 [95% CI: 1.01-1.24]). However, the association became non-significant when considering all NAFLD susceptibility genes. Conclusions NAFLD was independently associated with an elevated risk of incident AVC. Genetically predicted NAFLD was also associated with CAVS after excluding genetic variants related to impaired VLDL secretion.
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Affiliation(s)
- Qing-Yun Hao
- Department of Cardiology, Laboratory of Heart Center, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Yu-Hong Zeng
- Medical Apparatus and Equipment Deployment, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Ying Lin
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jing-Bin Guo
- Department of Cardiology, Laboratory of Heart Center, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Shi-Chao Li
- Department of Organ Transplantation, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Ping-Zhen Yang
- Department of Cardiology, Laboratory of Heart Center, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Jing-Wei Gao
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ze-Hua Li
- Department of Cardiology, Laboratory of Heart Center, Zhujiang Hospital, Southern Medical University, Guangzhou, China
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Wen W, Fan H, Zhang S, Hu S, Chen C, Tang J, You Y, Wang C, Li J, Luo L, Cheng Y, Zhou M, Zhao X, Tan T, Xu F, Fu X, Chen J, Dong P, Zhang X, Wang M, Feng Y. Associations between metabolic dysfunction-associated fatty liver disease and atherosclerotic cardiovascular disease. Am J Med Sci 2024:S0002-9629(24)01323-5. [PMID: 38944203 DOI: 10.1016/j.amjms.2024.06.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 06/20/2024] [Accepted: 06/21/2024] [Indexed: 07/01/2024]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is closely related to metabolic syndrome and remains a major global health burden. The increased prevalence of obesity and type 2 diabetes mellitus (T2DM) worldwide has contributed to the rising incidence of NAFLD. It is widely believed that atherosclerotic cardiovascular disease (ASCVD) is associated with NAFLD. In the past decade, the clinical implications of NAFLD have gone beyond liver-related morbidity and mortality, with a majority of patient deaths attributed to malignancy, coronary heart disease (CHD), and other cardiovascular (CVD) complications. To better define fatty liver disease associated with metabolic disorders, experts proposed a new term in 2020 - metabolic dysfunction associated with fatty liver disease (MAFLD). Along with this new designation, updated diagnostic criteria were introduced, resulting in some differentiation between NAFLD and MAFLD patient populations, although there is overlap. The aim of this review is to explore the relationship between MAFLD and ASCVD based on the new definitions and diagnostic criteria, while briefly discussing potential mechanisms underlying cardiovascular disease in patients with MAFLD.
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Affiliation(s)
- Wen Wen
- Department of Cardiology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, 313000, Zhejiang, China
| | - Hua Fan
- School of Clinical Medicine, The First Affiliated Hospital of Henan University of Science and Technology, Henan University of Science and Technology, Luoyang 471003, Henan, China
| | - Shenghui Zhang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Siqi Hu
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Chen Chen
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Jiake Tang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Yao You
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Chunyi Wang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Jie Li
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Lin Luo
- Hangzhou Ruolin Hospital Management Co. Ltd, Hangzhou, 310007, China
| | - Yongran Cheng
- School of Public Health, Hangzhou Medical College, Hangzhou, 311300, China
| | - Mengyun Zhou
- Department of Molecular & Cellular Physiology, Shinshu University School of Medicine, 3900803, Japan
| | - Xuezhi Zhao
- Department of Gynecology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou 310006, Zhejiang, China
| | - Tao Tan
- Faculty of Applied Science, Macao Polytechnic University, Macao SAR, 999078, China
| | - Fangfang Xu
- Strategy Research and Knowledge Information Center, SAIC Motor Group, 200030, Shanghai, China
| | - Xinyan Fu
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Juan Chen
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Peng Dong
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Xingwei Zhang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Mingwei Wang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China.
| | - Yan Feng
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang Key Laboratory of Medical Epigenetics, Hangzhou Normal University, Hangzhou, 310015, Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China.
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Chen J, Hu J, Guo X, Yang Y, Qin D, Tang X, Huang Z, Wang F, Hu D, Peng D, Yu B. Apolipoprotein O modulates cholesterol metabolism via NRF2/CYB5R3 independent of LDL receptor. Cell Death Dis 2024; 15:389. [PMID: 38830896 PMCID: PMC11148037 DOI: 10.1038/s41419-024-06778-4] [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: 08/03/2023] [Revised: 05/22/2024] [Accepted: 05/24/2024] [Indexed: 06/05/2024]
Abstract
Apolipoprotein O (APOO) plays a critical intracellular role in regulating lipid metabolism. Here, we investigated the roles of APOO in metabolism and atherogenesis in mice. Hepatic APOO expression was increased in response to hyperlipidemia but was inhibited after simvastatin treatment. Using a novel APOO global knockout (Apoo-/-) model, it was found that APOO depletion aggravated diet-induced obesity and elevated plasma cholesterol levels. Upon crossing with low-density lipoprotein receptor (LDLR) and apolipoprotein E (APOE) knockout hyperlipidemic mouse models, Apoo-/- Apoe-/- and Apoo-/- Ldlr-/- mice exhibited elevated plasma cholesterol levels, with more severe atherosclerotic lesions than littermate controls. This indicated the effects of APOO on cholesterol metabolism independent of LDLR and APOE. Moreover, APOO deficiency reduced cholesterol excretion through bile and feces while decreasing phospholipid unsaturation by inhibiting NRF2 and CYB5R3. Restoration of CYB5R3 expression in vivo by adeno-associated virus (AAV) injection reversed the reduced degree of phospholipid unsaturation while decreasing blood cholesterol levels. This represents the first in vivo experimental validation of the role of APOO in plasma cholesterol metabolism independent of LDLR and elucidates a previously unrecognized cholesterol metabolism pathway involving NRF2/CYB5R3. APOO may be a metabolic regulator of total-body cholesterol homeostasis and a target for atherosclerosis management. Apolipoprotein O (APOO) regulates plasma cholesterol levels and atherosclerosis through a pathway involving CYB5R3 that regulates biliary and fecal cholesterol excretion, independently of the LDL receptor. In addition, down-regulation of APOO may lead to impaired mitochondrial function, which in turn aggravates diet-induced obesity and fat accumulation.
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Affiliation(s)
- Jin Chen
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Jiarui Hu
- Department of Spine Surgery, The Second Xiangya Hospital, Central South University, NO.139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Xin Guo
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Yang Yang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Donglu Qin
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Xiaoyu Tang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Zhijie Huang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Fengjiao Wang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Die Hu
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Daoquan Peng
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Bilian Yu
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China.
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China.
- FuRong Laboratory, Changsha, 410078, Hunan, China.
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15
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Tharehalli U, Rimbert A. G protein-coupled receptor 146: new insights from genetics and model systems. Curr Opin Lipidol 2024; 35:162-169. [PMID: 38465903 DOI: 10.1097/mol.0000000000000929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
PURPOSE OF REVIEW Atherosclerotic cardiovascular diseases continue to be a significant global cause of death. Despite the availability of efficient treatments, there is an ongoing need for innovative strategies to lower lipid levels, especially for individuals experiencing refractory dyslipidemias or intolerable adverse effects. Based on human genetic findings and on mouse studies, the G protein-coupled receptor 146 (GPR146) emerges as a promising target against hypercholesterolemia and atherosclerosis. The present review aims at providing a thorough summary of the latest information acquired regarding GPR146, encompassing genetic evidence, functional insights, and its broader implications for cardiometabolic health. RECENT FINDINGS Human genetic studies uncovered associations between GPR146 variants, plasma lipid levels and metabolic parameters. Additionally, GPR146's influence extends beyond lipid regulation, impacting adipocyte differentiation, lipolysis, and inflammation pathways. Despite GPR146's orphan status, ongoing efforts to deorphanize it, suggest a potential ligand with downstream effects involving Gαi coupling. SUMMARY Here, we outline and deliberate on recent progress focused on: enhancing comprehension of the effects of inhibiting GPR146 in humans through genetic instruments, evaluating the extra-hepatic functions of GPR146, and discovering its natural ligand(s). Grasping these biological parameters and mechanisms is crucial in the exploration of GPR146 as a prospective therapeutic target.
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Affiliation(s)
- Umesh Tharehalli
- Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Antoine Rimbert
- Nantes Université, CNRS, INSERM, l'institut du thorax, Nantes, France
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16
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Jeenduang N, Horpet D, Plyduang T, Nuinoon M. Association of thalassemia, hemoglobinopathies, and vitamin D levels with lipid profile in adults: Community-based research in southern Thai population. Heliyon 2024; 10:e31374. [PMID: 38813217 PMCID: PMC11133901 DOI: 10.1016/j.heliyon.2024.e31374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 05/10/2024] [Accepted: 05/15/2024] [Indexed: 05/31/2024] Open
Abstract
This study explored the frequency of lipid-lowering drug use in the thalassemia population and investigated the association of thalassemia, hemoglobinopathies, and serum 25(OH)D levels with lipid profile and red blood cell parameters. A combination of cross-sectional and community-based studies was conducted with 615 participants from the southern Thai population. Thalassemia and hemoglobinopathies were diagnosed using hemoglobin analysis and polymerase chain reaction-based methods to genotype globin genes. Biochemical parameters such as lipid profile, fasting blood sugar (FBS), and serum 25(OH)D levels were assessed using standard enzymatic methods and electrochemiluminescence immunoassays. Differences in the means of hematological and biochemical parameters between the thalassemia and non-thalassemia groups were compared and analyzed. A significantly lower frequency of lipid-lowering drug use was observed in the thalassemia group. Thalassemia, with clearly defined abnormalities in red blood cells, is associated with a 4.72-fold decreased risk of taking lipid-lowering drugs. Among thalassemia participants, the total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels were significantly lower than those in non-thalassemia participants. The prevalence of hypovitaminosis D in carriers of thalassemia and/or hemoglobinopathies in the southern Thai population was 53 % in females and 21 % in males. The highest lipid profile was observed in samples without thalassemia and hypovitaminosis D. The genetics of thalassemia and hemoglobinopathies with obviously abnormal red blood cells could explain the variable lipid levels, in addition to lipid metabolism-related genes and environmental factors. However, the effect of thalassemia on lipid levels in each population may differ according to its prevalence. A larger sample size is required to confirm this association, especially in countries with a high prevalence of thalassemia.
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Affiliation(s)
- Nutjaree Jeenduang
- School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
- Food Technology and Innovation Research Center of Excellence, Walailak University, Nakhon Si Thammarat, Thailand
| | - Dararat Horpet
- Center for Scientific and Technological Equipment, Walailak University, Nakhon Si Thammarat, Thailand
| | - Thunyaluk Plyduang
- Center for Scientific and Technological Equipment, Walailak University, Nakhon Si Thammarat, Thailand
| | - Manit Nuinoon
- School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
- Hematology and Transfusion Science Research Center, Walailak University, Nakhon Si Thammarat, Thailand
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17
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Semmler G, Balcar L, Wernly S, Datz L, Semmler M, Rosenstatter L, Stickel F, Aigner E, Wernly B, Datz C. No association of NAFLD-related polymorphisms in PNPLA3 and TM6SF2 with all-cause and cardiovascular mortality in an Austrian population study. Wien Klin Wochenschr 2024; 136:251-257. [PMID: 37103556 DOI: 10.1007/s00508-023-02196-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 03/13/2023] [Indexed: 04/28/2023]
Abstract
BACKGROUND AND AIMS Single-nucleotide-polymorphisms in PNPLA3-rs738409 and the TM6SF2-rs58542926, associated with metabolic-dysfunction-associated fatty liver disease (MAFLD), have been discussed as potentially protective for cardiovascular diseases. Therefore, we aimed to study the associations of PNPLA3/TM6SF2 variants with MAFLD and cardiovascular risk in a population-based sample of asymptomatic patients. METHODS The study cohort comprised 1742 patients of European decent aged 45-80 years from a registry study undergoing screening colonoscopy for colorectal cancer between 2010 and 2014. SCORE2 and Framingham risk score calculated to assess cardiovascular risk. Data on survival were obtained from the national death registry RESULTS: Half of included patients were male (52%, 59 ± 10 years), 819 (47%) carried PNPLA3‑G and 278 (16%) TM6SF2-T-alleles. MAFLD (PNPLA3‑G-allele: 46% vs. 41%, p = 0.041; TM6SF2‑T-allele: 54% vs. 42%, p < 0.001) was more frequent in patients harbouring risk alleles with both showing independent associations with MAFLD on multivariable binary logistic regression analysis. While median Framingham risk score was lower in PNPLA3‑G-allele carriers (10 vs. 8, p = 0.011), SCORE2 and established cardiovascular diseases were similar across carriers vs. non-carriers of the respective risk-alleles. During a median follow-up of 9.1 years, neither PNPLA3‑G-allele nor TM6SF2‑T-allele was associated with overall nor with cardiovascular mortality. CONCLUSION Carriage of PNPLA3/TM6SF2 risk alleles could not be identified as significant factor for all-cause or cardiovascular mortality in asymptomatic middle-aged individuals undergoing screening colonoscopy.
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Affiliation(s)
- Georg Semmler
- Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, Salzburg, Austria
- Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Lorenz Balcar
- Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, Salzburg, Austria
- Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Sarah Wernly
- Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Leonora Datz
- Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Marie Semmler
- Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Lea Rosenstatter
- First Department of Medicine, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Felix Stickel
- Department of Gastroenterology and Hepatology, University Hospital of Zurich, Zurich, Switzerland
| | - Elmar Aigner
- First Department of Medicine, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Bernhard Wernly
- Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, Salzburg, Austria
- Institute of General Practice, Family Medicine and Preventive Medicine, Paracelsus Medical University, Salzburg, Austria
| | - Christian Datz
- Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, Salzburg, Austria.
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Momin MM, Zhou X, Hyppönen E, Benyamin B, Lee SH. Cross-ancestry genetic architecture and prediction for cholesterol traits. Hum Genet 2024; 143:635-648. [PMID: 38536467 DOI: 10.1007/s00439-024-02660-7] [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] [Received: 06/30/2023] [Accepted: 02/13/2024] [Indexed: 05/18/2024]
Abstract
While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.
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Affiliation(s)
- Md Moksedul Momin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- Department of Genetics and Animal Breeding, Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University (CVASU), Khulshi, Chattogram, 4225, Bangladesh.
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia.
| | - Xuan Zhou
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Beben Benyamin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
| | - S Hong Lee
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia.
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19
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Tuo L, Yan LT, Liu Y, Yang XX. Type 1 diabetes mellitus and non-alcoholic fatty liver disease: a two-sample Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1315046. [PMID: 38681765 PMCID: PMC11045944 DOI: 10.3389/fendo.2024.1315046] [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: 10/10/2023] [Accepted: 03/29/2024] [Indexed: 05/01/2024] Open
Abstract
Background NAFLD (Nonalcoholic fatty liver disease) is becoming an increasingly common cause of chronic liver disease. Metabolic dysfunction, overweight/obesity, and diabetes are thought to be closely associated with increased NAFLD risk. However, few studies have focused on the mechanisms of NAFLD occurrence in T1DM. Methods We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal association between T1DM and NAFLD with/without complications, such as coma, renal complications, ketoacidosis, neurological complications, and ophthalmic complications. Multiple Mendelian randomization methods, such as the inverse variance weighted (IVW) method, weighted median method, and MR-Egger test were performed to evaluate the causal association of T1DM and NAFLD using genome-wide association study summary data from different consortia, such as Finngen and UK biobank. Results We selected 37 SNPs strongly associated with NAFLD/LFC (at a significance level of p < 5 × 10-8) as instrumental variables from the Finnish database based on the T1DM phenotype (8,967 cases and 308,373 controls). We also selected 14/16 SNPs based on with or without complications. The results suggest that the genetic susceptibility of T1DM does not increase the risk of NAFLD (OR=1.005 [0.99, 1.02], IVW p=0.516, MR Egger p=0.344, Weighted median p=0.959, Weighted mode p=0.791), regardless of whether complications are present. A slight causal effect of T1DM without complications on LFC was observed (OR=1.025 [1.00, 1.03], MR Egger p=0.045). However, none of the causal relationships were significant in the IVW (p=0.317), Weighted median (p=0.076), and Weighted mode (p=0.163) methods. Conclusion Our study did not find conclusive evidence for a causal association between T1DM and NAFLD, although clinical observations indicate increasing abnormal transaminase prevalence and NAFLD progression in T1DM patients.
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Affiliation(s)
- Lin Tuo
- Department of Infectious Disease, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | | | | | - Xing-xiang Yang
- Department of Infectious Disease, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
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20
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Mellemkjær A, Kjær MB, Haldrup D, Grønbæk H, Thomsen KL. Management of cardiovascular risk in patients with metabolic dysfunction-associated steatotic liver disease. Eur J Intern Med 2024; 122:28-34. [PMID: 38008609 DOI: 10.1016/j.ejim.2023.11.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 11/06/2023] [Accepted: 11/08/2023] [Indexed: 11/28/2023]
Abstract
The novel term Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is proposed to replace non-alcoholic fatty liver disease (NAFLD) to highlight the close association with the metabolic syndrome. MASLD encompasses patients with liver steatosis and at least one of five cardiometabolic risk factors which implies that these patients are at increased risk of cardiovascular disease (CVD). Indeed, the prevalence of CVD in MASLD patients is increased and CVD is recognized as the most common cause of death in MASLD patients. We here present an update on the pathophysiology of CVD in MASLD, discuss the risk factors, and suggest screening for CVD in patients with MASLD. Currently, there is no FDA-approved pharmacological treatment for MASLD, and no specific treatment recommended for CVD in patients with MASLD. Thus, the treatment strategy is based on weight loss and a reduction and treatment of CVD risk factors. We recommend screening of MASLD patients for CVD using the SCORE2 system with guidance to specific treatment algorithms. In all patients with CVD risk factors, lifestyle intervention to induce weight loss through diet and exercise is recommended. Especially a Mediterranean diet may improve hyperlipidemia and if further treatment is needed, statins should be used as first-line treatment. Further, anti-hypertensive drugs should be used to treat hypertension. With the epidemic of obesity and type 2 diabetes mellitus (T2DM) the risk of MASLD and CVD is expected to increase, and preventive measures, screening, and effective treatments are highly needed to reduce morbidity and mortality in MASLD patients.
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Affiliation(s)
- Anders Mellemkjær
- Department of Hepatology & Gastroenterology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Mikkel Breinholt Kjær
- Department of Hepatology & Gastroenterology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - David Haldrup
- Department of Hepatology & Gastroenterology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Henning Grønbæk
- Department of Hepatology & Gastroenterology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
| | - Karen Louise Thomsen
- Department of Hepatology & Gastroenterology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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Hu X, Chen F, Jia L, Long A, Peng Y, Li X, Huang J, Wei X, Fang X, Gao Z, Zhang M, Liu X, Chen YG, Wang Y, Zhang H, Wang Y. A gut-derived hormone regulates cholesterol metabolism. Cell 2024; 187:1685-1700.e18. [PMID: 38503280 DOI: 10.1016/j.cell.2024.02.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 11/18/2023] [Accepted: 02/21/2024] [Indexed: 03/21/2024]
Abstract
The reciprocal coordination between cholesterol absorption in the intestine and de novo cholesterol synthesis in the liver is essential for maintaining cholesterol homeostasis, yet the mechanisms governing the opposing regulation of these processes remain poorly understood. Here, we identify a hormone, Cholesin, which is capable of inhibiting cholesterol synthesis in the liver, leading to a reduction in circulating cholesterol levels. Cholesin is encoded by a gene with a previously unknown function (C7orf50 in humans; 3110082I17Rik in mice). It is secreted from the intestine in response to cholesterol absorption and binds to GPR146, an orphan G-protein-coupled receptor, exerting antagonistic downstream effects by inhibiting PKA signaling and thereby suppressing SREBP2-controlled cholesterol synthesis in the liver. Therefore, our results demonstrate that the Cholesin-GPR146 axis mediates the inhibitory effect of intestinal cholesterol absorption on hepatic cholesterol synthesis. This discovered hormone, Cholesin, holds promise as an effective agent in combating hypercholesterolemia and atherosclerosis.
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Affiliation(s)
- Xiaoli Hu
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Fengyi Chen
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Liangjie Jia
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Aijun Long
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Ying Peng
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Xu Li
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Junfeng Huang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Xueyun Wei
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Xinlei Fang
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Zihua Gao
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Mengxian Zhang
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Xiao Liu
- Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan 430072, China
| | - Ye-Guang Chen
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China; Guangzhou Laboratory, Guangzhou 510005, China; School of Basic Medicine, Jiangxi Medical College, Nanchang University, Nanchang 330031, China
| | - Yan Wang
- Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan 430072, China
| | - Huijie Zhang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Yiguo Wang
- State Key Laboratory of Membrane Biology, MOE Key Laboratory of Bioinformatics, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China.
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Melton HJ, Zhang Z, Wu C. SUMMIT-FA: a new resource for improved transcriptome imputation using functional annotations. Hum Mol Genet 2024; 33:624-635. [PMID: 38129112 PMCID: PMC10954367 DOI: 10.1093/hmg/ddad205] [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: 05/16/2023] [Revised: 10/24/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023] Open
Abstract
Transcriptome-wide association studies (TWAS) integrate gene expression prediction models and genome-wide association studies (GWAS) to identify gene-trait associations. The power of TWAS is determined by the sample size of GWAS and the accuracy of the expression prediction model. Here, we present a new method, the Summary-level Unified Method for Modeling Integrated Transcriptome using Functional Annotations (SUMMIT-FA), which improves gene expression prediction accuracy by leveraging functional annotation resources and a large expression quantitative trait loci (eQTL) summary-level dataset. We build gene expression prediction models in whole blood using SUMMIT-FA with the comprehensive functional database MACIE and eQTL summary-level data from the eQTLGen consortium. We apply these models to GWAS for 24 complex traits and show that SUMMIT-FA identifies significantly more gene-trait associations and improves predictive power for identifying "silver standard" genes compared to several benchmark methods. We further conduct a simulation study to demonstrate the effectiveness of SUMMIT-FA.
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Affiliation(s)
- Hunter J Melton
- Department of Statistics, Florida State University, 214 Rogers Building, 117 N. Woodward Avenue, Tallahassee, FL 32306, United States
| | - Zichen Zhang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 7007 Bertner Avenue, Unit 1689, Houston, TX 77030, United States
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 7007 Bertner Avenue, Unit 1689, Houston, TX 77030, United States
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Lu J, Wang Z, Zhang J, Jiao F, Zou C, Han L, Jiang G. Causal association of blood lipids with all-cause and cause-specific mortality risk: a Mendelian randomization study. J Lipid Res 2024; 65:100528. [PMID: 38458338 PMCID: PMC10993189 DOI: 10.1016/j.jlr.2024.100528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 02/03/2024] [Accepted: 03/02/2024] [Indexed: 03/10/2024] Open
Abstract
Dyslipidemia has long been implicated in elevating mortality risk; yet, the precise associations between lipid traits and mortality remained undisclosed. Our study aimed to explore the causal effects of lipid traits on both all-cause and cause-specific mortality. One-sample Mendelian randomization (MR) with linear and nonlinear assumptions was conducted in a cohort of 407,951 European participants from the UK Biobank. Six lipid traits, consisting of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and lipoprotein(a), were included to investigate the causal associations with mortality. Two-sample MR was performed to replicate the association between each lipid trait and all-cause mortality. Univariable MR results showed that genetically predicted higher ApoA1 was significantly associated with a decreased all-cause mortality risk (HR[95% CI]:0.93 [0.89-0.97], P value = 0.001), which was validated by the two-sample MR analysis. Higher lipoprotein(a) was associated with an increased risk of all-cause mortality (1.03 [1.01-1.04], P value = 0.002). Multivariable MR confirmed the direct causal effects of ApoA1 and lipoprotein(a) on all-cause mortality. Meanwhile, nonlinear MR found no evidence for nonlinearity between lipids and all-cause mortality. Our examination into cause-specific mortality revealed a suggestive inverse association between ApoA1 and cancer mortality, a significant positive association between lipoprotein(a) and cardiovascular disease mortality, and a suggestive positive association between lipoprotein(a) and digestive disease mortality. High LDL-C was associated with an increased risk of cardiovascular disease mortality but a decreased risk of neurodegenerative disease mortality. The findings suggest that implementing interventions to raise ApoA1 and decrease lipoprotein(a) levels may improve overall health outcomes and mitigate cancer and digestive disease mortality.
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Affiliation(s)
- Jiawen Lu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhenqian Wang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jiaying Zhang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Feng Jiao
- Guangzhou Centre for Applied Mathematics, Guangzhou University, Guangzhou, Guangdong, China
| | - Chenfeng Zou
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Liyuan Han
- Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China.
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24
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Woerner J, Sriram V, Nam Y, Verma A, Kim D. Uncovering genetic associations in the human diseasome using an endophenotype-augmented disease network. Bioinformatics 2024; 40:btae126. [PMID: 38527901 PMCID: PMC10963079 DOI: 10.1093/bioinformatics/btae126] [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] [Received: 09/18/2023] [Revised: 01/17/2024] [Indexed: 03/27/2024] Open
Abstract
MOTIVATION Many diseases, particularly cardiometabolic disorders, exhibit complex multimorbidities with one another. An intuitive way to model the connections between phenotypes is with a disease-disease network (DDN), where nodes represent diseases and edges represent associations, such as shared single-nucleotide polymorphisms (SNPs), between pairs of diseases. To gain further genetic understanding of molecular contributors to disease associations, we propose a novel version of the shared-SNP DDN (ssDDN), denoted as ssDDN+, which includes connections between diseases derived from genetic correlations with intermediate endophenotypes. We hypothesize that a ssDDN+ can provide complementary information to the disease connections in a ssDDN, yielding insight into the role of clinical laboratory measurements in disease interactions. RESULTS Using PheWAS summary statistics from the UK Biobank, we constructed a ssDDN+ revealing hundreds of genetic correlations between diseases and quantitative traits. Our augmented network uncovers genetic associations across different disease categories, connects relevant cardiometabolic diseases, and highlights specific biomarkers that are associated with cross-phenotype associations. Out of the 31 clinical measurements under consideration, HDL-C connects the greatest number of diseases and is strongly associated with both type 2 diabetes and heart failure. Triglycerides, another blood lipid with known genetic causes in non-mendelian diseases, also adds a substantial number of edges to the ssDDN. This work demonstrates how association with clinical biomarkers can better explain the shared genetics between cardiometabolic disorders. Our study can facilitate future network-based investigations of cross-phenotype associations involving pleiotropy and genetic heterogeneity, potentially uncovering sources of missing heritability in multimorbidities. AVAILABILITY AND IMPLEMENTATION The generated ssDDN+ can be explored at https://hdpm.biomedinfolab.com/ddn/biomarkerDDN.
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Affiliation(s)
- Jakob Woerner
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Vivek Sriram
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Yonghyun Nam
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Anurag Verma
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
- Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Dokyoon Kim
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
- Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, United States
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25
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Lee SB, Choi JE, Hong KW, Jung DH. Genetic Variants Linked to Myocardial Infarction in Individuals with Non-Alcoholic Fatty Liver Disease and Their Potential Interaction with Dietary Patterns. Nutrients 2024; 16:602. [PMID: 38474730 DOI: 10.3390/nu16050602] [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: 01/25/2024] [Revised: 02/12/2024] [Accepted: 02/20/2024] [Indexed: 03/14/2024] Open
Abstract
In recent studies, non-alcoholic fatty liver disease (NAFLD) has been associated with a high risk of ischemic heart disease. This study aimed to investigate a genetic variant within a specific gene associated with myocardial infarction (MI) among patients with NAFLD. We included 57,205 participants from a Korean genome and epidemiology study. The baseline population consisted of 45,400 individuals, with 11,805 identified as patients with NAFLD. Genome-wide association studies were conducted for three groups: the entire sample, the healthy population, and patients with NAFLD. We defined the p-value < 1 × 10-5 as the nominal significance and the p-value < 5 × 10-2 as statistically significant for the gene-by-nutrient interaction. Among the significant single-nucleotide polymorphisms (SNPs), the lead SNP of each locus was further analyzed. In this cross-sectional study, a total of 1529 participants (2.8%) had experienced MI. Multivariable logistic regression was performed to evaluate the association of 102 SNPs across nine loci. Nine SNPs (rs11891202, rs2278549, rs13146480, rs17293047, rs184257317, rs183081683, rs1887427, rs146939423, and rs76662689) demonstrated an association with MI in the group with NAFLD Notably, the MI-associated SNP, rs134146480, located within the SORCS2 gene, known for its role in secreting insulin in islet cells, showed the most significant association with MI (p-value = 2.55 × 10-7). Our study identifies candidate genetic polymorphisms associated with NAFLD-related MI. These findings may serve as valuable indicators for estimating MI risk and for conducting future investigations into the underlying mechanisms of NAFLD-related MI.
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Affiliation(s)
- Sung-Bum Lee
- Department of Family Medicine, Soonchunhyang University Bucheon Hospital, Bucheon 22972, Republic of Korea
| | - Ja-Eun Choi
- R&D Division, Theragen Health Co., Ltd., Seongnam-si 13493, Republic of Korea
| | - Kyung-Won Hong
- R&D Division, Theragen Health Co., Ltd., Seongnam-si 13493, Republic of Korea
| | - Dong-Hyuk Jung
- Department of Family Medicine, Yongin Severance Hospital, Yongin-si 16995, Republic of Korea
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26
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Shahjahan, Dey JK, Dey SK. Translational bioinformatics approach to combat cardiovascular disease and cancers. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2024; 139:221-261. [PMID: 38448136 DOI: 10.1016/bs.apcsb.2023.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.
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Affiliation(s)
- Shahjahan
- Laboratory for Structural Biology of Membrane Proteins, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Joy Kumar Dey
- Central Council for Research in Homoeopathy, Ministry of Ayush, Govt. of India, New Delhi, Delhi, India
| | - Sanjay Kumar Dey
- Laboratory for Structural Biology of Membrane Proteins, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India.
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27
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Nogueira JP, Cusi K. Role of Insulin Resistance in the Development of Nonalcoholic Fatty Liver Disease in People With Type 2 Diabetes: From Bench to Patient Care. Diabetes Spectr 2024; 37:20-28. [PMID: 38385099 PMCID: PMC10877218 DOI: 10.2337/dsi23-0013] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Insulin resistance is implicated in both the pathogenesis of nonalcoholic fatty liver disease (NAFLD) and its progression from steatosis to steatohepatitis, cirrhosis, and even hepatocellular carcinoma, which is known to be more common in people with type 2 diabetes. This article reviews the role of insulin resistance in the metabolic dysfunction observed in obesity, type 2 diabetes, atherogenic dyslipidemia, and hypertension and how it is a driver of the natural history of NAFLD by promoting glucotoxicity and lipotoxicity. The authors also review the genetic and environmental factors that stimulate steatohepatitis and fibrosis progression and their relationship with cardiovascular disease and summarize guidelines supporting the treatment of NAFLD with diabetes medications that reduce insulin resistance, such as pioglitazone or glucagon-like peptide 1 receptor agonists.
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Affiliation(s)
- Juan Patricio Nogueira
- Universidad del Pacifico, Asunción, Paraguay
- Centro de Investigación en Endocrinología, Nutrición y Metabolismo, Facultad de Ciencias de la Salud, Universidad Nacional de Formosa, Formosa, Argentina
| | - Kenneth Cusi
- Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, FL
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28
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Tada H, Kaneko H, Suzuki Y, Okada A, Takeda N, Fujiu K, Morita H, Ako J, Node K, Takeji Y, Takamura M, Yasunaga H, Komuro I. Familial hypercholesterolemia is related to cardiovascular disease, heart failure and atrial fibrillation. Results from a population-based study. Eur J Clin Invest 2024; 54:e14119. [PMID: 37916502 DOI: 10.1111/eci.14119] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 09/05/2023] [Accepted: 09/27/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Familial hypercholesterolemia (FH) is associated with atherosclerotic cardiovascular disease (ASCVD). However, the prevalence of FH among a general population remains unknown, and it is unclear if FH is associated with other cardiovascular complications, including heart failure (HF) and atrial fibrillation (AF). METHODS Analyses were conducted on individuals without a prior history of cardiovascular disease using a nationwide health claims database collected in the JMDC Claims Database between 2005 and 2022 (n = 4,126,642; median age, 44 years; 57.5% men). We defined FH as either LDL cholesterol ≥250 mg/dL or LDL cholesterol ≥175 mg/dL under the lipid-lowering medications under the assumption that lipid-lowering medications reduced LDL cholesterol by 30%. We assessed the associations between FH and composite outcomes, including, ASCVD (myocardial infarction, angina pectoris, and stroke), HF, and AF using Cox proportional hazard model. RESULTS We identified 11,983 (.29%) FH patients. In total, 181,150 events were recorded during the mean follow-up period of 3.5 years. The status FH was significantly associated with composite outcomes after adjustments (hazard ratio [HR]; 1.38, 95% confidence interval [CI]: 1.30-1.47, p < .001). Interestingly, the status FH was significantly associated with HF (HR: 1.48, 95% CI: 1.36-1.61, p < .001) and AF (HR: 1.33, 95% CI: 1.08-1.64, p < .001) in addition to angina pectoris (HR: 1.45, 95% CI: 1.33-1.58, p < .001) and stroke (HR: 1.19, 95% CI: 1.04-1.36, p < .001). CONCLUSION We found that the prevalence of FH was .29% in a general population. FH was significantly associated with a higher risk of developing cardiovascular disease, HF and AF. LAY SUMMARY We sought to identify the prevalence of FH among a general population, and to clarify whether FH increases the risk of not only ASCVD but also HF and AF.
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Affiliation(s)
- Hayato Tada
- Department of Cardiovascular Medicine, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Hidehiro Kaneko
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
- The Department of Advanced Cardiology, The University of Tokyo, Tokyo, Japan
| | - Yuta Suzuki
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
- Center for Outcomes Research and Economic Evaluation for Health, National Institute of Public Health, Saitama, Japan
| | - Akira Okada
- Department of Prevention of Diabetes and Lifestyle-Related Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Norifumi Takeda
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
| | - Katsuhito Fujiu
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
- The Department of Advanced Cardiology, The University of Tokyo, Tokyo, Japan
| | - Hiroyuki Morita
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
| | - Junya Ako
- Department of Cardiovascular Medicine, Kitasato University School of Medicine, Kanagawa, Japan
| | - Koichi Node
- Department of Cardiovascular Medicine, Saga University, Saga, Japan
| | - Yasuaki Takeji
- Department of Cardiovascular Medicine, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Masayuki Takamura
- Department of Cardiovascular Medicine, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Hideo Yasunaga
- The Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo, Japan
| | - Issei Komuro
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
- International University of Health and Welfare, Tokyo, Japan
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29
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Ahles A, Engelhardt S. Genetic Variants of Adrenoceptors. Handb Exp Pharmacol 2024; 285:27-54. [PMID: 37578621 DOI: 10.1007/164_2023_676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Adrenoceptors are class A G-protein-coupled receptors grouped into three families (α1-, α2-, and β-adrenoceptors), each one including three members. All nine corresponding adrenoceptor genes display genetic variation in their coding and adjacent non-coding genomic region. Coding variants, i.e., nucleotide exchanges within the transcribed and translated receptor sequence, may result in a difference in amino acid sequence thus altering receptor function and signaling. Such variants have been intensely studied in vitro in overexpression systems and addressed in candidate-gene studies for distinct clinical parameters. In recent years, large cohorts were analyzed in genome-wide association studies (GWAS), where variants are detected as significant in context with specific traits. These studies identified two of the in-depth characterized 18 coding variants in adrenoceptors as repeatedly statistically significant genetic risk factors - p.Arg389Gly in the β1- and p.Thr164Ile in the β2-adrenoceptor, along with 56 variants in the non-coding regions adjacent to the adrenoceptor gene loci, the functional role of which is largely unknown at present. This chapter summarizes current knowledge on the two coding variants in adrenoceptors that have been consistently validated in GWAS and provides a prospective overview on the numerous non-coding variants more recently attributed to adrenoceptor gene loci.
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Affiliation(s)
- Andrea Ahles
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany
| | - Stefan Engelhardt
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany.
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany.
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30
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Fidler TP, Dunbar A, Kim E, Hardaway B, Pauli J, Xue C, Abramowicz S, Xiao T, O’Connor K, Sachs N, Wang N, Maegdefessel L, Levine R, Reilly M, Tall AR. Suppression of IL-1β promotes beneficial accumulation of fibroblast-like cells in atherosclerotic plaques in clonal hematopoiesis. NATURE CARDIOVASCULAR RESEARCH 2024; 3:60-75. [PMID: 38362011 PMCID: PMC10868728 DOI: 10.1038/s44161-023-00405-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 11/30/2023] [Indexed: 02/17/2024]
Abstract
Clonal hematopoiesis (CH) is an independent risk factor for atherosclerotic cardiovascular disease. Murine models of CH suggest a central role of inflammasomes and IL-1β in accelerated atherosclerosis and plaque destabilization. Here we show using single-cell RNA sequencing in human carotid plaques that inflammasome components are enriched in macrophages, while the receptor for IL-1β is enriched in fibroblasts and smooth muscle cells (SMCs). To address the role of inflammatory crosstalk in features of plaque destabilization, we conducted SMC fate mapping in Ldlr-/- mice modeling Jak2VF or Tet2 CH treated with IL-1β antibodies. Unexpectedly, this treatment minimally affected SMC differentiation, leading instead to a prominent expansion of fibroblast-like cells. Depletion of fibroblasts from mice treated with IL-1β antibody resulted in thinner fibrous caps. Conversely, genetic inactivation of Jak2VF during plaque regression promoted fibroblast accumulation and fibrous cap thickening. Our studies suggest that suppression of inflammasomes promotes plaque stabilization by recruiting fibroblast-like cells to the fibrous cap.
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Affiliation(s)
- Trevor P. Fidler
- Division of Molecular Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
- Department of Physiology, University of San Francisco, San Francisco, CA, USA
| | - Andrew Dunbar
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Eunyoung Kim
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Brian Hardaway
- Division of Molecular Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Jessica Pauli
- Department of Vascular and Endovascular Surgery, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich, Germany
| | - Chenyi Xue
- Department of Vascular and Endovascular Surgery, Technical University Munich, Munich, Germany
| | - Sandra Abramowicz
- Division of Molecular Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Tong Xiao
- Division of Molecular Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Kavi O’Connor
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nadja Sachs
- Department of Vascular and Endovascular Surgery, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich, Germany
| | - Nan Wang
- Division of Molecular Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Lars Maegdefessel
- Department of Vascular and Endovascular Surgery, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich, Germany
- Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Ross Levine
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Muredach Reilly
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Alan R. Tall
- Division of Molecular Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
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31
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He W, Han X, Ong JS, Wu Y, Hewitt AW, Mackey DA, Gharahkhani P, MacGregor S. Genome-Wide Meta-analysis Identifies Risk Loci and Improves Disease Prediction of Age-Related Macular Degeneration. Ophthalmology 2024; 131:16-29. [PMID: 37634759 DOI: 10.1016/j.ophtha.2023.08.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 07/22/2023] [Accepted: 08/15/2023] [Indexed: 08/29/2023] Open
Abstract
PURPOSE To identify age-related macular degeneration (AMD) risk loci and to establish a polygenic prediction model. DESIGN Genome-wide association study (GWAS) and polygenic risk score (PRS) construction. PARTICIPANTS We included 64 885 European patients with AMD and 568 740 control participants (with overlapped samples) in the UK Biobank, Genetic Epidemiology Research on Aging (GERA), International AMD Consortium, FinnGen, and published early AMD GWASs in meta-analyses, as well as 733 European patients with AMD and 20 487 control participants from the Canadian Longitudinal Study on Aging (CLSA) and non-Europeans from the UK Biobank and GERA for polygenic risk score validation. METHODS A multitrait meta-analysis of GWASs comprised 64 885 patients with AMD and 568 740 control participants; the multitrait approach accounted for sample overlap. We constructed a PRS for AMD based on both previously reported as well as unreported AMD loci. We applied the PRS to nonoverlapping data from the CLSA. MAIN OUTCOME MEASURES We identified several single nucleotide polymorphisms associated with AMD and established a PRS for AMD risk prediction. RESULTS We identified 63 AMD risk loci alongside the well-established AMD loci CFH and ARMS2, including 9 loci that were not reported in previous GWASs, some of which previously were linked to other eye diseases such as glaucoma (e.g., HIC1). We applied our PRS to nonoverlapping data from the CLSA. A new PRS was constructed using the PRS method, PRS-CS, and significantly improved the prediction accuracy of AMD risk compared with PRSs from previously published datasets. We further showed that even people who carry all the well-known AMD risk alleles at CFH and ARMS2 vary considerably in their AMD risk (ranging from close to 0 in individuals with low PRS to > 50% in individuals with high PRS). Although our PRS was derived in individuals of European ancestry, the PRS shows potential for predicting risk in people of East Asian, South Asian, and Latino ancestry. CONCLUSIONS Our findings improve the knowledge of the genetic architecture of AMD and help achieve better accuracy in AMD prediction. FINANCIAL DISCLOSURE(S) Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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Affiliation(s)
- Weixiong He
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia.
| | - Xikun Han
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Jue-Sheng Ong
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Yeda Wu
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Alex W Hewitt
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victorian, Australia; School of Medicine, Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - David A Mackey
- Lions Eye Institute, Centre for Ophthalmology and Visual Science, University of Western Australia, Perth, Western Australia, Australia
| | - Puya Gharahkhani
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
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32
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Driessen S, Francque SM, Anker SD, Castro Cabezas M, Grobbee DE, Tushuizen ME, Holleboom AG. Metabolic dysfunction-associated steatotic liver disease and the heart. Hepatology 2023:01515467-990000000-00699. [PMID: 38147315 DOI: 10.1097/hep.0000000000000735] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/13/2023] [Indexed: 12/27/2023]
Abstract
The prevalence and severity of metabolic dysfunction-associated steatotic liver disease (MASLD) are increasing. Physicians who treat patients with MASLD may acknowledge the strong coincidence with cardiometabolic disease, including atherosclerotic cardiovascular disease (asCVD). This raises questions on co-occurrence, causality, and the need for screening and multidisciplinary care for MASLD in patients with asCVD, and vice versa. Here, we review the interrelations of MASLD and heart disease and formulate answers to these matters. Epidemiological studies scoring proxies for atherosclerosis and actual cardiovascular events indicate increased atherosclerosis in patients with MASLD, yet no increased risk of asCVD mortality. MASLD and asCVD share common drivers: obesity, insulin resistance and type 2 diabetes mellitus (T2DM), smoking, hypertension, and sleep apnea syndrome. In addition, Mendelian randomization studies support that MASLD may cause atherosclerosis through mixed hyperlipidemia, while such evidence is lacking for liver-derived procoagulant factors. In the more advanced fibrotic stages, MASLD may contribute to heart failure with preserved ejection fraction by reduced filling of the right ventricle, which may induce fatigue upon exertion, often mentioned by patients with MASLD. Some evidence points to an association between MASLD and cardiac arrhythmias. Regarding treatment and given the strong co-occurrence of MASLD and asCVD, pharmacotherapy in development for advanced stages of MASLD would ideally also reduce cardiovascular events, as has been demonstrated for T2DM treatments. Given the common drivers, potential causal factors and especially given the increased rate of cardiovascular events, comprehensive cardiometabolic risk management is warranted in patients with MASLD, preferably in a multidisciplinary approach.
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Affiliation(s)
- Stan Driessen
- Department of Vascular Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Sven M Francque
- Department of Gastroenterology and Hepatology, University Hospital Antwerp, Antwerp, Belgium
| | - Stefan D Anker
- Department of Cardiology (CVK) of German Heart Center Charité, Institute of Health Center for Regenerative Therapies (BCRT), German Centre for Cardiovascular Research (DZHK) partner site Berlin, Charité Universitätsmedizin, Berlin, Germany
- Institute of Heart Diseases, Wroclaw Medical University, Wroclaw, Poland
| | - Manuel Castro Cabezas
- Julius Clinical, Zeist, The Netherlands
- Department of Internal Medicine, Franciscus Gasthuis and Vlietland, Rotterdam, The Netherlands
- Department of Internal Medicine and Endocrinology, Erasmus MC, Rotterdam, The Netherlands
| | - Diederick E Grobbee
- Julius Clinical, Zeist, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maarten E Tushuizen
- Department of Gastroenterology and Hepatology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Adriaan G Holleboom
- Department of Vascular Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
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Wang Z, Xiao Y, Lu J, Zou C, Huang W, Zhang J, Liu S, Han L, Jiao F, Tian D, Jiang Y, Du X, Ma RCW, Jiang G. Investigating linear and nonlinear associations of LDL cholesterol with incident chronic kidney disease, atherosclerotic cardiovascular disease and all-cause mortality: A prospective and Mendelian randomization study. Atherosclerosis 2023; 387:117394. [PMID: 38029611 DOI: 10.1016/j.atherosclerosis.2023.117394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND AND AIMS Observational studies suggest potential nonlinear associations of low-density lipoprotein cholesterol (LDL-C) with cardio-renal diseases and mortality, but the causal nature of these associations is unclear. We aimed to determine the shape of causal relationships of LDL-C with incident chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD) and all-cause mortality, and to evaluate the absolute risk of adverse outcomes contributed by LDL-C itself. METHODS Observational analysis and one-sample Mendelian randomization (MR) with linear and nonlinear assumptions were performed using the UK Biobank of >0.3 million participants with no reported prescription of lipid-lowering drugs. Two-sample MR on summary-level data from the Global Lipid Genetics Consortium (N = 296,680) and the CKDGen (N = 625,219) was employed to replicate the relationship for kidney traits. The 10-year probabilities of the outcomes was estimated by integrating the MR and Cox models. RESULTS Observationally, participants with low LDL-C were significantly associated with a decreased risk of ASCVD, but an increased risk of CKD and all-cause mortality. Univariable MR showed an inverse total effect of LDL-C on incident CKD (HR [95% CI]:0.84 [0.73-0.96]; p = 0.011), a positive effect on ASCVD (1.41 [1.29-1.53]; p<0.001), and no significant causal effect on all-cause mortality. Multivariable MR, controlling for high-density lipoprotein cholesterol (HDL-C) and triglycerides, identified a positive direct effect on ASCVD (1.32 [1.18-1.47]; p<0.001), but not on CKD and all-cause mortality. These results indicated that genetically predicted low LDL-C had an inverse indirect effect on CKD mediated by HDL-C and triglycerides, which was validated by a two-sample MR analysis using summary-level data from the Global Lipid Genetics Consortium (N = 296,680) and the CKDGen consortium (N = 625,219). Suggestive evidence of a nonlinear causal association between LDL-C and CKD was found. The 10-year probability curve showed that LDL-C concentrations below 3.5 mmol/L were associated with an increased risk of CKD. CONCLUSIONS In the general population, lower LDL-C was causally associated with lower risk of ASCVD, but appeared to have a trade-off for an increased risk of CKD, with not much effect on all-cause mortality. LDL-C concentration below 3.5 mmol/L may increase the risk of CKD.
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Affiliation(s)
- Zhenqian Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yang Xiao
- National Clinical Research Centre for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jiawen Lu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Chenfeng Zou
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Wenyu Huang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Jiaying Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Siyang Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Liyuan Han
- Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Feng Jiao
- Guangzhou Centre for Applied Mathematics, Guangzhou University, Guangzhou, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yawen Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China; Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
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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.
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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
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Ottensmann L, Tabassum R, Ruotsalainen SE, Gerl MJ, Klose C, Widén E, Simons K, Ripatti S, Pirinen M. Genome-wide association analysis of plasma lipidome identifies 495 genetic associations. Nat Commun 2023; 14:6934. [PMID: 37907536 PMCID: PMC10618167 DOI: 10.1038/s41467-023-42532-8] [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: 01/11/2023] [Accepted: 10/13/2023] [Indexed: 11/02/2023] Open
Abstract
The human plasma lipidome captures risk for cardiometabolic diseases. To discover new lipid-associated variants and understand the link between lipid species and cardiometabolic disorders, we perform univariate and multivariate genome-wide analyses of 179 lipid species in 7174 Finnish individuals. We fine-map the associated loci, prioritize genes, and examine their disease links in 377,277 FinnGen participants. We identify 495 genome-trait associations in 56 genetic loci including 8 novel loci, with a considerable boost provided by the multivariate analysis. For 26 loci, fine-mapping identifies variants with a high causal probability, including 14 coding variants indicating likely causal genes. A phenome-wide analysis across 953 disease endpoints reveals disease associations for 40 lipid loci. For 11 coronary artery disease risk variants, we detect strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and lipid species beyond the standard lipids.
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Affiliation(s)
- Linda Ottensmann
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Rubina Tabassum
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | | | - Elisabeth Widén
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Samuli Ripatti
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
- Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
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36
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Ding Y, Deng Q, Yang M, Niu H, Wang Z, Xia S. Clinical Classification of Obesity and Implications for Metabolic Dysfunction-Associated Fatty Liver Disease and Treatment. Diabetes Metab Syndr Obes 2023; 16:3303-3329. [PMID: 37905232 PMCID: PMC10613411 DOI: 10.2147/dmso.s431251] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/10/2023] [Indexed: 11/02/2023] Open
Abstract
Obesity,and metabolic dysfunction-associated fatty liver disease (MAFLD) have reached epidemic proportions globally. Obesity and MAFLD frequently coexist and act synergistically to increase the risk of adverse clinical outcomes (both hepatic and extrahepatic). Type 2 diabetes mellitus (T2DM) is the most important risk factor for rapid progression of steatohepatitis and advanced fibrosis. Conversely, the later stages of MAFLD are associated with an increased risk of T2DM incident. According to the proposed criteria, MAFLD is diagnosed in patients with liver steatosis and in at least one in three: overweight or obese, T2DM, or signs of metabolic dysregulation if they are of normal weight. However, the clinical classification and correlation between obesity and MAFLD is more complex than expected. In addition, treatment for obesity and MAFLD are associated with a reduced risk of T2DM, suggesting that liver-based treatments could reduce the risk of developing T2DM. This review describes the clinical classification of obesity and MAFLD, discusses the clinical features of various types of obesity and MAFLD, emphasizes the role of visceral obesity and insulin resistance (IR) in the development of MAFLD,and summarizes the existing treatments for obesity and MAFLD that reduce the risk of developing T2DM.
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Affiliation(s)
- Yuping Ding
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Quanjun Deng
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Mei Yang
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Haiyan Niu
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Zuoyu Wang
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Shihai Xia
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
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37
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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.
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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.
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38
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Demir M, Bornstein SR, Mantzoros CS, Perakakis N. Liver fat as risk factor of hepatic and cardiometabolic diseases. Obes Rev 2023; 24:e13612. [PMID: 37553237 DOI: 10.1111/obr.13612] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 06/26/2023] [Accepted: 07/10/2023] [Indexed: 08/10/2023]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a disorder characterized by excessive accumulation of fat in the liver that can progress to liver inflammation (non-alcoholic steatohepatitis [NASH]), liver fibrosis, and cirrhosis. Although most efforts for drug development are focusing on the treatment of the latest stages of NAFLD, where significant fibrosis and NASH are present, findings from studies suggest that the amount of liver fat may be an important independent risk factor and/or predictor of development and progression of NAFLD and metabolic diseases. In this review, we first describe the current tools available for quantification of liver fat in humans and then present the clinical and pathophysiological evidence that link liver fat with NAFLD progression as well as with cardiometabolic diseases. Finally, we discuss current pharmacological and non-pharmacological approaches to reduce liver fat and present open questions that have to be addressed in future studies.
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Affiliation(s)
- Münevver Demir
- Department of Hepatology and Gastroenterology, Campus Virchow Clinic and Campus Charité Mitte, Charité University Medicine, Berlin, Germany
| | - Stefan R Bornstein
- Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Paul Langerhans Institute Dresden (PLID), Helmholtz Center Munich, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
- Diabetes and Nutritional Sciences, King's College London, London, UK
| | - Christos S Mantzoros
- Division of Endocrinology, Boston VA Healthcare System and Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, 02215, USA
| | - Nikolaos Perakakis
- Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Paul Langerhans Institute Dresden (PLID), Helmholtz Center Munich, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
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Snaebjarnarson AS, Helgadottir A, Arnadottir GA, Ivarsdottir EV, Thorleifsson G, Ferkingstad E, Einarsson G, Sveinbjornsson G, Thorgeirsson TE, Ulfarsson MO, Halldorsson BV, Olafsson I, Erikstrup C, Pedersen OB, Nyegaard M, Bruun MT, Ullum H, Brunak S, Iversen KK, Christensen AH, Olesen MS, Ghouse J, Banasik K, Knowlton KU, Arnar DO, Thorgeirsson G, Nadauld L, Ostrowski SR, Bundgaard H, Holm H, Sulem P, Stefansson K, Gudbjartsson DF. Complex effects of sequence variants on lipid levels and coronary artery disease. Cell 2023; 186:4085-4099.e15. [PMID: 37714134 DOI: 10.1016/j.cell.2023.08.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/06/2023] [Accepted: 08/10/2023] [Indexed: 09/17/2023]
Abstract
Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Magnus O Ulfarsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik 102, Iceland
| | | | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus 8200, Denmark; Department of Clinical Medicine, Health, Aarhus University, Aarhus 8200, Denmark
| | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge 4600, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark
| | - Mette Nyegaard
- Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg 9220, Denmark
| | - Mie T Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense 5000, Denmark
| | - Henrik Ullum
- Statens Serum Institut, Copenhagen 2300, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Kasper Karmark Iversen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Emergency Medicine, Copenhagen University Hospital Herlev and Gentofte, Herlev 2900, Denmark; Department of Cardiology, Copenhagen University Hospital, Herlev-Gentofte Hospital, Herlev 2900, Denmark
| | - Alex Hoerby Christensen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Cardiology, Copenhagen University Hospital, Herlev-Gentofte Hospital, Herlev 2900, Denmark
| | - Morten S Olesen
- Laboratory for Molecular Cardiology, Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark; Laboratory for Molecular Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen 1165, Denmark
| | - Jonas Ghouse
- Laboratory for Molecular Cardiology, Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark; Laboratory for Molecular Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen 1165, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Kirk U Knowlton
- Intermountain Medical Center, Intermountain Heart Institute, Salt Lake City, UT 84143, USA
| | - David O Arnar
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland; Division of Cardiology, Department of Internal Medicine, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Gudmundur Thorgeirsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland; Division of Cardiology, Department of Internal Medicine, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Lincoln Nadauld
- Precision Genomics, Intermountain Healthcare, Saint George, UT 84790, USA
| | - Sisse Rye Ostrowski
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen 2100, Denmark
| | - Henning Bundgaard
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland
| | | | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland.
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; School of Engineering and Natural Sciences, University of Iceland, Reykjavik 102, Iceland.
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40
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Xu F, Ziebarth JD, Goeminne LJ, Gao J, Williams EG, Quarles LD, Makowski L, Cui Y, Williams RW, Auwerx J, Lu L. Gene network based analysis identifies a coexpression module involved in regulating plasma lipids with high-fat diet response. J Nutr Biochem 2023; 119:109398. [PMID: 37302664 PMCID: PMC10896179 DOI: 10.1016/j.jnutbio.2023.109398] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 05/08/2023] [Accepted: 05/30/2023] [Indexed: 06/13/2023]
Abstract
Plasma lipids are modulated by gene variants and many environmental factors, including diet-associated weight gain. However, understanding how these factors jointly interact to influence molecular networks that regulate plasma lipid levels is limited. Here, we took advantage of the BXD recombinant inbred family of mice to query weight gain as an environmental stressor on plasma lipids. Coexpression networks were examined in both nonobese and obese livers, and a network was identified that specifically responded to the obesogenic diet. This obesity-associated module was significantly associated with plasma lipid levels and enriched with genes known to have functions related to inflammation and lipid homeostasis. We identified key drivers of the module, including Cidec, Cidea, Pparg, Cd36, and Apoa4. The Pparg emerged as a potential master regulator of the module as it can directly target 19 of the top 30 hub genes. Importantly, activation of this module is causally linked to lipid metabolism in humans, as illustrated by correlation analysis and inverse-variance weighed Mendelian randomization. Our findings provide novel insights into gene-by-environment interactions for plasma lipid metabolism that may ultimately contribute to new biomarkers, better diagnostics, and improved approaches to prevent or treat dyslipidemia in patients.
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Affiliation(s)
- Fuyi Xu
- School of Pharmacy, Binzhou Medical University, Yantai, Shandong, China; Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Jesse D Ziebarth
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Ludger Je Goeminne
- Laboratory of Integrative Systems Physiology, Interfaculty Institute of Bioengineering, Lausanne, Switzerland
| | - Jun Gao
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Evan G Williams
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Leigh D Quarles
- Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Liza Makowski
- Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA; Center for Cancer Research, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Yan Cui
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Robert W Williams
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA; Center for Cancer Research, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Interfaculty Institute of Bioengineering, Lausanne, Switzerland.
| | - Lu Lu
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
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Papaefthymiou A, Doulberis M, Karafyllidou K, Chatzimichael E, Deretzi G, Exadaktylos AK, Sampsonas F, Gelasakis A, Papamichos SI, Kotronis G, Gialamprinou D, Vardaka E, Polyzos SA, Kountouras J. Effect of spironolactone on pharmacological treatment of nonalcoholic fatty liver disease. Minerva Endocrinol (Torino) 2023; 48:346-359. [PMID: 34669319 DOI: 10.23736/s2724-6507.21.03564-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Nonalcoholic fatty liver disease (NAFLD) was recently renamed to metabolic (dysfunction)-associated fatty liver disease (MAFLD) to better characterize its pathogenic origin. NAFLD represents, at least in western societies, a potential epidemic with raising prevalence. Its multifactorial pathogenesis is partially unraveled and till now there is no approved pharmacotherapy for NAFLD. A plethora of various choices are investigated in clinical trials, targeting an arsenal of different pathways and molecules. Since the mineralocorticoid receptor (MR) and renin-angiotensin-aldosterone system (RAAS) appear to be implicated in NAFLD, within this concise review, we focus on a rather classical and inexpensive pharmacological agent, spironolactone. We present the current lines of evidence of MR and RAAS-related preclinical models and human trials reporting an association with NAFLD. In conclusion, evidence about spironolactone of RAAS is commented, as potential future pharmacological management of NAFLD.
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Affiliation(s)
- Apostolis Papaefthymiou
- Department of Gastroenterology, University Hospital of Larisa, Larisa, Greece -
- School of Medicine, Second Medical Clinic, Ippokration Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece -
- School of Medicine, First Laboratory of Pharmacology, Aristotle University of Thessaloniki, Thessaloniki, Greece -
| | - Michael Doulberis
- School of Medicine, Second Medical Clinic, Ippokration Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
- School of Medicine, First Laboratory of Pharmacology, Aristotle University of Thessaloniki, Thessaloniki, Greece
- Department of Emergency Medicine, University Hospital Inselspital of Bern, Bern, Switzerland
- Division of Gastroenterology and Hepatology, Department of Medicine, Medical University, Kantonsspital Aarau, Aarau, Switzerland
| | - Kyriaki Karafyllidou
- Department of Pediatrics, University Children's Hospital of Zurich, Zurich, Switzerland
| | - Eleftherios Chatzimichael
- Department of Psychiatry, Psychotherapy and Psychosomatics, Center for Integrative Psychiatry, Psychiatric University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Georgia Deretzi
- Department of Neurology, Papageorgiou General Hospital, Thessaloniki, Greece
| | | | - Fotios Sampsonas
- Department of Respiratory Medicine, University Hospital of Patras, Patras, Greece
| | - Athanasios Gelasakis
- Department of Animal Science, Laboratory of Anatomy and Physiology of Farm Animals, Agricultural University of Athens, Athens, Greece
| | - Spyros I Papamichos
- Blood Transfusion Service Eastern Switzerland, Swiss Red Cross, St. Gallen, Switzerland
| | - Georgios Kotronis
- Department of Internal Medicine, General Hospital Aghios Pavlos of Thessaloniki, Thessaloniki, Greece
| | - Dimitra Gialamprinou
- Second Neonatal Department and NICU, Aristotle University of Thessaloniki, Papageorgiou General Hospital, Thessaloniki, Greece
| | - Elisabeth Vardaka
- School of Health Sciences, Department of Nutritional Sciences and Dietetics, International Hellenic University, Thessaloniki, Greece
| | - Stergios A Polyzos
- School of Medicine, First Laboratory of Pharmacology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Jannis Kountouras
- School of Medicine, Second Medical Clinic, Ippokration Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
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42
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Talamantes S, Lisjak M, Gilglioni EH, Llamoza-Torres CJ, Ramos-Molina B, Gurzov EN. Non-alcoholic fatty liver disease and diabetes mellitus as growing aetiologies of hepatocellular carcinoma. JHEP Rep 2023; 5:100811. [PMID: 37575883 PMCID: PMC10413159 DOI: 10.1016/j.jhepr.2023.100811] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 05/01/2023] [Accepted: 05/08/2023] [Indexed: 08/15/2023] Open
Abstract
Obesity-related complications such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D) are well-established risk factors for the development of hepatocellular carcinoma (HCC). This review provides insights into the molecular mechanisms that underlie the role of steatosis, hyperinsulinemia and hepatic inflammation in HCC development and progression. We focus on recent findings linking intracellular pathways and transcription factors that can trigger the reprogramming of hepatic cells. In addition, we highlight the role of enzymes in dysregulated metabolic activity and consequent dysfunctional signalling. Finally, we discuss the potential uses and challenges of novel therapeutic strategies to prevent and treat NAFLD/T2D-associated HCC.
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Affiliation(s)
- Stephanie Talamantes
- Signal Transduction and Metabolism Laboratory, Laboratoire de Gastroentérologie Expérimental et Endotools, Université Libre de Bruxelles, Route de Lennik 808, Brussels, 1070, Belgium
| | - Michela Lisjak
- Signal Transduction and Metabolism Laboratory, Laboratoire de Gastroentérologie Expérimental et Endotools, Université Libre de Bruxelles, Route de Lennik 808, Brussels, 1070, Belgium
| | - Eduardo H. Gilglioni
- Signal Transduction and Metabolism Laboratory, Laboratoire de Gastroentérologie Expérimental et Endotools, Université Libre de Bruxelles, Route de Lennik 808, Brussels, 1070, Belgium
| | - Camilo J. Llamoza-Torres
- Department of Hepatology, Virgen de la Arrixaca University Hospital, Murcia, 30120, Spain
- Obesity and Metabolism Laboratory, Biomedical Research Institute of Murcia (IMIB), Murcia, 30120, Spain
| | - Bruno Ramos-Molina
- Obesity and Metabolism Laboratory, Biomedical Research Institute of Murcia (IMIB), Murcia, 30120, Spain
| | - Esteban N. Gurzov
- Signal Transduction and Metabolism Laboratory, Laboratoire de Gastroentérologie Expérimental et Endotools, Université Libre de Bruxelles, Route de Lennik 808, Brussels, 1070, Belgium
- Obesity and Metabolism Laboratory, Biomedical Research Institute of Murcia (IMIB), Murcia, 30120, Spain
- WELBIO Department, WEL Research Institute, Avenue Pasteur 6, Wavre, 1300, Belgium
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43
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Bódis K, Bombrich M, Schön M, Knebel B, Zaharia OP, Bönhof G, Karusheva Y, Strassburger K, Kupriyanova Y, Kotzka J, Guthoff R, Schrauwen-Hinderling V, Al-Hasani H, Burkart V, Szendroedi J, Wagner R, Markgraf DF, Roden M. Effects of TM6SF2 rs58542926 polymorphism on hepatocellular lipids and insulin resistance in early type 2 diabetes. Nutr Metab Cardiovasc Dis 2023; 33:1785-1796. [PMID: 37495452 DOI: 10.1016/j.numecd.2023.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/02/2023] [Accepted: 06/07/2023] [Indexed: 07/28/2023]
Abstract
BACKGROUND AND AIMS Increased hepatocellular lipid content (HCL) is linked to insulin resistance, risk of type 2 diabetes and related complications. Conversely, a single-nucleotide polymorphism (TM6SF2EK; rs58542926) in the transmembrane 6 superfamily member 2-gene has been associated with nonalcoholic fatty liver disease (NAFLD), but lower cardiovascular risk. This case-control study tested the role of this polymorphism for tissue-specific insulin sensitivity during early course of diabetes. METHODS AND RESULTS Males with recent-onset type 2 diabetes with (TM6SF2EK: n = 16) or without (TM6SF2EE: n = 16) the heterozygous TM6SF2-polymorphism of similar age and body mass index, underwent Botnia-clamps with [6,6-2H2]glucose to measure whole-body-, hepatic- and adipose tissue-insulin sensitivity. HCL was assessed with 1H-magnetic-resonance-spectroscopy. A subset of both groups (n = 24) was re-evaluated after 5 years. Despite doubled HCL, TM6SF2EK had similar hepatic- and adipose tissue-insulin sensitivity and 27% higher whole-body-insulin sensitivity than TM6SF2EE. After 5 years, whole-body-insulin sensitivity, HCL were similar between groups, while adipose tissue-insulin sensitivity decreased by 87% and 55% within both groups and circulating triacylglycerol increased in TM6SF2EE only. CONCLUSIONS The TM6SF2-polymorphism rs58542926 dissociates HCL from insulin resistance in recent-onset type 2 diabetes, which is attenuated by disease duration. This suggests that diabetes-related metabolic alterations dominate over effects of the TM6SF2-polymorphism during early course of diabetes and NAFLD.
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Affiliation(s)
- Kálmán Bódis
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Maria Bombrich
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Martin Schön
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Birgit Knebel
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Oana-Patricia Zaharia
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Gidon Bönhof
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Yanislava Karusheva
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Klaus Strassburger
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Yuliya Kupriyanova
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Jörg Kotzka
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Rainer Guthoff
- Department of Ophthalmology, Faculty of Medicine and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Vera Schrauwen-Hinderling
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Hadi Al-Hasani
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Volker Burkart
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Julia Szendroedi
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Department of Internal Medicine I and Clinical Chemistry, University Hospital Heidelberg, Heidelberg, Germany; Joint Heidelberg-IDC Transnational Diabetes Program, Internal Medicine I, Heidelberg University Hospital, Heidelberg, Germany
| | - Robert Wagner
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Daniel F Markgraf
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Michael Roden
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany.
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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.
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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
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Zhou XD, Targher G, Byrne CD, Somers V, Kim SU, Chahal CAA, Wong VWS, Cai J, Shapiro MD, Eslam M, Steg PG, Sung KC, Misra A, Li JJ, Brotons C, Huang Y, Papatheodoridis GV, Sun A, Yilmaz Y, Chan WK, Huang H, Méndez-Sánchez N, Alqahtani SA, Cortez-Pinto H, Lip GYH, de Knegt RJ, Ocama P, Romero-Gomez M, Fudim M, Sebastiani G, Son JW, Ryan JD, Ikonomidis I, Treeprasertsuk S, Pastori D, Lupsor-Platon M, Tilg H, Ghazinyan H, Boursier J, Hamaguchi M, Nguyen MH, Fan JG, Goh GBB, Al Mahtab M, Hamid S, Perera N, George J, Zheng MH. An international multidisciplinary consensus statement on MAFLD and the risk of CVD. Hepatol Int 2023; 17:773-791. [PMID: 37204656 PMCID: PMC10198034 DOI: 10.1007/s12072-023-10543-8] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 04/18/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Fatty liver disease in the absence of excessive alcohol consumption is an increasingly common condition with a global prevalence of ~ 25-30% and is also associated with cardiovascular disease (CVD). Since systemic metabolic dysfunction underlies its pathogenesis, the term metabolic (dysfunction)-associated fatty liver disease (MAFLD) has been proposed for this condition. MAFLD is closely intertwined with obesity, type 2 diabetes mellitus and atherogenic dyslipidemia, which are established cardiovascular risk factors. Unlike CVD, which has received attention in the literature on fatty liver disease, the CVD risk associated with MAFLD is often underestimated, especially among Cardiologists. METHODS AND RESULTS A multidisciplinary panel of fifty-two international experts comprising Hepatologists, Endocrinologists, Diabetologists, Cardiologists and Family Physicians from six continents (Asia, Europe, North America, South America, Africa and Oceania) participated in a formal Delphi survey and developed consensus statements on the association between MAFLD and the risk of CVD. Statements were developed on different aspects of CVD risk, ranging from epidemiology to mechanisms, screening, and management. CONCULSIONS The expert panel identified important clinical associations between MAFLD and the risk of CVD that could serve to increase awareness of the adverse metabolic and cardiovascular outcomes of MAFLD. Finally, the expert panel also suggests potential areas for future research.
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Affiliation(s)
- Xiao-Dong Zhou
- Department of Cardiovascular Medicine, The Heart Center, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Giovanni Targher
- Department of Medicine, Section of Endocrinology, Diabetes, and Metabolism, University of Verona, Verona, Italy
| | - Christopher D Byrne
- Southampton National Institute for Health and Care Research Biomedical Research Centre, University Hospital Southampton, and University of Southampton, Southampton General Hospital, Southampton, UK
| | - Virend Somers
- Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, USA
| | - Seung Up Kim
- Department of Internal Medicine, Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, South Korea
| | - C Anwar A Chahal
- Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, USA
- Center for Inherited Cardiovascular Diseases, WellSpan Health, Lancaster, PA, USA
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, EC1A 7BE, West Smithfield, UK
| | - Vincent Wai-Sun Wong
- State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong, China
| | - Jingjing Cai
- Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Michael D Shapiro
- Center for Prevention of Cardiovascular Disease, Section on Cardiovascular Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Mohammed Eslam
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital, University of Sydney, Sydney, NSW, 2145, Australia
| | - Philippe Gabriel Steg
- Université Paris -Cité, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, FACT (French Alliance for Cardiovascular Trials), INSERM U1148, Paris, France
| | - Ki-Chul Sung
- Department of Internal Medicine, Division of Cardiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Anoop Misra
- Fortis C-DOC Centre of Excellence for Diabetes, Metabolic Diseases and Endocrinology, Chirag Enclave, National Diabetes Obesity and Cholesterol Foundation and Diabetes Foundation (India), New Delhi, India
| | - Jian-Jun Li
- State Key Laboratory of Cardiovascular Diseases, Fu Wai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Carlos Brotons
- Biomedical Research Institute Sant Pau (IIB Sant Pau), Sardenya Primary Health Care Center, Barcelona, Spain
| | - Yuli Huang
- Department of Cardiology, Shunde Hospital, Southern Medical University, Jiazi Road, Lunjiao Town, Shunde District, Foshan, China
| | - George V Papatheodoridis
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greece
| | - Aijun Sun
- Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yusuf Yilmaz
- Institute of Gastroenterology, Marmara University, Istanbul, Turkey
- Department of Gastroenterology, School of Medicine, Recep Tayyip Erdoğan University, Rize, Turkey
| | - Wah Kheong Chan
- Gastroenterology and Hepatology Unit, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Hui Huang
- Department of Cardiology, The Eighth Affiliated Hospital of Sun Yat-Sen University, 3025 Shennan Middle Road, Shenzhen, China
| | - Nahum Méndez-Sánchez
- Liver Research Unit, Medica Sur Clinic and Foundation and Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Saleh A Alqahtani
- Liver Transplantation Unit, King Faisal Specialist Hospital & Research Center, Riyadh, Saudi Arabia
- Division of Gastroenterology and Hepatology, Johns Hopkins University School of Medicine, 720 Rutland Avenue, Baltimore, MD, USA
| | - Helena Cortez-Pinto
- Laboratório de Nutrição e Metabolismo, Faculdade de Medicina, Clínica Universitária de Gastrenterologia, Universidade de Lisboa, Lisbon, Portugal
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- Danish Center for Clinical Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Robert J de Knegt
- Department of Gastroenterology and Hepatology, Erasmus MC University Medical Center Rotterdam, Gravendijkwal 230, Room Ha 206, Rotterdam, The Netherlands
| | - Ponsiano Ocama
- Department of Internal Medicine, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Manuel Romero-Gomez
- Department of Digestive and Liver Diseases, Institute of Biomedicine of Seville, University Hospital Virgen del Rocio, University of Seville, Seville, Spain
| | - Marat Fudim
- Department of Cardiology, Duke University School of Medicine, Durham, NC, USA
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA
| | - Giada Sebastiani
- Division of Gastroenterology and Hepatology, Chronic Viral Illness Service, McGill University Health Centre, Royal Victoria Hospital, 1001 Blvd. Décarie, Montreal, Canada
| | - Jang Won Son
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - John D Ryan
- Department of Hepatology, RCSI School of Medicine and Medical Sciences, Dublin/Beaumont Hospital, Dublin, Ireland
| | - Ignatios Ikonomidis
- Preventive Cardiology Laboratory and Cardiometabolic Clinic, Second Cardiology Department, Attikon Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Sombat Treeprasertsuk
- Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
| | - Daniele Pastori
- Department of Clinical, Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy
| | - Monica Lupsor-Platon
- Department of Medical Imaging, "Prof. Dr. Octavian Fodor" Regional Institute of Gastroenterology and Hepathology, "Iuliu Hațieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Herbert Tilg
- Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology and Metabolism, Medical University Innsbruck, Innsbruck, Austria
| | - Hasmik Ghazinyan
- Department of Hepatology, Nork Clinical Hospital of Infectious Disease, Yerevan, Armenia
| | - Jerome Boursier
- Hepato-Gastroenterology Department, University Hospital, 4 Larrey Street, 49933, Angers Cedex 09, France
- HIFIH Laboratory, UPRES 3859, SFR 4208, LUNAM University, Angers, France
| | - Masahide Hamaguchi
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465, Kajii-Cho, Kawaramachi-Hirokoji, Kamigyo-Ku, Kyoto, Japan
| | - Mindie H Nguyen
- Division of Gastroenterology and Hepatology, Stanford University Medical Center, Palo Alto, CA, USA
- Department of Epidemiology and Population Health, Stanford University Medical Center, Palo Alto, CA, USA
| | - Jian-Gao Fan
- Center for Fatty Liver, Department of Gastroenterology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - George Boon-Bee Goh
- Department of Gastroenterology and Hepatology, Singapore General Hospital, Singapore, Singapore
| | - Mamun Al Mahtab
- Department of Hepatology, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh
| | - Saeed Hamid
- Department of Medicine, Aga Khan University, Stadium Road, Karachi, 74800, Pakistan
| | - Nilanka Perera
- Department of Medicine, University of Sri Jayewardenepura, Nugegoda, Sri Lanka
| | - Jacob George
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital, University of Sydney, Sydney, NSW, 2145, Australia.
| | - Ming-Hua Zheng
- MAFLD Research Center, Department of Hepatology, The First Affiliated Hospital of Wenzhou Medical University, No. 2 Fuxue Lane, Wenzhou, 325000, China.
- Institute of Hepatology, Wenzhou Medical University, Wenzhou, China.
- Key Laboratory of Diagnosis and Treatment for the Development of Chronic Liver Disease in Zhejiang Province, Wenzhou, China.
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Vich Vila A, Hu S, Andreu-Sánchez S, Collij V, Jansen BH, Augustijn HE, Bolte LA, Ruigrok RAAA, Abu-Ali G, Giallourakis C, Schneider J, Parkinson J, Al-Garawi A, Zhernakova A, Gacesa R, Fu J, Weersma RK. Faecal metabolome and its determinants in inflammatory bowel disease. Gut 2023; 72:1472-1485. [PMID: 36958817 PMCID: PMC10359577 DOI: 10.1136/gutjnl-2022-328048] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 03/05/2023] [Indexed: 03/25/2023]
Abstract
OBJECTIVE Inflammatory bowel disease (IBD) is a multifactorial immune-mediated inflammatory disease of the intestine, comprising Crohn's disease and ulcerative colitis. By characterising metabolites in faeces, combined with faecal metagenomics, host genetics and clinical characteristics, we aimed to unravel metabolic alterations in IBD. DESIGN We measured 1684 different faecal metabolites and 8 short-chain and branched-chain fatty acids in stool samples of 424 patients with IBD and 255 non-IBD controls. Regression analyses were used to compare concentrations of metabolites between cases and controls and determine the relationship between metabolites and each participant's lifestyle, clinical characteristics and gut microbiota composition. Moreover, genome-wide association analysis was conducted on faecal metabolite levels. RESULTS We identified over 300 molecules that were differentially abundant in the faeces of patients with IBD. The ratio between a sphingolipid and L-urobilin could discriminate between IBD and non-IBD samples (AUC=0.85). We found changes in the bile acid pool in patients with dysbiotic microbial communities and a strong association between faecal metabolome and gut microbiota. For example, the abundance of Ruminococcus gnavus was positively associated with tryptamine levels. In addition, we found 158 associations between metabolites and dietary patterns, and polymorphisms near NAT2 strongly associated with coffee metabolism. CONCLUSION In this large-scale analysis, we identified alterations in the metabolome of patients with IBD that are independent of commonly overlooked confounders such as diet and surgical history. Considering the influence of the microbiome on faecal metabolites, our results pave the way for future interventions targeting intestinal inflammation.
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Affiliation(s)
- Arnau Vich Vila
- Department of Genetics, University Medical Centre, Groningen, The Netherlands
- Department of Pediatrics, University Medical Centre, Groningen, The Netherlands
| | - Shixian Hu
- Department of Genetics, University Medical Centre, Groningen, The Netherlands
- Department of Pediatrics, University Medical Centre, Groningen, The Netherlands
| | - Sergio Andreu-Sánchez
- Department of Pediatrics, University Medical Centre, Groningen, The Netherlands
- Department of Gastroenterology and Hepatology, University Medical Centre, Groningen, The Netherlands
| | - Valerie Collij
- Department of Genetics, University Medical Centre, Groningen, The Netherlands
- Department of Pediatrics, University Medical Centre, Groningen, The Netherlands
| | - Bernadien H Jansen
- Department of Genetics, University Medical Centre, Groningen, The Netherlands
| | - Hannah E Augustijn
- Department of Pediatrics, University Medical Centre, Groningen, The Netherlands
| | - Laura A Bolte
- Department of Genetics, University Medical Centre, Groningen, The Netherlands
| | - Renate A A A Ruigrok
- Department of Genetics, University Medical Centre, Groningen, The Netherlands
- Department of Pediatrics, University Medical Centre, Groningen, The Netherlands
| | - Galeb Abu-Ali
- Gastroenterology Drug Discovery Unit, Takeda Pharmaceutical, Cambridge, Massachusetts, USA
| | - Cosmas Giallourakis
- Gastroenterology Drug Discovery Unit, Takeda Pharmaceutical, Cambridge, Massachusetts, USA
| | - Jessica Schneider
- Gastroenterology Drug Discovery Unit, Takeda Pharmaceutical, Cambridge, Massachusetts, USA
| | - John Parkinson
- Gastroenterology Drug Discovery Unit, Takeda Pharmaceutical, Cambridge, Massachusetts, USA
| | - Amal Al-Garawi
- Gastroenterology Drug Discovery Unit, Takeda Pharmaceutical, Cambridge, Massachusetts, USA
| | | | - Ranko Gacesa
- Department of Genetics, University Medical Centre, Groningen, The Netherlands
- Department of Pediatrics, University Medical Centre, Groningen, The Netherlands
| | - Jingyuan Fu
- Department of Pediatrics, University Medical Centre, Groningen, The Netherlands
- Department of Gastroenterology and Hepatology, University Medical Centre, Groningen, The Netherlands
| | - Rinse K Weersma
- Department of Genetics, University Medical Centre, Groningen, The Netherlands
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Zhu X, Hong X, Wu J, Zhao F, Wang W, Huang L, Li J, Wang B. The Association between Circulating Lipids and Female Infertility Risk: A Univariable and Multivariable Mendelian Randomization Analysis. Nutrients 2023; 15:3130. [PMID: 37513548 PMCID: PMC10384410 DOI: 10.3390/nu15143130] [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: 06/07/2023] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Although observational studies have demonstrated that blood lipids are associated with female infertility, the causality of this association remains unclear. We performed a univariable and multivariable Mendelian randomization (MR) analysis to evaluate the causal relationship between blood lipids and female infertility. METHODS Single-nucleotide polymorphisms associated with lipid traits in univariate analysis were obtained from the Million Veteran Program (MVP) and Global Lipids Genetics Consortium (GLGC), involving up to 215,551 and 188,577 European individuals, respectively. Blood lipids in multivariate analysis were obtained from the latest genome-wide association study meta-analysis with lipid levels in 73 studies encompassing >300,000 participants. Data on female infertility were obtained from the FinnGen Consortium R6 release, which included 6481 samples and 75,450 controls. Subsequently, MR analysis was performed using inverse variance-weighted (IVW), weighted median, weighted-mode, simple-mode and MR-Egger regression to demonstrate the causal relationship between lipids and female infertility. RESULTS After controlling confounding factors including body mass index and age at menarche, two-sample MR demonstrated that genetically predicted LDL-C and TC were causally associated with the risk of female infertility (When the genetic instruments come from the MVP database, LDL-C and female infertility, IVW OR: 1.13, 95% CI: 1.001-1.269, p = 0.047; TC and female infertility, IVW OR: 1.16, 95% CI: 1.018-1.317, p = 0.025, and when the genetic instruments came from the GLGC database, LDL-C and female infertility, IVW OR: 1.10, 95% CI: 1.008-1.210, p = 0.033; TC and female infertility, IVW OR: 1.14, 95% CI: 1.024-1.258, p = 0.015). However, the IVW estimate showed that HDL-C was not significantly associated with the risk of female infertility (when the genetic instruments came from the MVP database, IVW OR: 1.00, 95% CI: 0.887-1.128, p = 0.999; when the genetic instruments came from the GLGC database, IVW OR: 1.00, 95% CI: 0.896-1.111, p = 0.968). The multivariable MR analysis also provided evidence that LDL-C (OR: 1.12, 95% CI: 1.006-1.243, p = 0.042) was significantly associated with the risk of female infertility after considering the correlation of all lipid-related traits. CONCLUSION These findings support a causal relationship between increased LDL-cholesterol and increased female infertility risk. Furthermore, the association between lipid-related traits and female infertility risk merits more studies.
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Affiliation(s)
- Xiaoqi Zhu
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - Xiang Hong
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - Jingying Wu
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - Fanqi Zhao
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - Wei Wang
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - Lingling Huang
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - Jiuming Li
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - Bei Wang
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
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Pik-Shan Kong A, Siu-Him Lau E, Chun-Kwan O, On-Yan Luk A, Cheuk-Fung Yip T, Yee-Kwan Chow E, Kwok R, Won Lee H, Lai-Hung Wong G, Ching-Wan Ma R, Lik-Yuen Chan H, Wai-Sun Wong V, Chung-Ngor Chan J. Advanced liver fibrosis predicts heart failure and hospitalizations in people with type 2 diabetes: A prospective cohort study from Hong Kong Diabetes Register. Diabetes Res Clin Pract 2023:110825. [PMID: 37442241 DOI: 10.1016/j.diabres.2023.110825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/05/2023] [Accepted: 07/08/2023] [Indexed: 07/15/2023]
Abstract
AIMS We aimed to examine the impact of non-alcoholic fatty liver disease (NAFLD) on the clinical outcomes in patients with type 2 diabetes (T2D). METHODS Between 2013 and 2014, 1,734 patients with T2D underwent transient elastography (TE) to assess liver status indicated by controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). Liver steatosis was defined by CAP ≥248 dB/m and advanced liver fibrosis by LSM ≥10kPa. In 2019, we assessed their clinical outcomes including hospitalizations and mortality. RESULTS In this prospective cohort [56% men, mean (±standard deviation) age:60.8±11.5 years; glycated hemoglobin (HbA1c)7.8±1.6 %], 798 patients had liver steatosis, 296 patients had advanced liver fibrosis and 640 patients had normal liver at baseline. T2D with advanced liver fibrosis had higher body mass index, waist circumference, waist-hip ratio, fasting plasma glucose, HbA1c, blood pressure and lipid profiles than their counterparts with NAFLD or normal liver (all p<0.05). After a median follow-up of 6.07 (interquartile range:5.84 to 6.30) years, there were 4,403 incident hospitalizations, 32,119 days of hospital stay, and 171 deaths. Using Cox regression analysis, advanced liver fibrosis was associated with increased risk of heart failure (hazard ratio [95% confidence interval] HR:3.07[1.08-8.68], p=0.035) and hospitalizations (HR: 1.39[1.14 -1.70], p=0.001) while liver steatosis was associated with reduced mortality (HR:0.60[0.41-0.87], p=0.007) compared to their counterparts with normal liver after adjustment for potential confounders. CONCLUSIONS T2D comorbid with liver steatosis and advanced liver fibrosis are distinct clinical entities with differences in outcomes. Advanced liver fibrosis is an important predictor for worse outcomes including heart failure and hospitalizations in people with T2D.
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Affiliation(s)
- Alice Pik-Shan Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Eric Siu-Him Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China; Asia Diabetes Foundation, Hong Kong SAR, China
| | - O Chun-Kwan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Andrea On-Yan Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Terry Cheuk-Fung Yip
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Elaine Yee-Kwan Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Raymond Kwok
- Department of Gastroenterology, Blacktown Hospital, Sydney, Australia
| | - Hye Won Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Grace Lai-Hung Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China; Medical Data Analytics Centre, Department of Medicine and Therapeutics, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Ronald Ching-Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Henry Lik-Yuen Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Vincent Wai-Sun Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Juliana Chung-Ngor Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong SAR, China; Asia Diabetes Foundation, Hong Kong SAR, China
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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 SLR, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJF, 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. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.28.23291966. [PMID: 37425772 PMCID: PMC10327287 DOI: 10.1101/2023.06.28.23291966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the 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 blood lipid levels (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 variations and rare protein coding variations 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 lncRNA, implicating new therapeutic opportunities.
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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, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology & Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 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
- 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
| | - 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 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
| | - 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
| | | | - 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
| | | | | | - 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
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Zuo Y, He Z, Chen Y, Dai L. Dual role of ANGPTL4 in inflammation. Inflamm Res 2023:10.1007/s00011-023-01753-9. [PMID: 37300585 DOI: 10.1007/s00011-023-01753-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/24/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023] Open
Abstract
BACKGROUND Angiopoietin-like 4 (ANGPTL4) belongs to the angiopoietin-like protein family and mediates the inhibition of lipoprotein lipase activity. Emerging evidence suggests that ANGPTL4 has pleiotropic functions with anti- and pro-inflammatory properties. METHODS A thorough search on PubMed related to ANGPTL4 and inflammation was performed. RESULTS Genetic inactivation of ANGPTL4 can significantly reduce the risk of developing coronary artery disease and diabetes. However, antibodies against ANGPTL4 result in several undesirable effects in mice or monkeys, such as lymphadenopathy and ascites. Based on the research progress on ANGPTL4, we systematically discussed the dual role of ANGPTL4 in inflammation and inflammatory diseases (lung injury, pancreatitis, heart diseases, gastrointestinal diseases, skin diseases, metabolism, periodontitis, and osteolytic diseases). This may be attributed to several factors, including post-translational modification, cleavage and oligomerization, and subcellular localization. CONCLUSION Understanding the potential underlying mechanisms of ANGPTL4 in inflammation in different tissues and diseases will aid in drug discovery and treatment development.
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Affiliation(s)
- Yuyue Zuo
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
- Department of Dermatology, Wuhan No. 1 Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Zhen He
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
- Hubei Provincial Engineering Research Center of Vascular Interventional Therapy, Wuhan, 430030, Hubei, China
| | - Yu Chen
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
- Hubei Provincial Engineering Research Center of Vascular Interventional Therapy, Wuhan, 430030, Hubei, China
| | - Lei Dai
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
- Hubei Provincial Engineering Research Center of Vascular Interventional Therapy, Wuhan, 430030, Hubei, China.
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