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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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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: 16] [Impact Index Per Article: 16.0] [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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Oh JH, Jun DW. Nonalcoholic fatty liver disease–related extrahepatic complications, associated outcomes, and their treatment considerations. METABOLIC STEATOTIC LIVER DISEASE 2024:101-122. [DOI: 10.1016/b978-0-323-99649-5.00007-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
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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: 18] [Impact Index Per Article: 18.0] [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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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: 0.5] [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: 99] [Impact Index Per Article: 49.5] [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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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: 0.5] [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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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: 2] [Impact Index Per Article: 1.0] [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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61
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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: 1.5] [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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62
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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: 7] [Impact Index Per Article: 3.5] [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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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: 0.5] [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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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: 20] [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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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: 0.5] [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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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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Eslam M, George J. Two years on, a perspective on MAFLD. EGASTROENTEROLOGY 2023; 1:e100019. [PMID: 39943998 PMCID: PMC11770426 DOI: 10.1136/egastro-2023-100019] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 04/24/2023] [Indexed: 01/03/2025]
Abstract
To provide clarity for research studies and clinical care, a set of positive criteria for adults and children with metabolic (dysfunction) associated fatty liver disease (MAFLD) was recently published and has subsequently been widely endorsed. The development and subsequent validation of the criteria for MAFLD has created a positive momentum for change. During the course of the ongoing discussion on the redefinition, some concerns have surfaced that we thought needs clarification. In this review, we provide a perspective on MAFLD and bringing clarity to some of the key aspects that have been recently raised.
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Affiliation(s)
- Mohammed Eslam
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, New South Wales, Australia
| | - Jacob George
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, New South Wales, Australia
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68
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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: 4] [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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69
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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: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [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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Kong APS, Lau ESH, O CK, Luk AOY, Yip TCF, Chow EYK, Kwok R, Lee HW, Wong GLH, Ma RCW, Chan HLY, Wong VWS, Chan JCN. 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; 202:110825. [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] [MESH Headings] [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 ≥ 10 kPa. 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 Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region.
| | - Eric Siu-Him Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Asia Diabetes Foundation, Hong Kong Special Administrative Region
| | - Chun-Kwan O
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Andrea On-Yan Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Terry Cheuk-Fung Yip
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Elaine Yee-Kwan Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Raymond Kwok
- Department of Gastroenterology, Blacktown Hospital, Sydney, Australia
| | - Hye Won Lee
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Grace Lai-Hung Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Medical Data Analytics Centre, Department of Medicine and Therapeutics, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Ronald Ching-Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Henry Lik-Yuen Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Vincent Wai-Sun Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region.
| | - Juliana Chung-Ngor Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Asia Diabetes Foundation, Hong Kong Special Administrative Region
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71
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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: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [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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72
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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: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [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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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, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, 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: 33] [Impact Index Per Article: 16.5] [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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75
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Ma Q, Wen L, Tian Y, Ma L, Wen Z, Kun Y, Xu M, Liu X. Sulfosuccinimidyl oleate ameliorates the high-fat diet-induced obesity syndrome by reducing intestinal and hepatic absorption. Front Pharmacol 2023; 14:1193006. [PMID: 37305546 PMCID: PMC10254412 DOI: 10.3389/fphar.2023.1193006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/04/2023] [Indexed: 06/13/2023] Open
Abstract
Background: A high-fat Western diet is a risk factor for obesity and steatosis. Reducing intestinal absorption of a high-fat diet (HFD) is a feasible strategy to control obesity. Sulfosuccinimidyl oleate (SSO) inhibits intestinal fatty acid transport. Therefore, the aim of this study was to investigate the effects of SSO on HFD-induced glucose and lipid metabolism in mice and its possible underlying mechanisms. Methods: Male C57/BL were fed a HFD (60% calories) for 12 weeks and were administered an oral dose of SSO (50 mg/kg/day). The expression of lipid absorption genes (CD36, MTTP, and DGAT1) and the serum levels of triglycerides (TGs), total cholesterol (TC), and free fatty acids (FFAs) were detected. Lipid distribution in the liver was detected by oil red and hematoxylin and eosin staining. In addition, serum levels of inflammatory factors, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were measured to detect side effects. Results: SSO was effective in the treatment of obesity and metabolic syndrome induced by HFD in mice. It attenuated the assembly of intestinal epithelial chylomicrons by inhibiting intestinal epithelial transport and absorption of fatty acids, thereby reducing the gene expression levels of MTTP and DGAT1, resulting in decreased plasma TG and FFA levels. At the same time, it inhibited the transport of fatty acids in the liver and improved the steatosis induced by a HFD. The results of oil red staining showed that SSO treatment can reduce lipid accumulation in the liver by 70%, with no drug-induced liver injury detected on the basis of interleukin-6, C-reactive protein, ALT, and AST levels. In addition, SSO treatment significantly improved insulin resistance, decreased fasting blood glucose levels, and improved glucose tolerance in HFD-fed mice. Conclusion: SSO is effective in the treatment of obesity and metabolic syndrome induced by a HFD in mice. SSO reduces intestinal fatty acid absorption by reducing the inhibition of intestinal CD36 expression, followed by decreased TG and FFA levels, which attenuates HFD-induced fatty liver.
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Affiliation(s)
- Qiming Ma
- The Department of General Surgery, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Li Wen
- Department of Neonatology, Ganzhou Maternal and Child Health Centre, Ganzhou, Jiangxi, China
| | - Yanxia Tian
- Department of Blood Transfusion, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Liqin Ma
- The Second Department of Surgery, People’s Hospital of Shicheng County, Ganzhou, Jiangxi, China
| | - Zhangsheng Wen
- The CT Room of the Imaging Department, People’s Hospital of Shicheng County, Ganzhou, Jiangxi, China
| | - Yang Kun
- Department of Blood Transfusion, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Mengping Xu
- The Department of General Surgery, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Xiaoping Liu
- The Department of General Surgery, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
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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. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.11.23289852. [PMID: 37293013 PMCID: PMC10246076 DOI: 10.1101/2023.05.11.23289852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Many diseases 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 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. Using PheWAS summary statistics from the UK Biobank, we constructed a ssDDN+ revealing hundreds of genetic correlations between disease phenotypes 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 diabetic retinopathy. Triglycerides, another blood lipid with known genetics causes in non-mendelian diseases, also adds a substantial number of edges to the ssDDN. 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.
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Affiliation(s)
- Jakob Woerner
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Vivek Sriram
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yonghyun Nam
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Anurag Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dokyoon Kim
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
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Zhang D, Mi Z, Peng J, Yang T, Han Y, Zhai Y, Song C, Teng X, Sun W, Guo J, Bilonda KP. Nonalcoholic Fatty Liver Disease as an Emerging Risk Factor and Potential Intervention Target for Atherosclerotic Cardiovascular Diseases. J Cardiovasc Pharmacol 2023; 81:327-335. [PMID: 36917556 PMCID: PMC10155697 DOI: 10.1097/fjc.0000000000001418] [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: 11/20/2022] [Accepted: 02/23/2023] [Indexed: 03/16/2023]
Abstract
ABSTRACT Nonalcoholic fatty liver disease (NAFLD) is an underappreciated independent risk factor for atherosclerotic cardiovascular diseases (ASCVDs). In recent years, the risk of ASCVD has increased along with the prevalence of NAFLD. ASCVD events are highly prevalent and are the main contributor to death in patients with NAFLD. The association between NAFLD and ASCVD has been validated in numerous observational, cohort, and genetic studies. Most of these studies agree that NAFLD significantly increases the risk of developing atherosclerosis and ASCVD. In addition, the underlying proatherosclerotic mechanisms of NAFLD have been gradually revealed; both disorders share several common pathophysiologic mechanisms including insulin resistance, whereas systemic inflammation and dyslipidemia driven by NAFLD directly promote atherosclerosis. Recently, NAFLD, as an emerging risk enhancer for ASCVD, has attracted attention as a potential treatment target for ASCVD. This brief review aims to illustrate the potential mechanistic insights, present recent clinically relevant investigations, and further explore the emerging therapies such as novel antidiabetic and lipid-lowering agents that could improve NAFLD and reduce ASCVD risk.
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Affiliation(s)
- Daqing Zhang
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
| | - Zhen Mi
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
| | - Jiya Peng
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
| | - Tiangui Yang
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
| | - Yuze Han
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
- Department of Cardiology, Dalian Friendship Hospital, Dalian City, PR China; and
| | - Yujia Zhai
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
| | - Chenliang Song
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
| | - Xianzhuo Teng
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
| | - Wei Sun
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
- Department of Cardiology, Dalian Third People's Hospital, Dalian City, PR China
| | - Jing Guo
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
| | - Kabeya Paulin Bilonda
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang City, PR China
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Gomes D, Sobolewski C, Conzelmann S, Schaer T, Lefai E, Alfaiate D, Tseligka ED, Goossens N, Tapparel C, Negro F, Foti M, Clément S. ANGPTL4 is a potential driver of HCV-induced peripheral insulin resistance. Sci Rep 2023; 13:6767. [PMID: 37185283 PMCID: PMC10130097 DOI: 10.1038/s41598-023-33728-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 04/18/2023] [Indexed: 05/17/2023] Open
Abstract
Chronic hepatitis C (CHC) is associated with the development of metabolic disorders, including both hepatic and extra-hepatic insulin resistance (IR). Here, we aimed at identifying liver-derived factor(s) potentially inducing peripheral IR and uncovering the mechanisms whereby HCV can regulate the action of these factors. We found ANGPTL4 (Angiopoietin Like 4) mRNA expression levels to positively correlate with HCV RNA (r = 0.46, p < 0.03) and HOMA-IR score (r = 0.51, p = 0.01) in liver biopsies of lean CHC patients. Moreover, we observed an upregulation of ANGPTL4 expression in two models recapitulating HCV-induced peripheral IR, i.e. mice expressing core protein of HCV genotype 3a (HCV-3a core) in hepatocytes and hepatoma cells transduced with HCV-3a core. Treatment of differentiated myocytes with recombinant ANGPTL4 reduced insulin-induced Akt-Ser473 phosphorylation. In contrast, conditioned medium from ANGPTL4-KO hepatoma cells prevented muscle cells from HCV-3a core induced IR. Treatment of HCV-3a core expressing HepG2 cells with PPARγ antagonist resulted in a decrease of HCV-core induced ANGPTL4 upregulation. Together, our data identified ANGPTL4 as a potential driver of HCV-induced IR and may provide working hypotheses aimed at understanding the pathogenesis of IR in the setting of other chronic liver disorders.
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Affiliation(s)
- Diana Gomes
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
- Koch Institute for Integrative Cancer Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cyril Sobolewski
- Cell Physiology and Metabolism, University of Geneva, Geneva, Switzerland
- U1286-INFINITE-Institute for Translational Research in Inflammation, CHU Lille, Inserm, University Lille, 59000, Lille, France
| | - Stéphanie Conzelmann
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
| | - Tifany Schaer
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
| | - Etienne Lefai
- Unité de Nutrition Humaine, INRAE, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
| | - Dulce Alfaiate
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
- Department of Infectious Diseases, Hôpital de la Croix Rousse, Lyon University Hospitals, Lyon, France
| | - Eirini D Tseligka
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
| | - Nicolas Goossens
- Gastroenterology and Hepatology Division, University Hospitals, Geneva, Switzerland
| | - Caroline Tapparel
- Department of Microbiology and Molecular Medicine, University of Geneva, Geneva, Switzerland
| | - Francesco Negro
- Gastroenterology and Hepatology Division, University Hospitals, Geneva, Switzerland
- Clinical Pathology Division, University Hospitals, Geneva, Switzerland
| | - Michelangelo Foti
- Cell Physiology and Metabolism, University of Geneva, Geneva, Switzerland
| | - Sophie Clément
- Department of Microbiology and Molecular Medicine, University of Geneva, Geneva, Switzerland.
- Clinical Pathology Division, University Hospitals, Geneva, Switzerland.
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Zhang Y, Zhu Z, Sun L, Yin W, Liang Y, Chen H, Bi Y, Zhai W, Yin Y, Zhang W. Hepatic G Protein-Coupled Receptor 180 Deficiency Ameliorates High Fat Diet-Induced Lipid Accumulation via the Gi-PKA-SREBP Pathway. Nutrients 2023; 15:1838. [PMID: 37111058 PMCID: PMC10144310 DOI: 10.3390/nu15081838] [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: 03/10/2023] [Revised: 04/09/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023] Open
Abstract
Single-nucleotide polymorphisms in G protein-coupled receptor 180 (GPR180) are associated with hypertriglyceridemia. The aim of this study was to determine whether hepatic GPR180 impacts lipid metabolism. Hepatic GPR180 was knocked down using two approaches: Gpr180-specific short hairpin (sh)RNA carried by adeno-associated virus 9 (AAV9) and alb-Gpr180-/- transgene established by crossbreeding albumin-Cre mice with Gpr180flox/flox animals, in which Gpr180 was specifically knocked down in hepatocytes. Adiposity, hepatic lipid contents, and proteins related to lipid metabolism were analyzed. The effects of GPR180 on triglyceride and cholesterol synthesis were further verified by knocking down or overexpressing Gpr180 in Hepa1-6 cells. Gpr180 mRNA was upregulated in the liver of HFD-induced obese mice. Deficiency of Gpr180 decreased triglyceride and cholesterol contents in the liver and plasma, ameliorated hepatic lipid deposition in HFD-induced obese mice, increased energy metabolism, and reduced adiposity. These alterations were associated with downregulation of transcription factors SREBP1 and SREBP2, and their target acetyl-CoA carboxylase. In Hepa1-6 cells, Gpr180 knockdown decreased intracellular triglyceride and cholesterol contents, whereas its overexpression increased their levels. Overexpression of Gpr180 significantly reduced the PKA-mediated phosphorylation of substrates and consequent CREB activity. Hence, GPR180 might represent a novel drug target for intervention of adiposity and liver steatosis.
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Affiliation(s)
- Yunhua Zhang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
- The Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of Medicine, Shihezi 832002, China
| | - Ziming Zhu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Lijun Sun
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Wenzhen Yin
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Yuan Liang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Hong Chen
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Yanghui Bi
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Wenbo Zhai
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
| | - Yue Yin
- Department of Pharmacology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China
| | - Weizhen Zhang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Peking University, Beijing 100191, China; (Y.Z.); (Z.Z.)
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Kosmalski M, Śliwińska A, Drzewoski J. Non-Alcoholic Fatty Liver Disease or Type 2 Diabetes Mellitus—The Chicken or the Egg Dilemma. Biomedicines 2023; 11:biomedicines11041097. [PMID: 37189715 DOI: 10.3390/biomedicines11041097] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/28/2023] [Accepted: 03/28/2023] [Indexed: 04/08/2023] Open
Abstract
In clinical practice, we often deal with patients who suffer from non-alcoholic fatty liver disease (NAFLD) concurrent with type 2 diabetes mellitus (T2DM). The etiopathogenesis of NAFLD is mainly connected with insulin resistance (IR) and obesity. Similarly, the latter patients are in the process of developing T2DM. However, the mechanisms of NAFLD and T2DM coexistence have not been fully elucidated. Considering that both diseases and their complications are of epidemic proportions and significantly affect the length and quality of life, we aimed to answer which of these diseases appears first and thereby highlight the need for their diagnosis and treatment. To address this question, we present and discuss the epidemiological data, diagnoses, complications and pathomechanisms of these two coexisting metabolic diseases. This question is difficult to answer due to the lack of a uniform procedure for NAFLD diagnosis and the asymptomatic nature of both diseases, especially at their beginning stages. To conclude, most researchers suggest that NAFLD appears as the first disease and starts the sequence of circumstances leading ultimately to the development of T2DM. However, there are also data suggesting that T2DM develops before NAFLD. Despite the fact that we cannot definitively answer this question, it is very important to bring the attention of clinicians and researchers to the coexistence of NAFLD and T2DM in order to prevent their consequences.
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Affiliation(s)
- Marcin Kosmalski
- Department of Clinical Pharmacology, Medical University of Lodz, 90-153 Lodz, Poland
| | - Agnieszka Śliwińska
- Department of Nucleic Acids Biochemistry, Medical University of Lodz, 92-213 Lodz, Poland
| | - Józef Drzewoski
- Central Teaching Hospital of Medical University of Lodz, 92-213 Lodz, Poland
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81
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Wang G, Bond TA, Warrington NM, Evans DM. Birth weight and cardiometabolic risk factors: a discordant twin study in the UK Biobank. J Dev Orig Health Dis 2023; 14:242-248. [PMID: 36193707 PMCID: PMC7615918 DOI: 10.1017/s2040174422000538] [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: 11/06/2022]
Abstract
One of the longstanding debates in life-course epidemiology is whether an adverse intrauterine environment, often proxied by birth weight, causally increases the future risk of cardiometabolic disease. The use of a discordant twin study design, which controls for the influence of shared genetic and environmental confounding factors, may be useful to investigate whether this relationship is causal. We conducted a discordant twin study of 120 monozygotic (MZ) and 148 dizygotic (DZ) twin pairs from the UK Biobank to explore the potential causal relationships between birth weight and a broad spectrum of later-life cardiometabolic risk factors. We used a linear mixed model to investigate the association between birth weight and later-life cardiometabolic risk factors for twins, allowing for both within-pair differences and between-pair differences in birth weight. Of primary interest is the within-pair association between differences in birth weight and cardiometabolic risk factors, which could reflect an intrauterine effect on later-life risk factors. We found no strong evidence of association in MZ twins between the within-pair differences in birth weight and most cardiometabolic risk factors in later life, except for nominal associations with C-reactive protein and insulin-like growth factor 1. However, these associations were not replicated in DZ twin pairs. Our study provided no strong evidence for intrauterine effects on later-life cardiometabolic risk factors, which is consistent with previous large-scale studies of singletons testing the potential causal relationship. It does not support the hypothesis that adverse intrauterine environments increase the risk of cardiometabolic disease in later life.
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Affiliation(s)
- Geng Wang
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia
- Institute for Molecular Biosciences, The University of Queensland, Brisbane, Australia
| | - Tom A Bond
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK
| | - Nicole M Warrington
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia
- Institute for Molecular Biosciences, The University of Queensland, Brisbane, Australia
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - David M Evans
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia
- Institute for Molecular Biosciences, The University of Queensland, Brisbane, Australia
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK
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Abstract
Thalassemia syndromes are common monogenic disorders and represent a significant health issue worldwide. In this review, the authors elaborate on fundamental genetic knowledge about thalassemias, including the structure and location of globin genes, the production of hemoglobin during development, the molecular lesions causing α-, β-, and other thalassemia syndromes, the genotype-phenotype correlation, and the genetic modifiers of these conditions. In addition, they briefly discuss the molecular techniques applied for diagnosis and innovative cell and gene therapy strategies to cure these conditions.
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Affiliation(s)
- Nicolò Tesio
- Department of Clinical and Biological Sciences, San Luigi Gonzaga University Hospital, University of Torino, Regione Gonzole, 10, 10043 Orbassano, Turin, Italy. https://twitter.com/nicolotesio
| | - Daniel E Bauer
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Pediatrics, Harvard Stem Cell Institute, Broad Institute, Harvard Medical School, Boston, MA, USA.
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83
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Adams LA. Cardiovascular disease in metabolic-associated fatty liver disease. Curr Opin Endocrinol Diabetes Obes 2023; 30:81-86. [PMID: 36779252 DOI: 10.1097/med.0000000000000803] [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: 02/14/2023]
Abstract
PURPOSE OF REVIEW Fatty liver disease is increasingly common worldwide and is associated with an increased risk of cardiovascular disease (CVD). RECENT FINDINGS This review describes the cardiovascular outcomes, clinical assessment and management as well as the impact of emerging drug treatment on CVD risk. SUMMARY Patients with fatty liver require CVD risk assessment including consideration of statin therapy. Emerging therapeutic drugs for fatty liver may have both adverse and beneficial effects on CVD risk.
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Affiliation(s)
- Leon A Adams
- Medical School, University of Western Australia
- Department of Hepatology, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
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Clifford BL, Jarrett KE, Cheng J, Cheng A, Seldin M, Morand P, Lee R, Chen M, Baldan A, de Aguiar Vallim TQ, Tarling EJ. RNF130 Regulates LDLR Availability and Plasma LDL Cholesterol Levels. Circ Res 2023; 132:849-863. [PMID: 36876496 PMCID: PMC10065965 DOI: 10.1161/circresaha.122.321938] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 02/23/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Removal of circulating plasma low-density lipoprotein cholesterol (LDL-C) by the liver relies on efficient endocytosis and intracellular vesicle trafficking. Increasing the availability of hepatic LDL receptors (LDLRs) remains a major clinical target for reducing LDL-C levels. Here, we describe a novel role for RNF130 (ring finger containing protein 130) in regulating plasma membrane availability of LDLR. METHODS We performed a combination of gain-of-function and loss-of-function experiments to determine the effect of RNF130 on LDL-C and LDLR recycling. We overexpressed RNF130 and a nonfunctional mutant RNF130 in vivo and measured plasma LDL-C and hepatic LDLR protein levels. We performed in vitro ubiquitination assays and immunohistochemical staining to measure levels and cellular distribution of LDLR. We supplement these experiments with 3 separate in vivo models of RNF130 loss-of-function where we disrupted Rnf130 using either ASO (antisense oligonucleotides), germline deletion, or AAV CRISPR (adeno-associated virus clustered regularly interspaced short palindromic repeats) and measured hepatic LDLR and plasma LDL-C. RESULTS We demonstrate that RNF130 is an E3 ubiquitin ligase that ubiquitinates LDLR resulting in redistribution of the receptor away from the plasma membrane. Overexpression of RNF130 decreases hepatic LDLR and increases plasma LDL-C levels. Further, in vitro ubiquitination assays demonstrate RNF130-dependent regulation of LDLR abundance at the plasma membrane. Finally, in vivo disruption of Rnf130 using ASO, germline deletion, or AAV CRISPR results in increased hepatic LDLR abundance and availability and decreased plasma LDL-C levels. CONCLUSIONS Our studies identify RNF130 as a novel posttranslational regulator of LDL-C levels via modulation of LDLR availability, thus providing important insight into the complex regulation of hepatic LDLR protein levels.
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Affiliation(s)
- Bethan L. Clifford
- Department of Medicine, Division of Cardiology, University of California Los Angeles, CA, USA
| | - Kelsey E. Jarrett
- Department of Medicine, Division of Cardiology, University of California Los Angeles, CA, USA
| | - Joan Cheng
- Department of Biological Chemistry, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
| | - Angela Cheng
- Department of Biological Chemistry, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
| | - Marcus Seldin
- Department of Biological Chemistry, University of California Irvine, CA, USA
| | - Pauline Morand
- Department of Biological Chemistry, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
| | | | - Mary Chen
- Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University, St. Louis, MO, USA
| | - Angel Baldan
- Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University, St. Louis, MO, USA
| | - Thomas Q. de Aguiar Vallim
- Department of Medicine, Division of Cardiology, University of California Los Angeles, CA, USA
- Department of Biological Chemistry, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
- Molecular Biology Institute, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
| | - Elizabeth J. Tarling
- Department of Medicine, Division of Cardiology, University of California Los Angeles, CA, USA
- Molecular Biology Institute, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
- Lead contact
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Nádasdi Á, Gál V, Masszi T, Somogyi A, Firneisz G. PNPLA3 rs738409 risk genotype decouples TyG index from HOMA2-IR and intrahepatic lipid content. Cardiovasc Diabetol 2023; 22:64. [PMID: 36944955 PMCID: PMC10031960 DOI: 10.1186/s12933-023-01792-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Recent reports suggested a different predictive value for TyG index compared to HOMA-IR in coronary artery calcification (CAC) and other atherosclerotic outcomes, despite that both indices are proposed as surrogate markers of insulin resistance. We hypothesized a key role for liver pathology as an explanation and therefore assessed the relationship among the two indices and the intrahepatic lipid content stratified by PNPLA3 rs738409 genotypes as a known non-alcoholic fatty liver disease (NAFLD) genetic risk. METHODS Thirty-nine women from a prior GDM-genetic study were recalled with PNPLA3 rs738409 CC and GG genotypes for metabolic phenotyping and to assess hepatic triglyceride content (HTGC). 75 g OGTT was performed, fasting lipid, glucose, insulin levels and calculated insulin resistance indices (TyG and HOMA2-IR) were used. HTGC was measured by MR based methods. Mann-Whitney-U, χ2 and for the correlation analysis Spearman rank order tests were applied. RESULTS The PNPLA3 rs738409 genotype had a significant effect on the direct correlation between the HOMA2-IR and TyG index: the correlation (R = 0.52, p = 0.0054) found in the CC group was completely abolished in those with the GG (NAFLD) risk genotype. In addition, the HOMA2-IR correlated with HTGC in the entire study population (R = 0.69, p < 0.0001) and also separately in both genotypes (CC R = 0.62, p = 0.0006, GG: R = 0.74, p = 0.0058). In contrast, the correlation between TyG index and HTGC was only significant in rs738409 CC genotype group (R = 0.42, p = 0.0284) but not in GG group. A similar pattern was observed in the correlation between TG and HTGC (CC: R = 0.41, p = 0.0335), when the components of the TyG index were separately assessed. CONCLUSIONS PNPLA3 rs738409 risk genotype completely decoupled the direct correlation between two surrogate markers of insulin resistance: TyG and HOMA2-IR confirming our hypothesis. The liver lipid content increased in parallel with the HOMA2-IR independent of genotype, in contrast to the TyG index where the risk genotype abolished the correlation. This phenomenon seems to be related to the nature of hepatic fat accumulation and to the different concepts establishing the two insulin resistance markers.
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Affiliation(s)
- Ákos Nádasdi
- Translational Medicine Institute, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- Department of Internal Medicine and Haematology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Viktor Gál
- Brain Imaging Centre, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary
- Medical Imaging Centre, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Tamás Masszi
- Department of Internal Medicine and Haematology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Anikó Somogyi
- Department of Internal Medicine and Haematology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Gábor Firneisz
- Translational Medicine Institute, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
- Department of Internal Medicine and Haematology, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
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Torres-Peña JD, Arenas-de Larriva AP, Alcala-Diaz JF, Lopez-Miranda J, Delgado-Lista J. Different Dietary Approaches, Non-Alcoholic Fatty Liver Disease and Cardiovascular Disease: A Literature Review. Nutrients 2023; 15:nu15061483. [PMID: 36986213 PMCID: PMC10058124 DOI: 10.3390/nu15061483] [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: 02/20/2023] [Revised: 03/14/2023] [Accepted: 03/19/2023] [Indexed: 03/30/2023] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is the first cause of chronic liver disease and is also associated with other harmful entities such as obesity, metabolic syndrome, dyslipidemia, and diabetes. NAFLD is a significant public health concern worldwide, impacting individuals of all ages, and its prevalence is projected to increase in the near future due to its connection with obesity. Intrinsic (genetics) and external (lifestyle) factors may also modulate NAFLD, and, in turn, may partly explain the observed relationship between NAFLD and cardiovascular disease (CVD). Although many drugs are been tested to treat NAFLD, to date, no drug has indication to specifically treat this disorder. Thus, the current management of NAFLD relies on lifestyle modifications and specifically on weight loss, physical activity, and the intake of a healthy diet. In the present narrative review, we will discuss the effects of certain dietary patterns on NAFLD incidence and progression.
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Affiliation(s)
- Jose D Torres-Peña
- Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Av. Menéndez Pidal s/n, 14004 Cordoba, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Antonio P Arenas-de Larriva
- Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Av. Menéndez Pidal s/n, 14004 Cordoba, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Juan F Alcala-Diaz
- Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Av. Menéndez Pidal s/n, 14004 Cordoba, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jose Lopez-Miranda
- Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Av. Menéndez Pidal s/n, 14004 Cordoba, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Javier Delgado-Lista
- Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Av. Menéndez Pidal s/n, 14004 Cordoba, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
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Tudor L, Nedic Erjavec G, Nikolac Perkovic M, Konjevod M, Uzun S, Kozumplik O, Mimica N, Lauc G, Svob Strac D, Pivac N. The Association of the Polymorphisms in the FUT8-Related Locus with the Plasma Glycosylation in Post-Traumatic Stress Disorder. Int J Mol Sci 2023; 24:ijms24065706. [PMID: 36982780 PMCID: PMC10056189 DOI: 10.3390/ijms24065706] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/04/2023] [Accepted: 03/11/2023] [Indexed: 03/19/2023] Open
Abstract
The molecular underpinnings of post-traumatic stress disorder (PTSD) are still unclear due to the complex interactions of genetic, psychological, and environmental factors. Glycosylation is a common post-translational modification of proteins, and different pathophysiological states, such as inflammation, autoimmune diseases, and mental disorders including PTSD, show altered N-glycome. Fucosyltransferase 8 (FUT8) is the enzyme that catalyzes the addition of core fucose on glycoproteins, and mutations in the FUT8 gene are associated with defects in glycosylation and functional abnormalities. This is the first study that investigated the associations of plasma N-glycan levels with FUT8-related rs6573604, rs11621121, rs10483776, and rs4073416 polymorphisms and their haplotypes in 541 PTSD patients and control participants. The results demonstrated that the rs6573604 T allele was more frequent in the PTSD than in the control participants. Significant associations of plasma N-glycan levels with PTSD and FUT8-related polymorphisms were observed. We also detected associations of rs11621121 and rs10483776 polymorphisms and their haplotypes with plasma levels of specific N-glycan species in both the control and PTSD groups. In carriers of different rs6573604 and rs4073416 genotypes and alleles, differences in plasma N-glycan levels were only found in the control group. These molecular findings suggest a possible regulatory role of FUT8-related polymorphisms in glycosylation, the alternations of which could partially explain the development and clinical manifestation of PTSD.
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Affiliation(s)
- Lucija Tudor
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.)
| | - Gordana Nedic Erjavec
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.)
| | - Matea Nikolac Perkovic
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.)
| | - Marcela Konjevod
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.)
| | - Suzana Uzun
- Department for Biological Psychiatry and Psychogeriatrics, University Hospital Vrapce, 10000 Zagreb, Croatia; (S.U.); (O.K.); (N.M.)
- School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
- Faculty of Education and Rehabilitation Sciences, University of Zagreb, 10000 Zagreb, Croatia
| | - Oliver Kozumplik
- Department for Biological Psychiatry and Psychogeriatrics, University Hospital Vrapce, 10000 Zagreb, Croatia; (S.U.); (O.K.); (N.M.)
- Faculty of Education and Rehabilitation Sciences, University of Zagreb, 10000 Zagreb, Croatia
| | - Ninoslav Mimica
- Department for Biological Psychiatry and Psychogeriatrics, University Hospital Vrapce, 10000 Zagreb, Croatia; (S.U.); (O.K.); (N.M.)
- School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Gordan Lauc
- Glycobiology Laboratory, Genos Ltd., 10000 Zagreb, Croatia;
| | - Dubravka Svob Strac
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.)
- Correspondence: (D.S.S.); (N.P.)
| | - Nela Pivac
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (L.T.); (G.N.E.); (M.N.P.); (M.K.)
- University of Applied Sciences Hrvatsko Zagorje Krapina, 49000 Krapina, Croatia
- Correspondence: (D.S.S.); (N.P.)
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88
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Dron JS, Patel AP, Zhang Y, Jurgens SJ, Maamari DJ, Wang M, Boerwinkle E, Morrison AC, de Vries PS, Fornage M, Hou L, Lloyd-Jones DM, Psaty BM, Tracy RP, Bis JC, Vasan RS, Levy D, Heard-Costa N, Rich SS, Guo X, Taylor KD, Gibbs RA, Rotter JI, Willer CJ, Oelsner EC, Moran AE, Peloso GM, Natarajan P, Khera AV. Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease. JAMA Cardiol 2023; 8:258-267. [PMID: 36723951 PMCID: PMC9996405 DOI: 10.1001/jamacardio.2022.5271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 11/29/2022] [Indexed: 02/02/2023]
Abstract
Importance Protein-truncating variants (PTVs) in apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are associated with significantly lower low-density lipoprotein (LDL) cholesterol concentrations. The association of these PTVs with coronary heart disease (CHD) warrants further characterization in large, multiracial prospective cohort studies. Objective To evaluate the association of PTVs in APOB and PCSK9 with LDL cholesterol concentrations and CHD risk. Design, Setting, and Participants This studied included participants from 5 National Heart, Lung, and Blood Institute (NHLBI) studies and the UK Biobank. NHLBI study participants aged 5 to 84 years were recruited between 1971 and 2002 across the US and underwent whole-genome sequencing. UK Biobank participants aged 40 to 69 years were recruited between 2006 and 2010 in the UK and underwent whole-exome sequencing. Data were analyzed from June 2021 to October 2022. Exposures PTVs in APOB and PCSK9. Main Outcomes and Measures Estimated untreated LDL cholesterol levels and CHD. Results Among 19 073 NHLBI participants (10 598 [55.6%] female; mean [SD] age, 52 [17] years), 139 (0.7%) carried an APOB or PCSK9 PTV, which was associated with 49 mg/dL (95% CI, 43-56) lower estimated untreated LDL cholesterol level. Over a median (IQR) follow-up of 21.5 (13.9-29.4) years, incident CHD was observed in 12 of 139 carriers (8.6%) vs 3029 of 18 934 noncarriers (16.0%), corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.28-0.89; P = .02). Among 190 464 UK Biobank participants (104 831 [55.0%] female; mean [SD] age, 57 [8] years), 662 (0.4%) carried a PTV, which was associated with 45 mg/dL (95% CI, 42-47) lower estimated untreated LDL cholesterol level. Estimated CHD risk by age 75 years was 3.7% (95% CI, 2.0-5.3) in carriers vs 7.0% (95% CI, 6.9-7.2) in noncarriers, corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.32-0.81; P = .004). Conclusions and Relevance Among 209 537 individuals in this study, 0.4% carried an APOB or PCSK9 PTV that was associated with less exposure to LDL cholesterol and a 49% lower risk of CHD.
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Affiliation(s)
- Jacqueline S. Dron
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Aniruddh P. Patel
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston
| | - Yiyi Zhang
- Division of General Medicine, Columbia University, New York, New York
| | - Sean J. Jurgens
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Experimental Cardiology, Amsterdam UMC, Amsterdam, the Netherlands
| | - Dimitri J. Maamari
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Minxian Wang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - 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
| | - 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
| | - 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
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
- Department of Health Systems and Population Health, University of Washington, Seattle
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine at the University of Vermont, Colchester, Vermont
- Department of Biochemistry, Larner College of Medicine at the University of Vermont, Colchester, Vermont
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Ramachandran S. Vasan
- Sections of Preventive Medicine and Epidemiology, Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | - Daniel Levy
- Framingham Heart Study, Framingham, Massachusetts
- Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, Maryland
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville
| | - 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, California
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas
| | - 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, California
| | | | | | - Andrew E. Moran
- Division of General Medicine, Columbia University, New York, New York
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Pradeep Natarajan
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston
| | - Amit V. Khera
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Verve Therapeutics, Boston, Massachusetts
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Yu WY, Yan SS, Zhang SH, Ni JJ, Bin-Li, Pei YF, Zhang L. Efficient identification of trait-associated loss-of-function variants in the UK Biobank cohort by exome-sequencing based genotype imputation. Genet Epidemiol 2023; 47:121-134. [PMID: 36490288 DOI: 10.1002/gepi.22511] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 11/22/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022]
Abstract
The large-scale open access whole-exome sequencing (WES) data of the UK Biobank ~200,000 participants is accelerating a new wave of genetic association studies aiming to identify rare and functional loss-of-function (LoF) variants associated with complex traits and diseases. We proposed to merge the WES genotypes and the genome-wide genotyping (GWAS) genotypes of 167,000 UKB homogeneous European participants into a combined reference panel, and then to impute 241,911 UKB homogeneous European participants who had the GWAS genotypes only. We then used the imputed data to replicate association identified in the discovery WES sample. The average imputation accuracy measure r2 is modest to high for LoF variants at all minor allele frequency intervals: 0.942 at MAF interval (0.01, 0.5), 0.807 at (1.0 × 10-3 , 0.01), 0.805 at (1.0 × 10-4 , 1.0 × 10-3 ), 0.664 at (1.0 × 10-5 , 1.0 × 10-4 ) and 0.410 at (0, 1.0 × 10-5 ). As applications, we studied associations of LoF variants with estimated heel BMD and four lipid traits. In addition to replicating dozens of previously reported genes, we also identified three novel associations, two genes PLIN1 and ANGPTL3 for high-density-lipoprotein cholesterol and one gene PDE3B for triglycerides. Our results highlighted the strength of WES based genotype imputation as well as provided useful imputed data within the UKB cohort.
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Affiliation(s)
- Wen-Yuan Yu
- Department of Plastic Surgery, The Second Affiliated Hospital of Soochow University, Jiangsu, People's Republic of China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China
| | - Shan-Shan Yan
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China.,Department of Epidemiology and Health Statistics, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China
| | - Shu-Han Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China.,Department of Epidemiology and Health Statistics, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China
| | - Jing-Jing Ni
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China.,Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China
| | - Bin-Li
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China.,Department of General Surgery, The Ninth Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China
| | - Yu-Fang Pei
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China.,Department of Epidemiology and Health Statistics, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China
| | - Lei Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China.,Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Jiangsu, People's Republic of China
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90
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Avvisato R, Jankauskas SS, Varzideh F, Kansakar U, Mone P, Santulli G. Sortilin and hypertension. Curr Opin Nephrol Hypertens 2023; 32:134-140. [PMID: 36683537 PMCID: PMC9976622 DOI: 10.1097/mnh.0000000000000866] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
PURPOSE OF REVIEW The current review aims to present the latest scientific updates on the role of Sortilin in the pathophysiology of hypertension. RECENT FINDINGS The main focus of this systematic overview is on the functional contribution of Sortilin to the pathogenesis of hypertension. Sortilin is a glycoprotein mostly known for its actions as a trafficking molecule directing proteins to specific secretory or endocytic compartments of the cell. Emerging evidence indicates that Sortilin is associated with pathological conditions, including inflammation, arteriosclerosis, dyslipidemia, insulin resistance, and vascular calcification. Most recently, Sortilin has been shown to finely control endothelial function and to drive hypertension by modulating sphingolipid/ceramide homeostasis and by triggering oxidative stress. SUMMARY The latest findings linking Sortilin and hypertension that are herein discussed can inspire novel areas of research which could eventually lead to the discovery of new therapeutic strategies in cardiovascular medicine.
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Affiliation(s)
- Roberta Avvisato
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Aging Research and
- Department of Molecular Pharmacology, Einstein-Mount Sinai Diabetes Research Center (ES-DRC), Fleischer Institute for Diabetes and Metabolism (FIDAM), Institute for Neuroimmunology and Inflammation, Albert Einstein College of Medicine, New York, New York, USA
| | - Stanislovas S. Jankauskas
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Aging Research and
- Department of Molecular Pharmacology, Einstein-Mount Sinai Diabetes Research Center (ES-DRC), Fleischer Institute for Diabetes and Metabolism (FIDAM), Institute for Neuroimmunology and Inflammation, Albert Einstein College of Medicine, New York, New York, USA
| | - Fahimeh Varzideh
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Aging Research and
- Department of Molecular Pharmacology, Einstein-Mount Sinai Diabetes Research Center (ES-DRC), Fleischer Institute for Diabetes and Metabolism (FIDAM), Institute for Neuroimmunology and Inflammation, Albert Einstein College of Medicine, New York, New York, USA
| | - Urna Kansakar
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Aging Research and
- Department of Molecular Pharmacology, Einstein-Mount Sinai Diabetes Research Center (ES-DRC), Fleischer Institute for Diabetes and Metabolism (FIDAM), Institute for Neuroimmunology and Inflammation, Albert Einstein College of Medicine, New York, New York, USA
| | - Pasquale Mone
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Aging Research and
- Department of Molecular Pharmacology, Einstein-Mount Sinai Diabetes Research Center (ES-DRC), Fleischer Institute for Diabetes and Metabolism (FIDAM), Institute for Neuroimmunology and Inflammation, Albert Einstein College of Medicine, New York, New York, USA
| | - Gaetano Santulli
- Department of Medicine, Division of Cardiology, Wilf Family Cardiovascular Research Institute, Einstein Institute for Aging Research and
- Department of Molecular Pharmacology, Einstein-Mount Sinai Diabetes Research Center (ES-DRC), Fleischer Institute for Diabetes and Metabolism (FIDAM), Institute for Neuroimmunology and Inflammation, Albert Einstein College of Medicine, New York, New York, USA
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91
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Zuriaga MA, Fuster JJ. Emerging Role of Acquired Mutations and Clonal Hematopoiesis in Atherosclerosis - Beyond Conventional Cardiovascular Risk Factors. Circ J 2023; 87:394-400. [PMID: 34433749 DOI: 10.1253/circj.cj-21-0505] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Accumulating evidence suggests that conventional cardiovascular risk factors are incompletely predictive of cardiovascular disease, as a substantial risk remains even when these factors are apparently managed well. In this context, clonal hematopoiesis has emerged as a new and potent risk factor for atherosclerotic cardiovascular disease and other cardiometabolic conditions. Clonal hematopoiesis typically arises from somatic mutations that confer a competitive advantage to a mutant hematopoietic stem cell, leading to its clonal expansion in the stem cell population and its progeny of blood leukocytes. Human sequencing studies and experiments in mice suggest that clonal hematopoiesis, at least when driven by certain mutations, contributes to accelerated atherosclerosis development. However, the epidemiology, biology and clinical implications of this phenomenon remain incompletely understood. Here, we review the current understanding of the connection between clonal hematopoiesis and atherosclerosis, and highlight knowledge gaps in this area of research.
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Affiliation(s)
| | - José J Fuster
- Centro Nacional de Investigaciones Cardiovasculares [CNIC].,CIBER en Enfermedades Cardiovasculares [CIBER-CV]
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92
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de Klerk JA, Beulens JWJ, Mei H, Bijkerk R, van Zonneveld AJ, Koivula RW, Elders PJM, 't Hart LM, Slieker RC. Altered blood gene expression in the obesity-related type 2 diabetes cluster may be causally involved in lipid metabolism: a Mendelian randomisation study. Diabetologia 2023; 66:1057-1070. [PMID: 36826505 PMCID: PMC10163084 DOI: 10.1007/s00125-023-05886-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 01/17/2023] [Indexed: 02/25/2023]
Abstract
AIMS/HYPOTHESIS The aim of this study was to identify differentially expressed long non-coding RNAs (lncRNAs) and mRNAs in whole blood of people with type 2 diabetes across five different clusters: severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), mild diabetes (MD) and mild diabetes with high HDL-cholesterol (MDH). This was to increase our understanding of different molecular mechanisms underlying the five putative clusters of type 2 diabetes. METHODS Participants in the Hoorn Diabetes Care System (DCS) cohort were clustered based on age, BMI, HbA1c, C-peptide and HDL-cholesterol. Whole blood RNA-seq was used to identify differentially expressed lncRNAs and mRNAs in a cluster compared with all others. Differentially expressed genes were validated in the Innovative Medicines Initiative DIabetes REsearCh on patient straTification (IMI DIRECT) study. Expression quantitative trait loci (eQTLs) for differentially expressed RNAs were obtained from a publicly available dataset. To estimate the causal effects of RNAs on traits, a two-sample Mendelian randomisation analysis was performed using public genome-wide association study (GWAS) data. RESULTS Eleven lncRNAs and 175 mRNAs were differentially expressed in the MOD cluster, the lncRNA AL354696.2 was upregulated in the SIDD cluster and GPR15 mRNA was downregulated in the MDH cluster. mRNAs and lncRNAs that were differentially expressed in the MOD cluster were correlated among each other. Six lncRNAs and 120 mRNAs validated in the IMI DIRECT study. Using two-sample Mendelian randomisation, we found 52 mRNAs to have a causal effect on anthropometric traits (n=23) and lipid metabolism traits (n=10). GPR146 showed a causal effect on plasma HDL-cholesterol levels (p = 2×10-15), without evidence for reverse causality. CONCLUSIONS/INTERPRETATION Multiple lncRNAs and mRNAs were found to be differentially expressed among clusters and particularly in the MOD cluster. mRNAs in the MOD cluster showed a possible causal effect on anthropometric traits, lipid metabolism traits and blood cell fractions. Together, our results show that individuals in the MOD cluster show aberrant RNA expression of genes that have a suggested causal role on multiple diabetes-relevant traits.
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Affiliation(s)
- Juliette A de Klerk
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands
| | - Joline W J Beulens
- Amsterdam Public Health Institute, Amsterdam UMC, Amsterdam, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Hailiang Mei
- Sequencing Analysis Support Core, Leiden University Medical Center, Leiden, the Netherlands
| | - Roel Bijkerk
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands
| | - Anton Jan van Zonneveld
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands
| | - Robert W Koivula
- Department of Clinical Sciences, Lund University, Genetic and Molecular Epidemiology, CRC, Skåne University Hospital Malmö, Malmö, Sweden
| | - Petra J M Elders
- Amsterdam Public Health Institute, Amsterdam UMC, Amsterdam, the Netherlands
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Leen M 't Hart
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
- Amsterdam Public Health Institute, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Roderick C Slieker
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands.
- Amsterdam Public Health Institute, Amsterdam UMC, Amsterdam, the Netherlands.
- Department of Epidemiology and Data Science, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands.
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Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods. Sci Rep 2023; 13:3078. [PMID: 36813803 PMCID: PMC9947228 DOI: 10.1038/s41598-023-30168-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 02/16/2023] [Indexed: 02/24/2023] Open
Abstract
Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and plasma lipidome (phenotype) in order to identify the genetic architecture of plasma lipidome profiled from 1,426 Finnish individuals aged 30-45 years. PGMRA involves biclustering genotype and lipidome data independently followed by their inter-domain integration based on hypergeometric tests of the number of shared individuals. Pathway enrichment analysis was performed on the SNP sets to identify their associated biological processes. We identified 93 statistically significant (hypergeometric p-value < 0.01) lipidome-genotype relations. Genotype biclusters in these 93 relations contained 5977 SNPs across 3164 genes. Twenty nine of the 93 relations contained genotype biclusters with more than 50% unique SNPs and participants, thus representing most distinct subgroups. We identified 30 significantly enriched biological processes among the SNPs involved in 21 of these 29 most distinct genotype-lipidome subgroups through which the identified genetic variants can influence and regulate plasma lipid related metabolism and profiles. This study identified 29 distinct genotype-lipidome subgroups in the studied Finnish population that may have distinct disease trajectories and therefore could be useful in precision medicine research.
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Vukadinovic M, Renjith G, Yuan V, Kwan A, Cheng SC, Li D, Clarke SL, Ouyang D. Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.16.23286058. [PMID: 36824841 PMCID: PMC9949184 DOI: 10.1101/2023.02.16.23286058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
Background Recent studies have leveraged quantitative traits from imaging to amplify the power of genome-wide association studies (GWAS) to gain further insights into the biology of diseases and traits. However, measurement imprecision is intrinsic to phenotyping and can impact downstream genetic analyses. Methods Left ventricular ejection fraction (LVEF), an important but imprecise quantitative imaging measurement, was examined to assess the impact of precision of phenotype measurement on genetic studies. Multiple approaches to obtain LVEF, as well as simulated measurement noise, were evaluated with their impact on downstream genetic analyses. Results Even within the same population, small changes in the measurement of LVEF drastically impacted downstream genetic analyses. Introducing measurement noise as little as 7.9% can eliminate all significant genetic associations in an GWAS with almost forty thousand individuals. An increase of 1% in mean absolute error (MAE) in LVEF had an equivalent impact on GWAS power as a decrease of 10% in the cohort sample size, suggesting optimizing phenotyping precision is a cost-effective way to improve power of genetic studies. Conclusions Improving the precision of phenotyping is important for maximizing the yield of genome-wide association studies.
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Affiliation(s)
- Milos Vukadinovic
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Gauri Renjith
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Victoria Yuan
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA
| | - Alan Kwan
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Susan C Cheng
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Shoa L Clarke
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA
| | - David Ouyang
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
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95
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Pieri K, Trichia E, Neville MJ, Taylor H, Bennett D, Karpe F, Koivula RW. Polygenic risk in Type III hyperlipidaemia and risk of cardiovascular disease: An epidemiological study in UK Biobank and Oxford Biobank. Int J Cardiol 2023; 373:72-78. [PMID: 36410544 DOI: 10.1016/j.ijcard.2022.11.024] [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: 08/22/2022] [Revised: 11/02/2022] [Accepted: 11/15/2022] [Indexed: 11/21/2022]
Abstract
BACKGROUND Type III hyperlipidaemia (T3HL) is characterised by equimolar increases in plasma triglycerides (TG) and cholesterol in <10% of APOE22 carriers conveying high cardiovascular disease (CVD) risk. We investigate the role of a weighted triglyceride-raising polygenic score (TG.PS) precipitating T3HL. METHODS The TG.PS (restricted to genome-wide significance and weighted by published independent effect estimates) was applied to the Oxford Biobank (OBB, n = 6952) and the UK Biobank (UKB, n = 460,037), to analyse effects on plasma lipid phenotypes. Fasting plasma lipid, lipoprotein biochemistry and NMR lipoprotein profiles were analysed in OBB. CVD prevalence/incidence was examined in UKB. RESULTS One TG.PS standard-deviation (SD) was associated with 13.0% (95% confidence-interval 12.0-14.0%) greater TG in OBB and 15.2% (15.0-15.4%) in UKB. APOE22 carriers had 19.0% (1.0-39.0%) greater TG in UKB. Males were more susceptible to TG.PS effects (4.0% (2.0-6.0%) greater TG with 1 TG.PS SD in OBB, 1.6% (1.3-1.9%) in UKB) than females. There was no interaction between APOE22 and TG.PS, BMI, sex or age on TG. APOE22 carriers had lower apolipoprotein B (apoB) (OBB; -0.35 (-0.29 to -0.40)g/L, UKB; -0.41 (-0.405 to -0.42)g/L). NMR lipoprotein lipid concentrations were discordant to conventional biochemistry in APOE22 carriers. In APOE22 compared with APOE33, CVD was no more prevalent in similarly hypertriglyceridaemic participants (OR 0.97 95%CI 0.76-1.25), but was less prevalent in normolipidaemia (OR 0.81, 95%CI 0.69-0.95); no differences were observed in CVD incidence. CONCLUSIONS TG.PS confers an additive risk for developing T3HL, that is of comparable effect size to conventional risk factors. The protective effect of APOE22 for prevalent CVD is consistent with lower apoB in APOE22 carriers.
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Affiliation(s)
- Kyriaki Pieri
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, United Kingdom
| | - Eirini Trichia
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 7LF, United Kingdom; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 7LF, United Kingdom
| | - Matt J Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, United Kingdom; NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Foundation Trust, Oxford OX4 2PG, United Kingdom
| | - Hannah Taylor
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 7LF, United Kingdom
| | - Derrick Bennett
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 7LF, United Kingdom; NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Foundation Trust, Oxford OX4 2PG, United Kingdom; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 7LF, United Kingdom
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, United Kingdom; NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Foundation Trust, Oxford OX4 2PG, United Kingdom.
| | - Robert W Koivula
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Oxford OX3 7LE, United Kingdom; Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Skåne University Hospital Malmö, CRC, 91-10, 205 02 Malmö, Sweden.
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96
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Melton HJ, Zhang Z, Wu C. SUMMIT-FA: A new resource for improved transcriptome imputation using functional annotations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.02.23285208. [PMID: 36798253 PMCID: PMC9934719 DOI: 10.1101/2023.02.02.23285208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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), that improves the accuracy of gene expression prediction by leveraging functional annotation resources and a large expression quantitative trait loci (eQTL) summary-level dataset. We build gene expression prediction models using SUMMIT-FA with a comprehensive functional database MACIE and the eQTL summary-level data from the eQTLGen consortium. By applying the resulting models to GWASs for 24 complex traits and exploring it through a simulation study, we show that SUMMIT-FA improves the accuracy of gene expression prediction models in whole blood, identifies significantly more gene-trait associations, and improves predictive power for identifying "silver standard" genes compared to several benchmark methods.
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Affiliation(s)
- Hunter J. Melton
- Department of Statistics, Florida State University, Tallahassee, FL, USA
| | - Zichen Zhang
- Department of Statistics, Florida State University, Tallahassee, FL, USA
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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97
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Hu R, Yang X, He X, Song G. The relationship between NAFLD and retinol-binding protein 4 - an updated systematic review and meta-analysis. Lipids Health Dis 2023; 22:8. [PMID: 36670387 PMCID: PMC9862531 DOI: 10.1186/s12944-022-01771-2] [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: 11/09/2022] [Accepted: 12/31/2022] [Indexed: 01/22/2023] Open
Abstract
PURPOSE Retinol-binding protein 4 (RBP4) has been considered to be related to metabolic related diseases, such as hyperuricemia, obesity, and diabetes mellitus. However, whether nonalcoholic fatty liver disease (NAFLD) is related to RBP4 is unclear. Previous studies on the relationship between NAFLD and RBP4 levels have yielded inconsistent results. Hence, this meta-analysis was aimed to clarify whether circulating RBP4 levels are in relation to the risk of NAFLD. METHODS A meta-analysis was performed by applying observational studies to evaluate circulating RBP4 levels and NAFLD. Eligible studies published up to September 23, 2022, were searched in Embase, PubMed, and Cochrane databases. RESULTS In this study, 17 cross-sectional studies involving 8423 participants were included. Results from a random effects model showed that circulating RBP4 levels were higher in NAFLD patients than non-NAFLD (standardized mean difference (SMD) 0.28; 95% confidence intervals (CI): 0.11-0.46, I2: 89.8%). This association was confirmed in the Yellow race. However, no significant association was noted in the Caucasian race. After excluding the morbidly obese Population from the weight loss study (n = 2), the results of the comparison remained largely unchanged (SMD 0.28; 95% CI: 0.10-0.47, I2: 90.8%). Remarkable publication bias was not found. Although considerable heterogeneity was observed among the studies, no potential sources of heterogeneity were found in the subgroup analysis. Diagnostic methods for NAFLD were determined to be a potential source of statistical heterogeneity in meta-regression. CONCLUSION The findings provide evidence that NAFLD patients exhibit higher levels of circulating RBP4 compared with controls, but high heterogeneity was observed. Thus, a high RBP4 level is probably a potential risk factor for NAFLD. To confirm the causal link between NAFLD and RBP4 level of causality, further prospective cohort studies are needed.
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Affiliation(s)
- Rui Hu
- grid.256883.20000 0004 1760 8442Department of Internal Medicine, Hebei Medical University, Shijiazhuang, 050017 Hebei People’s Republic of China ,grid.440208.a0000 0004 1757 9805Endocrinology Department, Hebei General Hospital, Shijiazhuang, 050051 Hebei People’s Republic of China
| | - Xiaoyue Yang
- grid.256883.20000 0004 1760 8442Department of Internal Medicine, Hebei Medical University, Shijiazhuang, 050017 Hebei People’s Republic of China ,grid.440208.a0000 0004 1757 9805Endocrinology Department, Hebei General Hospital, Shijiazhuang, 050051 Hebei People’s Republic of China
| | - Xiaoyu He
- grid.256883.20000 0004 1760 8442Department of Internal Medicine, Hebei Medical University, Shijiazhuang, 050017 Hebei People’s Republic of China ,grid.440208.a0000 0004 1757 9805Endocrinology Department, Hebei General Hospital, Shijiazhuang, 050051 Hebei People’s Republic of China
| | - Guangyao Song
- Endocrinology Department, Hebei General Hospital, Shijiazhuang, 050051, Hebei, People's Republic of China.
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98
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Ren Z, Simons PIHG, Wesselius A, Stehouwer CDA, Brouwers MCGJ. Relationship between NAFLD and coronary artery disease: A Mendelian randomization study. Hepatology 2023; 77:230-238. [PMID: 35441719 PMCID: PMC9970021 DOI: 10.1002/hep.32534] [Citation(s) in RCA: 75] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/05/2022] [Accepted: 04/16/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND AIMS There is an ongoing debate on whether NAFLD is an active contributor or an innocent bystander in the pathogenesis of coronary artery disease (CAD). The aim of the present study was to assess the causal relationship between NAFLD and CAD. APPROACH AND RESULTS We performed two-sample Mendelian randomization (MR) analyses using summary-level data to assess the association between genetically predicted NAFLD (i.e., chronically elevated serum alanine aminotransferase levels [cALT], imaging-based and biopsy-confirmed NAFLD) and risk of CAD. Analyses were repeated after exclusion of NAFLD susceptibility genes that are associated with impaired VLDL secretion.Inverse-variance weighted MR analyses showed a statistically significant association between genetically predicted cALT and risk of CAD (OR: 1.116, 95% CI: 1.039, 1.199), but not for the other NAFLD-related traits (OR: 1.046, 95% CI: 0.764, 1.433 and OR: 1.014, 95% CI: 0.968, 1.062 for imaging-based and biopsy-confirmed NAFLD, respectively). MR-Egger regression revealed a statistically significant intercept, indicative of directional pleiotropy, for all traits. Repeat analyses after exclusion of genes associated with impaired VLDL secretion showed consistent associations between genetically predicted NAFLD and CAD for all traits (i.e., cALT [OR: 1.203, 95% CI: 1.113, 1.300]), imaging-based (OR: 2.149, 95% CI: 1.276, 3.620) and biopsy-confirmed NAFLD (OR: 1.113, 95% CI: 1.041, 1.189), which persisted when more stringent biopsy-confirmed NAFLD criteria were used (OR: 1.154, 95% CI: 1.043, 1.278) or when more stringent MR methods were applied. MR-Egger regression did not show a statistically significant intercept. CONCLUSION The two-sample MR analyses showed a robust association between genetically predicted NAFLD and CAD after exclusion of genetic variants that are implicated in impaired VLDL secretion.
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Affiliation(s)
- Zhewen Ren
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Pomme I. H. G. Simons
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Anke Wesselius
- NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
- Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
| | - Coen D. A. Stehouwer
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Martijn C. G. J. Brouwers
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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Evans MA, Walsh K. Clonal hematopoiesis, somatic mosaicism, and age-associated disease. Physiol Rev 2023; 103:649-716. [PMID: 36049115 PMCID: PMC9639777 DOI: 10.1152/physrev.00004.2022] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 07/19/2022] [Accepted: 08/02/2022] [Indexed: 12/15/2022] Open
Abstract
Somatic mosaicism, the occurrence of multiple genetically distinct cell clones within the same tissue, is an evitable consequence of human aging. The hematopoietic system is no exception to this, where studies have revealed the presence of expanded blood cell clones carrying mutations in preleukemic driver genes and/or genetic alterations in chromosomes. This phenomenon is referred to as clonal hematopoiesis and is remarkably prevalent in elderly individuals. While clonal hematopoiesis represents an early step toward a hematological malignancy, most individuals will never develop blood cancer. Somewhat unexpectedly, epidemiological studies have found that clonal hematopoiesis is associated with an increase in the risk of all-cause mortality and age-related disease, particularly in the cardiovascular system. Studies using murine models of clonal hematopoiesis have begun to shed light on this relationship, suggesting that driver mutations in mature blood cells can causally contribute to aging and disease by augmenting inflammatory processes. Here we provide an up-to-date review of clonal hematopoiesis within the context of somatic mosaicism and aging and describe recent epidemiological studies that have reported associations with age-related disease. We will also discuss the experimental studies that have provided important mechanistic insight into how driver mutations promote age-related disease and how this knowledge could be leveraged to treat individuals with clonal hematopoiesis.
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Affiliation(s)
- Megan A Evans
- Hematovascular Biology Center, Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Kenneth Walsh
- Hematovascular Biology Center, Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia
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100
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Chen Z, Lehertshuber C, Schunkert H. Genome Editing in Dyslipidemia and Atherosclerosis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1396:139-156. [DOI: 10.1007/978-981-19-5642-3_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
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