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Jin Q, Lau ESH, Luk AO, Tam CHT, Ozaki R, Lim CKP, Wu H, Chow EYK, Kong APS, Lee HM, Fan B, Ng ACW, Jiang G, Lee KF, Siu SC, Hui G, Tsang CC, Lau KP, Leung JY, Tsang MW, Cheung EYN, Kam G, Lau IT, Li JK, Yeung VTF, Lau E, Lo S, Fung S, Cheng YL, Chow CC, Yu W, Tsui SKW, Tomlinson B, Huang Y, Lan HY, Szeto CC, So WY, Jenkins AJ, Fung E, Muilwijk M, Blom MT, 't Hart LM, Chan JCN, Ma RCW. Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank. Diabetologia 2024; 67:837-849. [PMID: 38413437 PMCID: PMC10954952 DOI: 10.1007/s00125-024-06108-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 01/03/2024] [Indexed: 02/29/2024]
Abstract
AIMS/HYPOTHESIS The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers. METHODS From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts. RESULTS At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts. CONCLUSIONS/INTERPRETATION Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.
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Affiliation(s)
- Qiao Jin
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Andrea O Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Hongjiang Wu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Elaine Y K Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Heung Man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Alex C W Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Ka Fai Lee
- Department of Medicine and Geriatrics, Kwong Wah Hospital, Hong Kong, China
| | - Shing Chung Siu
- Diabetes Centre, Tung Wah Eastern Hospital, Hong Kong, China
| | - Grace Hui
- Diabetes Centre, Tung Wah Eastern Hospital, Hong Kong, China
| | - Chiu Chi Tsang
- Diabetes and Education Centre, Alice Ho Miu Ling Nethersole Hospital, Hong Kong, China
| | | | - Jenny Y Leung
- Department of Medicine and Geriatrics, Ruttonjee Hospital, Hong Kong, China
| | - Man-Wo Tsang
- Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong, China
| | - Elaine Y N Cheung
- Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong, China
| | - Grace Kam
- Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong, China
| | - Ip Tim Lau
- Tseung Kwan O Hospital, Hong Kong, China
| | - June K Li
- Department of Medicine, Yan Chai Hospital, Hong Kong, China
| | - Vincent T F Yeung
- Centre for Diabetes Education and Management, Our Lady of Maryknoll Hospital, Hong Kong, China
| | - Emmy Lau
- Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Hong Kong, China
| | - Stanley Lo
- Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Hong Kong, China
| | - Samuel Fung
- Department of Medicine and Geriatrics, Princess Margaret Hospital, Hong Kong, China
| | - Yuk Lun Cheng
- Department of Medicine, Alice Ho Miu Ling Nethersole Hospital, Hong Kong, China
| | - Chun Chung Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Weichuan Yu
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Stephen K W Tsui
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Brian Tomlinson
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Faculty of Medicine, Macau University of Science and Technology, Macau, China
| | - Yu Huang
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China
| | - Hui-Yao Lan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Cheuk Chun Szeto
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Alicia J Jenkins
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Erik Fung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Mirthe Muilwijk
- Department of Epidemiology and Data Science, Amsterdam UMC - Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Health Behaviors & Chronic Diseases Research Program, Amsterdam Public Health, Amsterdam UMC, Amsterdam, the Netherlands
| | - Marieke T Blom
- Health Behaviors & Chronic Diseases Research Program, Amsterdam Public Health, Amsterdam UMC, Amsterdam, the Netherlands
- Department of General Practice, Amsterdam UMC - Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Leen M 't Hart
- Department of Epidemiology and Data Science, Amsterdam UMC - Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Health Behaviors & Chronic Diseases Research Program, Amsterdam Public Health, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Centre, Leiden, the Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China.
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China.
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China.
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Hall WL, Alkoblan A, Gibson PS, D'Annibale M, Coekaerts A, Bauer M, Bruce JH, Lecomte B, Penhoat A, Laugerette F, Michalski MC, Salt LJ, Wilde PJ, Berry SE. Postprandial lipid and vascular responses following consumption of a commercially-relevant interesterified palmitic acid-rich spread in comparison to functionally-equivalent non-interesterified spread and spreadable butter: a randomised controlled trial in healthy adults. Food Funct 2024; 15:2733-2750. [PMID: 38380649 PMCID: PMC10911404 DOI: 10.1039/d3fo05324e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 02/14/2024] [Indexed: 02/22/2024]
Abstract
Background: Interesterification is an industrial processing technique used widely where hard fats are essential for functionality and consumer acceptability, e.g. margarines and lower fat spreads. Objective: The aim of this study was to compare acute cardiovascular effects of functionally equivalent spreads (similar solid fat content) made with interesterified (IE) or non-IE palm-based fats, or spreadable butter. Methods: A randomised, controlled, 4-armed crossover, double-blind study (25 men, 25 women; 35-75 years; healthy; mean BMI 24.5, SD 3.8), compared effects of mixed nutrient meals containing 50 g fat from functionally equivalent products [IE spread, non-IE spread and spreadable butter (SB), with rapeseed oil (RO) as a reference treatment: with 16.7%, 27.9%, 19.3% and 4% palmitic acid, respectively] on 8 h postprandial changes in plasma triacylglycerol (TAG) and endothelial dysfunction (flow-mediated dilatation; FMD). Circulating reactive oxygen species (estimated using a neutrophil oxidative burst assay), glucose, insulin, NEFA, lipoprotein particle profiles, inflammatory markers (glycoprotein acetylation (Glyc-A) and IL-6), and biomarkers of endotoxemia were measured. Results: Postprandial plasma TAG concentrations after test meals were similar. However following RO versus the 3 spreads, there were significantly higher postprandial apolipoprotein B concentrations, and small HDL and LDL particle concentrations, and lower postprandial extra-large, large, and medium HDL particle concentrations, as well as smaller average HDL and LDL particle sizes. There were no differences following IE compared to the other spreads. Postprandial FMD% did not decrease after high-fat test meals, and there were no differences between treatments. Postprandial serum IL-6 increased similarly after test meals, but RO provoked a greater increase in postprandial concentrations of glycoprotein acetyls (GlycA), as well as 8 h sCD14, an endotoxemia marker. All other postprandial outcomes were not different between treatments. Conclusions: In healthy adults, a commercially-available IE-based spread did not evoke a different postprandial triacylglycerol, lipoprotein subclass, oxidative stress, inflammatory or endotoxemic response to functionally-equivalent, but compositionally-distinct alternative spreads. Clinical trial registry number: NCT03438084 (https://ClinicalTrials.gov).
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Affiliation(s)
- Wendy L Hall
- Department of Nutritional Sciences, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, Franklin Wilkins Building, Stamford St., London, UK.
| | - Aseel Alkoblan
- Department of Nutritional Sciences, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, Franklin Wilkins Building, Stamford St., London, UK.
- College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia
| | - Philippa S Gibson
- Department of Nutritional Sciences, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, Franklin Wilkins Building, Stamford St., London, UK.
| | - Maria D'Annibale
- Department of Nutritional Sciences, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, Franklin Wilkins Building, Stamford St., London, UK.
| | - Astrid Coekaerts
- Department of Nutritional Sciences, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, Franklin Wilkins Building, Stamford St., London, UK.
| | - Mathilde Bauer
- Department of Nutritional Sciences, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, Franklin Wilkins Building, Stamford St., London, UK.
| | | | - Beryle Lecomte
- CarMeN Laboratory INRAE, INSERM U1060, INRAE UMR1397, University of Lyon, France
| | - Armelle Penhoat
- CarMeN Laboratory INRAE, INSERM U1060, INRAE UMR1397, University of Lyon, France
| | - Fabienne Laugerette
- CarMeN Laboratory INRAE, INSERM U1060, INRAE UMR1397, University of Lyon, France
| | | | - Louise J Salt
- Food Innovation and Health Programme, Quadram Institute Bioscience, UK
| | - Peter J Wilde
- Food Innovation and Health Programme, Quadram Institute Bioscience, UK
| | - Sarah E Berry
- Department of Nutritional Sciences, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, Franklin Wilkins Building, Stamford St., London, UK.
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3
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Yang R, Wu S, Zhao Z, Deng X, Deng Q, Wang D, Liu Q. Causal association between lipoproteins and risk of coronary artery disease-a systematic review and meta-analysis of Mendelian randomization studies. Clin Res Cardiol 2024:10.1007/s00392-024-02420-7. [PMID: 38407584 DOI: 10.1007/s00392-024-02420-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/20/2024] [Indexed: 02/27/2024]
Abstract
OBJECTIVE To systematically evaluate the causal effect of lipoproteins to the risk of coronary artery disease (CAD) by systematic review and meta-analysis of the associated Mendelian randomization (MR) studies. METHODS This systematic review was registered in PROSPERO (ID CRD42023465430). Searches from the databases (e.g., PubMed, Embase, Cochrane, Web of Science) and non-database sources to collect MR studies. The search time frame was from the database inception to August 2023. After data extraction, quality evaluation was performed, and the meta-analysis with bias evaluation was carried out with RevMan software. RESULTS A total of 5,828,409 participants from 21 records were included. Quality and bias assessment was performed by evaluating the internal three assumptions of MR studies. Meta-analysis for the causal association between non-HDL lipoproteins and CAD showed a significantly positive association between LDL and CAD (OR 1.37, 95% CI 1.26-1.49; P < 0.001, I2 = 95%), apoB and CAD (OR 1.38, 95% CI 1.11-1.71; P = 0.003, I2 = 98%), and Lp(a) and CAD (OR 1.21, 95% CI 1.12-1.31; P < 0.001, I2 = 99%). Interestingly, although there was no statistical significance in the association between VLDL/apoA1 and CAD (both P > 0.05), the pooled non-HDL lipoproteins showed a significantly positive association with CAD (OR 1.28, 95% CI 1.22-1.34; P < 0.001, I2 = 99%). For the HDL lipoproteins, the pooled OR showed a significantly negative association with CAD (OR 0.84, 95% CI 0.72-0.98; P = 0.002, I2 = 72%). However, the protective effect of HDL on CAD diminished when analyzed together with apoA1 and/or apoB (both P > 0.05). The funnel plot did not show serious publication bias, and sensitivity analysis performed relatively well robustness of the causal association of LDL, apoB, Lp(a), and total cholesterol with CAD. CONCLUSION The present meta-analysis suggests an overall effect of causal association between lipoproteins and CAD. Most of the non-HDL lipoproteins (LDL, apoB, Lp(a)) promote CAD, while the protective effect of HDL in CAD still needs to be verified in the future.
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Affiliation(s)
- Rongyuan Yang
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, 510120, People's Republic of China
| | - Shirong Wu
- The Second Clinical School of Medicine, Guangzhou University of Traditional Chinese Medicine, Guangzhou, 510120, People's Republic of China
| | - Zhen Zhao
- The Second Clinical School of Medicine, Guangzhou University of Traditional Chinese Medicine, Guangzhou, 510120, People's Republic of China
| | - Xuanxuan Deng
- The Second Clinical School of Medicine, Guangzhou University of Traditional Chinese Medicine, Guangzhou, 510120, People's Republic of China
| | - Qiuying Deng
- The Second Clinical School of Medicine, Guangzhou University of Traditional Chinese Medicine, Guangzhou, 510120, People's Republic of China
| | - Dawei Wang
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, 510120, People's Republic of China
- The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, 510405, People's Republic of China
| | - Qing Liu
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, 510120, People's Republic of China.
- The Second Clinical School of Medicine, Guangzhou University of Chinese Medicine, #111 Dade Road, Yuexiu District, Guangzhou, 510120, People's Republic of China.
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4
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Lehtovirta M, Pahkala K, Rovio SP, Magnussen CG, Laitinen TT, Niinikoski H, Lagström H, Viikari JSA, Rönnemaa T, Jula A, Ala-Korpela M, Raitakari OT. Association of tobacco smoke exposure with metabolic profile from childhood to early adulthood: the Special Turku Coronary Risk Factor Intervention Project. Eur J Prev Cardiol 2024; 31:103-115. [PMID: 37655930 DOI: 10.1093/eurjpc/zwad285] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/04/2023] [Accepted: 08/29/2023] [Indexed: 09/02/2023]
Abstract
AIMS To investigate the associations between passive tobacco smoke exposure and daily smoking with a comprehensive metabolic profile, measured repeatedly from childhood to adulthood. METHODS AND RESULTS Study cohort was derived from the Special Turku Coronary Risk Factor Intervention Project (STRIP). Smoking status was obtained by questionnaire, while serum cotinine concentrations were measured using gas chromatography. Metabolic measures were quantified by nuclear magnetic resonance metabolomics at 9 (n = 539), 11 (n = 536), 13 (n = 525), 15 (n = 488), 17 (n = 455), and 19 (n = 409) years. Association of passive tobacco smoke exposure with metabolic profile compared participants who reported less-than-weekly smoking and had serum cotinine concentration <1 ng/mL (no exposure) with those whose cotinine concentration was ≥10 ng/mL (passive tobacco smoke exposure). Associations of daily smoking with metabolic profile in adolescence were analysed by comparing participants reporting daily smoking with those reporting no tobacco use and having serum cotinine concentrations <1 ng/mL. Passive tobacco smoke exposure was directly associated with the serum ratio of monounsaturated fatty acids to total fatty acids [β = 0.34 standard deviation (SD), (0.17-0.51), P < 0.0001] and inversely associated with the serum ratios of polyunsaturated fatty acids. Exposure to passive tobacco smoke was directly associated with very-low-density lipoprotein particle size [β = 0.28 SD, (0.12-0.45), P = 0.001] and inversely associated with HDL particle size {β = -0.21 SD, [-0.34 to -0.07], P = 0.003}. Daily smokers exhibited a similar metabolic profile to those exposed to passive tobacco smoke. These results persisted after adjusting for body mass index, STRIP study group allocation, dietary target score, pubertal status, and parental socio-economic status. CONCLUSION Both passive and active tobacco smoke exposures during childhood and adolescence are detrimentally associated with circulating metabolic measures indicative of increased cardio-metabolic risk.
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Affiliation(s)
- Miia Lehtovirta
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Kiinamyllynkatu 10, Turku FI-20520, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Kiinamyllynkatu 10, Turku FI-20520, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
- Paavo Nurmi Centre, Unit for Health and Physical Activity, University of Turku, Turku, Finland
| | - Suvi P Rovio
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Kiinamyllynkatu 10, Turku FI-20520, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - Costan G Magnussen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Kiinamyllynkatu 10, Turku FI-20520, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Tomi T Laitinen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Kiinamyllynkatu 10, Turku FI-20520, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
- Paavo Nurmi Centre, Unit for Health and Physical Activity, University of Turku, Turku, Finland
| | - Harri Niinikoski
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital, University of Turku, Turku, Finland
| | - Hanna Lagström
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
- Department of Public Health, Turku University Hospital, University of Turku, Turku, Finland
| | - Jorma S A Viikari
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Medicine, University of Turku, Turku, Finland
| | - Tapani Rönnemaa
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Medicine, University of Turku, Turku, Finland
| | - Antti Jula
- Department of Chronic Disease Prevention, Institute for Health and Welfare, Turku, Finland
| | - Mika Ala-Korpela
- Systems Epidemiology, Research Unit of Population Health, Faculty of Medicine, University of Oulu & Biocenter Oulu, Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Kiinamyllynkatu 10, Turku FI-20520, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
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5
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Blaauw MJT, Berrevoets MAH, Vos WAJW, Groenendijk AL, van Eekeren LE, Vadaq N, Weijers G, van der Ven AJAM, Rutten JHW, Riksen NP. Traditional Cardiovascular Risk Factors Are Stronger Related to Carotid Intima-Media Thickness Than to Presence of Carotid Plaques in People Living With HIV. J Am Heart Assoc 2023; 12:e030606. [PMID: 37804189 PMCID: PMC10757550 DOI: 10.1161/jaha.123.030606] [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: 04/17/2023] [Accepted: 09/08/2023] [Indexed: 10/09/2023]
Abstract
Background Cardiovascular disease is a major cause of morbidity and mortality in people living with HIV, who are at higher risk than the general population. We assessed, in a large cohort of people living with HIV, which cardiovascular, HIV-specific, and lipoproteomic markers were associated with carotid intima-media thickness (cIMT) and carotid plaque presence. We also studied guideline adherence on lipid-lowering medication in individuals with high and very high risk for cardiovascular disease. Methods and Results In 1814 individuals with a median (interquartile range) age of 53 (44-60) years, we found a carotid plaque in 909 (50.1%) and a median (interquartile range) intima-media thickness of 0.66 (0.57-0.76) mm. Ultrasonography was used for the assessment of cIMT and plaque presence. Univariable and multivariable regression models were used for associations with cIMT and presence of plaques. Age, Black race, body mass index, type 2 diabetes, and smoking (pack years) were all positively associated with higher cIMT. Levels of high-density lipoprotein cholesterol, specifically medium and large high-density lipoprotein subclasses, were negatively associated with higher cIMT. Only age and prior myocardial infarction were positively related to the presence of a carotid plaque. Lipid-lowering treatment was prescribed in one-third of people living with HIV, who are at high and very high risk for cardiovascular disease. Conclusions Traditional cardiovascular risk factors were significantly associated with higher cIMT but not with carotid plaques, except for age. HIV-specific factors were not associated with both ultrasound measurements. Future studies are needed to elucidate which factors contribute to plaque formation. Improvement of guideline adherence on prescription of lipid-lowering treatment in high- and very high-risk patients for cardiovascular disease is recommended. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03994835.
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Affiliation(s)
- Marc J. T. Blaauw
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenthe Netherlands
- Department of Internal MedicineElisabeth‐Tweesteden HospitalTilburgthe Netherlands
| | | | - Wilhelm A. J. W. Vos
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenthe Netherlands
- Department of Internal MedicineOLVGAmsterdamthe Netherlands
| | - Albert L. Groenendijk
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenthe Netherlands
- Department of Medical Microbiology and Infectious DiseasesErasmus Medical Center (MC)Rotterdamthe Netherlands
| | - Louise E. van Eekeren
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenthe Netherlands
| | - Nadira Vadaq
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenthe Netherlands
- Center for Tropical and Infectious Diseases, Faculty of MedicineDiponegoro University, Dr. Kariadi HospitalSemarangIndonesia
| | - Gert Weijers
- Medical UltraSound Imaging Center, Division of Medical ImagingRadboud University Medical CenterNijmegenthe Netherlands
| | - Andre J. A. M. van der Ven
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenthe Netherlands
| | - Joost H. W. Rutten
- Division of Vascular Medicine, Department of Internal MedicineRadboud University Medical CentreNijmegenthe Netherlands
| | - Niels P. Riksen
- Division of Vascular Medicine, Department of Internal MedicineRadboud University Medical CentreNijmegenthe Netherlands
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6
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An DB, Ann SJ, Seok S, Kang Y, Lee SH. Hepatic Cdkal1 deletion regulates HDL catabolism and promotes reverse cholesterol transport. Atherosclerosis 2023; 375:21-29. [PMID: 37245423 DOI: 10.1016/j.atherosclerosis.2023.05.012] [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: 09/19/2022] [Revised: 05/13/2023] [Accepted: 05/16/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND AND AIMS Associations between CDKAL1 variants and cholesterol efflux capacity (CEC) have been reported. This study aimed to investigate the effects of Cdkal1 deficiency on high-density lipoprotein (HDL) metabolism, atherosclerosis, and related pathways. METHODS Lipid and glucose metabolic profiles, CEC, and in vivo reverse cholesterol transport (RCT) were compared in liver-specific Alb-Cre:Cdkal1fl/fl and Cdkal1fl/fl mice. Aortic atherosclerosis was compared in Apoe-/-Alb-Cre:Cdkal1fl/fl and Apoe-/- mice fed high-fat diets. HDL subclasses and mediators of HDL metabolism from Alb-Cre:Cdkal1fl/fl mice were examined. RESULTS HDL-cholesterol level tended to be higher in the Alb-Cre:Cdkal1fl/fl mice (p = 0.050). Glucose and other lipid profiles were similar in the two groups of mice, irrespective of diet. The mean CEC was 27% higher (p = 0.007) in the Alb-Cre:Cdkal1fl/fl mice, as were the radioactivities of bile acids (mean difference 17%; p = 0.035) and cholesterol (mean difference 42%; p = 0.036) from faeces. The radioactivity tendency was largely similar in mice fed a high-fat diet. Atherosclerotic lesion area tended to be smaller in the Apoe-/-Alb-Cre:Cdkal1fl/fl mice than in the Apoe-/- mice (p = 0.067). Cholesterol concentrations in large HDLs were higher in the Alb-Cre:Cdkal1fl/fl mice (p = 0.024), whereas in small HDLs, they were lower (p = 0.024). Endothelial lipase (mean difference 39%; p = 0.002) and hepatic lipase expression levels (mean difference 34%; p < 0.001) were reduced in the Alb-Cre:Cdkal1fl/fl mice, whereas SR-B1 expression was elevated (mean difference 35%; p = 0.007). CONCLUSIONS The promotion of CEC and RCT in Alb-Cre:Cdkal1fl/fl mice verified the effect of CDKAL1 seen in human genetic data. These phenotypes were related to regulation of HDL catabolism. This study suggests that CDKAL1 and associated molecules could be targets for improving RCT and vascular pathology.
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Affiliation(s)
- Dan Bi An
- Yonsei University Graduate School, Seoul, South Korea
| | - Soo-Jin Ann
- Integrative Research Center for Cerebrovascular and Cardiovascular Diseases, Yonsei University College of Medicine, Seoul, South Korea
| | - Seungmin Seok
- Yonsei University Graduate School, Seoul, South Korea
| | - Yura Kang
- Department of Biostatistics and Computing, Yonsei University Graduate School, Seoul, South Korea
| | - Sang-Hak Lee
- Division of Cardiology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea; Pohang University of Science and Technology (POSTECH), Pohang, South Korea.
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7
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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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8
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Abedi F, Sadeghi M, Omidkhoda N, Kelesidis T, Ramezani J, Samadi S, Mohammadpour AH. HDL-cholesterol concentration and its association with coronary artery calcification: a systematic review and meta-analysis. Lipids Health Dis 2023; 22:60. [PMID: 37158895 PMCID: PMC10165789 DOI: 10.1186/s12944-023-01827-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 04/29/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND Coronary artery calcification (CAC) is a potential risk marker of coronary atherosclerosis that has high specificity and sensitivity. However, the association between high-density lipoprotein cholesterol (HDL-C) concentration and CAC incidence and progression is controversial. METHODS PubMed, Embase, Web of Science, and Scopus were systematically searched to identify relevant observational studies up to March 2023 and assessed the methodological quality using Newcastle-Ottawa Scale (NOS) scale. Random-effects meta-analysis was used to estimate pooled odds ratios (OR) and 95% confidence interval considering heterogeneity across studies. RESULTS Of the 2,411 records, 25 cross-sectional (n = 71,190) and 13 cohort (n = 25,442) studies were included in the systematic review. Ten cross-sectional and eight cohort studies were not eligible and were omitted from the meta-analysis. A total of 15 eligible cross-sectional studies (n = 33,913) were included in the meta-analysis and pooled results revealed no significant association between HDL-C and CAC > 0, CAC > 10, or CAC > 100 [pooled OR: 0.99 (0.97, 1.01)]. Meta-analysis of the 5 eligible prospective cohort studies (n = 10,721) revealed no significant protective effect of high HDL-C against CAC > 0 [pooled OR: 1.02 (0.93, 1.13)]. CONCLUSIONS According to this analysis of observational studies, high HDL-C levels were not found to predict protection against CAC. These results suggest HDL quality rather than HDL quantity is important for certain aspects of atherogenesis and CAC. REGISTRATION NUMBER CRD42021292077.
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Affiliation(s)
- Farshad Abedi
- Department of Clinical Pharmacy, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Masoumeh Sadeghi
- Department of Epidemiology, Faculty of Health, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Navid Omidkhoda
- Department of Clinical Pharmacy, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Theodoros Kelesidis
- Department of Medicine, Division of Infectious Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Javad Ramezani
- Department of Cardiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Sara Samadi
- Department of Clinical Pharmacy, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Amir Hooshang Mohammadpour
- Department of Clinical Pharmacy, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran.
- Pharmaceutical Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
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9
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Karageorgiou V, Gill D, Bowden J, Zuber V. Sparse dimensionality reduction approaches in Mendelian randomisation with highly correlated exposures. eLife 2023; 12:e80063. [PMID: 37074034 PMCID: PMC10229118 DOI: 10.7554/elife.80063] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 04/18/2023] [Indexed: 04/20/2023] Open
Abstract
Multivariable Mendelian randomisation (MVMR) is an instrumental variable technique that generalises the MR framework for multiple exposures. Framed as a regression problem, it is subject to the pitfall of multicollinearity. The bias and efficiency of MVMR estimates thus depends heavily on the correlation of exposures. Dimensionality reduction techniques such as principal component analysis (PCA) provide transformations of all the included variables that are effectively uncorrelated. We propose the use of sparse PCA (sPCA) algorithms that create principal components of subsets of the exposures with the aim of providing more interpretable and reliable MR estimates. The approach consists of three steps. We first apply a sparse dimension reduction method and transform the variant-exposure summary statistics to principal components. We then choose a subset of the principal components based on data-driven cutoffs, and estimate their strength as instruments with an adjusted F-statistic. Finally, we perform MR with these transformed exposures. This pipeline is demonstrated in a simulation study of highly correlated exposures and an applied example using summary data from a genome-wide association study of 97 highly correlated lipid metabolites. As a positive control, we tested the causal associations of the transformed exposures on coronary heart disease (CHD). Compared to the conventional inverse-variance weighted MVMR method and a weak instrument robust MVMR method (MR GRAPPLE), sparse component analysis achieved a superior balance of sparsity and biologically insightful grouping of the lipid traits.
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Affiliation(s)
- Vasileios Karageorgiou
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College LondonLondonUnited Kingdom
- University of ExeterExeterUnited Kingdom
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College LondonLondonUnited Kingdom
- Department of Clinical Pharmacology and Therapeutics, Institute for Infection and Immunity, St George’s, University of LondonLondonUnited Kingdom
- Genetics Department, Novo Nordisk Research Centre OxfordOxfordUnited Kingdom
| | - Jack Bowden
- University of ExeterExeterUnited Kingdom
- Genetics Department, Novo Nordisk Research Centre OxfordOxfordUnited Kingdom
| | - Verena Zuber
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College LondonLondonUnited Kingdom
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10
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Jin Q, Lau ESH, Luk AO, Tam CHT, Ozaki R, Lim CKP, Wu H, Chow EYK, Kong APS, Lee HM, Fan B, Ng ACW, Jiang G, Lee KF, Siu SC, Hui G, Tsang CC, Lau KP, Leung JY, Tsang MW, Cheung EYN, Kam G, Lau IT, Li JK, Yeung VT, Lau E, Lo S, Fung S, Cheng YL, Chow CC, Yu W, Tsui SKW, Huang Y, Lan HY, Szeto CC, So WY, Jenkins AJ, Chan JCN, Ma RCW. High-density lipoprotein subclasses and cardiovascular disease and mortality in type 2 diabetes: analysis from the Hong Kong Diabetes Biobank. Cardiovasc Diabetol 2022; 21:293. [PMID: 36587202 PMCID: PMC9805680 DOI: 10.1186/s12933-022-01726-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 12/13/2022] [Indexed: 01/01/2023] Open
Abstract
OBJECTIVE High-density lipoproteins (HDL) comprise particles of different size, density and composition and their vasoprotective functions may differ. Diabetes modifies the composition and function of HDL. We assessed associations of HDL size-based subclasses with incident cardiovascular disease (CVD) and mortality and their prognostic utility. RESEARCH DESIGN AND METHODS HDL subclasses by nuclear magnetic resonance spectroscopy were determined in sera from 1991 fasted adults with type 2 diabetes (T2D) consecutively recruited from March 2014 to February 2015 in Hong Kong. HDL was divided into small, medium, large and very large subclasses. Associations (per SD increment) with outcomes were evaluated using multivariate Cox proportional hazards models. C-statistic, integrated discrimination index (IDI), and categorial and continuous net reclassification improvement (NRI) were used to assess predictive value. RESULTS Over median (IQR) 5.2 (5.0-5.4) years, 125 participants developed incident CVD and 90 participants died. Small HDL particles (HDL-P) were inversely associated with incident CVD [hazard ratio (HR) 0.65 (95% CI 0.52, 0.81)] and all-cause mortality [0.47 (0.38, 0.59)] (false discovery rate < 0.05). Very large HDL-P were positively associated with all-cause mortality [1.75 (1.19, 2.58)]. Small HDL-P improved prediction of mortality [C-statistic 0.034 (0.013, 0.055), IDI 0.052 (0.014, 0.103), categorical NRI 0.156 (0.006, 0.252), and continuous NRI 0.571 (0.246, 0.851)] and CVD [IDI 0.017 (0.003, 0.038) and continuous NRI 0.282 (0.088, 0.486)] over the RECODe model. CONCLUSION Small HDL-P were inversely associated with incident CVD and all-cause mortality and improved risk stratification for adverse outcomes in people with T2D. HDL-P may be used as markers for residual risk in people with T2D.
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Affiliation(s)
- Qiao Jin
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Eric S. H. Lau
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Andrea O. Luk
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Claudia H. T. Tam
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
| | - Risa Ozaki
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Cadmon K. P. Lim
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
| | - Hongjiang Wu
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Elaine Y. K. Chow
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Alice P. S. Kong
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Heung Man Lee
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Baoqi Fan
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
| | - Alex C. W. Ng
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Guozhi Jiang
- grid.12981.330000 0001 2360 039XSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong China
| | - Ka Fai Lee
- grid.415591.d0000 0004 1771 2899Department of Medicine and Geriatrics, Kwong Wah Hospital, Yau Ma Tei, Hong Kong Special Administrative Region China
| | - Shing Chung Siu
- grid.417347.20000 0004 1799 526XDiabetes Centre, Tung Wah Eastern Hospital, Sheung Wan, Hong Kong Special Administrative Region China
| | - Grace Hui
- grid.417347.20000 0004 1799 526XDiabetes Centre, Tung Wah Eastern Hospital, Sheung Wan, Hong Kong Special Administrative Region China
| | - Chiu Chi Tsang
- grid.413608.80000 0004 1772 5868Diabetes and Education Centre, Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong Special Administrative Region China
| | - Kam Piu Lau
- grid.490321.d0000000417722990North District Hospital, Sheung Shui, Hong Kong Special Administrative Region China
| | - Jenny Y. Leung
- grid.416291.90000 0004 1775 0609Department of Medicine and Geriatrics, Ruttonjee Hospital, Wan Chai, Hong Kong Special Administrative Region China
| | - Man-wo Tsang
- grid.417037.60000 0004 1771 3082Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong Special Administrative Region China
| | - Elaine Y. N. Cheung
- grid.417037.60000 0004 1771 3082Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong Special Administrative Region China
| | - Grace Kam
- grid.417037.60000 0004 1771 3082Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong Special Administrative Region China
| | - Ip Tim Lau
- grid.490601.a0000 0004 1804 0692Tseung Kwan O Hospital, Hang Hau, Hong Kong Special Administrative Region China
| | - June K. Li
- grid.417335.70000 0004 1804 2890Department of Medicine, Yan Chai Hospital, Tsuen Wan, Hong Kong Special Administrative Region China
| | - Vincent T. Yeung
- grid.499546.30000 0000 9690 2842Centre for Diabetes Education and Management, Our Lady of Maryknoll Hospital, Wong Tai Sin, Hong Kong Special Administrative Region China
| | - Emmy Lau
- grid.417134.40000 0004 1771 4093Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong Special Administrative Region China
| | - Stanley Lo
- grid.417134.40000 0004 1771 4093Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong Special Administrative Region China
| | - Samuel Fung
- grid.415229.90000 0004 1799 7070Department of Medicine and Geriatrics, Princess Margaret Hospital, Lai Chi Kok, Hong Kong Special Administrative Region China
| | - Yuk Lun Cheng
- grid.413608.80000 0004 1772 5868Department of Medicine, Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong Special Administrative Region China
| | - Chun Chung Chow
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Weichuan Yu
- grid.24515.370000 0004 1937 1450Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Kowloon, Hong Kong Special Administrative Region China
| | - Stephen K. W. Tsui
- grid.10784.3a0000 0004 1937 0482School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Yu Huang
- grid.10784.3a0000 0004 1937 0482School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.35030.350000 0004 1792 6846Department of Biomedical Sciences, City University of Hong Kong, Kowloon, Hong Kong Special Administrative Region China
| | - Hui-yao Lan
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Cheuk Chun Szeto
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Wing Yee So
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Alicia J. Jenkins
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.1013.30000 0004 1936 834XNHMRC Clinical Trials Centre, University of Sydney, Sydney, Australia
| | - Juliana C. N. Chan
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
| | - Ronald C. W. Ma
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
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11
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von Eckardstein A, Nordestgaard BG, Remaley AT, Catapano AL. High-density lipoprotein revisited: biological functions and clinical relevance. Eur Heart J 2022; 44:1394-1407. [PMID: 36337032 PMCID: PMC10119031 DOI: 10.1093/eurheartj/ehac605] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 09/16/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022] Open
Abstract
Abstract
Previous interest in high-density lipoproteins (HDLs) focused on their possible protective role in atherosclerotic cardiovascular disease (ASCVD). Evidence from genetic studies and randomized trials, however, questioned that the inverse association of HDL-cholesterol (HDL-C) is causal. This review aims to provide an update on the role of HDL in health and disease, also beyond ASCVD. Through evolution from invertebrates, HDLs are the principal lipoproteins, while apolipoprotein B-containing lipoproteins first developed in vertebrates. HDLs transport cholesterol and other lipids between different cells like a reusable ferry, but serve many other functions including communication with cells and the inactivation of biohazards like bacterial lipopolysaccharides. These functions are exerted by entire HDL particles or distinct proteins or lipids carried by HDL rather than by its cholesterol cargo measured as HDL-C. Neither does HDL-C measurement reflect the efficiency of reverse cholesterol transport. Recent studies indicate that functional measures of HDL, notably cholesterol efflux capacity, numbers of HDL particles, or distinct HDL proteins are better predictors of ASCVD events than HDL-C. Low HDL-C levels are related observationally, but also genetically, to increased risks of infectious diseases, death during sepsis, diabetes mellitus, and chronic kidney disease. Additional, but only observational, data indicate associations of low HDL-C with various autoimmune diseases, and cancers, as well as all-cause mortality. Conversely, extremely high HDL-C levels are associated with an increased risk of age-related macular degeneration (also genetically), infectious disease, and all-cause mortality. HDL encompasses dynamic multimolecular and multifunctional lipoproteins that likely emerged during evolution to serve several physiological roles and prevent or heal pathologies beyond ASCVD. For any clinical exploitation of HDL, the indirect marker HDL-C must be replaced by direct biomarkers reflecting the causal role of HDL in the respective disease.
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Affiliation(s)
- Arnold von Eckardstein
- Institute of Clinical Chemistry, University Hospital Zurich and University of Zurich , Zurich , Switzerland
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Copenhagen University Hospital, Herlev and Gentofte Hospital , Herlev , Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital, Herlev and Gentofte Hospital , Herlev , Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen , Denmark
| | - Alan T Remaley
- Lipoprotein Metabolism Section, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, MD , USA
| | - Alberico L Catapano
- Department of Pharmacological and Biomolecular Sciences, University of Milan , Milan , Italy
- IRCCS MultiMedica, Sesto S. Giovanni , Milan , Italy
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12
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Girard D, Vandiedonck C. How dysregulation of the immune system promotes diabetes mellitus and cardiovascular risk complications. Front Cardiovasc Med 2022; 9:991716. [PMID: 36247456 PMCID: PMC9556991 DOI: 10.3389/fcvm.2022.991716] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 08/30/2022] [Indexed: 12/15/2022] Open
Abstract
Diabetes mellitus (DM) is a chronic metabolic disorder characterized by persistent hyperglycemia due to insulin resistance or failure to produce insulin. Patients with DM develop microvascular complications that include chronic kidney disease and retinopathy, and macrovascular complications that mainly consist in an accelerated and more severe atherosclerosis compared to the general population, increasing the risk of cardiovascular (CV) events, such as stroke or myocardial infarction by 2- to 4-fold. DM is commonly associated with a low-grade chronic inflammation that is a known causal factor in its development and its complications. Moreover, it is now well-established that inflammation and immune cells play a major role in both atherosclerosis genesis and progression, as well as in CV event occurrence. In this review, after a brief presentation of DM physiopathology and its macrovascular complications, we will describe the immune system dysregulation present in patients with type 1 or type 2 diabetes and discuss its role in DM cardiovascular complications development. More specifically, we will review the metabolic changes and aberrant activation that occur in the immune cells driving the chronic inflammation through cytokine and chemokine secretion, thus promoting atherosclerosis onset and progression in a DM context. Finally, we will discuss how genetics and recent systemic approaches bring new insights into the mechanisms behind these inflammatory dysregulations and pave the way toward precision medicine.
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Affiliation(s)
- Diane Girard
- Université Paris Cité, INSERM UMR-S1151, CNRS UMR-S8253, Institut Necker Enfants Malades, IMMEDIAB Laboratory, Paris, France
- Université Paris Cité, Institut Hors-Mur du Diabète, Faculté de Santé, Paris, France
| | - Claire Vandiedonck
- Université Paris Cité, INSERM UMR-S1151, CNRS UMR-S8253, Institut Necker Enfants Malades, IMMEDIAB Laboratory, Paris, France
- Université Paris Cité, Institut Hors-Mur du Diabète, Faculté de Santé, Paris, France
- *Correspondence: Claire Vandiedonck
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13
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Energy Homeostasis Gene Nucleotide Variants and Survival of Hemodialysis Patients-A Genetic Cohort Study. J Clin Med 2022; 11:jcm11185477. [PMID: 36143124 PMCID: PMC9501434 DOI: 10.3390/jcm11185477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/11/2022] [Accepted: 09/13/2022] [Indexed: 11/17/2022] Open
Abstract
Background: Patients undergoing hemodialysis (HD) therapy have an increased risk of death compared to the general population. We investigated whether selected single nucleotide variants (SNVs) involved in glucose and lipid metabolism are associated with mortality risk in HD patients. Methods: The study included 805 HD patients tested for 11 SNVs in FOXO3, IGFBP3, FABP1, PCSK9, ANGPTL6, and DOCK6 using HRM analysis and TaqMan assays. FOXO3, IGFBP3, L-FABP, PCSK9, ANGPTL6, and ANGPTL8 plasma concentrations were measured by ELISA in 86 individuals. The Kaplan–Meier method and Cox proportional hazards models were used for survival analyses. Results: We found out that the carriers of a C allele in ANGPTL6 rs8112063 had an increased risk of all-cause, cardiovascular, and cardiac mortality. In addition, the C allele of DOCK6 rs737337 was associated with all-cause and cardiac mortality. The G allele of DOCK6 rs17699089 was correlated with the mortality risk of patients initiating HD therapy. The T allele of FOXO3 rs4946936 was negatively associated with cardiac and cardiovascular mortality in HD patients. We observed no association between the tested proteins’ circulating levels and the survival of HD patients. Conclusions: The ANGPTL6 rs8112063, FOXO3 rs4946936, DOCK6 rs737337, and rs17699089 nucleotide variants are predictors of survival in patients undergoing HD.
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14
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Björkegren JLM, Lusis AJ. Atherosclerosis: Recent developments. Cell 2022; 185:1630-1645. [PMID: 35504280 PMCID: PMC9119695 DOI: 10.1016/j.cell.2022.04.004] [Citation(s) in RCA: 305] [Impact Index Per Article: 152.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/30/2022] [Accepted: 04/01/2022] [Indexed: 12/13/2022]
Abstract
Atherosclerosis is an inflammatory disease of the large arteries that is the major cause of cardiovascular disease (CVD) and stroke. Here, we review the current understanding of the molecular, cellular, genetic, and environmental contributions to atherosclerosis, from both individual pathway and systems perspectives. We place an emphasis on recent developments, some of which have yielded unexpected biology, including previously unknown heterogeneity of inflammatory and smooth muscle cells in atherosclerotic lesions, roles for senescence and clonal hematopoiesis, and links to the gut microbiome.
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Affiliation(s)
- Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Division of Cardiology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
| | - Aldons J Lusis
- Department of Medicine/Division of Cardiology, Department of Microbiology, Immunology and Molecular Genetics, Department of Human Genetics, A2-237 Center for the Health Sciences, University of California, Los Angeles, Los Angeles, CA USA.
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15
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Metz S, Krarup NT, Bryrup T, Støy J, Andersson EA, Christoffersen C, Neville MJ, Christiansen MR, Jonsson AE, Witte DR, Kampmann U, Nielsen LB, Jørgensen NR, Karpe F, Grarup N, Pedersen O, Kilpeläinen TO, Hansen T. The Arg82Cys polymorphism of the protein nepmucin implies a role in HDL metabolism. J Endocr Soc 2022; 6:bvac034. [PMID: 35382499 PMCID: PMC8974852 DOI: 10.1210/jendso/bvac034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Indexed: 12/02/2022] Open
Abstract
Context Blood lipid levels are linked to the risk of cardiovascular disease and regulated by genetic factors. A low-frequency polymorphism Arg82Cys (rs72836561) in the membrane protein nepmucin, encoded by CD300LG, is associated with lower fasting concentration of high-density lipoprotein cholesterol (HDLc) and higher fasting triglycerides. However, whether the variant is linked to postprandial lipids and glycemic status remains elusive. Objective Here, we augment the genetic effect of Arg82Cys on fasting plasma concentrations of HDL subclasses, postprandial lipemia after a standardized high-fat meal, and glycemic status to further untangle its role in HDL metabolism. Methods We elucidated fasting associations with HDL subclasses in a population-based cohort study (Oxford BioBank, OBB), including 4522 healthy men and women. We investigated fasting and postprandial consequences on HDL metabolism in recall-by-genotype (RbG) studies (fasting: 20 carrier/20 noncarrier; postprandial: 7 carrier/17 noncarrier), and shed light on the synergistic interaction with glycemic status. Results A lower fasting plasma concentration of cholesterol in large HDL particles was found in healthy male carriers of the Cys82 polymorphism compared to noncarriers, both in the OBB (P = .004) and RbG studies (P = .005). In addition, the Cys82 polymorphism was associated with low fasting plasma concentrations of ApoA1 (P = .008) in the OBB cohort. On the contrary, we did not find differences in postprandial lipemia or 2-hour plasma glucose levels. Conclusion Taken together, our results indicate an association between the Arg82Cys variant and a lower concentration of HDL particles and HDLc, especially in larger HDL subclasses, suggesting a link between nepmucin and HDLc metabolism or maturation.
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Affiliation(s)
- Sophia Metz
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nikolaj T Krarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Aalborg University Hospital, Department of Cardiology, Aalborg, Denmark
| | - Thomas Bryrup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Julie Støy
- Aarhus University Hospital, Steno Diabetes Center Aarhus, Aarhus, Denmark
| | - Ehm A Andersson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christina Christoffersen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Matt J Neville
- Oxford Centre for Diabetes, Endocrinology & Metabolism, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Malene R Christiansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anna E Jonsson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Daniel R Witte
- Department of Public Health, Section of Epidemiology, Aarhus University, Denmark
| | - Ulla Kampmann
- Aarhus University Hospital, Steno Diabetes Center Aarhus, Aarhus, Denmark
| | - Lars B Nielsen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Faculty of Health, Aarhus University, Aarhus, Denmark
| | - Niklas R Jørgensen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen Denmark
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology & Metabolism, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health, University of Southern Denmark, Odense, Denmark
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16
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Ong KL, Cochran BBiotech BJ, Manandhar B, Thomas S, Rye KA. HDL maturation and remodelling. Biochim Biophys Acta Mol Cell Biol Lipids 2022; 1867:159119. [PMID: 35121104 DOI: 10.1016/j.bbalip.2022.159119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 01/16/2022] [Accepted: 01/20/2022] [Indexed: 11/29/2022]
Abstract
Cholesterol in the circulation is mostly transported in an esterified form as a component of lipoproteins. The majority of these cholesteryl esters are produced in nascent, discoidal high density lipoproteins (HDLs) by the enzyme, lecithin:cholesterol acyltransferase (LCAT). Discoidal HDLs are discrete populations of particles that consist of a phospholipid bilayer, the hydrophobic acyl chains of which are shielded from the aqueous environment by apolipoproteins that also confer water solubility on the particles. The progressive LCAT-mediated accumulation of cholesteryl esters in discoidal HDLs generates the spherical HDLs that predominate in normal human plasma. Spherical HDLs contain a core of water insoluble, neutral lipids (cholesteryl esters and triglycerides) that is surrounded by a surface monolayer of phospholipids with which apolipoproteins associate. Although spherical HDLs all have the same basic structure, they are extremely diverse in size, composition, and function. This review is concerned with how the biogenesis of discoidal and spherical HDLs is regulated and the mechanistic basis of their size and compositional heterogeneity. Current understanding of the impact of this heterogeneity on the therapeutic potential of HDLs of varying size and composition is also addressed in the context of several disease states.
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Affiliation(s)
- Kwok-Leung Ong
- School of Medical Sciences, Faculty of Medicine, University of New South Wales Sydney, New South Wales, Australia
| | - Blake J Cochran BBiotech
- School of Medical Sciences, Faculty of Medicine, University of New South Wales Sydney, New South Wales, Australia
| | - Bikash Manandhar
- School of Medical Sciences, Faculty of Medicine, University of New South Wales Sydney, New South Wales, Australia
| | - Shane Thomas
- School of Medical Sciences, Faculty of Medicine, University of New South Wales Sydney, New South Wales, Australia
| | - Kerry-Anne Rye
- School of Medical Sciences, Faculty of Medicine, University of New South Wales Sydney, New South Wales, Australia.
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17
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HDL Is Not Dead Yet. Biomedicines 2022; 10:biomedicines10010128. [PMID: 35052806 PMCID: PMC8773442 DOI: 10.3390/biomedicines10010128] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/04/2022] [Accepted: 01/05/2022] [Indexed: 12/11/2022] Open
Abstract
High-density lipoprotein cholesterol (HDL-C) levels are inversely correlated with coronary heart disease (CHD) in multiple epidemiological studies, but whether HDL is causal or merely associated with CHD is unclear. Recent trials for HDL-raising drugs were either not effective in reducing CHD events or, if beneficial in reducing CHD events, were not conclusive as the findings could be attributed to the drugs’ LDL-reducing activity. Furthermore, the first large Mendelian randomization study did not causally relate HDL-C levels to decreased CHD. Thus, the hypothesis that HDL is protective against CHD has been rightfully challenged. However, subsequent Mendelian randomization studies found HDL characteristics that are causally related to decreased CHD. Many aspects of HDL structure and function, especially in reverse cholesterol transport, may be better indicators of HDL’s protective activity than simply measuring HDL-C. Cholesterol efflux capacity is associated with lower levels of prevalent and incident CHD, even after adjustment for HDL-C and apolipoprotein A-1 levels. Also, subjects with very high levels of HDL-C, including those with rare mutations that disrupt hepatic HDL uptake and reverse cholesterol transport, may be at higher risk for CHD than those with moderate levels. We describe here several cell-based and cell-free in vitro assays of HDL structure and function that may be used in clinical studies to determine which of HDL’s functions are best associated with protection against CHD. We conclude that the HDL hypothesis may need revision based on studies of HDL structure and function, but that the HDL hypothesis is not dead yet.
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18
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Groenen AG, Bazioti V, van Zeventer IA, Chen L, Groot HE, Balder JW, Zhernakova A, van der Harst P, Rimbert A, Kuivenhoven JA, Fu J, Westerterp M. Large HDL particles negatively associate with leukocyte counts independent of cholesterol efflux capacity: A cross sectional study in the population-based LifeLines DEEP cohort. Atherosclerosis 2022; 343:20-27. [DOI: 10.1016/j.atherosclerosis.2022.01.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 12/08/2021] [Accepted: 01/14/2022] [Indexed: 12/19/2022]
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19
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Zhou Y, Zha L, Pan S. The Risk of Atrial Fibrillation Increases with Earlier Onset of Obesity: A Mendelian Randomization Study. Int J Med Sci 2022; 19:1388-1398. [PMID: 36035367 PMCID: PMC9413561 DOI: 10.7150/ijms.72334] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 07/28/2022] [Indexed: 11/05/2022] Open
Abstract
Background: Obesity is a well-established risk factor for atrial fibrillation (AF). Previous epidemiological research on obesity and AF often focused on adult populations and now broadened to earlier in life. Therefore, this study aimed to determine the relationships between obesity at different periods of life and the risk of AF. Methods: A two-sample Mendelian randomization (MR) study design using summarised data from 6 genome-wide association studies (GWASs) was employed in this study. Single nucleotide polymorphisms (SNPs) associated with adult obesity, childhood obesity, childhood body mass index (BMI), waist-to-hip ratio adjusted for BMI (WHRadjBMI), birth weight and AF were independently retrieved from large-scale GWASs. For SNP identification, the genome-wide significance threshold was set at p <5.00×10-8. To obtain causal estimates, MR analysis was conducted using the inverse variance-weighted (IVW) method. The weighted median, MR-Egger methods and MR-robust adjusted profile score (MR-RAPS) were used to evaluate the robustness of MR analysis. Results: A total of 204 SNPs were identified as the genetic instrumental variables (5 SNPs for childhood obesity, 13 SNPs for childhood BMI, 137 SNPs for birth weight, 35 SNPs for adult WHRadjBMI, and 14 SNPs for adult obesity). The results of MR analysis demonstrated that the genetically predicted adult obesity, childhood BMI, and birth weight were associated with AF risk. Notably, a 1 unit standard deviation (1-SD) increase in adult obesity was related to a 13% increased risk of AF [p=6.51×10-7, OR, 1.13 (95% CI, 1.08-1.19)], a 1-SD increase in childhood BMI was related to a 18% increased risk of AF [p=1.77×10-4, OR, 1.18 (95% CI, 1.08-1.29)], and a 1-SD increase in birth weight was related to a 26% increased risk of AF [p=1.27×10-7, OR, 1.26 (95% CI, 1.16-1.37)]. There was no evidence of pleiotropy or heterogeneity between the MR estimates obtained from multiple SNPs. Conclusion: Our study reveals the association of genetic susceptibility to obesity with a higher risk of AF. Moreover, an earlier age at obesity was associated with an increased risk of AF. Therefore, public awareness of the dangers of obesity and active early weight control may prevent the development of AF.
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Affiliation(s)
- Yingchao Zhou
- Heart Center, Women and Children's Hospital, Qingdao University, Qingdao, China
| | - Lingfeng Zha
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Silin Pan
- Heart Center, Women and Children's Hospital, Qingdao University, Qingdao, China
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20
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Gautier T, Deckert V, Nguyen M, Desrumaux C, Masson D, Lagrost L. New therapeutic horizons for plasma phospholipid transfer protein (PLTP): Targeting endotoxemia, infection and sepsis. Pharmacol Ther 2021; 236:108105. [PMID: 34974028 DOI: 10.1016/j.pharmthera.2021.108105] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 12/10/2021] [Accepted: 12/27/2021] [Indexed: 12/13/2022]
Abstract
Phospholipid Transfer Protein (PLTP) transfers amphiphilic lipids between circulating lipoproteins and between lipoproteins, cells and tissues. Indeed, PLTP is a major determinant of the plasma levels, turnover and functionality of the main lipoprotein classes: very low-density lipoproteins (VLDL), low-density lipoproteins (LDL) and high-density lipoproteins (HDL). To date, most attention has been focused on the role of PLTP in the context of cardiometabolic diseases, with additional insights in neurodegenerative diseases and immunity. Importantly, beyond its influence on plasma triglyceride and cholesterol transport, PLTP plays a key role in the modulation of the immune response, with immediate relevance to a wide range of inflammatory diseases including bacterial infection and sepsis. Indeed, emerging evidence supports the role of PLTP, in the context of its association with lipoproteins, in the neutralization and clearance of bacterial lipopolysaccharides (LPS) or endotoxins. LPS are amphipathic molecules originating from Gram-negative bacteria which harbor major pathogen-associated patterns, triggering an innate immune response in the host. Although the early inflammatory reaction constitutes a key step in the anti-microbial defense of the organism, it can lead to a dysregulated inflammatory response and to hemodynamic disorders, organ failure and eventually death. Moreover, and in addition to endotoxemia and acute inflammation, small amounts of LPS in the circulation can induce chronic, low-grade inflammation with long-term consequences in several metabolic disorders such as atherosclerosis, obesity and diabetes. After an updated overview of the role of PLTP in lipid transfer, lipoprotein metabolism and related diseases, current knowledge of its impact on inflammation, infection and sepsis is critically appraised. Finally, the relevance of PLTP as a new player and novel therapeutic target in the fight against inflammatory diseases is considered.
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Affiliation(s)
- Thomas Gautier
- INSERM, LNC UMR1231, Dijon, France; University of Bourgogne and Franche-Comté, LNC UMR1231, Dijon, France; FCS Bourgogne-Franche Comté, LipSTIC LabEx, Dijon, France.
| | - Valérie Deckert
- INSERM, LNC UMR1231, Dijon, France; University of Bourgogne and Franche-Comté, LNC UMR1231, Dijon, France; FCS Bourgogne-Franche Comté, LipSTIC LabEx, Dijon, France
| | - Maxime Nguyen
- INSERM, LNC UMR1231, Dijon, France; University of Bourgogne and Franche-Comté, LNC UMR1231, Dijon, France; FCS Bourgogne-Franche Comté, LipSTIC LabEx, Dijon, France; Service Anesthésie-Réanimation Chirurgicale, Dijon University Hospital, Dijon, France
| | - Catherine Desrumaux
- INSERM, U1198, Montpellier, France; Faculty of Sciences, Université Montpellier, Montpellier, France
| | - David Masson
- INSERM, LNC UMR1231, Dijon, France; University of Bourgogne and Franche-Comté, LNC UMR1231, Dijon, France; FCS Bourgogne-Franche Comté, LipSTIC LabEx, Dijon, France; Plateau Automatisé de Biochimie, Dijon University Hospital, Dijon, France
| | - Laurent Lagrost
- INSERM, LNC UMR1231, Dijon, France; University of Bourgogne and Franche-Comté, LNC UMR1231, Dijon, France; FCS Bourgogne-Franche Comté, LipSTIC LabEx, Dijon, France; Service de la Recherche, Dijon University Hospital, Dijon, France.
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21
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von Eckardstein A. High Density Lipoproteins: Is There a Comeback as a Therapeutic Target? Handb Exp Pharmacol 2021; 270:157-200. [PMID: 34463854 DOI: 10.1007/164_2021_536] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Low plasma levels of High Density Lipoprotein (HDL) cholesterol (HDL-C) are associated with increased risks of atherosclerotic cardiovascular disease (ASCVD). In cell culture and animal models, HDL particles exert multiple potentially anti-atherogenic effects. However, drugs increasing HDL-C have failed to prevent cardiovascular endpoints. Mendelian Randomization studies neither found any genetic causality for the associations of HDL-C levels with differences in cardiovascular risk. Therefore, the causal role and, hence, utility as a therapeutic target of HDL has been questioned. However, the biomarker "HDL-C" as well as the interpretation of previous data has several important limitations: First, the inverse relationship of HDL-C with risk of ASCVD is neither linear nor continuous. Hence, neither the-higher-the-better strategies of previous drug developments nor previous linear cause-effect relationships assuming Mendelian randomization approaches appear appropriate. Second, most of the drugs previously tested do not target HDL metabolism specifically so that the futile trials question the clinical utility of the investigated drugs rather than the causal role of HDL in ASCVD. Third, the cholesterol of HDL measured as HDL-C neither exerts nor reports any HDL function. Comprehensive knowledge of structure-function-disease relationships of HDL particles and associated molecules will be a pre-requisite, to test them for their physiological and pathogenic relevance and exploit them for the diagnostic and therapeutic management of individuals at HDL-associated risk of ASCVD but also other diseases, for example diabetes, chronic kidney disease, infections, autoimmune and neurodegenerative diseases.
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Affiliation(s)
- Arnold von Eckardstein
- Institute of Clinical Chemistry, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
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22
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Wang J, Zhao Q, Bowden J, Hemani G, Davey Smith G, Small DS, Zhang NR. Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments. PLoS Genet 2021; 17:e1009575. [PMID: 34157017 PMCID: PMC8301661 DOI: 10.1371/journal.pgen.1009575] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 07/23/2021] [Accepted: 05/04/2021] [Indexed: 12/25/2022] Open
Abstract
Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that "all genes affect every complex trait" complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.
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Affiliation(s)
- Jingshu Wang
- Department of Statistics, University of Chicago, Chicago, Illinois, United States of America
| | - Qingyuan Zhao
- Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, United Kingdom
| | - Jack Bowden
- College of Medicine and Health, University of Exeter, Exeter, United Kingdom
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Dylan S. Small
- Department of Statistics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Nancy R. Zhang
- Department of Statistics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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