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Nguyen KT, Li J, Peng AW, Azar K, Heidenreich P, Palaniappan L, Yong CM. Temporal Trends in Cardiovascular Disease Prevalence Among Asian American Subgroups. J Am Heart Assoc 2024; 13:e031444. [PMID: 38606778 DOI: 10.1161/jaha.123.031444] [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: 06/29/2023] [Accepted: 03/12/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Asian and multiracial individuals represent the 2 fastest growing racial and ethnic groups in the United States, yet most prior studies report Asian American and Native Hawaiian or Other Pacific Islander as a single racial group, with limited data on cardiovascular disease (CVD) prevalence among subgroups. We sought to evaluate temporal trends in CVD burden among disaggregated Asian subgroups. METHODS AND RESULTS Patients with CVD based on International Classification of Diseases, Ninth Revision and Tenth Revision (ICD-9 and ICD-10) coding who received care from a mixed-payer health care organization in California between 2008 and 2018 were classified into self-identified racial and ethnic subgroups (non-Hispanic White [NHW], Asian Indian, Chinese, Filipino, Japanese, Korean, Native Hawaiian or Other Pacific Islander, and multiracial groups). Adjusted trends in CVD prevalence over time by subgroup were compared using logistic regression. Among 3 494 071 patient-years, prevalence of CVD increased faster among all subgroups except Japanese and Native Hawaiian or Other Pacific Islander patients (P<0.01 for each, reference: NHW). Filipino patients had the highest overall CVD prevalence, which increased from 34.3% to 45.1% over 11 years (increase from 17.3%-21.9%, P<0.0001, reference: NHW). Asian Indian patients had the fastest increase in CVD prevalence over time (16.9%-23.7%, P<0.0001, reference: NHW). Among subcategories of disease, hypertension increased faster among Asian Indian, Chinese, Filipino, Korean, and multiracial groups (P<0.01 for all, reference: NHW), and coronary artery disease increased faster among Asian Indian, Chinese, Filipino, and Japanese groups (P<0.05 for each, reference: NHW). CONCLUSIONS The increasing prevalence of CVD among disaggregated Asian, Native Hawaiian or Other Pacific Islander, and multiracial subgroups over time highlights the importance of tailored approaches to addressing CVD in these diverse subpopulations.
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Affiliation(s)
- Kaylin T Nguyen
- Division of Cardiovascular Medicine and Cardiovascular Institute Stanford University Stanford CA USA
- Veterans Affairs Palo Alto Healthcare System Palo Alto CA USA
| | - Jiang Li
- Palo Alto Medical Foundation Palo Alto CA USA
| | - Allison W Peng
- Department of Medicine Stanford University Stanford CA USA
| | | | - Paul Heidenreich
- Division of Cardiovascular Medicine and Cardiovascular Institute Stanford University Stanford CA USA
- Veterans Affairs Palo Alto Healthcare System Palo Alto CA USA
| | - Latha Palaniappan
- Division of Cardiovascular Medicine and Cardiovascular Institute Stanford University Stanford CA USA
| | - Celina M Yong
- Division of Cardiovascular Medicine and Cardiovascular Institute Stanford University Stanford CA USA
- Veterans Affairs Palo Alto Healthcare System Palo Alto CA USA
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Minhas AMK, Talha KM, Abramov D, Johnson HM, Antoine S, Rodriguez F, Fudim M, Michos ED, Misra A, Abushamat L, Nambi V, Fonarow GC, Ballantyne CM, Virani SS. Racial and ethnic disparities in cardiovascular disease - analysis across major US national databases. J Natl Med Assoc 2024:S0027-9684(24)00022-1. [PMID: 38342731 DOI: 10.1016/j.jnma.2024.01.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 01/14/2024] [Accepted: 01/16/2024] [Indexed: 02/13/2024]
Abstract
BACKGROUND There are several studies that have analyzed disparities in cardiovascular disease (CVD) health using a variety of different administrative databases; however, a unified analysis of major databases does not exist. In this analysis of multiple publicly available datasets, we sought to examine racial and ethnic disparities in different aspects of CVD, CVD-related risk factors, CVD-related morbidity and mortality, and CVD trainee representation in the US. METHODS We used National Health and Nutrition Examination Survey, National Ambulatory Medical Care Survey, National Inpatient Sample, Centers for Disease Control and Prevention Wide-Ranging OnLine Data for Epidemiologic Research, United Network for Organ Sharing, and American Commission for Graduate Medical Education data to evaluate CVD-related disparities among Non-Hispanic (NH) White, NH Black and Hispanic populations. RESULTS The prevalence of most CVDs and associated risk factors was higher in NH Black adults compared to NH White adults, except for dyslipidemia and ischemic heart disease (IHD). Statins were underutilized in IHD in NH Black and Hispanic patients. Hospitalizations for HF and stroke were higher among Black patients compared to White patients. All-cause, CVD, heart failure, acute myocardial infarction, IHD, diabetes mellitus, hypertension and cerebrovascular disease related mortality was highest in NH Black or African American individuals. The number of NH Black and Hispanic trainees in adult general CVD fellowship programs was disproportionately lower than NH White trainees. CONCLUSION Racial disparities are pervasive across the spectrum of CVDs with NH Black adults at a significant disadvantage compared to NH White adults for most CVDs.
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Affiliation(s)
| | - Khawaja M Talha
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Dmitry Abramov
- Division of Cardiology, Department of Medicine, Loma Linda University Health, Loma Linda, CA, USA
| | - Heather M Johnson
- Christine E. Lynn Women's Health & Wellness Institute, Baptist Health South Florida, Boca Raton, FL, USA
| | - Steve Antoine
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Fatima Rodriguez
- Stanford University Division of Cardiovascular Medicine and Cardiovascular Institute, Department of Medicine, Stanford University, Center for Academic Medicine, Stanford, CA, USA
| | - Marat Fudim
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA; Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Erin D Michos
- Division of Cardiology Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Arunima Misra
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Layla Abushamat
- Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX, USA
| | - Vijay Nambi
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA; Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX, USA
| | - Gregg C Fonarow
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles CA, USA
| | - Christie M Ballantyne
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA; Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX, USA
| | - Salim S Virani
- Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX, USA; Department of Medicine, Aga Khan University, Karachi, Pakistan
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Dastmalchi LN, German CA, Taub PR. High density lipoprotein: When to rethink too much of a good thing. Am J Prev Cardiol 2023; 15:100511. [PMID: 37434863 PMCID: PMC10331407 DOI: 10.1016/j.ajpc.2023.100511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/10/2023] [Accepted: 06/13/2023] [Indexed: 07/13/2023] Open
Abstract
High density lipoprotein cholesterol (HDL-C) is a known contributor to atherosclerotic cardiovascular disease (ASCVD) risk when HDL-C <40 mg/dL in men and <50 mg/dL in women. There has been much interest in the potential cardioprotective properties of HDL-C, as it removes cholesterol from the periphery to the liver for exertion and holds inherent anti-thrombotic and anti-inflammatory properties. However, clinical trials raising HDL-C pharmacologically have not shown to improve cardiovascular outcomes. In fact, observational studies have demonstrated an increased risk of non-cardiovascular mortality and infection when HDL-C >90 mg/dL and >70 mg/dL in women and men, respectively. The ability for the HDL particle to effectively transport cholesterol from the periphery for excretion in bile is more complex than illustrated on a standard cholesterol panel. There is variability in its function, size, density, subclass, reverse cholesterol transport, and cholesterol efflux capacity, which impact the particles ability to effectively reduce cardiovascular disease (CVD) risk. Research has shown that HDL particles are prone to have a reduction in its efficacy in response to infection, auto-immune disease, menopause and cardiometabolic conditions during pregnancy. Additionally, recent studies have shown that low HDL-C may not adequately influence ASCVD risk in Black adults. The purpose of this contemporary review is to highlight the utility of using HDL-C in assessing CVD risk.
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Affiliation(s)
- Lily N. Dastmalchi
- Section of Cardiology, Department of Medicine, Temple University Hospital, Philadelphia, PA, USA
| | - Charles A. German
- Section of Cardiology, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Pam R. Taub
- Section of Cardiology, Department of Medicine, University of California San Diego, San Diego, CA, USA
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Bechmann LE, Emanuelsson F, Nordestgaard BG, Benn M. SGLT2-inhibition increases total, LDL, and HDL cholesterol and lowers triglycerides: Meta-analyses of 60 randomized trials, overall and by dose, ethnicity, and drug type. Atherosclerosis 2023:117236. [PMID: 37582673 DOI: 10.1016/j.atherosclerosis.2023.117236] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 08/17/2023]
Abstract
BACKGROUND AND AIMS Sodium glucose co-transporter 2 (SGLT2)-inhibitors were developed as glucose-lowering drugs. Surprisingly, SGLT2-inhibitors also reduced risk of cardiovascular disease. The impact of SGLT2-inhibitors on lipids and lipoproteins is unclear, but an effect might contribute to the observed lower cardiovascular risk. We conducted a meta-analysis to examine this, overall and by dose, ethnicity, and drug type. METHODS PubMed, EMBASE and Web of Science were searched for randomized controlled trials examining all available SGLT2-inhibitors. Studies with available lipid measurements were included. Quantitative data synthesis was performed using random and fixed effects models. RESULTS We identified 60 randomized trials, including 147,130 individuals. Overall, using random effects models, SGLT2-inhibitor treatment increased total cholesterol by 0.09 mmol/L (95% CI: 0.06, 0.13), low-density lipoprotein (LDL) cholesterol by 0.08 mmol/L (0.05, 0.10), and high-density lipoprotein (HDL) cholesterol by 0.06 mmol/L (0.05, 0.07), while it reduced triglycerides by 0.10 mmol/L (0.06, 0.14). Fixed effects estimates were similar but with smaller effect sizes for HDL cholesterol and triglycerides. For higher SGLT2-inhibitor doses, there was a nominally higher non-significant effect on lipids and lipoproteins. In Asian compared to non-Asian populations, a slightly larger increase in HDL cholesterol and a decrease in triglycerides were observed, but with similar results for total and LDL cholesterol. Treatment effects on lipids and lipoproteins were generally robust across different SGLT2-inhibitor drugs. CONCLUSION In meta-analyses, SGLT2-inhibition increased total, LDL, and HDL cholesterol and decreased triglycerides. Effect sizes varied slightly by drug dose and ethnicity but were generally robust by drug type.
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Affiliation(s)
- Louise E Bechmann
- Department of Clinical Biochemistry, Copenhagen University Hospital - Rigshospitalet, 9 Blegdamsvej, DK-2100, Copenhagen, Denmark; Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, 3B Blegdamsvej, DK-2200, Copenhagen, Denmark; Department of Clinical Biochemistry, Copenhagen University Hospital - Herlev Gentofte, Borgmester Ib Juuls Vej 73, DK-2730, Herlev, Denmark
| | - Frida Emanuelsson
- Department of Clinical Biochemistry, Copenhagen University Hospital - Rigshospitalet, 9 Blegdamsvej, DK-2100, Copenhagen, Denmark; Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, 3B Blegdamsvej, DK-2200, Copenhagen, Denmark
| | - Børge G Nordestgaard
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, 3B Blegdamsvej, DK-2200, Copenhagen, Denmark; Department of Clinical Biochemistry, Copenhagen University Hospital - Herlev Gentofte, Borgmester Ib Juuls Vej 73, DK-2730, Herlev, Denmark
| | - Marianne Benn
- Department of Clinical Biochemistry, Copenhagen University Hospital - Rigshospitalet, 9 Blegdamsvej, DK-2100, Copenhagen, Denmark; Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, 3B Blegdamsvej, DK-2200, Copenhagen, Denmark.
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Poznyak AV, Sukhorukov VN, Guo S, Postnov AY, Orekhov AN. Sex Differences Define the Vulnerability to Atherosclerosis. CLINICAL MEDICINE INSIGHTS-CARDIOLOGY 2023; 17:11795468231189044. [PMID: 37529084 PMCID: PMC10387777 DOI: 10.1177/11795468231189044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 07/03/2023] [Indexed: 08/03/2023]
Abstract
For several decades, atherosclerosis has attracted the attention of researchers around the world. Even being a major cause of serious cardiovascular disease and events, atherosclerosis is still not fully understood. Despite the fact that the main players in the pathogenesis of atherosclerosis are well known, many mechanisms of their implementation and interactions remain unknown. The same can be said about the risk factors for atherosclerosis. Many of them are known, but exactly how they work remains to be seen. The main objective of this review is to summarize the latest data on sex as a biological variable in atherosclerosis in humans and animals; to determine what we do not still know about how sex affects the process of growth and complications of atherosclerosis. In this review, we summarized data on sex differences at 3 atherosclerotic aspects: inflammation, vascular remodeling, and plaque morphology. With all overviewed data, we came to the conclusion on the atheroprotective role of female sex.
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Affiliation(s)
| | - Vasiliy N Sukhorukov
- Laboratory of Angiopathology, Institute of General Pathology and Pathophysiology, Moscow, Russia
| | - Shuzhen Guo
- Diabetes Research Center, School of Traditional Chinese Medicine, Beijing University of Chinese, Beijing, China
| | - Anton Y Postnov
- Laboratory of Cellular and Molecular Pathology of Cardiovascular System, Federal State Budgetary Scientific Institution «Petrovsky National Research Centre of Surgery» (FSBSI “Petrovsky NRCS”), Moscow, Russia
| | - Alexander N Orekhov
- Laboratory of Angiopathology, Institute of General Pathology and Pathophysiology, Moscow, Russia
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Li G, Yu W, Yang H, Wang X, Ma T, Luo X. Relationship between Serum Ferritin Level and Dyslipidemia in US Adults Based on Data from the National Health and Nutrition Examination Surveys 2017 to 2020. Nutrients 2023; 15:nu15081878. [PMID: 37111096 PMCID: PMC10143246 DOI: 10.3390/nu15081878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 04/03/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
Previous research has suggested that high serum ferritin (SF) levels may be associated with dyslipidemia. This study investigated the association between SF levels and dyslipidemia in American adults, which held relevance for both clinical and public health areas concerned with screening and prevention. Data from the pre-pandemic National Health and Nutrition Examination Surveys (NHANES), conducted between 2017 and 2020, were utilized for this analysis. Multivariate linear regression models were used to explore the correlation between lipid and SF concentrations, and the connection between SF and the four types of dyslipidemia was further assessed by using multivariate logistic regression analysis. Odds ratios (ORs; 95% CI) for dyslipidemia were calculated for quartiles of SF concentrations, with the lowest ferritin quartile as the reference. The final subjects consisted of 2676 participants (1290 males and 1386 females). ORs for dyslipidemia were the highest in the fourth quartile (Q4) of SF both in males (OR: 1.60, 95% CI: 1.12-2.28) and females (OR: 1.52, 95% CI: 1.07-2.17). The crude ORs (95% CI) for the risk of High TC and High LDL-C increased progressively in both genders. However, after adjusting for covariates, the trend of significance was only present in females. Finally, the association between total daily iron intake and the four types of dyslipidemia was examined, revealing that the risk of High TG in the third quartile of the total daily iron intake was 2.16 times greater in females (adjusted OR: 3.16, 95% CI: 1.38-7.23). SF concentrations were remarkably associated with dyslipidemia. In females, daily dietary iron intake was associated with High-TG dyslipidemia.
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Affiliation(s)
- Guohua Li
- Department of Nutrition and Food Safety, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Wenlu Yu
- Department of Nutrition and Food Safety, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Hexiang Yang
- Department of Nutrition and Food Safety, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Xinyue Wang
- Department of Nutrition and Food Safety, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Tianyou Ma
- Department of Nutrition and Food Safety, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Xiaoqin Luo
- Department of Nutrition and Food Safety, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
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Kim M, Vu TH, Maas MB, Braun RI, Wolf MS, Roenneberg T, Daviglus ML, Reid KJ, Zee PC. Light at night in older age is associated with obesity, diabetes, and hypertension. Sleep 2023; 46:zsac130. [PMID: 35729737 PMCID: PMC9995772 DOI: 10.1093/sleep/zsac130] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 04/29/2022] [Indexed: 02/02/2023] Open
Abstract
Light at night (LAN) has been associated with negative health consequences and metabolic risk factors. Little is known about the prevalence of LAN in older adults in the United States and its association with CVD risk factors. We tested the hypothesis that LAN in older age is associated with higher prevalence of individual CVD risk factors. Five hundred and fifty-two community-dwelling adults aged 63-84 years underwent an examination of CVD risk factor profiles and 7-day actigraphy recording for activity and light measures. Associations between actigraphy-measured LAN, defined as no light vs. light within the 5-hour nadir (L5), and CVD risk factors, including obesity, diabetes, hypertension, and hypercholesterolemia, were examined, after adjusting for age, sex, race, season of recording, and sleep variables. LAN exposure was associated with a higher prevalence of obesity (multivariable-adjusted odds ratio [OR] 1.82 [95% CI 1.26-2.65]), diabetes (OR 2.00 [1.19-3.43]), and hypertension (OR 1.74 [1.21-2.52]) but not with hypercholesterolemia. LAN was also associated with (1) later timing of lowest light exposure (L5-light) and lowest activity (L5-activity), (2) lower inter-daily stability and amplitude of light exposure and activity, and (3) higher wake after sleep onset. Habitual LAN in older age is associated with concurrent obesity, diabetes, and hypertension. Further research is needed to understand long-term effects of LAN on cardiometabolic risks.
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Affiliation(s)
- Minjee Kim
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Applied Health Research on Aging, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Thanh-Huyen Vu
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Matthew B Maas
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Rosemary I Braun
- Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA
| | - Michael S Wolf
- Center for Applied Health Research on Aging, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Till Roenneberg
- Institute of Medical Psychology, Ludwig-Maximilian University, Munich, Germany
| | - Martha L Daviglus
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, IL, USA
| | - Kathryn J Reid
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Phyllis C Zee
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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Coronado G, Chio-Lauri J, Cruz RD, Roman YM. Health Disparities of Cardiometabolic Disorders Among Filipino Americans: Implications for Health Equity and Community-Based Genetic Research. J Racial Ethn Health Disparities 2022; 9:2560-2567. [PMID: 34837163 PMCID: PMC9248953 DOI: 10.1007/s40615-021-01190-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 10/19/2021] [Accepted: 11/10/2021] [Indexed: 12/29/2022]
Abstract
Health disparities are well-documented among different racial and ethnic minority groups in the United States. Filipino Americans (FAs) are the third-largest Asian-American group in the USA and are commonly grouped under the Asian categorization. FAs have a higher prevalence of cardiometabolic disorders than non-Hispanic Whites and other Asian subgroups with rates comparable to African Americans. Although no major epidemiological studies have ascertained the prevalence of cardiometabolic diseases in FAs, limited reports suggest that FAs have a higher prevalence of dyslipidemia, hypertension, diabetes, metabolic syndrome, hyperuricemia, and gout than non-FAs. A recent genetic study has shown that FAs could have the highest prevalence of a genetic polymorphism strongly associated with the development of gout and gout-related comorbidities. While developing cardiometabolic disorders is a heterogeneous and multifaceted process, the overall prevalence of certain cardiometabolic disorders parallel the prevalence of population-level risk factors, including genetics, dietary lifestyles, health beliefs, and social determinants of health. Therefore, assessment of the Filipino cuisine, health behaviors among Filipinos, socio-cultural factors, and acculturation to living in the USA are equally critical. Ascertaining the contribution of the biological causes to disease onset and the different psychosocial factors that could modulate disease risk or disease management are needed. Ultimately, a multilevel research approach is critical to assess the role of biological and non-biological risk factors of cardiometabolic disorders in FAs to inform culturally appropriate health promotion, disease prevention strategies, and a personalized approach to health.
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Affiliation(s)
- Gerald Coronado
- School of Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA
| | | | - Rosheanne Dela Cruz
- School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Youssef M. Roman
- School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
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9
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Herrington G, Riche DM. Part I: Interactive case: Hyperlipidemia management for special populations. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2022. [DOI: 10.1002/jac5.1688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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10
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Association between the ABCA1 (R219K) polymorphism and lipid profiles: a meta-analysis. Sci Rep 2021; 11:21718. [PMID: 34741058 PMCID: PMC8571387 DOI: 10.1038/s41598-021-00961-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 10/20/2021] [Indexed: 01/22/2023] Open
Abstract
Conflicting evidence was found about the relationship between lipid profiles and R219K polymorphism in adenosine triphosphate-binding cassette exporter A1 (ABCA1) gene. In this study, four meta-analyses were conducted to assess the effect of R219K on lipid levels, including high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol, total cholesterol, and triglycerides (TG). A total of 125 samples of 87 studies (about 60,262 subjects) were included. The effect of each study was expressed using the standard mean difference (SMD) and 95% confidence interval (95% CI) and pooled by meta-analysis in the random-effects model. Subgroup and meta-regression analyses were conducted to explore potential heterogeneity sources. The overall pooled effect showed the following results. (1) The R219K was significantly associated with HDLC level (SMD = - 0.25 mmol/L, 95%CI - 0.32 to - 0.18, z = - 6.96, P < 0.01, recessive genetic model). People with different genotypes had significantly different HDLC levels under the recessive, codominant and dominant genetic models (all Ps < 0.01). (2) A weak and indeterminate relationship between R219K and TG level was observed (SMD = 0.18 mmol/L, 95%CI 0.06-0.30, z = 3.01, P < 0.01, recessive genetic model). These findings suggested that R219K was associated with HDLC and TG levels, which might implicate a promising clinical application for lipid-related disorders, though the influences of race, health status, BMI, and other heterogeneity sources should be considered when interpreting current findings. The protocol was registered at PROSPERO (registration number: CRD42021231178).
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Haslam DE, Peloso GM, Guirette M, Imamura F, Bartz TM, Pitsillides AN, Wang CA, Li-Gao R, Westra JM, Pitkänen N, Young KL, Graff M, Wood AC, Braun KVE, Luan J, Kähönen M, Kiefte-de Jong JC, Ghanbari M, Tintle N, Lemaitre RN, Mook-Kanamori DO, North K, Helminen M, Mossavar-Rahmani Y, Snetselaar L, Martin LW, Viikari JS, Oddy WH, Pennell CE, Rosendall FR, Ikram MA, Uitterlinden AG, Psaty BM, Mozaffarian D, Rotter JI, Taylor KD, Lehtimäki T, Raitakari OT, Livingston KA, Voortman T, Forouhi NG, Wareham NJ, de Mutsert R, Rich SS, Manson JE, Mora S, Ridker PM, Merino J, Meigs JB, Dashti HS, Chasman DI, Lichtenstein AH, Smith CE, Dupuis J, Herman MA, McKeown NM. Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2021; 14:e003288. [PMID: 34270325 PMCID: PMC8373451 DOI: 10.1161/circgen.120.003288] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Supplemental Digital Content is available in the text. Background: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the CHREBP locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the CHREBP locus and dyslipidemia. Methods: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near CHREBP were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake. Results: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16–3.07] mg/dL per allele; P<0.0001), but not significantly among the lowest SSB consumers (P=0.81; PDiff <0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (β, 0.06 [95% CI, 0.02–0.09] ln-mg/dL per allele, P=0.001) but not the lowest SSB consumers (P=0.84; PDiff=0.0005). Conclusions: Our results identified genetic variants in the CHREBP locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005133, NCT00005121, NCT00005487, and NCT00000479.
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Affiliation(s)
- Danielle E Haslam
- Nutritional Epidemiology Program (D.E.H., M. Guirette, K.A.L., N.M.M.), Tufts University, Boston, MA.,Channing Division of Network Medicine (D.E.H., J.E.M.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA.,Department of Nutrition (D.E.H.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, MA (G.M.P., A.N.P., J.D.)
| | - Melanie Guirette
- Nutritional Epidemiology Program (D.E.H., M. Guirette, K.A.L., N.M.M.), Tufts University, Boston, MA
| | - Fumiaki Imamura
- Medical Research Council Epidemiology Unit, University of Cambridge, United Kingdom (F.I., J.L., N.G.F., N.J.W.)
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics (T.M.B.), University of Washington, Seattle.,Department of Medicine (T.M.B., R.N.L., B.M.P.), University of Washington, Seattle
| | - Achilleas N Pitsillides
- Department of Biostatistics, Boston University School of Public Health, MA (G.M.P., A.N.P., J.D.)
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, NSW, Australia (C.A.W., C.E.P.)
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology (R.L.G., D.O.M.-K., F.R.R., R.dM.), Leiden University Medical Center, the Netherlands
| | | | - Niina Pitkänen
- Auria Biobank (N.P.), University of Turku, Finland.,Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), University of Turku, Finland
| | - Kristin L Young
- Department of Epidemiology, Gillings School of Global Public Health (K.L.Y., M. Graff, K.N.), University of North Carolina, Chapel Hill
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health (K.L.Y., M. Graff, K.N.), University of North Carolina, Chapel Hill
| | - Alexis C Wood
- USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX (A.C.W.)
| | - Kim V E Braun
- Department of Epidemiology (K.V.E.B., J.C.K.-d.J., M. Ghanbari, M.A.I.), Erasmus MC University Medical Center Rotterdam, the Netherlands
| | - Jian'an Luan
- Medical Research Council Epidemiology Unit, University of Cambridge, United Kingdom (F.I., J.L., N.G.F., N.J.W.)
| | - Mika Kähönen
- Department of Clinical Physiology (M.K.), Tampere University Hospital, Finland.,Department of Clinical Physiology (M.K.), Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Finland
| | - Jessica C Kiefte-de Jong
- Department of Public Health and Primary Care (J.C.L.d.J., D.O.M.-K.), Leiden University Medical Center, the Netherlands.,Department of Epidemiology (K.V.E.B., J.C.K.-d.J., M. Ghanbari, M.A.I.), Erasmus MC University Medical Center Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology (K.V.E.B., J.C.K.-d.J., M. Ghanbari, M.A.I.), Erasmus MC University Medical Center Rotterdam, the Netherlands
| | | | - Rozenn N Lemaitre
- Department of Medicine (T.M.B., R.N.L., B.M.P.), University of Washington, Seattle
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology (R.L.G., D.O.M.-K., F.R.R., R.dM.), Leiden University Medical Center, the Netherlands.,Department of Public Health and Primary Care (J.C.L.d.J., D.O.M.-K.), Leiden University Medical Center, the Netherlands
| | - Kari North
- Department of Epidemiology, Gillings School of Global Public Health (K.L.Y., M. Graff, K.N.), University of North Carolina, Chapel Hill.,Carolina Center for Genome Science (K.N.), University of North Carolina, Chapel Hill
| | - Mika Helminen
- Research Development and Innovation Centre (M.H.), Tampere University Hospital, Finland.,Faculty of Social Sciences, Health Sciences, Tampere University, Finland (M.H.)
| | - Yasmin Mossavar-Rahmani
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY (Y.M.-R.)
| | - Linda Snetselaar
- Department of Epidemiology, University of Iowa, Iowa City (L.S.)
| | - Lisa W Martin
- George Washington University School of Medicine and Health Sciences, Washington, D.C. (L.W.M.)
| | - Jorma S Viikari
- Department of Medicine (J.S.V.), University of Turku, Finland.,Division of Medicine (J.S.V.), Turku University Hospital, Finland
| | - Wendy H Oddy
- Menzies Institute for Medical Research, University of Tasmania, HOB, Australia (W.H.O.)
| | - Craig E Pennell
- Nutrition and Genomics Laboratory (C.E.S.), Tufts University, Boston, MA.,School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, NSW, Australia (C.A.W., C.E.P.)
| | - Frits R Rosendall
- Department of Clinical Epidemiology (R.L.G., D.O.M.-K., F.R.R., R.dM.), Leiden University Medical Center, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology (K.V.E.B., J.C.K.-d.J., M. Ghanbari, M.A.I.), Erasmus MC University Medical Center Rotterdam, the Netherlands
| | - Andre G Uitterlinden
- Department of Internal Medicine (A.G.U.), Erasmus MC University Medical Center Rotterdam, the Netherlands
| | - Bruce M Psaty
- Department of Medicine (T.M.B., R.N.L., B.M.P.), University of Washington, Seattle.,Departments of Epidemiology and Health Services (B.M.P.), University of Washington, Seattle.,Kaiser Permanente Washington Health Research Institute, Seattle, WA (B.M.P.)
| | - Dariush Mozaffarian
- Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, and Friedman School of Nutrition Science and Policy (D.M.), Tufts University, Boston, MA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.I.R., K.D.T.)
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.I.R., K.D.T.)
| | - Terho Lehtimäki
- Department of Clinical Chemistry (T.L.), Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Finland.,Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (T.L.)
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine (N.P., O.T.R.), University of Turku, Finland.,Centre for Population Health Research (O.T.R.), University of Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine (O.T.R.), Turku University Hospital, Finland
| | - Kara A Livingston
- Nutritional Epidemiology Program (D.E.H., M. Guirette, K.A.L., N.M.M.), Tufts University, Boston, MA
| | | | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, University of Cambridge, United Kingdom (F.I., J.L., N.G.F., N.J.W.)
| | - Nick J Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, United Kingdom (F.I., J.L., N.G.F., N.J.W.)
| | - Renée de Mutsert
- Department of Clinical Epidemiology (R.L.G., D.O.M.-K., F.R.R., R.dM.), Leiden University Medical Center, the Netherlands
| | - Steven S Rich
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville (S.S.R.)
| | - JoAnn E Manson
- Channing Division of Network Medicine (D.E.H., J.E.M.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA.,Division of Preventive Medicine (J.E.M., S.M., P.M.R., D.I.C.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA.,Department of Epidemiology (J.E.M.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Samia Mora
- Division of Preventive Medicine (J.E.M., S.M., P.M.R., D.I.C.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA.,Cardiovascular Division of Medicine and Center for Lipid Metabolomics (S.M., P.M.R.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Paul M Ridker
- Division of Preventive Medicine (J.E.M., S.M., P.M.R., D.I.C.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA.,Cardiovascular Division of Medicine and Center for Lipid Metabolomics (S.M., P.M.R.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Jordi Merino
- Program in Medical and Population Genetics (J.M., J.B.M., H.S.D.), Broad Institute of MIT and Harvard, Cambridge, MA.,Program in Metabolism (J.M., J.B.M.), Broad Institute of MIT and Harvard, Cambridge, MA.,Department of Medicine, Harvard Medical School, Boston, MA (J.M., J.B.M.).,Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, Reus, Spain (J.M.).,Diabetes Unit and Center for Genomic Medicine (J.M., H.S.D.), Massachusetts General Hospital and Harvard Medical School, Boston
| | - James B Meigs
- Program in Medical and Population Genetics (J.M., J.B.M., H.S.D.), Broad Institute of MIT and Harvard, Cambridge, MA.,Program in Metabolism (J.M., J.B.M.), Broad Institute of MIT and Harvard, Cambridge, MA.,Department of Medicine, Harvard Medical School, Boston, MA (J.M., J.B.M.).,Division of General Internal Medicine (J.B.M.), Massachusetts General Hospital and Harvard Medical School, Boston
| | - Hassan S Dashti
- Program in Medical and Population Genetics (J.M., J.B.M., H.S.D.), Broad Institute of MIT and Harvard, Cambridge, MA.,Diabetes Unit and Center for Genomic Medicine (J.M., H.S.D.), Massachusetts General Hospital and Harvard Medical School, Boston.,Department of Anesthesia, Critical Care and Pain Medicine (H.S.D.), Massachusetts General Hospital and Harvard Medical School, Boston
| | - Daniel I Chasman
- Division of Preventive Medicine (J.E.M., S.M., P.M.R., D.I.C.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | | | | | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, MA (G.M.P., A.N.P., J.D.)
| | - Mark A Herman
- Division Of Endocrinology, Metabolism, and Nutrition, Department of Medicine and Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (M.A.H.)
| | - Nicola M McKeown
- Nutritional Epidemiology Program (D.E.H., M. Guirette, K.A.L., N.M.M.), Tufts University, Boston, MA
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12
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Nagarathna R, Kumar S, Anand A, Acharya IN, Singh AK, Patil SS, Latha RH, Datey P, Nagendra HR. Effectiveness of Yoga Lifestyle on Lipid Metabolism in a Vulnerable Population-A Community Based Multicenter Randomized Controlled Trial. MEDICINES 2021; 8:medicines8070037. [PMID: 34357153 PMCID: PMC8303653 DOI: 10.3390/medicines8070037] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 06/13/2021] [Accepted: 06/29/2021] [Indexed: 01/09/2023]
Abstract
Background: Dyslipidemia poses a high risk for cardiovascular disease and stroke in Type 2 diabetes (T2DM). There are no studies on the impact of a validated integrated yoga lifestyle protocol on lipid profiles in a high-risk diabetes population. Methods: Here, we report the results of lipid profile values of 11,254 (yoga 5932 and control 5322) adults (20–70 years) of both genders with high risk (≥60 on Indian diabetes risk score) for diabetes from a nationwide rural and urban community-based two group (yoga and conventional management) cluster randomized controlled trial. The yoga group practiced a validated integrated yoga lifestyle protocol (DYP) in nine day camps followed by daily one-hour practice. Biochemical profiling included glycated hemoglobin and lipid profiles before and after three months. Results: There was a significant difference between groups (p < 0.001 ANCOVA) with improved serum total cholesterol, triglycerides, low-density lipoprotein, and high-density lipoprotein in the yoga group compared to the control group. Further, the regulatory effect of yoga was noted with a significant decrease or increase in those with high or low values of lipids, respectively, with marginal or no change in those within the normal range. Conclusion: Yoga lifestyle improves and regulates (lowered if high, increased if low) the blood lipid levels in both genders of prediabetic and diabetic individuals in both rural and urban Indian communities.
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Affiliation(s)
- Raghuram Nagarathna
- Swami Vivekananda Yoga Anusandhana Samsthana (S-VYASA), Bengaluru 560105, India; (A.K.S.); (S.S.P.); (H.R.N.)
- Correspondence: (R.N.); (A.A.)
| | - Saurabh Kumar
- Neuroscience Research Lab, Department of Neurology, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India;
| | - Akshay Anand
- Neuroscience Research Lab, Department of Neurology, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India;
- Centre for Mind Body Medicine, PGIMER, Chandigarh 160012, India
- Centre for Cognitive Science and Phenomenology, Panjab University, Chandigarh 160014, India
- Correspondence: (R.N.); (A.A.)
| | - Ishwara N. Acharya
- Central Council for Research in Yoga & Naturopathy (CCRYN), Delhi 110058, India;
| | - Amit Kumar Singh
- Swami Vivekananda Yoga Anusandhana Samsthana (S-VYASA), Bengaluru 560105, India; (A.K.S.); (S.S.P.); (H.R.N.)
| | - Suchitra S. Patil
- Swami Vivekananda Yoga Anusandhana Samsthana (S-VYASA), Bengaluru 560105, India; (A.K.S.); (S.S.P.); (H.R.N.)
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13
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Du H, Rao Y, Liu R, Deng K, Guan Y, Luo D, Mao Q, Yu J, Bo T, Fan Z, Ouyang H, Feng Y, Zhu W. Proteomics and metabolomics analyses reveal the full spectrum of inflammatory and lipid metabolic abnormalities in dyslipidemia. Biomed Chromatogr 2021; 35:e5183. [PMID: 34058018 DOI: 10.1002/bmc.5183] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 05/18/2021] [Accepted: 05/26/2021] [Indexed: 01/21/2023]
Abstract
Dyslipidemia is a common, chronic metabolic disease associated with cardiovascular complications. Due to the multiplicity of etiological factors, the pathogenesis of dyslipidemia is still unclear. In this study, we combined proteomics and metabolomics methods to analyze the plasma of patients with dyslipidemia and healthy subjects. isobaric tags for relative and absolute quantification (iTRAQ) markers, combined with LC-MS/MS proteomics technology and the UHPLC/Orbitfast-X Tribrid system, were used to establish the metabolite profile in clinical dyslipidemia. A total of 137 differentially expressed proteins, mainly related to biological processes such as protein activation cascades, adaptive immune responses, complement activation, acute inflammatory responses, and regulation of acute inflammatory responses, were identified. These proteins are involved in the regulation of important metabolic pathways, such as immunity and inflammation, coagulation and hemostasis, lipid metabolism, and oxidation and antioxidant defenses. The analysis of clinical metabolites showed there were 69 different metabolites in plasma, mainly related to glycerolipid, sphingolipid, porphyrin, α-linolenic acid, linoleic acid, and arachidonic acid metabolism, suggesting that the regulation of inflammation and lipid metabolism may be disturbed in patients with dyslipidemia. Among these, significant changes were observed in indole-3-propionic acid (IPA), which is considered as a potential biomarker of dyslipidemia. The combined analysis of proteins and metabolites showed that arachidonic acid, linoleic acid, and lipid metabolic pathways were closely related to dyslipidemia. IPA may be a potential biomarker. The information provided in this study may provide new insights into the pathogenesis of animal models of dyslipidemia and related disease models, as well as potential intervention targets.
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Affiliation(s)
- Hui Du
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Yifei Rao
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Ronghua Liu
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Kesui Deng
- The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Yongmei Guan
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Dewei Luo
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Qiping Mao
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Jianwei Yu
- The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Tao Bo
- Thermo Fisher Scientific-CN, Shanghai, China
| | - Ziquan Fan
- Thermo Fisher Scientific-CN, Shanghai, China
| | - Hui Ouyang
- Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Yulin Feng
- State Key Laboratory of Innovative Drug and Efficient Energy-Saving Pharmaceutical Equipment, Nanchang, China
| | - Weifeng Zhu
- Key Laboratory of Ministry of Education of Jiangxi University of Traditional Chinese Medicine, Nanchang, China
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14
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Hama M, Horie R, Kubota T, Matsumura T, Kimura E, Nakamura H, Takahashi MP, Takada H. Metabolic complications in myotonic dystrophy type 1: A cross-sectional survey using the National Registry of Japan. J Neurol Sci 2021; 427:117511. [PMID: 34082146 DOI: 10.1016/j.jns.2021.117511] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 05/15/2021] [Accepted: 05/25/2021] [Indexed: 01/30/2023]
Abstract
Myotonic dystrophy type 1 (DM1) is the most common form of muscular dystrophy in adults, affecting multiple organs, including the eyes, heart, endocrine system, and central nervous system. The broad spectrum of DM1 symptoms has been attributed to the aberrant pre-mRNA splicing of various genes due to an abnormal expansion of the CTG repeat in the 3' untranslated region of the DMPK gene. The current challenge in the clinical care of DM1 is the lack of well-established protocols for the management of each organ disorder or symptom. Moreover, the current status of clinical management has not been adequately explored. Metabolic disturbance in DM1 has been less explored among the DM1 manifestations, even though impaired glucose tolerance is a widely known metabolic disorder associated with DM1. We investigated the metabolic disturbance related to DM1 using the national registry of neuromuscular diseases in Japan, Registry of Muscular Dystrophy (Remudy), and assessed the metabolic complications in DM1 and the current treatments. We obtained comprehensive information on the current status of liver dysfunction and dyslipidemia in a sizeable DM1 cohort (~300). We confirmed that the incidence of liver dysfunction and dyslipidemia, particularly hypertriglyceridemia, as well as impaired glucose tolerance, were significantly higher in DM1 patients. Furthermore, the majority of DM1 patients with dyslipidemia were not receiving pharmacotherapy. Our data highlight the current status of DM1 patients in Japan, which can guide the establishment of the standard of care for metabolic issues consequent to DM1.
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Affiliation(s)
- Manami Hama
- Clinical Neurophysiology, Department of Clinical Laboratory and Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Riho Horie
- Clinical Neurophysiology, Department of Clinical Laboratory and Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Tomoya Kubota
- Clinical Neurophysiology, Department of Clinical Laboratory and Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Tsuyoshi Matsumura
- Department of Neurology, National Hospital Organization Osaka Toneyama Medical Center Toneyama, Toyonaka, Osaka 560-8552, Japan
| | - En Kimura
- Translational Medical Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-8551, Japan
| | - Harumasa Nakamura
- Translational Medical Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-8551, Japan
| | - Masanori P Takahashi
- Clinical Neurophysiology, Department of Clinical Laboratory and Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka, Suita, Osaka 565-0871, Japan.
| | - Hiroto Takada
- Department of Neurology, National Hospital Organization Aomori National Hospital, Namioka, Aomori 038-1331, Japan.
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15
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Kim JB, Song WH, Park JS, Youn TJ, Park YH, Kim SJ, Ahn SG, Doh JH, Cho YH, Kim JW. A randomized, open-label, parallel, multi-center Phase IV study to compare the efficacy and safety of atorvastatin 10 and 20 mg in high-risk Asian patients with hypercholesterolemia. PLoS One 2021; 16:e0245481. [PMID: 33481866 PMCID: PMC7822387 DOI: 10.1371/journal.pone.0245481] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 01/01/2021] [Indexed: 12/03/2022] Open
Abstract
Background Although accumulating evidence suggests a more extensive reduction of low-density lipoprotein cholesterol (LDL-C), it is unclear whether a higher statin dose is more effective and cost-effective in the Asian population. This study compared the efficacy, safety, and cost-effectiveness of atorvastatin 20 and 10 mg in high-risk Asian patients with hypercholesterolemia. Methods A 12-week, open-label, parallel, multicenter, Phase IV randomized controlled trial was conducted at ten hospitals in the Republic of Korea between October 2017 and May 2019. High-risk patients with hypercholesterolemia, defined according to 2015 Korean guidelines for dyslipidemia management, were eligible to participate. We randomly assigned 250 patients at risk of atherosclerotic cardiovascular disease to receive 20 mg (n = 124) or 10 mg (n = 126) of atorvastatin. The primary endpoint was the difference in the mean percentage change in LDL-C levels from baseline after 12 weeks. Cost-effectiveness was measured as an exploratory endpoint. Results LDL-C levels were reduced more significantly by atorvastatin 20 mg than by 10 mg after 12 weeks (42.4% vs. 33.5%, p < 0.0001). Significantly more patients achieved target LDL-C levels (<100 mg/dL for high-risk patients, <70 mg/dL for very high-risk patients) with atorvastatin 20 mg than with 10 mg (40.3% vs. 25.6%, p < 0.05). Apolipoprotein B decreased significantly with atorvastatin 20mg versus 10 mg (−36.2% vs. −29.9%, p < 0.05). Lipid ratios also showed greater improvement with atorvastatin 20 mg than with 10 mg (total cholesterol/high-density lipoprotein cholesterol ratio, −33.3% vs. −29.4%, p < 0.05; apolipoprotein B/apolipoprotein A1 ratio, −36.7% vs. −31.4%, p < 0.05). Atorvastatin 20 mg was more cost-effective than atorvastatin 10 mg in terms of both the average and incremental cost-effectiveness ratios. Safety and tolerability of atorvastatin 20 mg were comparable to those of atorvastatin 10 mg. Conclusion In high-risk Asian patients with hypercholesterolemia, atorvastatin 20 mg was both efficacious in reducing LDL-C and cost-effective compared with atorvastatin 10 mg.
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Affiliation(s)
- Ji Bak Kim
- Department of Medicine, Korea University Graduate School, Seoul, Korea
| | - Woo Hyuk Song
- Division of Cardiology, Department of Internal Medicine, Korea University Ansan Hospital, Ansan, Korea
| | - Jong Sung Park
- Department of Cardiology, Dong-A University Hospital, Busan, Korea
| | - Tae-Jin Youn
- Division of Cardiology, Department of Internal Medicine, College of Medicine, Seoul National University and Cardiovascular Center, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Yong Hyun Park
- Division of Cardiology, Department of Internal Medicine, Cardiovascular Center, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Shin-Jae Kim
- Department of Cardiology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
| | - Sung Gyun Ahn
- Division of Cardiology, Department of Internal Medicine, Wonju Severance Christian Hospital, Wonju, Korea
| | - Joon-Hyung Doh
- Department of Cardiology, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Yun-Hyeong Cho
- Department of Internal Medicine, Myongji Hospital, Goyang, Korea
| | - Jin Won Kim
- Cardiovascular Center, Korea University Guro Hospital, Seoul, Korea
- * E-mail:
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16
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Wangeline MA, Hampton RY. An autonomous, but INSIG-modulated, role for the sterol sensing domain in mallostery-regulated ERAD of yeast HMG-CoA reductase. J Biol Chem 2020; 296:100063. [PMID: 33184059 PMCID: PMC7948459 DOI: 10.1074/jbc.ra120.015910] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 11/01/2020] [Accepted: 11/12/2020] [Indexed: 01/23/2023] Open
Abstract
HMG-CoA reductase (HMGR) undergoes feedback-regulated degradation as part of sterol pathway control. Degradation of the yeast HMGR isozyme Hmg2 is controlled by the sterol pathway intermediate GGPP, which causes misfolding of Hmg2, leading to degradation by the HRD pathway; we call this process mallostery. We evaluated the role of the Hmg2 sterol sensing domain (SSD) in mallostery, as well as the involvement of the highly conserved INSIG proteins. We show that the Hmg2 SSD is critical for regulated degradation of Hmg2 and required for mallosteric misfolding of GGPP as studied by in vitro limited proteolysis. The Hmg2 SSD functions independently of conserved yeast INSIG proteins, but its function was modulated by INSIG, thus imposing a second layer of control on Hmg2 regulation. Mutant analyses indicated that SSD-mediated mallostery occurred prior to and independent of HRD-dependent ubiquitination. GGPP-dependent misfolding was still extant but occurred at a much slower rate in the absence of a functional SSD, indicating that the SSD facilitates a physiologically useful rate of GGPP response and implying that the SSD is not a binding site for GGPP. Nonfunctional SSD mutants allowed us to test the importance of Hmg2 quaternary structure in mallostery: a nonresponsive Hmg2 SSD mutant strongly suppressed regulation of a coexpressed, normal Hmg2. Finally, we have found that GGPP-regulated misfolding occurred in detergent-solubilized Hmg2, a feature that will allow next-level analysis of the mechanism of this novel tactic of ligand-regulated misfolding.
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Affiliation(s)
- Margaret A Wangeline
- Division of Biological Sciences, the Section of Cell and Developmental Biology, UCSD, La Jolla, California, USA
| | - Randolph Y Hampton
- Division of Biological Sciences, the Section of Cell and Developmental Biology, UCSD, La Jolla, California, USA.
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17
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Role of Lipid-Lowering Therapy in Low-Density Lipoprotein Cholesterol Goal Attainment: Focus on Patients With Acute Coronary Syndrome. J Cardiovasc Pharmacol 2020; 76:658-670. [PMID: 33002965 PMCID: PMC7720869 DOI: 10.1097/fjc.0000000000000914] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Dyslipidemia is a major risk factor for cardiovascular (CV) disease, which is the leading cause of death globally. Acute coronary syndrome (ACS) is a common cause of death, accounting for nearly half of the global burden of CV mortality. Epidemiologic studies have identified low-density lipoprotein cholesterol (LDL-C) as an independent CV risk factor, and this is now the primary target for initiating and adjusting lipid-lowering therapies in most current guidelines. Evidence from pivotal studies supports the use of high-intensity statin therapy and a lower level for optimal LDL-C in secondary prevention of atherosclerotic CV disease, especially in patients with ACS undergoing percutaneous coronary intervention. However, current research has identified a gap between the target LDL-C goal attainment and target LDL-C levels recommended by the guidelines. Statins have proven benefits in the management of CV disease and are the cornerstone of lipid-lowering management in patients with ACS. Recent randomized controlled trials have also demonstrated the benefits of cholesterol absorption inhibitors and proprotein convertase subtilisin/kexin type 9 inhibitors. This review summarizes the current evidence for LDL-lowering therapy in patients with ACS, with an emphasis on the importance of LDL-C goal attainment, rapid LDL-C lowering, and duration of LDL-C–lowering therapy.
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18
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Abstract
INTRODUCTION There have been recent mounting concerns regarding multiple reports stating a significantly elevated relative-risk of COVID-19 mortality amongst the Black and Minority Ethnic (BAME) population. An urgent national enquiry investigating the possible reasons for this phenomenon has been issued in the UK. Inflammation is at the forefront of COVID-19 research as disease severity appears to correlate with pro-inflammatory cytokine dysregulation. This narrative review aims to shed light on the novel, pathophysiological role of inflammation in contributing towards the increased COVID-19 mortality risk amongst the BAME population. METHODS Searches in PubMed, Medline, Scopus, medRxiv and Google Scholar were performed to identify articles published in English from inception to 18th June 2020. These databases were searched using keywords including: 'COVID-19' or 'Black and Minority Ethnic' or 'Inflammation'. A narrative review was synthesized using these included articles. RESULTS We suggest a novel pathophysiological mechanism by which acute inflammation from COVID-19 may augment existing chronic inflammation, in order to potentiate a 'cytokine storm' and thus the more severe disease phenotype observed in the BAME population. Obesity, insulin resistance, cardiovascular disease, psychological stress, chronic infections and genetic predispositions are all relevant factors which may be contributing to elevated chronic systemic inflammation amongst the BAME population. CONCLUSION Overall, this review provides early insights and directions for ongoing research regarding the pathophysiological mechanisms that may explain the severe COVID-19 disease phenotype observed amongst the BAME population. We suggest 'personalization' of chronic disease management, which can be used with other interventions, in order to tackle this.
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Affiliation(s)
- Abhinav Vepa
- Department of Medicine, Milton Keynes University Hospital NHS Foundation Trust, Eaglestone, Milton Keynes, Buckinghamshire, UK.
| | - Joseph P Bae
- Department of Medicine, Milton Keynes University Hospital NHS Foundation Trust, Eaglestone, Milton Keynes, Buckinghamshire, UK
| | | | - Manish Pareek
- Department of Respiratory Sciences, University of Leicester, UK
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19
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Bohlen SM, Eckmann-Scholz C, Rath W, Maass N, Pecks U. [Does Apolipoprotein B Level in Early Pregnancy Predict Excessive Gestational Weight Gain and Adverse Pregnancy Outcome?]. Z Geburtshilfe Neonatol 2020; 224:348-354. [PMID: 32162284 DOI: 10.1055/a-1118-4084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
INTRODUCTION Excessive maternal gestational weight gain (GWG) is a risk factor for maternal and fetal complications. The lipid profile changes physiologically during pregnancy. Weight gain can affect lipid metabolism. The hypothesis of the study was that apoB levels early in pregnancy are associated with excessive GWG and predictive for adverse outcomes. METHODS Out of 547 patients there were 95 women with inadequate GWG, 171 with adequate GWG, and 281 with excessive GWG. Out of 581 patients there were 14 patients with pregnancy-induced hypertonus/pre-eclampsia, 67 with small-for-gestational-age (SGA) infants, and 7 with fetal growth restriction (FGR). ApoB levels were measured by ELISA. RESULTS There was no significant difference in apoB levels between the different GWG groups. We found significantly higher levels of apoB in overweight and obese patients compared to those with normal BMI. Smoking was correlated with higher apoB levels. There were no differences either between women with PIH/PE and normotensive women or between SGA/IUGR and pregnancies without. Women with pre-existing hypertension showed significantly higher apoB levels than the control group. CONCLUSIONS ApoB cannot be used as a marker for identifying the risk of excessive GWG or adverse pregnancy outcomes early in pregnancy. However, it may be involved in the pathophysiology of adverse pregnancy outcomes in high-risk patients.
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Affiliation(s)
- Sophia-Marie Bohlen
- Klinik für Gynäkologie und Geburtshilfe, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel
| | - Christel Eckmann-Scholz
- Klinik für Gynäkologie und Geburtshilfe, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel
| | - Werner Rath
- Klinik für Gynäkologie und Geburtshilfe, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel
| | - Nicolai Maass
- Klinik für Gynäkologie und Geburtshilfe, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel
| | - Ulrich Pecks
- Klinik für Gynäkologie und Geburtshilfe, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel
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20
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Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019; 139:e1082-e1143. [PMID: 30586774 PMCID: PMC7403606 DOI: 10.1161/cir.0000000000000625] [Citation(s) in RCA: 1090] [Impact Index Per Article: 218.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Scott M Grundy
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Neil J Stone
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Alison L Bailey
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Craig Beam
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Kim K Birtcher
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Roger S Blumenthal
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Lynne T Braun
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Sarah de Ferranti
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph Faiella-Tommasino
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Daniel E Forman
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Ronald Goldberg
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Paul A Heidenreich
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Mark A Hlatky
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Daniel W Jones
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Donald Lloyd-Jones
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Nuria Lopez-Pajares
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Chiadi E Ndumele
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Carl E Orringer
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Carmen A Peralta
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph J Saseen
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Sidney C Smith
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Laurence Sperling
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Salim S Virani
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph Yeboah
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
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21
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Chen Y, Yuan Z, Lu J, Eliaschewitz FG, Lorenzatti AJ, Monsalvo ML, Wang N, Hamer AW, Ge J. Randomized study of evolocumab in patients with type 2 diabetes and dyslipidaemia on background statin: Pre-specified analysis of the Chinese population from the BERSON clinical trial. Diabetes Obes Metab 2019; 21:1464-1473. [PMID: 30851062 PMCID: PMC6594089 DOI: 10.1111/dom.13700] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 02/28/2019] [Accepted: 03/06/2019] [Indexed: 12/26/2022]
Abstract
AIM The aim of this study was to evaluate the efficacy and safety of evolocumab with background atorvastatin in Chinese patients with type 2 diabetes mellitus (T2DM) and hyperlipidaemia or mixed dyslipidaemia. MATERIALS AND METHODS This is a pre-specified analysis of patients in the BERSON study (ClinicalTrials.gov, NCT02662569) in China. Patients initiated background atorvastatin 20 mg/d, after which they were randomized 2:2:1:1 to evolocumab 140 mg every 2 weeks (Q2W) or 420 mg monthly (QM) or to placebo Q2W or QM. Co-primary endpoints were percentage change in LDL cholesterol (LDL-C) from baseline to week 12 and from baseline to the mean of weeks 10 and 12. Additional endpoints included atherogenic lipids, glycaemic measures and adverse events (AEs). RESULTS Among 453 patients randomized in China, 451 received at least one dose of study drug (evolocumab or placebo). Evolocumab significantly reduced LDL-C compared with placebo at week 12 (Q2W, -85.0%; QM, -74.8%) and at the mean of weeks 10 and 12 (Q2W, -80.4%; QM, -81.0%) (adjusted P < 0.0001 for all) when administered with background atorvastatin. Non-HDL-C, ApoB100, total cholesterol, Lp(a), triglycerides, HDL-C and VLDL-C significantly improved with evolocumab vs placebo. No new safety findings were observed with evolocumab. The incidence of diabetes AEs was higher with evolocumab compared with placebo. There were no differences over time between evolocumab and placebo in measures of glycaemic control. CONCLUSIONS In patients in China with T2DM and hyperlipidaemia or mixed dyslipidaemia receiving background atorvastatin, evolocumab significantly reduced LDL-C and other atherogenic lipids, was well tolerated, and had no notable impact on glycaemic measures.
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Affiliation(s)
- Yundai Chen
- Department of CardiologyChinese People's Liberation Army General HospitalBeijingChina
| | - Zuyi Yuan
- First Affiliated Hospital of Xi'an Jiaotong UniversityShaanxiChina
| | - Juming Lu
- Department of EndocrinologyChinese People's Liberation Army General HospitalBeijingChina
| | | | - Alberto J. Lorenzatti
- Clinical Research and Cardiology, Instituto Medico DAMIC / Fundación RusculledaCórdobaArgentina
| | | | - Nan Wang
- Clinical Development, Amgen Inc.Thousand OaksCalifornia
| | | | - Junbo Ge
- Department of Cardiology, Shanghai Institute of Cardiovascular DiseasesZhongshan Hospital, Fudan UniversityShanghaiChina
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22
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Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol. J Am Coll Cardiol 2019; 73:e285-e350. [DOI: 10.1016/j.jacc.2018.11.003] [Citation(s) in RCA: 1113] [Impact Index Per Article: 222.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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23
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Interventions to Reduce Ethnic and Racial Disparities in Dyslipidemia Management. CURRENT TREATMENT OPTIONS IN CARDIOVASCULAR MEDICINE 2019; 21:24. [DOI: 10.1007/s11936-019-0725-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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24
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Safarova MS, Satterfield BA, Fan X, Austin EE, Ye Z, Bastarache L, Zheng N, Ritchie MD, Borthwick KM, Williams MS, Larson EB, Scrol A, Jarvik GP, Crosslin DR, Leppig K, Rasmussen-Torvik LJ, Pendergrass SA, Sturm AC, Namjou B, Shah AS, Carroll RJ, Chung WK, Wei WQ, Feng Q, Stein CM, Roden DM, Manolio TA, Schaid DJ, Denny JC, Hebbring SJ, de Andrade M, Kullo IJ. A phenome-wide association study to discover pleiotropic effects of PCSK9, APOB, and LDLR. NPJ Genom Med 2019; 4:3. [PMID: 30774981 PMCID: PMC6370860 DOI: 10.1038/s41525-019-0078-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Accepted: 01/16/2019] [Indexed: 01/09/2023] Open
Abstract
We conducted an electronic health record (EHR)-based phenome-wide association study (PheWAS) to discover pleiotropic effects of variants in three lipoprotein metabolism genes PCSK9, APOB, and LDLR. Using high-density genotype data, we tested the associations of variants in the three genes with 1232 EHR-derived binary phecodes in 51,700 European-ancestry (EA) individuals and 585 phecodes in 10,276 African-ancestry (AA) individuals; 457 PCSK9, 730 APOB, and 720 LDLR variants were filtered by imputation quality (r 2 > 0.4), minor allele frequency (>1%), linkage disequilibrium (r 2 < 0.3), and association with LDL-C levels, yielding a set of two PCSK9, three APOB, and five LDLR variants in EA but no variants in AA. Cases and controls were defined for each phecode using the PheWAS package in R. Logistic regression assuming an additive genetic model was used with adjustment for age, sex, and the first two principal components. Significant associations were tested in additional cohorts from Vanderbilt University (n = 29,713), the Marshfield Clinic Personalized Medicine Research Project (n = 9562), and UK Biobank (n = 408,455). We identified one PCSK9, two APOB, and two LDLR variants significantly associated with an examined phecode. Only one of the variants was associated with a non-lipid disease phecode, ("myopia") but this association was not significant in the replication cohorts. In this large-scale PheWAS we did not find LDL-C-related variants in PCSK9, APOB, and LDLR to be associated with non-lipid-related phenotypes including diabetes, neurocognitive disorders, or cataracts.
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Affiliation(s)
- Maya S. Safarova
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905 USA
| | | | - Xiao Fan
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905 USA
| | - Erin E. Austin
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905 USA
| | - Zhan Ye
- Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449 USA
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37235 USA
| | - Neil Zheng
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37235 USA
| | - Marylyn D. Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19111 USA
| | - Kenneth M. Borthwick
- Department of Biomedical and Translational Informatics, Geisinger, Danville, PA 17821 USA
| | | | | | - Aaron Scrol
- Group Health Research Institute, Seattle, WA 98101 USA
| | - Gail P. Jarvik
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA 98195 USA
| | - David R. Crosslin
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA 98195 USA
- Department of Genome Sciences, University of Washington, Seattle, WA 98195 USA
| | - Kathleen Leppig
- Genetic Services, Kaiser Permanente of Washington, Seattle, WA 98122 USA
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611 USA
| | - Sarah A. Pendergrass
- Department of Biomedical and Translational Informatics, Geisinger, Danville, PA 17821 USA
| | - Amy C. Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA 17822 USA
| | - Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, and Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, OH 45229 USA
| | - Amy Sanghavi Shah
- Division of Endocrinology, Cincinnati Children’s Hospital Medical Center and University of Cincinnati, Cincinnati, OH 45229 USA
| | - Robert J. Carroll
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37235 USA
| | - Wendy K. Chung
- Department of Pediatrics, Columbia University, New York, NY 10032 USA
- Department of Medicine, Columbia University, New York, NY 10032 USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37235 USA
| | - QiPing Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University, Nashville, TN 37232 USA
| | - C. Michael Stein
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University, Nashville, TN 37232 USA
| | - Dan M. Roden
- Department of Medicine, Vanderbilt University, Nashville, TN 37232 USA
| | - Teri A. Manolio
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD 20892 USA
| | - Daniel J. Schaid
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905 USA
| | - Joshua C. Denny
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37235 USA
| | - Scott J. Hebbring
- Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449 USA
| | - Mariza de Andrade
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905 USA
| | - Iftikhar J. Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905 USA
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Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2018; 139:e1046-e1081. [PMID: 30565953 DOI: 10.1161/cir.0000000000000624] [Citation(s) in RCA: 238] [Impact Index Per Article: 39.7] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Scott M Grundy
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Neil J Stone
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Alison L Bailey
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Craig Beam
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Kim K Birtcher
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Roger S Blumenthal
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Lynne T Braun
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Sarah de Ferranti
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph Faiella-Tommasino
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Daniel E Forman
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Ronald Goldberg
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Paul A Heidenreich
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Mark A Hlatky
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Daniel W Jones
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Donald Lloyd-Jones
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Nuria Lopez-Pajares
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Chiadi E Ndumele
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Carl E Orringer
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Carmen A Peralta
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph J Saseen
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Sidney C Smith
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Laurence Sperling
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Salim S Virani
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
| | - Joseph Yeboah
- ACC/AHA Representative. †AACVPR Representative. ‡ACC/AHA Task Force on Clinical Practice Guidelines Liaison. §Prevention Subcommittee Liaison. ‖PCNA Representative. ¶AAPA Representative. **AGS Representative. ††ADA Representative. ‡‡PM Representative. §§ACPM Representative. ‖‖NLA Representative. ¶¶APhA Representative. ***ASPC Representative. †††ABC Representative
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Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2018; 73:3168-3209. [PMID: 30423391 DOI: 10.1016/j.jacc.2018.11.002] [Citation(s) in RCA: 953] [Impact Index Per Article: 158.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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Santos RD, Bensenor IM, Pereira AC, Lotufo PA. Dyslipidemia according to gender and race: The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). J Clin Lipidol 2016; 10:1362-1368. [PMID: 27919353 DOI: 10.1016/j.jacl.2016.08.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2016] [Revised: 07/27/2016] [Accepted: 08/15/2016] [Indexed: 11/28/2022]
Abstract
BACKGROUND There is little information regarding lipid profiles of racially mixed populations. Differently from other Latin American countries, the proportion of African ancestry is much higher in Brazil. OBJECTIVE Verify whether there are differences in the lipid profile between black and white subjects and if people with mixed ancestry have a pattern more closely resembling whites or blacks. METHODS A total of 15,105 civil servants aged 35-74 years from the ELSA-Brasil study had their fasting lipid profile determined. Race/skin color was self-reported as white, mixed, black, Asian, or indigenous. Dyslipidemia subtypes were classified as high triglycerides (TG) (≥150 mg/dL), low HDL-C (<40 [men] and <50 [women] mg/dL), and high LDL-C (≥130 mg/dL or ever taking lipid-lowering agents). The adjusted odds ratios (95% confidence interval) for dyslipidemia were calculated for each racial group using white participants as the reference group by logistic regression. RESULTS Elevated concentrations in LDL-C and TG and low-HDL-C had a lower prevalence in the black group compared with whites after multivariate adjustment including adiposity and socioeconomic status. For women and men, respectively, the odds ratios (95% confidence interval) for high LDL-C are 0.94 (0.89-0.99) and 0.93 (0.87-0.99); for high TG, 0.63 (0.54-0.74) and 0.92 (0.84-1.00); and for low HDL-C, 0.77 (0.66-0.91) and 0.78 (0.64-0.94). The mixed race group presented a pattern of dyslipidemia closer to white than to black subjects. CONCLUSIONS Blacks in comparison with whites had lipid concentrations that are associated with a lower risk of atherosclerotic cardiovascular disease. The mixed racial group had lipid concentrations closer to the white grouping.
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Affiliation(s)
- Raul D Santos
- Heart Institute (InCor) University of Sao Paulo Medical School Hospital, Sao Paulo, Brazil; Center for Clinical and Epidemiological Research, University of Sao Paulo, Brazil
| | - Isabela M Bensenor
- Center for Clinical and Epidemiological Research, University of Sao Paulo, Brazil
| | - Alexandre C Pereira
- Heart Institute (InCor) University of Sao Paulo Medical School Hospital, Sao Paulo, Brazil; Center for Clinical and Epidemiological Research, University of Sao Paulo, Brazil
| | - Paulo A Lotufo
- Center for Clinical and Epidemiological Research, University of Sao Paulo, Brazil.
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Wall-Medrano A, Ramos-Jiménez A, Hernandez-Torres RP, Villalobos-Molina R, Tapia-Pancardo DC, Jiménez-Flores JR, Méndez-Cruz AR, Murguía-Romero M, Gallardo-Ortíz IA, Urquídez-Romero R. Cardiometabolic risk in young adults from northern Mexico: Revisiting body mass index and waist-circumference as predictors. BMC Public Health 2016; 16:236. [PMID: 26956639 PMCID: PMC4782332 DOI: 10.1186/s12889-016-2896-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Accepted: 02/19/2016] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND A body mass index (BMI) ≥30 kg/m(2) and a waist circumference (WC) ≥80 cm in women (WCF) or ≥90 cm in men (WCM) are reference cardiometabolic risk markers (CMM) for Mexicans adults. However, their reliability to predict other CMM (index tests) in young Mexicans has not been studied in depth. METHODS A cross-sectional descriptive study evaluating several anthropometric, physiological and biochemical CMM from 295 young Mexicans was performed. Sensitivity (Se), specificity (Sp) and Youden's index (J) of reference BMI/WC cutoffs toward other CMM (n = 14) were obtained and their most reliable cutoffs were further calculated at Jmax. RESULTS Prevalence, incidence and magnitude of most CMM increased along the BMI range (p < 0.01). BMI explained 81 % of WC's variance [Se (97 %), Sp (71 %), J (68 %), Jmax (86 %), BMI = 30 kg/m(2)] and 4-50 % of other CMM. The five most prevalent (≥71 %) CMM in obese subjects were high WC, low HDL-C, and three insulin-related CMM [Fasting insulin, HOMA-IR, and QUICKI]. For a BMI = 30 kg/m(2), J ranged from 16 % (HDL-C/LDL-C) to 68 % (WC), being moderately reliable (Jmax = 61-67) to predict high uric acid (UA), metabolic syndrome (MetS) and the hypertriglyceridemic-waist phenotype (HTGW). Corrected WCM/WCF were moderate-highly reliable (Jmax = 66-90) to predict HTGW, MetS, fasting glucose and UA. Most CMM were moderate-highly predicted at 27 ± 3 kg/m(2) (CI 95 %, 25-28), 85 ± 5 cm (CI 95 %, 82-88) and 81 ± 6cm (CI 95 %, 75-87), for BMI, WCM and WCF, respectively. CONCLUSION BMI and WC are good predictors of several CMM in the studied population, although at different cutoffs than current reference values.
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Affiliation(s)
- Abraham Wall-Medrano
- Instituto de Ciencias Biomédicas, Universidad Autónoma de Ciudad Juárez, Anillo Envolvente del Pronaf y Estocolmo, Ciudad Juárez, 32300, Chihuahua, México.
| | - Arnulfo Ramos-Jiménez
- Instituto de Ciencias Biomédicas, Universidad Autónoma de Ciudad Juárez, Anillo Envolvente del Pronaf y Estocolmo, Ciudad Juárez, 32300, Chihuahua, México.
| | - Rosa P Hernandez-Torres
- Facultad de Ciencias de la Cultura Física, Universidad Autónoma de Chihuahua, Chihuahua, México.
| | - Rafael Villalobos-Molina
- Unidad de Biomedicina, Universidad Nacional Autónoma de México, Tlalnepantla, México.
- Laboratorio Nacional en Salud: Diagnóstico Molecular y Efecto Ambiental en Enfermedades Crónico-Degenerativas, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla, México.
| | | | - J Rafael Jiménez-Flores
- Unidad de Biomedicina, Universidad Nacional Autónoma de México, Tlalnepantla, México.
- Laboratorio Nacional en Salud: Diagnóstico Molecular y Efecto Ambiental en Enfermedades Crónico-Degenerativas, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla, México.
| | - A René Méndez-Cruz
- Unidad de Biomedicina, Universidad Nacional Autónoma de México, Tlalnepantla, México.
- Laboratorio Nacional en Salud: Diagnóstico Molecular y Efecto Ambiental en Enfermedades Crónico-Degenerativas, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla, México.
| | - Miguel Murguía-Romero
- Unidad de Biomedicina, Universidad Nacional Autónoma de México, Tlalnepantla, México.
- Laboratorio Nacional en Salud: Diagnóstico Molecular y Efecto Ambiental en Enfermedades Crónico-Degenerativas, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla, México.
| | | | - René Urquídez-Romero
- Instituto de Ciencias Biomédicas, Universidad Autónoma de Ciudad Juárez, Anillo Envolvente del Pronaf y Estocolmo, Ciudad Juárez, 32300, Chihuahua, México.
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Eastwood SV, Tillin T, Sattar N, Forouhi NG, Hughes AD, Chaturvedi N. Associations Between Prediabetes, by Three Different Diagnostic Criteria, and Incident CVD Differ in South Asians and Europeans. Diabetes Care 2015; 38:2325-32. [PMID: 26486189 PMCID: PMC4868252 DOI: 10.2337/dc15-1078] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2015] [Accepted: 09/21/2015] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We examined longitudinal associations between prediabetes and cardiovascular disease (CVD) (coronary heart disease [CHD] and stroke) in Europeans and South Asians. RESEARCH DESIGN AND METHODS This was a U.K. cohort study of 1,336 Europeans and 1,139 South Asians, aged 40-69 years at baseline (1988-1991). Assessment included blood pressure, blood tests, anthropometry, and questionnaires. Prediabetes was determined by OGTT or HbA1c, using either International Expert Committee (IEC) (HbA1c 6.0-6.5% [42-48 mmol/mol]) or American Diabetes Association (ADA) (HbA1c 5.7-6.5% [39-48 mmol/mol]) cut points. Incident CHD and stroke were established at 20 years from death certification, hospital admission, primary care record review, and participant report. RESULTS Compared with normoglycemic individuals, IEC-defined prediabetes was related to both CHD and CVD risk in Europeans but not South Asians (subhazard ratio for CHD 1.68 [95% CI 1.19, 2.38] vs. 1.00 [0.75, 1.33], ethnicity interaction P = 0.008, and for CVD 1.49 [1.08, 2.07] vs. 1.03 [0.78, 1.36], ethnicity interaction P = 0.04). Conversely, IEC-defined prediabetes was associated with stroke risk in South Asians but not Europeans (1.73 [1.03, 2.90] vs. 0.85 [0.44, 1.64], ethnicity interaction P = 0.11). Risks were adjusted for age, sex, smoking, total-to-HDL cholesterol ratio, waist-to-hip ratio, systolic blood pressure, and antihypertensive use. Associations were weaker for OGTT or ADA-defined prediabetes. Conversion from prediabetes to diabetes was greater in South Asians, but accounting for time to conversion did not account for these ethnic differences. CONCLUSIONS Associations between prediabetes and CVD differed by prediabetes diagnostic criterion, type of CVD, and ethnicity, with associations being present for overall CVD in Europeans but not South Asians. Substantiation of these findings and investigation of potential explanations are required.
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Affiliation(s)
- Sophie V Eastwood
- Institute of Cardiovascular Science, University College London, London, U.K.
| | - Therese Tillin
- Institute of Cardiovascular Science, University College London, London, U.K
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K
| | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, U.K
| | - Alun D Hughes
- Institute of Cardiovascular Science, University College London, London, U.K
| | - Nish Chaturvedi
- Institute of Cardiovascular Science, University College London, London, U.K
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