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Paing PY, Littman AJ, Reese JA, Sitlani CM, Umans JG, Cole SA, Zhang Y, Ali T, Fretts AM. Association of Achievement of the American Heart Association's Life's Essential 8 Goals With Incident Cardiovascular Diseases in the SHFS. J Am Heart Assoc 2024; 13:e032918. [PMID: 38456410 DOI: 10.1161/jaha.123.032918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/02/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Cardiovascular disease (CVD) is a leading cause of morbidity and mortality in American Indian people. In 2022, the American Heart Association developed the Life's Essential 8 goals to promote cardiovascular health (CVH) for Americans, composed of diet, physical activity, nicotine exposure, sleep, body mass index, blood lipids, blood pressure, and blood glucose. We examined whether achievement of Life's Essential 8 goals was associated with incident CVD among SHFS (Strong Heart Family Study) participants. METHODS AND RESULTS A total of 2139 SHFS participants without CVD at baseline were included in analyses. We created a composite CVH score based on achievement of Life's Essential 8 goals, excluding sleep. Scores of 0 to 49 represented low CVH, 50 to 69 represented moderate CVH, and 70 to 100 represented high CVH. Incident CVD was defined as incident myocardial infarction, coronary heart disease, congestive heart failure, or stroke. Cox proportional hazard models were used to examine the relationship of CVH and incident CVD. The incidence rate of CVD at the 20-year follow-up was 7.43 per 1000 person-years. Compared with participants with low CVH, participants with moderate and high CVH had a lower risk of incident CVD; the hazard ratios and 95% CIs for incident CVD for moderate and high CVH were 0.52 (95% CI, 0.40-0.68) and 0.25 (95% CI, 0.14-0.44), respectively, after adjustment for age, sex, education, and study site. CONCLUSIONS Better CVH was associated with lower CVD risk which highlights the need for comprehensive public health interventions targeting CVH promotion to reduce CVD risk in American Indian communities.
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Affiliation(s)
| | | | - Jessica A Reese
- University of Oklahoma Health Sciences Center Oklahoma City OK
| | | | | | | | - Ying Zhang
- University of Oklahoma Health Sciences Center Oklahoma City OK
| | - Tauqeer Ali
- University of Oklahoma Health Sciences Center Oklahoma City OK
| | - Amanda M Fretts
- Department of Epidemiology University of Washington Seattle WA
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Reese JA, Roman MJ, Deen JF, Ali T, Cole SA, Devereux RB, Fretts AM, Howard WJ, Lee ET, Malloy K, Umans JG, Zhang Y. Dyslipidemia in American Indian Adolescents and Young Adults: Strong Heart Family Study. J Am Heart Assoc 2024; 13:e031741. [PMID: 38445515 DOI: 10.1161/jaha.123.031741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/27/2023] [Indexed: 03/07/2024]
Abstract
BACKGROUND Although many studies on the association between dyslipidemia and cardiovascular disease (CVD) exist in older adults, data on the association among adolescents and young adults living with disproportionate burden of cardiometabolic disorders are scarce. METHODS AND RESULTS The SHFS (Strong Heart Family Study) is a multicenter, family-based, prospective cohort study of CVD in an American Indian populations, including 12 communities in central Arizona, southwestern Oklahoma, and the Dakotas. We evaluated SHFS participants, who were 15 to 39 years old at the baseline examination in 2001 to 2003 (n=1440). Lipids were measured after a 12-hour fast. We used carotid ultrasounds to detect plaque at baseline and follow-up in 2006 to 2009 (median follow-up=5.5 years). We identified incident CVD events through 2020 with a median follow-up of 18.5 years. We used shared frailty proportional hazards models to assess the association between dyslipidemia and subclinical or clinical CVD, while controlling for covariates. Baseline dyslipidemia prevalence was 55.2%, 73.6%, and 78.0% for participants 15 to 19, 20 to 29, and 30 to 39 years old, respectively. Approximately 2.8% had low-density lipoprotein cholesterol ≥160 mg/dL, which is higher than the recommended threshold for lifestyle or medical interventions in young adults of 20 to 39 years old. During follow-up, 9.9% had incident plaque (109/1104 plaque-free participants with baseline and follow-up ultrasounds), 11.0% had plaque progression (128/1165 with both baseline and follow-up ultrasounds), and 9% had incident CVD (127/1416 CVD-free participants at baseline). Plaque incidence and progression were higher in participants with total cholesterol ≥200 mg/dL, low-density lipoprotein cholesterol ≥160 mg/dL, or non-high-density lipoprotein cholesterol ≥130 mg/dL, while controlling for covariates. CVD risk was independently associated with low-density lipoprotein cholesterol ≥160 mg/dL. CONCLUSIONS Dyslipidemia is a modifiable risk factor that is associated with both subclinical and clinical CVD, even among the younger American Indian population who have unexpectedly high rates of significant CVD events. Therefore, this population is likely to benefit from a variety of evidence-based interventions including screening, educational, lifestyle, and guideline-directed medical therapy at an early age.
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Affiliation(s)
- Jessica A Reese
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health University of Oklahoma Health Sciences Center Oklahoma City OK USA
| | | | - Jason F Deen
- Departments of Pediatrics and Medicine University of Washington Seattle WA USA
| | - Tauqeer Ali
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health University of Oklahoma Health Sciences Center Oklahoma City OK USA
| | - Shelley A Cole
- Population Health Texas Biomedical Research Institute San Antonio TX USA
| | | | - Amanda M Fretts
- Department of Epidemiology University of Washington Seattle WA USA
| | - Wm James Howard
- Georgetown-Howard Universities Center for Clinical and Translational Science Washington DC USA
| | - Elisa T Lee
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health University of Oklahoma Health Sciences Center Oklahoma City OK USA
| | - Kimberly Malloy
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health University of Oklahoma Health Sciences Center Oklahoma City OK USA
| | - Jason G Umans
- MedStar Health Research Institute Hyattsville MD USA
- Georgetown-Howard Universities Center for Clinical and Translational Science Washington DC USA
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health University of Oklahoma Health Sciences Center Oklahoma City OK USA
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Wen X, Fretts AM, Miao G, Malloy KM, Zhang Y, Umans JG, Cole SA, Best LG, Fiehn O, Zhao J. Plasma lipidomic markers of diet quality are associated with incident coronary heart disease in American Indian adults: the Strong Heart Family Study. Am J Clin Nutr 2024; 119:748-755. [PMID: 38160800 DOI: 10.1016/j.ajcnut.2023.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/15/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Identifying lipidomic markers of diet quality is needed to inform the development of biomarkers of diet, and to understand the mechanisms driving the diet- coronary heart disease (CHD) association. OBJECTIVES This study aimed to identify lipidomic markers of diet quality and examine whether these lipids are associated with incident CHD. METHODS Using liquid chromatography-mass spectrometry, we measured 1542 lipid species from 1694 American Indian adults (aged 18-75 years, 62% female) in the Strong Heart Family Study. Participants were followed up for development of CHD through 2020. Information on the past year diet was collected using the Block Food Frequency Questionnaire, and diet quality was assessed using the Alternative Healthy Eating Index-2010 (AHEI). Mixed-effects linear regression was used to identify individual lipids cross-sectionally associated with AHEI. In prospective analysis, Cox frailty model was used to estimate the hazard ratio (HR) of each AHEI-related lipid for incident CHD. All models were adjusted for age, sex, center, education, body mass index, smoking, alcohol drinking, level of physical activity, energy intake, diabetes, hypertension, and use of lipid-lowering drugs. Multiple testing was controlled at a false discovery rate of <0.05. RESULTS Among 1542 lipid species measured, 71 lipid species (23 known), including acylcarnitine, cholesterol esters, glycerophospholipids, sphingomyelins and triacylglycerols, were associated with AHEI. Most of the identified lipids were associated with consumption of ω-3 (n-3) fatty acids. In total, 147 participants developed CHD during a mean follow-up of 17.8 years. Among the diet-related lipids, 10 lipids [5 known: cholesterol ester (CE)(22:5)B, phosphatidylcholine (PC)(p-14:0/22:1)/PC(o-14:0/22:1), PC(p-38:3)/PC(o-38:4)B, phosphatidylethanolamine (PE)(p-18:0/20:4)/PE(o-18:0/20:4), and sphingomyelin (d36:2)A] were associated with incident CHD. On average, each standard deviation increase in the baseline level of these 5 lipids was associated with 17%-23% increased risk of CHD (from HR: 1.17; 95% CI: 1, 1.36; to HR: 1.23; 95% CI: 1.05, 1.43). CONCLUSIONS In this study, lipidomic markers of diet quality in American Indian adults are found. Some diet-related lipids are associated with risk of CHD beyond established risk factors.
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Affiliation(s)
- Xiaoxiao Wen
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, United States
| | - Guanhong Miao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States
| | - Kimberly M Malloy
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Jason G Umans
- Biomarker, Biochemistry, and Biorepository Core, MedStar Health Research Institute, Hyattsville, MD, United States; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, United States
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - Lyle G Best
- Missouri Breaks Industries Research, Timber Lake, SD, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, Davis, CA, United States
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States.
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Miao G, Pechlaner R, Fiehn O, Malloy KM, Zhang Y, Umans JG, Mayr M, Willeit J, Kiechl S, Zhao J. Longitudinal Lipidomic Signature of Coronary Heart Disease in American Indian People. J Am Heart Assoc 2024; 13:e031825. [PMID: 38293910 DOI: 10.1161/jaha.123.031825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/14/2023] [Indexed: 02/01/2024]
Abstract
BACKGROUND Dyslipidemia is an independent risk factor for coronary heart disease (CHD). Standard lipid panel cannot capture the complexity of the blood lipidome (ie, all molecular lipids in the blood). To date, very few large-scale epidemiological studies have assessed the full spectrum of the blood lipidome on risk of CHD, especially in a longitudinal setting. METHODS AND RESULTS Using an untargeted liquid chromatography-mass spectrometry, we repeatedly measured 1542 lipid species from 1835 unique American Indian participants who attended 2 clinical visits (≈5.5 years apart) and followed up to 17.8 years in the Strong Heart Family Study (SHFS). We first identified baseline lipid species associated with risk of CHD, followed by replication in a European population. The model adjusted for age, sex, body mass index, smoking, hypertension, diabetes, low-density lipoprotein cholesterol, estimated glomerular filtration rate, education, and physical activity at baseline. We then examined the longitudinal association between changes in lipid species and changes in cardiovascular risk factors during follow-up. Multiple testing was controlled by the false discovery rate. We found that baseline levels of multiple lipid species (eg, phosphatidylcholines, phosphatidylethanolamines, and ceramides) were associated with the risk of CHD and improved the prediction accuracy over conventional risk factors in American Indian people. Some identified lipids in American Indian people were replicated in European people. Longitudinal changes in multiple lipid species (eg, acylcarnitines, phosphatidylcholines, and triacylglycerols) were associated with changes in cardiovascular risk factors. CONCLUSIONS Baseline plasma lipids and their longitudinal changes over time are associated with risk of CHD. These findings provide novel insights into the role of dyslipidemia in CHD.
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Affiliation(s)
- Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine University of Florida Gainesville FL
- Center for Genetic Epidemiology and Bioinformatics University of Florida Gainesville FL
| | - Raimund Pechlaner
- Department of Neurology Medical University Innsbruck Innsbruck Austria
| | - Oliver Fiehn
- West Coast Metabolomics Center University of California Davis CA
| | - Kimberly M Malloy
- Department of Biostatistics and Epidemiology University of Oklahoma Health Sciences Center Oklahoma City OK
| | - Ying Zhang
- Department of Biostatistics and Epidemiology University of Oklahoma Health Sciences Center Oklahoma City OK
| | | | - Manuel Mayr
- National Heart & Lung Institute Imperial College London UK
| | - Johann Willeit
- Department of Neurology Medical University Innsbruck Innsbruck Austria
| | - Stefan Kiechl
- Department of Neurology Medical University Innsbruck Innsbruck Austria
- Research Centre on Vascular Ageing and Stroke Innsbruck Austria
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine University of Florida Gainesville FL
- Center for Genetic Epidemiology and Bioinformatics University of Florida Gainesville FL
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Henderson A, Rosenman R, Fyfe-Johnson AL, Taniguchi T, Standridge J, Shackleford T, Muller CJ, Umans JG, Jernigan VBB. The Cost-Efficacy of a Healthy Food Box for Managing Hypertension Within a Native American Population: The Chickasaw Healthy Eating Environment Research Study. Res Sq 2024:rs.3.rs-3901299. [PMID: 38352591 PMCID: PMC10862957 DOI: 10.21203/rs.3.rs-3901299/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Background Dietary interventions are used for the treatment of hypertension. We evaluated the cost-efficacy of delivering boxes of healthy, culturally tailored foods and checks that can only be spent on produce in a Native American population. Methods We conducted a group randomized controlled trial from 2018-2020 with N = 2 treatment counties and N = 2 control counties and a total of N = 160 Native American adults with baseline stage 1 or stage 2 hypertension. Participants in the intervention group received monthly boxes of food that adheres to the Dietary Approaches to Stop Hypertension diet as well as checks that could only be spent on produce for 6 months. We measured blood pressure and quality of life at baseline and at a 6-month follow-up in both intervention and control groups. We used ordered logistic regression to estimate the effect of treatment on probability of blood pressure improvements. We then conducted a cost-efficacy analysis. Results We found that treatment was effective in women with stage 1 hypertension at baseline. Based on this finding, we also estimate that this intervention satisfies normative cost-effectiveness thresholds, even when lifetime treatment is needed to preserve the impact, so long as treatment is only continued in those who respond to treatment. Conclusions Direct delivery of healthy foods and checks that can only be spent on produce are a potentially cost-effective intervention for the management of hypertension among Native American women with stage 1 hypertension. Further research is needed to understand why we found an impact only for this group.
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Lieberman‐Cribbin W, Li Z, Lewin M, Ruiz P, Jarrett JM, Cole SA, Kupsco A, O'Leary M, Pichler G, Shimbo D, Devereux RB, Umans JG, Navas‐Acien A, Nigra AE. The Contribution of Declines in Blood Lead Levels to Reductions in Blood Pressure Levels: Longitudinal Evidence in the Strong Heart Family Study. J Am Heart Assoc 2024; 13:e031256. [PMID: 38205795 PMCID: PMC10926826 DOI: 10.1161/jaha.123.031256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 11/21/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND Chronic lead exposure is associated with both subclinical and clinical cardiovascular disease. We evaluated whether declines in blood lead were associated with changes in systolic and diastolic blood pressure in adult American Indian participants from the SHFS (Strong Heart Family Study). METHODS AND RESULTS Lead in whole blood was measured in 285 SHFS participants in 1997 to 1999 and 2006 to 2009. Blood pressure and measures of cardiac geometry and function were obtained in 2001 to 2003 and 2006 to 2009. We used generalized estimating equations to evaluate the association of declines in blood lead with changes in blood pressure; cardiac function and geometry measures were considered secondary. Mean blood lead was 2.04 μg/dL at baseline. After ≈10 years, mean decline in blood lead was 0.67 μg/dL. In fully adjusted models, the mean difference in systolic blood pressure comparing the highest to lowest tertile of decline (>0.91 versus <0.27 μg/dL) in blood lead was -7.08 mm Hg (95% CI, -13.16 to -1.00). A significant nonlinear association between declines in blood lead and declines in systolic blood pressure was detected, with significant linear associations where blood lead decline was 0.1 μg/dL or higher. Declines in blood lead were nonsignificantly associated with declines in diastolic blood pressure and significantly associated with declines in interventricular septum thickness. CONCLUSIONS Declines in blood lead levels in American Indian adults, even when small (0.1-1.0 μg/dL), were associated with reductions in systolic blood pressure. These findings suggest the need to further study the cardiovascular impacts of reducing lead exposures and the importance of lead exposure prevention.
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Affiliation(s)
- Wil Lieberman‐Cribbin
- Department of Environmental Health SciencesColumbia University Mailman School of Public HealthNew YorkNYUSA
| | - Zheng Li
- Office of Capacity Development and Applied Prevention Science, Agency for Toxic Substances and Disease RegistryAtlantaGAUSA
| | - Michael Lewin
- Office of Community Health and Hazard Assessment, Agency for Toxic Substances and Disease RegistryAtlantaGAUSA
| | - Patricia Ruiz
- Office of Innovation and Analytics, Agency for Toxic Substances and Disease RegistryAtlantaGAUSA
| | - Jeffery M. Jarrett
- Division for Laboratory SciencesCenters for Disease Control and PreventionAtlantaGAUSA
| | - Shelley A. Cole
- Population Health ProgramTexas Biomedical Research InstituteSan AntonioTXUSA
| | - Allison Kupsco
- Department of Environmental Health SciencesColumbia University Mailman School of Public HealthNew YorkNYUSA
| | - Marcia O'Leary
- Missouri Breaks Research Industries Research, Inc.Eagle ButteSDUSA
| | - Gernot Pichler
- Department of CardiologyKarl Landsteiner Institute for Cardiovascular and Critical Care Research, Clinic FloridsdorfViennaAustria
| | - Daichi Shimbo
- Division of CardiologyColumbia University Irving Medical CenterNew YorkNYUSA
| | | | - Jason G. Umans
- MedStar Health Research InstituteHyattsvilleMDUSA
- Georgetown‐Howard Universities Center for Clinical and Translational ScienceWashingtonDCUSA
| | - Ana Navas‐Acien
- Department of Environmental Health SciencesColumbia University Mailman School of Public HealthNew YorkNYUSA
| | - Anne E. Nigra
- Department of Environmental Health SciencesColumbia University Mailman School of Public HealthNew YorkNYUSA
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7
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Hughes O, Bentley AR, Breeze CE, Aguet F, Xu X, Nadkarni G, Sun Q, Lin BM, Gilliland T, Meyer MC, Du J, Raffield LM, Kramer H, Morton RW, Gouveia MH, Atkinson EG, Valladares-Salgado A, Wacher-Rodarte N, Dueker ND, Guo X, Hai Y, Adeyemo A, Best LG, Cai J, Chen G, Chong M, Doumatey A, Eales J, Goodarzi MO, Ipp E, Irvin MR, Jiang M, Jones AC, Kooperberg C, Krieger JE, Lange EM, Lanktree MB, Lash JP, Lotufo PA, Loos RJF, Ha My VT, Peralta-Romero J, Qi L, Raffel LJ, Rich SS, Rodriquez EJ, Tarazona-Santos E, Taylor KD, Umans JG, Wen J, Young BA, Yu Z, Zhang Y, Ida Chen YD, Rundek T, Rotter JI, Cruz M, Fornage M, Lima-Costa MF, Pereira AC, Paré G, Natarajan P, Cole SA, Carson AP, Lange LA, Li Y, Perez-Stable EJ, Do R, Charchar FJ, Tomaszewski M, Mychaleckyj JC, Rotimi C, Morris AP, Franceschini N. Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas. Cell Genom 2024; 4:100468. [PMID: 38190104 PMCID: PMC10794846 DOI: 10.1016/j.xgen.2023.100468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 08/31/2023] [Accepted: 11/28/2023] [Indexed: 01/09/2024]
Abstract
Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.
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Affiliation(s)
- Odessica Hughes
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Charles E Breeze
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department Health and Human Services, Bethesda, MD, USA; UCL Cancer Institute, University College London, London, UK
| | - Francois Aguet
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine, and Health, The University of Manchester, Manchester, UK
| | - Girish Nadkarni
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bridget M Lin
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Thomas Gilliland
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Mariah C Meyer
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jiawen Du
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Holly Kramer
- Division of Nephrology and Hypertension, Loyola University Chicago, Maywood, IL, USA
| | - Robert W Morton
- Population Health Research Institute, Hamilton, ON, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Adan Valladares-Salgado
- Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Niels Wacher-Rodarte
- Unidad de Investigación Médica en Epidemiologia Clinica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Nicole D Dueker
- John P Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Yang Hai
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lyle G Best
- Missouri Breaks Industries Research Inc., Eagle Butte, SD, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael Chong
- Population Health Research Institute, Hamilton, ON, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Ayo Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - James Eales
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine, and Health, The University of Manchester, Manchester, UK
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Eli Ipp
- Division of Endocrinology and Metabolism, Department of Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marguerite Ryan Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Minzhi Jiang
- Department of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alana C Jones
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jose E Krieger
- Laboratório de Genética e Cardiologia Molecular do Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Ethan M Lange
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Matthew B Lanktree
- Division of Nephrology, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - James P Lash
- Division of Nephrology, Department of Medicine, University of Illinois, Chicago, IL, USA
| | - Paulo A Lotufo
- Center for Clinical and Epidemiological Research, Hospital Universitário, Universidade de São Paulo (USP), São Paulo, Brazil
| | - Ruth J F Loos
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Vy Thi Ha My
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jesús Peralta-Romero
- Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Lihong Qi
- Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA, USA
| | - Leslie J Raffel
- Department of Pediatrics, Genetic and Genomic Medicine, University of California, Irvine, Irvine, CA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Erik J Rodriquez
- Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Eduardo Tarazona-Santos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville MD and Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bessie A Young
- University of Washington School of Medicine, Seattle, WA, USA; Office of Healthcare Equity, UW Justice, Equity, Diversity, and Inclusion Center for Transformational Research (UW JEDI-CTR), University of Washington, Seattle, WA, USA; Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA, USA; Kidney Research Institute, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Zhi Yu
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, The University of Oklahoma Health Sciences Center, Oklahoma, OK, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Tanja Rundek
- Department of Neurology, Epidemiology and Public Health, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Miguel Cruz
- Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, Houston, TX, USA
| | | | - Alexandre C Pereira
- Laboratório de Genética e Cardiologia Molecular do Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Aging Division, Brigham Women's Hospital, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Guillaume Paré
- Population Health Research Institute, Hamilton, ON, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Shelley A Cole
- Texas Biomedical Research Institute, San Antonio, TX, USA
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Leslie A Lange
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Eliseo J Perez-Stable
- National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Ron Do
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Fadi J Charchar
- School of Science, Psychology and Sport, Federation University, Ballarat, VIC, Australia; Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; Department of Physiology, University of Melbourne, Melbourne, VIC, Australia
| | - Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine, and Health, The University of Manchester, Manchester, UK; Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Josyf C Mychaleckyj
- Department of Public Health Sciences, School of Medicine, University of California Davis, Davis, CA, USA
| | - Charles Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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8
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Rao ND, Lemaitre RN, Sitlani CM, Umans JG, Haack K, Handeland V, Navas-Acien A, Cole SA, Best LG, Fretts AM. Dietary magnesium, C-reactive protein and interleukin-6: The Strong Heart Family Study. PLoS One 2023; 18:e0296238. [PMID: 38128021 PMCID: PMC10734955 DOI: 10.1371/journal.pone.0296238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 11/13/2023] [Indexed: 12/23/2023] Open
Abstract
OBJECTIVES To examine the associations of dietary Mg intake with inflammatory biomarkers (C-reactive protein (CRP) and interleukin 6 (IL-6)), and the interaction of dietary Mg intake with single nucleotide polymorphism (SNP) rs3740393, a SNP related to Mg metabolism and transport, on CRP and IL-6 among American Indians (AIs). METHODS This cross-sectional study included AI participants (n = 1,924) from the Strong Heart Family Study (SHFS). Mg intake from foods and dietary supplements was ascertained using a 119-item Block food frequency questionnaire, CRP and IL-6 were measured from blood, and SNP rs3740393 was genotyped using MetaboChip. Generalized estimating equations were used to examine associations of Mg intake, and the interaction between rs3740393 and dietary Mg, with CRP and IL-6. RESULTS Reported Mg intake was not associated with CRP or IL-6, irrespective of genotype. A significant interaction (p-interaction = 0.018) was observed between Mg intake and rs3740393 on IL-6. Among participants with the C/C genotype, for every 1 SD higher in log-Mg, log-IL-6 was 0.04 (95% CI: -0.10 to 0.17) pg/mL higher. Among participants with the C/G genotype, for every 1 SD higher in log-Mg, log-IL-6 was 0.08 (95% CI: -0.21 to 0.05) pg/mL lower, and among participants with the G/G genotype, for every 1 SD higher in log-Mg, log-IL-6 was 0.19 (95% CI: -0.38 to -0.01) pg/mL lower. CONCLUSIONS Mg intake may be associated with lower IL-6 with increasing dosage of the G allele at rs3740393. Future research is necessary to replicate this finding and examine other Mg-related genes that influence associations of Mg intake with inflammation.
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Affiliation(s)
- Nandana D. Rao
- Institute of Public Health Genetics, University of Washington, Seattle, Washington, United States of America
| | - Rozenn N. Lemaitre
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Cardiovascular Research Health Unit, University of Washington, Seattle, Washington, United States of America
| | - Colleen M. Sitlani
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Cardiovascular Research Health Unit, University of Washington, Seattle, Washington, United States of America
| | - Jason G. Umans
- MedStar Health Research Institute, Hyattsville, Maryland, United States of America
- Department of Medicine, Georgetown University, Washington, DC, United States of America
| | - Karin Haack
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | | | - Ana Navas-Acien
- Department of Environmental Health Science, Columbia University, New York, New York, United States of America
| | - Shelley A. Cole
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Lyle G. Best
- Missouri Breaks Industries Research Inc, Eagle Butte, South Dakota, United States of America
| | - Amanda M. Fretts
- Institute of Public Health Genetics, University of Washington, Seattle, Washington, United States of America
- Cardiovascular Research Health Unit, University of Washington, Seattle, Washington, United States of America
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
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9
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Jiang EX, Domingo-Relloso A, Abuawad A, Haack K, Tellez-Plaza M, Fallin MD, Umans JG, Best LG, Zhang Y, Kupsco A, Belsky DW, Cole SA, Navas-Acien A. Arsenic Exposure and Epigenetic Aging: The Association with Cardiovascular Disease and All-Cause Mortality in the Strong Heart Study. Environ Health Perspect 2023; 131:127016. [PMID: 38133959 PMCID: PMC10743589 DOI: 10.1289/ehp11981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 12/24/2023]
Abstract
BACKGROUND Inorganic arsenic (As) may increase the risk of cardiovascular disease (CVD) and all-cause mortality through accelerated aging, which can be estimated using epigenetic-based measures. OBJECTIVES We evaluated three DNA methylation-based aging measures (PhenoAge, GrimAge, DunedinPACE) (epigenetic aging measures) as potential mediators of the previously reported association of As exposure with CVD incidence, CVD mortality, and all-cause mortality in the Strong Heart Study (SHS), an epidemiological cohort of American Indian adults. METHODS Blood DNA methylation and urinary As levels were measured in 2,323 SHS participants (41.5% men, mean age of 55 years old). PhenoAge and GrimAge values were calculated using a residual-based method. We tested the association of urinary As with epigenetic aging measures using linear regression, the association of epigenetic aging measures with the three health outcomes using additive hazards models, and the mediation of As-related CVD incidence, CVD mortality, and all-cause mortality by epigenetic aging measures using the product of coefficients method. RESULTS SHS participants with higher vs. lower urinary As levels had similar PhenoAge age, older GrimAge age, and faster DunedinPACE. An interquartile range increase in urinary As was associated with higher of PhenoAge age acceleration [mean difference ( 95 % confidence interval ) = 0.48 (0.17, 0.80) years], GrimAge age acceleration [0.80 (0.60, 1.00) years], and DunedinPACE [0.011 (0.005, 0.018)], after adjusting for age, sex, center location, genetic components, smoking status, and body mass index. Of the 347 incident CVD events per 100,000 person-years associated with a doubling in As exposure, 21.3% (9.1, 57.1) and 22.6% (9.5, 56.9), were attributable to differences in GrimAge and DunedinPACE, respectively. DISCUSSION Arsenic exposure was associated with older GrimAge and faster DunedinPACE measures of biological age. Furthermore, accelerated biological aging measured from DNA methylation accounted for a relevant fraction of As-associated risk for CVD, CVD mortality, and all-cause mortality in the SHS, supporting the role of As in accelerated aging. Research of the biological underpinnings can contribute to a better understanding of the role of aging in arsenic-related disease. https://doi.org/10.1289/EHP11981.
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Affiliation(s)
- Enoch X. Jiang
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain
- Department of Statistics and Operations Research, University of Valencia, Valencia, Spain
| | - Ahlam Abuawad
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain
| | - M. Danielle Fallin
- Department of Mental Health, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jason G. Umans
- MedStar Health Research Institute, Washington, DC, USA
- Center for Clinical and Translational Sciences, Georgetown/Howard Universities, Washington, DC, USA
| | - Lyle G. Best
- Missouri Breaks Industries Research, Eagle Butte, South Dakota, USA
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Allison Kupsco
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Daniel W. Belsky
- Department of Epidemiology, Columbia University, New York, USA
- Butler Columbia Aging Center, Columbia University, New York, USA
| | - Shelley A. Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
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10
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Li M, Do V, Brooks JL, Hilpert M, Goldsmith J, Chillrud SN, Ali T, Best LG, Yracheta J, Umans JG, van Donkelaar A, Martin RV, Navas-Acien A, Kioumourtzoglou MA. Fine particulate matter composition in American Indian vs. Non-American Indian communities. Environ Res 2023; 237:117091. [PMID: 37683786 PMCID: PMC10591960 DOI: 10.1016/j.envres.2023.117091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 09/04/2023] [Accepted: 09/05/2023] [Indexed: 09/10/2023]
Abstract
BACKGROUND Fine particulate matter (PM2.5) exposure is a known risk factor for numerous adverse health outcomes, with varying estimates of component-specific effects. Populations with compromised health conditions such as diabetes can be more sensitive to the health impacts of air pollution exposure. Recent trends in PM2.5 in primarily American Indian- (AI-) populated areas examined in previous work declined more gradually compared to the declines observed in the rest of the US. To further investigate components contributing to these findings, we compared trends in concentrations of six PM2.5 components in AI- vs. non-AI-populated counties over time (2000-2017) in the contiguous US. METHODS We implemented component-specific linear mixed models to estimate differences in annual county-level concentrations of sulfate, nitrate, ammonium, organic matter, black carbon, and mineral dust from well-validated surface PM2.5 models in AI- vs. non-AI-populated counties, using a multi-criteria approach to classify counties as AI- or non-AI-populated. Models adjusted for population density and median household income. We included interaction terms with calendar year to estimate whether concentration differences in AI- vs. non-AI-populated counties varied over time. RESULTS Our final analysis included 3108 counties, with 199 (6.4%) classified as AI-populated. On average across the study period, adjusted concentrations of all six PM2.5 components in AI-populated counties were significantly lower than in non-AI-populated counties. However, component-specific levels in AI- vs. non-AI-populated counties varied over time: sulfate and ammonium levels were significantly lower in AI- vs. non-AI-populated counties before 2011 but higher after 2011 and nitrate levels were consistently lower in AI-populated counties. CONCLUSIONS This study indicates time trend differences of specific components by AI-populated county type. Notably, decreases in sulfate and ammonium may contribute to steeper declines in total PM2.5 in non-AI vs. AI-populated counties. These findings provide potential directives for additional monitoring and regulations of key emissions sources impacting tribal lands.
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Affiliation(s)
- Maggie Li
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
| | - Vivian Do
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Jada L Brooks
- University of North Carolina School of Nursing, Chapel Hill, NC, USA
| | - Markus Hilpert
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Jeff Goldsmith
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Steven N Chillrud
- Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA
| | - Tauqeer Ali
- Department of Biostatistics and Epidemiology, Center for American Indian Health Research, Hudson College of Public Health, University of Oklahoma Health Sciences Center, OK, USA
| | - Lyle G Best
- Missouri Breaks Industries Research, Inc., Eagle Butte, SD, USA
| | | | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown/Howard Universities Center for Clinical and Translational Sciences, Washington, DC, USA
| | - Aaron van Donkelaar
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO, USA
| | - Randall V Martin
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
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11
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Wang K, Cunha GM, Hasenstab K, Henderson WC, Middleton MS, Cole SA, Umans JG, Ali T, Hsiao A, Sirlin CB. Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data. AJR Am J Roentgenol 2023; 221:620-631. [PMID: 37466189 DOI: 10.2214/ajr.23.29607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.
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Affiliation(s)
- Kang Wang
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
- Department of Radiology, Stanford University, 500 Pasteur Dr, Palo Alto, CA 94304
| | | | - Kyle Hasenstab
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA
| | - Walter C Henderson
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
| | - Michael S Middleton
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX
| | - Jason G Umans
- MedStar Health Research Institute, Field Studies Division, Hyattsville, MD
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Tauqeer Ali
- Department of Biostatistics and Epidemiology, Center for American Indian Health Research, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Albert Hsiao
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
| | - Claude B Sirlin
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
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12
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Miao G, Fiehn O, Chen M, Zhang Y, Umans JG, Lee ET, Howard BV, Roman MJ, Devereux RB, Zhao J. Longitudinal lipidomic signature of carotid atherosclerosis in American Indians: Findings from the Strong Heart Family Study. Atherosclerosis 2023; 382:117265. [PMID: 37722315 DOI: 10.1016/j.atherosclerosis.2023.117265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/20/2023]
Abstract
BACKGROUND AND AIMS Dyslipidemia is an independent risk factor for atherosclerosis and atherosclerotic cardiovascular disease (ASCVD). To date, a comprehensive assessment of individual lipid species associated with atherosclerosis is lacking in large-scale epidemiological studies, especially in a longitudinal setting. We investigated the association of circulating lipid species and its longitudinal changes with carotid atherosclerosis. METHODS Using liquid chromatograph-mass spectrometry, we repeatedly measured 1542 lipid species in 3687 plasma samples from 1918 unique American Indians attending two visits (mean ∼5 years apart) in the Strong Heart Family Study. Carotid atherosclerotic plaques were assessed by ultrasonography at each visit. We identified lipids associated with prevalence or progression of carotid plaques, adjusting age, sex, BMI, smoking, hypertension, diabetes, and eGFR. Then we examined whether longitudinal changes in lipids were associated with changes in cardiovascular risk factors. Multiple testing was controlled at false discovery rate (FDR) < 0.05. RESULTS Higher levels of sphingomyelins, ether-phosphatidylcholines, and triacylglycerols were significantly associated with prevalence or progression of carotid plaques (odds ratios ranged from 1.15 to 1.34). Longitudinal changes in multiple lipid species (e.g., acylcarnitines, phosphatidylcholines, triacylglycerols) were associated with changes in cardiometabolic traits (e.g., BMI, blood pressure, fasting glucose, eGFR). Network analysis identified differential lipid networks associated with plaque progression. CONCLUSIONS Baseline and longitudinal changes in multiple lipid species were significantly associated with carotid atherosclerosis and its progression in American Indians. Some plaque-related lipid species were also associated with risk for CVD events.
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Affiliation(s)
- Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Mingjing Chen
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Elisa T Lee
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Mary J Roman
- Weill Cornell Medical College, New York, NY, 10065, USA
| | | | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA.
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13
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Domingo-Relloso A, Joehanes R, Rodriguez-Hernandez Z, Lahousse L, Haack K, Fallin MD, Herreros-Martinez M, Umans JG, Best LG, Huan T, Liu C, Ma J, Yao C, Jerolon A, Bermudez JD, Cole SA, Rhoades DA, Levy D, Navas-Acien A, Tellez-Plaza M. Smoking, blood DNA methylation sites and lung cancer risk. Environ Pollut 2023; 334:122153. [PMID: 37442331 PMCID: PMC10528956 DOI: 10.1016/j.envpol.2023.122153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/07/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023]
Abstract
Altered DNA methylation (DNAm) might be a biological intermediary in the pathway from smoking to lung cancer. In this study, we investigated the contribution of differential blood DNAm to explain the association between smoking and lung cancer incidence. Blood DNAm was measured in 2321 Strong Heart Study (SHS) participants. Incident lung cancer was assessed as time to event diagnoses. We conducted mediation analysis, including validation with DNAm and paired gene expression data from the Framingham Heart Study (FHS). In the SHS, current versus never smoking and pack-years single-mediator models showed, respectively, 29 and 21 differentially methylated positions (DMPs) for lung cancer with statistically significant mediated effects (14 of 20 available, and five of 14 available, positions, replicated, respectively, in FHS). In FHS, replicated DMPs showed gene expression downregulation largely in trans, and were related to biological pathways in cancer. The multimediator model identified that DMPs annotated to the genes AHRR and IER3 jointly explained a substantial proportion of lung cancer. Thus, the association of smoking with lung cancer was partly explained by differences in baseline blood DNAm at few relevant sites. Experimental studies are needed to confirm the biological role of identified eQTMs and to evaluate potential implications for early detection and control of lung cancer.
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Affiliation(s)
- Arce Domingo-Relloso
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain; Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA; Department of Statistics and Operations Research, University of Valencia, Spain.
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, USA; Framingham Heart Study, Framingham, MA, USA
| | - Zulema Rodriguez-Hernandez
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Lies Lahousse
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - M Daniele Fallin
- Department of Mental Health, Johns Hopkins University, Baltimore, USA; Department of Epidemiology, Johns Hopkins University, Baltimore, USA
| | | | - Jason G Umans
- MedStar Health Research Institute, Washington DC, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington DC, USA
| | - Lyle G Best
- Missouri Breaks Industries and Research Inc., Eagle Butte, SD, USA
| | - Tianxiao Huan
- Framingham Heart Study, Framingham, MA, USA; University of Massachusetts Medical School, Worcester, MA, USA
| | - Chunyu Liu
- Framingham Heart Study, Framingham, MA, USA; Boston University School of Public Health, Boston, MA, USA
| | - Jiantao Ma
- Framingham Heart Study, Framingham, MA, USA; Tufts University Friedman School of Nutrition Science and Policy, Boston, MA, USA
| | - Chen Yao
- Framingham Heart Study, Framingham, MA, USA; Bristol Myers Squibb, Cambridge, MA, USA
| | - Allan Jerolon
- Université Paris Cité, CNRS, MAP5, F-75006, Paris, France
| | - Jose D Bermudez
- Department of Statistics and Operations Research, University of Valencia, Spain
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Dorothy A Rhoades
- Stephenson Cancer Center, University of Oklahoma Health Sciences Department of Medicine, Oklahoma City, OK, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, USA; Framingham Heart Study, Framingham, MA, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
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14
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Kaptoge S, Seshasai SRK, Sun L, Walker M, Bolton T, Spackman S, Ataklte F, Willeit P, Bell S, Burgess S, Pennells L, Altay S, Assmann G, Ben-Shlomo Y, Best LG, Björkelund C, Blazer DG, Brenner H, Brunner EJ, Dagenais GR, Cooper JA, Cooper C, Crespo CJ, Cushman M, D'Agostino RB, Daimon M, Daniels LB, Danker R, Davidson KW, de Jongh RT, Donfrancesco C, Ducimetiere P, Elders PJM, Engström G, Ford I, Gallacher I, Bakker SJL, Goldbourt U, de La Cámara G, Grimsgaard S, Gudnason V, Hansson PO, Imano H, Jukema JW, Kabrhel C, Kauhanen J, Kavousi M, Kiechl S, Knuiman MW, Kromhout D, Krumholz HM, Kuller LH, Laatikainen T, Lowler DA, Meyer HE, Mukamal K, Nietert PJ, Ninomiya T, Nitsch D, Nordestgaard BG, Palmieri L, Price JF, Ridker PM, Sun Q, Rosengren A, Roussel R, Sakurai M, Salomaa V, Schöttker B, Shaw JE, Strandberg TE, Sundström J, Tolonen H, Tverdal A, Verschuren WMM, Völzke H, Wagenknecht L, Wallace RB, Wannamethee SG, Wareham NJ, Wassertheil-Smoller S, Yamagishi K, Yeap BB, Harrison S, Inouye M, Griffin S, Butterworth AS, Wood AM, Thompson SG, Sattar N, Danesh J, Di Angelantonio E, Tipping RW, Russell S, Johansen M, Bancks MP, Mongraw-Chaffin M, Magliano D, Barr ELM, Zimmet PZ, Knuiman MW, Whincup PH, Willeit J, Willeit P, Leitner C, Lawlor DA, Ben-Shlomo Y, Elwood P, Sutherland SE, Hunt KJ, Cushman M, Selmer RM, Haheim LL, Ariansen I, Tybjaer-Hansen A, Frikkle-Schmidt R, Langsted A, Donfrancesco C, Lo Noce C, Balkau B, Bonnet F, Fumeron F, Pablos DL, Ferro CR, Morales TG, Mclachlan S, Guralnik J, Khaw KT, Brenner H, Holleczek B, Stocker H, Nissinen A, Palmieri L, Vartiainen E, Jousilahti P, Harald K, Massaro JM, Pencina M, Lyass A, Susa S, Oizumi T, Kayama T, Chetrit A, Roth J, Orenstein L, Welin L, Svärdsudd K, Lissner L, Hange D, Mehlig K, Salomaa V, Tilvis RS, Dennison E, Cooper C, Westbury L, Norman PE, Almeida OP, Hankey GJ, Hata J, Shibata M, Furuta Y, Bom MT, Rutters F, Muilwijk M, Kraft P, Lindstrom S, Turman C, Kiyama M, Kitamura A, Yamagishi K, Gerber Y, Laatikainen T, Salonen JT, van Schoor LN, van Zutphen EM, Verschuren WMM, Engström G, Melander O, Psaty BM, Blaha M, de Boer IH, Kronmal RA, Sattar N, Rosengren A, Nitsch D, Grandits G, Tverdal A, Shin HC, Albertorio JR, Gillum RF, Hu FB, Cooper JA, Humphries S, Hill- Briggs F, Vrany E, Butler M, Schwartz JE, Kiyama M, Kitamura A, Iso H, Amouyel P, Arveiler D, Ferrieres J, Gansevoort RT, de Boer R, Kieneker L, Crespo CJ, Assmann G, Trompet S, Kearney P, Cantin B, Després JP, Lamarche B, Laughlin G, McEvoy L, Aspelund T, Thorsson B, Sigurdsson G, Tilly M, Ikram MA, Dorr M, Schipf S, Völzke H, Fretts AM, Umans JG, Ali T, Shara N, Davey-Smith G, Can G, Yüksel H, Özkan U, Nakagawa H, Morikawa Y, Ishizaki M, Njølstad I, Wilsgaard T, Mathiesen E, Sundström J, Buring J, Cook N, Arndt V, Rothenbacher D, Manson J, Tinker L, Shipley M, Tabak AG, Kivimaki M, Packard C, Robertson M, Feskens E, Geleijnse M, Kromhout D. Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation. Lancet Diabetes Endocrinol 2023; 11:731-742. [PMID: 37708900 PMCID: PMC7615299 DOI: 10.1016/s2213-8587(23)00223-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 07/14/2023] [Accepted: 07/14/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy. METHODS For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961-2007, median latest follow-up years 1980-2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU. FINDINGS For participants with diabetes, we observed a linear dose-response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43-2·97) when diagnosed at 30-39 years, 2·26 (2·08-2·45) at 40-49 years, 1·84 (1·72-1·97) at 50-59 years, 1·57 (1·47-1·67) at 60-69 years, and 1·39 (1·29-1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier. INTERPRETATION Every decade of earlier diagnosis of diabetes was associated with about 3-4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes. FUNDING British Heart Foundation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.
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Lidgard B, Bansal N, Zelnick LR, Hoofnagle AN, Fretts AM, Longstreth WT, Shlipak MG, Siscovick DS, Umans JG, Lemaitre RN. Evaluation of plasma sphingolipids as mediators of the relationship between kidney disease and cardiovascular events. EBioMedicine 2023; 95:104765. [PMID: 37634384 PMCID: PMC10474367 DOI: 10.1016/j.ebiom.2023.104765] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 08/04/2023] [Accepted: 08/06/2023] [Indexed: 08/29/2023] Open
Abstract
BACKGROUND Sphingolipids are a family of circulating lipids with regulatory and signaling roles that are strongly associated with both eGFR and cardiovascular disease. Patients with chronic kidney disease (CKD) are at high risk for cardiovascular events, and have different plasma concentrations of certain plasma sphingolipids compared to patients with normal kidney function. We hypothesize that circulating sphingolipids partially mediate the associations between eGFR and cardiovascular events. METHODS We measured the circulating concentrations of 8 sphingolipids, including 4 ceramides and 4 sphingomyelins with the fatty acids 16:0, 20:0, 22:0, and 24:0, in plasma from 3,463 participants in a population-based cohort (Cardiovascular Health Study) without prevalent cardiovascular disease. We tested the adjusted mediation effects by these sphingolipids of the associations between eGFR and incident cardiovascular disease via quasi-Bayesian Monte Carlo method with 2,000 simulations, using a Bonferroni correction for significance. FINDINGS The mean (±SD) eGFR was 70 (±16) mL/min/1.73 m2; 62% of participants were women. Lower eGFR was associated with higher plasma ceramide-16:0 and sphingomyelin-16:0, and lower ceramides and sphingomyelins-20:0 and -22:0. Lower eGFR was associated with risk of incident heart failure and ischemic stroke, but not myocardial infarction. Five of eight sphingolipids partially mediated the association between eGFR and heart failure. The sphingolipids associated with the greatest proportion mediated were ceramide-16:0 (proportion mediated 13%, 95% CI 8-22%) and sphingomyelin-16:0 (proportion mediated 10%, 95% CI 5-17%). No sphingolipids mediated the association between eGFR and ischemic stroke. INTERPRETATION Plasma sphingolipids partially mediated the association between lower eGFR and incident heart failure. Altered sphingolipids metabolism may be a novel mechanism for heart failure in patients with CKD. FUNDING This study was supported by T32 DK007467 and a KidneyCure Ben J. Lipps Research Fellowship (Dr. Lidgard). Sphingolipid measurements were supported by R01 HL128575 (Dr. Lemaitre) and R01 HL111375 (Dr. Hoofnagle) from the National Heart, Lung, and Blood Institute (NHLBI).
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Affiliation(s)
- Benjamin Lidgard
- Department of Medicine, University of Washington, United States.
| | - Nisha Bansal
- Department of Medicine, University of Washington, United States
| | - Leila R Zelnick
- Department of Medicine, University of Washington, United States
| | | | - Amanda M Fretts
- Department of Medicine, University of Washington, United States
| | | | - Michael G Shlipak
- Kidney Health Research Collaborative, San Francisco Veterans Affairs Healthcare System and University of California San Francisco, United States
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16
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Chen M, Miao G, Zhang Y, Umans JG, Lee ET, Howard BV, Fiehn O, Zhao J. Longitudinal Lipidomic Profile of Hypertension in American Indians: Findings From the Strong Heart Family Study. Hypertension 2023; 80:1771-1783. [PMID: 37334699 PMCID: PMC10526703 DOI: 10.1161/hypertensionaha.123.21144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 06/06/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND Dyslipidemia is an important risk factor for hypertension and cardiovascular disease. Standard lipid panel cannot reflect the complexity of blood lipidome. The associations of individual lipid species with hypertension remain to be determined in large-scale epidemiological studies, especially in a longitudinal setting. METHODS Using liquid chromatography-mass spectrometry, we repeatedly measured 1542 lipid species in 3699 fasting plasma samples at 2 visits (1905 at baseline, 1794 at follow-up, ~5.5 years apart) from 1905 unique American Indians in the Strong Heart Family Study. We first identified baseline lipids associated with prevalent and incident hypertension, followed by replication of top hits in Europeans. We then conducted repeated measurement analysis to examine the associations of changes in lipid species with changes in systolic blood pressure, diastolic blood pressure, and mean arterial pressure. Network analysis was performed to identify lipid networks associated with the risk of hypertension. RESULTS Baseline levels of multiple lipid species, for example, glycerophospholipids, cholesterol esters, sphingomyelins, glycerolipids, and fatty acids, were significantly associated with both prevalent and incident hypertension in American Indians. Some lipids were confirmed in Europeans. Longitudinal changes in multiple lipid species, for example, acylcarnitines, phosphatidylcholines, fatty acids, and triacylglycerols, were significantly associated with changes in blood pressure measurements. Network analysis identified distinct lipidomic patterns associated with the risk of hypertension. CONCLUSIONS Baseline plasma lipid species and their longitudinal changes are significantly associated with hypertension development in American Indians. Our findings shed light on the role of dyslipidemia in hypertension and may offer potential opportunities for risk stratification and early prediction of hypertension.
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Affiliation(s)
- Mingjing Chen
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL
| | - Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Jason G. Umans
- MedStar Health Research Institute, Hyattsville, MD
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Elisa T. Lee
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Barbara V. Howard
- MedStar Health Research Institute, Hyattsville, MD
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, CA
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL
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17
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Mokiao RH, Fretts AM, Deen JF, Umans JG. Diet Quality and Kidney Outcomes in Adolescent and Adult American Indians: the Strong Heart Family Study. J Racial Ethn Health Disparities 2023:10.1007/s40615-023-01735-x. [PMID: 37526878 DOI: 10.1007/s40615-023-01735-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/17/2023] [Accepted: 07/21/2023] [Indexed: 08/02/2023]
Abstract
BACKGROUND The burden of kidney disease is exceedingly high among American Indians (AIs). We sought to examine the relationship of diet quality, a modifiable risk factor, and kidney outcomes in AI adolescents and adults, hypothesizing that healthier diets are associated with lower odds of incident albuminuria and eGFR decline. METHODS This is an analysis from the Strong Heart Family Study, a longitudinal study of cardiovascular disease and its risk factors among AIs from Arizona, North and South Dakota, and Oklahoma (n = 1720, mean age 39 + / - 16 years, 16% adolescents at baseline). Participants completed two exams (baseline: 2001-2003; follow-up: 2007-2009). The primary exposure was diet quality, expressed as the Alternative Healthy Eating Index 2010 (AHEI), on a 110-point scale (assessed using a 119-item Block food frequency questionnaire). The primary outcomes were as follows: 1) incident albuminuria (albumin to creatinine ratio 30 mg/g or greater); and 2) eGFR decline of 30% or greater. Generalized estimating equations were used to examine the association of AHEI (in quartiles) with outcomes. RESULTS Ten percent of participants (6% of adolescents) had incident albuminuria and 2% of participants (2% of adolescents) had eGFR decline. For those with normal fasting glucose levels, the odds ratio (OR) for incident albuminuria comparing extreme quartiles of diet quality (least healthy [reference] versus healthiest quartiles) was 0.48 (95% CI 0.28, 0.81) after adjustment for demographics and comorbidities. CONCLUSIONS For American Indians with normal fasting glucose, higher diet quality decreases the odds of developing albuminuria. These findings inform future efforts to prevent CKD in American Indian adolescents and young adults.
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Affiliation(s)
- Reya H Mokiao
- Seattle Children's Hospital, 4800 Sandpoint Way NE, Seattle, WA, 98105, USA.
- University of Washington, Seattle, WA, USA.
| | | | - Jason F Deen
- Seattle Children's Hospital, 4800 Sandpoint Way NE, Seattle, WA, 98105, USA
- University of Washington, Seattle, WA, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA
- Georgetown University, Washington, DC, USA
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18
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Boyer K, Domingo-Relloso A, Jiang E, Haack K, Goessler W, Zhang Y, Umans JG, Belsky DW, Cole SA, Navas-Acien A, Kupsco A. Metal mixtures and DNA methylation measures of biological aging in American Indian populations. Environ Int 2023; 178:108064. [PMID: 37364305 PMCID: PMC10617409 DOI: 10.1016/j.envint.2023.108064] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/18/2023] [Accepted: 06/22/2023] [Indexed: 06/28/2023]
Abstract
INTRODUCTION Native American communities suffer disproportionately from elevated metal exposures and increased risk for cardiovascular diseases and diabetes. DNA methylation is a sensitive biomarker of aging-related processes and novel epigenetic-based "clocks" can be used to estimate accelerated biological aging that may underlie increased risk. Metals alter DNA methylation, yet little is known about their individual and combined impact on epigenetic age acceleration. Our objective was to investigate the associations of metals on several DNA methylation-based aging measures in the Strong Heart Study (SHS) cohort. METHODS Blood DNA methylation data from 2,301 SHS participants was used to calculate age acceleration of epigenetic clocks (PhenoAge, GrimAge, DunedinPACE, Hannum, Horvath). Urinary metals [arsenic (As), cadmium (Cd), tungsten (W), zinc (Zn), selenium (Se), molybdenum (Mo)] were creatinine-adjusted and categorized into quartiles. We examined associations of individual metals through linear regression models and used Bayesian Kernel Machine Regression (BKMR) for the impact of the total metal mixture on epigenetic age acceleration. RESULTS The mixture of nonessential metals (W, As, Cd) was associated with greater GrimAge acceleration and DunedinPACE, while the essential metal mixture (Se, Zn, Mo) was associated with lower epigenetic age acceleration. Cd was associated with increased epigenetic age acceleration across all clocks and BKMR analysis suggested nonlinear associations between Se and DunedinPACE, GrimAge, and PhenoAge acceleration. No interactions between individual metals were observed. The associations between Cd, Zn, and epigenetic age acceleration were greater in never smokers in comparison to current/former smokers. CONCLUSION Nonessential metals were positively associated with greater epigenetic age acceleration, with strongest associations observed between Cd and DunedinPACE and GrimAge acceleration. In contrast, essential metals were associated with lower epigenetic aging. Examining the influence of metal mixtures on epigenetic age acceleration can provide insight into metals and aging-related diseases.
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Affiliation(s)
- Kaila Boyer
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Arce Domingo-Relloso
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA; Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain; Department of Statistics and Operations Research, University of Valencia, Spain
| | - Enoch Jiang
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Walter Goessler
- Institute of Chemistry, Universität Graz, Universität Platz 3, 8010 Graz, Austria
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Jason G Umans
- MedStar Health Research Institute, Washington, DC, USA; Center for Clinical and Translational Sciences, Georgetown/Howard Universities, Washington, DC, USA
| | - Daniel W Belsky
- Department of Epidemiology and Butler Columbia Aging Center, Columbia University, New York, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Allison Kupsco
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
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Dye CK, Domingo-Relloso A, Kupsco A, Tinkelman NE, Spratlen MJ, Bozack AK, Tellez-Plaza M, Goessler W, Haack K, Umans JG, Baccarelli AA, Cole SA, Navas-Acien A. Maternal DNA methylation signatures of arsenic exposure is associated with adult offspring insulin resistance in the Strong Heart Study. Environ Int 2023; 173:107774. [PMID: 36805808 PMCID: PMC10166110 DOI: 10.1016/j.envint.2023.107774] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 12/16/2022] [Accepted: 01/20/2023] [Indexed: 05/10/2023]
Abstract
Exposure to low to moderate arsenic (As) levels has been associated with type 2 diabetes (T2D) and other chronic diseases in American Indian communities. Prenatal exposure to As may also increase the risk for T2D in adulthood, and maternal As has been associated with adult offspring metabolic health measurements. We hypothesized that T2D-related outcomes in adult offspring born to women exposed to low to moderate As can be evaluated utilizing a maternally-derived molecular biosignature of As exposure. Herein, we evaluated the association of maternal DNA methylation with incident T2D and insulin resistance (Homeostatic model assessment of insulin resistance [HOMA2-IR]) in adult offspring. For DNA methylation, we used 20 differentially methylated cytosine-guanine dinucleotides (CpG) previously associated with the sum of inorganic and methylated As species (ΣAs) in urine in the Strong Heart Study (SHS). Of these 20 CpGs, we found six CpGs nominally associated (p < 0.05) with HOMA2-IR in a fully adjusted model that included clinically relevant covariates and offspring adiposity measurements; a similar model that adjusted instead for maternal adiposity measurements found three CpGs nominally associated with HOMA2-IR, two of which overlapped the offspring adiposity model. After adjusting for multiple comparisons, cg03036214 remained associated with HOMA2-IR (q < 0.10) in the offspring adiposity model. The odds ratio of incident T2D increased with an increase in maternal DNA methylation at one HOMA2-IR associated CpG in the model adjusting for offspring adiposity, cg12116137, whereas adjusting for maternal adiposity had a minimal effect on the association. Our data suggests offspring adiposity, rather than maternal adiposity, potentially influences the effects of maternal DNAm signatures on offspring metabolic health parameters. Here, we have presented evidence supporting a role for epigenetic biosignatures of maternal As exposure as a potential biomarker for evaluating risk of T2D-related outcomes in offspring later in life.
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Affiliation(s)
- Christian K Dye
- Department of Environmental Health Sciences, Columbia University, New York, New York, USA.
| | - Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University, New York, New York, USA; Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institutes, Madrid, Spain
| | - Allison Kupsco
- Department of Environmental Health Sciences, Columbia University, New York, New York, USA
| | - Naomi E Tinkelman
- Department of Environmental Health Sciences, Columbia University, New York, New York, USA
| | - Miranda J Spratlen
- Department of Environmental Health Sciences, Columbia University, New York, New York, USA
| | - Anne K Bozack
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institutes, Madrid, Spain
| | | | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Jason G Umans
- MedStar Health Research Institute, Washington, DC, USA; Center for Clinical and Translational Sciences, Georgetown-Howard Universities, Washington, DC, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia University, New York, New York, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University, New York, New York, USA
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20
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Galvez-Fernandez M, Bhatt KA, Ravalli F, Goessler W, Zhang Y, Fretts AM, Umans JG, Sanchez T, Ujueta F, Lamas GA, Fabsitz RR, Navas-Acien A. Abstract P170: The Association of Urinary Cadmium and Zinc With Lower Extremity Amputations. Evidence From the Strong Heart Study. Circulation 2023. [DOI: 10.1161/circ.147.suppl_1.p170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
Background:
Cadmium is a cardiotoxic divalent metal that accumulates in the liver and kidney. It resembles the essential metal zinc, replacing it in numerous enzymes and proteins. Zinc plays a major role in insulin function. Glucose dyshomeostasis increases the loss of zinc through the urine. Cadmium has been associated with peripheral artery disease and critical limb ischemia, conditions that lead to limb amputations. Chelation treatment with edetate disodium, an agent that facilitates the excretion of cadmium from the body, was beneficial for individuals with critical limb ischemia and diabetes in several small studies. This study evaluated the association of urinary levels of cadmium and zinc with amputations in a population with a high burden of diabetes from Arizona, Oklahoma, North Dakota and South Dakota.
Hypothesis:
We hypothesize that urinary cadmium and zinc levels are related to prevalent amputations in the SHS cohort.
Methods:
We included 2,724 participants from the Strong Heart Study, a population-based cohort study in 12 American Indian communities, recruited in 1989-1991 and followed for amputations through 1998-1999. Trained staff identified amputations of the lower extremity through visual examination at the baseline visit. We censored traumatic amputations. Baseline metal levels in spot urine samples were divided by urinary creatinine to account for urine dilution.
Results:
Mean age was 56.4 years, 41.5% participants were male, and 42% had diabetes. We identified a total of 35 (1.3%) amputations of the lower extremities during the study period. Median urinary levels were 0.97 μg/g for cadmium and 0.56 mg/g for zinc. Higher levels of urinary cadmium and zinc were positively associated with the presence of amputations. The odds ratios of prevalent amputations for an IQR of cadmium and zinc distribution were 1.54 (1.00, 2.38) and 2.24 (1.48, 3.39), respectively, in models adjusted for sociodemographic, lifestyle (tobacco and alcohol intake), and other factors (BMI, hypertension and diabetes status, HDL and LDL-cholesterol, and estimated glomerular filtration rate). The associations remained after further adjustment for fasting plasma glucose levels. Urinary cadmium and zinc levels were positively correlated (r=0.24, P<0.001).
Conclusions:
Urinary cadmium and zinc were positively associated with the presence of lower extremity amputations in American Indian adults with a high burden of diabetes. These results support the current evidence of cadmium as a cardiometabolic risk factor, and the potential role of impaired zinc metabolism, reflected as increased urinary zinc excretion, in vascular complications of diabetes.
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Affiliation(s)
| | - Kishan A Bhatt
- Columbia Univ Mailman Sch of Public Health, New York, NY
| | | | | | - Ying Zhang
- The Univ of Oklahoma Health Sciences Cntr, Oklahoma City, OK
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21
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Brown MC, Hawley C, Ornelas IJ, Huber C, Best L, Thorndike AN, Beresford S, Howard BV, Umans JG, Hager A, Fretts AM. Adapting a cooking, food budgeting and nutrition intervention for a rural community of American Indians with type 2 diabetes in the North-Central United States. Health Educ Res 2023; 38:13-27. [PMID: 36342521 PMCID: PMC9853931 DOI: 10.1093/her/cyac033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 09/06/2022] [Accepted: 10/18/2022] [Indexed: 05/24/2023]
Abstract
American Indian (AI) communities experience persistent diabetes-related disparities, yet few nutrition interventions are designed for AI with type 2 diabetes or address socio-contextual barriers to healthy eating. We describe our process of adapting the evidence-based Cooking Matters® program for use by AI adults with type 2 diabetes in a rural and resource-limited setting in the North-Central United States. We conducted three focus groups with AI adults with diabetes to (i) identify Cooking Matters® adaptations and (ii) gather feedback on appropriateness of the adapted intervention using Barrera and Castro's cultural adaptation framework. Transcripts were coded using an inductive, constant comparison approach. Queries of codes were reviewed to identify themes. Contextual considerations included limited access to grocery stores and transportation barriers, reliance on government food assistance and the intergenerational burden of diabetes. Adaptations to content and delivery included incorporating traditional and locally available foods; appealing to children or others in multigenerational households and prioritizing visual over written content. Our use of Barrera and Castro's framework adds rigor and structure to the cultural adaptation process and increases the likelihood of future intervention success. Other researchers may benefit from using this framework to guide the adaptation of evidence-based interventions in AI communities.
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Affiliation(s)
- Meagan C Brown
- Department of Epidemiology, University of Washington School of Public Health, Hans Rosling Center for Population Health, 3980 15th Ave NE, Seattle, WA 98195, USA and Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave, Seattle, WA 98101, USA
| | - Caitie Hawley
- Department of Medicine, University of Washington, Health Sciences Building, Box 356420, 1959 NE Pacific Street, Seattle, WA 98195-6420, USA
| | - India J Ornelas
- Department of Health Systems and Population Health, University of Washington School of Public Health, Hans Rosling Center for Population Health, 3980 15th Ave NE, Seattle, WA 98195, USA
| | - Corrine Huber
- Missouri Breaks Industries Research Inc., 18 South Willow Street, P.O. Box 1824, Eagle Butte, SD 57625, USA
| | - Lyle Best
- Missouri Breaks Industries Research Inc., 18 South Willow Street, P.O. Box 1824, Eagle Butte, SD 57625, USA
| | - Anne N Thorndike
- Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA and Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA
| | - Shirley Beresford
- Department of Epidemiology, University of Washington School of Public Health, Hans Rosling Center for Population Health, 3980 15th Ave NE, Seattle, WA 98195, USA
| | - Barbara V Howard
- Field Studies Division, Medstar Health Research Institute, 6525 Belcrest Rd #700c, Hyattsville, MD 20782, USA
- Georgetown and Howard Universities Center for Clinical and Translational Science, 4000 Reservoir Rd NW #7, Washington, DC 20057, USA
| | - Jason G Umans
- Georgetown and Howard Universities Center for Clinical and Translational Science, 4000 Reservoir Rd NW #7, Washington, DC 20057, USA
- Field Studies Division and Biomarker, Biochemistry, and Biorepository Core, Medstar Health Research Institute, 6525 Belcrest Rd #700c, Hyattsville, MD 20782, USA
| | - Arlette Hager
- Cheyenne River Sioux Tribe Adult Diabetes Program, 24276 166th St. Airport Road, P.O. Box 590 Eagle Butte, SD 57625, USA
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington School of Public Health, Hans Rosling Center for Population Health, 3980 15th Ave NE, Seattle, WA 98195, USA
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22
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Chernoff MB, Delgado D, Tong L, Chen L, Oliva M, Tamayo LI, Best LG, Cole S, Jasmine F, Kibriya MG, Nelson H, Huang L, Haack K, Kent J, Umans JG, Graziano J, Navas-Acien A, Karagas MR, Ahsan H, Pierce BL. Sequencing-based fine-mapping and in silico functional characterization of the 10q24.32 arsenic metabolism efficiency locus across multiple arsenic-exposed populations. PLoS Genet 2023; 19:e1010588. [PMID: 36668670 PMCID: PMC9891528 DOI: 10.1371/journal.pgen.1010588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 02/01/2023] [Accepted: 12/20/2022] [Indexed: 01/22/2023] Open
Abstract
Inorganic arsenic is highly toxic and carcinogenic to humans. Exposed individuals vary in their ability to metabolize arsenic, and variability in arsenic metabolism efficiency (AME) is associated with risks of arsenic-related toxicities. Inherited genetic variation in the 10q24.32 region, near the arsenic methyltransferase (AS3MT) gene, is associated with urine-based measures of AME in multiple arsenic-exposed populations. To identify potential causal variants in this region, we applied fine mapping approaches to targeted sequencing data generated for exposed individuals from Bangladeshi, American Indian, and European American populations (n = 2,357, 557, and 648 respectively). We identified three independent association signals for Bangladeshis, two for American Indians, and one for European Americans. The size of the confidence sets for each signal varied from 4 to 85 variants. There was one signal shared across all three populations, represented by the same SNP in American Indians and European Americans (rs191177668) and in strong linkage disequilibrium (LD) with a lead SNP in Bangladesh (rs145537350). Beyond this shared signal, differences in LD patterns, minor allele frequency (MAF) (e.g., rs12573221 ~13% in Bangladesh ~0.2% among American Indians), and/or heterogeneity in effect sizes across populations likely contributed to the apparent population specificity of the additional identified signals. One of our potential causal variants influences AS3MT expression and nearby DNA methylation in numerous GTEx tissue types (with rs4919690 as a likely causal variant). Several SNPs in our confidence sets overlap transcription factor binding sites and cis-regulatory elements (from ENCODE). Taken together, our analyses reveal multiple potential causal variants in the 10q24.32 region influencing AME, including a variant shared across populations, and elucidate potential biological mechanisms underlying the impact of genetic variation on AME.
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Affiliation(s)
- Meytal Batya Chernoff
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
- Interdisciplinary Scientist Training Program, University of Chicago, Chicago, Illinois, United States of America
- University of Chicago Pritzker School of Medicine, Chicago, Illinois, United States of America
| | - Dayana Delgado
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
| | - Lin Tong
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
| | - Lin Chen
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
| | - Meritxell Oliva
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
| | - Lizeth I. Tamayo
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
| | - Lyle G. Best
- Missouri Breaks Industries Research Inc, Eagle Butte, South Dakota, United States of America
| | - Shelley Cole
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Farzana Jasmine
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
| | - Muhammad G. Kibriya
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
| | - Heather Nelson
- School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Lei Huang
- Center for Research Informatics, University of Chicago, Chicago, Illinois, United States of America
| | - Karin Haack
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Jack Kent
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Jason G. Umans
- MedStar Health Research Institute, Hyattsville, Maryland, United States of America
- Georgetown-Howard Universities Center for Clinical and Translational Science, Georgetown University, Washington, District of Columbia, United States of America
| | - Joseph Graziano
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
- Department of Pharmacology, Columbia University, New York City, New York, United States of America
| | - Ana Navas-Acien
- Mailman School of Public Health, Columbia University, New York City, New York, United States of America
| | - Margaret R. Karagas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America
| | - Habib Ahsan
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
- Comprehensive Cancer Center, University of Chicago, Chicago, Illinois, United States of America
- Department of Medicine, University of Chicago, Chicago, Illinois, United States of America
| | - Brandon L. Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America
- Comprehensive Cancer Center, University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
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23
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Domingo-Relloso A, Gribble MO, Riffo-Campos AL, Haack K, Cole SA, Tellez-Plaza M, Umans JG, Fretts AM, Zhang Y, Fallin MD, Navas-Acien A, Everson TM. Epigenetics of type 2 diabetes and diabetes-related outcomes in the Strong Heart Study. Clin Epigenetics 2022; 14:177. [PMID: 36529747 PMCID: PMC9759920 DOI: 10.1186/s13148-022-01392-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The prevalence of type 2 diabetes has dramatically increased in the past years. Increasing evidence supports that blood DNA methylation, the best studied epigenetic mark, is related to diabetes risk. Few prospective studies, however, are available. We studied the association of blood DNA methylation with diabetes in the Strong Heart Study. We used limma, Iterative Sure Independence Screening and Cox regression to study the association of blood DNA methylation with fasting glucose, HOMA-IR and incident type 2 diabetes among 1312 American Indians from the Strong Heart Study. DNA methylation was measured using Illumina's MethylationEPIC beadchip. We also assessed the biological relevance of our findings using bioinformatics analyses. RESULTS Among the 358 differentially methylated positions (DMPs) that were cross-sectionally associated either with fasting glucose or HOMA-IR, 49 were prospectively associated with incident type 2 diabetes, although no DMPs remained significant after multiple comparisons correction. Multiple of the top DMPs were annotated to genes with relevant functions for diabetes including SREBF1, associated with obesity, type 2 diabetes and insulin sensitivity; ABCG1, involved in cholesterol and phospholipids transport; and HDAC1, of the HDAC family. (HDAC inhibitors have been proposed as an emerging treatment for diabetes and its complications.) CONCLUSIONS: Our results suggest that differences in peripheral blood DNA methylation are related to cross-sectional markers of glucose metabolism and insulin activity. While some of these DMPs were modestly associated with prospective incident type 2 diabetes, they did not survive multiple testing. Common DMPs with diabetes epigenome-wide association studies from other populations suggest a partially common epigenomic signature of glucose and insulin activity.
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Affiliation(s)
- Arce Domingo-Relloso
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain. .,Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA. .,Department of Statistics and Operations Research, University of Valencia, Valencia, Spain.
| | - Matthew O. Gribble
- grid.265892.20000000106344187Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL USA
| | - Angela L. Riffo-Campos
- grid.412163.30000 0001 2287 9552Millennium Nucleus On Sociomedicine (SocioMed) and Vicerrectoría Académica, Universidad de La Frontera, Temuco, Chile ,grid.5338.d0000 0001 2173 938XDepartment of Computer Science, ETSE, University of Valencia, Valencia, Spain
| | - Karin Haack
- grid.250889.e0000 0001 2215 0219Population Health Program, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Shelley A. Cole
- grid.250889.e0000 0001 2215 0219Population Health Program, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Maria Tellez-Plaza
- grid.413448.e0000 0000 9314 1427Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Jason G. Umans
- grid.415232.30000 0004 0391 7375MedStar Health Research Institute, Hyattsville, MD USA ,grid.440590.cGeorgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC USA
| | - Amanda M. Fretts
- grid.34477.330000000122986657Department of Epidemiology, Cardiovascular Health Research Unit, University of Washington, Seattle, WA USA
| | - Ying Zhang
- grid.266902.90000 0001 2179 3618Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK USA
| | - M. Daniele Fallin
- grid.189967.80000 0001 0941 6502Emory University Rollins School of Public Health, Atlanta, GA USA ,grid.189967.80000 0001 0941 6502Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA USA
| | - Ana Navas-Acien
- grid.21729.3f0000000419368729Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY USA
| | - Todd M. Everson
- grid.189967.80000 0001 0941 6502Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA USA ,grid.189967.80000 0001 0941 6502Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA USA
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24
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Suchy-Dicey AM, Oziel K, Sawyer C, Olufadi Y, Ali T, Fretts AM, Umans JG, Shibata DK, Longstreth WT, Rhoads K, Buchwald DS, Grabowski TJ. Educational and Clinical Associations With Longitudinal Cognitive Function and Brain Imaging in American Indians: The Strong Heart Study. Neurology 2022; 99:e2637-e2647. [PMID: 36289000 PMCID: PMC9757873 DOI: 10.1212/wnl.0000000000201261] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 08/01/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Little is known about incidence of vascular and Alzheimer dementias in American Indians. METHODS We conducted a large, heterogeneous, population-based, longitudinal cohort study of brain aging in community-dwelling American Indians aged 64-95 years from 11 tribes across 3 states, with neurologic examinations, 1.5T MRI, and extensive cognitive testing. Visit 1 in 2010-2013 (n = 817) and visit 2 in 2017-2019 (n = 403) included all willing, surviving participants. Standardized cognitive tests at both visits included Modified Mini-Mental Status Examination (MMSE), Wechsler Adult Intelligence Scale digit symbol coding (WAIS), Controlled Oral Word Association (COWA), and California Verbal Learning Test short form (CVLT). Test materials added at follow-up included Wide Range Achievement (reading) Test (WRAT) and National Alzheimer Coordinating Center Uniform Data Set cognitive battery (v3 form C2), including Montreal Cognitive Assessment (MoCA). MRI neuroradiologists coded infarcts, hemorrhages, white matter hyperintensities, sulcal atrophy, and ventricle enlargement. RESULTS The mean time between examinations was 6.7 years (SD 1.1, range 3.8-9.1 years). Years of formal education had modest correlation with WRAT reading score (r = 0.45). Prevalence and incidence (respectively) of infarcts were 32% and 12.8/1,000 person-years (PYs) hemorrhages 6% and 4.4/1000 PY worsening sulci 74% and 19.0/1000 PY worsening ventricle 79% and 30.1/1000 PY worsening leukoaraiosis 44% and 26.1/1000 PY. Linear losses per year in cognitive scores were 0.6% MMSE, 1.2% WAIS, 0.6% COWA, and 2.2% CVLT. The mean MoCA scores were 18.9 (SD 4.3). DISCUSSION These are the first data on longitudinal cognitive and imaging changes in American Indians and first reports of Alzheimer disease-related features. The mean scores in MoCA were similar or lower than standard cutoffs used to diagnose dementia in other racial/ethnic groups, suggesting that standardized cognitive tests may not perform well in this population. Test validation, adaptation, and score adjustment are warranted. Years of education were a poor proxy for premorbid function, suggesting novel methods for cognitive score contextualization is also needed in this population. Evaluation of selective survival suggests attrition from death, and frailty should be accounted for in causal analyses. Overall, these data represent a unique opportunity to examine neurology topics of critical importance to an understudied population.
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Affiliation(s)
- Astrid M Suchy-Dicey
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle.
| | - Kyra Oziel
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Charles Sawyer
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Yunusa Olufadi
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Tauqeer Ali
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Amanda M Fretts
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Jason G Umans
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Dean K Shibata
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - W T Longstreth
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Kristoffer Rhoads
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Dedra S Buchwald
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
| | - Thomas J Grabowski
- From the Elson S. Floyd College of Medicine (A.M.S.-D., K.O., C.S., Y.O., D.S.B.), Washington State University, Spokane; Oklahoma University Health Sciences Center (T.A.), Oklahoma City; Epidemiology (A.M.F., M.D.J.), School of Public Health, University of Washington, Seattle; MedStar Health Research Institute (J.G.U.), Washington, DC; Neuroradiology (D.K.S.) and Neurology (M.D.J., K.R., T.J.G.), School of Medicine, University of Washington, Seattle
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25
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Li Z, Lewin M, Ruiz P, Nigra AE, Henderson NB, Jarrett JM, Ward C, Zhu J, Umans JG, O'Leary M, Zhang Y, Ragin-Wilson A, Navas-Acien A. Blood cadmium, lead, manganese, mercury, and selenium levels in American Indian populations: The Strong Heart Study. Environ Res 2022; 215:114101. [PMID: 35977585 PMCID: PMC9644284 DOI: 10.1016/j.envres.2022.114101] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 05/15/2023]
Abstract
BACKGROUND Many American Indian (AI) communities are in areas affected by environmental contamination, such as toxic metals. However, studies assessing exposures in AI communities are limited. We measured blood metals in AI communities to assess historical exposure and identify participant characteristics associated with these levels in the Strong Heart Study (SHS) cohort. METHOD Archived blood specimens collected from participants (n = 2014, all participants were 50 years of age and older) in Arizona, Oklahoma, and North and South Dakota during SHS Phase-III (1998-1999) were analyzed for cadmium, lead, manganese, mercury, and selenium using inductively coupled plasma triple quadrupole mass spectrometry. We conducted descriptive analyses for the entire cohort and stratified by selected subgroups, including selected demographics, health behaviors, income, waist circumference, and body mass index. Bivariate associations were conducted to examine associations between blood metal levels and selected socio-demographic and behavioral covariates. Finally, multivariate regression models were used to assess the best model fit that predicted blood metal levels. FINDINGS All elements were detected in 100% of study participants, with the exception of mercury (detected in 73% of participants). The SHS population had higher levels of blood cadmium and manganese than the general U.S. population 50 years and older. The median blood mercury in the SHS cohort was at about 30% of the U.S. reference population, potentially due to low fish consumption. Participants in North Dakota and South Dakota had the highest blood cadmium, lead, manganese, and selenium, and the lowest total mercury levels, even after adjusting for covariates. In addition, each of the blood metals was associated with selected demographic, behavioral, income, and/or weight-related factors in multivariate models. These findings will help guide the tribes to develop education, outreach, and strategies to reduce harmful exposures and increase beneficial nutrient intake in these AI communities.
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Affiliation(s)
- Zheng Li
- Office of Community Health and Hazard Assessment, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Michael Lewin
- Office of Community Health and Hazard Assessment, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Patricia Ruiz
- Office of Innovation and Analytics, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Anne E Nigra
- Department of Environmental Health Sciences, School of Public Health, Columbia University, New York City, NY, USA
| | - Noelle B Henderson
- Office of Community Health and Hazard Assessment, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jeffery M Jarrett
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Cynthia Ward
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jianhui Zhu
- MedStar Health Research Institute, Hyattsville, MD, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington DC, USA
| | - Marcia O'Leary
- Missouri Breaks Industries and Research, Inc., Eagle Butte, SD, USA
| | - Ying Zhang
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Angela Ragin-Wilson
- Office of Associate Director, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, School of Public Health, Columbia University, New York City, NY, USA
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26
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Zhao D, Domingo-Relloso A, Tellez-Plaza M, Nigra AE, Valeri L, Moon KA, Goessler W, Best LG, Ali T, Umans JG, Fretts A, Cole SA, Navas-Acien A. High Level of Selenium Exposure in the Strong Heart Study: A Cause for Incident Cardiovascular Disease? Antioxid Redox Signal 2022; 37:990-997. [PMID: 35350849 PMCID: PMC9689768 DOI: 10.1089/ars.2022.0029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 03/21/2022] [Indexed: 11/12/2022]
Abstract
Increasing evidence suggests that high selenium (Se) exposure is associated with adverse health effects. However, limited evidence exists on the association of Se exposure with cardiovascular disease (CVD), especially in communities affected by high naturally occurring Se in environmental media. We evaluated the prospective association between urinary Se levels and CVD incidence and mortality for 2727 American Indian adults who participated in the Strong Heart Study, with urinary Se levels measured at baseline (1989-1991) and CVD outcomes ascertained through 2017. The median (interquartile range) of urinary Se was 49.0 (36.7-67.4) μg/g creatinine. The multivariable adjusted hazard ratios (95% confidence interval) of incident CVD, coronary heart disease, and stroke comparing the 75th versus 25th percentile of urinary Se distributions were 1.11 (1.01-1.22), 1.05 (0.94-1.17), and 1.08 (0.88-1.33), respectively. In flexible dose-response models, increased risk for CVD incidence was only observed when the urinary Se level exceeded 60 μg/g creatinine. For CVD mortality, a nonstatistically significant U-shaped relationship was found across urinary Se levels. There was no evidence of effect modification by other urinary metal/metalloid levels. Our observation leads to the hypothesis that elevated Se exposure is a risk factor for CVD, especially in Se-replete populations. Antioxid. Redox Signal. 37, 990-997.
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Affiliation(s)
- Di Zhao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Arce Domingo-Relloso
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Maria Tellez-Plaza
- Department of Epidemiology of Chronic Diseases, National Centre for Epidemiology, Carlos III Institute of Health, Madrid, Spain
| | - Anne E. Nigra
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Linda Valeri
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Katherine A. Moon
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | | | - Lyle G. Best
- Missouri Breaks Industries Research, Inc., Eagle Butte, South Dakota, USA
| | - Tauqeer Ali
- Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Jason G. Umans
- MedStar Health Research Institute, Washington, District of Columbia, USA
- Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, District of Columbia, USA
| | - Amanda Fretts
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Shelley A. Cole
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, North Carolina, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
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Galvez-Fernandez M, Powers M, Grau-Perez M, Domingo-Relloso A, Lolacono N, Goessler W, Zhang Y, Fretts A, Umans JG, Maruthur N, Navas-Acien A. Urinary Zinc and Incident Type 2 Diabetes: Prospective Evidence From the Strong Heart Study. Diabetes Care 2022; 45:2561-2569. [PMID: 36134919 PMCID: PMC9679259 DOI: 10.2337/dc22-1152] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 08/15/2022] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Hyperglycemia can increase urinary zinc excretion. We evaluated the association of higher urinary zinc level with new diagnosis of incident type 2 diabetes mellitus (T2DM) in adult populations with a high burden of T2DM from AZ, OK, and ND and SD. We also assessed the cross-sectional association of urinary zinc levels with prevalent prediabetes. RESEARCH DESIGN AND METHODS We included 1,339 adults free of T2DM at baseline (1989-1991) followed through 1998-1999 in the Strong Heart Study (SHS) and 1,905 family members of SHS participants followed as part of the Strong Heart Family Study (SHFS) through 2006-2009. RESULTS T2DM incidence was 14.7% (mean follow-up 6.6 years) in the SHS and 13.5% (mean follow-up 5.6 years) in the SHFS. After adjustment for sex, site, education, smoking status, BMI, and estimated glomerular filtration rate, the hazard ratio of T2DM in comparing 75th vs. 25th percentiles of urinary zinc distribution was 1.21 (95% CI 1.08, 1.36) in the SHS and 1.12 (0.96, 1.31) in the SHFS. These associations were attenuated but significant in the SHS after adjustment for HOMA of insulin resistance (HOMA-IR) score. With exclusion of participants with prediabetes at baseline, urinary zinc remained significantly associated with T2DM in the SHS. In cross-sectional analyses, prediabetes was associated with higher urinary zinc levels. CONCLUSIONS Urinary zinc levels were associated with T2DM incidence and prediabetes prevalence even after adjustment for HOMA-IR in populations with a high burden of T2DM. These results highlight the importance of zinc metabolism in diabetes development.
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Affiliation(s)
- Marta Galvez-Fernandez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY
- Department of Preventive Medicine, Hospital Universitario Severo Ochoa, Madrid, Spain
| | - Martha Powers
- Department of Sociology and Anthropology, Northeastern University, Boston, MA
| | - Maria Grau-Perez
- Biomedical Research Institute of Valencia (INCLIVA), Valencia, Spain
| | - Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY
| | - Nancy Lolacono
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY
| | | | - Ying Zhang
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Amanda Fretts
- Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, WA
| | - Jason G. Umans
- Division of Nephrology and Hypertension, Department of Medicine, Georgetown University Medical Center, Washington, DC
| | - Nisa Maruthur
- Division of General Internal Medicine, Department of Medicine and Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY
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Zeng W, Beyene HB, Kuokkanen M, Miao G, Magliano DJ, Umans JG, Franceschini N, Cole SA, Michailidis G, Lee ET, Howard BV, Fiehn O, Curran JE, Blangero J, Meikle PJ, Zhao J. Lipidomic profiling in the Strong Heart Study identified American Indians at risk of chronic kidney disease. Kidney Int 2022; 102:1154-1166. [PMID: 35853479 PMCID: PMC10753995 DOI: 10.1016/j.kint.2022.06.023] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 06/09/2022] [Accepted: 06/16/2022] [Indexed: 12/14/2022]
Abstract
Dyslipidemia associates with and usually precedes the onset of chronic kidney disease (CKD), but a comprehensive assessment of molecular lipid species associated with risk of CKD is lacking. Here, we sought to identify fasting plasma lipids associated with risk of CKD among American Indians in the Strong Heart Family Study, a large-scale community-dwelling of individuals, followed by replication in Mexican Americans from the San Antonio Family Heart Study and Caucasians from the Australian Diabetes, Obesity and Lifestyle Study. We also performed repeated measurement analysis to examine the temporal relationship between the change in the lipidome and change in kidney function between baseline and follow-up of about five years apart. Network analysis was conducted to identify differential lipid classes associated with risk of CKD. In the discovery cohort, we found that higher baseline level of multiple lipid species, including glycerophospholipids, glycerolipids and sphingolipids, was significantly associated with increased risk of CKD, independent of age, sex, body mass index, diabetes and hypertension. Many lipid species were replicated in at least one external cohort at the individual lipid species and/or the class level. Longitudinal change in the plasma lipidome was significantly associated with change in the estimated glomerular filtration rate after adjusting for covariates, baseline lipids and the baseline rate. Network analysis identified distinct lipidomic signatures differentiating high from low-risk groups. Thus, our results demonstrated that disturbed lipid metabolism precedes the onset of CKD. These findings shed light on the mechanisms linking dyslipidemia to CKD and provide potential novel biomarkers for identifying individuals with early impaired kidney function at preclinical stages.
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Affiliation(s)
- Wenjie Zeng
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Habtamu B Beyene
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Mikko Kuokkanen
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, USA
| | - Guanhong Miao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, Maryland, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, District of Columbia, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - George Michailidis
- Department of Statistics, University of Florida, Gainesville, Florida, USA
| | - Elisa T Lee
- Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, Maryland, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, District of Columbia, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, Davis, California, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, USA
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA.
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Lemaitre RN, Jensen PN, Zeigler M, Fretts AM, Umans JG, Howard BV, Sitlani CM, McKnight B, Gharib SA, King IB, Siscovick DS, Psaty BM, Sotoodehnia N, Totah RA. Plasma epoxyeicosatrienoic acids and diabetes-related cardiovascular disease: The cardiovascular health study. EBioMedicine 2022; 83:104189. [PMID: 35930887 PMCID: PMC9356248 DOI: 10.1016/j.ebiom.2022.104189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 07/07/2022] [Accepted: 07/14/2022] [Indexed: 11/04/2022] Open
Abstract
Background Epoxyeicosatrienoic acids (EETs) are metabolites of arachidonic acid that may impact atherosclerosis, and animal experimental studies suggest EETs protect cardiac function. Plasma EETs are mostly esterified to phospholipids and part of an active pool. To address the limited information about EETs and CVD in humans, we conducted a prospective study of total plasma EETs (free + esterified) and diabetes-related CVD in the Cardiovascular Health Study (CHS). Methods We measured 4 EET species and their metabolites, dihydroxyepoxyeicosatrienoic acids (DHETs), in plasma samples from 892 CHS participants with type 2 diabetes. We determined the association of EETs and DHETs with incident myocardial infarction (MI) and ischemic stroke using Cox regression. Findings During follow-up (median 7.5 years), we identified 150 MI and 134 ischemic strokes. In primary, multivariable analyses, elevated levels of each EET species were associated with non-significant lower risk of incident MI (for example, hazard ratio for 1 SD higher 14,15-EET: 0.86, 95% CI: 0.72–1.02; p=0.08). The EETs-MI associations became significant in analyses further adjusted for DHETs (hazard ratio for 1 SD higher 14,15-EET adjusted for 14,15-DHET: 0.76, 95% CI: 0.63–0.91; p=0.004). Elevated EET levels were associated with higher risk of ischemic stroke in primary but not secondary analyses. Three DHET species were associated with higher risk of ischemic stroke in all analyses. Interpretation Findings from this prospective study complement the extensive studies in animal models showing EETs protect cardiac function and provide new information in humans. Replication is needed to confirm the associations. Funding US National Institutes of Health.
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Bredella MA, Rubio DM, Attia J, Kelly TH, McIntosh S, Meagher EA, Pusek S, Rubio M, Tsevat J, Umans JG. The Virtual CTSA Visiting Scholar Program to Support Early-Stage Clinical and Translational Researchers: Implementation and Outcomes. Acad Med 2022; 97:1311-1316. [PMID: 35263302 PMCID: PMC10732303 DOI: 10.1097/acm.0000000000004645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In addition to restrictions on conducting research, COVID-19-related travel bans and scientific meeting cancellations have negatively affected scholars in the Clinical and Translational Science Award (CTSA) Mentored Career Development Award (KL2) program. In response, a national virtual visiting scholar program was developed to provide opportunity for KL2 scholars to be virtual visiting professors at another CTSA hub, meet faculty and scholars, and expand networks and build collaborations. This article describes the design and short-term outcomes of the virtual CTSA Visiting Scholar Program. In 2020, a working group designed core program elements and developed an application and selection process. Anonymized surveys were sent to scholars post visit and to scholars and program directors 6 months post visit to evaluate their experience and solicit suggestions for improvements. Between November 2020 and May 2021, 56 KL2 scholars and 27 hubs participated. Forty-five (80.4%) participating scholars responded to the initial survey. Nearly all scholars (44, 97.7%) agreed their experience was valuable. All respondents indicated they would recommend the program to other KL2 scholars. For the 6-month survey, the response rate was 87.5% (49/56). Within 6 months of their visit, 36 (73.5%) respondents had contacted at least one person at the host hub and for 17 (34.7%) respondents, new collaborations with the host hub ensued. Twenty-five of 27 (92.6%) host hubs responded to the survey. Most (21, 84.0%) agreed that hearing visiting scholar talks was valuable to their own scholars and 23 (92%) indicated likelihood of their hub participating in future round of the program. The virtual Visiting Scholar Program provided KL2 scholars an opportunity to virtually visit another CTSA hub, present their research, and meet with faculty and other scholars to expand their networks. Although geared to KL2 scholars, this model is potentially generalizable to other nationally coordinated career development programs.
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Affiliation(s)
- Miriam A Bredella
- M.A. Bredella is professor of radiology, vice chair, Department of Radiology, Massachusetts General Hospital, and director, KL2/Catalyst Medical Research Investigator Training Program, Harvard Catalyst, The Harvard Clinical and Translational Science Center, Harvard Medical School, Boston, Massachusetts
| | - Doris M Rubio
- D.M. Rubio is professor of medicine, biostatistics, bioinformatics, and clinical and translational science, assistant vice chancellor for clinical research education and training, Health Sciences, director, Institute for Clinical Research Education, and director, KL2, Team Science, and Workforce Development, Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jacqueline Attia
- J. Attia is health project coordinator, Center for Leading Innovation and Collaboration, Department of Public Health Sciences, University of Rochester Medical Center, Rochester, New York
| | - Thomas H Kelly
- T.H. Kelly is Robert Straus Professor and chair, Department of Behavioral Science, College of Medicine, associate dean for research and PhD faculty affairs, College of Nursing, and director, KL2 and Workforce Development, Center for Clinical and Translational Science, University of Kentucky, Lexington, Kentucky
| | - Scott McIntosh
- S. McIntosh is associate professor and survey team faculty lead, Center for Leading Innovation and Collaboration, Department of Public Health Sciences, University of Rochester Medical Center, Rochester, New York
| | - Emma A Meagher
- E.A. Meagher is professor of medicine and pharmacology, director, Translational Research Education, Institute for Translational Medicine and Therapeutics, and vice dean, Clinical Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Susan Pusek
- S. Pusek is director, Education Programs, North Carolina TraCS Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Mercedes Rubio
- M. Rubio is program director, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland
| | - Joel Tsevat
- J. Tsevat is professor of medicine, Joaquin G. Cigarroa, Jr., MD, Distinguished Chair, director, ReACH Center, director, KL2 Program, University of Texas Health Science Center at San Antonio, and professor of population health, Dell Medical School, University of Texas at Austin, and Institute for the Integration of Medicine and Science, Center for Research to Advance Community Health, Department of Medicine, Joe R. and Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | - Jason G Umans
- J.G. Umans is KL2 program director, Georgetown-Howard Universities Center for Clinical and Translational Science, associate professor of medicine and of obstetrics and gynecology, Georgetown University, Washington, DC, scientific director, Biomarker, Biochemistry and Biorepository Core, and scientific director, Field Studies Division, MedStar Health Research Institute, Hyattsville, Maryland
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Jensen PN, Fretts AM, Hoofnagle AN, McKnight B, Howard BV, Umans JG, Sitlani CM, Siscovick DS, King IB, Sotoodehnia N, Lemaitre RN. Circulating ceramides and sphingomyelins and the risk of incident cardiovascular disease among people with diabetes: the strong heart study. Cardiovasc Diabetol 2022; 21:167. [PMID: 36042511 PMCID: PMC9429431 DOI: 10.1186/s12933-022-01596-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 08/04/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Plasma ceramides and sphingomyelins have been independently linked to diabetes risk, glucose and insulin levels, and the risk of several cardiovascular (CVD) outcomes. However, whether individual ceramide and sphingomyelin species contribute to CVD risk among people with type 2 diabetes is uncertain. Our goal was to evaluate associations of 4 ceramide and 4 sphingomyelin species with incident CVD in a longitudinal population-based study among American Indians with diabetes. METHODS This analysis included participants with prevalent type 2 diabetes from two cohorts: a prospective cohort of 597 participants in the Strong Heart Family Study (116 incident CVD cases; mean age: 49 years; average length of follow-up: 14 years), and a nested case-control sample of 267 participants in the Strong Heart Study (78 cases of CVD and 189 controls; mean age: 61 years; average time until incident CVD in cases: 3.8 years). The average onset of diabetes was 7 years prior to sphingolipid measurement. Sphingolipid species were measured using liquid chromatography and mass spectrometry. Cox regression and logistic regression were used to assess associations of sphingolipid species with incident CVD; results were combined across cohorts using inverse-variance weighted meta-analysis. RESULTS There were 194 cases of incident CVD in the two cohorts. In meta-analysis of the 2 cohort results, higher plasma levels of Cer-16 (ceramide with acylated palmitic acid) were associated with higher CVD risk (HR per two-fold higher Cer-16: 1.85; 95% CI 1.05-3.25), and higher plasma levels of sphingomyelin species with a very long chain saturated fatty acid were associated with lower CVD risk (HR per two-fold higher SM-22: 0.48; 95% CI 0.26-0.87), although none of the associations met our pre-specified threshold for statistical significance of p = 0.006. CONCLUSIONS While replication of the findings from the SHS in other populations is warranted, our findings add to a growing body of research suggesting that ceramides, in particular Cer-16, not only are associated with higher diabetes risk, but may also be associated with higher CVD risk after diabetes onset. We also find support for the hypothesis that sphingomyelins with a very long chain saturated fatty acid are associated with lower CVD risk among adults with type 2 diabetes.
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Affiliation(s)
- Paul N Jensen
- Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA. .,Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, USA.,Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | - Barbara McKnight
- Department of Biostatistics, University of Washington, Seattle, WA, USA.,Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD, USA.,Georgetown and Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA
| | - Colleen M Sitlani
- Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA.,Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | | | - Irena B King
- Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Nona Sotoodehnia
- Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA.,Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Rozenn N Lemaitre
- Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA, 98101, USA.,Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
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Bhatt SP, Balte PP, Schwartz JE, Jaeger BC, Cassano PA, Chaves PH, Couper D, Jacobs DR, Kalhan R, Kaplan R, Lloyd-Jones D, Newman AB, O’Connor G, Sanders JL, Smith BM, Sun Y, Umans JG, White WB, Yende S, Oelsner EC. Pooled Cohort Probability Score for Subclinical Airflow Obstruction. Ann Am Thorac Soc 2022; 19:1294-1304. [PMID: 35176216 PMCID: PMC9353954 DOI: 10.1513/annalsats.202109-1020oc] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 02/16/2022] [Indexed: 11/20/2022] Open
Abstract
Rationale: Early detection of chronic obstructive pulmonary disease (COPD) is a public health priority. Airflow obstruction is the single most important risk factor for adverse COPD outcomes, but spirometry is not routinely recommended for screening. Objectives: To describe the burden of subclinical airflow obstruction (SAO) and to develop a probability score for SAO to inform potential detection and prevention programs. Methods: Lung function and clinical data were harmonized and pooled across nine U.S. general population cohorts. Adults with respiratory symptoms, inhaler use, or prior diagnosis of COPD or asthma were excluded. A probability score for prevalent SAO (forced expiratory volume in 1 second/forced vital capacity < 0.70) was developed via hierarchical group-lasso regularization from clinical variables in strata of sex and smoking status, and its discriminative accuracy for SAO was assessed in the pooled cohort as well as in an external validation cohort (NHANES [National Health and Nutrition Examination Survey] 2011-2012). Incident hospitalizations and deaths due to COPD (respiratory events) were defined by adjudication or administrative criteria in four of nine cohorts. Results: Of 33,546 participants (mean age 52 yr, 54% female, 44% non-Hispanic White), 4,424 (13.2%) had prevalent SAO. The incidence of respiratory events (Nat-risk = 14,024) was threefold higher in participants with SAO versus those without (152 vs. 39 events/10,000 person-years). The probability score, which was based on six commonly available variables (age, sex, race and/or ethnicity, body mass index, smoking status, and smoking pack-years) was well calibrated and showed excellent discrimination in both the testing sample (C-statistic, 0.81; 95% confidence interval [CI], 0.80-0.82) and in NHANES (C-statistic, 0.83; 95% CI, 0.80-0.86). Among participants with predicted probabilities ⩾ 15%, 3.2 would need to undergo spirometry to detect one case of SAO. Conclusions: Adults with SAO demonstrate excess respiratory hospitalization and mortality. A probability score for SAO using commonly available clinical risk factors may be suitable for targeting screening and primary prevention strategies.
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Affiliation(s)
- Surya P. Bhatt
- Division of Pulmonary, Allergy, and Critical Care Medicine
- Lung Health Center, and
| | - Pallavi P. Balte
- Division of General Medicine, Columbia University Medical Center, New York, New York
| | - Joseph E. Schwartz
- Division of General Medicine, Columbia University Medical Center, New York, New York
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York
| | - Byron C. Jaeger
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
| | - Patricia A. Cassano
- Division of Nutritional Sciences, Weill Cornell Medical College, Ithaca, New York
| | - Paulo H. Chaves
- Benjamin Leon Center for Geriatric Research and Education, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| | - David R. Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Ravi Kalhan
- Division of Pulmonary and Critical Care Medicine and
| | - Robert Kaplan
- Albert Einstein College of Medicine, New York, New York
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University, Chicago, Illinois
| | | | - George O’Connor
- Division of Pulmonary, Allergy, Sleep, and Critical Care, Boston University, Boston, Massachusetts
| | - Jason L. Sanders
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | | | | | - Jason G. Umans
- Georgetown Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Wendy B. White
- Undergraduate Training and Education Center, Tougaloo College, Tougaloo, Mississippi; and
| | - Sachin Yende
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
| | - Elizabeth C. Oelsner
- Division of General Medicine, Columbia University Medical Center, New York, New York
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, New York
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Reese JA, Roman MJ, Deen JF, Ali T, Cole SA, Devereux RB, Fretts AM, Howard BV, Lee ET, Malloy K, Singh P, Umans JG, Zhang Y. Subclinical atherosclerosis in adolescents and young adults and the risk of cardiovascular disease: The Strong Heart Family Study (SHFS). Nutr Metab Cardiovasc Dis 2022; 32:1863-1871. [PMID: 35680485 PMCID: PMC9377778 DOI: 10.1016/j.numecd.2022.04.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND AND AIMS Rates of cardiovascular disease (CVD) among American Indians (AI) have been increasing. Although we have observed an association between atherosclerosis and CVD in older adults, the potential association among young AI is unclear. Therefore, we aim to describe the prevalence of atherosclerosis among young AI and determine its association with CVD and all-cause mortality. METHODS AND RESULTS We evaluated AI participants from the Strong Heart Family Study (SHFS), who were <40 years old and CVD free at the baseline examination, 2001-2003 (n = 1376). We used carotid ultrasound to detect baseline atherosclerotic plaque. We identified CVD events and all-cause mortality through 2019, with a median follow-up of 17.8 years. We used shared frailty Cox Proportional Hazards models to assess the association between atherosclerosis and time to CVD event or all-cause mortality, while controlling for covariates. Among 1376 participants, 71 (5.2%) had atherosclerosis at baseline. During follow-up, 120 (8.7%) had CVD events and 104 (7.6%) died from any cause. CVD incidence was higher in participants who had baseline atherosclerosis (13.51/1000 person-years) than in those who did not (4.95/1000 person-years, p = 0.0003). CVD risk and all-cause mortality were higher in participants with atherosclerosis, while controlling for covariates (CVD HR = 1.85, 95%CI = 1.02-3.37, p = 0.0420; all-cause mortality HR = 2.04, 95%CI = 1.07-3.89, p = 0.0291). CONCLUSIONS Among young AI, atherosclerosis was independently associated with incident CVD and all-cause mortality later in life. Thus, atherosclerosis begins early in life and interventions in adolescents and young adults to slow the progression of disease could prevent or delay CVD events later in life.
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Affiliation(s)
- Jessica A Reese
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Mary J Roman
- Weill Cornell Medical College, New York, NY, USA
| | - Jason F Deen
- Department of Pediatrics and Medicine, University of Washington, Seattle WA, USA
| | - Tauqeer Ali
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX, USA
| | | | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Elisa T Lee
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Kimberly Malloy
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | | | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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Domingo-Relloso A, Makhani K, Riffo-Campos AL, Tellez-Plaza M, Klein KO, Subedi P, Zhao J, Moon KA, Bozack AK, Haack K, Goessler W, Umans JG, Best LG, Zhang Y, Herreros-Martinez M, Glabonjat RA, Schilling K, Galvez-Fernandez M, Kent JW, Sanchez TR, Taylor KD, Johnson WC, Durda P, Tracy RP, Rotter JI, Rich SS, Van Den Berg D, Kasela S, Lappalainen T, Vasan RS, Joehanes R, Howard BV, Levy D, Lohman K, Liu Y, Fallin MD, Cole SA, Mann KK, Navas-Acien A. Arsenic Exposure, Blood DNA Methylation, and Cardiovascular Disease. Circ Res 2022; 131:e51-e69. [PMID: 35658476 DOI: 10.1161/circresaha.122.320991] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND Epigenetic dysregulation has been proposed as a key mechanism for arsenic-related cardiovascular disease (CVD). We evaluated differentially methylated positions (DMPs) as potential mediators on the association between arsenic and CVD. METHODS Blood DNA methylation was measured in 2321 participants (mean age 56.2, 58.6% women) of the Strong Heart Study, a prospective cohort of American Indians. Urinary arsenic species were measured using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. We identified DMPs that are potential mediators between arsenic and CVD. In a cross-species analysis, we compared those DMPs with differential liver DNA methylation following early-life arsenic exposure in the apoE knockout (apoE-/-) mouse model of atherosclerosis. RESULTS A total of 20 and 13 DMPs were potential mediators for CVD incidence and mortality, respectively, several of them annotated to genes related to diabetes. Eleven of these DMPs were similarly associated with incident CVD in 3 diverse prospective cohorts (Framingham Heart Study, Women's Health Initiative, and Multi-Ethnic Study of Atherosclerosis). In the mouse model, differentially methylated regions in 20 of those genes and DMPs in 10 genes were associated with arsenic. CONCLUSIONS Differential DNA methylation might be part of the biological link between arsenic and CVD. The gene functions suggest that diabetes might represent a relevant mechanism for arsenic-related cardiovascular risk in populations with a high burden of diabetes.
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Affiliation(s)
- Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY (A.D.-R., R.A.G., K.S., M.G.-F., T.R.S., A.N.-A.).,Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain (A.D.-R., M.T.-P., M.G.-F.).,Department of Statistics and Operations Research (A.D.-R.), University of Valencia, Spain
| | - Kiran Makhani
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada (K.M., K.O.K., K.K.M.)
| | - Angela L Riffo-Campos
- Department of Computer Science, ETSE (A.L.R.-C.), University of Valencia, Spain.,Millennium Nucleus on Sociomedicine (SocioMed) and Vicerrectoría Académica, Universidad de La Frontera, Temuco, Chile (A.L.R.-C.)
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain (A.D.-R., M.T.-P., M.G.-F.)
| | - Kathleen Oros Klein
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada (K.M., K.O.K., K.K.M.)
| | - Pooja Subedi
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville (P.S., J.Z.)
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville (P.S., J.Z.)
| | - Katherine A Moon
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K.A.M.)
| | - Anne K Bozack
- Department of Environmental Health Sciences, School of Public Health, University of California, Berkeley (A.K.B.)
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio' TX (K.H., J.W.K., S.A.C.)
| | - Walter Goessler
- Institute of Chemistry - Analytical Chemistry for Health and Environment, University of Graz, Austria (W.G.)
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD. Now with Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC (J.G.U., B.W.H.).,Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC (J.G.U., B.V.H.)
| | - Lyle G Best
- Missouri Breaks Industries and Research, Inc, Eagle Butte, SD (L.G.B.)
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center (Y.Z.)
| | | | - Ronald A Glabonjat
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY (A.D.-R., R.A.G., K.S., M.G.-F., T.R.S., A.N.-A.)
| | - Kathrin Schilling
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY (A.D.-R., R.A.G., K.S., M.G.-F., T.R.S., A.N.-A.)
| | - Marta Galvez-Fernandez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY (A.D.-R., R.A.G., K.S., M.G.-F., T.R.S., A.N.-A.).,Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain (A.D.-R., M.T.-P., M.G.-F.)
| | - Jack W Kent
- Population Health Program, Texas Biomedical Research Institute, San Antonio' TX (K.H., J.W.K., S.A.C.)
| | - Tiffany R Sanchez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY (A.D.-R., R.A.G., K.S., M.G.-F., T.R.S., A.N.-A.)
| | - 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 (K.D.T., J.I.R.)
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle (W.C.J.)
| | - Peter Durda
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT (P.D., R.P.T.)
| | - Russell P Tracy
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT (P.D., R.P.T.)
| | - 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 (K.D.T., J.I.R.)
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA (S.S.R.)
| | - David Van Den Berg
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, University of Southern California, Los Angeles' CA (D.V.D.B.)
| | - Silva Kasela
- New York Genome Center (S.K., T.L.).,Department of Systems Biology, Columbia University' NY (S.K., T.L.)
| | - Tuuli Lappalainen
- New York Genome Center (S.K., T.L.).,Department of Systems Biology, Columbia University' NY (S.K., T.L.)
| | - Ramachandran S Vasan
- National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA (R.S.V.).,Sections of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, Department of Epidemiology, Boston University Schools of Medicine and Public Health, MA (R.S.V.)
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD (R.J., D.L.).,Framingham Heart Study, MA (R.J., D.L.)
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD. Now with Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC (J.G.U., B.W.H.).,Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC (J.G.U., B.V.H.)
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD (R.J., D.L.).,Framingham Heart Study, MA (R.J., D.L.)
| | - Kurt Lohman
- Department of Medicine, Duke University Medical Center, Durham, NC (K.L., Y.L.)
| | - Yongmei Liu
- Department of Medicine, Duke University Medical Center, Durham, NC (K.L., Y.L.)
| | - M Daniele Fallin
- Departments of Mental Health and Epidemiology, Johns Hopkins University, Baltimore, MD (M.D.F.)
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio' TX (K.H., J.W.K., S.A.C.)
| | - Koren K Mann
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada (K.M., K.O.K., K.K.M.).,Department of Pharmacology and Therapeutics, McGill University, Montreal, Canada (K.K.M.)
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY (A.D.-R., R.A.G., K.S., M.G.-F., T.R.S., A.N.-A.)
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Oelsner EC, Krishnaswamy A, Balte PP, Allen NB, Ali T, Anugu P, Andrews H, Arora K, Asaro A, Barr RG, Bertoni AG, Bon J, Boyle R, Chang AA, Chen G, Coady S, Cole SA, Coresh J, Cornell E, Correa A, Couper D, Cushman M, Demmer RT, Elkind MSV, Folsom AR, Fretts AM, Gabriel KP, Gallo L, Gutierrez J, Han MLK, Henderson JM, Howard VJ, Isasi CR, Jacobs Jr DR, Judd SE, Mukaz DK, Kanaya AM, Kandula NR, Kaplan R, Kinney GL, Kucharska-Newton A, Lee JS, Lewis CE, Levine DA, Levitan EB, Levy B, Make B, Malloy K, Manly JJ, Mendoza-Puccini C, Meyer KA, Min YI, Moll M, Moore WC, Mauger D, Ortega VE, Palta P, Parker MM, Phipatanakul W, Post WS, Postow L, Psaty BM, Regan EA, Ring K, Roger VL, Rotter JI, Rundek T, Sacco RL, Schembri M, Schwartz DA, Seshadri S, Shikany JM, Sims M, Hinckley Stukovsky KD, Talavera GA, Tracy RP, Umans JG, Vasan RS, Watson K, Wenzel SE, Winters K, Woodruff PG, Xanthakis V, Zhang Y, Zhang Y, C4R Investigators FT. Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design. Am J Epidemiol 2022; 191:1153-1173. [PMID: 35279711 PMCID: PMC8992336 DOI: 10.1093/aje/kwac032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 01/26/2022] [Accepted: 02/09/2022] [Indexed: 01/26/2023] Open
Abstract
The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories.
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Affiliation(s)
- Elizabeth C Oelsner
- Correspondence to Dr. Elizabeth C Oelsner, MD MPH, Herbert Irving Associate Professor of Medicine, Division of General Medicine, Columbia University Irving Medical Center, 622 West 168 Street, PH9-105K New York, NY 10032 Tel: 917-880-7099
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Domingo-Relloso A, Riffo-Campos AL, Powers M, Tellez-Plaza M, Haack K, Brown RH, Umans JG, Fallin MD, Cole SA, Navas-Acien A, Sanchez TR. An epigenome-wide study of DNA methylation profiles and lung function among American Indians in the Strong Heart Study. Clin Epigenetics 2022; 14:75. [PMID: 35681244 PMCID: PMC9185990 DOI: 10.1186/s13148-022-01294-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/25/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Epigenetic modifications, including DNA methylation (DNAm), are often related to environmental exposures, and are increasingly recognized as key processes in the pathogenesis of chronic lung disease. American Indian communities have a high burden of lung disease compared to the national average. The objective of this study was to investigate the association of DNAm and lung function in the Strong Heart Study (SHS). We conducted a cross-sectional study of American Indian adults, 45-74 years of age who participated in the SHS. DNAm was measured using the Illumina Infinium Human MethylationEPIC platform at baseline (1989-1991). Lung function was measured via spirometry, including forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC), at visit 2 (1993-1995). Airflow limitation was defined as FEV1 < 70% predicted and FEV1/FVC < 0.7, restriction was defined as FEV1/FVC > 0.7 and FVC < 80% predicted, and normal spirometry was defined as FEV1/FVC > 0.7, FEV1 > 70% predicted, FVC > 80% predicted. We used elastic-net models to select relevant CpGs for lung function and spirometry-defined lung disease. We also conducted bioinformatic analyses to evaluate the biological plausibility of the findings. RESULTS Among 1677 participants, 21.2% had spirometry-defined airflow limitation and 13.6% had spirometry-defined restrictive pattern lung function. Elastic-net models selected 1118 Differentially Methylated Positions (DMPs) as predictors of airflow limitation and 1385 for restrictive pattern lung function. A total of 12 DMPs overlapped between airflow limitation and restrictive pattern. EGFR, MAPK1 and PRPF8 genes were the most connected nodes in the protein-protein interaction network. Many of the DMPs targeted genes with biological roles related to lung function such as protein kinases. CONCLUSION We found multiple differentially methylated CpG sites associated with chronic lung disease. These signals could contribute to better understand molecular mechanisms involved in lung disease, as assessed systemically, as well as to identify patterns that could be useful for diagnostic purposes. Further experimental and longitudinal studies are needed to assess whether DNA methylation has a causal role in lung disease.
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Affiliation(s)
- Arce Domingo-Relloso
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, 28029, Madrid, Spain. .,Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA. .,Department of Statistics and Operations Research, University of Valencia, Valencia, Spain.
| | - Angela L Riffo-Campos
- Millennium Nucleus on Sociomedicine (SocioMed) and Vicerrectoría Académica, Universidad de La Frontera, Temuco, Chile.,Department of Computer Science, ETSE, University of Valencia, Valencia, Spain
| | - Martha Powers
- United States Environmental Protection Agency, Washington, DC, USA
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, 28029, Madrid, Spain
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Robert H Brown
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA.,Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - M Daniele Fallin
- Departments of Mental Health and Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
| | - Tiffany R Sanchez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
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Patten CA, Hiratsuka VY, Nash SH, Day G, Redwood DG, Beans JA, Howard BV, Umans JG, Koller KR. Smoking Patterns Among Urban Alaska Native and American Indian Adults: The Alaska EARTH 10-Year Follow-up Study. Nicotine Tob Res 2022; 24:840-846. [PMID: 34850172 PMCID: PMC9048910 DOI: 10.1093/ntr/ntab245] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 11/16/2021] [Accepted: 11/22/2021] [Indexed: 11/13/2022]
Abstract
INTRODUCTION Data on cigarette smoking prevalence among Alaska Native and American Indian (ANAI) people are limited to cross-sectional studies or specific subpopulations. Using data from the Alaska Education and Research toward Health (EARTH) Study 10-year follow-up, this study assessed patterns of smoking from baseline and factors associated with current use. AIMS AND METHODS EARTH Study urban south central ANAI participants (N = 376; 73% women) provided questionnaire data on smoking at baseline and 10-year follow-up. Multivariable-adjusted logistic regression assessed whether gender, cultural factors (Tribal identity, language spoken in the home), depressive symptoms (PHQ-9), baseline smoking status, and baseline cigarettes per day (CPD) were associated with current smoking at follow-up. RESULTS Current smoking was 27% and 23% at baseline and follow-up, respectively. Of baseline smokers, 60% reported smoking at follow-up (77% men, 52% women). From multivariable-adjusted analyses, the odds of current smoking at follow-up were lower among women than men, those who never or formerly smoked versus currently smoked at baseline, and smoking <10 CPD compared with ≥10 CPD at baseline. PHQ-9 score or cultural variables were not associated with smoking at follow-up. Smoking fewer baseline CPD was associated with former smoking status (ie, quitting) at follow-up among women, but not men. CONCLUSIONS Our project is among the first to longitudinally explore smoking within an ANAI cohort. While we observed persistent smoking during a 10-year period, there were important differences by gender and CPD in quitting. These differences may be important to enhance the reach and efficacy of cessation interventions for ANAI people. IMPLICATIONS This study contributes novel longitudinal information on cigarette smoking prevalence during a 10-year period among Alaska Native and American Indian (ANAI) people. Prior data on smoking prevalence among ANAI people are limited to cross-sectional studies or specific subpopulations. Our project is among the first to longitudinally explore smoking prevalence within an ANAI cohort. We observed persistent smoking during a 10-year period. The study also contributes information on differences by gender and cigarettes smoked per day in quitting. These findings have implications for enhancing the reach and efficacy of cessation interventions for ANAI people.
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Affiliation(s)
- Christi A Patten
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Vanessa Y Hiratsuka
- Center for Human Development, University of Alaska Anchorage, Anchorage, AK, USA
- Research Department, Southcentral Foundation, Anchorage, AK, USA
| | - Sarah H Nash
- Alaska Native Epidemiology Center, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Gretchen Day
- Research Services, Division of Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Diana G Redwood
- Alaska Native Epidemiology Center, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Julie A Beans
- Research Department, Southcentral Foundation, Anchorage, AK, USA
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD, USA
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Kathryn R Koller
- Research Services, Division of Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
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Li M, Hilpert M, Goldsmith J, Brooks JL, Shearston JA, Chillrud SN, Ali T, Umans JG, Best LG, Yracheta J, van Donkelaar A, Martin RV, Navas-Acien A, Kioumourtzoglou MA. Air Pollution in American Indian Versus Non-American Indian Communities, 2000-2018. Am J Public Health 2022; 112:615-623. [PMID: 35319962 PMCID: PMC8961849 DOI: 10.2105/ajph.2021.306650] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/30/2021] [Indexed: 11/04/2022]
Abstract
Objectives. To compare fine particulate matter (PM2.5) concentrations in American Indian (AI)-populated with those in non-AI-populated counties over time (2000-2018) in the contiguous United States. Methods. We used a multicriteria approach to classify counties as AI- or non--AI-populated. We ran linear mixed effects models to estimate the difference in countywide annual PM2.5 concentrations from well-validated prediction models and monitoring sites (modeled and measured PM2.5, respectively) in AI- versus non-AI-populated counties. Results. On average, adjusted modeled PM2.5 concentrations in AI-populated counties were 0.38 micrograms per cubic meter (95% confidence interval [CI] = 0.23, 0.54) lower than in non-AI-populated counties. However, this difference was not constant over time: in 2000, modeled concentrations in AI-populated counties were 1.46 micrograms per cubic meter (95% CI = 1.25, 1.68) lower, and by 2018, they were 0.66 micrograms per cubic meter (95% CI = 0.45, 0.87) higher. Over the study period, adjusted modeled PM2.5 mean concentrations decreased by 2.13 micrograms per cubic meter in AI-populated counties versus 4.26 micrograms per cubic meter in non-AI-populated counties. Results were similar for measured PM2.5. Conclusions. This study highlights disparities in PM2.5 trends between AI- and non-AI-populated counties over time, underscoring the need to strengthen air pollution regulations and prevention implementation in tribal territories and areas where AI populations live. (Am J Public Health. 2022;112(4): 615-623. https://doi.org/10.2105/AJPH.2021.306650).
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Affiliation(s)
- Maggie Li
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Markus Hilpert
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Jeff Goldsmith
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Jada L Brooks
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Jenni A Shearston
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Steven N Chillrud
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Tauqeer Ali
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Jason G Umans
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Lyle G Best
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Joseph Yracheta
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Aaron van Donkelaar
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Randall V Martin
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Ana Navas-Acien
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
| | - Marianthi-Anna Kioumourtzoglou
- Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO
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Kuo CC, Balakrishnan P, Gribble MO, Best LG, Goessler W, Umans JG, Navas-Acien A. The association of arsenic exposure and arsenic metabolism with all-cause, cardiovascular and cancer mortality in the Strong Heart Study. Environ Int 2022; 159:107029. [PMID: 34890900 PMCID: PMC9123362 DOI: 10.1016/j.envint.2021.107029] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 12/03/2021] [Accepted: 12/03/2021] [Indexed: 05/24/2023]
Abstract
The effect of low-moderate levels of arsenic exposure and of arsenic metabolism on mortality remains uncertain. We used data from a prospective cohort study in 3600 men and women aged 45 to 75 years living in Arizona, Oklahoma, and North and South Dakota. The biomarker of inorganic arsenic exposure was the sum of urine inorganic (iAs), monomethylated (MMA) and dimethylated (DMA) arsenic compounds (ƩAs) at baseline. The proportions of urine iAs, MMA and DMA over the ƩiAs, expressed as iAs%, MMA%, and DMA%, respectively, were used as biomarkers of arsenic metabolism. Arsenic exposure and arsenic metabolism were associated with all-cause, cardiovascular, and cancer mortality. For each interquartile range (IQR) increase in ƩAs (12.5 μg/L, overall range 0.7-194.1 μg/L), the adjusted hazard ratios (aHRs) were 1.28 (95% CI 1.16-1.41) for all-cause mortality, 1.28 (1.08-1.52) for cardiovascular mortality and 1.15 (0.92-1.44) for cancer mortality. The aHR for mortality for each IQR increase in MMA%, when iAs% is decreasing, was 1.52 (95% CI 1.16-1.99) for cardiovascular disease, 0.73 (0.55-0.98) for cancer, and 1.03 (0.90-1.19) for all-cause mortality. These findings at low-moderate levels of arsenic exposure highlight the need to implement public health measures to protect populations from involuntary arsenic exposure and for research to advance the biological and clinical understanding of arsenic-related health effects in general populations.
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Affiliation(s)
- Chin-Chi Kuo
- Big Data Center, China Medical University Hospital and China Medical University, Taichung, Taiwan; Division of Nephrology, Department of Internal Medicine, China Medical University Hospital and China Medical University, Taichung, Taiwan; Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, MD, USA.
| | - Poojitha Balakrishnan
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, NY, USA
| | - Matthew O Gribble
- Department of Environmental Health, Emory University, Atlanta, GA, USA; Department of Epidemiology, Emory University, Atlanta, GA, USA
| | - Lyle G Best
- Missouri Breaks Industries Research, Inc., Timber Lake, South Dakota
| | - Walter Goessler
- Institute of Chemistry - Analytical Chemistry, Karl-Franzens University Graz, Graz, Austria
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, MD, USA; Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, NY, USA
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Smyth SS, Coller BS, Jackson RD, Kern PA, McIntosh S, Meagher EA, Rubio DM, Sandberg K, Tsevat J, Umans JG, Attia J, Baker HL, Nagel JD, McMullen CA, Rosemond E. KL2 scholars' perceptions of factors contributing to sustained translational science career success. J Clin Transl Sci 2021; 6:e34. [PMID: 35433037 PMCID: PMC9003634 DOI: 10.1017/cts.2021.886] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 12/21/2021] [Accepted: 12/22/2021] [Indexed: 11/05/2022] Open
Abstract
Introduction Identifying the most effective ways to support career development of early stage investigators in clinical and translational science should yield benefits for the biomedical research community. Institutions with Clinical and Translational Science Awards (CTSA) offer KL2 programs to facilitate career development; however, the sustained impact has not been widely assessed. Methods A survey comprised of quantitative and qualitative questions was sent to 2144 individuals that had previously received support through CTSA KL2 mechanisms. The 547 responses were analyzed with identifying information redacted. Results Respondents held MD (47%), PhD (36%), and MD/PhD (13%) degrees. After KL2 support was completed, physicians' time was divided 50% to research and 30% to patient care, whereas PhD respondents devoted 70% time to research. Funded research effort averaged 60% for the cohort. Respondents were satisfied with their career progression. More than 95% thought their current job was meaningful. Two-thirds felt confident or very confident in their ability to sustain a career in clinical and translational research. Factors cited as contributing to career success included protected time, mentoring, and collaborations. Conclusion This first large systematic survey of KL2 alumni provides valuable insight into the group's perceptions of the program and outcome information. Former scholars are largely satisfied with their career choice and direction, national recognition of their expertise, and impact of their work. Importantly, they identified training activities that contributed to success. Our results and future analysis of the survey data should inform the framework for developing platforms to launch sustaining careers of translational scientists.
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Affiliation(s)
- Susan S. Smyth
- University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | | | | | | | | | | | | | | | - Joel Tsevat
- University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | | | | | - Heather L. Baker
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Joan D. Nagel
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | | | - Erica Rosemond
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
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Sancheznieto F, Sorkness CA, Attia J, Buettner K, Edelman D, Hobbs S, McIntosh S, McManus LM, Sandberg K, Schnaper HW, Scholl L, Umans JG, Weavers K, Windebank A, McCormack WT. Clinical and translational science award T32/TL1 training programs: program goals and mentorship practices. J Clin Transl Sci 2021; 6:e13. [PMID: 35211339 PMCID: PMC8826009 DOI: 10.1017/cts.2021.884] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 12/15/2021] [Accepted: 12/16/2021] [Indexed: 01/29/2023] Open
Abstract
INTRODUCTION A national survey characterized training and career development for translational researchers through Clinical and Translational Science Award (CTSA) T32/TL1 programs. This report summarizes program goals, trainee characteristics, and mentorship practices. METHODS A web link to a voluntary survey was emailed to 51 active TL1 program directors and administrators. Descriptive analyses were performed on aggregate data. Qualitative data analysis used open coding of text followed by an axial coding strategy based on the grounded theory approach. RESULTS Fifty out of 51 (98%) invited CTSA hubs responded. Training program goals were aligned with the CTSA mission. The trainee population consisted of predoctoral students (50%), postdoctoral fellows (30%), and health professional students in short-term (11%) or year-out (9%) research training. Forty percent of TL1 programs support both predoctoral and postdoctoral trainees. Trainees are diverse by academic affiliation, mostly from medicine, engineering, public health, non-health sciences, pharmacy, and nursing. Mentor training is offered by most programs, but mandatory at less than one-third of them. Most mentoring teams consist of two or more mentors. CONCLUSIONS CTSA TL1 programs are distinct from other NIH-funded training programs in their focus on clinical and translational research, cross-disciplinary approaches, emphasis on team science, and integration of multiple trainee types. Trainees in nearly all TL1 programs were engaged in all phases of translational research (preclinical, clinical, implementation, public health), suggesting that the CTSA TL1 program is meeting the mandate of NCATS to provide training to develop the clinical and translational research workforce.
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Affiliation(s)
- Fátima Sancheznieto
- University of Wisconsin Institute for Clinical and Translational Research, Madison, WI, USA
| | - Christine A. Sorkness
- University of Wisconsin Institute for Clinical and Translational Research, Madison, WI, USA
| | - Jacqueline Attia
- Center for Leading Innovation and Collaboration, Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | - Kathryn Buettner
- Center for Leading Innovation and Collaboration, Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | - David Edelman
- Division of General Internal Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Stuart Hobbs
- The Ohio State University, Center for Clinical and Translational Science, Columbus, OH, USA
| | - Scott McIntosh
- Center for Leading Innovation and Collaboration, Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | | | - Kathryn Sandberg
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - H. William Schnaper
- Northwestern University Clinical and Translational Sciences Institute, Northwestern University, Chicago, IL, USA
| | | | - Jason G. Umans
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | | | | | - Wayne T. McCormack
- Clinical & Translational Science Institute, Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA
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Miao G, Zhang Y, Huo Z, Zeng W, Zhu J, Umans JG, Wohlgemuth G, Pedrosa D, DeFelice B, Cole SA, Fretts AM, Lee ET, Howard BV, Fiehn O, Zhao J. Longitudinal Plasma Lipidome and Risk of Type 2 Diabetes in a Large Sample of American Indians With Normal Fasting Glucose: The Strong Heart Family Study. Diabetes Care 2021; 44:2664-2672. [PMID: 34702783 PMCID: PMC8669540 DOI: 10.2337/dc21-0451] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 08/03/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Comprehensive assessment of alterations in lipid species preceding type 2 diabetes (T2D) is largely unknown. We aimed to identify plasma molecular lipids associated with risk of T2D in American Indians. RESEARCH DESIGN AND METHODS Using untargeted liquid chromatography-mass spectrometry, we repeatedly measured 3,907 fasting plasma samples from 1,958 participants who attended two examinations (∼5.5 years apart) and were followed up to 16 years in the Strong Heart Family Study. Mixed-effects logistic regression was used to identify lipids associated with risk of T2D, adjusting for traditional risk factors. Repeated measurement analysis was performed to examine the association between change in lipidome and change in continuous measures of T2D, adjusting for baseline lipids. Multiple testing was controlled by false discovery rate at 0.05. RESULTS Higher baseline level of 33 lipid species, including triacylglycerols, diacylglycerols, phosphoethanolamines, and phosphocholines, was significantly associated with increased risk of T2D (odds ratio [OR] per SD increase in log2-transformed baseline lipids 1.50-2.85) at 5-year follow-up. Of these, 21 lipids were also associated with risk of T2D at 16-year follow-up. Aberrant lipid profiles were also observed in prediabetes (OR per SD increase in log2-transformed baseline lipids 1.30-2.19 for risk lipids and 0.70-0.78 for protective lipids). Longitudinal changes in 568 lipids were significantly associated with changes in continuous measures of T2D. Multivariate analysis identified distinct lipidomic signatures differentiating high- from low-risk groups. CONCLUSIONS Lipid dysregulation occurs many years preceding T2D, and novel molecular lipids (both baseline level and longitudinal change over time) are significantly associated with risk of T2D beyond traditional risk factors. Our findings shed light on the mechanisms linking dyslipidemia to T2D and may yield novel therapeutic targets for early intervention tailored to American Indians.
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Affiliation(s)
- Guanhong Miao
- Department of Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL
| | - Ying Zhang
- West Coast Metabolomics Center, University of California Davis, Davis, CA
| | - Zhiguang Huo
- Department of Biostatistics, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL
| | - Wenjie Zeng
- Department of Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL
| | - Jianhui Zhu
- MedStar Health Research Institute, Hyattsville, MD
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD.,Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Gert Wohlgemuth
- West Coast Metabolomics Center, University of California Davis, Davis, CA
| | - Diego Pedrosa
- West Coast Metabolomics Center, University of California Davis, Davis, CA
| | - Brian DeFelice
- West Coast Metabolomics Center, University of California Davis, Davis, CA
| | | | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Elisa T Lee
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | | | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA
| | - Jinying Zhao
- Department of Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL
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Scarton L, Hebert LE, Goins RT, Umans JG, Jiang L, Comiford A, Chen S, White A, Ritter T, Manson SM. Diabetes and health-related quality of life among American Indians: the role of psychosocial factors. Qual Life Res 2021; 30:2497-2507. [PMID: 33837892 PMCID: PMC8658625 DOI: 10.1007/s11136-021-02830-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/20/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE Little is known about the association of psychosocial factors with health-related quality of life (HRQoL) among American Indians with type 2 diabetes (T2D). This study described functional social support, emotional support, coping, resilience, post-traumatic stress disorder, and HRQoL, among American Indians by diabetes status and, among those with diabetes, examined the association of these factors with HRQoL. METHODS Using data from the Cherokee Nation Health Survey collected between 2017 and 2019, we evaluated differences in each measure of interest according to diabetes status, using t-test and Chi-squared tests of association. We used weighted multiple logistic regression to examine associations between multiple psychosocial factors and HRQoL among those with diabetes. RESULTS Compared to individuals without diabetes, participants with diabetes rated their functional social support (4.62 vs. 4.56, respectively) and coping (2.65 vs. 2.61, respectively) slightly lower and were more likely to report ≥ 15 days of poor physical (14% vs. 26%, respectively) and mental health (14% vs. 17%, respectively) in the past month. Odds of reporting poor overall health increased more than sixfold for those who were dissatisfied/very dissatisfied with life (AOR = 6.70). Resilience scores reduced odds of reporting ≥ 15 days with poor physical health, while experiences of post-traumatic stress doubled these odds. CONCLUSION Our study yielded insights into the risk as well as protective factors associated with diabetes outcomes in a large sample of American Indians with T2D. Researchers should design pragmatic trials that deepen understanding of preventive as well as treatment leverage through greater attention to experiences that compromise HRQoL.
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Affiliation(s)
- Lisa Scarton
- College of Nursing, University of Florida, 1225 Center Drive, Gainesville, FL, 32603, USA.
| | - Luciana E Hebert
- Department of Medical Education and Clinical Sciences, Washington State University, Seattle, WA, USA
| | - R Turner Goins
- College of Health and Human Sciences, Western Carolina University, Cullowhee, NC, USA
| | - Jason G Umans
- Georgetown-Howard Universities Center for Clinical and Translational Science and MedStar Health Research Institute, Washington, DC, USA
| | - Luohua Jiang
- Department of Epidemiology, University of California, Irvine, CA, USA
| | | | - Sixia Chen
- Health Sciences Center, The University of Oklahoma, Oklahoma, OK, USA
| | - Ashley White
- Health Sciences Center, The University of Oklahoma, Oklahoma, OK, USA
| | | | - Spero M Manson
- Colorado School of Public Health, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
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Navas-Acien A, Domingo-Relloso A, Subedi P, Riffo-Campos AL, Xia R, Gomez L, Haack K, Goldsmith J, Howard BV, Best LG, Devereux R, Tauqeer A, Zhang Y, Fretts AM, Pichler G, Levy D, Vasan RS, Baccarelli AA, Herreros-Martinez M, Tang WY, Bressler J, Fornage M, Umans JG, Tellez-Plaza M, Fallin MD, Zhao J, Cole SA. Blood DNA Methylation and Incident Coronary Heart Disease: Evidence From the Strong Heart Study. JAMA Cardiol 2021; 6:1237-1246. [PMID: 34347013 DOI: 10.1001/jamacardio.2021.2704] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Importance American Indian communities experience a high burden of coronary heart disease (CHD). Strategies are needed to identify individuals at risk and implement preventive interventions. Objective To investigate the association of blood DNA methylation (DNAm) with incident CHD using a large number of methylation sites (cytosine-phosphate-guanine [CpG]) in a single model. Design, Setting, and Participants This prospective study, including a discovery cohort (the Strong Heart Study [SHS]) and 4 additional cohorts (the Women's Health Initiative [WHI], the Framingham Heart Study [FHS], the Atherosclerosis Risk in Communities Study ([ARIC]-Black, and ARIC-White), evaluated 12 American Indian communities in 4 US states; African American women, Hispanic women, and White women throughout the US; White men and White women from Massachusetts; and Black men and women and White men and women from 4 US communities. A total of 2321 men and women (mean [SD] follow-up, 19.1 [9.2] years) were included in the SHS, 1874 women (mean [SD] follow-up, 15.8 [5.9] years) in the WHI, 2128 men and women (mean [SD] follow-up, 7.7 [1.8] years) in the FHS, 2114 men and women (mean [SD] follow-up, 20.9 [7.2] years) in the ARIC-Black, and 931 men and women (mean [SD] follow-up, 20.9 [7.2] years) in the ARIC-White. Data were collected from May 1989 to December 2018 and analyzed from February 2019 to May 2021. Exposure Blood DNA methylation. Main Outcome and Measure Using a high-dimensional time-to-event elastic-net model for the association of 407 224 CpG sites with incident CHD in the SHS (749 events), this study selected the differentially methylated CpG positions (DMPs) selected in the SHS and evaluated them in the WHI (531 events), FHS (143 events), ARIC-Black (350 events), and ARIC-White (121 events) cohorts. Results The median (IQR) age of participants in SHS was 55 (49-62) years, and 1359 participants (58.6%) were women. Elastic-net models selected 505 DMPs associated with incident CHD in the SHS beyond established risk factors, center, blood cell counts, and genetic principal components. Among those DMPs, 33 were commonly selected in 3 or 4 of the other cohorts and the pooled hazard ratios from the standard Cox models were significant at P < .05 for 10 of the DMPs. For example, the hazard ratio (95% CI) for CHD comparing the 90th and 10th percentiles of differentially methylated CpGs was 0.86 (0.78-0.95) for cg16604233 (tagged to COL11A2) and 1.23 (1.08-1.39) for cg09926486 (tagged to FRMD5). Some of the DMPs were consistent in the direction of the association; others showed associations in opposite directions across cohorts. Untargeted independent elastic-net models of CHD showed distinct DMPs, genes, and network of genes in the 5 cohorts. Conclusions and Relevance In this multi-cohort study, blood-based DNAm findings supported an association between a complex blood epigenomic signature and CHD that was largely different across populations.
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Affiliation(s)
- Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | - Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York.,Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain.,Department of Statistics and Operations Research, University of Valencia, Valencia, Spain
| | - Pooja Subedi
- College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville
| | | | - Rui Xia
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston
| | - Lizbeth Gomez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio
| | - Jeff Goldsmith
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York
| | | | - Lyle G Best
- Missouri Breaks Industries Research Inc, Eagle Butte, South Dakota
| | | | - Ali Tauqeer
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle
| | - Gernot Pichler
- Department of Cardiology, Heart Center Clinic Floridsdorf, Vienna, Austria
| | - Daniel Levy
- National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts.,Section of Preventive Medicine and Epidemiology and Section of Cardiovascular Medicine, Department of Medicine, Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Ramachandran S Vasan
- National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts.,Section of Preventive Medicine and Epidemiology and Section of Cardiovascular Medicine, Department of Medicine, Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | | | - Wan-Yee Tang
- Department of Occupational and Environmental Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston.,Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston
| | - Jason G Umans
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York.,Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - M Daniele Fallin
- Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland.,Department of Mental Health, Johns Hopkins University, Baltimore, Maryland
| | - Jinying Zhao
- College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio
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Schaefer KR, Fyfe-Johnson AL, Noonan CJ, Todd MR, Umans JG, Castille DM, Rosenman R, Buchwald DS, Dillard DA, Robinson RF, Muller CJ. Home Blood Pressure Monitoring Devices: Device Performance in an Alaska Native and American Indian Population. J Aging Health 2021; 33:40S-50S. [PMID: 34167348 DOI: 10.1177/08982643211013692] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Objectives: Home blood pressure monitoring (HBPM) is an important component of blood pressure (BP) management. We assessed performance of two HBPM devices among Alaska Native and American Indian people (ANAIs). Methods: We measured BP using Omron BP786 arm cuff, Omron BP654 wrist cuff, and Baum aneroid sphygmomanometer in 100 ANAIs. Performance was assessed with intraclass correlation, paired t-tests, and calibration models. Results: Compared to sphygmomanometer, average BP was higher for wrist cuff (systolic = 4.8 mmHg and diastolic = 3.6 mmHg) and varied for arm cuff (systolic = -1.5 mmHg and diastolic = 2.5 mmHg). Calibration increased performance from grade B to A for arm cuff and from D to B for wrist cuff. Calibration increased false negatives and decreased false positives. Discussion: The arm HBPM device is more accurate than the wrist cuff among ANAIs with hypertension. Most patients are willing to use the arm cuff when accuracy is discussed.
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Affiliation(s)
| | | | | | | | - Jason G Umans
- 121577MedStar Health Research Institute, Hyattsville, MD, USA
- 553614Georgetown-Howard Universities Center for Clinical and Translational Science, Washington DC, USA
| | - Dorothy M Castille
- 35051National Institute on Minority Health and Health Disparities, Bethesda, MD, USA
| | | | | | | | - Renee F Robinson
- College of Pharmacy, Idaho State University, 3291University of Alaska Anchorage, Anchorage, AK, USA
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46
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Kaufman JA, Mattison C, Fretts AM, Umans JG, Cole SA, Voruganti VS, Goessler W, Best LG, Zhang Y, Tellez-Plaza M, Navas-Acien A, Gribble MO. Arsenic, blood pressure, and hypertension in the Strong Heart Family Study. Environ Res 2021; 195:110864. [PMID: 33581093 PMCID: PMC8021390 DOI: 10.1016/j.envres.2021.110864] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 02/02/2021] [Accepted: 02/05/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Arsenic has been associated with hypertension, though it is unclear whether associations persist at the exposure concentrations (e.g. <100 μg/L) in drinking water occurring in parts of the Western United States. METHODS We assessed associations between arsenic biomarkers and systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension in the Strong Heart Family Study, a family-based cohort of American Indians from the Northern plains, Southern plains, and Southwest. We included 1910 participants from three study centers with complete baseline visit data (2001-2003) in the cross-sectional analysis of all three outcomes, and 1453 participants in the prospective analysis of incident hypertension (follow-up 2006-2009). We used generalized estimating equations with exchangeable correlation structure conditional on family membership to estimate the association of arsenic exposure biomarker levels with SBP or DBP (linear regressions) or hypertension prevalence and incidence (Poisson regressions), adjusting for urine creatinine, urine arsenobetaine, and measured confounders. RESULTS We observed cross-sectional associations for a two-fold increase in inorganic and methylated urine arsenic species of 0.64 (95% CI: 0.07, 1.35) mm Hg for SBP, 0.49 (95% CI: 0.03, 1.02) mm Hg for DBP, and a prevalence ratio of 1.10 (95% CI: 1.01, 1.21) for hypertension in fully adjusted models. During follow-up, 14% of subjects developed hypertension. We observed non-monotonic relationships between quartiles of arsenic and incident hypertension. Effect estimates were null for incident hypertension with continuous exposure metrics. Stratification by study site revealed elevated associations in Arizona, the site with the highest arsenic levels, while results for Oklahoma and North and South Dakota were largely null. Blood pressure changes with increasing arsenic concentrations were larger for those with diabetes at baseline. CONCLUSIONS Our results suggest a modest cross-sectional association of arsenic exposure biomarkers with blood pressure, and possible non-linear effects on incident hypertension.
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Affiliation(s)
- John A Kaufman
- Department of Epidemiology, Emory University, Atlanta, GA, USA.
| | - Claire Mattison
- Department of Environmental Health, Emory University, Atlanta, GA, USA
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, USA
| | - Jason G Umans
- Department of Medicine, Georgetown University Medical Center, Washington, DC, USA
| | - Shelley A Cole
- Texas Biomedical Research Institute, San Antonio, TX, USA
| | - V Saroja Voruganti
- Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA
| | | | - Lyle G Best
- Missouri Breaks Industries Research, Inc., Eagle Butte, SD, United States
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University, New York, NY, USA
| | - Matthew O Gribble
- Department of Epidemiology, Emory University, Atlanta, GA, USA; Department of Environmental Health, Emory University, Atlanta, GA, USA
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47
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Oelsner EC, Allen NB, Ali T, Anugu P, Andrews H, Asaro A, Balte PP, Barr RG, Bertoni AG, Bon J, Boyle R, Chang AA, Chen G, Cole SA, Coresh J, Cornell E, Correa A, Couper D, Cushman M, Demmer RT, Elkind MSV, Folsom AR, Fretts AM, Gabriel KP, Gallo L, Gutierrez J, Han MK, Henderson JM, Howard VJ, Isasi CR, Jacobs DR, Judd SE, Mukaz DK, Kanaya AM, Kandula NR, Kaplan R, Krishnaswamy A, Kinney GL, Kucharska-Newton A, Lee JS, Lewis CE, Levine DA, Levitan EB, Levy B, Make B, Malloy K, Manly JJ, Meyer KA, Min YI, Moll M, Moore WC, Mauger D, Ortega VE, Palta P, Parker MM, Phipatanakul W, Post W, Psaty BM, Regan EA, Ring K, Roger VL, Rotter JI, Rundek T, Sacco RL, Schembri M, Schwartz DA, Seshadri S, Shikany JM, Sims M, Hinckley Stukovsky KD, Talavera GA, Tracy RP, Umans JG, Vasan RS, Watson K, Wenzel SE, Winters K, Woodruff PG, Xanthakis V, Zhang Y, Zhang Y. Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design. medRxiv 2021:2021.03.19.21253986. [PMID: 33758891 PMCID: PMC7987050 DOI: 10.1101/2021.03.19.21253986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults at risk for coronavirus disease 2019 (COVID-19) comprising 14 established United States (US) prospective cohort studies. For decades, C4R cohorts have collected extensive data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R will link this pre-COVID phenotyping to information on SARS-CoV-2 infection and acute and post-acute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and broadly reflects the racial, ethnic, socioeconomic, and geographic diversity of the US. C4R is ascertaining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations, and high-quality events surveillance. Extensive pre-pandemic data minimize referral, survival, and recall bias. Data are being harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these will be pooled and shared widely to expedite collaboration and scientific findings. This unique resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including post-acute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term trajectories of health and aging.
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48
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Lemaitre RN, Jensen PN, Zeigler M, Denham J, Fretts AM, Umans JG, Howard BV, Sitlani CM, McKnight B, Gharib SA, King IB, Siscovick DS, Psaty BM, Sotoodehnia N, Totah RA. Plasma epoxyeicosatrienoic acids and dihydroxyeicosatrieonic acids, insulin, glucose and risk of diabetes: The strong heart study. EBioMedicine 2021; 66:103279. [PMID: 33752126 PMCID: PMC8010619 DOI: 10.1016/j.ebiom.2021.103279] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 02/24/2021] [Accepted: 02/25/2021] [Indexed: 12/28/2022] Open
Abstract
Background Epoxyeicosatrienoic acids (EETs) are metabolites of arachidonic acid with multiple biological functions. Rodent experiments suggest EETs play a role in insulin sensitivity and diabetes, but evidence in humans is limited. To address this knowledge gap, we conducted a case-cohort study in the Strong Heart Family Study, a prospective cohort among American Indians. Methods We measured 4 EET species and 4 species of corresponding downstream metabolites, dihydroxyeicosatrieonic acids (DHETs), in plasma samples from 1161 participants, including 310 with type 2 diabetes. We estimated the associations of total (esterified and free) EETs and DHETs with incident diabetes risk, adjusting for known risk factors. We also examined cross-sectional associations with plasma fasting insulin and glucose in the case-cohort and in 271 participants without diabetes from the older Strong Heart Study cohort, and meta-analyzed the results from the 2 cohorts. Findings We observed no significant association of total EET or DHET levels with incident diabetes. In addition, plasma EETs were not associated with plasma insulin or plasma glucose. However, higher plasma 14,15-DHET was associated with lower plasma insulin and lower plasma glucose. Interpretation In this first prospective study of EETs and diabetes, we found no evidence for a role of total plasma EETs in diabetes. The novel associations of 14,15-DHET with insulin and glucose warrant replication and exploration of possible mechanisms. Funding US National Institutes of Health
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Affiliation(s)
- Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
| | - Paul N Jensen
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Maxwell Zeigler
- Department of Medicinal Chemistry, University of Washington, Seattle, WA, USA
| | - Julie Denham
- Department of Medicinal Chemistry, University of Washington, Seattle, WA, USA
| | - Amanda M Fretts
- Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown and Howard Universities Center for Translational Science, Washington DC, USA
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Barbara McKnight
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Sina A Gharib
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Irena B King
- Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | | | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, WA, USA; Kaiser Permanente Washington Health Research Institute, Seattle, WA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Rheem A Totah
- Department of Medicinal Chemistry, University of Washington, Seattle, WA, USA
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49
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Lewis JP, Suchy-Dicey AM, Noonan C, Jernigan VBB, Umans JG, Domoto-Reilly K, Buchwald DS, Manson S. Associations of Binge Drinking With Vascular Brain Injury and Atrophy in Older American Indians: The Strong Heart Study. J Aging Health 2021; 33:51S-59S. [PMID: 34167344 PMCID: PMC8845484 DOI: 10.1177/08982643211013696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Objectives: American Indians (AIs) generally consume less alcohol than the US general population; however, the prevalence of alcohol use disorder is higher. This is the first large cohort study to examine binge drinking as a risk factor for vascular brain injury (VBI). Methods: We used linear and Poisson regression to examine the association of self-reported binge drinking with VBI, measured via magnetic resonance imaging (MRI), in 817 older AIs who participated in the Strong Heart and Cerebrovascular Disease and Its Consequences in American Indians studies. Results: Any binge drinking at multiple time-points was associated with increased sulcal (β = 0.360, 95% CI [0.079, 0.641]) and ventricle dilatation (β = 0.512, 95% CI [0.174, 0.850]) compared to no binge drinking. Discussion: These observed associations are consistent with previous findings. Identifying how binge drinking may contribute to VBI in older AIs may suggest modifiable health behaviors for neurological risk reduction and disease prevention.
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Affiliation(s)
- Jordan P. Lewis
- University of Alaska Anchorage, WWAMI School of Medical Education, College of Health
| | - Astrid M Suchy-Dicey
- Institute for Research and Education to Advance Community Health, Washington State University,Elson S Floyd College of Medicine, Washington State University
| | - Carolyn Noonan
- Institute for Research and Education to Advance Community Health, Washington State University,Elson S Floyd College of Medicine, Washington State University
| | | | - Jason G. Umans
- MedStar Health Research Institute, Hyattsville, MD; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | | | - Dedra S Buchwald
- Institute for Research and Education to Advance Community Health, Washington State University,Elson S Floyd College of Medicine, Washington State University
| | - Spero Manson
- Centers for American Indian and Alaska Native Health, University of Colorado Anschutz Medical Campus
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50
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Koller KR, Day GE, Hiratsuka VY, Beans JA, Nash SH, Redwood DG, Zhu J, Howard BV, Umans JG. Increase in diabetes among urban Alaska Native people in the Alaska EARTH follow-up study: A call for prediabetes screening, diagnosis, and referral for intervention. Diabetes Res Clin Pract 2020; 167:108357. [PMID: 32745696 PMCID: PMC7530054 DOI: 10.1016/j.diabres.2020.108357] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 07/12/2020] [Accepted: 07/28/2020] [Indexed: 11/30/2022]
Abstract
AIMS This study estimates incidence of diabetes (DM) and pre-DM relative to DM risk factors among relatively healthy Alaska Native and American Indian (henceforth AN) adults living in urban south central Alaska. METHODS Baseline (2004-2006) and follow-up (2014-2017) surveys, blood samples, and medical chart review data were collected from AN adults living in south central Alaska. We analyzed associations between prevalent risk factors and incident DM and pre-DM using Cox proportional hazards and used multivariable models to identify independent predictors for both DM and pre-DM. RESULTS Among 379 participants with follow-up data, overall DM incidence was 16.5/1,000 PY; overall pre-DM incidence was 77.6/1,000 PY, with marked differences between men and women. Prevalent cardiometabolic risk factors also varied with greater amounts of overweight in men and greater amounts of obesity in women. Controlling for age and sex, obesity, abdominal adiposity, pre-DM, and metabolic syndrome independently increased DM risk. CONCLUSION Health care providers of AN populations must seize the opportunity to screen, refer, and treat individuals with pre-DM and other modifiable DM risk factors prior to DM diagnosis if we are to alter the epidemiologic course of disease progression in this urban AN population.
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Affiliation(s)
- Kathryn R Koller
- Clinical and Research Services, Alaska Native Tribal Health Consortium, Anchorage, AK, United States.
| | - Gretchen E Day
- Clinical and Research Services, Alaska Native Tribal Health Consortium, Anchorage, AK, United States
| | | | - Julie A Beans
- Research Department, Southcentral Foundation, Anchorage, AK, United States
| | - Sarah H Nash
- Alaska Native Epidemiology Center, Alaska Native Tribal Health Consortium, Anchorage, AK, United States
| | - Diana G Redwood
- Alaska Native Epidemiology Center, Alaska Native Tribal Health Consortium, Anchorage, AK, United States
| | - Jianhui Zhu
- Medstar Health Research Institute, Hyattsville, MD, United States
| | - Barbara V Howard
- Medstar Health Research Institute, Hyattsville, MD, United States; Georgetown/Howard Universities, Center for Clinical and Translational Research, Washington, DC, United States
| | - Jason G Umans
- Medstar Health Research Institute, Hyattsville, MD, United States; Georgetown/Howard Universities, Center for Clinical and Translational Research, Washington, DC, United States
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