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Li D, An B, Men L, Glittenberg M, Lutsey PL, Mielke MM, Yu F, Hoogeveen RC, Gottesman R, Zhang L, Meyer M, Sullivan K, Zantek N, Alonso A, Walker KA. The association of high-density lipoprotein cargo proteins with brain volume in older adults in the Atherosclerosis Risk in Communities (ARIC). J Alzheimers Dis 2025:13872877241305806. [PMID: 39772982 DOI: 10.1177/13872877241305806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Abstract
BACKGROUND High-density lipoprotein (HDL) modulates the blood-brain barrier and cerebrovascular integrity, likely influencing the risk of Alzheimer's disease (AD), neurodegeneration, and cognitive decline. OBJECTIVE This study aims to identify HDL protein cargo associated with brain amyloid deposition and brain volume in regions vulnerable to AD pathology in older adults. METHODS HDL was separated from the plasma of 65 non-demented participants of the Atherosclerosis Risk in Communities (ARIC) study using a fast protein liquid chromatography method. HDL cargo proteins were measured using a label-free, untargeted proteomic method based on mass spectrometry and data-independent acquisition. Linear regression with multiple imputations assessed the associations between each HDL cargo protein (log2-transformed) and brain amyloid deposition or temporal-parietal meta-ROI volume, adjusting for covariates. RESULTS The mean (SD) age of the participants was 76.3 (5.4) years old, 53.8% (35/65) female, 30.8% (20/65) black, and 28.1% (18/64, 1 missing) APOE4 carriers. We found few HDL cargo proteins associated with brain amyloid deposition and considerably more HDL cargo proteins associated with temporal-parietal meta-ROI volume. Two HDL cargo proteins mostly associated with temporoparietal meta-ROI volume were fibrinogen B (FGB) and plasminogen (PLG). A doubling of FGB in HDL was associated with a greater temporoparietal meta-ROI volume of 1638 mm3 (95% CI [688, 2589]). In comparison, a doubling of PLG in HDL was associated with a lower temporoparietal meta-ROI of 2025 mm3 (95% CI [-3669, -1034]). CONCLUSIONS This study suggests that HDL cargo proteins associated with temporal-parietal meta-ROI volume are involved in complement and coagulation pathways.
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Affiliation(s)
- Danni Li
- Department of Lab Medicine Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Binchong An
- Department of Lab Medicine Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lu Men
- Department of Lab Medicine Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Matthew Glittenberg
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Pamela L Lutsey
- School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Fang Yu
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, USA
| | - Ron C Hoogeveen
- Division of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Rebecca Gottesman
- Stroke, Cognition, and Neuroepidemiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Lin Zhang
- School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Michelle Meyer
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kevin Sullivan
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Nicole Zantek
- Department of Lab Medicine Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Keenan A Walker
- Multimodal Imaging of Neurodegenerative Disease (MIND) Unit, National Institute of Aging, Intramural Research Program, Baltimore, MD, USA
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2
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Lin PJ, Abraham AG, Ramulu P, Mihailovic A, Kucharska-Newton A, Guo X. Social Determinants of Uncorrected Distance and Near Visual Impairment in an Older Adult Population. Transl Vis Sci Technol 2025; 14:8. [PMID: 39792056 DOI: 10.1167/tvst.14.1.8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2025] Open
Abstract
Purpose Uncorrected visual impairment (VI) significantly impacts life quality and exacerbates age-related health issues. Social determinants of health (SDOH) are associated with uncorrected VI, but quantitative evidence is limited. This study investigated the link between SDOH and uncorrected VI among aging adults to identify disparities and improve vision care. Methods We used data from the Atherosclerosis Risk in Communities (ARIC) study visits 4 and 6 and the ancillary Eye Determinants of Cognition (EyeDOC) study. We included subjects who were >70 years old and extracted their sex, race, residence, household income, education level, having an eye doctor, health insurance status, and Area Deprivation Index (ADI) and vision outcomes. Uncorrected VI was categorized into uncorrected distance (UDVI) or near visual impairment (UNVI). Associations between SDOH indicators and VI were evaluated using logistic regressions. Results Among 967 adults (mean ± SD age, 78.6 ± 4.35 years; 37.9% male), UDVI was found in 293 and UNVI in 186. Living in Jackson, MS, was associated with lower odds for UNVI (adjusted odds ratio [aOR] = 0.36; 95% CI, 0.20-0.65). Higher odds for UNVI were associated with male sex (aOR = 2.01; 95% CI, 1.41-2.87), low educational attainment (aOR for not completing high school = 2.32; 95% CI, 1.37-3.92; aOR for high school only = 1.92; 95% CI, 1.26-2.92), no eye doctor (aOR = 1.58; 95% CI, 1.05-2.39), and having government health insurance only (aOR = 1.48; 95% CI, 1.00-2.17). Associations between SDOH factors and UDVI were weaker or non-existent. Conclusions This study links SDOH factors to uncorrected VI among older adults. Translational Relevance SDOH should be considered when designing interventions to reduce VI in vulnerable communities.
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Affiliation(s)
- Po-Jen Lin
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Medicine, Nuvance Health Danbury Hospital, Danbury, CT, USA
| | - Alison G Abraham
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
- Department of Ophthalmology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Pradeep Ramulu
- Wilmer Eye Institute, Johns Hopkins University, Baltimore, MD, USA
| | - Aleks Mihailovic
- Wilmer Eye Institute, Johns Hopkins University, Baltimore, MD, USA
| | - Anna Kucharska-Newton
- University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Xinxing Guo
- Wilmer Eye Institute, Johns Hopkins University, Baltimore, MD, USA
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3
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Bennett EE, Liu C, Stapp EK, Gianattasio KZ, Zimmerman SC, Wei J, Griswold ME, Fitzpatrick AL, Gottesman RF, Launer LJ, Windham BG, Levine DA, Fohner AE, Glymour MM, Power MC. Target Trial Emulation Using Cohort Studies: Estimating the Effect of Antihypertensive Medication Initiation on Incident Dementia. Epidemiology 2025; 36:48-59. [PMID: 39352756 PMCID: PMC11598662 DOI: 10.1097/ede.0000000000001802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2024]
Abstract
BACKGROUND Observational studies link high midlife systolic blood pressure to increased dementia risk. However, the synthesis of evidence from randomized controlled trials has not definitively demonstrated that antihypertensive medication use reduces dementia risk. Here, we emulate target trials of antihypertensive medication initiation on incident dementia using three cohort studies, with attention to potential violations of necessary assumptions. METHODS We emulated trials of antihypertensive medication initiation on incident dementia using data from the Atherosclerosis Risk in Communities study, Cardiovascular Health Study, and Health and Retirement Study. We used data-driven methods to restrict participants to initiators and noninitiators with overlap in propensity scores and positive control outcomes to look for violations of positivity and exchangeability assumptions. RESULTS Analyses were limited by the small number of cohort participants who met eligibility criteria. Associations between antihypertensive medication initiation and incident dementia were inconsistent and imprecise (Atherosclerosis Risk in Communities: HR = 0.30 [0.05, 1.93]; Cardiovascular Health Study: HR = 0.66 [0.27, 1.64]; Health and Retirement Study: HR = 1.09 [0.75, 1.59]). More stringent propensity score restrictions had little effect on findings. Sensitivity analyses using a positive control outcome unexpectedly suggested antihypertensive medication initiation increased the risk of coronary heart disease in all three samples. CONCLUSIONS Positive control outcome analyses suggested substantial residual confounding in effect estimates from our target trials, precluding conclusions about the impact of antihypertensive medication initiation on dementia risk through target trial emulation. Formalized processes for identifying violations of necessary assumptions will strengthen confidence in target trial emulation and avoid inappropriate confidence in emulated trial results.
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Affiliation(s)
- Erin E. Bennett
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Chelsea Liu
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Emma K. Stapp
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Kan Z. Gianattasio
- Department of Health Care Evaluation, NORC at the University of Chicago, Bethesda, MD, USA
| | - Scott C. Zimmerman
- Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA, USA
| | - Jingkai Wei
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Michael E. Griswold
- Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Annette L. Fitzpatrick
- Department of Family Medicine, School of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | | | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, National Institute of Aging, Bethesda, MD, USA
| | - B. Gwen Windham
- Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Deborah A. Levine
- Department of Internal Medicine, School of Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Alison E. Fohner
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA, USA
| | - Melinda C. Power
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
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Rosenberg AT, Flaherty C, Anderson AH, Appel LJ, Coresh J, He J, Lash JP, Liu C, Rao PS, Taliercio J, Surapaneni A, Grams ME. Surrogate End Points in Apolipoprotein L1 - Associated Kidney Disease : Evaluation in Three Cohorts. Clin J Am Soc Nephrol 2025; 20:23-30. [PMID: 39499577 DOI: 10.2215/cjn.0000000000000575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 10/31/2024] [Indexed: 11/07/2024]
Abstract
Key Points
Apolipoprotein L1 (APOL1) high-risk genotype had higher risk of 3-year GFR-related surrogate end points and long-term kidney failure than those with the low-risk genotype.No consistent difference in surrogate–clinical outcome associations by APOL1 genotype, supporting the use of surrogates in APOL1 kidney disease.
Background
Surrogate end points for the clinical outcome of kidney failure have been accepted by the US Food and Drug Administration. However, they have not been specifically evaluated in Apolipoprotein L1 (APOL1)-associated kidney disease.
Methods
This random-effects meta-analysis included Black participants in the Atherosclerosis Risk in Communities study (N=3071), Chronic Renal Insufficiency Cohort (N=998), and African American Study of Kidney Disease and Hypertension (N=609). Surrogate end points included a 3-year 30% and 40% decline in GFR, doubling of urine protein–creatinine ratio, and >3 ml/min per 1.73 m2 per year decline in GFR. Clinical outcomes included kidney failure requiring KRT, heart failure, cardiovascular disease, and death after 3 years.
Results
22% in the African American Study of Kidney Disease and Hypertension, 18% in the Chronic Renal Insufficiency Cohort, and 13% in the Atherosclerosis Risk in Communities study had the APOL1 high-risk genotype. Participants with the APOL1 high-risk genotype had higher risk of all 3-year GFR outcomes but not doubling of urine protein–creatinine ratio, as well as kidney failure after 3 years. The 3-year outcomes were strongly associated with kidney failure with weaker but statistically significant associations with the development of heart failure, cardiovascular disease, and mortality. There were no differences in associations between short-term and long-term clinical outcomes by APOL1 risk status.
Conclusions
Individuals with the APOL1 high-risk genotype were more susceptible to 3-year GFR-related end points and long-term kidney failure than individuals with the APOL1 low-risk genotype. There was no consistent difference in short-term clinical outcome associations by APOL1 genotype, supporting the use of surrogates in APOL1-associated kidney disease.
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Grants
- R01DK124399 NIDDK NIH HHS
- R01DK100446 NIDDK NIH HHS
- K24HL155861 NHLBI NIH HHS
- U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, U01DK060902 and U24DK060990 NIDDK NIH HHS
- 75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, 75N92022D00005 NHLBI NIH HHS
- UL1TR000003 Perelman School of Medicine, University of Pennsylvania
- UL1 TR-000424 Johns Hopkins University
- GCRC M01 RR-16500 University of Maryland
- UL1TR000439 Clinical and Translational Science Collaborative of Cleveland, School of Medicine, Case Western Reserve University
- UL1TR000433 Michigan Institute for Clinical and Health Research
- CTSA UL1RR029879 University of Illinois at Chicago
- P20 GM109036 NIGMS NIH HHS
- UCSF-CTSI UL1 RR-024131 Kaiser Permanente
- NM R01DK119199 School of Medicine, University of New Mexico
- R01DK124399 NIDDK NIH HHS
- R01DK100446 NIDDK NIH HHS
- K24HL155861 NHLBI NIH HHS
- U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, U01DK060902 and U24DK060990 NIDDK NIH HHS
- 75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, 75N92022D00005 NHLBI NIH HHS
- P20 GM109036 NIGMS NIH HHS
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Affiliation(s)
- Alix T Rosenberg
- Division of Precision Medicine, Department of Medicine, New York University, New York, New York
| | - Carina Flaherty
- Division of Precision Medicine, Department of Medicine, New York University, New York, New York
| | - Amanda H Anderson
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Alabama, Birmingham, Alabama
| | - Lawrence J Appel
- Welch Center for Epidemiology, Prevention, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Josef Coresh
- Department of Population Health, Aging Institute, New York University, New York, New York
| | - Jiang He
- Department of Epidemiology, Tulane University, New Orleans, Louisiana
| | - James P Lash
- Division of Nephology, Department of Medicine, University of Illinois, Chicago, Illinois
| | - Celina Liu
- Division of Precision Medicine, Department of Medicine, New York University, New York, New York
| | - Panduranga S Rao
- Division of Nephrology, Department of Medicine, University of Michigan, Ann Arbor, Michigan
| | | | - Aditya Surapaneni
- Division of Precision Medicine, Department of Medicine, New York University, New York, New York
| | - Morgan E Grams
- Division of Precision Medicine, Department of Medicine, New York University, New York, New York
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5
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Wang W, Lutsey PL, Inciardi RM, Reyes JL, Mosley TH, Johansen MC, Gottesman RF, Alonso A, Jack CR, Solomon SD, Shah AM, Wasserman BA, Chen LY. Association of left atrial function with vascular brain injury: The Atherosclerosis Risk in Communities study. Eur J Neurol 2025; 32:e16549. [PMID: 39569699 PMCID: PMC11625916 DOI: 10.1111/ene.16549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2024] [Revised: 10/18/2024] [Accepted: 10/31/2024] [Indexed: 11/22/2024]
Abstract
BACKGROUND AND PURPOSE Lower left atrial (LA) function is associated with higher dementia risk and may be mechanistically linked through vascular brain injury, an established correlate for higher dementia risk. Using data from the Atherosclerosis Risk in Communities study, we assessed the cross-sectional association between LA function and brain magnetic resonance imaging (MRI) markers of vascular brain injury. METHODS We included 1488 participants who were free of prevalent dementia, stroke, or atrial fibrillation and who underwent a two-dimensional echocardiogram and brain MRI in 2011-2013 (mean [± standard deviation] age 76 [± 5] years, 60% female, 27% Black). LA function measures (reservoir, conduit, contractile strain) were assessed in quartiles. Brain MRI measures included cerebral microbleeds, brain infarcts, and white matter hyperintensity (WMH) volume. Logistic regression was used for dichotomous outcomes. Linear regression was used for WMH volume. RESULTS Overall, 343 (23%) and 344 participants (23%) had ≥1 cerebral microbleed or brain infarct. After multivariable adjustments, the lowest LA reservoir and conduit strain quartiles (vs. highest quartile) were associated with higher odds of the presence of ≥1 cerebral microbleed (odds ratios [95% confidence intervals] 1.78 [1.42-2.22] and 1.52 [1.22-1.90]). Compared to the highest quartile, participants in the lowest LA conduit strain quartile had 1.51 (95% confidence interval 1.22-1.88) times higher odds of having ≥1 brain infarct. Lower LA contractile strain was associated with lower odds of brain infarcts. No association with WMH volume was noted. CONCLUSIONS We found that LA reservoir and conduit strain were associated with cerebral microbleeds and brain infarcts. Lower LA function may be linked to dementia risk via vascular brain injury. Prospective studies are needed to confirm these findings.
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Affiliation(s)
- Wendy Wang
- Division of Epidemiology and Community Health, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Riccardo M. Inciardi
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Institute of CardiologyUniversity of BresciaBresciaItaly
| | - Jorge L. Reyes
- Lillehei Heart Institute and Department of Medicine (Cardiovascular Division)University of Minnesota Medical SchoolMinneapolisMinnesotaUSA
| | - Thomas H. Mosley
- The MIND CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | | | - Rebecca F. Gottesman
- Stroke BranchNational Institute of Neurological Disorders and Stroke Intramural Research ProgramBethesdaMarylandUSA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | | | - Scott D. Solomon
- Cardiovascular DivisionBrigham and Women's HospitalBostonMassachusettsUSA
| | - Amil M. Shah
- Division of CardiologyUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Bruce A. Wasserman
- Department of Diagnostic Radiology and Nuclear MedicineUniversity of Maryland School of MedicineBaltimoreMarylandUSA
- Johns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Lin Yee Chen
- Lillehei Heart Institute and Department of Medicine (Cardiovascular Division)University of Minnesota Medical SchoolMinneapolisMinnesotaUSA
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6
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Miyata M. Arterial stiffness and left atrial function. Hypertens Res 2025; 48:434-435. [PMID: 39543420 DOI: 10.1038/s41440-024-01911-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2024] [Accepted: 09/02/2024] [Indexed: 11/17/2024]
Affiliation(s)
- Masaaki Miyata
- School of Health Sciences, Faculty of Medicine, Kagoshima University, Kagoshima, Japan.
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7
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Chen D, Yao Y, Moser ED, Wang W, Soliman EZ, Mosley T, Pan W. A novel electrocardiogram-based model for prediction of dementia-The Atherosclerosis Risk in Communities (ARIC) study. J Electrocardiol 2025; 88:153832. [PMID: 39612620 PMCID: PMC11717592 DOI: 10.1016/j.jelectrocard.2024.153832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2024] [Revised: 08/23/2024] [Accepted: 11/17/2024] [Indexed: 12/01/2024]
Abstract
AIM Create an ECG-based model to predict dementia and compare its performance with the existing Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) model. METHODS AND RESULTS Participants without prevalent dementia in the Atherosclerosis Risk in Communities study were studied. Visit 4 (V4) (1996-98, mean age, 62 years) and V5 (2011-13, mean age, 75 years) were used as baselines. Incident dementia cases were adjudicated through 2019. We created parsimonious ECG models by using Cox regression with a backward selection method. C-statistic (95 % CI) of the ECG-based model (two or three ECG variables and age) was higher than the CAIDE model (seven variables) at V4 (0.72 [0.71-0.74] vs. 0.67 [0.66-0.68]) and V5 (0.70 [0.68-0.72] vs. 0.64 [0.62-0.66]). The ECG-based model was well calibrated, but the CAIDE model was poorly calibrated at V4 (P < 0.001). CONCLUSION For middle-aged and older adults, a novel ECG-based model has good discrimination that is superior to the CAIDE model in predicting dementia. Since ECG variables are readily obtainable, the ECG-based model will be easy to adopt clinically.
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Affiliation(s)
- Deling Chen
- Division of Biostatistics and Health Data Science, University of Minnesota School of Public Health, Minneapolis, USA
| | - Yuchen Yao
- Division of Biostatistics and Health Data Science, University of Minnesota School of Public Health, Minneapolis, USA; School of Statistics, College of Liberal Arts, University of Minnesota, Minneapolis, USA
| | - Ethan D Moser
- Department of Medicine, University of Minnesota Medical School, Minneapolis, USA
| | - Wendy Wang
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, USA
| | - Elsayed Z Soliman
- Epidemiological Cardiology Research Center, Department of Cardiovascular Medicine, Wake Forest University School of Medicine, Winston Salem, NC, USA
| | - Thomas Mosley
- MIND Center, University of Mississippi Medical Center, Jackson, USA
| | - Wei Pan
- Division of Biostatistics and Health Data Science, University of Minnesota School of Public Health, Minneapolis, USA.
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8
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Schneider ALC, Kamath V, Reed NS, Mosley T, Gottesman RF, Sharrett AR, Lin FR, Deal JA. Associations of Traumatic Brain Injury and Hearing: Results From the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS). J Head Trauma Rehabil 2024:00001199-990000000-00220. [PMID: 39740144 DOI: 10.1097/htr.0000000000001032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2025]
Abstract
OBJECTIVE To examine associations of traumatic brain injury (TBI) with self-reported and clinical measures of hearing function. SETTING Four US communities. PARTICIPANTS A total of 3176 Atherosclerosis Risk in Communities Study participants who attended the sixth study visit in 2016-2017, when hearing was assessed. DESIGN Prospective cohort study. TBI occurring prior to the hearing assessment was defined using self-reported questions and "International Classification of Diseases-9th/10th Edition" (ICD-9/10) codes. MAIN MEASURES Hearing function was assessed by self-reported questionnaires and clinically measured indices (audiometry [4-frequency pure tone average for each ear] and speech-in-noise testing). Linear, logistic, and multinomial logistic models adjusted for sociodemographics, vascular risk factors, and occupational noise exposure were used to examine associations. RESULTS Participants were a mean age of 79 years, 59% were female, 21% were of self-reported Black race, and 33% had a history of TBI (median time from first TBI to hearing assessment: 39 years (25th-75th percentile = 19-63 years). Compared to participants without TBI, participants with prior TBI had higher age-adjusted prevalence of self-reported hearing loss (42.3% vs 35.3%), tinnitus (28.0% vs 23.8%), hearing aid use (23.4% vs 17.8%), pure tone average > 40 dB (30.6% vs 24.8%), and presence in the lowest quartile of speech-in-noise performance (27.6% vs 22.8%). With further adjustment, and particularly with adjustment for occupational noise exposure, associations with hearing measures were largely no longer statistically significant. In secondary analyses of associations of TBI frequency and severity with hearing function, results were similar to our main analyses, without evidence of dose-dependent associations. CONCLUSIONS AND RELEVANCE In this community-based cohort, prior TBI was associated with impaired hearing on both self-reported and clinically measured assessments, but these associations were attenuated after adjustment for occupational noise exposure. These results underscore the importance of the consideration of loud noise exposures, which may confound associations of TBI with hearing, in future studies.
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Affiliation(s)
- Andrea L C Schneider
- Author Affiliations: Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (Dr Schneider); Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (Dr Schneider); Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland (Dr Kamath); Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland (Drs Reed, Sharrett, Lin, and Deal); The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi (Dr Mosley); National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, Maryland (Dr Gottesman); Department of Otolaryngology, School of Medicine, Johns Hopkins University, Baltimore, Maryland (Drs Lin and Deal); and Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (Drs Lin and Deal)
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9
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Schneider ALC, Reyes A, Henegan JA, Kamath V, Wruck L, Pike JR, Gross A, Walker K, Kucharska-Newton A, Coresh J, Mosley TH, Gottesman RF, Griswold M. Evaluating Social Determinants of Health-Based Alternatives to Race-Based Cognitive Normative Models. Neurology 2024; 103:e210030. [PMID: 39546740 PMCID: PMC11567649 DOI: 10.1212/wnl.0000000000210030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Accepted: 09/05/2024] [Indexed: 11/17/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Race and ethnicity are proxy measures of sociocultural factors that influence cognitive test performance. Our objective was to compare different regression-based cognitive normative models adjusting for demographics and different combinations of easily accessible/commonly used social determinants of health (SDoH) factors, which may help describe cognitive performance variability historically captured by ethnoracial differences. METHODS We performed cross-sectional analyses on data from Black and White participants without mild cognitive impairment/dementia in the Atherosclerosis Risk in Communities Study who attended visit 5 in 2011-2013. Participants underwent a battery of 11 cognitive tests (3 domains: memory, executive function, language). We fit 6 separate normative models for each cognitive test, all including age and education, with different combinations of race, the Wide Range of Achievement Test (education quality proxy), and area deprivation index (neighborhood deprivation) associated with current residence. We compared model fits and calculated concordances/discordances between models using z-scores derived from each normative model and a z-score <-1.5 threshold for impairment. RESULTS Participants (n = 2,392) had a mean age of 74.4 years, 60.4% were female, and 17.1% were of self-reported Black race. The "Full" model with race alongside demographic and SDoH measures consistently outperformed other nested submodels (likelihood ratios ≥ 100) for all domains/tests except Delayed Word Recall. Models with education quality alone ("WRAT") generally outperformed models with neighborhood deprivation ("ADI") or race ("Race") alone for memory and language tests while "Race" models performed better for executive function tests. Adding neighborhood deprivation to education quality ("WRAT + ADI") did not improve models vs using "WRAT" alone. Across all domains/tests, the concordance compared with the "Full" model was lower for "Education" and "ADI" models than for other nested models. Although numbers were small, there was greater discordance among Black (range = 8.2%-23.2%) compared with White (range = 2.2%-3.4%) participants, particularly for Boston Naming Test and executive function tests. DISCUSSION Education quality outperformed neighborhood disadvantage as an additional/alternative SDoH measure in normative models and may be useful to collect in cognitive aging studies. While performance varied across cognitive domains and tests, routinely reported SDoH variables (education level, education quality, late-life neighborhood deprivation) did not fully account for observed ethnoracial variability; future work should evaluate SDoH across the lifespan in more ethnoracially diverse populations.
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Affiliation(s)
- Andrea Lauren Christman Schneider
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Anny Reyes
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - James A Henegan
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Vidyulata Kamath
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Lisa Wruck
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - James Russell Pike
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Alden Gross
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Keenan Walker
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Anna Kucharska-Newton
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Josef Coresh
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Thomas H Mosley
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Rebecca F Gottesman
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
| | - Michael Griswold
- From the Department of Neurology (A.L.C.S.); Department of Biostatistics, Epidemiology, and Informatics, (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiation Medicine and Applied Sciences (A.R.), University of California, San Diego; Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.A.H., T.H.M., M.G.), University of Mississippi Medical Center, Jackson; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biostatistics and Bioinformatics (L.W.), Duke University, Durham, NC; Department of Population Health (J.R.P., J.C.), New York University Grossman School of Medicine, New York; Department of Epidemiology (A.G.), Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; National Institute on Aging Intramural Program (K.W.), Baltimore, MD; Department of Epidemiology (A.K.-N.), University of North Carolina at Chapel Hill; and National Institute of Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), Bethesda, MD
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10
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Lee M, Lakshminarayan K, Sedaghat S, Sabayan B, Chen LY, Johansen MC, Gottesman RF, Heckbert SR, Misialek JR, Szklo M, Lutsey PL. Population attributable fraction of total stroke associated with modifiable risk factors in the United States. Am J Epidemiol 2024; 193:1712-1719. [PMID: 38897982 DOI: 10.1093/aje/kwae132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 04/25/2024] [Accepted: 06/14/2024] [Indexed: 06/21/2024] Open
Abstract
Stroke is a leading cause of death in the United States across all race/ethnicity and sex groups, though disparities exist. We investigated the potential for primary prevention of total first stroke for Americans aged 20 years or older, stratified by sex and race/ethnicity. Specifically, we calculated population attributable fractions (PAFs) of first stroke for 7 potentially modifiable risk factors: smoking, physical inactivity, poor diet, obesity, hypertension, diabetes, and atrial fibrillation. Population attributable fractions are a function of (1) the relative risk of first stroke for people with the exposure and (2) the prevalence of the risk factor in the population. Relative risks came from recent meta-analyses, and sex- and race/ethnicity-specific prevalence estimates came from the 2015-2018 National Health and Nutrition Examination Survey or Multi-Ethnic Study of Atherosclerosis (for atrial fibrillation only). Approximately one-third of strokes (35.7% [95% CI, 21.6-49.0] for women; 32.7% [95% CI, 19.2-45.1] for men) were attributable to the 7 risk factors we considered. A 20% proportional reduction in stroke risk factors would result in approximately 37 000 fewer strokes annually in the United States. The estimated PAF was highest for non-Hispanic Black women (39.3%; 95% CI, 24.8-52.3) and lowest for non-Hispanic Asian men (25.5%; 95% CI, 14.6-36.2). For most groups, obesity and hypertension were the largest contributors to stroke rates.
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Affiliation(s)
- Mark Lee
- Minnesota Population Center, University of Minnesota, Minneapolis, MN 55455, United States
| | - Kamakshi Lakshminarayan
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN 55454, United States
| | - Sanaz Sedaghat
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN 55454, United States
| | - Behnam Sabayan
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN 55454, United States
- Department of Neurology, HealthPartners Neuroscience Center, St. Paul, MN 55130, United States
| | - Lin Yee Chen
- Lillehei Heart Institute and Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN 55455, United States
| | - Michelle C Johansen
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States
| | - Rebecca F Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, United States
| | - Susan R Heckbert
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA 98101, United States
| | - Jeffrey R Misialek
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN 55454, United States
| | - Moyses Szklo
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, United States
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN 55454, United States
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11
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Luckey AM, Ghosh S, Wang CP, Beiser A, Bernal R, Li Z, Mbangdadji D, Fadaee E, Snoussi H, Dediós AGV, Trevino HA, Goss M, Hillmer LJ, Bauer CE, Staffaroni AM, Stables L, Albert M, Himali JJ, Mosley TH, Forsberg L, Guðnason V, Singh B, Singh H, Schwab K, Kramer JH, Rosenberg GA, Helmer KG, Greenberg SM, Habes M, Wang DJJ, Gold BT, Lu H, Caprihan A, Fornage M, Launer LJ, Arfanakis K, Seshadri S, DeCarli C, Maillard P, Satizabal CL. Biological validation of peak-width of skeletonized mean diffusivity as a VCID biomarker: The MarkVCID Consortium. Alzheimers Dement 2024; 20:8814-8824. [PMID: 39569745 DOI: 10.1002/alz.14345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Revised: 09/18/2024] [Accepted: 09/21/2024] [Indexed: 11/22/2024]
Abstract
BACKGROUND Peak-width of skeletonized mean diffusivity (PSMD), a neuroimaging marker of cerebral small vessel disease (SVD), has shown excellent instrumental properties. Here, we extend our work to perform a biological validation of PSMD. METHODS We included 396 participants from the Biomarkers for Vascular Contributions to Cognitive Impairment and Dementia (MarkVCID-1) Consortium and three replication samples (Cohorts for Heart and Aging Research in Genomic Epidemiology = 6172, Rush University Medical Center = 287, University of California Davis Alzheimer's Disease Research Center = 567). PSMD was derived from diffusion tensor imaging using an automated algorithm. We related PSMD to a composite measure of general cognitive function using linear regression models adjusting for confounders. RESULTS Higher PSMD was associated with lower general cognition in MarkVCID-1 independent of age, sex, education, and intracranial volume (Beta [95% confidence interval], -0.8 [-1.2, -0.4], P < 0.001). These findings were replicated in independent samples. Furthermore, PSMD explained cognitive status above and beyond white matter hyperintensities. DISCUSSION Our biological validation work supports the pursuit of larger clinical validation studies evaluating PSMD as a susceptibility/risk biomarker of small vessel disease contributing to cognitive impairment and dementia. HIGHLIGHTS Peak-width of skeletonized mean diffusivity (PSMD) is a novel small vessel disease neuroimaging biomarker. A prior instrumental validation study demonstrated that PSMD is a robust biomarker. This biological validation study shows that high PSMD relates to worse cognition. PSMD explains cognitive function above and beyond white matter hyperintensities. Future clinical validation will assess PSMD as a vascular contribution to cognitive impairment and dementia biomarker in clinical trials.
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Affiliation(s)
- Alison M Luckey
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Saptaparni Ghosh
- Department of Neurology, Boston Chobanian & Avedisian University School of Medicine, Boston, Massachusetts, USA
| | - Chen-Pin Wang
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Alexa Beiser
- Department of Neurology, Boston Chobanian & Avedisian University School of Medicine, Boston, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Rebecca Bernal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Zhiguang Li
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Gaithersburg, Maryland, USA
| | - Djass Mbangdadji
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Gaithersburg, Maryland, USA
| | - Elyas Fadaee
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Haykel Snoussi
- Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Angel Gabriel Velarde Dediós
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Hector A Trevino
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Monica Goss
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Laura J Hillmer
- Center for Memory and Aging, University of New Mexico School of Medicine, Albuquerque, New Mexico, USA
| | - Christopher E Bauer
- Department of Neuroscience, University of Kentucky, Lexington, Kentucky, USA
| | - Adam M Staffaroni
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, California, USA
| | - Lara Stables
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, California, USA
| | - Marilyn Albert
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jayandra J Himali
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
- Department of Neurology, Boston Chobanian & Avedisian University School of Medicine, Boston, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Thomas H Mosley
- MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | | | - Vilmundur Guðnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland School of Health Sciences, Reykjavík, Iceland
| | - Baljeet Singh
- Department of Neurology, University of California at Davis, Sacramento, California, USA
| | - Herpreet Singh
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Kristin Schwab
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Joel H Kramer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, California, USA
| | - Gary A Rosenberg
- Center for Memory and Aging, University of New Mexico School of Medicine, Albuquerque, New Mexico, USA
- Department of Neurology, University of New Mexico, Albuquerque, New Mexico, USA
| | - Karl G Helmer
- Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Steven M Greenberg
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Danny J J Wang
- Laboratory of FMRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Brian T Gold
- Department of Neuroscience, University of Kentucky, Lexington, Kentucky, USA
| | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | | | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Lenore J Launer
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Gaithersburg, Maryland, USA
| | - Konstantinos Arfanakis
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
- Department of Neurology, Boston Chobanian & Avedisian University School of Medicine, Boston, Massachusetts, USA
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Sacramento, California, USA
| | - Pauline Maillard
- Department of Neurology, University of California at Davis, Sacramento, California, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
- Department of Neurology, Boston Chobanian & Avedisian University School of Medicine, Boston, Massachusetts, USA
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12
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Stone K, Fryer S, McDonnell BJ, Meyer ML, Faulkner J, Agharazii M, Fortier C, Pugh CJA, Paterson C, Zieff G, Chauntry AJ, Kucharska-Newton A, Bahls M, Stoner L. Aortic-Femoral Stiffness Gradient and Cardiovascular Risk in Older Adults. Hypertension 2024; 81:e185-e196. [PMID: 39371003 DOI: 10.1161/hypertensionaha.124.23392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Accepted: 09/12/2024] [Indexed: 10/08/2024]
Abstract
BACKGROUND The aortic-femoral arterial stiffness gradient, calculated as the ratio of lower-limb pulse-wave velocity (PWV) to central (aortic) PWV, is a promising tool for assessing cardiovascular disease (CVD) risk, but whether it predicts incident CVD is unknown. METHODS We examined the association of the aortic-femoral arterial stiffness gradient measures carotid-femoral stiffness gradient (femoral-ankle PWV divided by carotid-femoral PWV) and the heart-femoral stiffness gradient (femoral-ankle PWV divided by heart-femoral PWV), as well as PWV, with incident CVD (coronary disease, stroke, and heart failure) and all-cause mortality among 3109 participants of the Atherosclerosis Risk in Communities Study cohort (age, 75±5 years; carotid-femoral PWV, 11.5±3.0 m/s), free of CVD. Cox regression was used to estimate hazard ratios (HR) and 95% CIs. RESULTS Over a median 7.4-year follow-up, there were 322 cases of incident CVD and 410 deaths. In fully adjusted models, only top quartiles of carotid-femoral stiffness gradient (quartile 4: HR, 1.43 [95% CI, 1.03-1.97]; and quartile 3: HR, 1.49 [95% CI, 1.08-2.05]) and heart-femoral stiffness gradient (quartile 4: HR, 1.77 [95% CI, 1.27-2.48]; and quartile 3: HR, 1.41 [95% CI, 1.00-2.00]) were significantly associated with a greater risk of incident CVD. Only high aortic stiffness in combination with low lower-limb stiffness was significantly associated with incident CVD (HR, 1.46 [95% CI, 1.06-2.02]) compared with the referent low aortic stiffness and high lower-limb stiffness. No PWVs were significantly associated with incident CVD. No exposures were associated with all-cause mortality. CONCLUSIONS The aortic-femoral arterial stiffness gradient may enhance CVD risk assessment in older adults in whom the predictive capacity of traditional risk factors and PWV are attenuated.
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Affiliation(s)
- Keeron Stone
- Centre for Cardiovascular Research, Innovation and Development, Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Wales, United Kingdom (K.S., B.J.M., C.J.A.P.)
- National Cardiovascular Research Network, Wales, United Kingdom (K.S., B.J.M. , C.J.A.P.)
| | - Simon Fryer
- School of Education and Science, University of Gloucestershire, Gloucester, United Kingdom (S.F.)
| | - Barry J McDonnell
- Centre for Cardiovascular Research, Innovation and Development, Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Wales, United Kingdom (K.S., B.J.M., C.J.A.P.)
- National Cardiovascular Research Network, Wales, United Kingdom (K.S., B.J.M. , C.J.A.P.)
| | - Michelle L Meyer
- Department of Emergency Medicine, School of Medicine (M.L.M.), University of North Carolina at Chapel Hill
| | - James Faulkner
- Department of Sport, Exercise and Health, University of Winchester, United Kingdom (J.F.)
| | - Mohsen Agharazii
- Endocrinology and Nephrology Axis, Centre hospitalier universitaire de Québec Research Center, Faculty and Department of Medicine, Université Laval, Quebec City, Canada (M.A., C.F.)
| | - Catherine Fortier
- Endocrinology and Nephrology Axis, Centre hospitalier universitaire de Québec Research Center, Faculty and Department of Medicine, Université Laval, Quebec City, Canada (M.A., C.F.)
| | - Christopher J A Pugh
- Centre for Cardiovascular Research, Innovation and Development, Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Wales, United Kingdom (K.S., B.J.M., C.J.A.P.)
- National Cardiovascular Research Network, Wales, United Kingdom (K.S., B.J.M. , C.J.A.P.)
| | - Craig Paterson
- Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom (C.P.)
| | - Gabriel Zieff
- School of Kinesiology, University of British Columbia, Canada (G.Z.)
| | - Aiden J Chauntry
- Department of Exercise and Sport Science (A.J.C., L.S.), University of North Carolina at Chapel Hill
| | - Anna Kucharska-Newton
- Department of Epidemiology, The Gillings School of Global Public Health (A.K.-N., L.S.), University of North Carolina at Chapel Hill
| | - Martin Bahls
- Center for Health Promotion and Disease Prevention (M.B.), University of North Carolina at Chapel Hill
- Department of Internal Medicine B, University Medicine Greifswald, Germany (M.B.)
- German Centre for Cardiovascular Research, partner site Greifswald, Germany (M.B.)
| | - Lee Stoner
- Department of Exercise and Sport Science (A.J.C., L.S.), University of North Carolina at Chapel Hill
- Department of Epidemiology, The Gillings School of Global Public Health (A.K.-N., L.S.), University of North Carolina at Chapel Hill
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13
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Sun D, Parikh RR, Wang W, Eaton A, Lutsey PL, Windham BG, Inciardi RM, Solomon SD, Ballantyne CM, Shah AM, Chen LY. Association of left atrial function with frailty: The Atherosclerosis Risk in Communities (ARIC) study. J Am Geriatr Soc 2024; 72:3810-3823. [PMID: 39268991 PMCID: PMC11637300 DOI: 10.1111/jgs.19187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 07/30/2024] [Accepted: 08/13/2024] [Indexed: 09/15/2024]
Abstract
BACKGROUND Frailty is common in people with cardiovascular disease. Worse left atrial (LA) function is an independent risk factor for cardiovascular disease. However, whether worse LA function is associated with frailty is unclear. METHODS We included 3292 older adults from the Atherosclerosis Risk in Communities study who were non-frail at baseline (visit 5, 2011-2013) and had LA function (reservoir, conduit, and contractile strain) measured from two-dimensional speckle-tracking echocardiography. LA stiffness index was calculated as a ratio of E/e' to LA reservoir strain. Frailty was defined using the validated Fried frailty phenotype. Incident frailty was assessed between 2016 and 2019 during two follow-up visits. LA function was analyzed as quintiles. Multivariable logistic regression examined odds of incident frailty. RESULTS Median (interquartile range [IQR]) age was 74 (71-77) years, 58% were female, and 214 (7%) participants developed frailty during a median (IQR) follow-up of 6.3 (5.6-6.8) years. After adjusting for baseline confounders and incident cardiovascular events during follow-up, the odds of developing frailty was 2.42 (1.26-4.66) times greater among participants in the lowest (vs highest) quintile of LA reservoir strain and 2.41 (1.11-5.22) times greater among those in the highest (vs lowest) quintile of LA stiffness index. Worse LA function was significantly associated with the development of exhaustion, but not the other components of the Fried frailty phenotype. CONCLUSIONS Worse LA function is associated with higher incidence of frailty and exhaustion component independent of LA size and left ventricular function. Future studies are needed to elucidate the underlying mechanisms that drive the observed association.
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Affiliation(s)
- Daokun Sun
- Division of Epidemiology and Community Health, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Romil R. Parikh
- Division of Epidemiology and Community Health, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Wendy Wang
- Division of Epidemiology and Community Health, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Anne Eaton
- Division of Biostatistics and Public Health Data Science, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - B. Gwen Windham
- Division of Geriatrics, Department of MedicineUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Riccardo M. Inciardi
- Institute of Cardiology, ASST Spedali Civili, Department of Medical and Surgical Specialties, Radiological Sciences and Public HealthUniversity of BresciaBresciaItaly
| | - Scott D. Solomon
- Division of Cardiovascular Medicine, Department of MedicineBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | | | - Amil M. Shah
- Division of Cardiovascular Medicine, Department of MedicineBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Internal MedicineUT Southwestern Medical CenterDallasTexasUSA
| | - Lin Yee Chen
- Lillehei Heart Institute and Cardiovascular DivisionUniversity of MinnesotaMinneapolisMinnesotaUSA
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14
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Ejiri K, Mok Y, Ding N, Chang PP, Rosamond WD, Shah AM, Lutsey PL, Chen LY, Blaha MJ, Mathews L, Matsushita K. Chest Symptoms and Long-Term Risk of Incident Cardiovascular Disease. Am J Med 2024; 137:1255-1263.e16. [PMID: 39084313 PMCID: PMC11585413 DOI: 10.1016/j.amjmed.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 07/07/2024] [Accepted: 07/09/2024] [Indexed: 08/02/2024]
Abstract
BACKGROUND We sought to evaluate the associations of chest pain and dyspnea with the long-term risk of cardiovascular disease including coronary disease, heart failure, atrial fibrillation, and stroke. METHODS In 13,200 participants without cardiovascular disease in the Atherosclerosis Risk in Communities study (1987-1989), chest pain was categorized into definite angina, possible angina, non-anginal chest pain, and no chest pain using the Rose questionnaire. Dyspnea was categorized into grades 3-4, 2, 1, and 0 by the modified Medical Research Council scale. The associations of chest pain and dyspnea with incident myocardial infarction, heart failure, atrial fibrillation, and stroke over a median follow-up of ∼27 years were quantified with multivariable Cox models. RESULTS Definite angina and possible angina were associated with myocardial infarction (adjusted hazard ratios [HR] 1.80 [95%CI 1.45-2.13] and 1.65 [1.27-2.15]). Although lesser magnitude than myocardial infarction, both definite and possible angina were associated with heart failure. For atrial fibrillation, possible angina showed higher HR than definite angina. Dyspnea showed similar HRs for myocardial infarction and heart failure in grades 3-4 (2.00 [1.61-2.49] and 1.94 [1.62-2.32]). Stroke was least associated with chest symptoms. Chest pain and dyspnea significantly improved the discrimination of cardiovascular disease except stroke, beyond traditional risk factors. CONCLUSIONS In individuals without cardiovascular disease, chest pain and dyspnea were independently associated with incident cardiovascular disease for about 3 decades, suggesting the need for evaluating chest pain from a broader perspective of cardiovascular disease beyond coronary disease and the importance of dyspnea for cardiovascular risk assessment including myocardial infarction.
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Affiliation(s)
- Kentaro Ejiri
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Yejin Mok
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Ning Ding
- Yale New Haven Health Bridgeport Hospital, Bridgeport, Conn
| | | | | | - Amil M Shah
- University of Texas Southwestern Medical Center, Dallas, TX
| | | | | | | | | | - Kunihiro Matsushita
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Md; Johns Hopkins School of Medicine, Baltimore, Md.
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15
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Springer MV, Chen B, Whitney RT, Briceño EM, Gross AL, Aparicio HJ, Beiser AS, Burke JF, Giordani B, Gottesman RF, Hayward RA, Howard VJ, Koton S, Lazar RM, Sussman JB, Ye W, Levine DA. Age differences in the change in cognition after stroke. J Stroke Cerebrovasc Dis 2024; 33:108087. [PMID: 39401577 DOI: 10.1016/j.jstrokecerebrovasdis.2024.108087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 09/23/2024] [Accepted: 10/11/2024] [Indexed: 10/21/2024] Open
Abstract
OBJECTIVE To compare changes in cognitive trajectories after stroke between younger (18-64) and older (65+) adults, accounting for pre-stroke cognitive trajectories. MATERIALS AND METHODS Pooled cohort study using individual participant data from 3 US cohorts (1971-2019), the Atherosclerosis Risk In Communities Study (ARIC), Framingham Offspring Study (FOS), and REasons for Geographic And Racial Differences in Stroke Study (REGARDS). Linear mixed effect models evaluated the association between age and the initial change (intercept) and rate of change (slope) in cognition after compared to before stroke. Outcomes were global cognition (primary), memory and executive function. RESULTS We included 1,292 participants with stroke; 197 younger (47.2 % female, 32.5 % Black race) and 1,095 older (50.2 % female, 46.4 % Black race). Median (IQR) age at stroke was 59.7 (56.6-61.7) (younger group) and 75.2 (70.5-80.2) years (older group). Compared to the young, older participants had greater declines in global cognition (-1.69 point [95 % CI, -2.82 to -0.55] greater), memory (-1.05 point [95 % CI, -1.92 to -0.17] greater), and executive function (-3.72 point [95 % CI, -5.23 to -2.21] greater) initially after stroke. Older age was associated with faster declines in global cognition (-0.18 points per year [95 % CI, -0.36 to -0.01] faster) and executive function (-0.16 [95 % CI, -0.26 to -0.06] points per year for every 10 years of higher age), but not memory (-0.006 [95 % CI, -0.15 to 0.14]), after compared to before stroke. CONCLUSION Older age was associated with greater post-stroke cognitive declines, accounting for differences in pre-stroke cognitive trajectories between the old and the young.
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Affiliation(s)
- Mellanie V Springer
- Department of Neurology and Stroke Program, University of Michigan, Ann Arbor, MI, USA; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA.
| | - Bingxin Chen
- Department of Nursing, University of Michigan, Ann Arbor, MI, USA
| | - Rachael T Whitney
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Emily M Briceño
- Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA; Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, MI, USA
| | - Alden L Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School Public Health, Baltimore, MD, USA
| | - Hugo J Aparicio
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, USA
| | - Alexa S Beiser
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - James F Burke
- Department of Neurology, Ohio State University College of Medicine, Columbus, OH, USA
| | - Bruno Giordani
- Department of Psychiatry and Michigan Alzheimer's Disease Center, University of Michigan, Ann Arbor, MI, USA
| | - Rebecca F Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Rodney A Hayward
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA; Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA; VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Virginia J Howard
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Silvia Koton
- Department of Epidemiology, Johns Hopkins Bloomberg School Public Health, Baltimore, MD, USA; Department of Nursing, The Stanley Steyer School of Health Professions, Tel Aviv University, Tel Aviv, Israel
| | - Ronald M Lazar
- Department of Neurology and Evelyn F. McKnight Brain Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jeremy B Sussman
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA; Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA; VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Wen Ye
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Deborah A Levine
- Department of Neurology and Stroke Program, University of Michigan, Ann Arbor, MI, USA; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA; Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
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16
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Hawwash NK, Sperrin M, Martin GP, Sinha R, Matthews CE, Ricceri F, Tjønneland A, Heath AK, Neuhouser ML, Joshu CE, Platz EA, Freisling H, Gunter MJ, Renehan AG. Excess weight by degree and duration and cancer risk (ABACus2 consortium): a cohort study and individual participant data meta-analysis. EClinicalMedicine 2024; 78:102921. [PMID: 39640936 PMCID: PMC11617392 DOI: 10.1016/j.eclinm.2024.102921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 10/16/2024] [Accepted: 10/23/2024] [Indexed: 12/07/2024] Open
Abstract
Background Elevated body mass index (BMI) ≥25 kg/m2 is a major preventable cause of cancer. A single BMI measure does not capture the degree and duration of exposure to excess BMI. We investigate associations between adulthood overweight-years, incorporating exposure time to BMI ≥25 kg/m2, and cancer incidence, and compare this with single BMI. Methods In this cohort study and individual participant data meta-analysis, we obtained data from the ABACus 2 Consortium, consisting of four US cohorts: Atherosclerosis Risk in Communities (ARIC) study (1987-2015), Women's Health Initiative (WHI; 1991 to 2005 [main study], to 2010 [Extension 1], and to 2020 [Extension 2]), Prostate, Lung, Colorectal, Ovarian Cancer Screening (PLCO) Trial (1993-2009), NIH-AARP Diet and Health Study (1996-2011), and one European cohort, the European Prospective Investigation into Cancer and Nutrition (EPIC; participants enrolled in 1990 and administrative censoring was centre-specific). Participants with at least 3 BMI measurements and complete cancer follow-up data were included. We calculated overweight-years: degree of overweight (BMI ≥25 kg/m2) multiplied by the duration of overweight (years). Using random effects two-stage individual participant data meta-analyses, associations between cancer and overweight-years, single BMI, cumulative overweight degree and duration, measured at the same time and captured over a median of 41 years in men and 39 years in women, were evaluated with Cox proportional hazards models. Models were age-adjusted or multivariable (MV) adjusted for baseline age, ethnicity, alcohol, smoking and hormone replacement therapy (HRT). Harrell's C-statistic of metrics were compared. This study is registered at PROSPERO, CRD42021238270. Findings 720,210 participants, including 312,132 men and 408,078 women, were followed up for cancer incidence over a median 9.85 years (interquartile range (IQR) 8.03, 11.67) in men and 10.80 years (IQR 6.05, 15.55) in women. 12,959 men (4.15%) and 36,509 women (8.95%) were diagnosed with obesity-related cancer. Hazard ratios for obesity-related cancers in men, per 1 standard deviation (SD) overweight-years were 1.15 (95% CI: 1.14, 1.16, I2: 0) age-adjusted and 1.15 (95% CI: 1.13, 1.17, I2: 0%) MV-adjusted and per 1SD increment in single BMI were 1.17 (95% CI: 1.16, 1.18, I2: 0) age-adjusted and 1.16 (95% CI: 1.15, 1.18, I2: 0%) MV-adjusted. The HR for overweight-years in women per 1 SD increment was 1.08 (95% CI: 1.04, 1.13, I2: 82%) age-adjusted and 1.08 (95% CI: 1.04, 1.13, I2: 83%) MV-adjusted and per 1SD increment in single BMI was 1.10 (95% CI: 1.07, 1.14, I2: 72%) age-adjusted and 1.11 (95% CI: 1.07, 1.15, I2: 79%) MV-adjusted. C-statistics for overweight-years and single BMI for obesity-related cancers were 0.612 (95% CI: 0.578, 0.646) and 0.611 (95% CI: 0.578, 0.644) respectively for men and 0.566 (95% CI: 0.534, 0.598) and 0.573 (95% CI: 0.546, 0.600) for women. Interpretation Adulthood degree and duration of excess BMI were associated with cancer risk. Both factors should be considered in cancer prevention strategies and policies. This study only focused on adulthood exposure to excess BMI, so the minimal differences in the predictive performance between adiposity metrics may be due to underestimation of cumulative excess BMI exposure. Funding Cancer Research UK, the Manchester NIHR Biomedical Research Centre, the National Cancer Institute, the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, U.S. Department of Health and Human Services, the Intramural Research Program of the National Cancer Institute, the International Agency for Research on Cancer, Imperial College London, European Commission (DG-SANCO), the Danish Cancer Society, Ligue Contre le Cancer, Institut Gustave-Roussy, Mutuelle Générale de l'Education Nationale, Institut National de la Santé et de la Recherche Médicale, Deutsche Krebshilfe, Deutsches Krebsforschungszentrum, German Federal Ministry of Education and Research, the Hellenic Health Foundation, Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council, Dutch Ministry of Public Health, Welfare, and Sports, Netherlands Cancer Registry, LK Research Funds, Dutch Prevention Funds, Dutch Zorg Onderzoek Nederland, World Cancer Research Fund, Statistics Netherlands, Health Research Fund, Instituto de Salud Carlos III, regional Spanish governments of Andalucía, Asturias, Basque Country, Murcia, and Navarra, the Catalan Institute of Oncology, Swedish Cancer Society, Swedish Scientific Council, and Region Skåne and Region Västerbotten, and the Medical Research Council.
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Affiliation(s)
- Nadin K. Hawwash
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Cancer Research UK Manchester Cancer Research Centre, Manchester, United Kingdom
| | - Matthew Sperrin
- Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Glen P. Martin
- Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Rashmi Sinha
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Shady Grove, USA
| | - Charles E. Matthews
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Shady Grove, USA
| | - Fulvio Ricceri
- Centre for Biostatistics, Epidemiology, and Public Health (C-BEPH), Department of Clinical and Biological Sciences, University of Turin, Regione Gonzole 10, Orbassano (TO), Italy
| | - Anne Tjønneland
- Danish Cancer Institute, Strandboulevarden 49, 2100 Copenhagen O, Denmark
| | - Alicia K. Heath
- Cancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London, London, W2 1PG, United Kingdom
| | - Marian L. Neuhouser
- Cancer Prevention Program, Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Corinne E. Joshu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Heinz Freisling
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Marc J. Gunter
- Cancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London, London, W2 1PG, United Kingdom
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Andrew G. Renehan
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Cancer Research UK Manchester Cancer Research Centre, Manchester, United Kingdom
- National Institute for Health Research (NIHR) Manchester Biomedical Research Centre, Manchester, United Kingdom
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17
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Rooney MR, Norby FL, Soliman EZ, Chen LY, Selvin E, Echouffo-Tcheugui JB. Duration of diabetes, glycemic control, and low heart rate variability: The Atherosclerosis Risk in Communities (ARIC) study. J Diabetes Complications 2024; 38:108903. [PMID: 39541734 PMCID: PMC11588038 DOI: 10.1016/j.jdiacomp.2024.108903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2024] [Revised: 10/17/2024] [Accepted: 11/03/2024] [Indexed: 11/16/2024]
Abstract
Persons with long-standing, poorly controlled diabetes or recent hyperglycemia had the highest burden of cardiac autonomic neuropathy. Cardiac autonomic neuropathy contributed to elevated long-term incidence of cardiovascular disease and mortality even in persons with well-controlled diabetes.
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Affiliation(s)
- Mary R Rooney
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
| | - Faye L Norby
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Elsayed Z Soliman
- Epidemiological Cardiology Research Center, School of Medicine, Wake Forest Univ, Winston-Salem, NC, United States
| | - Lin Yee Chen
- Lillehei Heart Institute and Department of Medicine (Cardiovascular Division), Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Elizabeth Selvin
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Justin B Echouffo-Tcheugui
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University, Baltimore, MD, United States
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18
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Inciardi RM, Wang W, Alonso A, Soliman EZ, Selvaraj S, Gonçalves A, Zhang MJ, Chandra A, Prasad NG, Skali H, Shah AM, Solomon SD, Chen LY. Cardiac mechanics and the risk of atrial fibrillation in a community-based cohort of older adults. Eur Heart J Cardiovasc Imaging 2024; 25:1686-1694. [PMID: 38959330 DOI: 10.1093/ehjci/jeae162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 05/15/2024] [Accepted: 06/30/2024] [Indexed: 07/05/2024] Open
Abstract
AIMS Assessment of cardiac structure and function improves risk prediction of new-onset atrial fibrillation (AF) in different populations. We aimed to comprehensively compare standard and newer measures of cardiac structure and function in improving prediction of AF in a cohort of older adults without history of AF and stroke. METHODS AND RESULTS We included 5050 participants without prevalent AF and stroke (mean age 75 ± 5 years, 59% women, and 22% Black) from the Atherosclerosis Risk in Communities (ARIC) study who underwent complete two-dimensional echocardiography, including speckle-tracking analysis of the left ventricle (LV) and left atrium (LA). We assessed the association of cardiac measures with incident AF (including atrial flutter) and quantified the extent to which these measures improved model discrimination and risk classification of AF compared with the CHARGE-AF score. Over a median follow-up time of 7 years, 676 participants developed AF (incidence rate 2.13 per 100 person-years). LV mass index and wall thickness, E/e', and measures of LA structure and function, but not LV systolic function, were associated with incident AF, after accounting for confounders. Above all, LA reservoir strain, contraction strain, and LA minimal volume index (C-statistics [95% confidence interval]: 0.73 [0.70, 0.75], 0.72 [0.70, 0.75], and 0.72 [0.69, 0.75], respectively) significantly improved the risk discrimination of the CHARGE-AF score (baseline C-statistic: 0.68 [0.65, 0.70]) and achieved the highest category-based net reclassification improvement (29%, 24%, and 20%, respectively). CONCLUSION In a large cohort of older adults without prevalent AF and stroke, measures of LA function improved the prediction of AF more than other conventional cardiac measures.
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Affiliation(s)
- Riccardo M Inciardi
- Cardiovascular Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Cardiology, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Italy
| | - Wendy Wang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, MN, USA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Elsayed Z Soliman
- Section on Cardiovascular Medicine, Department of Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Senthil Selvaraj
- Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Alexandra Gonçalves
- Philips Healthcare, 3000 Minuteman Road, Andover, MA, USA
- University of Porto Medical School, Porto, Portugal
| | - Michael J Zhang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, MN, USA
| | - Alvin Chandra
- Department of Internal Medicine, Division of Cardiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Narayana G Prasad
- Cardiovascular Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Hicham Skali
- Cardiovascular Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Amil M Shah
- Cardiovascular Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Scott D Solomon
- Cardiovascular Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Lin Yee Chen
- Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, 420 Delaware Street SE, MMC 508, Minneapolis, MN 55455, USA
- Lillehei Heart Institute, University of Minnesota Medical School, 420 Delaware Street SE, MMC 508, Minneapolis, MN 55455, USA
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19
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Young L, Richey LN, Law CA, Esagoff AI, Ismail Z, Senjem ML, Jack CR, Shrestha S, Gottesman RF, Moussawi K, Peters ME, Schneider ALC. Associations of Mild Behavioral Impairment Domains with Brain Volumes: Cross-sectional Analysis of Atherosclerosis Risk in Community (ARIC) Study. J Acad Consult Liaison Psychiatry 2024:S2667-2960(24)00117-4. [PMID: 39603508 DOI: 10.1016/j.jaclp.2024.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Revised: 11/03/2024] [Accepted: 11/18/2024] [Indexed: 11/29/2024]
Abstract
BACKGROUND Mild behavioral impairment (MBI) has been associated with global brain atrophy, but the regional neural correlates of MBI symptoms are less clear, particularly among community-dwelling older individuals without dementia. OBJECTIVE Our objective was to examine the associations of MBI domains with gray matter (GM) volumes in a large population-based sample of older adults without dementia. METHODS We performed a cross-sectional study of 1445 community-dwelling older adults in the Atherosclerosis Risk in Communities Study who underwent detailed neurocognitive assessment and brain magnetic resonance imaging in 2011-2013. MBI domains were defined using an established algorithm that maps data collected from informants on the Neuropsychiatric Inventory Questionnaire to the 5 MBI domains of decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, and abnormal perception/thought content. We performed voxel-based morphometry analyses to investigate associations of any MBI domain symptoms with GM volumes. We additionally performed region-of-interest analyses using adjusted linear regression models to examine associations between individual MBI domains with a priori-hypothesized regional GM volumes. RESULTS Overall, the mean age of participants was 76.5 years; 59% were female, 21% were of Black race, and 26% had symptoms in at least one MBI domain. Participants with normal cognition comprised 60% of the population, and 40% had mild cognitive impairment. Compared to individuals without any MBI domain symptoms, voxel-based morphometry analyses showed that participants with symptoms in at least one MBI domain had consistently lower GM volumes in the cerebellum and bilateral temporal lobes, particularly involving the hippocampus. In adjusted region-of-interest models, affective dysregulation domain symptoms were associated with lower GM volume in the inferior temporal lobe (β = -0.34; 95% confidence interval = -0.64, -0.04), and impulse dyscontrol domain symptoms were associated with lower GM volume in the parahippocampal gyrus (β = -0.06; 95% confidence interval = -0.11, 0.00). CONCLUSIONS In this community-dwelling population of older adults without dementia, MBI symptoms were associated with lower GM volumes in regions commonly implicated in early Alzheimer's disease pathology. These findings lend support to the notion that MBI symptoms may be useful in identifying individuals at risk for future dementia.
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Affiliation(s)
- Lisa Young
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.
| | - Lisa N Richey
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Connor A Law
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Aaron I Esagoff
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Zahinoor Ismail
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada; NIHR Exeter Biomedical Research Centre, University of Exeter, Exeter, UK
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, MN; Mayo Clinic Department of Information Technology, Rochester, MN
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, MN
| | - Srishti Shrestha
- University of Mississippi Medical Center School of Medicine, The MIND Center and Department of Neurology, Oxford, MS
| | - Rebecca F Gottesman
- National Institutes of Health, National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD
| | - Khaled Moussawi
- Department of Neurology, University of California San Francisco, San Francisco, CA
| | - Matthew E Peters
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Andrea L C Schneider
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
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20
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Hong YS, Pasca S, Shi W, Puiu D, Lake NJ, Lek M, Ru M, Grove ML, Prizment A, Joshu CE, Platz EA, Guallar E, Arking DE, Gondek LP. Mitochondrial heteroplasmy improves risk prediction for myeloid neoplasms. Nat Commun 2024; 15:10133. [PMID: 39578475 PMCID: PMC11584845 DOI: 10.1038/s41467-024-54443-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 11/07/2024] [Indexed: 11/24/2024] Open
Abstract
Clonal hematopoiesis of indeterminate potential is the primary pathogenic risk factor for myeloid neoplasms, while heteroplasmy (mutations in a subset of cellular mitochondrial DNA) is another marker of clonal expansion associated with hematological malignancies. We explore how these two markers relate and influence myeloid neoplasms incidence, and their role in risk stratification. We find that heteroplasmy is more common in individuals with clonal hematopoiesis of indeterminate potential, particularly those with higher variant allele fractions, multiple mutations, or spliceosome machinery mutations. Individuals with both markers have a higher risk of myeloid neoplasms than those with either alone. Furthermore, heteroplasmic variants with higher predicted deleteriousness increase the risk of myeloid neoplasms. Incorporating heteroplasmy in an existing risk score model for individuals with clonal hematopoiesis of indeterminate potential significantly improves sensitivity and better identifies high-risk groups. This suggests heteroplasmy as a clonal expansion marker and potentially as a biomarker for myeloid neoplasms development.
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Affiliation(s)
- Yun Soo Hong
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sergiu Pasca
- Division of Hematological Malignancies, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wen Shi
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniela Puiu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nicole J Lake
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Meng Ru
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Megan L Grove
- Human Genetics Center; Department of Epidemiology, Human Genetics, and Environmental Sciences; School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Anna Prizment
- Department of Laboratory Medicine & Pathology, University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - Corinne E Joshu
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth A Platz
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Eliseo Guallar
- Department of Epidemiology, School of Global Public Health, New York University, New York, NY, USA
| | - Dan E Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Lukasz P Gondek
- Division of Hematological Malignancies, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Egle M, Johri M, Power MC, Deal JA, Jack CR, Sullivan KJ, Mosley TH, Gottesman RF. Two-Stage Recruitment Design to Reduce Magnetic Resonance Imaging Screening Cost for a Theoretical Clinical Trial of White Matter Hyperintensity Progression. J Am Heart Assoc 2024; 13:e036140. [PMID: 39547991 DOI: 10.1161/jaha.124.036140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 09/20/2024] [Indexed: 11/17/2024]
Abstract
BACKGROUND White matter hyperintensities (WMH) and their progression are associated with risk of dementia and stroke, so are an important target for clinical trials. The cost of broad magnetic resonance imaging (MRI) screening to identify eligible individuals, however, limits the feasibility of designing clinical trials targeting WMH. A low-cost retinal or clinical screening measure before MRI could reduce recruitment costs versus an MRI-only screening design in a hypothetical clinical trial. METHODS AND RESULTS Data from the Atherosclerosis Risk in Communities study with valid retinal and WMH measurements (N=1311) were used. To identify a population at greater likelihood of significant WMH on MRI and thus reduce the number of screening MRIs required, we evaluated 3 theoretical prescreening measures: (1) retinal, (2) clinical, (3) combined clinical-retinal. Given a target sample for clinical trials (N=646), we calculated screening sample sizes based on the proportion within the population having an elevated score for each prescreening measure (separately) multiplied by the proportion of significant WMH among those with that prescreening feature. Recruitment costs were calculated using estimated retinal and MRI cost estimates. Compared with the estimated cost of MRI-only screening (>$4.24 million, requiring MRI on 6526 participants), prescreening for a high clinical score resulted in total cost of $2.47 million, with an initial screening group of 52 778 participants, with MRI in 3801. A high clinical-retinal score cutoff resulted in costs of $2.9 million while requiring 13 572 participants, with 3801 completing MRI. CONCLUSIONS A 2-stage design with low-cost prescreening measures is a promising approach, resulting in reduced theoretical recruitment costs compared with an MRI-only design.
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Affiliation(s)
- Marco Egle
- National Institute of Neurological Disorders and Stroke, Intramural Research Program National Institutes of Health Bethesda MD USA
| | - Mohini Johri
- National Institute of Neurological Disorders and Stroke, Intramural Research Program National Institutes of Health Bethesda MD USA
| | - Melinda C Power
- Department of Epidemiology George Washington University Milken Institute School of Public Health Washington DC USA
| | - Jennifer A Deal
- Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD USA
| | | | - Kevin J Sullivan
- Department of Medicine University of Mississippi Medical Center Jackson MS USA
| | - Thomas H Mosley
- Department of Medicine University of Mississippi Medical Center Jackson MS USA
| | - Rebecca F Gottesman
- National Institute of Neurological Disorders and Stroke, Intramural Research Program National Institutes of Health Bethesda MD USA
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22
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Rooney MR, Wallace AS, Echouffo Tcheugui JB, Fang M, Hu J, Lutsey PL, Grams ME, Coresh J, Selvin E. Prediabetes is associated with elevated risk of clinical outcomes even without progression to diabetes. Diabetologia 2024:10.1007/s00125-024-06315-0. [PMID: 39531040 DOI: 10.1007/s00125-024-06315-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Accepted: 09/24/2024] [Indexed: 11/16/2024]
Abstract
AIMS/HYPOTHESIS Prediabetes (HbA1c 39-47 mmol/mol [5.7-6.4%] or fasting glucose 5.6-6.9 mmol/l) is associated with elevated risks of microvascular and macrovascular complications. It is unknown to what extent these risks in prediabetes remain after accounting for progression to diabetes. METHODS In 10,310 participants from the Atherosclerosis Risk in Communities (ARIC) Study (aged 46-70 years, ~55% women, ~20% Black adults) without diabetes at baseline (1990-1992), we used Cox regression to characterise age- and sex-adjusted associations of prediabetes with ~30 year incidence of complications (composite and separately), including atherosclerotic CVD (ASCVD), heart failure, chronic kidney disease (CKD) and all-cause mortality before and after accounting for intervening incidence of diabetes, modelled as a time-varying variable. We calculated the excess risk of complications in prediabetes remaining after accounting for progression to diabetes. RESULTS Of the 60% of adults with prediabetes at baseline, ~30% progressed to diabetes (median time to diabetes, 7 years). Over the maximum follow-up of ~30 years, there were 7069 events (1937 ASCVD, 2109 heart failure, 3288 CKD and 4785 deaths). Prediabetes was modestly associated with risk of any complication (HR 1.21 [95% CI 1.15, 1.27]) vs normoglycaemia. This association remained significant after accounting for progression to diabetes (HR 1.18 [95% CI 1.12, 1.24]) with 85% (95% CI 75, 94%) of the excess risk of any complication in prediabetes remaining. Results were similar for the individual complications. CONCLUSIONS/INTERPRETATION Progression to diabetes explained less than one-quarter of the risks of clinical outcomes associated with prediabetes. Prediabetes contributes to the risk of clinical outcomes even without progression to diabetes.
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Affiliation(s)
- Mary R Rooney
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Amelia S Wallace
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Justin B Echouffo Tcheugui
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Michael Fang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jiaqi Hu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Institute for Hospital Management, Tsinghua University, Beijing, China
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Morgan E Grams
- Division of Precision Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Josef Coresh
- Optimal Aging Institute, New York University Grossman School of Medicine, New York, NY, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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23
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Huang AR, Morales EG, Arnold ML, Burgard S, Couper D, Deal JA, Glynn NW, Gmelin T, Goman AM, Gravens-Mueller L, Hayden KM, Mitchell CM, Pankow JS, Pike JR, Reed NS, Sanchez VA, Schrack JA, Sullivan KJ, Coresh J, Lin FR, Chisolm TH. A Hearing Intervention and Health-Related Quality of Life in Older Adults: A Secondary Analysis of the ACHIEVE Randomized Clinical Trial. JAMA Netw Open 2024; 7:e2446591. [PMID: 39570588 PMCID: PMC11582982 DOI: 10.1001/jamanetworkopen.2024.46591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2024] Open
Abstract
Importance Health-related quality of life is a critical health outcome and a clinically important patient-reported outcome in clinical trials. Hearing loss is associated with poorer health-related quality-of-life in older adults. Objective To investigate the 3-year outcomes of hearing intervention vs health education control on health-related quality of life. Design, Setting, and Participants This secondary analysis of a randomized clinical trial included participants treated for hearing loss at multiple US centers between 2018 and 2019 with 3-year follow-up completed in 2022. Eligible participants were aged 70 to 84 years, had untreated hearing loss, and were without substantial cognitive impairment. Participants were randomized (1:1) to hearing intervention or health education control and followed every 6 months. Intervention Hearing intervention (provision of hearing aids and related technologies, counseling, education) or health education control (individual sessions covering topics relevant to chronic disease, disability prevention). Main Outcomes and Measures Three-year change in the RAND-36 physical and mental health component scores over 3 years. The 8 individual domains of health-related quality-of-life were additionally assessed. Outcomes measured at baseline and at 6-month, 1-year, 2-year, and 3-year follow-ups. Intervention effect sizes estimated using a 2-level linear mixed effects model under the intention-to-treat principle. Results A total of 977 participants were analyzed (mean [SD] age, 76.8 [4.0] years; 523 female [53.5%]; 112 Black [11.5%], 858 White [87.8%]; 521 had a Bachelor's degree or higher [53.4%]), with 490 in the hearing intervention and 487 in the control group. Over 3 years, hearing intervention (vs health education control) had no significant association with physical (intervention, -0.49 [95% CI, -3.05 to 2.08]; control, -0.92 [95% CI, -3.39 to 1.55]; difference, 0.43 [95% CI, -0.64 to 1.51]) or mental (intervention, 0.38 [95% CI, -1.58 to 2.34]; control, -0.09 [95% CI, -1.99 to 1.81]; difference, 0.47 [95% CI, -0.41 to 1.35]) health-related quality of life. Conclusions and Relevance In this secondary analysis of a randomized clinical trial, hearing intervention had no association with physical and mental health-related quality-of-life over 3 years among older adults with hearing loss. Additional intervention strategies may be needed to modify health-related quality among older adults with hearing loss. Trial Registration ClinicalTrials.gov Identifier: NCT03243422.
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Affiliation(s)
- Alison R Huang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Emmanuel Garcia Morales
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Michelle L Arnold
- College of Science and Mathematics, University of South Florida Sarasota-Manatee
| | - Sheila Burgard
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - Jennifer A Deal
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Nancy W Glynn
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania
| | - Theresa Gmelin
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania
| | - Adele M Goman
- School of Health and Social Care, Edinburgh Napier University, Edinburgh, United Kingdom
| | - Lisa Gravens-Mueller
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - Kathleen M Hayden
- Department of Social Sciences and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Christine M Mitchell
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis
| | - James R Pike
- Optimal Aging Institute, Department of Population Health and Medicine, New York University Grossman School of Medicine, New York University Langone Health, New York
| | - Nicholas S Reed
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Victoria A Sanchez
- College of Science and Mathematics, University of South Florida Sarasota-Manatee
| | - Jennifer A Schrack
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Kevin J Sullivan
- Department of Medicine: The MIND Center, The University of Mississippi Medical Center, Jackson
| | - Josef Coresh
- Optimal Aging Institute, Department of Population Health and Medicine, New York University Grossman School of Medicine, New York University Langone Health, New York
| | - Frank R Lin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Theresa H Chisolm
- College of Science and Mathematics, University of South Florida Sarasota-Manatee
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Du S, Chen J, Kim H, Lichtenstein AH, Yu B, Appel LJ, Coresh J, Rebholz CM. Protein Biomarkers of Ultra-Processed Food Consumption and Risk of Coronary Heart Disease, Chronic Kidney Disease, and All-Cause Mortality. J Nutr 2024; 154:3235-3245. [PMID: 39299474 PMCID: PMC11600079 DOI: 10.1016/j.tjnut.2024.08.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 07/01/2024] [Accepted: 08/01/2024] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND There is a need to understand the underlying biological mechanisms through which ultra-processed foods negatively affect health. Proteomics offers a valuable tool with which to examine different aspects of ultra-processed foods and their impact on health. OBJECTIVES The aim of this study was to identify protein biomarkers of usual ultra-processed food consumption and assess their relation to the incidence of coronary heart disease (CHD), chronic kidney disease (CKD), and all-cause mortality risk. METHODS A total of 9361 participants from the Atherosclerosis Risk in Communities visit 3 (1993-1995) were included. Dietary intake was assessed using a 66-item food-frequency questionnaire and the processing levels were categorized on the basis of the Nova classification. Plasma proteins were detected using an aptamer-based proteomic assay. We used multivariable linear regressions to examine the association between ultra-processed food and proteins, and Cox proportional hazard models to identify associations between ultra-processed food-related proteins and health outcomes. Models extensively controlled for sociodemographic characteristics, health behaviors, and clinical factors. RESULTS Eight proteins (6 positive, 2 negative) were identified as significantly associated with ultra-processed food consumption. Over a median follow-up of 22 y, there were 1276, 3084, and 5127 cases of CHD, CKD, and death, respectively. Three, 5, and 3 ultra-processed food-related proteins were associated with each outcome, respectively. One protein (β-glucuronidase) was significantly associated with a higher risk of all 3 outcomes, and 3 proteins (receptor-type tyrosine-protein phosphatase U, C-C motif chemokine 25, and twisted gastrulation protein homolog 1) were associated with a higher risk of 2 outcomes. CONCLUSIONS We identified a panel of protein biomarkers that were significantly associated with ultra-processed food consumption. These proteins may be considered potential biomarkers for ultra-processed food intake and may elucidate the biological processes through which ultra-processed foods impact health outcomes.
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Affiliation(s)
- Shutong Du
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Jingsha Chen
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Hyunju Kim
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, United States
| | - Alice H Lichtenstein
- Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Lawrence J Appel
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Josef Coresh
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States; Department of Medicine, New York University Grossman School of Medicine, New York, NY, United States
| | - Casey M Rebholz
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.
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25
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Hawwash N, Sperrin M, Martin GP, Joshu CE, Florido R, Platz EA, Renehan AG. Waist circumference-years and cancer risk: a prospective study of the association and comparison of predictive performance with waist circumference and body mass index. Br J Cancer 2024; 131:1623-1634. [PMID: 39367274 PMCID: PMC11554801 DOI: 10.1038/s41416-024-02860-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 09/09/2024] [Accepted: 09/18/2024] [Indexed: 10/06/2024] Open
Abstract
BACKGROUND Associations of waist circumferences (WC) and body mass index (BMI) measured once or over time, with cancer incidence were studied. WC is associated with some cancers independent of BMI. Analyses of cumulative central adiposity and cancer are lacking. We investigated associations between waist circumference-years, incorporating exposure time to WC ≥ 102 cm in men or ≥88 cm in women, and cancer, and compared this with single WC or BMI. METHODS Serial WC measurements taken over 9 years in the prospective Atherosclerosis Risk in Communities Study (ARIC) predicted yearly WC. Cox proportional hazards regression estimated hazard ratios (HRs) of cancer incidence for waist circumference-years, WC or BMI, measured in Visit 4. Harrell's C-statistic quantified metric predictive performances. RESULTS 10,172 participants were followed up from Visit 4 for cancer over a median 13.7 for men and 15.8 years for women. For obesity-related cancers, HRs per standard deviation waist circumference-years were 1.14 (95%CI:1.04,1.25) and 1.19 (95%CI:1.12,1.27), respectively. Differences in metric predictive performances were marginal. DISCUSSION This is the first study to identify positive associations between waist circumference-years and cancer. Waist circumference-years did not provide additional information on cancer risk beyond that of WC and BMI. BMI is routinely measured in clinic so it may be preferred over WC.
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Affiliation(s)
- Nadin Hawwash
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
- Cancer Research UK Manchester Cancer Research Centre, Manchester, UK.
| | - Matthew Sperrin
- Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Glen P Martin
- Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Corinne E Joshu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Roberta Florido
- Johns Hopkins University School of Medicine, Department of Medicine, Division of Cardiology, Baltimore, MD, USA
- Department of Medicine, Division of Cardiology, University of Utah, Salt Lake City, UT, USA
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Andrew G Renehan
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- National Institute for Health Research (NIHR) Manchester Biomedical Research Centre, Manchester, UK
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Deshotels MR, Al Rifai M, Sun C, Agha A, Selvin E, Windham BG, Vaccarino V, Michos ED, Jneid H, Levine GN, Fagundes C, Virani SS, Ballantyne CM, Nambi V. Vital Exhaustion and Biomarkers Associated With Cardiovascular Risk: The ARIC Study. JACC. ADVANCES 2024; 3:101355. [PMID: 39539949 PMCID: PMC11557454 DOI: 10.1016/j.jacadv.2024.101355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 09/15/2024] [Accepted: 09/17/2024] [Indexed: 11/16/2024]
Abstract
Background Vital exhaustion, defined as excessive fatigue, demoralization, and irritability due to chronic stress, is independently associated with cardiovascular disease (CVD). Objectives The purpose of this study was to examine the association of vital exhaustion with biomarkers associated with CVD risk in the ARIC (Atherosclerosis Risk In Communities) study. Methods We examined the cross-sectional association of vital exhaustion (assessed using the Maastricht Vital Exhaustion Questionnaire [MVEQ]) with cardiac biomarker (high-sensitivity troponin T [hs-TnT], N-terminal pro-B-type natriuretic peptide [NT-proBNP]) and high-sensitivity C-reactive protein (hs-CRP) levels in 11,542 ARIC study participants without CVD at ARIC visit 2 using multivariable logistic and linear regression models. We then analyzed the association of vital exhaustion symptoms in the presence or absence of elevated biomarker levels with incident CVD events (coronary heart disease, ischemic stroke, or heart failure hospitalization) and all-cause mortality over a 10- and 20-year follow-up period using Cox proportional hazard models. Results Compared with the lowest quartile of vital exhaustion (MVEQ ≤4), the highest quartile (MVEQ 16-42) was associated with elevated hs-TnT, NT-proBNP, and hs-CRP, with ORs of 1.75 (95% CI: 1.34-2.29), 1.40 (95% CI: 1.19-1.64), and 1.14 (95% CI: 1.01-1.28), respectively. The presence of both severe symptoms of vital exhaustion and elevated biomarker levels was associated with greater risk of CVD events and all-cause mortality. Conclusions In middle-aged adults without CVD, vital exhaustion was associated with elevated hs-TnT, NT-proBNP, and hs-CRP, independent of traditional CVD risk factors. Evaluation of vital exhaustion symptoms and cardiac biomarker levels can help identify individuals at increased risk for incident CVD events and all-cause mortality.
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Affiliation(s)
- Matthew R. Deshotels
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Mahmoud Al Rifai
- Division of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas, USA
| | - Caroline Sun
- Section of Cardiovascular Research and Center for Cardiometabolic Disease Prevention, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Ali Agha
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - B. Gwen Windham
- Division of Geriatrics, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Viola Vaccarino
- Department of Epidemiology, Rollins School of Public Health, and Department of Medicine (Cardiology), School of Medicine, Emory University, Atlanta, Georgia, USA
| | - Erin D. Michos
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hani Jneid
- Department of Cardiology, University of Texas Medical Branch, Galveston, Texas, USA
| | - Glenn N. Levine
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
- Section of Cardiology, Michael E. DeBakey Department of Veterans Affairs Medical Center, Houston, Texas, USA
| | | | - Salim S. Virani
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
- Office of Research and Graduate Studies, Aga Khan University, Karachi, Pakistan
| | - Christie M. Ballantyne
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
- Section of Cardiovascular Research and Center for Cardiometabolic Disease Prevention, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Vijay Nambi
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
- Section of Cardiovascular Research and Center for Cardiometabolic Disease Prevention, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
- Section of Cardiology, Michael E. DeBakey Department of Veterans Affairs Medical Center, Houston, Texas, USA
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Bessen SY, Zhang W, Huang AR, Arnold M, Burgard S, Chisolm TH, Couper D, Deal JA, Faucette SP, Goman AM, Glynn NW, Gmelin T, Gravens-Mueller L, Hayden KM, Mitchell CM, Pankow JS, Pike JR, Reed NS, Sanchez VA, Schrack JA, Sullivan KJ, Coresh J, Lin FR, Martinez-Amezcua P. Effect of Hearing Intervention Versus Health Education Control on Fatigue: A Secondary Analysis of the ACHIEVE Study. J Gerontol A Biol Sci Med Sci 2024; 79:glae193. [PMID: 39093692 PMCID: PMC11402025 DOI: 10.1093/gerona/glae193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND Fatigue is a common complaint among older adults with hearing loss. The impact of addressing hearing loss on fatigue symptoms has not been studied in a randomized controlled trial. In a secondary analysis of the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) study, we investigated the effect of hearing intervention versus health education control on 3-year change in fatigue in community-dwelling older adults with hearing loss. METHODS Participants aged 70-84 years old with untreated hearing loss recruited across 4 study sites in the United States (Forsyth County, North Carolina; Jackson, Mississippi; Minneapolis, Minnesota; Washington County, Maryland) were randomized (1:1) to hearing intervention or health education control and followed for 3 years. Three-year change in fatigue symptoms was measured by 2 instruments (RAND-36 and PROMIS). We estimated the intervention effect as the difference in the 3-year change in fatigue between intervention and control groups using a linear mixed-effects model under the intention-to-treat principle. RESULTS Participants (n = 977) had a mean age (SD) of 76.8 (4.0) years, were 53.5% female and 87.8% White. Over 3 years, a beneficial effect of the hearing intervention versus health education control on fatigue was observed using the RAND-fatigue score (β = -0.12 [95% CI: -0.22, -0.02]). Estimates also suggested beneficial effect of hearing intervention on fatigue when measured by the PROMIS-fatigue score (β = -0.32 [95% CI: -1.15, 0.51]). CONCLUSIONS Our findings suggest that hearing intervention may reduce fatigue over 3 years among older adults with hearing loss.
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Affiliation(s)
- Sarah Y Bessen
- Department of Otolaryngology—Head and Neck Surgery, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Wuyang Zhang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Alison R Huang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Michelle Arnold
- Department of Communication Sciences and Disorders, University of South Florida, Tampa, Florida, USA
| | - Sheila Burgard
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Theresa H Chisolm
- Department of Communication Sciences and Disorders, University of South Florida, Tampa, Florida, USA
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Jennifer A Deal
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Sarah P Faucette
- Department of Medicine, The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Adele M Goman
- School of Health and Social Care, Edinburgh Napier University, Edinburgh, UK
| | - Nancy W Glynn
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Theresa Gmelin
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Lisa Gravens-Mueller
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Kathleen M Hayden
- Department of Social Sciences and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Christine M Mitchell
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - James R Pike
- Optimal Aging Institute, NYU Grossman School of Medicine, New York, New York, USA
| | - Nicholas S Reed
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Optimal Aging Institute, NYU Grossman School of Medicine, New York, New York, USA
| | - Victoria A Sanchez
- Department of Otolaryngology—Head and Neck Surgery, University of South Florida, Tampa, Florida, USA
| | - Jennifer A Schrack
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kevin J Sullivan
- Department of Medicine, The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Josef Coresh
- Optimal Aging Institute, NYU Grossman School of Medicine, New York, New York, USA
| | - Frank R Lin
- Department of Otolaryngology—Head and Neck Surgery, Johns Hopkins University, Baltimore, Maryland, USA
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Pablo Martinez-Amezcua
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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Yu Z, Vromman A, Nguyen NQH, Schuermans A, Rentz T, Vellarikkal SK, Uddin MM, Niroula A, Griffin G, Honigberg MC, Lin AE, Gibson CJ, Katz DH, Tahir U, Fang S, Haidermota S, Ganesh S, Antoine T, Weinstock J, Austin TR, Ramachandran VS, Peloso GM, Hornsby W, Ganz P, Manson JE, Haring B, Kooperberg CL, Reiner AP, Bis JC, Psaty BM, Min YI, Correa A, Lange LA, Post WS, Rotter JI, Rich SS, Wilson JG, Ebert BL, Yu B, Ballantyne CM, Coresh J, Sankaran VG, Bick AG, Jaiswal S, Gerszten RE, Libby P, Gupta RM, Natarajan P. Human Plasma Proteomic Profile of Clonal Hematopoiesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.25.550557. [PMID: 39554199 PMCID: PMC11565774 DOI: 10.1101/2023.07.25.550557] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/19/2024]
Abstract
Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer novel insights into downstream clinical consequences. Here, we explore such patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 ancestrally diverse participants (3,881 with CHIP) from NHLBI TOPMed and UK Biobank with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2,917 proteins by Olink in UK Biobank), we identified 32 and 345 unique proteins from TOPMed and UK Biobank, respectively, associated with the most prevalent driver genes ( DNMT3A , TET2 , and ASXL1 ). These associations showed substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic Tet2 -/- vs wild-type mice validation, disentangled causal proteomic perturbations from TET2 CHIP. Lastly, we identified plasma proteins shared between CHIP and CAD.
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Giardina J, Haneuse S, Pandya A. Using Joint Longitudinal and Time-to-Event Models to Improve the Parameterization of Chronic Disease Microsimulation Models: an Application to Cardiovascular Disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.10.27.24316240. [PMID: 39574877 PMCID: PMC11581079 DOI: 10.1101/2024.10.27.24316240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2024]
Abstract
Background Chronic disease microsimulation models often simulate disease incidence as a function of risk factors that evolve over time (e.g., blood pressure increasing with age) in order to facilitate decision analyses of different disease screening and prevention strategies. Existing models typically rely on incidence rates estimated with standard survival analysis techniques (e.g., proportional hazards from baseline data) that are not designed to be continually updated each model cycle. We introduce the use of joint longitudinal and time-to-event to parameterize microsimulations to avoid potential issues from using these existing methods. These joint models include random effects regressions to estimate the risk factor trajectories and a survival model to predict disease risk based on those estimated trajectories. In a case study on cardiovascular disease (CVD), we compare the validity of microsimulation models parameterized with this joint model approach to those parameterized with the standard approaches. Methods A CVD microsimulation model was constructed that modeled the trajectory of seven CVD risk factors/predictors as a function of age (smoking, diabetes, systolic blood pressure, antihypertensive medication use, total cholesterol, HDL, and statin use) and predicted yearly CVD incidence as a function of these predictors, plus age, sex, and race. We parameterized the model using data from the Atherosclerosis Risk in Communities study (ARIC). The risk of CVD in the microsimulation was parameterized with three approaches: (1) joint longitudinal and time-to-event model, (2) proportional hazards model estimated using baseline data, and (3) proportional hazards model estimated using time-varying data. We accounted for non-CVD mortality across all the parameterization approaches. We simulated risk factor trajectories and CVD incidence from age 70y to 85y for an external test set comprised of individuals from the Multi-Ethnic Study of Atherosclerosis (MESA). We compared the simulated to observed incidence using both average survival curves and the E50 and E90 calibration metrics (the median and 90th percentile absolute difference between observed and predicted incidence) to measure the validity of each parameterization approach. Results The average CVD survival curve estimated by the microsimulation model parameterized with the joint model approach matched the observed curve from the test set relatively closely. The other parameterization methods generally performed worse, especially the proportional hazards model estimated using baseline data. Similar results were observed for the calibration metrics, with the joint model performing particularly well on the E90 metric compared to the other models. Conclusions Using a joint longitudinal and time-to-event model to parameterize a CVD simulation model produced incidence predictions that more accurately reflected observed data than a model parameterized with standard approaches. This parameterization approach could lead to more reliable microsimulation models, especially for models that evaluate policies which depend on tracking dynamic risk factors over time. Beyond this single case study, more work is needed to identify the specific circumstances where the joint model approach will outperform existing methods.
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Affiliation(s)
- John Giardina
- Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts
| | - Sebastien Haneuse
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Ankur Pandya
- Department of Health Policy and Management and Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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30
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Narinx N, Marriott RJ, Murray K, Adams RJ, Ballantyne CM, Bauer DC, Bhasin S, Biggs ML, Cawthon PM, Couper DJ, Dobs AS, Flicker L, Hankey GJ, Hannemann A, Wilkening R, Martin SA, Matsumoto AM, Ohlsson C, O'Neill TW, Orwoll ES, Shores MM, Steveling A, Travison TG, Wittert GA, Wu FCW, Antonio L, Vanderschueren D, Yeap BB. Sociodemographic, lifestyle, and medical factors associated with calculated free testosterone concentrations in men: individual participant data meta-analyses. Eur J Endocrinol 2024; 191:523-534. [PMID: 39575586 DOI: 10.1093/ejendo/lvae133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Revised: 08/30/2024] [Accepted: 09/25/2024] [Indexed: 12/06/2024]
Abstract
OBJECTIVE Sociodemographic, lifestyle, and medical variables influence total testosterone (T) and sex hormone-binding globulin (SHBG) concentrations. The relationship between these factors and "free" T remains unclear. We examined 21 sociodemographic, lifestyle, and medical predictors influencing calculated free T (cFT) in community-dwelling men across ages. DESIGN This is a cross-sectional analysis in 20 631 participants in the Androgens in Men Study. METHODS Individual participant data (IPD) were provided by 9 cohorts. Total T was determined using mass spectrometry, SHBG using immunoassays, and cFT using the Vermeulen formula. Associations were analyzed using 2-stage random effects IPD meta-analyses. RESULTS Cohort median ages ranged from 40 to 76 years and median cFT concentrations from 174.3 to 422.8 pmol/L. In men aged 17-99 years, there was a linear inverse association of cFT with age (-57.2 pmol/L [95% confidence interval, -69.4, -44.9] per 1 SD increase in age). Calculated free T increased with increasing baseline body mass index (BMI) among men with BMI < 23.6 kg/m2, but decreased among men with BMI > 23.6 kg/m2 (-24.7 pmol/L [-29.1, -20.3] per 1 SD increase in the 25.4-29.6 kg/m2 BMI range). Calculated free T was lower in younger men, who were married or in a de facto relationship (-18.4 pmol/L [-27.6, -9.3]) and in men who formerly smoked (-5.7 pmol/L [-8.9, -2.6]), were in poor general health (-14.0 pmol/L [-20.1, -7.8]), and had diabetes (-19.6 pmol/L [-23.0, -16.3]), cardiovascular disease (-5.8 pmol/L [-8.3, -3.2]), or cancer (-19.2 pmol/L [-24.4, -14.1]). CONCLUSIONS Calculated free T was most prominently associated with age and BMI. The linear, inverse association with age, nonlinear association with BMI, and presence of diabetes, cancer, and sociodemographic factors should be considered when interpreting cFT values.
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Affiliation(s)
- Nick Narinx
- Laboratory of Clinical and Experimental Endocrinology, KU Leuven, 3000 Leuven, Belgium
- Department of Laboratory Medicine, UZ Leuven, 3000 Leuven, Belgium
| | - Ross J Marriott
- School of Population and Global Health, University of Western Australia, Perth 6009, Australia
| | - Kevin Murray
- School of Population and Global Health, University of Western Australia, Perth 6009, Australia
| | - Robert J Adams
- Adelaide Institute for Sleep Health, Flinders University, Bedford Park, South Australia 5042, Australia
| | | | - Douglas C Bauer
- General Internal Medicine, University of California, San Francisco 94115, United States
| | - Shalender Bhasin
- Brigham and Women's Hospital, Harvard Medical School, Boston 02115, United States
| | - Mary L Biggs
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA 98115, United States
| | - Peggy M Cawthon
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA 94158, United States
| | - David J Couper
- Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Adrian S Dobs
- School of Medicine, Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University, Baltimore, MD 21287, United States
| | - Leon Flicker
- Medical School, University of Western Australia, Perth 6009, Australia
- Western Australian Centre for Health and Ageing, University of Western Australia, Perth 6000, Australia
| | - Graeme J Hankey
- Medical School, University of Western Australia, Perth 6009, Australia
- Perron Institute for Neurological and Translational Science, Perth 6009, Australia
| | - Anke Hannemann
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17489 Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, 17475 Greifswald, Germany
| | - Robin Wilkening
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
- European University of Applied Sciences, 18057 Rostock, Germany
| | - Sean A Martin
- Australian Institute of Family Studies, Southbank 3006, Australia
| | - Alvin M Matsumoto
- Department of Medicine, Division of Gerontology & Geriatric Medicine, University of Washington School of Medicine, Seattle, WA 98104, United States
- Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, United States
| | - Claes Ohlsson
- Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, 405 30 Goteborg, Sweden
| | - Terence W O'Neill
- Centre for Epidemiology Versus Arthritis, University of Manchester and NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester M13 9PT, United Kingdom
| | - Eric S Orwoll
- Oregon Health and Science University, Portland, OR 97239, United States
| | - Molly M Shores
- School of Medicine, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98102, United States
| | - Antje Steveling
- Department of Internal Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Thomas G Travison
- Brigham and Women's Hospital, Harvard Medical School, Boston 02115, United States
- Institute for Aging Research, Hebrew Senior Life, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02131, United States
| | - Gary A Wittert
- Freemasons Centre for Men's Health and Wellbeing, School of Medicine, University of Adelaide, Adelaide 5000, Australia
| | - Frederick C W Wu
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, University of Manchester, Manchester M13 9NT, United Kingdom
| | - Leen Antonio
- Laboratory of Clinical and Experimental Endocrinology, KU Leuven, 3000 Leuven, Belgium
| | - Dirk Vanderschueren
- Laboratory of Clinical and Experimental Endocrinology, KU Leuven, 3000 Leuven, Belgium
- Department of Laboratory Medicine, UZ Leuven, 3000 Leuven, Belgium
| | - Bu B Yeap
- Medical School, University of Western Australia, Perth 6009, Australia
- Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Perth 6150, Australia
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Behera S, Belyeu JR, Chen X, Paulin LF, Nguyen NQH, Newman E, Mahmoud M, Menon VK, Qi Q, Joshi P, Marcovina S, Rossi M, Roller E, Han J, Onuchic V, Avery CL, Ballantyne CM, Rodriguez CJ, Kaplan RC, Muzny DM, Metcalf GA, Gibbs RA, Yu B, Boerwinkle E, Eberle MA, Sedlazeck FJ. Identification of allele-specific KIV-2 repeats and impact on Lp(a) measurements for cardiovascular disease risk. BMC Med Genomics 2024; 17:255. [PMID: 39449055 PMCID: PMC11515395 DOI: 10.1186/s12920-024-02024-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Accepted: 10/07/2024] [Indexed: 10/26/2024] Open
Abstract
The abundance of Lp(a) protein holds significant implications for the risk of cardiovascular disease (CVD), which is directly impacted by the copy number (CN) of KIV-2, a 5.5 kbp sub-region. KIV-2 is highly polymorphic in the population and accurate analysis is challenging. In this study, we present the DRAGEN KIV-2 CN caller, which utilizes short reads. Data across 166 WGS show that the caller has high accuracy, compared to optical mapping and can further phase approximately 50% of the samples. We compared KIV-2 CN numbers to 24 previously postulated KIV-2 relevant SNVs, revealing that many are ineffective predictors of KIV-2 copy number. Population studies, including USA-based cohorts, showed distinct KIV-2 CN, distributions for European-, African-, and Hispanic-American populations and further underscored the limitations of SNV predictors. We demonstrate that the CN estimates correlate significantly with the available Lp(a) protein levels and that phasing is highly important.
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Affiliation(s)
- Sairam Behera
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jonathan R Belyeu
- Illumina Inc, San Diego, CA, USA
- Present Address: Pacific Biosciences, San Francisco, CA, USA
| | - Xiao Chen
- Illumina Inc, San Diego, CA, USA
- Present Address: Pacific Biosciences, San Francisco, CA, USA
| | - Luis F Paulin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Ngoc Quynh H Nguyen
- School of Public Health, University of Texas Health Science Center, Houston, TX, USA
| | | | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Vipin K Menon
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Genentech, San Francisco, CA, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Parag Joshi
- Medpace Reference Laboratories, Cincinnati, OH, USA
| | | | | | | | | | | | - Christy L Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Carlos J Rodriguez
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Fred Hutchinson Cancer Center, Public Health Sciences Division, Seattle, WA, USA
| | - Donna M Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Ginger A Metcalf
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Bing Yu
- School of Public Health, University of Texas Health Science Center, Houston, TX, USA
| | - Eric Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- School of Public Health, University of Texas Health Science Center, Houston, TX, USA
| | - Michael A Eberle
- Illumina Inc, San Diego, CA, USA
- Present Address: Pacific Biosciences, San Francisco, CA, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
- Department of Computer Science, Rice University, Houston, TX, USA.
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Yang J, Bernard L, Wong KE, Yu B, Steffen LM, Sullivan VK, Rebholz CM. Serum metabolite signature of the modified Mediterranean-DASH intervention for neurodegenerative delay (MIND) diet. Metabolomics 2024; 20:118. [PMID: 39432124 DOI: 10.1007/s11306-024-02184-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 10/10/2024] [Indexed: 10/22/2024]
Abstract
INTRODUCTION There is a lack of biomarkers of clinically important diets, such as the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet. OBJECTIVES Our study explored serum metabolites associated with adherence to the MIND diet. METHODS In 3,908 Atherosclerosis Risk in Communities (ARIC) study participants, we calculated a modified MIND diet score based on a 66-item self-reported food frequency questionnaire (FFQ). The modified score did not include berries and olive oil, as these items were not assessed in the FFQ. We used multivariable linear regression models in 2 subgroups of ARIC study participants and meta-analyzed results using fixed effects regression to identify significant metabolites after Bonferroni correction. We also examined associations between these metabolites and food components of the modified MIND diet. C-statistics evaluated the prediction of high modified MIND diet adherence using significant metabolites beyond participant characteristics. RESULTS Of 360 metabolites analyzed, 27 metabolites (15 positive, 12 negative) were significantly associated with the modified MIND diet score (lipids, n = 13; amino acids, n = 5; xenobiotics, n = 3; cofactors and vitamins, n = 3; carbohydrates n = 2; nucleotide n = 1). The top 4 metabolites that improved the prediction of high dietary adherence to the modified MIND diet were 7-methylxanthine, theobromine, docosahexaenoate (DHA), and 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF). CONCLUSION Twenty-seven metabolomic markers were correlated with the modified MIND diet. The biomarkers, if further validated, could be useful to objectively assess adherence to the MIND diet.
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Affiliation(s)
- Jiaqi Yang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Lauren Bernard
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- School of Medicine, University of Maryland, Baltimore, MD, USA
| | - Kari E Wong
- Metabolon, Research Triangle Park, Morrisville, NC, USA
| | - Bing Yu
- Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Valerie K Sullivan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.
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Lu Y, Pike JR, Chen J, Walker KA, Sullivan KJ, Thyagarajan B, Mielke MM, Lutsey PL, Knopman D, Gottesman RF, Sharrett AR, Coresh J, Mosley TH, Palta P. Changes in Alzheimer Disease Blood Biomarkers and Associations With Incident All-Cause Dementia. JAMA 2024; 332:1258-1269. [PMID: 39068543 PMCID: PMC11284635 DOI: 10.1001/jama.2024.6619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 03/29/2024] [Indexed: 07/30/2024]
Abstract
Importance Plasma biomarkers show promise for identifying Alzheimer disease (AD) neuropathology and neurodegeneration, but additional examination among diverse populations and throughout the life course is needed. Objective To assess temporal plasma biomarker changes and their association with all-cause dementia, overall and among subgroups of community-dwelling adults. Design, Setting, and Participants In 1525 participants from the US-based Atherosclerosis Risk in Communities (ARIC) study, plasma biomarkers were measured using stored specimens collected in midlife (1993-1995, mean age 58.3 years) and late life (2011-2013, mean age 76.0 years; followed up to 2016-2019, mean age 80.7 years). Midlife risk factors (hypertension, diabetes, lipids, coronary heart disease, cigarette use, and physical activity) were assessed for their associations with change in plasma biomarkers over time. The associations of biomarkers with incident all-cause dementia were evaluated in a subpopulation (n = 1339) who were dementia-free in 2011-2013 and had biomarker measurements in 1993-1995 and 2011-2013. Exposure Plasma biomarkers of amyloid-β 42 to amyloid-β 40 (Aβ42:Aβ40) ratio, phosphorylated tau at threonine 181 (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured using the Quanterix Simoa platform. Main Outcomes and Measures Incident all-cause dementia was ascertained from January 1, 2012, through December 31, 2019, from neuropsychological assessments, semiannual participant or informant contact, and medical record surveillance. Results Among 1525 participants (mean age, 58.3 [SD, 5.1] years), 914 participants (59.9%) were women, and 394 participants (25.8%) were Black. A total of 252 participants (16.5%) developed dementia. Decreasing Aβ42:Aβ40 ratio and increasing p-tau181, NfL, and GFAP were observed from midlife to late life, with more rapid biomarker changes among participants carrying the apolipoprotein E epsilon 4 (APOEε4) allele. Midlife hypertension was associated with a 0.15-SD faster NfL increase and a 0.08-SD faster GFAP increase per decade; estimates for midlife diabetes were a 0.11-SD faster for NfL and 0.15-SD faster for GFAP. Only AD-specific biomarkers in midlife demonstrated long-term associations with late-life dementia (hazard ratio per SD lower Aβ42:Aβ40 ratio, 1.11; 95% CI, 1.02-1.21; per SD higher p-tau181, 1.15; 95% CI, 1.06-1.25). All plasma biomarkers in late life had statistically significant associations with late-life dementia, with NfL demonstrating the largest association (1.92; 95% CI, 1.72-2.14). Conclusions and Relevance Plasma biomarkers of AD neuropathology, neuronal injury, and astrogliosis increase with age and are associated with known dementia risk factors. AD-specific biomarkers' association with dementia starts in midlife whereas late-life measures of AD, neuronal injury, and astrogliosis biomarkers are all associated with dementia.
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Affiliation(s)
- Yifei Lu
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - James Russell Pike
- Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York
- Optimal Aging Institute, New York University Grossman School of Medicine, New York
| | - Jinyu Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Keenan A. Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging Intramural Research Program, Baltimore, Maryland
| | - Kevin J. Sullivan
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Michelle M. Mielke
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis
| | - David Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, Maryland
| | - A. Richey Sharrett
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson
| | - Josef Coresh
- Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York
- Optimal Aging Institute, New York University Grossman School of Medicine, New York
| | - Thomas H. Mosley
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson
| | - Priya Palta
- Department of Neurology, University of North Carolina at Chapel Hill
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Ding Y, Ge T, Shen J, Duan M, Yuan C, Zhu Y, Zhou D. Associations of metabolic heterogeneity of obesity with the risk of dementia in middle-aged adults: three prospective studies. Alzheimers Res Ther 2024; 16:220. [PMID: 39394616 PMCID: PMC11468300 DOI: 10.1186/s13195-024-01581-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Accepted: 09/25/2024] [Indexed: 10/13/2024]
Abstract
BACKGROUND The associations of different obesity and metabolic phenotypes during midlife with the risk of incident dementia remain unclear. This study aimed to investigate the associations between metabolic heterogeneity of obesity and long-term risk of dementia. METHODS We conducted prospective analyses from three cohorts, including the UK Biobank (UKB), Atherosclerosis Risk in Communities (ARIC) study, and Framingham Offspring Study (FOS). Eligible participants were those aged 45-65 years with valid assessments of body mass index (BMI) and metabolic status at the study baseline. Obesity was defined as a BMI of ≥ 30.0 kg/m2, while metabolic abnormality was defined as meeting ≥ 2 of the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) criteria. Metabolic heterogeneity of obesity was evaluated based on obesity and metabolic phenotypes and grouped as metabolically normal non-obesity (MNNO), metabolically abnormal non-obesity (MANO), metabolically normal obesity (MNO), and metabolically abnormal obesity (MAO). RESULTS Included in this study were 295,823 participants aged 56.3 ± 5.9 years from the UKB, 12,547 participants aged 54.0 ± 5.7 years from the ARIC, and 2,004 participants aged 53.9 ± 5.9 years from the FOS. Over 4,348,208 person-years, a total of 6,190 participants (3,601 in the UKB, 2,405 in the ARIC, and 184 in the FOS) developed incident dementia. In the pooled analysis of three cohorts, metabolic abnormality was associated with a hazard ratio (HR) of 1.41 (95% confidence interval [CI]: 1.10-1.80) for dementia, while obesity was associated with an HR of 1.20 (1.03-1.41). Compared with MNNO, individuals with MANO and MAO had increased risks of dementia (pooled HR: 1.33, 95% CI: 1.04-1.71 for MANO and 1.48, 1.16-1.89 for MAO). However, there was no significant difference in the risk of dementia among MNO (pooled HR: 1.10, 95% CI: 0.98-1.24). In addition, participants who recovered from MANO to MNNO had a lower risk of dementia (pooled HR: 0.79, 95% CI: 0.64-0.97), as compared with stable MANO. CONCLUSIONS Metabolic abnormality has a stronger association with dementia than obesity. Metabolically abnormal non-obesity and obesity, but not metabolically normal obesity, are associated with higher risks of incident dementia as compared with metabolically normal non-obesity. Recovering from an abnormal metabolic status to normal reduces the risk of dementia in populations without obesity. Our findings highlight the important role of metabolic status in the development of dementia and recommend the stratified management of obesity based on metabolic status.
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Affiliation(s)
- Yihong Ding
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Tian Ge
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jie Shen
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Mingrui Duan
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Changzheng Yuan
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Yimin Zhu
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
- Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Dan Zhou
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, Zhejiang, China.
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Gomez GT, Shi L, Fohner AE, Chen J, Yang Y, Fornage M, Duggan MR, Peng Z, Daya GN, Tin A, Schlosser P, Longstreth WT, Kalani R, Sharma M, Psaty BM, Nevado-Holgado AJ, Buckley NJ, Gottesman RF, Lutsey PL, Jack CR, Sullivan KJ, Mosley T, Hughes TM, Coresh J, Walker KA. Plasma proteome-wide analysis of cerebral small vessel disease identifies novel biomarkers and disease pathways. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.10.07.24314972. [PMID: 39417098 PMCID: PMC11483013 DOI: 10.1101/2024.10.07.24314972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
Cerebral small vessel disease (SVD), as defined by neuroimaging characteristics such as white matter hyperintensities (WMHs), cerebral microhemorrhages (CMHs), and lacunar infarcts, is highly prevalent and has been associated with dementia risk and other clinical sequelae. Although conditions such as hypertension are known to contribute to SVD, little is known about the diverse set of subclinical biological processes and molecular mediators that may also influence the development and progression of SVD. To better understand the mechanisms underlying SVD and to identify novel SVD biomarkers, we used a large-scale proteomic platform to relate 4,877 plasma proteins to MRI-defined SVD characteristics within 1,508 participants of the Atherosclerosis Risk in Communities (ARIC) Study cohort. Our proteome-wide analysis of older adults (mean age: 76) identified 13 WMH-associated plasma proteins involved in synaptic function, endothelial integrity, and angiogenesis, two of which remained associated with late-life WMH volume when measured nearly 20 years earlier, during midlife. We replicated the relationship between 9 candidate proteins and WMH volume in one or more external cohorts; we found that 11 of the 13 proteins were associated with risk for future dementia; and we leveraged publicly available proteomic data from brain tissue to demonstrate that a subset of WMH-associated proteins was differentially expressed in the context of cerebral atherosclerosis, pathologically-defined Alzheimer's disease, and cognitive decline. Bidirectional two-sample Mendelian randomization analyses examined the causal relationships between candidate proteins and WMH volume, while pathway and network analyses identified discrete biological processes (lipid/cholesterol metabolism, NF-kB signaling, hemostasis) associated with distinct forms of SVD. Finally, we synthesized these findings to identify two plasma proteins, oligodendrocyte myelin glycoprotein (OMG) and neuronal pentraxin receptor (NPTXR), as top candidate biomarkers for elevated WMH volume and its clinical manifestations.
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Paskiewicz A, Wang FM, Ishigami J, Pang Y, Sang Y, Ballew SH, Grams ME, Heiss G, Coresh J, Matsushita K. Peripheral artery disease and risk of kidney outcomes: The Atherosclerosis Risk in Communities (ARIC) study. Atherosclerosis 2024; 397:118558. [PMID: 39276420 PMCID: PMC11467911 DOI: 10.1016/j.atherosclerosis.2024.118558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/24/2024] [Accepted: 08/06/2024] [Indexed: 09/17/2024]
Abstract
BACKGROUND AND AIMS The potential impact of peripheral artery disease (PAD) on kidney outcomes is not well understood. The aim of this study was to explore the association between PAD and end-stage kidney disease (ESKD) and chronic kidney disease (CKD). METHODS Among 14,051 participants (mean age 54 [SD 6 years]) from the Atherosclerosis Risk in Communities study, we categorized PAD status as symptomatic PAD (intermittent claudication or leg revascularization), asymptomatic PAD (ankle-brachial index [ABI] ≤0.90 without clinical history of symptoms), and ABI 0.91-1.00, 1.01-1.10, 1.11-1.20 (reference), 1.21-1.30, and >1.30. We evaluated their associations with two kidney outcomes: ESKD (the need of renal replacement therapy or death due to kidney disease) and CKD (ESKD cases or an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 with a ≥25 % decline from the baseline) using multivariable Cox proportional hazards models. RESULTS Over ∼30 years of follow-up, there were 598 cases of incident ESKD and 4686 cases of incident CKD. After adjusting for potential confounders, both symptomatic PAD and asymptomatic PAD conferred a significantly elevated risk of ESKD (hazard ratio 2.28 [95 % confidence interval 1.23-4.22] and 1.75 [1.19-2.57], respectively). Corresponding estimates for CKD were 1.54 (1.14-2.09) and 1.63 (1.38-1.93). Borderline low ABI 0.91-1.00 also showed elevated risk of adverse kidney outcomes after adjustment for demographic variables. Largely consistent results were observed across demographic and clinical subgroups. CONCLUSIONS Symptomatic PAD and asymptomatic PAD were independently associated with an elevated risk of ESKD and CKD. These results highlight the importance of monitoring kidney function in persons with PAD, even when symptoms are absent.
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Affiliation(s)
- Amy Paskiewicz
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Frances M Wang
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Junichi Ishigami
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Yuanjie Pang
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Yingying Sang
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Shoshana H Ballew
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Optimal Aging Institute, Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Morgan E Grams
- Division of Precision Medicine, Department of Medicine, New York University, New York, NY, USA
| | - Gerardo Heiss
- University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Josef Coresh
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Optimal Aging Institute, Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
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Djousse L, Zhou X, Lim J, Kim E, Sesso HD, Lee IM, Buring JE, McClelland RL, Gaziano JM, Steffen LM, Manson JE. Potato Consumption and Risk of Type 2 Diabetes Mellitus: A Harmonized Analysis of 7 Prospective Cohorts. J Nutr 2024; 154:3079-3087. [PMID: 39289134 DOI: 10.1016/j.tjnut.2024.07.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 06/27/2024] [Accepted: 07/12/2024] [Indexed: 09/19/2024] Open
Abstract
BACKGROUND Data on the relation of potato consumption with risk of type 2 diabetes (T2D) are limited and inconsistent. It is unclear whether the plant-based diet index (PDI), which is a novel and comprehensive tool to assess overall dietary pattern, modifies the association of potato intake with T2D. OBJECTIVES We examined the association of total, combined baked, boiled, and mashed potatoes and fried potatoes with risk of T2D and test the interaction between PDI score and potato consumption on T2D risk. METHODS We conducted a de novo, harmonized, individual-level data from 7 United States cohorts (N = 105,531). Cox regression was used to estimate hazard ratios (HRs) separately in each cohort adjusting for anthropometric, demographic, and lifestyle factors and cohort-specific results were pooled using an inverse-variance weighted method. RESULTS Mean age ranged from 25 to 72 y, 65% women, and mean consumption of total potatoes ranged from 1.9 to 4.3 times per week. In the primary analysis, total potato intake was not associated with T2D risk: multivariable adjusted HR of 1.01 (95% confidence interval [CI]: 0.95, 1.08) for consumption of 1-2 servings/wk; 1.01 (95% CI: 0.93, 1.10) for >2-3 servings/wk; 1.05 (95% CI: 0.99, 1.12) for >3 to <5 servings/wk; and 1.07 (95% CI: 0.99, 1.16) for 5+ servings/wk compared with no potato intake. In secondary analyses, consumption of combined baked, boiled, and mashed potatoes was not associated with T2D risk, whereas fried potato consumption was positively associated with T2D risk: HR were 1 (ref), 1.07 (95% CI: 1.02, 1.12), and 1.12 (95% CI: 1.03, 1.22) for intake frequency of 0/wk, >0 to 1/wk, and >1/wk, respectively (P-trend = 0.04). There was no significant interaction between PDI score and potato consumption on T2D risk. CONCLUSIONS Although consumption of total potato is not associated with T2D risk, a modest elevated risk of T2D is observed with fried potato consumption.
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Affiliation(s)
- Luc Djousse
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States.
| | - Xia Zhou
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Jaewon Lim
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Eunjung Kim
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States
| | - Howard D Sesso
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - I-Min Lee
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Julie E Buring
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Robyn L McClelland
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - John M Gaziano
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
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Flaherty CM, Surapaneni A, Seegmiller JC, Coresh J, Grams ME, Ballew SH. CKD Prevalence and Incidence in Older Adults Using Estimated GFR With Different Filtration Markers: The Atherosclerosis Risk in Communities Study. Kidney Med 2024; 6:100893. [PMID: 39319210 PMCID: PMC11420509 DOI: 10.1016/j.xkme.2024.100893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/26/2024] Open
Abstract
Rationale & Objective The prevalence of chronic kidney disease (CKD) is known to increase with age; however, creatinine may be a less reliable filtration marker in older adults. Few studies have investigated the prevalence and progression of CKD using different filtration markers for estimating glomerular filtration rate (GFR). Study Design A prospective observational cohort study. Setting & Participants 6,393 White and African American participants aged 65-100 years from the Atherosclerosis Risk in Communities Study (ARIC) at Visit 5, followed longitudinally at Visits 6 and 7. Exposure and Outcome The eGFR was estimated either by creatinine (eGFRcr), cystatin C (eGFRcys), creatinine and cystatin C (eGFRcr-cys), or using creatinine, cystatin C, and β-2-microglobulin (eGFRcr-cys-b2m). CKD progression was defined as 30% decline in eGFR at follow-up visits. Analytical Approach Logistic regression models, adjusted for sex, race and study center, diabetes, blood pressure, body mass index, prevalent cardiovascular disease, and heart failure. Results At Visit 5, the mean age in the study population was 75.8 years, and the mean eGFR ranged from 71.2 to 61.2 mL/min/1.73m2 using eGFRcr or eGFRcys, respectively. The proportion with eGFR < 60 mL/min/1.73m2 was lowest with eGFRcr and highest with eGFRcys for all age groups, and prevalence increased with age for all markers. For example, the prevalence of eGFRcr < 60 mL/min/1.73m2 in ages 70-74 years ranged from 15% to 21% and in ages 85-89 years ranged from 38% to 46% at the different visits. The proportion with a 30% eGFR decline over a mean of 8 years in people who were originally aged 65-69 years ranged from 9% (eGFRcr)-18% (eGFRcys). More people with eGFRcr ≥ 60 mL/min/1.73m2 were reclassified to < 60 mL/min/1.73m2 when using eGFRcys (33%) compared with eGFRcr-cys (12%) or eGFRcr-cys-b2m (18%). The proportion with 30% eGFR decline was lowest with eGFRcr and highest with eGFRcys, with greater incidence in older age groups for all markers. Limitations No direct measurement of GFR. Not all participants survived or attended subsequent follow-up visits. Conclusions The prevalence and progression of CKD increase with age, but estimates vary with the filtration marker used. The eGFRcr gave the lowest estimate of CKD at 15% for people aged 65-69 years at Visit 5 while eGFRcys gave the highest estimates of CKD at 26% for that same population.
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Affiliation(s)
- Carina M Flaherty
- Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY
| | - Aditya Surapaneni
- Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY
| | - Jesse C Seegmiller
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN
| | - Josef Coresh
- Optimal Aging Institute, New York University Grossman School of Medicine, New York, NY
| | - Morgan E Grams
- Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY
| | - Shoshana H Ballew
- Optimal Aging Institute, New York University Grossman School of Medicine, New York, NY
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Eswaran S, Knopman DS, Koton S, Kucharska-Newton AM, Liu AC, Liu C, Lutsey PL, Mosley TH, Palta P, Sharrett AR, Sullivan KJ, Walker KA, Gottesman RF, Groechel RC. Psychosocial Health and the Association Between Cerebral Small Vessel Disease Markers With Dementia: The ARIC Study. Stroke 2024; 55:2449-2458. [PMID: 39193713 DOI: 10.1161/strokeaha.124.047455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 06/27/2024] [Accepted: 07/10/2024] [Indexed: 08/29/2024]
Abstract
BACKGROUND Associations between magnetic resonance imaging markers of cerebral small vessel disease (CSVD) and dementia risk in older adults have been established, but it remains unclear how lifestyle factors, including psychosocial health, may modify this association. METHODS Social support and social isolation were assessed among participants of the community-based ARIC (Atherosclerosis Risk in Communities) Study, via self-reported questionnaires (1990-1992). Following categorization of both factors, participants were classified as having strong or poor mid-life social relationships. At visit 5 (2011-2013), participants underwent 3T brain magnetic resonance imaging quantifying CSVD measures: white matter hyperintensity volume, microbleeds (subcortical), infarcts (lacunar), and white matter integrity (diffusion tensor imaging). Incident dementia cases were identified from the time of imaging through December 31, 2020 with ongoing surveillance. Associations between CSVD magnetic resonance imaging markers and incident dementia were evaluated using Cox proportional-hazard regressions adjusted for demographic and additional risk factors (from visit 2). Effect modification by mid-life social relationships was evaluated. RESULTS Of the 1977 participants with magnetic resonance imaging, 1617 participants (60.7% women; 26.5% Black participants; mean age at visit 2, 55.4 years) were examined. In this sample, mid-life social relationships significantly modified the association between white matter hyperintensity volume and dementia risk (P interaction=0.001). Greater white matter hyperintensity volume was significantly associated with risk of dementia in all participants, yet, more substantially in those with poor (hazard ratio, 1.84 [95% CI, 1.49-2.27]) versus strong (hazard ratio, 1.26 [95% CI, 1.08-1.47]) mid-life social relationships. Although not statistically significant, subcortical microbleeds in participants with poor mid-life social relationships were associated with a greater risk of dementia, relative to those with strong social relationships, in whom subcortical microbleeds were no longer associated with elevated dementia risk. CONCLUSIONS The elevated risk of dementia associated with CSVD may be reduced in participants with strong mid-life social relationships. Future studies evaluating psychosocial health through the life course and the mechanisms by which they modify the relationship between CSVD and dementia are needed.
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Affiliation(s)
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN (D.S.K.)
| | - Silvia Koton
- Department of Nursing, The Stanley Steyer School of Health Professions, Tel Aviv University, Israel (S.K.)
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD (S.K., A.R.S.)
| | - Anna M Kucharska-Newton
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill (A.M.K.-N., A.C.L.)
| | - Albert C Liu
- Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill (A.M.K.-N., A.C.L.)
| | - Chelsea Liu
- Department of Epidemiology, George Washington University-Milken Institute School of Public Health, DC (C.L.)
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis (P.L.L.)
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., K.J.S.)
| | - Priya Palta
- Department of Neurology, University of North Carolina at Chapel Hill (P.P.)
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD (S.K., A.R.S.)
| | - Kevin J Sullivan
- Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., K.J.S.)
| | - Keenan A Walker
- National Institute on Aging Intramural Research Program, Baltimore, MD (K.A.W.)
| | - Rebecca F Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD (R.F.G., R.C.G.)
| | - Renee C Groechel
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD (R.F.G., R.C.G.)
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Domingo-Relloso A, Riffo-Campos AL, Zhao N, Ayala G, Haack K, Manterola C, Rhoades DA, Umans JG, Fallin MD, Herreros-Martinez M, Pollan M, Boerwinkle E, Platz EA, Jones MR, Bressler J, Joehanes R, Ryan CP, Gonzalez JR, Levy D, Belsky DW, Cole SA, Michaud DS, Navas-Acien A, Tellez-Plaza M. Multicohort Epigenome-Wide Association Study of All-Cause Cardiovascular Disease and Cancer Incidence: A Cardio-Oncology Approach. JACC CardioOncol 2024; 6:731-742. [PMID: 39479324 PMCID: PMC11520201 DOI: 10.1016/j.jaccao.2024.07.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 07/05/2024] [Accepted: 07/08/2024] [Indexed: 11/02/2024] Open
Abstract
Background Emerging evidence reveals a complex relationship between cardiovascular disease (CVD) and cancer, which share common risk factors and biological pathways. Objectives The aim of this study was to evaluate common epigenetic signatures for CVD and cancer incidence in 3 ethnically diverse cohorts: Native Americans from the SHS (Strong Heart Study), European Americans from the FHS (Framingham Heart Study), and European Americans and African Americans from the ARIC (Atherosclerosis Risk In Communities) study. Methods A 2-stage strategy was used that included first conducting untargeted epigenome-wide association studies for each cohort and then running targeted models in the union set of identified differentially methylated positions (DMPs). We also explored potential molecular pathways by conducting a bioinformatics analysis. Results Common DMPs were identified across all populations. In a subsequent meta-analysis, 3 and 1 of those DMPs were statistically significant for CVD only and both cancer and CVD, respectively. No meta-analyzed DMPs were statistically significant for cancer only. The enrichment analysis pointed to interconnected biological pathways involved in cancer and CVD. In the DrugBank database, elements related to 1-carbon metabolism and cancer and CVD medications were identified as potential drugs for target gene products. In an additional analysis restricted to the 950 SHS participants who developed incident CVD, the C index for incident cancer increased from 0.618 (95% CI: 0.570-0.672) to 0.971 (95% CI: 0.963-0.978) when adjusting the models for the combined cancer and CVD DMPs identified in the other cohorts. Conclusions These results point to molecular pathways and potential treatments for precision prevention of CVD and cancer. Screening based on common epigenetic signatures of incident CVD and cancer may help identify patients with newly diagnosed CVD at increased cancer risk.
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Affiliation(s)
- Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
- Integrative Epidemiology Group, National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain
- Department of Chronic Disease Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain
| | - Angela L. Riffo-Campos
- Universidad de La Frontera, Ph.D. Program in Medical Sciences; and Millennium Nucleus on Sociomedicine (SocioMed), Temuco, Chile
- Department of Computer Science, Universidad de Valencia, Valencia, Spain
- Center for Cancer Prevention and Control, Santiago, Chile
| | - Naisi Zhao
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, USA
| | - Guillermo Ayala
- Department of Computer Science, Universidad de Valencia, Valencia, Spain
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Carlos Manterola
- Universidad de La Frontera, Ph.D. Program in Medical Sciences; and Millennium Nucleus on Sociomedicine (SocioMed), Temuco, Chile
| | - Dorothy A. Rhoades
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | | | - M Daniele Fallin
- Emory University Rollins School of Public Health, Atlanta, Georgia, USA
| | | | - Marina Pollan
- Department of Chronic Disease Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain
| | - Eric Boerwinkle
- The University of Texas Health Science Center at Houston, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA
| | - Miranda R. Jones
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jan Bressler
- The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
- Framingham Heart Study, Framingham, Massachusetts, USA
| | - Calen P. Ryan
- Columbia Aging Center, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Juan R. Gonzalez
- Bioinformatics and Genetic Epidemiology Unit, Instituto de Salud Global, Barcelona, Spain
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
- Framingham Heart Study, Framingham, Massachusetts, USA
| | - Daniel W. Belsky
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Shelley A. Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Dominique S. Michaud
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain
- Department of Chronic Disease Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain
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Duong T, Austin TR, Brody JA, Shojaie A, Battle A, Bader JS, Hong YS, Ballantyne CM, Coresh J, Gerszten RE, Tracy RP, Psaty BM, Sotoodehnia N, Arking DE. Circulating Blood Plasma Profiling Reveals Proteomic Signature and a Causal Role for SVEP1 in Sudden Cardiac Death. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004494. [PMID: 39234668 PMCID: PMC11479847 DOI: 10.1161/circgen.123.004494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/06/2024]
Affiliation(s)
- ThuyVy Duong
- McKusick-Nathans Inst, Dept of Genetic Medicine, Johns Hopkins Univ School of Medicine, Baltimore, MD
| | - Thomas R. Austin
- Cardiovascular Health Rsrch Unit, Dept of Medicine, Univ of Washington, Seattle, WA
- Dept of Epidemiology, Univ of Washington, Seattle, WA
| | - Jennifer A. Brody
- Cardiovascular Health Rsrch Unit, Dept of Medicine, Univ of Washington, Seattle, WA
| | - Ali Shojaie
- Dept of Biostatistics, Univ of Washington, Seattle, WA
| | - Alexis Battle
- Dept of Biomedical Engineering, Johns Hopkins Univ, Baltimore, MD
- Dept of Computer Science, Johns Hopkins Univ, Baltimore, MD
| | - Joel S. Bader
- Dept of Biomedical Engineering, Johns Hopkins Univ, Baltimore, MD
| | - Yun Soo Hong
- McKusick-Nathans Inst, Dept of Genetic Medicine, Johns Hopkins Univ School of Medicine, Baltimore, MD
| | | | - Josef Coresh
- Dept of Epidemiology, Johns Hopkins Univ Bloomberg School of Public Health, Baltimore, MD
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Ctr, Boston, MA
| | - Russell P. Tracy
- Dept of Pathology & Laboratory Medicine & Biochemistry, Larner College of Medicine, Univ of Vermont, Burlington, VT
| | - Bruce M. Psaty
- Cardiovascular Health Rsrch Unit, Dept of Medicine, Univ of Washington, Seattle, WA
- Dept of Epidemiology, Univ of Washington, Seattle, WA
- Dept of Health Systems & Population Health, Univ of Washington, Seattle, WA
| | - Nona Sotoodehnia
- Cardiovascular Health Rsrch Unit, Dept of Medicine, Univ of Washington, Seattle, WA
| | - Dan E Arking
- McKusick-Nathans Inst, Dept of Genetic Medicine, Johns Hopkins Univ School of Medicine, Baltimore, MD
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McDermott KM, Wang D, Windham BG, Schrack JA, Selvin E, Hicks CW. Peripheral neuropathy, gait speed, and lower extremity function in community-dwelling older adults with and without diabetes. J Am Geriatr Soc 2024; 72:3242-3245. [PMID: 38994636 PMCID: PMC11461110 DOI: 10.1111/jgs.19072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 06/12/2024] [Accepted: 06/19/2024] [Indexed: 07/13/2024]
Affiliation(s)
| | - Dan Wang
- Johns Hopkins Department of Surgery
| | | | | | | | - Caitlin W. Hicks
- Johns Hopkins Bloomberg School of Public Health
- Johns Hopkins Department of Surgery
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Song Z, Lynch K, Parker-Allotey NA, Bennett EE, Xu X, Whitsel EA, Smith R, Stewart JD, Park ES, Ying Q, Power MC. Association of midlife air pollution exposures and residential road proximity with incident dementia: The Atherosclerosis Risk in Communities (ARIC) study. ENVIRONMENTAL RESEARCH 2024; 258:119425. [PMID: 38879108 PMCID: PMC11323165 DOI: 10.1016/j.envres.2024.119425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Increasing evidence links higher air pollution exposures to increased risk of cognitive impairment. While midlife risk factors are often most strongly linked to dementia risk, few studies have considered associations between midlife roadway proximity or ambient air pollution exposure and incident dementia decades later, in late life. OBJECTIVES Our objective was to determine if midlife exposures to ambient air pollution or roadway proximity are associated with increased risk of dementia in the Atherosclerosis Risk in Communities (ARIC) study over up to 29 years of follow-up. METHODS Our eligible sample included Black and White ARIC participants without dementia at Visit 2 (1990-1992). Participants were followed through Visit 7 (2018-2019), with dementia status and onset date defined based on formal dementia ascertainment at study visits, informant interviews, and surveillance efforts. We used adjusted Weibull survival models to assess the associations of midlife ambient air pollution and road proximity with incident dementia. RESULTS The median age at baseline (1990-1992, Visit 2) of the 12,700 eligible ARIC participants was 57.0 years; 56.0% were female, 24.2% were Black, and 78.9% had at least a high school education. Over up to 29 years of follow-up, 2511 (19.8%) persons developed dementia. No associations were found between ambient air pollutants and proximity to major roadways with risk of incident dementia. In exploratory analyses, living closer to roadways in midlife increased dementia risk in individuals younger at baseline and those without midlife hypertension, and there was evidence of increased risk of dementia with increased midlife exposure to NOx, several PM2.5 components, and trace metals among those with diabetes in midlife. CONCLUSIONS Midlife exposure to ambient air pollution and midlife roadway proximity was not associated with dementia risk over decades of follow-up. Further investigation to explore potential for greater susceptibility among specific subgroups identified here is needed.
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Affiliation(s)
- Ziwei Song
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States
| | - Katie Lynch
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States
| | - Naa Adoley Parker-Allotey
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States
| | - Erin E Bennett
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States
| | - Xiaohui Xu
- School of Public Health, Texas A&M Health Science Center, College Station, TX, United States
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States; Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, United States
| | - Richard Smith
- Department of Statistics and Operations Research, College of Arts and Sciences, University of North Carolina, Chapel Hill, NC, United States; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States
| | - Eun Sug Park
- Texas A&M Transportation Institute, Texas A&M University System, College Station, TX, United States
| | - Qi Ying
- Zachry Department of Civil Engineering, Texas A&M University, College Station, TX, 77843, United States
| | - Melinda C Power
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States.
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Semancik CS, Zhao N, Koestler DC, Boerwinkle E, Bressler J, Buchsbaum RJ, Kelsey KT, Platz EA, Michaud DS. DNA Methylation-Derived Immune Cell Proportions and Cancer Risk in Black Participants. CANCER RESEARCH COMMUNICATIONS 2024; 4:2714-2723. [PMID: 39324671 PMCID: PMC11484294 DOI: 10.1158/2767-9764.crc-24-0257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 07/31/2024] [Accepted: 09/24/2024] [Indexed: 09/27/2024]
Abstract
SIGNIFICANCE This study describes associations between immune cell types and cancer risk in a Black population; elevated regulatory T-cell proportions that were associated with increased overall cancer and lung cancer risk, and elevated memory B-cell proportions that were associated with increased prostate and all cancer risk.
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Affiliation(s)
- Christopher S. Semancik
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Tufts University, Boston, Massachusetts.
| | - Naisi Zhao
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Tufts University, Boston, Massachusetts.
| | - Devin C. Koestler
- The University of Kansas Cancer Center, Kansas City, Kansas.
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, Kansas.
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas.
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas.
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas.
| | - Rachel J. Buchsbaum
- Division of Hematology and Oncology, Tufts Medical Center, Boston, Massachusetts.
| | - Karl T. Kelsey
- Department of Epidemiology, Brown University, Providence, Rhode Island.
- Department of Pathology and Laboratory Medicine, Brown University, Providence, Rhode Island.
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland.
| | - Dominique S. Michaud
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Tufts University, Boston, Massachusetts.
- Department of Epidemiology, Brown University, Providence, Rhode Island.
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Liu F, Schrack JA, Walston J, Mathias RA, Windham BG, Grams ME, Coresh J, Walker KA. Mid-life plasma proteins associated with late-life prefrailty and frailty: a proteomic analysis. GeroScience 2024; 46:5247-5265. [PMID: 38856871 PMCID: PMC11336072 DOI: 10.1007/s11357-024-01219-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 05/21/2024] [Indexed: 06/11/2024] Open
Abstract
Physical frailty is a syndrome that typically manifests in later life, although the pathogenic process causing physical frailty likely begins decades earlier. To date, few studies have examined the biological signatures in mid-life associated with physical frailty later in life. Among 4,189 middle-aged participants (57.8 ± 5.0 years, 55.8% women) from the Atherosclerosis Risk in Community (ARIC) study, we evaluated the associations of 4,955 plasma proteins (log 2-transformed and standardized) measured using the SomaScan platform with their frailty status approximately 20 years later. Using multinomial logistic regression models adjusting for demographics, health behaviors, kidney function, total cholesterol, and comorbidities, 12 and 221 proteins were associated with prefrailty and frailty in later life, respectively (FDR p < 0.05). Top frailty-associated proteins included neurocan core protein (NCAN, OR = 0.66), fatty acid-binding protein heart (FABP3, OR = 1.62) and adipocyte (FABP4, OR = 1.65), as well proteins involved in the contactin-1 (CNTN1), toll-like receptor 5 (TLR5), and neurogenic locus notch homolog protein 1 (NOTCH1) signaling pathway relevant to skeletal muscle regeneration, myelination, and inflammation. Pathway analyses suggest midlife dysregulation of inflammation, metabolism, extracellular matrix, angiogenesis, and lysosomal autophagy among those at risk for late-life frailty. After further adjusting for midlife body mass index (BMI) - an established frailty risk factor - only CNTN1 (OR = 0.75) remained significantly associated with frailty. Post-hoc analyses demonstrated that the top 41 midlife frailty-associated proteins mediate 32% of the association between mid-life BMI and late-life frailty. Our findings provide new insights into frailty etiology earlier in the life course, enhancing the potential for prevention.
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Affiliation(s)
- Fangyu Liu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Jennifer A Schrack
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Center On Aging and Health, Johns Hopkins University, Baltimore, MD, USA
| | - Jeremy Walston
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Rasika A Mathias
- Genomics and Precision Health Section, Laboratory of Allergic Diseases, National Institute of Allergy and Infection Disease, Bethesda, MD, USA
| | - B Gwen Windham
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Morgan E Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Precision Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Population Health and Medicine, Optimal Aging Institute, New York University Grossman School of Medicine, New York, NY, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute On Aging, Baltimore, MD, USA
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Marrero N, Jha K, Hughes TM, Razavi AC, Grant JK, Boakye E, Anchouche K, Dzaye O, Budoff MJ, Rotter JI, Guo X, Yao J, Wood AC, Blumenthal RS, Michos ED, Thanassoulis G, Post WS, Blaha MJ, Ibeh C, Whelton SP. Association of aortic valve calcium with dementia and stroke: The Multi-Ethnic Study of Atherosclerosis. Atherosclerosis 2024; 397:117596. [PMID: 38890039 DOI: 10.1016/j.atherosclerosis.2024.117596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 05/01/2024] [Accepted: 05/22/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND AND AIMS Calcific aortic valve disease is associated with increased thrombin formation, platelet activation, decreased fibrinolysis, and subclinical brain infarcts. We examined the long-term association of aortic valve calcification (AVC) with newly diagnosed dementia and incident stroke in the Multi-Ethnic Study of Atherosclerosis (MESA). METHODS AVC was measured using non-contrast cardiac CT at Visit 1. We examined AVC as a continuous (log-transformed) and categorical variable (0, 1-99, 100-299, ≥300). Newly diagnosed dementia was adjudicated using International Classification of Disease codes. Stroke was adjudicated from medical records. We calculated absolute event rates (per 1000 person-years) and multivariable adjusted Cox proportional hazards ratios (HR). RESULTS Overall, 6812 participants had AVC quantified with a mean age of 62.1 years old, 52.9 % were women, and the median 10-year estimated atherosclerotic cardiovascular disease (ASCVD) risk was 13.5 %. Participants with AVC >0 were older and less likely to be women compared to those with AVC=0. Over a median 16-year follow-up, there were 535 cases of dementia and 376 cases of stroke. The absolute risk of newly diagnosed dementia increased in a stepwise pattern with higher AVC scores, and stroke increased in a logarithmic pattern. In multivariable analyses, AVC was significantly associated with newly diagnosed dementia as a log-transformed continuous variable (HR 1.09; 95 % CI 1.04-1.14) and persons with AVC ≥300 had nearly a two-fold higher risk (HR 1.77; 95 % CI 1.14-2.76) compared to those with AVC=0. AVC was associated with an increased risk of stroke after adjustment for age, sex, and race/ethnicity, but not after adjustment for ASCVD risk factors. CONCLUSIONS After multivariable adjustment, AVC >0 was significantly associated with an increased risk of newly diagnosed dementia, but not incident stroke. This suggests that AVC may be an important risk factor for the long-term risk of dementia beyond traditional ASCVD risk factors.
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Affiliation(s)
- Natalie Marrero
- University of Miami/Jackson Memorial Hospital, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kunal Jha
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA; University of Louisville, Division of Cardiology, Louisville, KY, USA
| | - Timothy M Hughes
- Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Alexander C Razavi
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA; Center for Heart Disease Prevention, Emory School of Medicine, Atlanta, GA, USA
| | - Jelani K Grant
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Ellen Boakye
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Khalil Anchouche
- Preventive and Genomic Cardiology, Department of Medicine, McGill University, and the McGill University Health Center Research Institute, Montréal, Québec, Canada
| | - Omar Dzaye
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Matthew J Budoff
- Department of Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 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
| | - 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
| | - Jie Yao
- 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
| | | | - Roger S Blumenthal
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Erin D Michos
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - George Thanassoulis
- Preventive and Genomic Cardiology, Department of Medicine, McGill University, and the McGill University Health Center Research Institute, Montréal, Québec, Canada
| | - Wendy S Post
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Michael J Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Chinwe Ibeh
- Columbia University, Department of Neurology, New York, NY, USA
| | - Seamus P Whelton
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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White A, Dixon DD, Agrawal V, Brittain E, Lindman B, Mallugari R, Mosley JD, Perry AS, Shah RV, Wells QS, Kuipers AL, Gupta DK. Left Ventricular Wall Stress and Incident Heart Failure in Elderly Community-Dwelling Individuals. JACC. ADVANCES 2024; 3:101262. [PMID: 39309659 PMCID: PMC11416663 DOI: 10.1016/j.jacadv.2024.101262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 07/28/2024] [Accepted: 08/02/2024] [Indexed: 09/25/2024]
Abstract
Background Greater left ventricular (LV) wall stress is associated with adverse outcomes among patients with prevalent heart failure (HF). Less is known about the association between LV wall stress and incident HF. Objectives The purpose of the study was to identify clinical factors associated with wall stress and test the association between wall stress and incident HF. Methods We studied 4,601 ARIC (Atherosclerosis Risk In Communities) study participants without prevalent HF who underwent echocardiography between 2011 and 2013. LV end systolic and diastolic wall stress (LVESWS, LVEDWS) were calculated from chamber and wall thickness, systemic blood pressure, and transmitral Doppler E/e' as a surrogate for LV end diastolic pressure. Incident HF was ascertained by International Classification of Diseases (ICD)-9/10 claims for hospitalized HF through December 31, 2016. We used Cox regression to test the association between wall stress and incident HF, adjusted for demographics, traditional cardiovascular risk factors, prevalent coronary artery disease and atrial fibrillation, creatinine, N-terminal pro-B-type natriuretic peptide, troponin, triglycerides, C-reactive protein, LV ejection fraction, and LV mass. Results The cohort had a median age of 75 years and 58% women, with 18% identifying as Black. Median LVESWS and LVEDWS were 48.8 (25th-75th percentile: 39.3-60.1) and 18.9 (25th-75th percentile: 15.8-22.5) kdynes/cm2, respectively. LVESWS and LVEDWS were modestly related (rho = 0.30, P < 0.001). Over 4.6 years of median follow-up (156 HF events), each 1 kdyne/cm2 greater LVEDWS was significantly associated with higher risk of incident HF (HR: 1.03; 95% CI: 1.01-1.06), while LVESWS was not (HR: 1.00; 95% CI: 0.99-1.01). Conclusions Among community-dwelling elderly individuals, greater LVEDWS is associated with a higher risk for incident HF.
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Affiliation(s)
- Audrey White
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Debra D. Dixon
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Vineet Agrawal
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Veterans Affairs, Nashville, Tennessee, USA
| | - Evan Brittain
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Brian Lindman
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ravinder Mallugari
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jonathan D. Mosley
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Division of Clinical Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Andrew S. Perry
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ravi V. Shah
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Quinn S. Wells
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Allison L. Kuipers
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Deepak K. Gupta
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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Charry D, Xu J, Meyer ML, Kucharska-Newton A, Matsushita K, Tanaka H. Contralateral differences in ankle SBP and pulse wave velocity: associations with incident heart failure and mortality. J Hypertens 2024; 42:1728-1735. [PMID: 38973478 PMCID: PMC11361835 DOI: 10.1097/hjh.0000000000003790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/09/2024]
Abstract
BACKGROUND Contralateral differences in brachial SBP are indicative of underlaying cardiovascular issues. OBJECTIVES To examine the association of contralateral differences in ankle SBP, brachial-ankle pulse wave velocity (baPWV), and heart-ankle pulse wave velocity (haPWV) with incident heart failure and all-cause and cardiovascular mortality. METHODS Cox proportional-hazards models were used to calculate hazard ratios and 95% confidence intervals (95% CIs) in 5077 participants (75 ± 5 years) of the Atherosclerosis Risk in Communities study. RESULTS Over a mean follow-up of 7.5 ± 2.2 years, there were 457 heart failure events, 1275 all-cause and 363 cardiovascular deaths. Interankle SBP difference of at least 10 mmHg [hazard ratio = 1.12; confidence interval (CI) 1.00-1.28], at least 15 mmHg (hazard ratio = 1.21; CI 1.03-1.43), contralateral difference in baPWV more than 240 cm/s (hazard ratio = 1.22; CI 1.02-1.46), and haPWV more than 80 cm/s (hazard ratio = 1.24; CI 1.04-1.48) were each independently associated with all-cause mortality after adjustment for confounders. Contralateral differences in ankle SBP of at least 15 mmHg (hazard ratio = 1.56; CI 1.17-2.09), and haPWV more than 80 cm/s (hazard ratio = 1.42; CI 1.03-1.96) were both independently associated with cardiovascular mortality. Unadjusted analysis revealed that those with contralateral differences in ankle SBP of at least 10 and at least 15 mmHg, baPWV more than 240, and haPWV more than 80 cm/s had higher risks of heart failure (all P < 0.05). CONCLUSION These results underscore the significance of evaluating contralateral differences in ankle SBP and PWV as potential markers of increased mortality risk among older adults.
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Affiliation(s)
- Daniela Charry
- Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, Texas
| | - Jing Xu
- Department of Health Administration, Brooks College of Health, University of North Florida, Jacksonville, Florida
| | | | - Anna Kucharska-Newton
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| | - Kunihiro Matsushita
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Division of Cardiology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Hirofumi Tanaka
- Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, Texas
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Du S, Sullivan VK, Fang M, Appel LJ, Selvin E, Rebholz CM. Ultra-processed food consumption and risk of diabetes: results from a population-based prospective cohort. Diabetologia 2024; 67:2225-2235. [PMID: 39001935 PMCID: PMC11559431 DOI: 10.1007/s00125-024-06221-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/22/2024] [Indexed: 07/15/2024]
Abstract
AIMS/HYPOTHESIS Understanding the impact of the overall construct of ultra-processed foods on diabetes risk can inform dietary approaches to diabetes prevention. In this study, we aimed to evaluate the association between ultra-processed food consumption and risk of diabetes in a community-based cohort of middle-aged adults in the USA. We hypothesised that a higher intake of ultra-processed foods is associated with a higher risk of incident diabetes. METHODS The study included 13,172 participants without diabetes at baseline (1987-1989) in the Atherosclerosis Risk in Communities (ARIC) study. Dietary intake was assessed with a 66-item semiquantitative food frequency questionnaire, and foods were categorised by processing level using the Nova classification system. Ultra-processed food was analysed categorically (quartiles of energy-adjusted intake) and continuously (per one additional serving/day). We used Cox regression to evaluate the association of ultra-processed food intake with risk of diabetes with adjustment for sociodemographic characteristics, total energy intake, health behaviours and clinical factors. RESULTS Over a median follow-up of 21 years, there were 4539 cases of incident diabetes. Participants in the highest quartile of ultra-processed food intake (8.4 servings/day on average) had a significantly higher risk of diabetes (HR 1.13; 95% CI 1.03, 1.23) compared with participants in the lowest quartile of intake after adjustment for sociodemographic, lifestyle and clinical factors. Each additional serving of ultra-processed food consumed daily was associated with a 2% higher risk of diabetes (HR 1.02; 95% CI 1.00, 1.04). Highest quartile consumption of certain ultra-processed food groups, including sugar- and artificially sweetened beverages, ultra-processed meats and sugary snacks, was associated with a 29%, 21% and 16% higher risk of diabetes, respectively, compared with the lowest quartile. CONCLUSIONS/INTERPRETATION We found that a higher intake of ultra-processed food was associated with higher risk of incident diabetes, particularly sugar- and artificially sweetened beverages, ultra-processed meats and sugary snacks. Our findings suggest interventions reducing ultra-processed food consumption and specific food groups may be an effective strategy for diabetes prevention.
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Affiliation(s)
- Shutong Du
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Valerie K Sullivan
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Fang
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Lawrence J Appel
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Elizabeth Selvin
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Casey M Rebholz
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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Sarnowski C, Ma J, Nguyen NQH, Hoogeveen RC, Ballantyne CM, Coresh J, Morrison AC, Chatterjee N, Boerwinkle E, Yu B. Ancestrally diverse genome-wide association analysis highlights ancestry-specific differences in genetic regulation of plasma protein levels. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.27.24314500. [PMID: 39399032 PMCID: PMC11469718 DOI: 10.1101/2024.09.27.24314500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
Fully characterizing the genetic architecture of circulating proteins in multi-ancestry populations provides an unprecedented opportunity to gain insights into the etiology of complex diseases. We characterized and contrasted the genetic associations of plasma proteomes in 9,455 participants of European and African (19.8%) ancestry from the Atherosclerosis Risk in Communities Study. Of 4,651 proteins, 1,408 and 2,565 proteins had protein-quantitative trait loci (pQTLs) identified in African and European ancestry respectively, and twelve unreported potentially causal protein-disease relationships were identified. Shared pQTLs across the two ancestries were detected in 1,113 aptamer-region pairs pQTLs, where 53 of them were not previously reported (all trans pQTLs). Sixteen unique protein-cardiovascular trait pairs were colocalized in both European and African ancestry with the same candidate causal variants. Our systematic cross-ancestry comparison provided a reliable set of pQTLs, highlighted the shared and distinct genetic architecture of proteome in two ancestries, and demonstrated possible biological mechanisms underlying complex diseases.
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Affiliation(s)
- Chloé Sarnowski
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
| | - Jianzhong Ma
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
| | - Ngoc Quynh H. Nguyen
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
| | - Ron C Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, TX
| | | | - Josef Coresh
- Optimal Aging Institute, New York University Grossman School of Medicine, New York, NY
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Alanna C Morrison
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Eric Boerwinkle
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Bing Yu
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
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