1
|
Cannon EJ, Windham BG, Griswold M, Palta P, Knopman DS, Sedaghat S, Lutsey PL. Association of Body Mass Index in Late Life, and Change from Midlife to Late Life, With Incident Dementia in the ARIC Study Participants. Neurology 2025; 104:e213534. [PMID: 40215425 PMCID: PMC11998017 DOI: 10.1212/wnl.0000000000213534] [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: 11/14/2024] [Accepted: 02/12/2025] [Indexed: 04/17/2025] Open
Abstract
BACKGROUND AND OBJECTIVES Midlife obesity is a risk factor of dementia, but late-life obesity has been associated with lower dementia risk. We investigated this paradox by exploring the relationship between late-life body mass index (BMI) category and dementia, with and without considering midlife to late-life BMI change. METHODS This observational cohort study included participants of the community-based Atherosclerosis Risk in Communities (ARIC) study who were dementia-free at visit 5 (2011-2013). Dementia was ascertained by expert-adjudicated, algorithmic classification from an in-person neuropsychological battery, as well as telephone interviews and International Classification of Diseases codes from medical records. We first assessed the association of incident dementia with visit 5 BMI categories (normal weight, overweight, obese). Next, we used a cross-classification of visit 5 BMI categories with visit 4-visit 5 BMI change (decrease [loss of ≥2 kg/m2], increase [gain of ≥2 kg/m2], or stable [loss or gain of <2 kg/m2]) occurring during the 15 years before baseline. Cox regression was used. RESULTS A total of 5,129 participants were included in the study (59% female; 22% identified as Black; mean (standard deviation) age at visit 5 of 75 (5) years). Over 8 years of follow-up, 20% of the sample developed dementia (n = 1,026). After covariate adjustment, participants with high late-life BMI had a lower risk of dementia; the hazard ratio (95% CI) was 0.86 (0.73-1.00) for overweight and 0.81 (0.68-0.96) for obesity. In stratified models, elevated dementia risk was observed only for participants of each late-life BMI category whose BMI had decreased from midlife to late life. Compared with normal-weight individuals who had maintained BMI from midlife to late life, the hazard ratio (95% CI) for those with BMI loss was 2.08 (1.62-2.67) for normal-weight individuals, 1.62 (1.25-2.10) for those with overweight, and 1.36 (1.00-1.85) for those with obesity. DISCUSSION Our results provide insight into the dementia obesity paradox at older ages, tempering a causal interpretation of high late-life BMI as protective against dementia. Instead, they highlight the importance of considering weight loss from midlife to late life in conjunction with late-life BMI in dementia risk stratification.
Collapse
Affiliation(s)
- Ethan J Cannon
- Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis
| | - B Gwen Windham
- Division of Geriatrics, Department of Medicine, University of Mississippi Medical Center, Jackson
| | - Michael Griswold
- Division of Geriatrics, Department of Medicine, University of Mississippi Medical Center, Jackson
| | - Priya Palta
- Department of Neurology, University of North Carolina, Chapel Hill; and
| | | | - Sanaz Sedaghat
- Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis
| | - Pamela L Lutsey
- Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis
| |
Collapse
|
2
|
Walter AE, Gugger JJ, Law CA, Brennan DJ, Mosley TH, Reid RI, Jack CR, Gottesman RF, Diaz-Arrastia R, Schneider ALC. Neuroimaging Correlates of Traumatic Brain Injury in an Older Community-Dwelling Population: The Atherosclerosis Risk in Communities Study. Neurology 2025; 104:e213506. [PMID: 40184574 PMCID: PMC11974259 DOI: 10.1212/wnl.0000000000213506] [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: 09/26/2024] [Accepted: 02/07/2025] [Indexed: 04/06/2025] Open
Abstract
BACKGROUND AND OBJECTIVES Neuroimaging correlates of remote traumatic brain injury (TBI) are not well understood. Our objective was to examine associations of TBI with brain MRI markers of degeneration and vascular disease. METHODS We performed a cross-sectional analysis using data from a subset of participants who underwent a 3T brain MRI during the fifth Atherosclerosis Risk in Communities Study visit in 2011-2013. Prior TBI and age at first TBI (<18 years, 18-65 years, >65 years) was defined using self-report and International Classification of Diseases, Ninth Edition code data. We examined the following brain MRI metrics: presence of infarcts and microhemorrhages, white matter hyperintensity (WMH) volume, and the distribution of the number of regions of interest (ROIs) below a z-score cut-point of -1.5 for volumetrics, cortical thickness, and fractional anisotropy (FA) and above +1.5 for mean diffusivity (MD). RESULTS A total of 1,642 participants were included (mean age 76.8 ± 5.32 years, 61.0% female, 28.3% self-reported Black race, and 25.5% with a history of TBI [median time between first TBI and MRI: 38.2 years]). There was no evidence of differences in vascular imaging findings by overall TBI status, but individuals who sustained their first TBI at age <18 years had higher WMH volume (adjusted β = 0.22 mm3, 95% CI 0.00-0.43) and individuals who sustained their first TBI at age >65 years were more likely to have subcortical microhemorrhages (adjusted OR 1.69, 95% CI 1.03-2.75) compared with individuals without TBI. Compared with individuals without TBI, individuals with a history of TBI had a greater number of ROIs beyond the z-score cut-point for all metrics (smaller volumes, lower cortical thickness, lower FA, and higher MD). These findings were consistent among participants with first TBI sustained at age >65 years old, whereas participants with first TBI sustained at age <18 years old had a greater number of regions beyond the z-score cut-point only for FA and MD. DISCUSSION In this community-dwelling cohort of older adults, TBI was associated with smaller brain volumes, lower cortical thickness, lower FA, and higher MD. Further work is needed in the chronic postinjury period to elucidate the mechanisms underlying the observed structural changes after TBI.
Collapse
Affiliation(s)
- Alexa E Walter
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - James J Gugger
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Connor A Law
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Daniel James Brennan
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Thomas H Mosley
- The MIND Center, University of Mississippi Medical Center, Jackson
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | | | | | - Ramon Diaz-Arrastia
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | | |
Collapse
|
3
|
Ishak E, Burg EA, Pike JR, Amezcua PM, Jiang K, Powell DS, Huang AR, Suen JJ, Lutsey PL, Sharrett AR, Coresh J, Reed NS, Deal JA, Smith JR. Population Attributable Fraction of Incident Dementia Associated With Hearing Loss. JAMA Otolaryngol Head Neck Surg 2025:2832869. [PMID: 40244612 DOI: 10.1001/jamaoto.2025.0192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/18/2025]
Abstract
Importance Hearing loss treatment delays cognitive decline in high-risk older adults. The preventive potential of addressing hearing loss on incident dementia in a community-based population of older adults, and whether it varies by method of hearing loss measurement, is unknown. Objective To calculate the population attributable fraction of incident dementia associated with hearing loss in older adults and to investigate differences by age, sex, self-reported race, and method of hearing loss measurement. Design, Setting, and Participants This prospective cohort study was part of the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) and had up to 8 years of follow-up (2011-2019). The 4 ARIC field centers in the study included Jackson, Mississippi; Forsyth County, North Carolina; the Minneapolis suburbs, Minnesota; and Washington County, Maryland. Community-dwelling older adults aged 66 to 90 years without dementia at baseline who underwent a hearing assessment at ARIC-NCS visit 6 (2016-2017) were included in the analysis. Data analysis took place between June 2022 and July 2024. Exposures Hearing loss measured objectively (audiometric) and subjectively (self-reported). Main Outcomes and Measures The main outcome was incident dementia (standardized algorithmic diagnosis with expert panel review). The population attributable fractions of dementia from both audiometric and self-reported hearing loss were calculated in the same participants, which quantified the maximum proportion of dementia risk in the population that can be attributed to hearing loss. Results Among 2946 participants (mean [SD] age, 74.9 [4.6] years; 1751 [59.4] female; 637 Black [21.6%] and 2309 White [78.4%] individuals), 1947 participants (66.1%) had audiometric hearing loss, and 1097 (37.2%) had self-reported hearing loss. The population attributable fraction of dementia from any audiometric hearing loss was 32.0% (95% CI, 11.0%-46.5%). Population attributable fractions were similar by hearing loss severity (mild HL: 16.2% [95% CI, 4.2%-24.2%]; moderate or greater HL: 16.6% [95% CI, 3.9%-24.3%]). Self-reported hearing loss was not associated with an increased risk for dementia, so the population attributable fraction was not quantifiable. Population attributable fractions from audiometric hearing loss were larger among those who were 75 years and older (30.5% [95% CI, -5.8% to 53.1%]), female (30.8% [95% CI, 5.9%-47.1%]), and White (27.8% [95% CI, -6.0% to 49.8%]), relative to those who were younger than 75 years, male, and Black. Conclusions and Relevance This cohort study suggests that treating hearing loss might delay dementia for a large number of older adults. Public health interventions targeting clinically significant audiometric hearing loss might have broad benefits for dementia prevention. Future research quantifying population attributable fractions should carefully consider which measures are used to define hearing loss, as self-reporting may underestimate hearing-associated dementia risk.
Collapse
Affiliation(s)
- Emily Ishak
- Columbia University Irving Medical Center, New York, New York
| | - Emily A Burg
- Vanderbilt Bill Wilkerson Center for Otolaryngology and Communication Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - James Russell Pike
- Department of Population Health, New York University Grossman School of Medicine, New York
| | - Pablo Martinez Amezcua
- 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
| | - Kening Jiang
- 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
| | - Danielle S Powell
- Department of Hearing and Speech Sciences, University of Maryland-College Park
| | - 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
| | - Jonathan J Suen
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Johns Hopkins School of Nursing, Baltimore, Maryland
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Josef Coresh
- Department of Population Health, New York University Grossman School of Medicine, New York
- Department of Medicine, New York University Grossman School of Medicine, 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
- The Johns Hopkins Disability Health Research Center, Johns Hopkins University, Baltimore, Maryland
| | - 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
- The Johns Hopkins Disability Health Research Center, Johns Hopkins University, Baltimore, Maryland
| | - Jason R Smith
- 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
| |
Collapse
|
4
|
Kim H, Chen J, Prescott B, Walker ME, Grams ME, Yu B, Vasan RS, Floyd J, Sotoodehnia N, Smith NL, Arking DE, Coresh J, Rebholz CM. Plant-based diets and cardiovascular events: a proteomics approach to examine the underlying pathways. J Nutr 2025:S0022-3166(25)00195-6. [PMID: 40228715 DOI: 10.1016/j.tjnut.2025.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2024] [Revised: 03/19/2025] [Accepted: 04/08/2025] [Indexed: 04/16/2025] Open
Abstract
BACKGROUND Plant-based diets are associated with a lower risk of cardiovascular disease (CVD). Proteomics may improve our understanding of the biological pathways underlying these associations. OBJECTIVES Using large-scale proteomics, we aimed to examine if plant-based diet-related proteins, which have been previously identified, are associated with incident CVD and subtypes of CVD in the Atherosclerosis Risk in Communities (ARIC) Study and Framingham Heart Study (FHS) Offspring cohort. METHODS Discovery analyses were based on 9,078 participants free of CVD at ARIC visit 3 (1993-1995). Cox proportional hazards regression was used to evaluate the associations between plant-based diet-related proteins and incident CVD, coronary heart disease, heart failure, and stroke. Replication analyses were based on 1,279 participants without CVD in FHS Offspring cohort. RESULTS In the ARIC Study, over a median follow-up of 21 years, there were 3,167 CVD events. At a false discovery rate (FDR) <0.05, 26 out of 73 plant-based diet-related proteins were significantly associated with incident CVD, after adjusting for important confounders. 18, 1, and 0 proteins were associated with heart failure, stroke, and coronary heart disease, respectively. Three, and 2 additional proteins were associated with CVD, and heart failure risk in FHS Offspring cohort at the nominal threshold (p value <0.05). Soluble advanced glycosylation end product-specific receptor (AGER) was inversely associated with incident CVD whereas thrombospondin-2 (THBS2) and N-terminal pro-BNP (NT-proBNP) was positively associated with incident CVD. THBS2 was positively associated with incident heart failure, whereas neuronal growth factor regulator 1 (NEGR1) and insulin-like growth factor-binding protein 1 (IGFBP1) was inversely associated. CONCLUSION These proteins highlight several pathways that could explain plant-based diets-CVD associations.
Collapse
Affiliation(s)
- Hyunju Kim
- Department of Epidemiology, University of Washington, Seattle, Washington; Cardiovascular Health Research Unit, Department of Medicine, University of Washington School of Public Health, Seattle, Washington.
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Brenton Prescott
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston University, Boston, Massachusetts
| | - Maura E Walker
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston University, Boston, Massachusetts; Department of Health Sciences, Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, Massachusetts
| | - Morgan E Grams
- Division of Precision Medicine, New York University Grossman School of Medicine, New York, New York
| | - Bing Yu
- Department of Epidemiology, University of Texas Health Sciences Center at Houston School of Public Health, Houston, Texas
| | | | - James Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington School of Public Health, Seattle, Washington; Division of Cardiology, University of Washington, Seattle, Washington
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington School of Public Health, Seattle, Washington; Division of Cardiology, University of Washington, Seattle, Washington
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, Washington; Cardiovascular Health Research Unit, Department of Medicine, University of Washington School of Public Health, Seattle, Washington
| | - Dan E Arking
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Optimal Aging Institute and Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York, New York
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland; Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| |
Collapse
|
5
|
Xing Z, Schocken DD, Zgibor JC, Alman AC. BMI, waist circumference, and waist-to-hip trajectories and all-cause, CVD, and cancer mortality by sex in people without diabetes. Int J Obes (Lond) 2025:10.1038/s41366-025-01778-6. [PMID: 40204962 DOI: 10.1038/s41366-025-01778-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2024] [Revised: 03/25/2025] [Accepted: 03/31/2025] [Indexed: 04/11/2025]
Abstract
OBJECTIVES We examined the associations of BMI, waist circumference, and waist-to-hip ratio trajectories with mortality in people without diabetes. METHODS We analyzed 7601 people without diabetes from the Atherosclerosis Risk in Communities Study. We used latent class analysis to identify trajectory patterns for BMI, waist circumference, and waist-to-hip. We employed propensity score matching to enhance the balance of covariates and used Cox proportional hazards regression models to examine the associations. RESULTS In females, the high trajectory of BMI was associated with higher cancer mortality risks than the low group, with the hazard ratio and 95% confidence interval of 1.76 (1.14-2.73). The high waist circumference trajectory was related to increased all-cause, CVD, and cancer mortality risks in males. The moderate and high waist-to-hip ratio trajectories were associated with elevated all-cause and CVD mortality risks in females, and the high trajectory was associated with high all-cause mortality risks in males. The mean lifespan of deceased females did not significantly differ across the trajectories. However, the mean lifespan of males in the waist circumference high group (73.0 years) was shorter than the low group (75.3 years). CONCLUSIONS Sex differences were observed in the long-term impact of high BMI, waist circumference, and waist-to-hip ratio on mortality risks and lifespan in people without diabetes.
Collapse
Affiliation(s)
- Zailing Xing
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Douglas D Schocken
- College of Public Health, University of South Florida, Tampa, FL, USA
- School of Medicine, Duke University, Durham, NC, USA
| | - Janice C Zgibor
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Amy C Alman
- College of Public Health, University of South Florida, Tampa, FL, USA.
| |
Collapse
|
6
|
Sullivan VK, Chen J, Bernard L, Yu B, Michos ED, Appel LJ, Lichtenstein AH, Rebholz CM. Serum and urine metabolite correlates of vitamin D supplementation in the Atherosclerosis Risk in Communities (ARIC) study. Clin Nutr ESPEN 2025; 67:523-532. [PMID: 40189143 DOI: 10.1016/j.clnesp.2025.03.172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2025] [Revised: 03/07/2025] [Accepted: 03/30/2025] [Indexed: 04/12/2025]
Abstract
BACKGROUND & AIMS Vitamin D regulates calcium and phosphorus homeostasis, skeletal health, and potentially other aspects of health. There are limitations of existing vitamin D biomarkers. We aimed to discover novel vitamin D biomarkers by investigating serum and urine metabolites associated with vitamin D supplementation. METHODS We examined cross-sectional associations between vitamin D supplementation and serum and urine metabolites in Atherosclerosis Risk in Communities Study participants at visit 5 (2011-2013). Untargeted metabolomic profiling of serum and spot urine samples was performed by Metabolon, Inc. We analyzed associations between vitamin D supplementation and log2-transformed metabolites using linear regression models adjusted for demographic, lifestyle, and health covariates. RESULTS Of 5225 participants with serum metabolites analyzed (mean age 76 [SD 5] years, 57 % female, 20 % Black), 45 % reported taking vitamin D supplements. Eighty-two of 933 serum metabolites were associated with vitamin D supplementation (P < 0.05/933). Most were lipids (n = 36). Of 1565 participants with urine metabolites analyzed, one-third (37 %) used vitamin D. Nineteen of 946 urine metabolites were associated with vitamin D supplementation (P < 0.05/946). Most were cofactors and vitamins (n = 12). After adjusting for other supplement use (multivitamin/mineral, omega-3, B and C vitamins), 5 serum metabolites (pro-hydroxy-pro, pyroglutamine, sulfate, creatine, and 2-hydroxypalmitate) and no urine metabolites were significantly associated with vitamin D supplementation. CONCLUSIONS Many serum and urine metabolites were associated with vitamin D supplementation. Five serum metabolites remained associated with vitamin D after adjustment for other dietary supplements, including metabolites of bone collagen degradation, glutathione metabolism, and sphingolipid metabolism. These metabolites may reflect physiological activities of vitamin D and, thus, improve assessment of vitamin D adequacy to achieve functional outcomes. These merit further investigation as potential vitamin D biomarkers.
Collapse
Affiliation(s)
- Valerie K Sullivan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; The Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Lauren Bernard
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; University of Maryland School of Medicine, Baltimore, MD, USA
| | - Bing Yu
- Department of Epidemiology, University of Texas Health Sciences Center at Houston School of Public Health, Houston, TX, USA
| | - Erin D Michos
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lawrence J Appel
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; The Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA; The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alice H Lichtenstein
- Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; The Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA; Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| |
Collapse
|
7
|
Hu Y, Haessler J, Lundin JI, Darst BF, Whitsel EA, Grove M, Guan W, Xia R, Szeto M, Raffield LM, Ratliff S, Wang Y, Wang X, Fohner AE, Lynch MT, Patel YM, Lani Park S, Xu H, Mitchell BD, Bis JC, Sotoodehnia N, Brody JA, Psaty BM, Peloso GM, Tsai MY, Rich SS, Rotter JI, Smith JA, Kardia SLR, Reiner AP, Lange L, Fornage M, Pankow JS, Graff M, North KE, Kooperberg C, Peters U. Methylome-wide association analyses of lipids and modifying effects of behavioral factors in diverse race and ethnicity participants. Clin Epigenetics 2025; 17:54. [PMID: 40176173 PMCID: PMC11967142 DOI: 10.1186/s13148-025-01859-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2024] [Accepted: 03/11/2025] [Indexed: 04/04/2025] Open
Abstract
Circulating lipid concentrations are clinically associated with cardiometabolic diseases. The phenotypic variance explained by identified genetic variants remains limited, highlighting the importance of searching for additional factors beyond genetic sequence variants. DNA methylation has been linked to lipid concentrations in previous studies, although most of the studies harbored moderate sample sizes and exhibited underrepresentation of non-European ancestry populations. In addition, knowledge of nongenetic factors on lipid profiles is extremely limited. In the Population Architecture Using Genomics and Epidemiology (PAGE) Study, we performed methylome-wide association analysis on 9,561 participants from diverse race and ethnicity backgrounds for HDL-c, LDL-c, TC, and TG levels, and also tested interactions between smoking or alcohol intake and methylation in their association with lipid levels. We identified novel CpG sites at 16 loci (P < 1.18E-7) with successful replication on 3,215 participants. One additional novel locus was identified in the self-reported White participants (P = 4.66E-8). Although no additional CpG sites were identified in the genome-wide interaction analysis, 13 reported CpG sites showed significant heterogeneous association across smoking or alcohol intake strata. By mapping novel and reported CpG sites to genes, we identified enriched pathways directly linked to lipid metabolism as well as ones spanning various biological functions. These findings provide new insights into the regulation of lipid concentrations.
Collapse
Grants
- N01HC95160 NHLBI NIH HHS
- 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, 75N92021D00005, and S10OD028685 NIH HHS
- 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1TR001881, DK063491, HL148610, and R01HL105756 NHLBI NIH HHS
- R01 HL087652 NHLBI NIH HHS
- UL1 TR000040 NCATS NIH HHS
- HHSN268201800010I NHLBI NIH HHS
- N01HC85081 NHLBI NIH HHS
- R01 HL103612 NHLBI NIH HHS
- 75N92020D00002 NHLBI NIH HHS
- 75N92021D00002 NHLBI NIH HHS
- HHSN268201500003C NHLBI NIH HHS
- U01HG007397 NHGRI NIH HHS
- HHSN268201800012C NHLBI NIH HHS
- 75N92020D00005 NHLBI NIH HHS
- 75N92021D00005 WHI NIH HHS
- U01HL054457, RC1HL100185, R01HL087660, R01HL119443, R01HL133221 NHLBI NIH HHS
- 75N92022D00001 NIH HHS
- N01HC95163 NHLBI NIH HHS
- U01 HL080295 NHLBI NIH HHS
- UL1 TR001079 NCATS NIH HHS
- DK063491 National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center
- HHSN268201800014I NHLBI NIH HHS
- U01CA164973 NCI NIH HHS
- U01 HL130114 NHLBI NIH HHS
- R01 HL087660 NHLBI NIH HHS
- HHSN268200800007C NHLBI NIH HHS
- S10 OD028685 NIH HHS
- 75N92020D00001 NHLBI NIH HHS
- N01HC95169 NHLBI NIH HHS
- N01HC95164 NHLBI NIH HHS
- UL1 TR000124 NCATS NIH HHS
- N01HC55222 NHLBI NIH HHS
- HHSN268201800014C NHLBI NIH HHS
- N01HC95162 NHLBI NIH HHS
- N01HC85086 NHLBI NIH HHS
- 75N92020D00003 NHLBI NIH HHS
- R01 HL119443 NHLBI NIH HHS
- R01 HL105756 NHLBI NIH HHS
- N01HC95168 NHLBI NIH HHS
- K08 HL116640 NHLBI NIH HHS
- 75N92021D00001 NHLBI NIH HHS
- P30 DK063491 NIDDK NIH HHS
- RC1 HL100185 NHLBI NIH HHS
- HHSN268201200036C NHLBI NIH HHS
- HHSN268201800001C NHLBI NIH HHS
- HHSN268201800013I NIMHD NIH HHS
- UL1TR000124 NCATS NIH HHS
- U01 HL054457 NHLBI NIH HHS
- N01HC95165 NHLBI NIH HHS
- N01HC95159 NHLBI NIH HHS
- HHSN268201800012I NHLBI NIH HHS
- 75N92021D00003 WHI NIH HHS
- N01HC95161 NHLBI NIH HHS
- UL1 TR001420 NCATS NIH HHS
- 75N92020D00004 NHLBI NIH HHS
- HHSN268201800011C NHLBI NIH HHS
- 75N92020D00007 NHLBI NIH HHS
- R01AG023629 NIA NIH HHS
- HHSN268201800013I, HHSN268201800014I, HHSN268201800015I, HHSN268201800010I, HHSN268201800011I, and HHSN268201800012I NIMHD NIH HHS
- HHSN268201500003I NHLBI NIH HHS
- R01HL105756, HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, R01AG023629, 75N92021D00006, U01HL080295, U01HL130114, K08HL116640, R01HL087652, R01HL092111, R01HL103612, R01HL111089, R01HL116747 and R01HL120393 NHLBI NIH HHS
- R01 HL133221 NHLBI NIH HHS
- 75N92021D00006 NHLBI NIH HHS
- R01HG010297 NHGRI NIH HHS
- N01HC85082 NHLBI NIH HHS
- N01HC95167 NHLBI NIH HHS
- N01HC85083 NHLBI NIH HHS
- HHSN268201800015I NHLBI NIH HHS
- 75N92020D00006 NHLBI NIH HHS
- N01HC85079 NHLBI NIH HHS
- N01HC95166 NHLBI NIH HHS
- R01 AG023629 NIA NIH HHS
- UL1 TR001881 NCATS NIH HHS
- HHSN268201800011I NHLBI NIH HHS
- N01HC85080 NHLBI NIH HHS
- R01 HG010297 NHGRI NIH HHS
- U01 CA164973 NCI NIH HHS
- 75N92021D00004 WHI NIH HHS
- R01 HL111089 NHLBI NIH HHS
- R01 HL116747 NHLBI NIH HHS
- R01 HL092111 NHLBI NIH HHS
- National Institutes of Health
- National Human Genome Research Institute
- National Institute on Minority Health and Health Disparities
- National Heart, Lung, and Blood Institute
- National Institute on Aging
- National Center for Advancing Translational Sciences
- National Cancer Institute
Collapse
Affiliation(s)
- Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jessica I Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Burcu F Darst
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Eric A Whitsel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Megan Grove
- School of Public Health, Human Genetics Center, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Weihua Guan
- Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Rui Xia
- McGovern Medical School, The Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Mindy Szeto
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Scott Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Xuzhi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Alison E Fohner
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Megan T Lynch
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yesha M Patel
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - S Lani Park
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Huichun Xu
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Leslie Lange
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Myriam Fornage
- School of Public Health, Human Genetics Center, University of Texas Health Sciences Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
| |
Collapse
|
8
|
Copp KL, Steffen LM, Yi SY, Lutsey PL, Rebholz CM, Rooney MR. Magnesium-rich diet score is inversely associated with incident cardiovascular disease: the Atherosclerosis Risk in Communities (ARIC) study. Eur J Prev Cardiol 2025; 32:386-393. [PMID: 39096274 PMCID: PMC11806921 DOI: 10.1093/eurjpc/zwae251] [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: 10/21/2023] [Revised: 07/06/2024] [Accepted: 07/29/2024] [Indexed: 08/05/2024]
Abstract
AIMS Numerous studies have shown inverse associations between serum magnesium (Mg) and risk of cardiovascular disease (CVD), but studies of dietary Mg have not been consistent. To examine the association of a Mg-rich diet score with risks of CVD, coronary heart disease (CHD), and ischaemic stroke in the Atherosclerosis Risk in Communities (ARIC) study. METHODS AND RESULTS There were 15 022 Black and White adults without prevalent CVD at baseline (1987-89) included in this analysis. Diet was assessed at two visits 6 years apart using an interviewer-administered 66-item food frequency questionnaire. A Mg-rich diet score was created that included servings of whole grain products, nuts, vegetables, fruit, legumes, coffee, and tea. Cox proportional hazard regression evaluated associations of incident CVD, CHD, and stroke across quintiles of Mg-rich diet score, adjusting for demographics, lifestyle factors, and clinical characteristics. Over >30 years of follow-up, there were 3531 incident CVD events (2562 CHD, 1332 ischaemic stroke). Participants who consumed more Mg-rich foods were older, female, White, had lower blood pressure, fewer were not current smokers, and more reported being physically active. A Mg-rich diet was inversely associated with incident CVD (HRQ5 vs. Q1 = 0.87, 95% CI: 0.77-0.98, Ptrend = 0.02) and CHD (HRQ5 vs. Q1 = 0.82, 95% CI: 0.71-0.95, Ptrend = 0.01); however, the diet-stroke association was null (HRQ5 vs. Q1 = 1.00, 95% CI: 0.82-1.22, Ptrend = 0.97). CONCLUSION Consuming a diet including Mg-rich foods, such as whole grains, nuts, vegetables, fruits, legumes, coffee, and tea, is associated with lower risk of CVD and CHD, but not ischaemic stroke.
Collapse
Affiliation(s)
- Katherine L Copp
- University of Minnesota School of Public Health, Division of Epidemiology and Community Health, 1300 South Second St, Suite 300, Minneapolis, MN 55454, USA
| | - Lyn M Steffen
- University of Minnesota School of Public Health, Division of Epidemiology and Community Health, 1300 South Second St, Suite 300, Minneapolis, MN 55454, USA
| | - So-Yun Yi
- University of Minnesota School of Public Health, Division of Epidemiology and Community Health, 1300 South Second St, Suite 300, Minneapolis, MN 55454, USA
| | - Pamela L Lutsey
- University of Minnesota School of Public Health, Division of Epidemiology and Community Health, 1300 South Second St, Suite 300, Minneapolis, MN 55454, USA
| | - Casey M Rebholz
- Johns Hopkins University Bloomberg School of Public Health, Department of Epidemiology, Baltimore, MD 21287, USA
| | - Mary R Rooney
- Johns Hopkins University Bloomberg School of Public Health, Department of Epidemiology, Baltimore, MD 21287, USA
| |
Collapse
|
9
|
Rooney MR, Chen J, Ballantyne CM, Hoogeveen RC, Boerwinkle E, Yu B, Walker KA, Schlosser P, Selvin E, Chatterjee N, Couper D, Grams ME, Coresh J. Correlations Within and Between Highly Multiplexed Proteomic Assays of Human Plasma. Clin Chem 2025:hvaf030. [PMID: 40172053 DOI: 10.1093/clinchem/hvaf030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2024] [Accepted: 02/11/2025] [Indexed: 04/04/2025]
Abstract
INTRODUCTION The number of assays on proteomic platforms has grown rapidly. The leading platforms, SomaScan and Olink, have strengths and limitations. Comparisons of precision on the latest platforms-SomaScan 11k and Olink Explore HT-have not yet been established. METHODS Among 102 participants in the Atherosclerosis Risk in Communities Study (mean age 74 years, 53% women, 47% Black), we used split plasma samples to measure platform precision. CV and Spearman correlations were calculated for each assay. Cross-platform agreement was assessed for overlapping proteins. RESULTS SomaScan 11k demonstrated a median correlation of 0.85 for the 10 778 assays and a median CV of 6.8%, similar precision to earlier versions. The 5420 assays on Olink Explore HT exhibited a median correlation of 0.65 and median CV of 35.7%, which was higher than observed in its predecessors (e.g., 19.8% for Olink Explore 3072). Precision of Olink assays was inversely correlated with the percentage of samples above the limit of detection (LOD) (r = -0.77). Upon replacing Olink values below the LOD with values half the LOD, the median correlation for Olink assays measured in duplicate increased to 0.79; the median CV decreased to 13.3%. The distribution of between-platform correlations for the 4443 overlapping proteins had peaks at r approximately 0 and at r approximately 0.8. One-tenth of the protein pairs had cross-platform correlations r ≥ 0.8. CONCLUSIONS Precision of these 2 proteomics platforms in human plasma has diverged as the coverage has increased. These results highlight the need for careful consideration in platform selection based on specific research requirements.
Collapse
Affiliation(s)
- Mary R Rooney
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | | | - Ron C Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, TX, United States
| | - Eric Boerwinkle
- Department of Epidemiology, University of Texas Health Science Center, Houston, TX, United States
| | - Bing Yu
- Department of Epidemiology, University of Texas Health Science Center, Houston, TX, United States
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, United States
| | - Pascal Schlosser
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Morgan E Grams
- Division of Precision Medicine, New York University Grossman School of Medicine, New York, NY, 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
| |
Collapse
|
10
|
Levine DA, Whitney RT, Ye W, Briceño EM, Gross AL, Giordani BJ, Sussman JB, Lazar RM, Howard VJ, Aparicio HJ, Beiser AS, Elkind MSV, Gottesman RF, Koton S, Pendlebury ST, Kollipara AS, Springer MV, Seshadri S, Romero JR, Fitzpatrick AL, Longstreth WT, Hayward RA. Associations Between Stroke Type, Ischemic Stroke Subtypes, and Poststroke Cognitive Trajectories. Stroke 2025; 56:898-907. [PMID: 40062407 DOI: 10.1161/strokeaha.124.047640] [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: 04/26/2024] [Revised: 11/22/2024] [Accepted: 01/27/2025] [Indexed: 03/26/2025]
Abstract
BACKGROUND It is unclear how poststroke cognitive trajectories differ by stroke type and ischemic stroke subtype. We studied associations between stroke types (ischemic and hemorrhagic), ischemic stroke subtypes (cardioembolic, large artery atherosclerotic, lacunar/small vessel, and cryptogenic/other determined causes), and poststroke cognitive decline. METHODS We pooled participants from 4 US cohort studies (1971-2019). Outcomes were change in global cognition (primary) and changes in executive function and memory (secondary). Outcomes were standardized as T scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1 SD difference in cognition. The median follow-up for the primary outcome was 6.0 (interquartile range, 3.2-9.2) years. Linear mixed-effects models estimated changes in cognition after stroke. RESULTS We identified 1143 dementia-free individuals with acute stroke during follow-up: 1061 (92.8%) ischemic, 82 (7.2%) hemorrhagic, 49.9% female, and 30.8% Black. The median age at stroke was 74.1 (interquartile range, 68.6-79.3) years. On average, ischemic stroke survivors showed declines in global cognition (-0.35 [95% CI, -0.43 to -0.27] points/y; P<0.001), executive function (-0.48 [95% CI, -0.59 to -0.36] points/y; P<0.001), and memory (-0.27 [95% CI, -0.36 to -0.19] points/y; P<0.001). Poststroke declines in global cognition, executive function, and memory did not differ between hemorrhagic and ischemic stroke survivors. Differences in poststroke cognitive slope between hemorrhagic and ischemic stroke survivors were global cognition (0.02 [95% CI, -0.21 to 0.26] points/y; P=0.85), executive function (-0.13 [95% CI, -0.48 to 0.23] points/y; P=0.48), and memory (0.19 [95% CI, -0.05 to 0.43] points/y; P=0.12). On average, small vessel stroke survivors showed declines in global cognition (-0.33 [95% CI, -0.49 to -0.16] points/y; P<0.001), executive function (-0.44 [95% CI, -0.68 to -0.19] points/y; P<0.001), and memory (-0.19 [95% CI, -0.35 to -0.03] points/y; P=0.02). Poststroke cognitive declines did not differ between small vessel survivors and survivors of other ischemic stroke subtypes. CONCLUSIONS Stroke survivors had cognitive decline in multiple domains. Declines did not differ by stroke type or ischemic stroke subtype.
Collapse
Affiliation(s)
- Deborah A Levine
- Departments of Internal Medicine (D.A.L., R.T.W., J.B.S., A.S.K., R.A.H.), University of Michigan, Ann Arbor
- Neurology (D.A.L., M.V.S.), University of Michigan, Ann Arbor
| | - Rachael T Whitney
- Departments of Internal Medicine (D.A.L., R.T.W., J.B.S., A.S.K., R.A.H.), University of Michigan, Ann Arbor
| | - Wen Ye
- Biostatistics (W.Y.), University of Michigan, Ann Arbor
| | - Emily M Briceño
- Physical Medicine and Rehabilitation (E.M.B.), University of Michigan, Ann Arbor
| | - Alden L Gross
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD (A.L.G., S.K.)
| | | | - Jeremy B Sussman
- Departments of Internal Medicine (D.A.L., R.T.W., J.B.S., A.S.K., R.A.H.), University of Michigan, Ann Arbor
- VA Ann Arbor Healthcare System, MI (J.B.S., R.A.H.)
| | - Ronald M Lazar
- Departments of Neurology (R.M.L.), University of Alabama at Birmingham
| | | | - Hugo J Aparicio
- Departments of Neurology (H.J.A., A.S.B., J.R.R.), Boston University, MA
| | - Alexa S Beiser
- Departments of Neurology (H.J.A., A.S.B., J.R.R.), Boston University, MA
- Biostatistics (A.S.B.), Boston University, MA
| | | | - Rebecca F Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke, Bethesda, MD (R.F.G.)
| | - Silvia Koton
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD (A.L.G., S.K.)
- Department of Nursing, Tel Aviv University, Israel (S.K.)
| | - Sarah T Pendlebury
- Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom; National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Departments of Medicine and Geratology, Oxford University Hospitals National Health Service (NHS) Foundation Trust, United Kingdom (S.T.P.)
| | - Adam S Kollipara
- Departments of Internal Medicine (D.A.L., R.T.W., J.B.S., A.S.K., R.A.H.), University of Michigan, Ann Arbor
| | | | - Sudha Seshadri
- Department of Neurology, University of Texas San Antonio (S.S.)
| | - Jose R Romero
- Departments of Neurology (H.J.A., A.S.B., J.R.R.), Boston University, MA
| | | | - W T Longstreth
- Departments of Epidemiology (A.L.F., W.T.L.), University of Washington, Seattle
- Neurology (W.T.L.), University of Washington, Seattle
| | - Rodney A Hayward
- Departments of Internal Medicine (D.A.L., R.T.W., J.B.S., A.S.K., R.A.H.), University of Michigan, Ann Arbor
- VA Ann Arbor Healthcare System, MI (J.B.S., R.A.H.)
| |
Collapse
|
11
|
Masini G, Wang W, Ji Y, Eaton A, Inciardi RM, Soliman EZ, Passman RS, Solomon SD, Shah AM, De Caterina R, Chen LY. Markers of Left Atrial Myopathy: Prognostic Usefulness for Ischemic Stroke and Dementia in People in Sinus Rhythm. Stroke 2025; 56:858-867. [PMID: 40052267 DOI: 10.1161/strokeaha.124.047747] [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: 05/06/2024] [Revised: 12/09/2024] [Accepted: 01/21/2025] [Indexed: 03/26/2025]
Abstract
BACKGROUND Various measures of abnormal left atrial (LA) structure or function (LA myopathy) are associated with a higher risk of ischemic stroke and dementia, independent of atrial fibrillation. However, limited data exist on their prognostic usefulness. Therefore, we aimed to assess the ability of markers of LA myopathy to improve the prediction of ischemic stroke and dementia. METHODS The ARIC study (Atherosclerosis Risk in Communities) is a prospective community-based cohort study. For this analysis, we included participants who attended visit 5 (2011-2013) without a history of stroke or atrial fibrillation and had a 12-lead ECG and a transthoracic echocardiogram. Markers of LA myopathy included P wave abnormalities from 12-lead ECG, NT-proBNP (N-terminal pro-B-type natriuretic peptide), and LA volume and strain parameters from the echocardiogram. The primary composite outcome comprised ischemic stroke and dementia, which were ascertained through hospital surveillance, cohort follow-up, and death registries. To determine improvement in risk prediction of the composite outcome, each marker was individually added to a model that included CHA2DS2-VASc variables, and Akaike information criterion, C statistic, and its change were computed. Cox proportional hazards models were used to assess the independent association of LA myopathy markers with the outcome. RESULTS Among 4712 participants (59% female; mean age, 74 years), 193 ischemic strokes and 769 dementia cases were ascertained over a median follow-up of 8.3 years. Of LA myopathy markers, only LA reservoir strain and NT-proBNP significantly improved C statistic when added to the CHA2DS2-VASc model (base C statistic, 0.677) for the prediction of the composite outcome. Adding the LA reservoir yielded the highest increase in C statistic (0.010 [95% CI, 0.003-0.017]), and the model including the LA reservoir showed the lowest Akaike information criterion. In multivariable regression models, LA volume index, NT-proBNP, and LA strain parameters were significantly associated with the composite outcome. CONCLUSIONS Of various LA myopathy markers, LA reservoir yields the greatest improvement in the prediction of ischemic stroke and dementia, supporting its use to identify people at high risk of cerebrovascular events and dementia.
Collapse
Affiliation(s)
- Gabriele Masini
- Pisa University Hospital, Cardiology Division, University of Pisa, Italy (G.M., R.D.C.)
| | - Wendy Wang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (W.W.)
| | - Yuekai Ji
- Johns Hopkins University, Baltimore, MD (Y.J.)
| | - Anne Eaton
- Division of Biostatistics and Health Data Science, School of Public Health University of Minnesota, Minneapolis (A.E.)
| | - Riccardo M Inciardi
- Brescia University Hospital, Cardiology Division, University of Brescia, Italy (R.M.I.)
| | - Elsayed Z Soliman
- Department of Internal Medicine, Cardiovascular Medicine Section, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Rod S Passman
- Division of Cardiology, Feinberg School of Medicine, Northwestern University, Chicago, IL (R.S.P.)
| | - Scott D Solomon
- Department of Cardiology, Harvard Medical School, Boston, MA (S.D.S.)
| | - Amil M Shah
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA (A.M.S.)
| | - Raffaele De Caterina
- Pisa University Hospital, Cardiology Division, University of Pisa, Italy (G.M., R.D.C.)
| | - Lin Yee Chen
- Lillehei Heart Institute and Department of Medicine, University of Minnesota Medical School, Minneapolis (L.Y.C.)
| |
Collapse
|
12
|
Venkataraghavan S, Pankow JS, Boerwinkle E, Fornage M, Selvin E, Ray D. Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study. Diabetologia 2025; 68:815-834. [PMID: 39971753 DOI: 10.1007/s00125-024-06352-9] [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: 08/28/2023] [Accepted: 05/29/2024] [Indexed: 02/21/2025]
Abstract
AIMS/HYPOTHESIS DNA methylation studies of incident type 2 diabetes in US populations are limited and to our knowledge none include individuals of African descent. We aimed to fill this gap by identifying methylation sites (CpG sites) and regions likely influencing the development of type 2 diabetes using data from Black and White individuals from the USA. METHODS We prospectively followed 2091 Black and 1029 White individuals without type 2 diabetes from the Atherosclerosis Risk in Communities study over a median follow-up period of 17 years, and performed an epigenome-wide association analysis of blood-based methylation levels with incident type 2 diabetes using Cox regression. We assessed whether significant CpG sites were associated with incident type 2 diabetes independently of BMI or fasting glucose at baseline. We estimated variation in incident type 2 diabetes accounted for by the major non-genetic risk factors and the significant CpG sites. We also examined groups of methylation sites that were differentially methylated. We performed replication of previously discovered CpG sites associated with prevalent and/or incident type 2 diabetes. All analyses were adjusted for batch effects, cell-type proportions and relevant confounders. RESULTS At an epigenome-wide threshold (10-7), we detected seven novel diabetes-associated CpG sites, of which the sites at MICOS10 (cg05380846: HR 0.89, p=8.4 × 10-12), ZNF2 (cg01585592: HR 0.88, p=1.6 × 10-9), JPH3 (cg16696007: HR 0.87, p=7.8 × 10-9) and GPX6 (cg02793507: HR 0.85, p=2.7 × 10-8; cg00647063: HR 1.20, p=2.5 × 10-8) were identified in Black adults; chr17q25 (cg16865890: HR 0.8, p=6.9 × 10-8) in White adults; and chr11p15 (cg13738793: HR 1.11, p=7.7 × 10-8) in the meta-analysed group. The JPH3 and GPX6 sites remained epigenome-wide significant on adjustment for BMI, while only the JPH3 site retained significance after adjusting for fasting glucose. We replicated known type 2 diabetes-associated CpG sites, including cg19693031 at TXNIP, cg00574958 at CPT1A, cg16567056 at PLCB2, cg11024682 at SREBF1, cg08857797 at VPS25 and cg06500161 at ABCG1, three of which were replicated in Black adults at the epigenome-wide threshold and all of which had directionally consistent effects. We observed a modest increase in type 2 diabetes variance explained by the significantly associated CpG sites over and above traditional type 2 diabetes risk factors and fasting glucose (26.2% vs 30.5% in Black adults; 36.9% vs 39.4% in White adults). At the Šidák-corrected significance threshold of 5%, our differentially methylated region (DMR) analyses revealed several clusters of significant CpG sites, including a DMR consisting of a previously discovered CpG site at ADCY7 (pBlack=1.8 × 10-4, pWhite=3.6 × 10-3, pAll=1.6 × 10-9) and a DMR consisting of the promoter region of TP63 (pBlack=7.4 × 10-4, pWhite=3.9 × 10-3, pAll=1.4 × 10-5), which were differentially methylated across all racial and ethnic groups. CONCLUSIONS/INTERPRETATION This study illustrates improved discovery of CpG sites and regions by leveraging both individual CpG site analysis and DMR analyses in an unexplored population. Our findings include genes linked to diabetes in experimental studies (e.g. GPX6, JPH3 and TP63). The JPH3 and GPX6 sites were likely associated with incident type 2 diabetes independently of BMI. All the CpG sites except that at JPH3 were likely consequences of elevated glucose. Replication in African-descent individuals of CpG sites previously discovered mostly in individuals of European descent indicates that some of these methylation-type 2 diabetes associations are robust across racial and ethnic groups. This study is a first step towards understanding the influence of methylation on the incidence of type 2 diabetes and its disparity in two major racial and ethnic groups in the USA. It paves the way for future studies to investigate causal relationships between type 2 diabetes and the CpG sites and potentially elucidate molecular targets for intervention.
Collapse
Affiliation(s)
- Sowmya Venkataraghavan
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Eric Boerwinkle
- The University of Texas Health School of Public Health, Houston, TX, USA
| | - Myriam Fornage
- Brown Foundation Institute for Molecular Medicine, The University of Texas Health Science Center, Houston, TX, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, & Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Debashree Ray
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
| |
Collapse
|
13
|
Kim H, Yin Y, Steffen LM, Lutsey PL, Grams ME, Walker KA, Ugoji C, Matsushita K, Rebholz CM. Novel Dietary Inflammatory Score and Risk of Incident CKD. Clin J Am Soc Nephrol 2025; 20:485-494. [PMID: 39960780 DOI: 10.2215/cjn.0000000635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Accepted: 02/12/2025] [Indexed: 04/11/2025]
Abstract
Key Points
Inflammation is relevant for CKD. Dietary intake influences inflammation.In 9814 individuals, our study found that concordance to a proinflammatory diet was associated with greater risk of CKD.Our results suggest that clinicians should consider recommending reducing dietary patterns high in inflammatory potential.
Background
Inflammation contributes to the onset of CKD. Diet is a modifiable risk factor for CKD; however, it remains unknown if the inflammatory potential of the diet is prospectively associated with CKD risk in healthy individuals.
Methods
In 9814 participants (mean age: 60 years) free of CKD in the Atherosclerosis Risk in Communities Study at visit 3 (1993–1995), we developed a novel empirically derived, food-based, dietary inflammatory score (Comprehensive Dietary Inflammation Index [CDII]) from a random two-thirds sample (N=6,542, discovery) and validated in the remaining one-third sample (N=3,272, validation). Reduced rank regression with 13 inflammatory biomarkers as the response variables and 31 food groups as the independent variables was used to develop the CDII. Cox proportional hazards models were used to calculate hazard ratios and 95% confidence intervals and test the association between the CDII and incident CKD, adjusting for important confounders.
Results
The CDII included eight food groups (four proinflammatory and four anti-inflammatory), with a higher score representing a more proinflammatory diet. In the validation sample, the CDII was positively correlated with most proinflammatory proteins (C-reactive protein, interferon-γ, IL-8, IL-6, and monocyte chemoattractant protein-1) and negatively correlated with adiponectin. However, the CDII was positively associated with one anti-inflammatory protein (transforming growth factor-β). Over a median follow-up of 19 years (mean follow-up of 18 years), 3293 participants developed CKD. A diet that was the most versus least concordant with the CDII (quartile 4 versus quartile 1) had 28% greater risk of incident CKD (hazard ratio, 1.28; 95% confidence interval, 1.15 to 1.43; P trend < 0.001).
Conclusions
A novel diet score, representing its inflammatory potential, was associated with a higher risk of developing CKD. Reducing consumption of proinflammatory diet may be a strategy to prevent CKD.
Collapse
Affiliation(s)
- Hyunju Kim
- Department of Epidemiology, University of Washington, Seattle, Washington
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington
| | - Yang Yin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Morgan E Grams
- Division of Precision Medicine, New York University Grossman School of Medicine, New York, New York
| | - Keenan A Walker
- Intramural Research Program, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland
| | | | - Kunihiro Matsushita
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, Maryland
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, Maryland
- Division of Nephrology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| |
Collapse
|
14
|
Wu Y, Zhao J, Chen C, Huang J, Liang W, Li J, Dong Y, Liu C, Xue R. Pulse pressure and aortic valve peak velocity and incident heart failure after myocardial infarction: a cohort study. Heart 2025; 111:370-377. [PMID: 39915069 DOI: 10.1136/heartjnl-2024-324517] [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: 06/03/2024] [Accepted: 12/01/2024] [Indexed: 03/28/2025] Open
Abstract
BACKGROUND Heart failure with preserved ejection fraction is a recognised outcome in patients with myocardial infarction, although heart failure with reduced ejection fraction is more common. Identifying early indicators specific to heart failure with preserved ejection fraction in patients with myocardial infarction could support targeted preventive strategies. This study aimed to determine if pulse pressure and aortic valve peak velocity could serve as early predictors of heart failure with preserved ejection fraction in patients with myocardial infarction. METHODS We retrospectively analysed data from 5188 participants in the Atherosclerosis Risk in Communities Study who were free from heart failure at baseline, including 802 individuals with a history of myocardial infarction. Heart failure events were classified as either heart failure with preserved ejection fraction (left ventricular ejection fraction ≥50%) or heart failure with mildly reduced or reduced ejection fraction (left ventricular ejection fraction <50%). Competing risk regression models were used to examine associations of baseline pulse pressure and aortic valve peak velocity with heart failure subtypes. RESULTS Over 6 years of follow-up, 217 cases of heart failure with preserved ejection fraction (including 50 in patients with myocardial infarction) and 127 cases of heart failure with mildly reduced or reduced ejection fraction (33 in patients with myocardial infarction) were identified. Among patients with myocardial infarction, a 1-SD increase in pulse pressure was associated with a 1.60-fold higher risk of heart failure with preserved ejection fraction (95% CI 1.30 to 1.97), and a similar association was observed for aortic valve peak velocity (HR: 1.37, 95% CI 1.19 to 1.58). Patients with pulse pressure ≥68 mm Hg had a 3.83-fold higher risk of heart failure with preserved ejection fraction compared with those with lower pulse pressure, and those with aortic valve peak velocity ≥1.4 m/s had a 2.10-fold higher risk compared with those with lower values. Patients with myocardial infarction with two or more risk factors among elevated pulse pressure, aortic valve peak velocity, diabetes and atrial fibrillation had over 16 times the risk of developing heart failure with preserved ejection fraction compared with those without these risk factors (p<0.001). CONCLUSIONS Pulse pressure and aortic valve peak velocity are significant predictors of heart failure with preserved ejection fraction in patients with myocardial infarction, suggesting their potential value in early risk stratification. These findings support the use of these markers to guide timely interventions aimed at preventing the progression to heart failure with preserved ejection fraction.
Collapse
Affiliation(s)
- Yuzhong Wu
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
| | - Jingjing Zhao
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
| | - Chen Chen
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
| | - Jiale Huang
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
| | - Weihao Liang
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
| | - Jiayong Li
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
| | - Yugang Dong
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
| | - Chen Liu
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
- National-Guangdong Joint Engineering Laboratory for Diagnosis and Treatment of Vascular Diseases, Guangzhou, China
| | - Ruicong Xue
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
- Key Laboratory of Assisted Circulation and Vascular Diseases, Chinese Academy of Medical Sciences, Guangzhou, China
- National-Guangdong Joint Engineering Laboratory for Diagnosis and Treatment of Vascular Diseases, Guangzhou, China
| |
Collapse
|
15
|
He Q, Liao YJ, Wang JJ, Chen YL, Huang MJ, Lin MP, Zhou HL, Chen ZE, Wu Q, Lu SL, Wu SL, Xue YM, Fang XH, Cheng YJ. Long-Term Risk of Incident Arrhythmias Associated With Early Repolarization Pattern - The Atherosclerosis Risk in Communities (ARIC) Study. Circ J 2025:CJ-24-0964. [PMID: 40128949 DOI: 10.1253/circj.cj-24-0964] [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] [Indexed: 03/26/2025]
Abstract
BACKGROUND The early repolarization pattern (ERP) is associated with cardiovascular death, but its connection with arrhythmias remains unknown. This study evaluated relationships between ERP and incident arrhythmias, including ventricular arrhythmias, bradyarrhythmias, and atrial fibrillation (AF)/flutter (Afl). METHODS AND RESULTS We analyzed 14,679 middle-aged (45-64 years) participants from the Atherosclerosis Risk in Communities cohort, a prospective population-based study in the US. Participants were monitored for ERP status at baseline and at 3 subsequent follow-up visits. We examined associations between incident arrhythmias and baseline ERP, time-varying ERP, time-updated ERP, and changes in ERP over time using Cox models to estimate hazard ratios (HRs) adjusted for potential confounders. Over a 20-year follow-up, there were 1,252 ventricular arrhythmias, 890 bradyarrhythmias, and 2,202 cases of AF. Time-updated ERP was associated with increased HRs for ventricular arrhythmias (1.55; 95% confidence interval [CI] 1.35-1.77), bradyarrhythmias (1.76; 95% CI 1.48-2.08), and AF (1.25; 95% CI 1.10-1.43). Time-varying ERP also showed associations with these outcomes. Compared with individuals with consistently normal electrocardiogram results, those with new-onset or persistent ERP had increased risks of incident arrhythmias. In subjects with time-updated ERP, anterior leads and J wave amplitudes ≥0.2 mV were associated with a higher incidence of arrhythmias. CONCLUSIONS Several types of ERP, including time-varying, time-updated, new-onset, and consistent, are associated with the incidence of arrhythmias in the middle-aged biracial (Black and White) population.
Collapse
Affiliation(s)
- Qian He
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Yi-Jian Liao
- The First Clinical Medical College, Guangdong Medical University
| | - Jin-Jie Wang
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Yan-Lin Chen
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Min-Jing Huang
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Mei-Ping Lin
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Hai-Ling Zhou
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Zi-En Chen
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Qian Wu
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
- School of Medicine, South China University of Technology
| | - Si-Long Lu
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
- School of Medicine, South China University of Technology
| | - Shu-Lin Wu
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Yu-Mei Xue
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Xian-Hong Fang
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Yun-Jiu Cheng
- Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| |
Collapse
|
16
|
Prizment A, Standafer A, Qu C, Beutel KM, Wang S, Huang WY, Lindblom A, Pearlman R, Van Guelpen B, Wolk A, Buchanan DD, Grant RC, Schmit SL, Platz EA, Joshu CE, Couper DJ, Peters U, Starr TK, Scott P, Pankratz N. Functional variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene are associated with increased risk of colorectal cancer. Hum Mol Genet 2025; 34:617-625. [PMID: 39825500 PMCID: PMC11924186 DOI: 10.1093/hmg/ddaf007] [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: 07/06/2024] [Revised: 12/17/2024] [Accepted: 01/14/2025] [Indexed: 01/20/2025] Open
Abstract
BACKGROUND Individuals with cystic fibrosis (CF; a recessive disorder) have an increased risk of colorectal cancer (CRC). Evidence suggests individuals with a single CFTR variant may also have increased CRC risk. METHODS Using population-based studies (GECCO, CORECT, CCFR, and ARIC; 53 785 CRC cases and 58 010 controls), we tested for an association between the most common CFTR variant (Phe508del) and CRC risk. For replication, we used whole exome sequencing data from UK Biobank (UKB; 5126 cases and 20 504 controls matched 4:1 based on genetic distance, age, and sex), and extended our analyses to all other heterozygous CFTR variants annotated as CF-causing. RESULTS In our meta-analysis of GECCO-CORECT-CCFR-ARIC, the odds ratio (OR) for CRC risk associated with Phe508del was 1.11 (P = 0.010). In our UKB replication, the OR for CRC risk associated with Phe508del was 1.28 (P = 0.002). The sequencing data from UKB also revealed an association between the presence of any other single CF-causing variant (excluding Phe508del) and CRC risk (OR = 1.33; P = 0.030). When stratifying CFTR variants by functional class, class I variants (no protein produced) had a stronger association (OR = 1.77; p = 0.002), while class II variants (misfolding and retention of the protein in the endoplasmic reticulum) other than Phe508del (OR = 1.75; p = 0.107) had similar effect size as Phe508del, and variants in classes III-VI had non-significant ORs less than 1.0 and/or were not present in cases. CONCLUSIONS CF-causing heterozygous variants, especially class I variants, are associated with a modest but statistically significant increased CRC risk. More research is needed to explain the biology underlying these associations.
Collapse
Affiliation(s)
- Anna Prizment
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
- Masonic Cancer Center, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Abby Standafer
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98019, USA
| | - Kathleen M Beutel
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Shuo Wang
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, MSC 9776, Bethesda, MD, 20892, USA
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, K1 Molekylär medicin och kirurgi, K1 MMK Klinisk genetik, 171 76 Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Eugeniavägen 3, 171 64 Solna, Sweden
| | - Rachel Pearlman
- Department of Internal Medicine, Division of Human Genetics, The Ohio State University Comprehensive Cancer Center, 2012 Kenny Rd, Columbus, OH, 43221, USA
| | - Bethany Van Guelpen
- Department of Radiation Sciences, Oncology Unit, 27C, Målpunkt QC11, NUS, Norrlands universitetssjukhus, Umeå University, 901 85 Umeå, Sweden
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, C6 Institutet för miljömedicin, C6 CVD-NUT-EPI Wolk, 171 77 Stockholm, Sweden
| | - Daniel D Buchanan
- Department of Clinical Pathology, University of Melbourne Center for Cancer Research, University of Melbourne, 305 Grattan Street, Melbourne, Victoria, 3010, Australia
| | - Robert C Grant
- UHN-Princess Margaret Cancer Centre, University of Toronto, 7-811 700 University Ave, Toronto, Ontario, M5G 1X6, Canada
| | - Stephanie L Schmit
- Genomic Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, Mail Code NE50, Cleveland, OH, 44195, USA
- Population and Cancer Prevention Program, Case Comprehensive Cancer Center, 10900 Euclid Ave, Cleveland, OH, 44106, USA
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street, Baltimore, MD, 21205, USA
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, 615 N Wolfe Street, Baltimore, MD, 21205, USA
| | - Corinne E Joshu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street, Baltimore, MD, 21205, USA
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, 615 N Wolfe Street, Baltimore, MD, 21205, USA
| | - David J Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill, 123 W Franklin Street, Suite 450, CB #8030, Chapel Hill, NC, 27516, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98019, USA
| | - Timothy K Starr
- Masonic Cancer Center, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
- Department of Obstetrics and Gynecology, Medical School, University of Minnesota, 515 Delaware St SE, Minneapolis, MN, 55455, USA
| | - Patricia Scott
- Masonic Cancer Center, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
- Department of Biomedical Sciences, University of Minnesota Medical School Duluth, 1035 University Drive, Duluth, MN, 55812, USA
| | - Nathan Pankratz
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| |
Collapse
|
17
|
Yang J, Bernard L, Chen J, Sullivan VK, Deal JA, Kim H, Yu B, Steffen LM, Rebholz CM. Plasma Proteins Associated with the Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) Diet and Incident Dementia. J Nutr 2025:S0022-3166(25)00167-1. [PMID: 40118346 DOI: 10.1016/j.tjnut.2025.03.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Revised: 01/22/2025] [Accepted: 03/10/2025] [Indexed: 03/23/2025] Open
Abstract
BACKGROUND The Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) diet slows cognitive decline and protects brain health, but the mechanisms are poorly understood. OBJECTIVES We aimed to determine the plasma proteins associated with the MIND diet score and their ability to predict incident dementia in the Atherosclerosis Risk in Communities study. METHODS We analyzed 10,230 Black and White participants at visit 3 (1993-1995) with food frequency questionnaire and proteomics data and randomly divided them into discovery (n = 6850) and replication (n = 3380) samples. We examined associations between the MIND diet score and 4955 proteins using multivariable linear regression and elastic net regression. C-statistics were calculated to assess if proteins improved the prediction of high MIND diet adherence beyond participant characteristics. Cox proportional hazards models were used to assess associations between significant diet-related proteins and incident dementia over 2 decades. C-statistics assessed the ability of significant proteins to improve dementia prediction beyond known risk factors. RESULTS Of 316 proteins associated with the MIND diet score in the discovery sample at a false discovery rate <0.05, 62 were internally replicated. Of these, 21 proteins selected by the elastic net individually improved MIND diet score prediction. After a median follow-up of 21 y, there were 2311 dementia cases. Five diet-related proteins, thrombospondin-2 [hazard ratio (HR): 1.19; 95% confidence interval (CI): 1.11, 1.29], protein ABHD14A (HR: 1.23; 95% CI: 1.11, 1.37), structural maintenance of chromosomes protein 3 (HR: 1.19; 95% CI: 1.08, 1.31), epidermal growth factor receptor (HR: 0.68; 95% CI: 0.53, 0.86), and interleukin-12 subunit beta (HR: 1.14; 95% CI: 1.05, 1.25) were significantly associated with incident dementia. All 5 proteins individually and together improved the prediction of dementia risk. CONCLUSIONS Using high-throughput proteomics, we identified candidate biomarkers of the MIND diet score and incident dementia, which are implicated in neural signaling, angiogenesis, and anti-inflammatory pathways.
Collapse
Affiliation(s)
- Jiaqi Yang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States
| | - Lauren Bernard
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States; School of Medicine, University of Maryland, Baltimore, MD, United States
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States
| | - Valerie K Sullivan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States
| | - Jennifer A Deal
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Hyunju Kim
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, United States
| | - Bing Yu
- Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, United States
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, United States
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, United States.
| |
Collapse
|
18
|
Bernard L, Yang J, Chen J, Sullivan VK, Yu B, Rhee EP, Welling PA, Rebholz CM. Serum Metabolomic Markers of Dietary Potassium and Risk of CKD. Clin J Am Soc Nephrol 2025:01277230-990000000-00567. [PMID: 40067387 DOI: 10.2215/cjn.0000000675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2024] [Accepted: 03/06/2025] [Indexed: 04/15/2025]
Abstract
Key Points
We identified metabolomic markers of dietary potassium and diet-related metabolites that were associated with incident CKD in US adults.These metabolites may be prioritized for elucidating mechanisms that could be modified by dietary strategies to prevent CKD.
Background
Discovering metabolomic markers of dietary potassium may help improve dietary assessment of potassium and trace the effect of dietary potassium on CKD development.
Methods
We included adults from the Atherosclerosis Risk in Communities study without CKD at visit 1 (N=3812). Cross-sectional associations between dietary potassium and serum metabolites were assessed using multivariable linear regression models. Cox regression models estimated hazard ratios for potassium-related metabolites and incident CKD. Incident CKD was defined as eGFR (<60 ml/min per 1.73 m2 and ≥25% decline), CKD-related hospitalization or death, or KRT identified using the United States Renal Data System registry from visit 1 (1987–1989) through December 31, 2020.
Results
There were 33 significant associations between dietary potassium and serum metabolites, including pyridoxate, N-methylproline, stachydrine, pantothenate, and scyllo-inositol. During more than two decades of follow-up (median: 23 years, 25th–75th percentile: 14–30), 1616 (42%) of participants developed incident CKD. Ten of the 33 potassium-related metabolites were significantly associated with incident CKD. Metabolites involved in phenylalanine and tyrosine metabolism—3-(4-hydroxyphenyl)lactate and 3-phenylpropionate—were significantly associated with dietary potassium and CKD. In addition, glycerate, involved in glucose metabolism, was positively associated with dietary potassium (β=0.09, P = 4.01×10−17) and inversely associated with CKD (hazard ratio, 0.77; 95% confidence interval, 0.69 to 0.85; P = 8.57×10−7). There was a significant trend for CKD risk across quartiles of 3-(4-hydroxyphenyl)lactate, 3-phenylpropionate, and glycerate.
Conclusions
Dietary potassium was associated with 33 serum metabolites. 3-(4-hydroxyphenyl)lactate 3-phenylpropionate and glycerate are candidate markers of dietary potassium's effect on CKD.
Collapse
Affiliation(s)
- Lauren Bernard
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
- School of Medicine, University of Maryland, Baltimore, Maryland
| | - Jiaqi Yang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Valerie K Sullivan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Bing Yu
- Department of Epidemiology, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas
| | - Eugene P Rhee
- Division of Nephrology and Endocrine Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Paul A Welling
- Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
- Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| |
Collapse
|
19
|
Pleasants H, Yuan Y, Chamberlin K, Li C, Couper D, Shrestha S, Kamath V, Deal JA, Mosley TH, Palta P, Pinto JM, Chen H, Kucharska-Newton A. Longitudinal Association of Olfactory Function with Frailty in Older Adults: The Atherosclerosis Risk in Communities Study. J Gerontol A Biol Sci Med Sci 2025; 80:glaf018. [PMID: 39886987 PMCID: PMC11949427 DOI: 10.1093/gerona/glaf018] [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: 09/09/2024] [Indexed: 02/01/2025] Open
Abstract
BACKGROUND Emerging evidence suggests that olfactory dysfunction may be a marker of frailty, a key predictor of adverse health outcomes in aging populations. This study examines the association between olfactory impairment and frailty in older adults. METHODS We analyzed data from 5,231 participants (mean age: 75.3 ± 5.0 years; 59% women; 22% Black) of the Atherosclerosis Risk in Communities (ARIC) Study. Olfactory function, assessed using the 12-item Sniffin' Sticks Test at Visit 5 (2011-2013), was categorized as poor (0-8), moderate (9-10), or good (11-12). Frailty status was ascertained using both the Fried Frailty Phenotype and the Cumulative Frailty Index. Cross-sectional associations between olfactory function and frailty status were examined using logistic regression and linear regression. Logistic regression was used to examine the association between olfactory function and prefrailty or frailty occurring within five years among 1,519 participants robust at baseline. RESULTS In cross-sectional analyses, good olfactory function was associated with lower odds of frailty (odds ratio [OR] = 0.29, 95% confidence interval [CI]: 0.22, 0.39) and prefrailty (OR = 0.52, 95% CI: 0.45, 0.61). These associations remained robust after adjusting for covariates. Longitudinal analyses similarly showed a dose-response pattern, with improved olfaction associated with decreased odds of experiencing prefrailty (OR=0.63 95% CI [0.48, 0.83]) or frailty (OR=0.50, 95% CI [0.25, 1.02]). CONCLUSIONS Good, as compared to poor, olfactory function is associated with lower frailty risk in older adults, suggesting that olfactory impairment may serve as an early marker of frailty. Further research is needed to elucidate the mechanisms linking olfaction and frailty and explore potential interventions.
Collapse
Affiliation(s)
- Hannah Pleasants
- Department of Epidemiology, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
| | - Yaqun Yuan
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, USA
| | - Keran Chamberlin
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, USA
| | - Chenxi Li
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, USA
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
| | - Srishti Shrestha
- The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Vidyulata Kamath
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Jennifer A Deal
- Department of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Thomas H Mosley
- The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Priya Palta
- Department of Neurology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA
| | - Jayant M Pinto
- Department of Surgery, University of Chicago, Chicago, Illinois, USA
| | - Honglei Chen
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, USA
| | - Anna Kucharska-Newton
- Department of Epidemiology, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
| |
Collapse
|
20
|
Springer MV, Whitney RT, Ye W, Briceño EM, Gross AL, Aparicio HJ, Beiser AS, Burke JF, Elkind MSV, Ferber RA, Giordani B, Gottesman RF, Hayward RA, Howard VJ, Kollipara AS, Koton S, Lazar RM, Longstreth WT, Pendlebury ST, Sussman JB, Thacker EL, Levine DA. Education Levels and Poststroke Cognitive Trajectories. JAMA Netw Open 2025; 8:e252002. [PMID: 40136300 PMCID: PMC11947833 DOI: 10.1001/jamanetworkopen.2025.2002] [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] [Received: 10/08/2024] [Accepted: 01/24/2025] [Indexed: 03/27/2025] Open
Abstract
Importance Acute stroke is associated with accelerated, years-long cognitive decline. Whether education levels are associated with faster cognitive decline after stroke is unclear. Objective To evaluate the association of education level with poststroke cognitive decline and to determine whether age at stroke modifies the association. Design, Setting, and Participants Individual participant data meta-analysis of 4 US cohort studies (January 1971 to December 2019). Analysis began August 2022 and was completed in January 2024. Exposures Education level (less than high school, completed high school, some college, and college graduate). Main Outcomes and Measures Harmonized cognitive outcomes were global cognition (primary outcome), memory, and executive function. Outcomes were standardized as t scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1-SD difference in cognition, with higher score representing better function. Linear mixed-effect models estimated the trajectory of cognitive decline after incident stroke. Results The analysis included 2019 initially dementia-free stroke survivors (1048 female [51.9%]; median [IQR] age at stroke, 74.8 [69.0-80.4] years; 339 with less than a high school education [16.7%]; 613 who completed high school [30.4%]; 484 with some college [24.0%]; 583 with a college degree or higher [28.9%]). Median (IQR) follow-up time after stroke was 4.1 (1.8-7.2) years. Compared with those with less than a high school degree, college graduates had higher initial poststroke performance in global cognition (1.09 points higher; 95% CI, 0.02 to 2.17 points higher), executive function (1.81 points higher; 95%CI, 0.38 to 3.24 points higher), and memory (0.99 points higher; 95% CI, 0.02 to 1.96 points higher). Compared with stroke survivors with less than a high school education, there was a faster decline in executive function among college graduates (-0.44 points/y faster; 95% CI, -0.69 to -0.18 points/y faster) and those with some college education(-0.30 points/y faster; 95% CI, -0.57 to -0.03 points/y faster). Education level was not associated with declines in global cognition or memory. Age did not modify the association of education with cognitive decline. Conclusions and Relevance In this pooled cohort study, the trajectory of cognitive decline after stroke varied by education level and cognitive domain, suggesting that stroke survivors with a higher education level may have greater cognitive reserve but steeper decline in executive function than those with a lower education level.
Collapse
Affiliation(s)
- Mellanie V. Springer
- Department of Neurology and Stroke Program, University of Michigan, Ann Arbor
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
| | - Rachael T. Whitney
- Department of Internal Medicine, University of Michigan, Ann Arbor
- Cognitive Health Services Research Program, University of Michigan, Ann Arbor
| | - Wen Ye
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor
| | - Emily M. Briceño
- Department of Neurology and Stroke Program, University of Michigan, Ann Arbor
- Department of Internal Medicine, University of Michigan, Ann Arbor
- Cognitive Health Services Research Program, University of Michigan, Ann Arbor
- Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor
| | - Alden L. Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Hugo J. Aparicio
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, Massachusetts
| | - Alexa S. Beiser
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - James F. Burke
- Department of Neurology, Ohio State University College of Medicine, Columbus
| | - Mitchell S. V. Elkind
- Department of Neurology, Vagelos College of Physicians and Surgeons , Columbia University, New York, New York
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | | | - Bruno Giordani
- Department of Psychiatry, Michigan Alzheimer’s Disease Center, University of Michigan, Ann Arbor
| | - Rebecca F. Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland
| | - Rodney A. Hayward
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Department of Internal Medicine, University of Michigan, Ann Arbor
- Cognitive Health Services Research Program, University of Michigan, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Virginia J. Howard
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health
| | - Adam S. Kollipara
- Department of Internal Medicine, University of Michigan, Ann Arbor
- Cognitive Health Services Research Program, University of Michigan, Ann Arbor
| | - Silvia Koton
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Nursing, The Stanley Steyer School of Health Professions, Tel Aviv University, Tel Aviv, Israel
| | - Ronald M. Lazar
- Department of Neurology, Evelyn F. McKnight Brain Institute, Heersink School of Medicine, University of Alabama at Birmingham
| | - W. T. Longstreth
- Department of Neurology, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
| | - Sarah T. Pendlebury
- Wolfson Centre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Department of Acute General Medicine, National Institute for Health and Care Research Oxford Biomedical Research Centre, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
- Department of Geratology, National Institute for Health and Care Research Oxford Biomedical Research Centre, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
| | - Jeremy B. Sussman
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Department of Internal Medicine, University of Michigan, Ann Arbor
- Cognitive Health Services Research Program, University of Michigan, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Evan L. Thacker
- Department of Public Health, Brigham Young University, Provo, Utah
| | - Deborah A. Levine
- Department of Neurology and Stroke Program, University of Michigan, Ann Arbor
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Department of Internal Medicine, University of Michigan, Ann Arbor
- Cognitive Health Services Research Program, University of Michigan, Ann Arbor
| |
Collapse
|
21
|
Giao DM, Col H, Larbi Kwapong F, Turkson-Ocran RA, Ngo LH, Cluett JL, Wagenknecht L, Windham BG, Selvin E, Lutsey PL, Juraschek SP. Supine Blood Pressure and Risk of Cardiovascular Disease and Mortality. JAMA Cardiol 2025; 10:265-275. [PMID: 39841470 PMCID: PMC11904725 DOI: 10.1001/jamacardio.2024.5213] [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: 01/23/2025]
Abstract
Importance Nocturnal hypertension while asleep is associated with substantial increases in risk of cardiovascular disease (CVD) and death. Whether hypertension while supine is a risk factor associated with CVD independent of seated hypertension remains unknown. Objective To investigate the association between supine hypertension and CVD outcomes and by hypertension treatment status. Design, Setting, and Participants This prospective cohort study used data from the Atherosclerosis Risk in Communities (ARIC) study, which was established in 1987 to examine cardiovascular risk factors among middle-aged adults from 4 communities in the US. Supine and seated blood pressure were measured in more than 13 000 middle-aged adults with longitudinal surveillance for CVD over 27 years. Participants with a history of coronary heart disease (CHD), heart failure, or stroke were excluded. Data were analyzed from May 2023 through December 2024. Exposures Supine hypertension (supine systolic blood pressure ≥130 or diastolic blood pressure ≥80 mm Hg) with and without seated hypertension (seated systolic blood pressure ≥130 or diastolic blood pressure ≥80 mm Hg). Main Outcomes and Measures Cox proportional hazard models with adjustment for CVD risk factors were performed to investigate the association of supine hypertension with and without seated hypertension with incident CHD, heart failure, stroke, fatal CHD, and all-cause mortality. Results Of 11 369 participants without known CVD (6332 female [55.7%] and 5037 male [44.3%]; 2858 Black [25.1%] and 8511 White [74.9%]; mean [SD] age 53.9 [5.7] years]), 16.4% (95% CI, 15.5%-17.2%) of those without seated hypertension had supine hypertension and 73.5% (95% CI, 72.2%-74.8%) of those with seated hypertension had supine hypertension. Supine hypertension was associated with incident CHD (hazard ratio [HR], 1.60; 95% CI, 1.45-1.76), heart failure (HR, 1.83; 95% CI, 1.68-2.01), stroke (HR, 1.86; 95% CI, 1.63-2.13), fatal CHD (HR, 2.18; 95% CI, 1.84-2.59), and all-cause mortality (HR, 1.43; 95% CI, 1.35-1.52) during a median (25th, 75th percentile) follow-up of 25.7 (15.4, 30.4) years, 26.9 (17.6, 30.5) years, 27.6 (18.5, 30.6 years), 28.3 (20.5, 30.7) years, and 28.3 (20.5 years, 30.7) years, respectively. There were no meaningful differences by seated hypertension status. Results were similar by hypertension medication use. Participants with supine hypertension alone had risk associations similar to those of participants with hypertension in both positions and significantly greater than those of participants with seated hypertension alone with the exception of fatal CHD; seated vs supine HRs were 0.72 (95% CI, 0.61-0.85) for CHD, 0.72 (95% CI, 0.60-0.85) for heart failure, 0.66 (95% CI, 0.51-0.86) for stroke, and 0.83 (95% CI, 0.74-0.92) for all-cause mortality. Conclusions and Relevance Supine hypertension regardless of seated hypertension had a higher HR for CVD risk than seated hypertension alone. Future research should evaluate supine hypertension in the setting of nocturnal hypertension and as an independent target of blood pressure treatment.
Collapse
Affiliation(s)
- Duc M Giao
- Harvard Medical School, Boston, Massachusetts
- Department of Cardiac Surgery, Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California
| | - Hannah Col
- Department of Medicine, Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Fredrick Larbi Kwapong
- Department of Medicine, Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Ruth-Alma Turkson-Ocran
- Department of Medicine, Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Long H Ngo
- Department of Medicine, Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Jennifer L Cluett
- Department of Medicine, Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Lynne Wagenknecht
- Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - B Gwen Windham
- Memory Impairment and Neurodegenerative Dementia Center, Department of Medicine, University of Mississippi Medical Center, Jackson
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis
| | - Stephen P Juraschek
- Department of Medicine, Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| |
Collapse
|
22
|
Begzati A, Godinez-Macias KP, Long T, Watrous JD, Moranchel R, Kantz ED, Tuomilehto J, Havulinna AS, Niiranen TJ, Jousilahti P, Salomaa V, Yu B, Norby F, Rebholz CM, Selvin E, Winzeler EA, Cheng S, Alotaibi M, Goyal R, Ideker T, Jain M, Majithia AR. Plasma Lipid Metabolites, Clinical Glycemic Predictors, and Incident Type 2 Diabetes. Diabetes Care 2025; 48:473-480. [PMID: 39761415 PMCID: PMC11870283 DOI: 10.2337/dc24-2266] [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: 10/16/2024] [Accepted: 12/12/2024] [Indexed: 03/03/2025]
Abstract
OBJECTIVE Plasma metabolite profiling has uncovered several nonglycemic markers of incident type 2 diabetes (T2D). We investigated whether such biomarkers provide information about specific aspects of T2D etiology, such as impaired fasting glucose and impaired glucose tolerance, and whether their association with T2D risk varies by race. RESEARCH DESIGN AND METHODS Untargeted plasma metabolite profiling was performed of participants in the FINRISK 2002 cohort (n = 7,564). Cox regression modeling was conducted to identify metabolites associated with incident T2D during 14 years of follow-up. Metabolites were clustered into pathways using Gaussian graphical modeling. Clusters enriched for T2D biomarkers were further examined for covariation with fasting plasma glucose (FPG), 2-h postchallenge plasma glucose (2hPG), HbA1c, or fasting insulin. Validation analyses and tests of interaction with race were performed in the Atherosclerosis Risk in Communities (ARIC) study. RESULTS Two clusters of metabolites, representing diacylglycerols (DAGs) and phosphatidylcholines (PCs), contained the largest number of metabolite associations with incident T2D. DAGs associated with increased T2D incidence (hazard ratio [HR] 1.22; 95% CI 1.14-1.30) independent of FPG, HbA1c, and fasting insulin, but not 2hPG. PCs were inversely associated with T2D risk (HR 0.78; 95% CI 0.71-0.85) independent of FPG, 2hPG, HbA1c, and fasting insulin. No significant interaction between DAGs or PCs and race was observed. CONCLUSIONS Fasting DAGs may capture information regarding T2D risk similar to that represented by 2hPG; PCs may capture aspects of T2D etiology that differ from those represented by conventional biomarkers. The direction of effect and strength of DAG and PC associations with incident T2D are similar across European and African Americans.
Collapse
Affiliation(s)
- Arjana Begzati
- Department of Medicine, University of California San Diego, La Jolla, CA
| | | | - Tao Long
- Department of Medicine, University of California San Diego, La Jolla, CA
- Sapient Bioanalytics, San Diego, CA
| | - Jeramie D. Watrous
- Department of Medicine, University of California San Diego, La Jolla, CA
- Sapient Bioanalytics, San Diego, CA
| | - Rafael Moranchel
- Department of Medicine, University of California San Diego, La Jolla, CA
- Sapient Bioanalytics, San Diego, CA
| | - Edward D. Kantz
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Jaakko Tuomilehto
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Aki S. Havulinna
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Computing, University of Turku, Turku, Finland
- Institute for Molecular Medicine Finland, FIMM-HiLIFE, Helsinki, Finland
| | - Teemu J. Niiranen
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Internal Medicine, University of Turku, Turku, Finland
| | - Pekka Jousilahti
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Bing Yu
- Department of Epidemiology, School of Public Health, University of Texas School of Public Health, Houston, TX
| | - Faye Norby
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN
| | - Casey M. Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | | | - Susan Cheng
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Mona Alotaibi
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Ravi Goyal
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Trey Ideker
- Department of Medicine, University of California San Diego, La Jolla, CA
| | - Mohit Jain
- Department of Medicine, University of California San Diego, La Jolla, CA
- Sapient Bioanalytics, San Diego, CA
| | - Amit R. Majithia
- Department of Medicine, University of California San Diego, La Jolla, CA
| |
Collapse
|
23
|
Fang M, Hu J, Weiss J, Knopman DS, Albert M, Windham BG, Walker KA, Sharrett AR, Gottesman RF, Lutsey PL, Mosley T, Selvin E, Coresh J. Lifetime risk and projected burden of dementia. Nat Med 2025; 31:772-776. [PMID: 39806070 DOI: 10.1038/s41591-024-03340-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Accepted: 10/03/2024] [Indexed: 01/16/2025]
Abstract
Understanding the lifetime risk of dementia can inform public health planning and improve patient engagement in prevention. Using data from a community-based, prospective cohort study (n = 15,043; 26.9% Black race, 55.1% women and 30.8% with at least one apolipoprotein E4 (APOE ε4) allele), we estimated the lifetime risk of dementia (from age 55 years to 95 years), with mortality treated as a competing event. We applied lifetime risk estimates to US Census projections to evaluate the annual number of incident dementia cases from 2020 to 2060. The lifetime risk of dementia after age 55 years was 42% (95% confidence interval: 41-43). Rates were substantially higher in women, Black adults and APOE ε4 carriers, with lifetime risks ranging from approximately 45% to 60% in these populations. The number of US adults who will develop dementia each year was projected to increase from approximately 514,000 in 2020 to approximately 1 million in 2060. The relative growth in new dementia cases was especially pronounced for Black adults. These results highlight the urgent need for policies that enhance healthy aging, with a focus on health equity.
Collapse
Affiliation(s)
- Michael Fang
- Department of Epidemiology, 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
- Institute for Hospital Management, Tsinghua University, Beijing, China
| | - Jordan Weiss
- Optimal Aging Institute and Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | | | - Marilyn Albert
- Department of Neurology, Johns Hopkins Medicine, Baltimore, MD, USA
| | - B Gwen Windham
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Keenan A Walker
- Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Rebecca F Gottesman
- Intramural Research Program, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Pamela L Lutsey
- Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Thomas Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Josef Coresh
- Optimal Aging Institute and Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA.
- Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
| |
Collapse
|
24
|
Shore S, Li H, Zhang M, Whitney R, Gross AL, Bhatt AS, Nallamothu BK, Giordani B, Briceño EM, Sussman JB, Gutierrez J, Yaffe K, Griswold M, Johansen MC, Lopez OL, Gottesman RF, Sidney S, Heckbert SR, Rundek T, Hughes TM, Longstreth WT, Levine DA. Trajectory of Cognitive Function After Incident Heart Failure. Circ Heart Fail 2025; 18:e011837. [PMID: 39963777 PMCID: PMC11992552 DOI: 10.1161/circheartfailure.124.011837] [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: 03/21/2024] [Accepted: 12/13/2024] [Indexed: 02/26/2025]
Abstract
BACKGROUND The magnitude of cognitive changes after incident heart failure (HF) is unclear. We assessed whether incident HF is associated with changes in cognition after accounting for pre-HF cognitive trajectories and known determinants of cognition. METHODS This pooled cohort study included adults without HF, stroke, or dementia from 6 US population-based studies from 1971 to 2019. Linear mixed-effects models estimated cognitive change with incident HF diagnosis and the rate of cognitive change over the years after HF, controlling for pre-HF cognitive trajectories and participant factors. Outcomes included change in global cognition (primary outcome), executive function, and memory (secondary outcomes). Cognitive outcomes were standardized to a t score metric (mean [SD], 50 [10]); a 1-point difference represented a 0.1-SD difference in cognition. RESULTS We included 29 614 adults (mean [SD] age was 61 [10] years, 55% female, 70% White). During a median follow-up of 6.6 (Q1-Q3, 5.0-19.8) years, 1407 (5%) adults received an incident diagnosis of HF. Incident HF diagnosis was associated with initial decreases in global cognition (-1.1 points [95% CI, -1.4 to -0.8]) and executive function (-0.6 points [95% CI, -1.0 to -0.3]). Larger decreases in global cognition after HF were seen with older age, female sex, and White race. Participants with incident HF diagnosis demonstrated faster and long-term declines in global cognition (-0.1 points per year [95% CI, -0.2 to -0.1]) and executive function (-0.2 points per year [95% CI, -0.2 to -0.1]). The change in memory with incident HF diagnosis was not statistically significant but showed a similar trend with an initial decline of -0.5 points (95% CI, -1.4 to +0.3) and a slope of -0.1 points per year (95% CI, -0.3 to 0.0). CONCLUSIONS In this pooled cohort study, incident HF diagnosis was associated with initial decreases in global cognition and executive function and faster, persistent declines in these domains at follow-up.
Collapse
Affiliation(s)
| | - Hanyu Li
- University of Michigan, Ann Arbor, MI, USA
| | - Min Zhang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | | | - Alden L. Gross
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ankeet S. Bhatt
- Kaiser Permanente San Francisco Medical Center and Division of Research, San Francisco, CA, USA
| | | | | | | | | | | | | | - Michael Griswold
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | | | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD, USA
| | - Stephen Sidney
- Kaiser Permanente San Francisco Medical Center and Division of Research, San Francisco, CA, USA
| | | | - Tatjana Rundek
- University of Miami – Miller School of Medicine, Evelyn F. McKnight Brain Institute, FL, USA
| | | | | | | |
Collapse
|
25
|
Abushamat LA, Jia X, Xu L, Cheng C, Ndumele CE, Sun C, Windham BG, Matsushita K, Yu B, Nambi V, Bozkurt B, Reusch JEB, Rebholz CM, Selvin E, Ballantyne CM, Hoogeveen RC. Does Adiponectin Inform Cardiovascular Risk in Older Adults?: The ARIC Study. JACC. ADVANCES 2025; 4:101625. [PMID: 39983616 PMCID: PMC11891717 DOI: 10.1016/j.jacadv.2025.101625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 01/07/2025] [Accepted: 01/17/2025] [Indexed: 02/23/2025]
Abstract
BACKGROUND Adiponectin, an atheroprotective adipokine, is associated with adverse outcomes in older age. It is unclear whether this is due to overlapping pathophysiological pathways with N-terminal pro-B-type natriuretic peptide (NT-proBNP). OBJECTIVES The authors investigated adiponectin's associations with cardiovascular disease (CVD) risk in older adults. METHODS Among Atherosclerosis Risk in Communities prospective cohort study participants without baseline CVD at visit 5 (n = 4,729, mean age 75), adiponectin and adiponectin/NT-proBNP category associations with incident CVD events (heart failure [HF], atherosclerotic cardiovascular disease, and death during median follow-up of 5.5 years) and echocardiographic parameters were assessed. Metabolomic signatures of adiponectin/NT-proBNP categories were explored. RESULTS Higher adiponectin was associated with older age, female sex, and less obesity, diabetes, and hypertension but increased risk for incident HF (HR: 1.91 [95% CI: 1.49-2.44], per natural-log unit increase) and CVD death (HR: 1.67 [95% CI: 1.19-2.32]). Interaction of NT-proBNP with adiponectin was significant for HF (P-interaction = 0.03). There was no significant association between adiponectin and heart failure with preserved ejection fraction after adjusting for NT-proBNP. Elevations of both biomarkers (A+ [upper tertile]/N+ [≥125 pg/mL]) had higher risk (vs A+/N-; HF: HR 5.41 [95% CI: 2.72-10.78]; CVD death: HR 3.50 [95% CI: 1.48-8.24]). Compared with A+/N-, A-/N+ had increased risk for HF (HR 2.84 [95% CI: 1.41-5.72]) while A-/N- had no increased event risk. A+/N+'s metabolomic signature (88% similar to NT-proBNP's) showed acylcarnitine species consistent with incomplete beta-oxidation; top-associated metabolites were significantly associated with HF and CVD death. CONCLUSIONS Elevated adiponectin and NT-proBNP in older adults are associated with increased risk for HF and CVD death beyond traditional risk factors.
Collapse
Affiliation(s)
- Layla A Abushamat
- Section of Cardiovascular Research, Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.
| | - Xiaoming Jia
- Section of Cardiovascular Research, Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA; Section of Cardiology, and Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Lu Xu
- Section of Cardiovascular Research, Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Chao Cheng
- Section of Epidemiology and Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Chiadi E Ndumele
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Caroline Sun
- Section of Cardiovascular Research, Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - B Gwen Windham
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Kunihiro Matsushita
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center, Houston, Texas, USA
| | - Vijay Nambi
- Section of Cardiovascular Research, Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA; Section of Cardiology, and Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA; Section of Cardiology, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
| | - Biykem Bozkurt
- Section of Cardiology, and Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA; Section of Cardiology, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA; Winters Center for Heart Failure Research, Baylor College of Medicine, Houston, Texas, USA
| | - Jane E B Reusch
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Christie M Ballantyne
- Section of Cardiovascular Research, Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA; Section of Cardiology, and Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Ron C Hoogeveen
- Section of Cardiovascular Research, Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| |
Collapse
|
26
|
Abushamat LA, Yu B, Hoogeveen RC, Sun C, Cheng C, Hartig SM, Herman MA, Balasubramanyam A, Reusch JE, Selvin E, Ndumele CE, Nambi V, Ballantyne CM. Erythritol, Erythronate, and Cardiovascular Outcomes in Older Adults in the ARIC Study. JACC. ADVANCES 2025; 4:101605. [PMID: 39983608 PMCID: PMC11889355 DOI: 10.1016/j.jacadv.2025.101605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2024] [Revised: 01/08/2025] [Accepted: 01/10/2025] [Indexed: 02/23/2025]
Abstract
BACKGROUND Circulating erythritol, an endogenously produced metabolite and an artificial sweetener, is associated with cardiovascular outcomes. OBJECTIVES The authors assessed associations of erythritol and its downstream metabolite, erythronate, with cardiovascular risk factors and events in older adults in the ARIC (Atherosclerosis Risk In Communities) study (visit 5, 2011-2013). METHODS We included 4,006 participants without prevalent cardiovascular disease and with metabolomic profiling. Erythritol and erythronate were measured by mass spectrometry. We analyzed associations of log-transformed erythritol and erythronate with cardiovascular risk factors and events using Cox proportional hazard models. RESULTS Participants in the highest tertiles of erythritol or erythronate were older, more likely to have diabetes, hypertension, hyperlipidemia, or microalbuminuria, and had higher body mass index and cardiac biomarkers and lower estimated glomerular filtration rate (P < 0.001). Over median follow-up of 8.41 (7.62, 8.93) years, higher erythritol and erythronate concentrations were significantly associated with heart failure (HF) hospitalization, HF with preserved ejection fraction, cardiovascular death, and total mortality after adjustment for demographics and traditional cardiovascular risk factors. Erythronate was additionally significantly associated with coronary heart disease (HR: 1.30 [95% CI: 1.04-1.61], P = 0.02), stroke (1.40 [95% CI: 1.08-1.83], P = 0.012), and HF with reduced ejection fraction (1.38 [95% CI: 1.09-1.74], P = 0.007). Diabetes status did not modify any of these associations (P for interaction >0.20). CONCLUSIONS Circulating erythritol and erythronate levels are markers of cardiometabolic health and cardiovascular outcomes in an older adult population. In particular, erythronate is associated with all cardiovascular outcomes assessed. Future studies should assess the role of erythronate and its related pathways in cardiovascular disease.
Collapse
Affiliation(s)
- Layla A Abushamat
- Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.
| | - Bing Yu
- Department of Epidemiology, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Ron C Hoogeveen
- Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Caroline Sun
- Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Chao Cheng
- Section of Epidemiology and Population Science, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Sean M Hartig
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Mark A Herman
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Ashok Balasubramanyam
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Jane Eb Reusch
- Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA; Rocky Mountain Regional VAMC, Aurora, Colorado, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Chiadi E Ndumele
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Vijay Nambi
- Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA; Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Christie M Ballantyne
- Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA; Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| |
Collapse
|
27
|
Ge X, Brittain B, Dawson L, Dwivedi G, Kaye DM, Morahan G. A Genetic Test to Identify People at High Risk of Heart Failure. Int J Mol Sci 2025; 26:1782. [PMID: 40004245 PMCID: PMC11855781 DOI: 10.3390/ijms26041782] [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: 12/19/2024] [Revised: 02/10/2025] [Accepted: 02/12/2025] [Indexed: 02/27/2025] Open
Abstract
Earlier intervention may delay or prevent heart failure (HF), a widespread health problem. However, it is not currently possible to identify those who are most at risk, especially before the appearance of any clinical signs. This study presents the development and subsequent validation of a novel genetic test for predicting the risk of HF, utilizing data from three independent cohorts of Australian and US subjects. We developed a first-phase test using the Baker Biobank case-control cohort, identifying 41 genetic variants indicative of HF risk through genome-wide interaction and association analyses. Subsequently, a second-phase test was designed. This identified 29 additional single-nucleotide polymorphisms. The combination of these two tests resulted in an aggregate test with a high predictive accuracy, achieving an Area Under the Curve of 0.93 and a balanced accuracy of 0.89. High genetic risk subjects in the Baker Biobank cohort had an odds ratio of 533.2. The test's robustness was validated by applying it to data from the Busselton Health Study and the Atherosclerosis Risk in Communities cohorts, yielding, respectively, Areas Under the Curve of 0.83 and 0.72, a balanced accuracy of 0.76 and 0.67, and Odds Ratios of 12.3 and 4.6. These results highlight the critical role of genetic factors in the development of heart failure and demonstrate this test's potential as a significant tool for clinical HF risk prediction.
Collapse
Affiliation(s)
- Xintian Ge
- Centre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia; (X.G.); (B.B.); (G.D.)
- Stroke Research Centre, Perron Institute for Neurological and Translational Science, Nedlands, WA 6009, Australia
| | - Bek Brittain
- Centre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia; (X.G.); (B.B.); (G.D.)
| | - Luke Dawson
- Heart Failure Research Group, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia; (L.D.); (D.M.K.)
| | - Girish Dwivedi
- Centre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia; (X.G.); (B.B.); (G.D.)
- Department of Cardiology, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | - David M. Kaye
- Heart Failure Research Group, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia; (L.D.); (D.M.K.)
| | - Grant Morahan
- Centre for Diabetes Research, Harry Perkins Institute of Medical Research, Nedlands, WA 6009, Australia; (X.G.); (B.B.); (G.D.)
- Advanced Genetic Diagnostics, Nedlands, WA 6009, Australia
| |
Collapse
|
28
|
Ji Y, Zhang MJ, Wang W, Norby FL, Eaton AA, Inciardi RM, Alonso A, Sedaghat S, Ganz P, Van’t Hof J, Solomon SD, Chaves PHM, Heckbert SR, Shah AM, Chen LY. Association of Coagulation Factor XI Level With Cardiovascular Events and Cardiac Function in Community-Dwelling Adults: From ARIC and CHS. Circulation 2025; 151:356-367. [PMID: 39569504 PMCID: PMC11810597 DOI: 10.1161/circulationaha.124.070278] [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: 04/27/2024] [Accepted: 10/15/2024] [Indexed: 11/22/2024]
Abstract
BACKGROUND Coagulation factor XI (FXI) inhibitors are a promising and novel class of anticoagulants, but a recent animal study found that FXI inhibition exacerbated diastolic dysfunction and heart failure (HF). In the ARIC study (Atherosclerosis Risk in Communities), we investigated whether plasma FXI level was associated with cardiovascular events and cardiac function. METHODS ARIC was our primary analytic cohort. We included 4471 participants (median age, 75 years; 57% female; 17% Black) who attended visit 5 (2011-2013) with Somalogic-quantified plasma FXI levels and echocardiographic cardiac function. Prevalent HF and atrial fibrillation (AF) cases were defined as having HF or AF diagnosed at or before each participant's visit 5 exam date. Incident HF and AF events were ascertained through 2021. Associations were assessed using Cox, logistic, and linear regression models. Primary prospective associations were also validated in the CHS (Cardiovascular Health Study) using an orthogonal FXI assay (enzyme-linked immunosorbent assay). RESULTS At ARIC visit 5, there were 665 and 419 participants with prevalent HF and AF, respectively. During a median follow-up of 9 years, there were 580 and 788 incident HF and AF events, respectively. Lower FXI level was associated prospectively with higher incidence of HF (hazard ratio [HR], 1.36 [for each 1-unit decrement of log2-transformed FXI level] [95% CI, 1.01-1.83]) but not incident AF, and cross-sectionally with increased odds of AF (odds ratio [OR], 1.96 [95% CI, 1.23-3.07]) but not HF. In age-stratified analyses, decreased FXI was associated with higher incidence of HF in participants ≥75 years of age (HR, 1.57 [95% CI, 1.08-2.28]) but not <75 years of age (HR, 1.11 [95% CI, 0.68-1.79]). The inverse FXI-HF association was validated in CHS (HR, 1.18 [95% CI, 1.02-1.36]). At ARIC visit 5, lower FXI level was also associated with higher prevalence of diastolic dysfunction and worse E/A ratio, left atrial (LA) volume index, LA function, and left ventricular mass index, but not left ventricular ejection fraction or global longitudinal strain. CONCLUSIONS Decreased FXI level is associated with greater incidence of HF, especially in older adults. It is also associated with prevalent AF, worse diastolic function, worse LA function, and greater LA size. More research is needed to assess potential unwanted effects of FXI inhibition on the risk of cardiovascular events and cardiac function.
Collapse
Affiliation(s)
- Yuekai Ji
- Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota
- Lillehei Heart Institute, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Michael J. Zhang
- Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota
- Lillehei Heart Institute, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Wendy Wang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Faye L. Norby
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Anne A. Eaton
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Riccardo M. Inciardi
- Institute of Cardiology, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Sanaz Sedaghat
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Peter Ganz
- Department of Medicine, University of California, San Francisco, CA
| | - Jeremy Van’t Hof
- Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota
- Lillehei Heart Institute, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Scott D. Solomon
- Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital, Boston, MA
| | - Paulo H. M. Chaves
- Benjamin Leon Center for Geriatric Research and Education, Department of Cellular and Molecular Medicine, Florida International University, Miami, FL
| | - Susan R. Heckbert
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA
| | - Amil M. Shah
- Division of Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, TX
| | - Lin Yee Chen
- Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota
- Lillehei Heart Institute, University of Minnesota Medical School, Minneapolis, Minnesota
| |
Collapse
|
29
|
Oelsner EC, Krishnaswamy A, Rustamov R, Balte PP, Ali T, Allen NB, Andrews HF, Anugu P, Arynchyn A, Bateman LA, Cai J, Chang H, Chen L, Elkind MSV, Floyd JS, Gabriel KP, Gharib SA, Gutierrez JD, Stukovsky KH, Howard VJ, Isasi CR, Jager L, Jin L, Judd SE, Kanaya AM, Kandula NR, Kelly MR, Khan SS, Kucharska-Newton A, Lee JS, Levitan EB, Lewis CE, Make BJ, Malloy K, Manly JJ, Mauger D, Min YI, Murabito JM, Murphy CG, Norwood AF, O’Connor GT, Ortega VE, Patel AA, Pirzada A, Regan EA, Ring KB, Rosamond WD, Schwartz DA, Shikany JM, Sotres-Alvarez D, Tarlton C, Tse J, Meneses EMU, Vankineni M, Wenzel SE, Woodruff PG, Xanthakis V, Yang JH, Zakai NA, Zhang Y, Post WS. Classifying COVID-19 hospitalizations in epidemiology cohort studies: The C4R study. PLoS One 2025; 20:e0316198. [PMID: 39928595 PMCID: PMC11809881 DOI: 10.1371/journal.pone.0316198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2024] [Accepted: 12/08/2024] [Indexed: 02/12/2025] Open
Abstract
RATIONALE Robust COVID-19 outcomes classification is important for ongoing epidemiology research on acute and post-acute COVID-19 conditions. Protocolized medical record review is an established method to validate endpoints for clinical trials and cardiovascular epidemiology cohorts; however, a protocol to adjudicate hospitalizations for COVID-19 among epidemiology cohorts was lacking. OBJECTIVES We developed a protocol to ascertain and adjudicate hospitalized COVID-19 across a meta-cohort of 14 US prospective cohort studies. This report describes the first three years of protocol implementation (October 1, 2020-October 1, 2023) and evaluates its repeatability and performance compared to classification by administrative codes. METHODS The protocol was adapted from cohort approaches to clinical cardiovascular events ascertainment and adjudication. Potential COVID-19 hospitalizations and deaths were identified by self-/proxy-report and, in some cases, active surveillance. Medical records were requested from hospitals and adjudicated for COVID-19 outcomes by clinically trained personnel according to a standardized rubric. Inter-rater agreement was assessed. The sensitivity and specificity of discharge diagnosis codes was compared to adjudicated diagnoses. MEASUREMENTS AND MAIN RESULTS The study obtained medical records for 1,167 potential COVID-19 hospitalizations, which underwent protocolized adjudication. Adjudication confirmed COVID-19 infection was present for 1,030 (88%) events, of which COVID-19 was not the cause of hospitalization for 78 (8%). Of 952 hospitalizations determined by adjudicators to be caused by COVID-19, 319 (34%) participants were critically ill and 210 (22%) died. Pneumonia was confirmed in 822 (86%) and acute kidney injury in 350 (37%); other cardiovascular and thrombotic complications were rare (2-5%). Interrater reliability among adjudicators was high (kappa = 0.85-1.00) except for myocardial infarction (kappa = 0.60). Compared to adjudication, sensitivity of discharge diagnosis codes was higher for pneumonia (84%) and pulmonary embolism (81%) than for other complications (48-70%). CONCLUSIONS Protocolized adjudication confirmed four out of five COVID-19 hospitalizations in a US meta-cohort and confirmed cases of pneumonia, pulmonary embolism, and other conditions that were not indicated by discharge diagnosis codes. These results highlight the importance of validating health outcomes for use in research on COVID-19 and post-COVID-19 conditions, and some limitations of claims-based data.
Collapse
Affiliation(s)
- Elizabeth C. Oelsner
- Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Akshaya Krishnaswamy
- Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Rafail Rustamov
- Department of Medicine, Nassau University Medical Center, East Meadow, New York, United States of America
| | - Pallavi P. Balte
- Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Tauqeer Ali
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Norrina B. Allen
- Center for Epidemiology and Population Health, Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Howard F. Andrews
- Data Coordinating Center and Biostatistics Department, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Pramod Anugu
- Department of Medicine University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Alexander Arynchyn
- Division of General Internal Medicine and Population Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Lori A. Bateman
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Jianwen Cai
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Harry Chang
- Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Lucas Chen
- NHLBI’s Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Mitchell S. V. Elkind
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, United States of America
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | - James S. Floyd
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, United States of America
- Division of General Medicine, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Kelley Pettee Gabriel
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Sina A. Gharib
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle, Washington, United States of America
| | - Jose D. Gutierrez
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, United States of America
| | - Karen Hinckley Stukovsky
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, United States of America
| | - Virginia J. Howard
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Carmen R. Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Lauren Jager
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, United States of America
| | - Ling Jin
- NHLBI’s Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Suzanne E. Judd
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Alka M. Kanaya
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Namratha R. Kandula
- Center for Epidemiology and Population Health, Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States of America
- Division of General Internal Medicine, Department of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Maureen R. Kelly
- Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Sadiya S. Khan
- Division of Cardiology, Department of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Anna Kucharska-Newton
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Joyce S. Lee
- Division of Pulmonary Sciences and Critical Care, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Emily B. Levitan
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Cora E. Lewis
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Barry J. Make
- Division of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, National Jewish Health, Denver, Colorado, United States of America
| | - Kimberly Malloy
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Jennifer J. Manly
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, United States of America
| | - David Mauger
- Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Pennsylvania State University, State College, Pennsylvania, United States of America
| | - Yuan-I Min
- Department of Medicine University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Joanne M. Murabito
- NHLBI’s Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts, United States of America
| | - Charles G. Murphy
- Division of Pulmonary Allergy, and Critical Care Medicine, Department of Medicine, Columbia University Medical Center, New York, New York, United States of America
| | - Arnita F. Norwood
- Department of Medicine University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - George T. O’Connor
- NHLBI’s Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts, United States of America
| | - Victor E. Ortega
- Division of Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Department of Medicine, Mayo Clinic Scottsdale, Scottsdale, Arizona, United States of America
| | - Ashmi A. Patel
- Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Amber Pirzada
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, Illinois, United States of America
| | - Elizabeth A. Regan
- Division of Rheumatology, Department of Medicine, National Jewish Health, Denver, Colorado, United States of America
| | - Kimberly B. Ring
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Wayne D. Rosamond
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - David A. Schwartz
- Division of Pulmonary Sciences and Critical Care, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - James M. Shikany
- Division of General Internal Medicine and Population Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Daniela Sotres-Alvarez
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Cheryl Tarlton
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Janis Tse
- NHLBI’s Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Elman M. Urbina Meneses
- Division of Pulmonary and Critical Care, Graduate School of Medicine, University of Tennessee, Knoxville, Tennessee, United States of America
| | - Maya Vankineni
- Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Sally E. Wenzel
- Department of Environmental and Occupational Health, School of Public Heath, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Prescott G. Woodruff
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Vanessa Xanthakis
- NHLBI’s Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, and Department of Biostatistics, School of Public Health, Boston University, Boston, Massachusetts, United States of America
| | - Ji Hyun Yang
- NHLBI’s Framingham Heart Study, Framingham, Massachusetts, United States of America
- Division of Cardiovascular Medicine, Department of Medicine, Lahey Hospital and Medical Center, Burlington, Massachusetts, United States of America
| | - Neil A. Zakai
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, United States of America
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, Vermont, United States of America
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Wendy S. Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
| |
Collapse
|
30
|
Jakubek YA, Ma X, Stilp AM, Yu F, Bacon J, Wong JW, Aguet F, Ardlie K, Arnett DK, Barnes K, Bis JC, Blackwell T, Becker LC, Boerwinkle E, Bowler RP, Budoff MJ, Carson AP, Chen J, Cho MH, Coresh J, Cox NJ, de Vries PS, DeMeo DL, Fardo DW, Fornage M, Guo X, Hall ME, Heard-Costa N, Hidalgo B, Irvin MR, Johnson AD, Jorgenson E, Kenny EE, Kessler MD, Levy D, Li Y, Lima JAC, Liu Y, Locke AE, Loos RJF, Machiela MJ, Mathias RA, Mitchell BD, Murabito JM, Mychaleckyj JC, North KE, Orchard P, Parker SCJ, Pershad Y, Peyser PA, Pratte KA, Psaty BM, Raffield LM, Redline S, Rich SS, Rotter JI, Shah SJ, Smith JA, Smith AP, Smith A, Taub MA, Tiwari HK, Tracy R, Tuftin B, Bick AG, Sankaran VG, Reiner AP, Scheet P, Auer PL. Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood. Am J Hum Genet 2025; 112:276-290. [PMID: 39809269 PMCID: PMC11866972 DOI: 10.1016/j.ajhg.2024.12.014] [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: 04/19/2024] [Revised: 12/12/2024] [Accepted: 12/13/2024] [Indexed: 01/16/2025] Open
Abstract
Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole-genome sequencing (WGS) of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. We show that haplotype-based calling methods can be used with WGS data to successfully identify mLOY events. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European (EUR) ancestry group compared to other ancestries. We identify multiple loci associated with mLOY susceptibility and show that subsets of human hematopoietic stem cells are enriched for the activity of mLOY susceptibility variants. Finally, we found that certain alleles on chromosome Y are more likely to be lost than others in detectable mLOY clones.
Collapse
Affiliation(s)
- Yasminka A Jakubek
- Department of Internal Medicine, University of Kentucky, Lexington, KY, USA
| | - Xiaolong Ma
- Division of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Fulong Yu
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
| | - Jason Bacon
- Department of Computer Science, Department of Biological Sciences, University of Wisconsin Milwaukee, Milwaukee, WI, USA
| | - Justin W Wong
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | | | | | - Kathleen Barnes
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, School of Medicine University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Tom Blackwell
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Lewis C Becker
- Department of Medicine, Division of Cardiology, Johns Hopkins Hospital, Johns Hopkins University of Medicine, Baltimore, MD, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Matthew J Budoff
- Department of Medicine, Division of Cardiology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Josef Coresh
- NYU Grossman School of Medicine, NYU Langone Health, New York, NY, USA
| | - Nancy J Cox
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - David W Fardo
- Department of Biostatistics, University of Kentucky, Lexington, KY, USA
| | - Myriam Fornage
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Michael E Hall
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Nancy Heard-Costa
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Bertha Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Marguerite Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Andrew D Johnson
- Framingham Heart Study, Framingham, MA, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yun Li
- Department of Biostatistics, Department of Genetics, Department of Computer Science, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Joao A C Lima
- Department of Medicine, Division of Cardiology, Johns Hopkins Hospital, Johns Hopkins University of Medicine, Baltimore, MD, USA
| | - Yongmei Liu
- Duke University School of Medicine, Durham, NC, USA
| | | | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Rasika A Mathias
- Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland Baltimore, Baltimore, MD, USA
| | - Joanne M Murabito
- Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Stephen C J Parker
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Yash Pershad
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | | | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, Department of Epidemiology, Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Susan Redline
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Sanjiv J Shah
- Department of Medicine, Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA; Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, USA
| | - Aaron P Smith
- Institute for Biomedical Informatics, University of Kentucky, Lexington, KY, USA
| | - Albert Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Margaret A Taub
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Russell Tracy
- Departments of Pathology & Laboratory Medicine and Biochemistry, Larner College of Medicine at the University of Vermont, Colchester, VT, USA
| | - Bjoernar Tuftin
- Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Alexander G Bick
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Howard Hughes Medical Institute, Boston, MA, USA
| | | | - Paul Scheet
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Paul L Auer
- Division of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, WI, USA; Cancer Center, Medical College of Wisconsin, Milwaukee, WI, USA.
| |
Collapse
|
31
|
Molinsky RL, Shah A, Yuzefpolskaya M, Yu B, Misialek JR, Bohn B, Vock D, MacLehose R, Borlaug BA, Colombo PC, Ndumele CE, Ishigami J, Matsushita K, Lutsey PL, Demmer RT. Infection-Related Hospitalization and Incident Heart Failure: The Atherosclerosis Risk in Communities Study. J Am Heart Assoc 2025; 14:e033877. [PMID: 39883116 DOI: 10.1161/jaha.123.033877] [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: 12/11/2023] [Accepted: 12/03/2024] [Indexed: 01/31/2025]
Abstract
BACKGROUND The immune response to infections may become dysregulated and promote myocardial damage contributing to heart failure (HF). We examined the relationship between infection-related hospitalization (IRH) and HF, HF with preserved ejection fraction, and HF with reduced ejection fraction. METHODS AND RESULTS We studied 14 468 adults aged 45 to 64 years in the ARIC (Atherosclerosis Risk in Communities) Study who were HF free at visit 1 (1987-1989). IRH was identified using select International Classification of Diseases (ICD) codes in hospital discharge records and was treated as a time-varying exposure. HF incidence was defined as the first occurrence of either a hospitalization that included an ICD, Ninth Revision (ICD-9) discharge code of 428 (428.0-428.9) among the primary or secondary diagnoses or a death certificate with an ICD-9 code of 428 or an ICD, Tenth Revision (ICD-10) code of I50 among any of the listed diagnoses or underlying causes of death. We used multivariable-adjusted Cox proportional hazards models to assess the association between IRH and incident HF, HF with reduced ejection fraction, and HF with preserved ejection fraction. Median follow-up time was 27 years, 55% were women, 26% were Black, mean age at baseline was 54±6 years, 46% had an IRH, and 3565 had incident HF. Hazard ratio (HR) for incident HF events among participants who had an IRH compared with those who did not was 2.35 (95% CI, 2.19-2.52). This relationship was consistent across different types of infections. Additionally, IRH was associated with both HF with reduced ejection fraction and HF with preserved ejection fraction: 1.77 (95% CI, 1.35-2.32) and 2.97 (95% CI, 2.36-3.75), respectively. CONCLUSIONS IRH was associated with incident HF, HF with reduced ejection fraction, and HF with preserved ejection fraction. IRH might represent a modifiable risk factor for HF pathophysiology.
Collapse
Affiliation(s)
- Rebecca L Molinsky
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN USA
| | - Amil Shah
- Cardiovascular Imaging Program, Departments of Medicine and Radiology Brigham and Women's Hospital, Harvard Medical School Boston MA USA
| | - Melana Yuzefpolskaya
- Division of Cardiology, Department of Medicine Columbia University Irving Medical Center New York NY USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health University of Texas Health Science Center at Houston Houston TX USA
| | - Jeffrey R Misialek
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN USA
| | - Bruno Bohn
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN USA
| | - David Vock
- Division of Biostatistics, School of Public Health University of Minnesota Minneapolis MN USA
| | - Richard MacLehose
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN USA
| | - Barry A Borlaug
- Department of Cardiovascular Medicine Mayo Clinic College of Medicine and Science Rochester MN USA
| | - Paolo C Colombo
- Division of Cardiology, Department of Medicine Columbia University Irving Medical Center New York NY USA
| | - Chiadi E Ndumele
- Johns Hopkins Ciccarone Center for the Prevention of Heart Disease Johns Hopkins University School of Medicine Baltimore MD USA
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research Johns Hopkins Bloomberg School of Public Health Baltimore MD USA
| | - Junichi Ishigami
- Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University Baltimore MD USA
- Welch Center for Prevention, Epidemiology, and Clinical Research Johns Hopkins University Baltimore MD USA
| | - Kunihiro Matsushita
- Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University Baltimore MD USA
- Welch Center for Prevention, Epidemiology, and Clinical Research Johns Hopkins University Baltimore MD USA
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN USA
| | - Ryan T Demmer
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN USA
- Division of Epidemiology, Department of Quantitative Health Sciences Mayo Clinic College of Medicine and Science Rochester MN USA
| |
Collapse
|
32
|
Zhang M, Ru M, Zhang J, Wang Z, Lu J, Butler KR, Chatterjee N, Couper DJ, Prizment AE, Soori MM, Visvanathan K, Zahnow CA, Joshu CE, Platz EA. Alcohol Consumption Does not Modify the Polygenic Risk Score-Based Genetic Risk of Breast Cancer in Postmenopausal Women: Atherosclerosis Risk in Communities Study. Cancer Prev Res (Phila) 2025; 18:73-83. [PMID: 39676351 PMCID: PMC11790378 DOI: 10.1158/1940-6207.capr-24-0208] [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: 05/07/2024] [Revised: 10/31/2024] [Accepted: 12/12/2024] [Indexed: 12/17/2024]
Abstract
High genetic risk and alcohol consumption ≥1 drink/day are associated with increased breast cancer risk. However, the interaction between alcohol and genetics on breast cancer risk is poorly understood, including in populations not enriched with daily drinkers. We prospectively studied 5,651 White and Black postmenopausal women in the Atherosclerosis Risk in Communities study. Alcohol intake was assessed by a food frequency questionnaire. The 313-SNP polygenic risk score (PRS) was calculated. Breast cancer cases were ascertained primarily by cancer registry linkage through 2015. Multivariable Cox regression was used to estimate HRs and 95% confidence intervals (CI) for the association of PRS and current ethanol intake with breast cancer, and their interaction. Of these individuals, 50.6% were current drinkers, and of them, 50.8% drank <1 drink/week and 12.8% drank >7 drinks/week. A higher PRS was associated with a higher breast cancer risk among White (HR1-SD, 1.48; 95% CI, 1.34-1.65) and Black (HR1-SD, 1.15; 95% CI, 0.96-1.38) women. Positive associations were not observed between current ethanol intake and breast cancer risk (White: HR13 g/week, 1.00; 95% CI, 0.98-1.03; Black: HR, 0.83; 95% CI, 0.69-1.00). Among both White and Black women, PRS generally seemed to be positively associated with risk in drinkers and nondrinkers. There was no evidence of a PRS-ethanol intake interaction among White or Black women. Patterns in Black women were similar when using an 89-SNP PRS developed among African ancestry women. In conclusion, in a prospective analysis of White and Black postmenopausal women in a study population not enriched with daily drinkers, our findings suggest that alcohol drinking does not modify the PRS-based genetic risk of breast cancer. Prevention Relevance: Although our findings suggest that alcohol drinking does not modify the PRS-based genetic risk of breast cancer among White and Black women with lower alcohol intake, nevertheless, women should consider limiting alcohol consumption as a general cancer prevention strategy, as indicated in dietary guidelines.
Collapse
Affiliation(s)
- Minghui Zhang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Meng Ru
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Jingning Zhang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Ziqiao Wang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Jiayun Lu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Kenneth R. Butler
- Department of Medicine: Division of Geriatrics, School of Medicine, University of Mississippi Medical Center, Jackson, MS
| | - 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
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD
| | - David J. Couper
- University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Anna E. Prizment
- Department of Laboratory Medicine & Pathology, University of Minnesota Medical School, and the University of Minnesota Masonic Cancer Center, Minneapolis, MN
| | - Mehrnoosh M. Soori
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Kala Visvanathan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD
| | - Cynthia A. Zahnow
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD
| | - Corinne E. Joshu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD
| |
Collapse
|
33
|
Chamberlin KW, Li C, Kucharska-Newton A, Luo Z, Reeves M, Shrestha S, Pinto JM, Deal JA, Kamath V, Palta P, Couper D, Mosley TH, Chen H. Poor Olfaction and Risk of Stroke in Older Adults: The Atherosclerosis Risk in Communities Study. Stroke 2025; 56:465-474. [PMID: 39869711 PMCID: PMC11774471 DOI: 10.1161/strokeaha.124.048713] [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: 07/26/2024] [Revised: 10/17/2024] [Accepted: 10/31/2024] [Indexed: 01/29/2025]
Abstract
BACKGROUND Poor olfaction may be associated with adverse cerebrovascular events, but empirical evidence is limited. We aimed to investigate the association of olfaction with the risk of stroke in the Atherosclerosis Risk in Communities Study. METHODS We included 5799 older adults with no history of stroke at baseline from 2011 to 2013 (75.5±5.1 years, 59.0% female and 22.2% Black). Olfaction was assessed by the 12-item Sniffin' Sticks odor identification test and defined as poor (number correct ≤8), moderate (9-10), or good (11-12). Participants were followed from baseline to the date of the first stroke, death, last contact, or December 31, 2020, whichever occurred first. We used the discrete-time subdistribution hazard model to estimate the marginal cumulative incidence of stroke across olfactory statuses and adjusted risk ratios, accounting for covariates and competing risk of death. RESULTS After up to 9.6 years of follow-up, we identified 332 incident stroke events. The adjusted marginal cumulative incidence of stroke at 9.6-year follow-up was 5.3% (95% CI, 4.2%-6.3%), 5.9% (95% CI, 4.8%-7.1%), and 7.7% (95% CI, 6.5%-9.1%) for good, moderate, and poor olfaction, respectively. Compared with good olfaction, poor olfaction was significantly associated with higher stroke risk throughout follow-up, albeit the association modestly attenuated after 6 years. Specifically, the adjusted risk ratios were 2.14 (95% CI, 1.22-3.94) at year 2, 1.98 (95% CI, 1.43-3.02) at year 4, 1.91 (95% CI, 1.43-2.77) at year 6, 1.49 (95% CI, 1.17-2.00) at year 8, and 1.45 (95% CI, 1.16-1.95) at year 9.6. Results were robust in multiple subgroup and sensitivity analyses. CONCLUSIONS In older adults, poor olfaction assessed by a single olfaction test was associated with the higher risk of stroke in the next 10 years.
Collapse
Affiliation(s)
- Keran W. Chamberlin
- Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Chenxi Li
- Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Anna Kucharska-Newton
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zhehui Luo
- Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Mathew Reeves
- Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Srishti Shrestha
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jayant M. Pinto
- Section of Otolaryngology-Head and Neck Surgery, Department of Surgery, The University of Chicago Medicine and Biological Sciences, Chicago, IL, USA
| | - Jennifer A. Deal
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Vidyulata Kamath
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Priya Palta
- Department of Neurology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Thomas H. Mosley
- The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Honglei Chen
- Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| |
Collapse
|
34
|
Tokodi M, Shah R, Jamthikar A, Craig N, Hamirani Y, Casaclang-Verzosa G, Hahn RT, Dweck MR, Pibarot P, Yanamala N, Sengupta PP. Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis. JACC Cardiovasc Imaging 2025; 18:150-165. [PMID: 39297852 DOI: 10.1016/j.jcmg.2024.07.017] [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: 08/11/2023] [Revised: 05/19/2024] [Accepted: 07/19/2024] [Indexed: 02/07/2025]
Abstract
BACKGROUND The development and progression of aortic stenosis (AS) from aortic valve (AV) sclerosis is highly variable and difficult to predict. OBJECTIVES The authors investigated whether a previously validated echocardiography-based deep learning (DL) model assessing diastolic dysfunction (DD) could identify the latent risk associated with the development and progression of AS. METHODS The authors evaluated 898 participants with AV sclerosis from the ARIC (Atherosclerosis Risk In Communities) cohort study and associated the DL-predicted probability of DD with 2 endpoints: 1) the new diagnosis of AS; and 2) the composite of subsequent mortality or AV interventions. Validation was performed in 2 additional cohorts: 1) in 50 patients with mild-to-moderate AS undergoing cardiac magnetic resonance (CMR) imaging and serial echocardiographic assessments; and 2) in 18 patients with AV sclerosis undergoing 18F-sodium fluoride (NaF) and 18F-fluorodeoxyglucose positron emission tomography (PET) combined with computed tomography (CT) to assess valvular inflammation and calcification. RESULTS In the ARIC cohort, a higher DL-predicted probability of DD was associated with the development of AS (adjusted HR: 3.482 [95% CI: 2.061-5.884]; P < 0.001) and subsequent mortality or AV interventions (adjusted HR: 7.033 [95% CI: 3.036-16.290]; P < 0.001). The multivariable Cox model (incorporating the DL-predicted probability of DD) derived from the ARIC cohort efficiently predicted the progression of AS (C-index: 0.798 [95% CI: 0.648-0.948]) in the CMR cohort. Moreover, the predictions of this multivariable Cox model correlated positively with valvular 18F-NaF mean standardized uptake values in the PET/CT cohort (r = 0.62; P = 0.008). CONCLUSIONS Assessment of DD using DL can stratify the latent risk associated with the progression of early-stage AS.
Collapse
Affiliation(s)
- Márton Tokodi
- Division of Cardiovascular Diseases and Hypertension, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA; Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Rohan Shah
- Division of General Internal Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
| | - Ankush Jamthikar
- Division of Cardiovascular Diseases and Hypertension, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
| | - Neil Craig
- Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Yasmin Hamirani
- Division of Cardiovascular Diseases and Hypertension, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
| | - Grace Casaclang-Verzosa
- Division of Cardiovascular Diseases and Hypertension, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
| | - Rebecca T Hahn
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA; Cardiovascular Research Foundation, New York, New York, USA
| | - Marc R Dweck
- Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Philippe Pibarot
- Québec Department of Medicine, Heart and Lung Institute, Laval University, Québec City, Québec, Canada
| | - Naveena Yanamala
- Division of Cardiovascular Diseases and Hypertension, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA; Institute for Software Research, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Partho P Sengupta
- Division of Cardiovascular Diseases and Hypertension, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.
| |
Collapse
|
35
|
Dooley SW, Kwapong FL, Col H, Turkson-Ocran RAN, Ngo LH, Cluett JL, Mukamal KJ, Lipsitz LA, Zhang M, Daya NR, Selvin E, Lutsey PL, Coresh J, Windham BG, Wagenknecht L, Juraschek SP. Orthostatic and Standing Hypertension and Risk of Cardiovascular Disease. Hypertension 2025; 82:382-392. [PMID: 39633562 PMCID: PMC11781805 DOI: 10.1161/hypertensionaha.124.23409] [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: 05/28/2024] [Accepted: 11/04/2024] [Indexed: 12/07/2024]
Abstract
BACKGROUND Orthostatic hypertension is an emerging risk factor for adverse events. Recent consensus statements combine an increase in blood pressure upon standing with standing hypertension, but whether these 2 components have similar risk associations with cardiovascular disease (CVD) is unknown. METHODS The ARIC study (Atherosclerosis Risk in Communities) measured supine and standing blood pressure during visit 1 (1987-1989). We defined systolic orthostatic increase (a rise in systolic blood pressure [SBP] ≥20 mm Hg, standing minus supine blood pressure) and elevated standing SBP (standing SBP ≥140 mm Hg) to examine the new consensus statement definition (rise in SBP ≥20 mm Hg and standing SBP ≥140 mm Hg). We used Cox regression to examine associations with incident coronary heart disease, heart failure, stroke, fatal coronary heart disease, and all-cause mortality. RESULTS Of 11 369 participants (56% female; 25% Black adults; mean age, 54 years) without CVD at baseline, 1.8% had systolic orthostatic increases, 20.1% had standing SBP ≥140 mm Hg, and 1.3% had systolic orthostatic increases with standing SBP ≥140 mm Hg. During up to 30 years of follow-up, orthostatic increases were not significantly associated with any of the adverse outcomes of interest, while standing SBP ≥140 mm Hg was significantly associated with all end points. In joint models comparing systolic orthostatic increases and standing SBP ≥140 mm Hg, standing SBP ≥140 mm Hg was significantly associated with a higher risk of CVD, and associations differed significantly from systolic orthostatic increases. CONCLUSIONS Unlike systolic orthostatic increases, standing SBP ≥140 mm Hg was strongly associated with CVD outcomes and death. These differences in CVD risk raise important concerns about combining systolic orthostatic increases and standing SBP ≥140 mm Hg in a consensus definition for orthostatic hypertension.
Collapse
Affiliation(s)
- Sean W. Dooley
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Hannah Col
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Ruth-Alma N. Turkson-Ocran
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School; Boston, MA
| | - Long H. Ngo
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School; Boston, MA
| | - Jennifer L. Cluett
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Kenneth J. Mukamal
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School; Boston, MA
| | - Lewis A. Lipsitz
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Hebrew SeniorLife Marcus Center
| | - Mingyu Zhang
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School; Boston, MA
| | - Natalie R. Daya
- Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland
| | | | - Josef Coresh
- New York University, Grossman School of Medicine
| | | | | | - Stephen P. Juraschek
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School; Boston, MA
| |
Collapse
|
36
|
Duggan MR, Paterson C, Lu Y, Biegel H, Dark HE, Cordon J, Bilgel M, Kaneko N, Shibayama M, Kato S, Furuichi M, Waga I, Hiraga K, Katsuno M, Nishita Y, Otsuka R, Davatzikos C, Erus G, Loupy K, Simpson M, Lewis A, Moghekar A, Palta P, Gottesman RF, Resnick SM, Coresh J, Williams SA, Walker KA. The Dementia SomaSignal Test (dSST): A plasma proteomic predictor of 20-year dementia risk. Alzheimers Dement 2025; 21:e14549. [PMID: 39936291 PMCID: PMC11851157 DOI: 10.1002/alz.14549] [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: 06/24/2024] [Revised: 12/21/2024] [Accepted: 12/23/2024] [Indexed: 02/13/2025]
Abstract
INTRODUCTION There is an unmet need for tools to quantify dementia risk during its multi-decade preclinical/prodromal phase, given that current biomarkers predict risk over shorter follow-up periods and are specific to Alzheimer's disease. METHODS Using high-throughput proteomic assays and machine learning techniques in the Atherosclerosis Risk in Communities study (n = 11,277), we developed the Dementia SomaSignal Test (dSST). RESULTS In addition to outperforming existing plasma biomarkers, the dSST predicted mid-life dementia risk over a 20-year follow-up across two independent cohorts with different ethnic backgrounds (areas under the curve [AUCs]: dSST 0.68-0.70, dSST+age 0.75-0.81). In a separate cohort, the dSST was associated with longitudinal declines across multiple cognitive domains, accelerated brain atrophy, and elevated measures of neuropathology (as evidenced by positron emission tomography and plasma biomarkers). DISCUSSION The dSST is a cost-effective, scalable, and minimally invasive protein-based prognostic aid that can quantify risk up to two decades before dementia onset. HIGHLIGHTS The Dementia SomaSignal Test (dSST) predicts 20-year dementia risk across two independent cohorts. dSST outperforms existing plasma biomarkers in predicting multi-decade dementia risk. dSST predicts cognitive decline and accelerated brain atrophy in a third cohort. dSST is a prognostic aid that can predict dementia risk over two decades.
Collapse
Grants
- U01HL096812 NHLBI, NIA, NINDS, NIDCD
- U01 HL096812 NHLBI NIH HHS
- 75N92022D00002 NHLBI NIH HHS
- U01 HL096917 NHLBI NIH HHS
- U01 HL096902 NHLBI NIH HHS
- U01HL096902 NHLBI, NIA, NINDS, NIDCD
- 75N92022D00004 NHLBI NIH HHS
- U01HL096917 NHLBI, NIA, NINDS, NIDCD
- U01HL096814 NHLBI, NIA, NINDS, NIDCD
- U01 HL096814 NHLBI NIH HHS
- 75N92022D00003 NHLBI NIH HHS
- 75N92022D00005 NHLBI NIH HHS
- Intramural Research Program (IRP) of the National Institute on Aging (NIA)
- 75N92022D00001 NHLBI NIH HHS
- National Center for Geriatrics and Gerontology
- Nagoya University
- U01HL096899 NHLBI, NIA, NINDS, NIDCD
- NEC Solution Innovators Limited
- U01 HL096899 NHLBI NIH HHS
- National Center for Geriatrics and Gerontology
- Nagoya University
Collapse
Affiliation(s)
- Michael R. Duggan
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Clare Paterson
- Department of Clinical and Research DevelopmentStandard BioToolsBoulderColoradoUSA
| | - Yifei Lu
- Department of EpidemiologyUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Hannah Biegel
- Department of Clinical and Research DevelopmentStandard BioToolsBoulderColoradoUSA
| | - Heather E. Dark
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Jenifer Cordon
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Murat Bilgel
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Naoto Kaneko
- Innovation LaboratoryNEC Solution Innovators Limited, TokyoKoto‐kuJapan
| | - Masaki Shibayama
- Innovation LaboratoryNEC Solution Innovators Limited, TokyoKoto‐kuJapan
| | - Shintaro Kato
- Innovation LaboratoryNEC Solution Innovators Limited, TokyoKoto‐kuJapan
- FonesLife Proteomics LaboratoryFonesLife Corporation, Chuo CityTokyoJapan
| | - Makio Furuichi
- Innovation LaboratoryNEC Solution Innovators Limited, TokyoKoto‐kuJapan
- FonesLife Proteomics LaboratoryFonesLife Corporation, Chuo CityTokyoJapan
| | - Iwao Waga
- Innovation LaboratoryNEC Solution Innovators Limited, TokyoKoto‐kuJapan
- FonesLife Proteomics LaboratoryFonesLife Corporation, Chuo CityTokyoJapan
- Well‐being Design Institute for HealthTohoku UniversityAoba‐kuSendaiJapan
| | - Keita Hiraga
- Department of NeurologyNagoya University Graduate School of MedicineNagoyaAichiJapan
| | - Masahisa Katsuno
- Department of NeurologyNagoya University Graduate School of MedicineNagoyaAichiJapan
- Department of Clinical Research EducationNagoya University Graduate School of MedicineNagoyaAichiJapan
| | - Yukiko Nishita
- Department of Epidemiology of AgingNational Center for Geriatrics and GerontologyObuAichiJapan
| | - Rei Otsuka
- Department of Epidemiology of AgingNational Center for Geriatrics and GerontologyObuAichiJapan
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging LaboratoryPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Guray Erus
- Artificial Intelligence in Biomedical Imaging LaboratoryPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Kelsey Loupy
- Department of Clinical and Research DevelopmentStandard BioToolsBoulderColoradoUSA
| | - Melissa Simpson
- Department of Clinical and Research DevelopmentStandard BioToolsBoulderColoradoUSA
| | - Alexandria Lewis
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Abhay Moghekar
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Priya Palta
- Department of NeurologyUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Rebecca F. Gottesman
- Stroke BranchNational Institute of Neurological Disorders and StrokeBethesdaMarylandUSA
| | - Susan M. Resnick
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Josef Coresh
- Departments of Population Health and MedicineNew York University Grossman School of MedicineNew YorkNew YorkUSA
| | - Stephen A. Williams
- Department of Clinical and Research DevelopmentStandard BioToolsBoulderColoradoUSA
| | - Keenan A. Walker
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| |
Collapse
|
37
|
Shrestha S, Zhu X, Kucharska‐Newton AM, Yuan Y, Kamath V, Palta P, Deal JA, Mosley TH, Griswold ME, Chen H. Characterizing the olfaction and dementia association in the community-based ARIC study. Alzheimers Dement 2025; 21:e14613. [PMID: 39988999 PMCID: PMC11847982 DOI: 10.1002/alz.14613] [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: 09/16/2024] [Revised: 01/17/2025] [Accepted: 01/17/2025] [Indexed: 02/25/2025]
Abstract
INTRODUCTION Few studies have characterized the association of olfaction with dementia in detail across diverse sociodemographic subgroups. METHODS We examined the association of one-time-point olfactory status with incident dementia overall and by age, race, sex, and apolipoprotein E (APOE) ε4 status (n = 4470, mean age: 75 ± 5 years, 21% Black), and 5-year olfactory change with incident dementia (n = 2658) in the community-based Atherosclerosis Risk in Communities (ARIC) study. RESULTS Compared to good olfaction, moderate olfaction (hazard ratio [HR]: 1.53, 95% confidence interval [CI]: 1.26 to 1.86), hyposmia (HR: 2.24, 95% CI: 1.81 to 2.78), and anosmia (HR: 3.47, 95% CI: 2.77 to 4.34) were all associated with higher dementia hazard; these associations were consistent across age, race, sex, and APOE ε4 groups. The absolute risk difference between anosmia and good olfaction was higher in APOE ε4 carriers than in non-carriers. Those with stable anosmia and converting from normal olfaction to anosmia over time showed particularly strong associations. DISCUSSION Olfactory impairment was robustly associated with incident dementia, with strongest associations in those with persistent impairment and greater olfactory decline over ∼5 years. HIGHLIGHTS We examined olfactory status and olfactory change in relation to incident dementia. Poor olfactory status was robustly associated with higher dementia rate. Associations were robust across subgroups of age, sex, race, and APOE ε4 status. Persistent poor olfaction or decline over time showed the strongest associations.
Collapse
Grants
- U01HL096917 ARIC Neurocognitive Study grants, National Heart, Lung, and Blood Institute; National Institute of Neurological Disorders and Stroke; National Institute on Aging; and National Institute on Deafness and Other Communication Disorders
- U01 HL096812 NHLBI NIH HHS
- R01 AG064093 NIA NIH HHS
- U01HL096902 ARIC Neurocognitive Study grants, National Heart, Lung, and Blood Institute; National Institute of Neurological Disorders and Stroke; National Institute on Aging; and National Institute on Deafness and Other Communication Disorders
- 75N92022D00002 NHLBI NIH HHS
- R01 NS108452 NINDS NIH HHS
- U01HL096814 ARIC Neurocognitive Study grants, National Heart, Lung, and Blood Institute; National Institute of Neurological Disorders and Stroke; National Institute on Aging; and National Institute on Deafness and Other Communication Disorders
- U01 HL096902 NHLBI NIH HHS
- National Institutes of Health (US)
- 75N92022D00004 NHLBI NIH HHS
- R01AG071517 NIA NIH HHS
- R01 AG071517 NIA NIH HHS
- 75N92022D00003 NHLBI NIH HHS
- 75N92022D00005 NHLBI NIH HHS
- 75N92022D00001 NHLBI NIH HHS
- R00AG052830 NIA NIH HHS
- U01HL096899 ARIC Neurocognitive Study grants, National Heart, Lung, and Blood Institute; National Institute of Neurological Disorders and Stroke; National Institute on Aging; and National Institute on Deafness and Other Communication Disorders
- U01 HL096917 NHLBI NIH HHS
- U01HL096812 ARIC Neurocognitive Study grants, National Heart, Lung, and Blood Institute; National Institute of Neurological Disorders and Stroke; National Institute on Aging; and National Institute on Deafness and Other Communication Disorders
- U01 HL096814 NHLBI NIH HHS
- R01AG064093 NIA NIH HHS
- U01 HL096899 NHLBI NIH HHS
- R00 AG052830 NIA NIH HHS
- National Heart, Lung, and Blood Institute
- National Institute on Aging
Collapse
Affiliation(s)
- Srishti Shrestha
- The Memory Impairment and Neurodegenerative Dementia (MIND) CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Xiaoqian Zhu
- The Memory Impairment and Neurodegenerative Dementia (MIND) CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Anna M. Kucharska‐Newton
- Department of EpidemiologyUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Yaqun Yuan
- Department of Epidemiology and BiostatisticsMichigan State UniversityEast LansingMichiganUSA
| | - Vidyulata Kamath
- Department of Psychiatry and Behavioral SciencesJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Priya Palta
- Department of NeurologyUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Jennifer A. Deal
- Department of EpidemiologyJohns Hopkins University Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Thomas H. Mosley
- The Memory Impairment and Neurodegenerative Dementia (MIND) CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Michael E. Griswold
- The Memory Impairment and Neurodegenerative Dementia (MIND) CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Honglei Chen
- Department of Epidemiology and BiostatisticsMichigan State UniversityEast LansingMichiganUSA
| |
Collapse
|
38
|
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 2025; 68:357-366. [PMID: 39531040 PMCID: PMC11732724 DOI: 10.1007/s00125-024-06315-0] [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: 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.
Collapse
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
| |
Collapse
|
39
|
Gomez GT, Sathyan S, Chen J, Fornage M, Schlosser P, Peng Z, Cordon J, Palta P, Sullivan KJ, Tin A, Windham BG, Gottesman RF, Barzilai N, Milman S, Verghese J, Coresh J, Walker KA. Plasma proteomic characterization of motoric cognitive risk and mild cognitive impairment. Alzheimers Dement 2025; 21:e14429. [PMID: 39887533 PMCID: PMC11848158 DOI: 10.1002/alz.14429] [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: 07/11/2024] [Revised: 10/23/2024] [Accepted: 10/27/2024] [Indexed: 02/01/2025]
Abstract
INTRODUCTION Motoric cognitive risk (MCR) is a pre-dementia syndrome characterized by mobility and cognitive dysfunction. This study conducted a proteome-wide study of MCR and compared the proteomic signatures of MCR to that of mild cognitive impairment (MCI). METHODS Participants were classified as MCR using a memory questionnaire and 4-meter walk. We measured 4877 plasma proteins collected during late-life and midlife. Multivariable logistic regression related each protein to late-life MCR/MCI. MCR-associated proteins were replicated internally at midlife and in an external cohort. RESULTS Proteome-wide analysis (n = 4076) identified 25 MCR-associated proteins. Eight of these proteins remained associated with late-life MCR when measured during midlife. Two proteins (SVEP1 and TAGLN) were externally replicated. Compared to MCI, MCR had a distinct and much stronger proteomic signature enriched for cardiometabolic and immune pathways. DISCUSSION Our findings highlight the divergent biology underlying two pre-dementia syndromes. Metabolic and immune dysfunction may be a primary driver of MCR. HIGHLIGHTS MCR is defined by concurrent cognitive and gait dysfunction. MCR protein biomarkers have key roles in cardiometabolic and vascular function. MCR biomarkers are also associated with cerebrovascular disease and dementia. MCR and MCI demonstrate overlapping but divergent proteomic signatures.
Collapse
Affiliation(s)
- Gabriela T. Gomez
- Department of Internal MedicineMass General BrighamBostonMassachusettsUSA
| | - Sanish Sathyan
- Department of NeurologyAlbert Einstein College of MedicineBronxNew YorkUSA
| | - Jingsha Chen
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular MedicineMcGovern Medical School and Human Genetics Center, School of Public Health, The University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Pascal Schlosser
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Zhongsheng Peng
- Laboratory of Behavioral NeuroscienceNational Institute on AgingBaltimoreMarylandUSA
| | - Jenifer Cordon
- Laboratory of Behavioral NeuroscienceNational Institute on AgingBaltimoreMarylandUSA
| | - Priya Palta
- Gillings School of Global Public HealthUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - Kevin J. Sullivan
- Department of MedicineDivision of GeriatricsUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Adrienne Tin
- MIND Center and Division of NephrologyUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - B. Gwen Windham
- Department of MedicineDivision of GeriatricsUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and StrokeIntramural Research ProgramBethesdaMarylandUSA
| | - Nir Barzilai
- Department of MedicineDepartment of GeneticsInstitute for Aging Research, Albert Einstein College of MedicineBronxNew YorkUSA
| | - Sofiya Milman
- Department of MedicineDepartment of GeneticsInstitute for Aging Research, Albert Einstein College of MedicineBronxNew YorkUSA
| | - Joe Verghese
- Department of NeurologyRenaissance School of MedicineStony BrookNew YorkUSA
| | - Josef Coresh
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Keenan A. Walker
- Laboratory of Behavioral NeuroscienceNational Institute on AgingBaltimoreMarylandUSA
| |
Collapse
|
40
|
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; 103:724-734. [PMID: 39772982 DOI: 10.1177/13872877241305806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 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.
Collapse
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
| |
Collapse
|
41
|
Chiu TS, Pankow JS, Cushman M, Windham BG, Matsushita K, Mok Y, Kucharska-Newton AM, Tang W, Lutsey PL. Frailty and risk of venous thromboembolism in older adults: the Atherosclerosis Risk in Communities Study. J Thromb Haemost 2025:S1538-7836(25)00049-2. [PMID: 39894445 DOI: 10.1016/j.jtha.2025.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Revised: 12/11/2024] [Accepted: 01/27/2025] [Indexed: 02/04/2025]
Abstract
BACKGROUND Frailty may be a marker of risk for developing venous thromboembolism (VTE). OBJECTIVES To examine the relationship of frailty and its components with risk of incident VTE among older adults. METHODS We examined 5551 participants of the Atherosclerosis Risk in Communities Study without a history of VTE, using visit 5 (2011-2013) as baseline (mean age, 75.4 years; 57.8% female; 21.5% Black race). Frailty status (frail, prefrail, or robust) was defined as having ≥3 components, 1 to 2 components, or no components, respectively, from assessments of weight loss, low grip strength, exhaustion, slow walking speed, and low physical activity. VTE events were identified from hospitalization records and adjudicated by physicians. RESULTS In total, 182 incident VTE events accrued over a median follow-up of 7.2 years. Participants who were frail, vs robust, had a hazard ratio (HR) for incident VTE of 2.20 (95% CI, 1.30-3.71) after accounting for demographics. Further adjustment for potential confounders only slightly attenuated the association (HR, 2.09; 95% CI, 1.23-3.55). When analyzed separately, frailty was associated with a fully adjusted HR of 2.46 (95% CI, 1.26-4.80) for provoked VTE and 1.56 (95% CI, 0.66-3.69) for unprovoked VTE. Of the frailty components, exhaustion, slow walking speed, and low physical activity were significantly associated with increased risk of incident VTE. CONCLUSION Among this sample of older adults, frail participants had a 2-fold greater risk of incident VTE than robust participants. Exhaustion, slow walking speed, and low physical activity were frailty components identified as being predictors of incident VTE. Frailty status may be a means for identifying older adults at elevated VTE risk.
Collapse
Affiliation(s)
- Tobyn S Chiu
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA
| | - B Gwen Windham
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Kunihiro Matsushita
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Yejin Mok
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Anna M Kucharska-Newton
- Department of Epidemiology, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, USA; Department of Epidemiology, University of Kentucky, Lexington, Kentucky, USA
| | - Weihong Tang
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Pamela L Lutsey
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA.
| |
Collapse
|
42
|
Richey LN, Daneshvari NO, Young L, Bray MJC, Gottesman RF, Mosley T, Walker KA, Schneider ALC, Peters ME. Associations of Traumatic Brain Injury and Mild Behavioral Impairment With Cognitive Function and Dementia. J Geriatr Psychiatry Neurol 2025:8919887251317726. [PMID: 39882790 DOI: 10.1177/08919887251317726] [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] [Indexed: 01/31/2025]
Abstract
OBJECTIVE Traumatic Brain Injury (TBI) may contribute additional complexity to the clinical picture of mild behavioral impairment (MBI). MBI, a behavioral analog to mild cognitive impairment (MCI), is comprised of five neuropsychiatric domains: decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, and abnormal perception/thought content. We investigated (1) if cross-sectional associations of cognitive status with MBI symptoms differ by TBI status and (2) if prospective associations of MBI domain positivity with incident dementia risk differ by TBI status. METHODS 2246 participants without dementia from the Atherosclerosis Risk in Communities Study were included (mean age = 75.6 years, 59.0% female). TBI was defined by self-report/ICD-9/10 codes, MBI via an established algorithm based on the Neuropsychiatric Inventory Questionnaire, and baseline cognitive status/incident dementia using neuropsychological tests, informant interviews, and hospital/death certificate codes. RESULTS Cross-sectionally, although MCI status was associated with greater odds of MBI, this did not differ based on TBI status (MCI with TBI: OR = 2.04, 95% CI = 1.44-2.88, MCI without TBI: OR = 1.60, 95% CI = 1.20-2.14). Individuals with MCI (with or without TBI) were more likely to have decreased motivation, affective dysregulation, and impulse dyscontrol. Prospectively, positivity in 1+ MBI domains was associated with increased risk of incident dementia, not differing by TBI status (no TBI and MBI: HR = 2.15, 95% CI = 1.55-2.99, TBI and MBI: HR = 2.62, 95% CI = 1.81-3.80). CONCLUSIONS Neither cross-sectional associations between cognitive status and MBI domain positivity nor prospective associations of MBI domain positivity with incident dementia risk differed by TBI status. How TBI may relate to neuropsychiatric symptomatology in the context of neurodegenerative processes requires further clarification.
Collapse
Affiliation(s)
- Lisa N Richey
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Lisa Young
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael J C Bray
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Rebecca F Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Thomas Mosley
- University of Mississippi Medical Center, Jackson, MI, USA
| | - Keenan A Walker
- National Institute on Aging Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Andrea L C Schneider
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Matthew E Peters
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| |
Collapse
|
43
|
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 Cardiovascular Disease in a Harmonized Analysis of Seven Prospective Cohorts. Nutrients 2025; 17:451. [PMID: 39940309 PMCID: PMC11820226 DOI: 10.3390/nu17030451] [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: 01/06/2025] [Revised: 01/18/2025] [Accepted: 01/24/2025] [Indexed: 02/14/2025] Open
Abstract
Background/Objectives: While previous study results have suggested an elevated risk of type 2 diabetes with potato consumption, limited and inconsistent results are available on the association of potato consumption with the risk of cardiovascular disease (CVD) and hypertension (HTN). We assessed the associations of (i) total potato consumption with the risk of CVD and HTN as the primary aim and (ii) fried potatoes and combined baked, boiled, and mashed potatoes with the risk of CVD and HTN as the secondary aim. Methods: We conducted a meta-analysis using data from seven cohorts for CVD (n = 110,063) and five cohorts for HTN (n = 67,146). Cox regression was used to estimate multivariable adjusted hazard ratios separately in each cohort and the cohort-specific results were meta-analyzed using an inverse-variance weighted method. Results: The mean age ranged from 25 to 72 years, 65% of the respondents were women, and the 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 the risk of either CVD or HTN: multivariable adjusted HR (95% CI) comparing 5+ servings/week to no potato intake: 0.96 (0.89-1.04) for CVD and 1.04 (0.99-1.08) for HTN. In secondary analyses, the consumption of combined baked, boiled, and mashed potatoes was not associated with CVD or HTN; while fried potato consumption was not associated with CVD risk, there was a 10% higher risk of HTN (95% CI: 4% to 17%) comparing 1+ servings/week to no fried potato intake. Conclusions: While the consumption of total potato was not associated with the risk of CVD or HTN risk, a modest elevated risk of HTN but not CVD was observed only with fried potato consumption.
Collapse
Affiliation(s)
- Luc Djousse
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02120, USA; (E.K.); (H.D.S.); (I.-M.L.); (J.E.B.); (J.M.G.); (J.E.M.)
- School of Medicine, Harvard University, Boston, MA 02115, USA
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Xia Zhou
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55454, USA; (X.Z.)
| | - Jaewon Lim
- Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA; (J.L.); (R.L.M.)
| | - Eunjung Kim
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02120, USA; (E.K.); (H.D.S.); (I.-M.L.); (J.E.B.); (J.M.G.); (J.E.M.)
| | - Howard D. Sesso
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02120, USA; (E.K.); (H.D.S.); (I.-M.L.); (J.E.B.); (J.M.G.); (J.E.M.)
- School of Medicine, Harvard University, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - I-Min Lee
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02120, USA; (E.K.); (H.D.S.); (I.-M.L.); (J.E.B.); (J.M.G.); (J.E.M.)
- School of Medicine, Harvard University, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Julie E. Buring
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02120, USA; (E.K.); (H.D.S.); (I.-M.L.); (J.E.B.); (J.M.G.); (J.E.M.)
- School of Medicine, Harvard University, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Robyn L. McClelland
- Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA; (J.L.); (R.L.M.)
| | - John Michael Gaziano
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02120, USA; (E.K.); (H.D.S.); (I.-M.L.); (J.E.B.); (J.M.G.); (J.E.M.)
- School of Medicine, Harvard University, Boston, MA 02115, USA
| | - Lyn M. Steffen
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55454, USA; (X.Z.)
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02120, USA; (E.K.); (H.D.S.); (I.-M.L.); (J.E.B.); (J.M.G.); (J.E.M.)
- School of Medicine, Harvard University, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| |
Collapse
|
44
|
Sedaghat S, Park S, Walker R, Wang S, Liu J, Hughes T, Sabayan B, Tang W, Coresh J, Pankow J, Walker K, Casanova R, Dubin R, Deo R, Rotter J, Wood A, Ganz P, Lutsey P, Guan W, Prizment A. Proteomics-based aging clocks in midlife and late-life and risk of dementia. RESEARCH SQUARE 2025:rs.3.rs-5500348. [PMID: 39877085 PMCID: PMC11774457 DOI: 10.21203/rs.3.rs-5500348/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2025]
Abstract
Background Biological age can be quantified by composite proteomic scores, called aging clocks. We investigated whether biological age acceleration (a discrepancy between chronological and biological age) in midlife and late-life is associated with cognitive function and risk of dementia. Methods We used two population-based cohort studies: Atherosclerosis Risk in Communities (ARIC) Study and Multi-Ethnic Study of Atherosclerosis (MESA). Proteomics-based aging clocks (PACs) were created in ARIC at midlife (mean age: 58 years, n=11,758) and late-life (mean age: 77 years, n=4,934) using elastic net regression models in two-thirds of dementia-free participants and validated in the remaining one-third of participants. Age acceleration (AA) was calculated as residuals after regressing PACs on chronological age. We validated the midlife PAC in the MESA cohort (mean age: 62 years, n=5,829). We used multivariable linear and Cox proportional hazards regression to assess the association of AA with cognitive function and dementia incidence, respectively. Results In ARIC, every five years AA was associated with lower global cognitive function: difference: -0.11, 95% confidence interval (CI): -0.16, -0.06) using midlife AA and difference: -0.17, CI: -0.23, -0.12 using late-life AA. Consistently, midlife AA was associated with higher risk of dementia (hazard ratio [HR]: 1.20 [CI: 1.04, 1.36]) and more prominently when using late-life AA (HR: 2.14 [CI:1.67, 2.73]). Similar findings were observed in the MESA study: every five years AA was associated with lower global cognitive function (difference: -0.08 [CI: -0.14, -0.03]) and higher risk of dementia (HR:1.23 [CI: 1.04, 1.46]). Conclusion Accelerated biological age - as defined by the plasma proteome - is associated with lower cognitive function and predicts a higher risk of dementia in midlife and more prominently in late-life.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Ramon Casanova
- Department of Biostatistics and Data Science, School of Medicine, Wake Forest University
| | - Ruth Dubin
- University of Texas Southwestern Medical Center
| | | | - Jerome Rotter
- The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | | | | | | | | | | |
Collapse
|
45
|
Wang S, Rao Z, Li A, Blaes AH, Blaha MJ, Coresh J, Dubin R, Deo R, Joshu CE, Marshall CH, Pankow JS, Rotter JI, Thyagarajan B, Whelton SP, Ganz P, Guan W, Platz EA, Prizment A. The Association between Proteomic Aging Clocks and the Risk of Cancer in Midlife Individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.01.05.25320018. [PMID: 39830250 PMCID: PMC11741449 DOI: 10.1101/2025.01.05.25320018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
Background To measure the aging process before a cancer diagnosis, we developed the first cancer-specific proteomic aging clock (CaPAC) and examined its association with cancer risk in the Atherosclerosis Risk in Communities (ARIC) and Multi-Ethnic Study of Atherosclerosis (MESA) studies. Methods Using the SomaScan assay, ARIC measured 4,712 proteins in plasma samples collected in 1990-92 from 3,347 participants who developed cancer over follow-up until 2015 and 7,487 who remained cancer-free, all aged 46-70. We constructed CaPAC0 using elastic net regression among two-thirds randomly selected cancer-free participants (N=4,991, training set) and calculated age acceleration for CaPAC0 (CaPAA0) as residuals of CaPAC0 on chronological age in all remaining ARIC participants. We used multivariable-adjusted Cox proportional hazards regression to calculate hazard ratios (HRs) for the risk of overall, obesity-related, smoking-related, and the most common cancers (prostate, lung, breast, colorectal) with CaPAA0 using a case-cohort design. We replicated the analysis in 3,893 MESA participants aged 46-70 at Exam 1 (456 incident cancer). Results CaPAC0 was correlated with chronological age in ARIC and MESA (r=0.82 and 0.86, respectively). In both ARIC and MESA, CaPAA0 was significantly (p<0.05) associated with the risk of overall [HRs per 5-years=1.08 and 1.23, respectively], smoking-related [HRs=1.30 and 1.54, respectively], and lung cancers [HRs=1.54 and 1.94, respectively]. CaPAA0 was also significantly associated with colorectal cancer risk in ARIC [HR=1.31], but not in MESA. CaPAA0 was not associated with obesity-related, breast, or prostate cancers. Conclusion CaPAA0 was associated with several types of cancer with the strongest association observed for lung cancer risk.
Collapse
|
46
|
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 PMCID: PMC11731176 DOI: 10.1167/tvst.14.1.8] [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: 07/04/2024] [Accepted: 11/28/2024] [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.
Collapse
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
| |
Collapse
|
47
|
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 2025; 66:37-48. [PMID: 39603508 PMCID: PMC11903177 DOI: 10.1016/j.jaclp.2024.11.003] [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: 06/19/2024] [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.
Collapse
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
| |
Collapse
|
48
|
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.
Collapse
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
| |
Collapse
|
49
|
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 PMCID: PMC11737446 DOI: 10.2215/cjn.0000000000000575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [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.
Collapse
Grants
- U01 DK060963 NIDDK NIH HHS
- UL1 RR024131 NCRR NIH HHS
- UL1 TR000003 NCATS NIH HHS
- CTSA UL1RR029879 University of Illinois at Chicago
- UL1 TR000439 NCATS NIH HHS
- 75N92022D00003 NHLBI NIH HHS
- R01DK124399 NIDDK NIH HHS
- R01 DK100446 NIDDK NIH HHS
- UL1 RR029879 NCRR NIH HHS
- K24HL155861 NHLBI NIH HHS
- U01 DK061028 NIDDK NIH HHS
- UL1 TR000433 NCATS NIH HHS
- 75N92022D00002 NHLBI NIH HHS
- U01 DK060984 NIDDK NIH HHS
- U01 DK061021 NIDDK NIH HHS
- U24 DK060990 NIDDK NIH HHS
- UL1TR000433 Michigan Institute for Clinical and Health Research
- U01 DK060980 NIDDK NIH HHS
- UCSF-CTSI UL1 RR-024131 Kaiser Permanente
- R01DK100446 NIDDK NIH HHS
- 75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, 75N92022D00005 NHLBI NIH HHS
- U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, U01DK060902 and U24DK060990 NIDDK NIH HHS
- UL1TR000003 Perelman School of Medicine, University of Pennsylvania
- 75N92022D00004 NHLBI NIH HHS
- U01 DK061022 NIDDK NIH HHS
- K24 HL155861 NHLBI NIH HHS
- UL1TR000439 Clinical and Translational Science Collaborative of Cleveland, School of Medicine, Case Western Reserve University
- R01 DK119199 NIDDK NIH HHS
- NM R01DK119199 School of Medicine, University of New Mexico
- GCRC M01 RR-16500 University of Maryland
- UL1 TR000424 NCATS NIH HHS
- M01 RR016500 NCRR NIH HHS
- P20 GM109036 NIGMS NIH HHS
- U01 DK060902 NIDDK NIH HHS
- U01 DK060990 NIDDK NIH HHS
- R01 DK124399 NIDDK NIH HHS
- 75N92022D00005 NHLBI NIH HHS
- 75N92022D00001 NHLBI NIH HHS
- UL1 TR-000424 Johns Hopkins University
Collapse
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
| |
Collapse
|
50
|
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.
Collapse
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
| |
Collapse
|