دورية أكاديمية
أعرض في EDS

Associations of plasma proteomics and age-related outcomes with brain age in a diverse cohort.

التفاصيل البيبلوغرافية
العنوان: Associations of plasma proteomics and age-related outcomes with brain age in a diverse cohort.
المؤلفون: Casanova R; Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Medical Center Blvd., Winston-Salem, NC, USA. casanova@wakehealth.edu., Walker KA; National Institute of Health, Baltimore, MD, USA., Justice JN; Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA., Anderson A; Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Medical Center Blvd., Winston-Salem, NC, USA., Duggan MR; National Institute of Health, Baltimore, MD, USA., Cordon J; National Institute of Health, Baltimore, MD, USA., Barnard RT; Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Medical Center Blvd., Winston-Salem, NC, USA., Lu L; Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Medical Center Blvd., Winston-Salem, NC, USA., Hsu FC; Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Medical Center Blvd., Winston-Salem, NC, USA., Sedaghat S; School of Public Health, Oncology and Transplantation, University of Minnesota, Minneapolis, MN, USA., Prizment A; Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA., Kritchevsky SB; Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA., Wagenknecht LE; Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA., Hughes TM; Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
المصدر: GeroScience [Geroscience] 2024 Aug; Vol. 46 (4), pp. 3861-3873. Date of Electronic Publication: 2024 Mar 04.
نوع المنشور: Journal Article; Research Support, N.I.H., Intramural; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.
اللغة: English
بيانات الدورية: Publisher: Springer International Publishing Country of Publication: Switzerland NLM ID: 101686284 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2509-2723 (Electronic) Linking ISSN: 25092723 NLM ISO Abbreviation: Geroscience Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Cham : Springer International Publishing, [2017]-
مواضيع طبية MeSH: Proteomics* , Brain*/metabolism , Brain*/diagnostic imaging , Aging*/physiology , Aging*/metabolism , Magnetic Resonance Imaging*, Humans ; Female ; Male ; Aged ; Cohort Studies ; Aged, 80 and over ; Cognition/physiology ; Biomarkers/blood ; Biomarkers/metabolism
مستخلص: Machine learning models are increasingly being used to estimate "brain age" from neuroimaging data. The gap between chronological age and the estimated brain age gap (BAG) is potentially a measure of accelerated and resilient brain aging. Brain age calculated in this fashion has been shown to be associated with mortality, measures of physical function, health, and disease. Here, we estimate the BAG using a voxel-based elastic net regression approach, and then, we investigate its associations with mortality, cognitive status, and measures of health and disease in participants from Atherosclerosis Risk in Communities (ARIC) study who had a brain MRI at visit 5 of the study. Finally, we used the SOMAscan assay containing 4877 proteins to examine the proteomic associations with the MRI-defined BAG. Among N = 1849 participants (age, 76.4 (SD 5.6)), we found that increased values of BAG were strongly associated with increased mortality and increased severity of the cognitive status. Strong associations with mortality persisted when the analyses were performed in cognitively normal participants. In addition, it was strongly associated with BMI, diabetes, measures of physical function, hypertension, prevalent heart disease, and stroke. Finally, we found 33 proteins associated with BAG after a correction for multiple comparisons. The top proteins with positive associations to brain age were growth/differentiation factor 15 (GDF-15), Sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SEVP 1), matrilysin (MMP7), ADAMTS-like protein 2 (ADAMTS), and heat shock 70 kDa protein 1B (HSPA1B) while EGF-receptor (EGFR), mast/stem-cell-growth-factor-receptor (KIT), coagulation-factor-VII, and cGMP-dependent-protein-kinase-1 (PRKG1) were negatively associated to brain age. Several of these proteins were previously associated with dementia in ARIC. These results suggest that circulating proteins implicated in biological aging, cellular senescence, angiogenesis, and coagulation are associated with a neuroimaging measure of brain aging.
(© 2024. The Author(s).)
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معلومات مُعتمدة: U01 HL096812 United States HL NHLBI NIH HHS; P30 AG049638 United States AG NIA NIH HHS; U01 HL096917 United States HL NHLBI NIH HHS; P30 AG021332 United States GF NIH HHS; R01 HL134320 United States HL NHLBI NIH HHS; R01 HL070825 United States HL NHLBI NIH HHS; U01HL096812 United States GF NIH HHS; U01 HL096814 United States HL NHLBI NIH HHS; U01 HL096899 United States HL NHLBI NIH HHS; P30 AG021332 United States AG NIA NIH HHS; U01 HL096902 United States HL NHLBI NIH HHS; U01 AG024904 United States AG NIA NIH HHS
فهرسة مساهمة: Keywords: Alzheimer’s disease; Brain age; Machine learning; Mortality; Proteomics
المشرفين على المادة: 0 (Biomarkers)
تواريخ الأحداث: Date Created: 20240304 Date Completed: 20240705 Latest Revision: 20240725
رمز التحديث: 20240726
مُعرف محوري في PubMed: PMC11226584
DOI: 10.1007/s11357-024-01112-4
PMID: 38438772
قاعدة البيانات: MEDLINE
الوصف
تدمد:2509-2723
DOI:10.1007/s11357-024-01112-4