Medical College of Wisconsin
CTSICores SearchResearch InformaticsREDCap

Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals. JAMA Psychiatry 2024 May 01;81(5):456-467

Date

02/14/2024

Pubmed ID

38353984

Pubmed Central ID

PMC10867779

DOI

10.1001/jamapsychiatry.2023.5599

Scopus ID

2-s2.0-85185283495 (requires institutional sign-in at Scopus site)

Abstract

IMPORTANCE: Brain aging elicits complex neuroanatomical changes influenced by multiple age-related pathologies. Understanding the heterogeneity of structural brain changes in aging may provide insights into preclinical stages of neurodegenerative diseases.

OBJECTIVE: To derive subgroups with common patterns of variation in participants without diagnosed cognitive impairment (WODCI) in a data-driven manner and relate them to genetics, biomedical measures, and cognitive decline trajectories.

DESIGN, SETTING, AND PARTICIPANTS: Data acquisition for this cohort study was performed from 1999 to 2020. Data consolidation and harmonization were conducted from July 2017 to July 2021. Age-specific subgroups of structural brain measures were modeled in 4 decade-long intervals spanning ages 45 to 85 years using a deep learning, semisupervised clustering method leveraging generative adversarial networks. Data were analyzed from July 2021 to February 2023 and were drawn from the Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) international consortium. Individuals WODCI at baseline spanning ages 45 to 85 years were included, with greater than 50 000 data time points.

EXPOSURES: Individuals WODCI at baseline scan.

MAIN OUTCOMES AND MEASURES: Three subgroups, consistent across decades, were identified within the WODCI population. Associations with genetics, cardiovascular risk factors (CVRFs), amyloid β (Aβ), and future cognitive decline were assessed.

RESULTS: In a sample of 27 402 individuals (mean [SD] age, 63.0 [8.3] years; 15 146 female [55%]) WODCI, 3 subgroups were identified in contrast with the reference group: a typical aging subgroup, A1, with a specific pattern of modest atrophy and white matter hyperintensity (WMH) load, and 2 accelerated aging subgroups, A2 and A3, with characteristics that were more distinct at age 65 years and older. A2 was associated with hypertension, WMH, and vascular disease-related genetic variants and was enriched for Aβ positivity (ages ≥65 years) and apolipoprotein E (APOE) ε4 carriers. A3 showed severe, widespread atrophy, moderate presence of CVRFs, and greater cognitive decline. Genetic variants associated with A1 were protective for WMH (rs7209235: mean [SD] B = -0.07 [0.01]; P value = 2.31 × 10-9) and Alzheimer disease (rs72932727: mean [SD] B = 0.1 [0.02]; P value = 6.49 × 10-9), whereas the converse was observed for A2 (rs7209235: mean [SD] B = 0.1 [0.01]; P value = 1.73 × 10-15 and rs72932727: mean [SD] B = -0.09 [0.02]; P value = 4.05 × 10-7, respectively); variants in A3 were associated with regional atrophy (rs167684: mean [SD] B = 0.08 [0.01]; P value = 7.22 × 10-12) and white matter integrity measures (rs1636250: mean [SD] B = 0.06 [0.01]; P value = 4.90 × 10-7).

CONCLUSIONS AND RELEVANCE: The 3 subgroups showed distinct associations with CVRFs, genetics, and subsequent cognitive decline. These subgroups likely reflect multiple underlying neuropathologic processes and affect susceptibility to Alzheimer disease, paving pathways toward patient stratification at early asymptomatic stages and promoting precision medicine in clinical trials and health care.

Author List

Skampardoni I, Nasrallah IM, Abdulkadir A, Wen J, Melhem R, Mamourian E, Erus G, Doshi J, Singh A, Yang Z, Cui Y, Hwang G, Ren Z, Pomponio R, Srinivasan D, Govindarajan ST, Parmpi P, Wittfeld K, Grabe HJ, Bülow R, Frenzel S, Tosun D, Bilgel M, An Y, Marcus DS, LaMontagne P, Heckbert SR, Austin TR, Launer LJ, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Johnson SC, Morris JC, Albert MS, Bryan RN, Yaffe K, Völzke H, Ferrucci L, Benzinger TLS, Ezzati A, Shinohara RT, Fan Y, Resnick SM, Habes M, Wolk D, Shou H, Nikita K, Davatzikos C

Author

Gyujoon Hwang PhD Assistant Professor in the Psychiatry and Behavioral Medicine department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Aged
Aged, 80 and over
Aging
Brain
Cognitive Dysfunction
Cohort Studies
Female
Humans
Magnetic Resonance Imaging
Male
Middle Aged