Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics among Patients with Late-Life Depression

Junhao Wen, Cynthia H.Y. Fu, Duygu Tosun, Yogasudha Veturi, Zhijian Yang, Ahmed Abdulkadir, Elizabeth Mamourian, Dhivya Srinivasan, Ioanna Skampardoni, Ashish Singh, Hema Nawani, Jingxuan Bao, Guray Erus, Haochang Shou, Mohamad Habes, Jimit Doshi, Erdem Varol, R. Scott Mackin, Aristeidis Sotiras, Yong FanAndrew J. Saykin, Yvette I. Sheline, Li Shen, Marylyn D. Ritchie, David A. Wolk, Marilyn Albert, Susan M. Resnick, Christos Davatzikos

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Importance: Late-life depression (LLD) is characterized by considerable heterogeneity in clinical manifestation. Unraveling such heterogeneity might aid in elucidating etiological mechanisms and support precision and individualized medicine. Objective: To cross-sectionally and longitudinally delineate disease-related heterogeneity in LLD associated with neuroanatomy, cognitive functioning, clinical symptoms, and genetic profiles. Design, Setting, and Participants: The Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) study is an international multicenter consortium investigating brain aging in pooled and harmonized data from 13 studies with more than 35000 participants, including a subset of individuals with major depressive disorder. Multimodal data from a multicenter sample (N = 996), including neuroimaging, neurocognitive assessments, and genetics, were analyzed in this study. A semisupervised clustering method (heterogeneity through discriminative analysis) was applied to regional gray matter (GM) brain volumes to derive dimensional representations. Data were collected from July 2017 to July 2020 and analyzed from July 2020 to December 2021. Main Outcomes and Measures: Two dimensions were identified to delineate LLD-associated heterogeneity in voxelwise GM maps, white matter (WM) fractional anisotropy, neurocognitive functioning, clinical phenotype, and genetics. Results: A total of 501 participants with LLD (mean [SD] age, 67.39 [5.56] years; 332 women) and 495 healthy control individuals (mean [SD] age, 66.53 [5.16] years; 333 women) were included. Patients in dimension 1 demonstrated relatively preserved brain anatomy without WM disruptions relative to healthy control individuals. In contrast, patients in dimension 2 showed widespread brain atrophy and WM integrity disruptions, along with cognitive impairment and higher depression severity. Moreover, 1 de novo independent genetic variant (rs13120336; chromosome: 4, 186387714; minor allele, G) was significantly associated with dimension 1 (odds ratio, 2.35; SE, 0.15; P = 3.14 ×108) but not with dimension 2. The 2 dimensions demonstrated significant single-nucleotide variant-based heritability of 18% to 27% within the general population (N = 12518 in UK Biobank). In a subset of individuals having longitudinal measurements, those in dimension 2 experienced a more rapid longitudinal change in GM and brain age (Cohen f2= 0.03; P =.02) and were more likely to progress to Alzheimer disease (Cohen f2= 0.03; P =.03) compared with those in dimension 1 (N = 1431 participants and 7224 scans from the Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], and Biomarkers for Older Controls at Risk for Dementia [BIOCARD] data sets). Conclusions and Relevance: This study characterized heterogeneity in LLD into 2 dimensions with distinct neuroanatomical, cognitive, clinical, and genetic profiles. This dimensional approach provides a potential mechanism for investigating the heterogeneity of LLD and the relevance of the latent dimensions to possible disease mechanisms, clinical outcomes, and responses to interventions..

Original languageEnglish (US)
Pages (from-to)464-474
Number of pages11
JournalJAMA Psychiatry
Volume79
Issue number5
DOIs
StatePublished - May 2022
Externally publishedYes

ASJC Scopus subject areas

  • Psychiatry and Mental health

Fingerprint

Dive into the research topics of 'Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics among Patients with Late-Life Depression'. Together they form a unique fingerprint.

Cite this