Abstract The Cortical Asymmetry Index (CAI) evaluates the cortical thickness asymmetry between hemispheres. We investigated CAI in asymptomatic (AMC) and symptomatic (SMC) mutation carriers of Autosomal Dominant Alzheimer’s Disease (ADAD) to explore the brain asymmetry within the Alzheimer’s disease (AD) continuum. Sixty baseline T1-weighted MRI scans were obtained from the Clinic Barcelona cohort. Baseline and longitudinal MRI data from 564 participants within the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS) were used as an independent, confirmatory cohort. Cerebrospinal fluid (CSF) and plasma neurofilament light chain (NfL) levels were included when available. Cortical thickness was calculated using Freesurfer and CAI was calculated via an open-source pipeline. Cross-sectional analyses examined CAI differences based on clinical classification and APOE ε4 status, adjusting for age, sex, and estimated years from onset (EYO), while correlations were assessed with age, EYO, Mini-Mental State Examination (MMSE) scores, and NfL. Longitudinal CAI evolution was modeled using generalized additive models (GAM) in the DIAN-OBS cohort, incorporating age, sex, and the interaction between group and EYO. The CAI successfully distinguished AMC and SMC from healthy controls (CTR) in the Clinic Barcelona cohort and SMC from CTR in DIAN-OBS. Higher CAI in mutation carriers (AMC and SMC combined) and in SMC were associated with higher plasma NfL levels, a closer proximity to symptom onset, and lower MMSE in the Clinic Barcelona cohort. In the DIAN-OBS cohort, mutation carriers exhibited increased CAI compared to CTR and correlated with elevated NfL (plasma and CSF), lower MMSE, and a closer proximity to symptom onset. APOE3/3 carriers showed greater asymmetry than other APOE genotypes and significant CAI differences between AMC and SMC. Longitudinally, CAI increased over time significantly in SMC. These findings underscore brain asymmetry as a potential biomarker for early AD progression in ADAD, with implications for detection and monitoring tracking disease-related neuroanatomical changes.
Pérez‐Millan et al. (Thu,) studied this question.