Serum Lipoprotein Subclasses as Predictors of Tensor-Based Morphometry Atrophy in the Alzheimer Disease Continuum

OBJECTIVE: To evaluate whether serum lipoprotein subclasses and related metabolites quantified by nuclear magnetic resonance (NMR) are associated with longitudinal tensor-based morphometry (TBM) atrophy in mild cognitive impairment (MCI). METHODS: Secondary analysis of ADNI-GO and ADNI-2 participants with a baseline diagnosis of MCI, baseline serum Nightingale NMR metabolomics, and at least 2 quality-controlled T1-weighted MRI examinations processed with the Mayo TBM-SyN pipeline. The TBM-SyN summary score was the mean annualized log-Jacobian volume change across 31 Alzheimer disease (AD)-vulnerable regions, derived from baseline-to-follow-up symmetric registration. Linear mixed-effects models adjusted for age and included subject-level random intercepts. Associations with the Clinical Dementia Rating (CDR) and the Alzheimer Disease Assessment Scale (ADAS) were tested. RESULTS: The analytic cohort included 93 participants (mean age: 65.23 y, SD: 6.47; 51 male, 54.8%). Eight biomarkers were significantly associated with TBM-SyN atrophy: medium HDL free cholesterol percentage (M_HDL_FC_PCT; β=-0.0020, P=0.0016), apolipoprotein B (P=0.005), apolipoprotein A1 (P=0.017), extra-large HDL particle concentration (XL_HDL_P; P=0.029), medium HDL particle concentration (P=0.028), medium HDL cholesterol (P=0.025), medium HDL cholesterol esters (P=0.031), and glycerol (P=0.038). XL_HDL_P alone was associated with the CDR score (P=0.03). CONCLUSIONS: Specific HDL-related lipoprotein subclasses, apolipoproteins, and glycerol are associated with TBM-derived structural atrophy in MCI, supporting peripheral lipid metabolism as a candidate scalable correlate of early neurodegeneration.