Abstract

The high cost, limited availability, and perceived invasiveness of amyloid PET and cerebrospinal fluid biomarkers limit their use for the diagnosis of Alzheimer's disease. The present study aimed to assess the associations of mild cognitive impairment (MCI) with circulating amyloid-β (Aβ), methionine circulating metabolites (MCMs), and their downstream products, and to develop a nomogram based on these easily accessible blood indexes for the individualized prediction of MCI risk in older adults. In this nested case-control study, we recruited 74 MCI patients and, for each, 3 matched controls (n = 222) within the context of the Tianjin Elderly Nutrition and Cognition (TENC) cohort, a population-based prospective study in China. Concentrations of Aβ, MCMs, and their circulating downstream factors (i.e., leukocyte telomere length and inflammatory cytokines) were evaluated in fasting blood sample using standard procedures. We constructed a nomogram for MCI harnessed multivariable logistic models incorporating variables selected in the Lasso regression. Among the many biomarkers examined, the final prediction nomogram retained only 3 factors: Aβ42/Aβ40 ratio, Hcy, and SAM/SAH ratio. The model achieved favorable discrimination, with a C-statistic of 0.75 (95% confidence interval 0.69-0.81) in internal validation after adjustment of optimism. The calibration accuracy was satisfactory; the Brier score of the model was 0.161 in internal validation after adjustment of optimism. his study presents an individualized prediction nomogram incorporating only three blood biomarkers (i.e., Aβ42/Aβ40 ratio, Hcy, and SAM/SAH ratio), which can be conveniently utilized to facilitate early identification and the development of high-risk prevention strategies for MCI in older adults.

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