Hai-Xia Li, Jin-Tao Wang, Yu Dong, Jian-Ping Li, Jin-Wen Xiao, Ru-Jing Ren, Chun-Bo Li , Gang Wang
Background: The predictive effects of blood biomarkers (BBMs) in the progression of Alzheimer’s disease (AD) have been reported recently. However, controversies still exist. In the present study, we aim to identify the predictive performances of BBMs in the conversion from Mild cognitive impairment (MCI) to AD.
Methods: PubMed, Embase, Cochrane Library, and Web of Science from inception to June 10, 2023 were searched. Predictive potentials were evaluated by pooling the ratio of means (ROMs), relative risks (RRs), and diagnostic indexes from MCI-converters (MCI-c: MCI patients who convert to AD) and MCI-non converters (MCI-nc) based on fixed-effects or random-effects. Newcastle–Ottawa Quality Assessment Scale (NOS) was applied for quality assessment.
Results: A total of 44 studies with 9343 participants from 28 cohorts were included in the meta-analysis, whereas the other 45 articles were included in the qualitative review. The average score of 44 studies included in the meta-analysis was 7.125. In pooled ROMs, plasma Aβ42/Aβ40 was lower, whereas Aβ40, T-tau, P-tau 181, P-tau 217, NFL, and GFAP were higher in MCI-c than MCI-nc. In pooled RRs, P-tau (RR=2.50, 95%CI: 2.04-3.06) as a continuous variable, Aβ42/Aβ40 as a categorical variable (RR=1.28, 95%CI: 1.01-1.61) could predict future conversion risk of MCI patients. In diagnostic indexes, the diagnostic odds ratio (DOR) was 42 for P-tau 217 (sensitivity: 91%; specificity: 81%), 15 for P-tau 181 (sensitivity: 81%; specificity: 78%), 12.71 for GFAP (sensitivity: 71%; specificity: 86%), 6 for Aβ42/Aβ40 (sensitivity: 86%; specificity: 49%, and 6 for NFL (sensitivity: 80%; specificity: 61%).
Conclusion: Here, our results indicated that blood biomarkers held promising potential in predicting MCI conversion. However, more prospective cohorts based on particular MCI types and high-sensitivity assays are warranted to validate the results next.