Soluble TREM2 levels associate with conversion from mild cognitive impairment to Alzheimer’s disease

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Abstract

BACKGROUND Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) plays an important role in the clearance of pathological amyloid-β (Aβ) in Alzheimer’s disease (AD). This study aimed to explore sTREM2 as a central and peripheral predictor of the conversion from mild cognitive impairment (MCI) to AD.METHODS sTREM2 and Aβ1–42 levels in cerebrospinal fluid (CSF) and florbetapir-PET (AV45) images were analyzed for healthy control (HCs), patients with MCI, and patients with AD from the ADNI database. Peripheral plasma sTREM2 and Aβ1–42 levels were determined for our Neurology database of Ruijin Hospital for Alzheimer’s Disease (NRHAD) cohort, and patients with MCI were reevaluated at follow-up visits to assess for progression to AD. The association between CSF and plasma sTREM2 levels was analyzed in data from the Chinese Alzheimer’s Biomarker and Lifestyle (CABLE) database.RESULTS The results showed that patients with MCI who had low levels of CSF sTREM2 and Aβ1–42 were more likely to develop AD. Among participants with positive Aβ deposition, as assessed by AV45 imaging, elevated CSF sTREM2 levels were associated with a decreased risk of MCI-to-AD conversion. Meanwhile, in the NRHAD cohort, individuals in the MCI group with high sTREM2 levels in plasma were at a greater risk for AD, whereas low Aβ1–42 with high sTREM2 levels in plasma were associated with a faster cognitive decline. In addition, CSF sTREM2 levels were highly correlated with plasma sTREM2 levels in the CABLE database.CONCLUSION These findings suggest that sTREM2 may be useful as a potential predictive biomarker of MCI-to-AD conversion.FUNDING This study was supported by grants from the National Natural Science Foundation of China (grant nos. 82001341, 82071415, 81873778, and 82201392); the Shanghai Sailing Program (grant no. 22YF1425100); and the China Postdoctoral Science Foundation funded project (grant no. 2021M702169).

Authors

Aonan Zhao, Yang Jiao, Guanyu Ye, Wenyan Kang, Lan Tan, Yuanyuan Li, Yulei Deng, Jun Liu, for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)