Found programs: National Natural Science Foundation of China (No . 82471952) ; Research Project of Anhui Pro- vincial Institute of Translational Medicine (No . 2023zhyx-B02) ; Sicience Foundation for Clinical Research of An- hui Medical University (No . 2023xkj143) ; Basic and Clinical Collaborative Research Enhancement Project of An- hui Medical University (No . 2023xkjT025)
Authors：Wang Jie1 , 2 , Miao Ziyue3 , Chang Jiayue3 , Wu Xingwang1 , Zhu Jiajia1 , Cai Huanhuan1
Keywords：diabetes; magnetic resonance imaging; machine learning; brain age;cognition; aging;
DOI：10.19405/j.cnki.issn1000-1492.2025.11.022
〔Abstract〕 Objective To explore the brain-predicted age difference(Brain-PAD) in patients with type 2 diabetes mellitus(T2DM) by a machine learning prediction model based on structural magnetic resonance(sMRI) in the Southwest University Adult Lifespan Dataset(SALD),and to reveal the relationship between Brain-PAD and duration of T2DM and cognition.Methods Group comparisons about demographic variables and cognitive function were conducted respectively in local database of 104 T2DM patients and 83 healthy controls(HC).The prediction model via Gaussian process regression(GPR) was constructed by training sMRI data of 329 healthy volunteers in SALD,then its performance was validated and evaluated.Furthermore,Brain-PAD(predicted age-chronological age) in the local database was calculated.Group comparisons of Brain-PAD between T2DM patients and HCs were conducted by Mann-Whitney U test.Finally,Pearson correlation coefficient(r) was calculated between Brain-PAD and duration of disease and cognition.Results Poor performance in auditory verbal learning test(AVLT)-delayed recall,AVLT-recognition,symbol digital modalities test(SDMT)(P