Developing digital biomarker for predicting cognitive response to multi-domain intervention

  • Park, Ji Hyeun
  • Kim, Hyun Sook
  • Choi, Seong Hye
  • Jeong, Jee Hyang
  • Moon, So Young
  • 외 5명
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초록

Computerized cognitive training allows real-time tracking of performance metrics that may serve as digital biomarkers. This study investigated the value of a novel in-game digital biomarker, RTACC (Reaction Time-Accuracy Correlation), the correlation between reaction time and accuracy, using data from 130 participants with mild cognitive impairment enrolled in the intervention arm of the SUPERBRAIN-MEET randomized controlled trial. Participants underwent a 24-week multi-domain intervention, consisting of computerized cognitive training, physical exercise, nutritional education, vascular/metabolic risk management, and motivation enhancement. RTACC was derived from task-level RT and accuracy and examined in relation to cognitive and biomarker outcomes. Linear regression analysis revealed a significant association between RTACC and changes in Repeatable Battery for the Assessment of Neuropsychological Status scores from baseline to 24 weeks (beta coefficient = -11.90 +/- 3.78, T = - 3.14, P = 0.002). RTACC also showed a marginal effect on changes in brain-derived neurotrophic factor levels (beta coefficient = - 3.13 +/- 1.64, P = 0.057). Logistic regression analysis demonstrated that RTACC combined with clinical information identified good responders with an area under the receiver operating characteristic curve of 0.73 (95% CI: 0.62-0.84). These findings suggest that this in-game digital biomarker (RTACC) may help identify individuals likely to benefit from multi-domain intervention.

키워드

Digital biomarkerComputerized cognitive trainingMild cognitive impairmentPREVENTIONTASKSBDNF
제목
Developing digital biomarker for predicting cognitive response to multi-domain intervention
저자
Park, Ji HyeunKim, Hyun SookChoi, Seong HyeJeong, Jee HyangMoon, So YoungPark, Yoo KyoungHong, Chang HyungCho, Soo HyunNa, Hae RiKim, Hang-Rai
DOI
10.1038/s41598-026-37123-8
발행일
2026-01-30
유형
Article
저널명
Scientific Reports
16
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