“Deep learning enhanced ALPS reveals genetic and environmental factors of brain glymphatic function”

Authors: Cha Lin, Hao Wu, Wenbiao Xian, Yifan Zheng, Wenxuan Du, Xinyi Chen, Jinxia Li, Weineng Chen, Lishan Lin, Fengjuan Su, Zhong Pei, Ganqiang Liu, For The Alzheimer’s Disease Neuroimaging Initiative For The European Prevention of Alzheimer’s Disease (EPAD) Consortium

Abstract:

Background: The glymphatic system plays a critical role in brain waste clearance and health. Diffusion tensor imaging along the perivascular space (DTI-ALPS) is an emerging approach to assess glymphatic function, but manual analysis is limited by its subjectivity and laboriousness in clinical practice. To address these challenges, we developed a deep learning-enhanced DTI-ALPS (dALPS) method that automates and enhances measurement of DTI-ALPS in large-scale cohorts, enabling us to uncover its genetic and environmental determinants.

Methods: We proposed an automated workflow combining convolutional neural network (CNN) and You Only Look Once (YOLO) for region-of-interest detection in DTI images. Using this method, we calculated dALPS index for over 65,000 participants from UK Biobank and multiple cohorts, and performed a genome-wide association study (GWAS). Additionally, we conducted transcriptome-wide association study (TWAS) and proteome-wide association study (PWAS) to explore the genetic and molecular underpinnings of glymphatic function. Associations between dALPS and demographic, lifestyle, and clinical traits were comprehensively evaluated. Mediation analysis was conducted to explore the potential mediating role of pharmacological treatments, including antidepressants and sleep medications, in the relationship between disease status and dALPS outcomes.

Findings: Our automated dALPS index showed excellent reliability and reproducibility compared to conventional manual techniques (intraclass correlation coefficient = 0·95). We observed that the dALPS index was associated with a wide range of body composition measures and brain structures across different age groups and sex. GWAS identified five significant genetic loci associated with dALPS, two of which were replicated in an independent dataset. Subsequent TWAS and PWAS analyses highlighted potential causal genes and proteins linked to brain fluid dynamics. We found that higher healthy lifestyle index (HLI) was positively correlated with improved dALPS, and confirmed the associations between reduced dALPS and various central nervous system (CNS) disorders, including depression, anxiety and neurodegenerative diseases. Notably, mediation analysis indicated that antidepressants were a risk factor for lower brain glymphatic function (P = 0·004) by partly mediating the risk factor of depression.

Interpretation: The dALPS analysis provides a reliable, precise, and automated biomarker for assessing brain glymphatic function. Our findings illuminate the genetic and environmental determinants of glymphatic activity, underscoring the potential of dALPS in clinical assessment, disease prediction and targeted therapeutic strategies.

DOI: https://doi.org/10.1016/j.ebiom.2026.106133

Published online: 30 January 2026 in the journal eBioMedicine