Integrating genetic, transcriptomic, and clinical studies for SLE to achieve personalized treatment of the disease based on predisposition, early manifestation, and molecular and cellular signatures

Professor Lau, Wallace Chak Sing   (Project Coordinator (PC))

Professor Li Philip Hei   (Co-principal investigator)

Professor Chan Chiu Wai Shirley   (Co-principal investigator)

Tam Lai-shan   (Co-principal investigator)

Sun Ren   (Collaborator)

Dr Chan Sau Fong   (Co-principal investigator)

Professor Yang Wanling   (Co-principal investigator)

Wang Yongfei   (Co-principal investigator)

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2024-06-01

6476284

Integrating genetic, transcriptomic, and clinical studies for SLE to achieve personalized treatment of the disease based on predisposition, early manifestation, and molecular and cellular signatures

1) systemic lupus erythematosus 2) genomic medicine 3) clinical subphenotype mapping

RheumatologyGenomic Medicine

Biology and Medicine (M)

C7046-23G

Collaborative Research Fund (CRF) - Group Research Project 2023/2024

2024

On-going

1. Expansion of SLE cohort from currently 1800 to 2800 cases, covering a majority of the Hong Kong cases; and to conduct longitudinal phenotypic correlation analysis between various clinical features2. To understand SLE disease heterogeneity from the genetic point of view by performing whole genome sequencing on newly collected samples, aiming to detect common, rare and structural variants associated with disease subphenotypes, severity, and treatment responses3. Using single-cell RNA sequencing to evaluate longitudinal changes in blood cellular and molecular signatures in association with LN flare, disease remission and treatment response; and to understand SLE heterogeneity by identifying molecular signatures and cellular composition that discriminate patients with stable disease from those susceptible to LN relapse4. Using advanced statistical approaches including machine learning to develop models to predict LN development, drug response, and disease outcomes based on clinical features, genetics, and molecular/cellular signatures derived from omics data