Approved Research

Exploring "Gene-Biofunction-Drug" Network of Multimorbidity Patterns among Diseases, Traits and Behavioral Features

Lay summary

Multimorbidity pattern is commonly defined as a pattern that at least two chronic conditions coexist in the same individual, which has posted a great challenge on public health and drawn great interest of healthcare system due to its substantial effect and financial burden on the individuals, their family and the society.

The current studies on multimorbidity pattern mainly focus on three elements: diseases, results of auxiliary examinations and behavioral features (such as socioeconomic behavior, psychological factor, lifestyle, etc.). Previous studies have shown that a mass of multimorbidities or disease-pairs have close association with each other, but the majority of the researches are centralized among the observational studies, which are affected by confounding factors and cannot reflect the direct causality among the diseases. Although some non-observational studies, Mendelian randomization studies for example, have revealed the causality among some diseases or traits, the studies are limited in summary data of genome-wide association studies (GWASs) instead of individual-level data and lack the details of individual distinguish data. Also, mechanisms underlying the development of multimorbidity still are complex and unclear. Therefore, it is necessary to further explore shared genetic architecture and deeper mechanisms of the multimorbidity pattern on the basis of individual level, which may contribute to the treatments, administration, prevention and rehabilitation for the patients.

Our team have been focusing on multimorbidity pattern and have found close relationship among some trait-pairs by means of observational studies and Mendelian randomization studies, such as cancers and cardiovascular diseases. Further, the project we proposed here aims to investigate the shared genetic architecture and underlying biological mechanisms of the multimorbidity pattern, using the de-identified individual data of the people living in the United Kingdom. We also aim to find some potential drug targets through the investigation of genetic architecture and their biological mechanisms to build a network of "Gene-Biofunction-Drug" and to apply to the treatment, prevention and management for the diseases.

This project will be conducted over the next three years. Through appropriate analysis and deep investigation, this project has the potential to uncover shared biological mechanisms and drug targets for multimorbidity pattern, and to contribute towards decision-making around treatment choice. With the identification of treatment for multimorbidity pattern, it can encourag people to seek medical help and release financial burden for healthcare system and society.