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Approved Research

To investigate the risk factors in the circadian rhythm-related diseases using the UK biobank data.

Principal Investigator: Dr Shin-Yi Tsai
Approved Research ID: 60239
Approval date: March 7th 2022

Lay summary

A. The aim of this study is to analyze the questionnaires, and genetic data for the epidemiology of circadian-related diseases through using the International Classification of Diseases (ICD) 9 and 10 databases to define the related diseases. We would investigate the potential risk factors in some certain conditions such as lifestyles, environmental exposures, genetic polymorphisms, blood types, images, and etc. Through those processes, we expect to develop the predictive algorithms for risk estimations to optimize the healthcare workflow and to help with preventive medicine.

B. Circadian rhythm is an essential mechanism in every organism to modulate time and physiological activities. Based on it, organisms can regulate internal biological functions and respond to environmental changes.[1] Circadian rhythm disorders lead to deleterious effects on our physiological balances. It concerns many diseases such as metabolic syndrome, cardiovascular diseases(CVD), cancers, irritable bowel syndrome(IBS), inflammatory bowel disease(IBD), fibromyalgia, osteoporosis, Alzheimer's disease (AD), bipolar disorder, major depressive disorder, schizophrenia,  dementia, drug abuse, hemolysis, coagulopathy, antiphospholipid syndrome(APS), Human Immunodeficiency Virus(HIV), etc.[1-17] Those diseases cause tremendous economic losses. Scientists found some important mechanisms of the genetic level or metabolites. For instance, the two DNA-binding transcription factors, CLOCK and BMAL1, can activate core clock genes and clock-controlled genes (CCGs). CCGs produce the repressors, PER and CRY family members, to create a feedback loop in circadian rhythm. Furthermore, orphan nuclear receptors, RORa and REV-ERBa, activate and inhibit BMAL1 gene, respectively.[18] The majority of studies in circadian systems individally focused on the risk estimation, genetic breakdowns, or protein expressions. Neverthless,  we would develop risk models of circadian- related diseases and investigate what precipitates the susceptibility to diseases.

C. This project will take around 36 months as a project duration. We aim to optimize the healthcare services and preventive medicine by investigating the epidemiologic topics on the circadian-related diseases in UK and Taiwan biobanks and compare the significant difference between the two biobanks for global health. Additionally, we hope the findings can raise the awareness of clinicians or policy-makers for preventing medicine and clinical settings. Through finding the factors affecting the susceptibilities in the diseases related to the circadian rhythm for modeling algorithms, we expect to promote healthcare in the near future.