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    Melbourne VIC 3004


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Personal profile


Dr. Chenglong Yu is a genetic epidemiologist and statistical geneticist affiliated with the Public Health Genomics group at the School of Public Health and Preventive Medicine. His expertise encompasses a wide range of areas including genome-wide association studies, polygenic risk scores, population genetics, genotype by environment interaction, risk prediction, and epigenetics. Chenglong currently maintains the genomics research programs for the ASPirin in Reducing Events in the Elderly (ASPREE) study, Australia's largest randomised controlled trial and genomic cohort of ageing.

Chenglong’s research career began in mathematics (B.Sc, M.Sc, Ph.D.). During his Ph.D. (the Chinese University of Hong Kong) and early postdoctoral stages (University of Illinois Chicago), he delved into the mathematical theories and applications of molecular evolution and phylogenetics. In the past few years, his research focus has entirely shifted towards genetic epidemiology and statistical genetics, resulting in significant publication outputs. Chenglong is pleased that these studies are highly relevant to human health and is committed to long-term engagement in this area.

Chenglong's research revolves around investigating the effects of genetic factors on various complex diseases. As the leading author, he has disseminated his findings on major depression (Transl Psychiatry 2017, 2018; J Affect Disord 2017, 2018[2]; Psychiatry Res 2017), cancer (CEBP 2021; Cancers 2021; Cells 2021; Epigenetics 2022), cardiovascular disease (JAHA 2023; JACC Adv 2024), dementia (Alzheimer's & Dementia 2023), age-related macular degeneration (Ophthalmology 2024), women's health (eBioMedicine 2024), and more.

Research interests

  • Genetic Epidemiology
  • Statistical Genetics
  • Bioinformatics
  • Biostatistics

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Mathematics, Ph.D., Chinese University of Hong Kong

Mathematics, M.Sc., Zhejiang University

Research area keywords

  • GWAS
  • Polygenic risk score
  • Ageing
  • Cardiovascular diseases
  • Cancer epidemiology
  • Dementia
  • Genomic epidemiology
  • Major depression
  • Prediction Analysis
  • Heritability
  • Population genetics and genomics
  • Genomic medicine
  • Epigenetics
  • Age-related macular degeneration
  • Risk stratification
  • DNA methylation

Collaborations and top research areas from the last five years

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