Loic Yengo

Dr Loic Yengo is a Professor of Statistical Genomics at The University of Queensland (UQ) and Group Leader of the Statistical Genomics Laboratory within UQ's Institute for Molecular Bioscience. He was awarded a prestigious Snow Medical Research Fellowship in 2024 to dramatically advance the use of genomics to prevent chronic disease such as type 2 diabetes, heart disease and Alzheimer's, with a particular focus on increasing participation of people with diverse ancestries. After completing a PhD in applied mathematics and statistics at the University of Lille (France) in 2014, he joined UQ in 2016 for postdoctoral training in Quantitative and Statistical Genetics. Loic started his own lab in 2020 to investigate the causes and consequences of genetic variation within and between human populations. His group develops and applies novel statistical methods to analyse large volumes of genomic data. Loic's research has contributed to improving understanding of the genetic and phenotypic consequences of non-random mating (inbreeding and assortative mating) in human populations and has led to identifying novel genetic variants associated with complex traits and diseases. Loic was named among the top 40 rising stars of research by The Australian newspaper in 2021 and received the UQ Foundation research excellence award the same year. Loic is the 2022 recipient of the Ruth Stephens Gani Medal of the Australian Academy of Science recognizing outstanding contributions to research in human genetics, and was named in Nature Medicine's 2022 Yearbook among 11 early-career researchers "to watch". In 2024, he was the recipient of the American Society of Human Genetics Early Career Award and a Snow Medical Research Foundation Fellowship to accelerate the deployment of genomic risk prediction in the clinic and improve the benefit of genomic medicine in all populations. Statistical Genomics, Quantitative and Statistical Genetics, genetic variation within and between human populations, genetic and phenotypic consequences of non-random mating (inbreeding and assortative mating), identifying novel genetic variants associated with complex traits and diseases, discovery of genes and biological pathways involved in the etiology of multifactorial diseases such as obesity and type 2 diabetes, genomic risk prediction, genomic medicine

[2026] Why pharmacogenomic biomarkers for chemotherapy-induced peripheral neuropathy fail: a systematic review of genetic associations, replication, and clinical translation [2026] Genetics of skeletal proportions across two different populations [2026] Empirical evaluation of analytic validity of polygenic scores [2026] Genetics of skeletal proportions across two different populations [2026] Genome-wide fine-mapping improves identification of causal variants [2026] Distinct genetic profiles influence body mass index between infancy and adolescence [2026] Contribution to variable clusteringin high dimensional linear regression models [2026] Author Correction: Genome-wide fine-mapping improves identification of causal variants (Nature Genetics, (2026), 58, 4, (940-951), 10.1038/s41588-026-0