Soyeon Kim and Yundan Liao received the ASHG Trainee Research Excellence Awards

Soyeon Kim received the ASHG Trainee Research Excellence Award – Finalist (Postdoctoral)

Yundan Liao received the ASHG Trainee Research Excellence Award – Semifinalist (Predoctoral)

Hailiang Huang received the Pamela Sklar Innovation Award

Hailiang Huang received the Pamela Sklar Innovation Award from the International Society of Psychiatric Genetics.

Danqing Yin joined Huang Lab as a Visiting Graduate Student

Danqing Yin joined Huang Lab as a Visiting Graduate Student on September 9, 2024. Danqing received her master’s degree from University of Sydney.

“Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases” published in Nature Genetics

Statistical fine-mapping helps narrow down a GWAS hit to a smaller set of potentially causal genetic variants and works well on data from relatively homogeneous populations. Kai Yuan, Tian Ge, Hailiang Huang, and colleagues have developed a technique, SuSiEx, for cross-population fine-mapping. The method integrates data from multiple ancestries, models population specific allele frequencies and linkage disequilibrium patterns, and can be applied to GWAS summary statistics. In Nature Genetics, the team showed how SuSiEx improved fine-mapping for various traits in both the UK Biobank and Taiwan Biobank and the fine-mapping of schizophrenia loci across East Asian and European ancestries.

Kai Yuan was awarded the K99/R00 award from NIMH

NIMH awarded Dr. Kai Yuan a K99/R00 award: Whole chromosome fine-mapping integrating diverse ancestries for psychiatric disorders.

Statistical fine-mapping identifies a handful of putative causal variants from hundreds of GWAS loci for psychiatric disorders, but current findings are primarily based on analysis of the European cohort, leading to bias in causal genetic variant discovery and limiting the resolution of findings. The status quo persists due to the lacking of data and the unavailability of suitable methods. Several large international genetic projects, including PUMAS and A-BIG-NET, have recently launched to target non-European populations and make data more accessible. The absence of proper fine-mapping methods for populations with complex genetic structures is a significant hindrance in the field. The candidate proposes to address gaps between the forthcoming data and appropriate methods by developing a suite of open-source statistical methods and publicly available analytical resources. The candidate will: 1) develop a local-ancestry-aware admixed population fine-mapping method, enabling the fine-mapping of entire chromosome data by optimizing the algorithm and effectively managing memory; 2) develop a burden test approach to prioritize putative causal genes for psychiatric disorders by fine-mapping the gene-based burden of Neanderthal introgressed sequences; 3) develop the most inclusive fine-mapping method for psychiatric disorders by integrating fine-mapped results across diverse ancestries. The proposed research and training plan was carefully designed to confer expertise in four domains: 1) psychiatric genetics and psychiatric phenotyping, 2) statistical methods development and software engineering, 3) large-scale Blended Genome and Exome (BGE) sequencing data analysis, 4) admixed population genomic data analysis, and 5) professional development. These skills are fundamental to the candidate’s goal of becoming a leading investigator who develops and applies statistical methods to understand underlying causal genetic factors for psychiatric disorders. In addition to research training, the candidate will take coursework to gain greater expertise in statistical method development, participate in regular seminars, attend workshops and conferences, and gain mentorship and teaching experience. All research will be conducted in the Analytic and Translational Genetics Unit at Massachusetts General Hospital and the Broad Institute with mentorship from renowned scientists Drs. Hailiang Huang, Tian Ge and Jordan Smoller. Additional guidance from leading experts Drs. Benjamin Neale, Kenneth Kendler, Xiaofeng Zhu, and Elizabeth Atkinson will ensure exceptional guidance and support. Overall, the training environment is outstanding, the mentors and advisors are world-class, the proposed studies address an urgent unmet need, and the additional skills gained in this award will poise the candidate to establish independent leadership in inclusive fine-mapping analysis for psychiatric disorders.

 

Yundan Liao joined Huang Lab as a Visiting Graduate Student

Yundan Liao joined Huang Lab as a Visiting Graduate Student on July 29, 2024. Yundan is studying for her Ph.D. at Peking University.

Arsalan Hassan joined Huang Lab as a Visiting Researcher

Arsalan Hassan joined Huang Lab as a Visiting Researcher on April 29, 2024. Arsalan received his doctoral degree from University of Peshawar.

Ruifei Zhu joined Huang Lab as a Computational Associate

Ruifei Zhu joined Huang Lab as a Computational Associate I on March 1st, 2024. Ruifei received her Master’s degrees from Boston University and Imperial College London, and her Bachelor’s degree from Jiangnan University.

 

“Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits” published in Cell Genomics

Working with our collaborators in Taiwan and US, Mingrui Yu, Hailiang Huang and others published “Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits” in Cell Genomics.

Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.

Yunqi Huang joined Huang Lab as a Visiting Graduate Student

Yunqi Huang joined Huang Lab as a Visiting Graduate Student on November 7, 2023. Yunqi Huang is studying for her M.D. at Sichuan University.