Group Leader
WANG Wallace (Minxian) is a professor and principal investigator at the Beijing Institute of Genomics, Chinese Academy of Sciences. Before accepting a faculty position, he was a computational biologist in the Medical and Population Genetics Program of the Broad Institute of MIT and Harvard, working with Dr. Amit Khera and Dr. Sekar Kathiresan in human cardiovascular genetics and genetic risk prediction. He completed a postdoctoral fellowship supervised by Dr. Martin Pollak (academician of US National Academy of Sciences) at the Harvard Medical school. He completed his doctoral studies in computational biology and human population genetics at the University of Chinese Academy of Sciences/CAS-MPG Partner Institute for Computational Biology. He also holds a bachelor’s degree in animal sciences from Jilin University, China.
His lab is interested in disease risk variants and risk genes profiling by genome-wide association studies, genetic risk prediction, precision medicine, and making large-scale biomedical data sounds through statistical genetic modeling and artificial intelligence algorithms, with the ultimate goal of assisting in guiding precise disease prevention, leading to healthier lifestyles, and in the discovery of new therapeutic targets.
Introduction
Our lab is making precision medicine a reality through the catalytic power of big genomic data, statistical genetics, and artificial intelligence. We are actively working on the following projects:
1. New disease risk gene and novel biomarker discovery
We have extensive experiences, solid genetic knowledge, and professional data analyzing skills on disease risk gene and novel biomarker discoveries (Zhang#, Wang#* et al. 2018, PNAS; Wang et al. 2019, J Am Soc Nephrol; Chun*, Wang* et al. 2020, KI Reports; Khetarpal*, Wang* et al. 2019，N. Engl. J. Med ). We will analyze large-scale biomedical data to profile the associations between genetics and phenotypes, which include but are not limited to the associations from, large-scale genotyping data, sequencing data, in-depth phenotyping data by clinical images, transcriptomics data, proteomics data, biomarkers, and electronic health records data from biobanks, to build a comprehensive “geno-pheo” association map. From this map, we will fine-map the causal variants and genes for disease etiology and will use Mendelian randomization to distinguish causations from associations.
2. Disease risk prediction
Building on our previous works on disease risk prediction (Wang et al. 2020 J Am Coll Cardiol.; Emdin*, Bhatnagar*, Wang* et al. 2020, and Dron*, Wang* et al. 2021, Circ Genomic Precis Med.; Patel*, Wang* et al. 2020, JAMA network open; Fahed*, Wang*, homburger*, et al. 2020，Nat. Commun)，we will develop novel statistical genetics and deep-learning based risk prediction models to quantify the risk information jointly from disease risk factors, genetic mutations, biomarkers, latent features derived from raw clinical imaging data, correlations from different diseases, and genomic annotations. The models will have the advantages of integrating inherited innate genetic risks and late age responses to developmental and environmental stimuli. As a result, the prediction will be more powerful and precise. Furthermore, taking advantage of the large-scale data from the Chinese people, we will increase model transferability for East Asian populations that are tailored, specific, and precise to the Chinese people.
Publications
(*Co-first author, #Co-corresponding author)
1. Wang, Minxian, Vivian S. Lee-Kim, Deepak S. Atri, Nadine H. Elowe, et al. Rare, Damaging DNA Variants in CORIN and Risk of Coronary Artery Disease: Insights From Functional Genomics and Large-Scale Sequencing Analyses. Circulation: Genomic and Precision Medicine (Oct. 2021). doi: 10.1161/CIRCGEN. 121.003399.
2. Veryan Codd, Qingning Wang, [...], Wang, Minxian, et al. Polygenic basis and biomedical consequences of telomere length variation. Nature Genetics 2021 53:10 53.10 (Oct. 2021), pp. 1425–1433. doi: 10.1038/ s41588-021-00944-6.
3. Aniruddh P. Patel, Wang, Minxian, Uri Kartoun, Kenney Ng, and Amit V. Khera. Quantifying and Understanding the Higher Risk of Atherosclerotic Cardiovascular Disease Among South Asian Individuals. Circulation (Aug. 2021), pp. 410–422. doi: 10.1161/CIRCULATIONAHA.120.052430.
4. María José Pérez-Sáez, Audrey Uffing, [...], Wang, Minxian, et al. Immunological Impact of a Gluten- Free Dairy-Free Diet in Children With Kidney Disease: A Feasibility Study. Frontiers in Immunology 12.June (2021), pp. 1–11. doi: 10.3389/fimmu.2021.624821.
5. Yudong Cai, Jialiang Yang, Tao Huang, and Wang, Minxian. Editorial: Computational Methods in Predicting Complex Disease Associated Genes and Environmental Factors. Frontiers in Genetics (2021). doi: 10.3389/fgene.2021.679651.
6. Jacqueline S Dron*, Wang, Minxian*, Aniruddh P Patel, Uri Kartoun, Kenney Ng, Robert A Hegele, and Amit V Khera. Genetic Predictor to Identify Individuals With High Lipoprotein(a) Concentrations. Circulation: Genomic and Precision Medicine (Feb. 2021), CIRCGEN120003182. doi: 10.1161/CIRCGEN.120. 003182. (Equal contributions).
7. Patricia L Weng, Amar J Majmundar, [...], Wang, Minxian, et al. De novo TRIM8 variants impair its protein localization to nuclear bodies and cause developmental delay, epilepsy, and focal segmental glomerulosclerosis. American journal of human genetics 108.2 (Feb. 2021), pp. 357–367. doi: 10.1016/j. ajhg.2021.01.008.
8. Wang, Minxian, Ramesh Menon, Sanghamitra Mishra, Aniruddh P. Patel, et al. Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians. Journal of the American College of Cardiology 76.6 (2020), pp. 703–714. doi: 10.1016/j.jacc.2020.06.024.
9. Akl C Fahed*, Wang, Minxian*, Julian R Homburger*, Aniruddh P Patel, et al. Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions. Nature communications 11.1 (2020), p. 3635. doi: 10.1038/s41467-020-17374-3. (Equal contributions).
10. Aniruddh P. Patel*, Wang, Minxian*, Akl C. Fahed, Heather Mason-Suares, et al. Association of Rare Pathogenic DNA Variants for Familial Hypercholesterolemia, Hereditary Breast and Ovarian Cancer Syndrome, and Lynch Syndrome With Disease Risk in Adults According to Family History. JAMA network open 3.4 (2020), e203959. doi: 10.1001/jamanetworkopen.2020.3959. (Equal contributions).
11. Connor A. Emdin*, Pallav Bhatnagar*, Wang, Minxian*, Sreekumar G. Pillai, et al. Genome-wide polygenic score and cardiovascular outcomes with evacetrapib in patients with high-risk vascular disease: A nested case-control study. Circulation: Genomic and Precision Medicine February (2020), pp. 30–32. doi: 10.1161/CIRCGEN.119.002767. (Equal contributions).
12. Justin Chun*, Wang, Minxian*, Maris S. Wilkins, Andrea U. Knob, Ava Benjamin, Lihong Bu, and Martin R. Pollak. Autosomal Dominant Tubulointerstitial Kidney Disease-Uromodulin Misclassified as Focal Segmental Glomerulosclerosis or Hereditary Glomerular Disease. Kidney International Reports 5.4 (2020), pp. 519–529. doi: 10.1016/j.ekir.2019.12.016. (Equal contributions).
13. Aniruddh P. Patel, Wang, Minxian, James P. Pirruccello, Patrick T. Ellinor, Kenney Ng, Sekar Kathiresan, and Amit V. Khera. Lp(a) (Lipoprotein[a]) Concentrations and Incident Atherosclerotic Cardiovascular Disease. Arteriosclerosis, Thrombosis, and Vascular Biology December (2020), pp. 1–10. doi: 10.1161/ atvbaha.120.315291.
14. James P Pirruccello, Alexander Bick, Wang, Minxian, Mark Chaffin, et al. Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy. Nature communications 11.1 (2020), p. 2254. doi: 10.1038/s41467-020-15823-7.
15. Di Feng, Mukesh Kumar, [...], Wang, Minxian, et al. Phosphorylation of ACTN4 leads to podocyte vulnerability and proteinuric glomerulosclerosis. Journal of the American Society of Nephrology 31.7 (2020), pp. 1479–1495. doi: 10.1681/ASN.2019101032.
16. Sumeet A. Khetarpal*, Wang, Minxian*, and Amit V. Khera. Volanesorsen, familial chylomicronemia syndrome, and thrombocytopenia. New England Journal of Medicine 381.26 (2019), pp. 2582–2584. doi: 10.1056/NEJMc1912350. (Equal contributions).
17. Wang, Minxian, Justin Chun, Giulio Genovese, Andrea U Knob, et al. Contributions of rare gene variants to familial and sporadic FSGS. Journal of the American Society of Nephrology 30.9 (2019), pp. 1625–1640. doi: 10.1681/ASN.2019020152.
18. Amit V. Khera, Heather Mason-Suares, Deanna Brockman, Wang, Minxian, et al. Rare Genetic Variants Associated With Sudden Cardiac Death in Adults. Journal of the American College of Cardiology 74.21 (2019), pp. 2623–2634. doi: 10.1016/j.jacc.2019.08.1060.
19. Cristian Riella, Tobias A. Siemens, Wang, Minxian, Rodrigo P. Campos, et al. APOL1-Associated Kidney Disease in Brazil. Kidney International Reports 4.7 (2019), pp. 923–929. doi: 10.1016/j.ekir.2019.03. 006.
20. Jia-Yue Zhang*, Wang, Minxian*, Lei Tian, Giulio Genovese, et al. UBD modifies APOL1 -induced kidney disease risk. Proceedings of the National Academy of Sciences (2018), p. 201716113. doi: 10.1073/ pnas.1716113115. (Equal contributions, joint corresponding author).
21. Di Feng, Jacob Notbohm, Ava Benjamin, Shijie He, Wang, Minxian, Lay-hong Ang, and Minaspi Bantawa. Disease-causing mutation in α-actinin-4 promotes podocyte detachment through maladaptation to periodic stretch. Proceedings of the National Academy of Sciences 115.7 (2018), pp. 1517–1522. doi: 10.1073/pnas.1717870115.
22. Yungang He, Wang, Minxian, Xin Huang, Ran Li, Hongyang Xu, Shuhua Xu, and Li Jin. A probabilistic method for testing and estimating selection differences between populations. Genome Research 25.12 (Dec. 2015), pp. 1903–1909. doi: 10.1101/gr.192336.115.
23. Bin Zhou, Hui Dong, [...], Wang, Minxian, et al. Composition and Interactions of Hepatitis B Virus Quasispecies Defined the Virological Response during Telbivudine Therapy. Scientific Reports 5.July (2015), pp. 1–10. doi: 10.1038/srep17123.
24. Wang, Minxian, Xin Huang, Ran Li, Hongyang Xu, Li Jin, and Yungang He. Detecting Recent Positive Selection with High Accuracy and Reliability by Conditional Coalescent Tree. Molecular biology and evolution 31.11 (Aug. 2014), pp. 3068–3080. doi: 10.1093/molbev/msu244.
25. Yueming Jiang*, Wang, Minxian*, Hongxiang Zheng, Wei R Wang, Li Jin, and Yungang He. Resolving ambiguity in the phylogenetic relationship of genotypes A, B, and C of hepatitis B virus. BMC evolutionary biology 13.1 (Jan. 2013), p. 120. doi: 10.1186/1471-2148-13-120. (Equal contributions).
26. Ran Li, Wang, Minxian, Li Jin, and Yungang He. A Monte Carlo permutation test for random mating using genome sequences. PloS one 8.8 (Jan. 2013), e71496. doi: 10.1371/journal.pone.0071496.
Staff scientists
Dr. WANG Fei, wangfei@big.ac.cn
Graduate Students
A Yunga, ayunga@big.ac.cn
CHEN Qiuli, chenqiuli@big.ac.cn
LI Jia, lijia@big.ac.cn
