CHAN, K. H. Katie

CHAN, K. H. Katie (陳紀行)

Associate Professor (Department of Biomedical Sciences & Department of Electrical Engineering)

PhD (UCLA)

MPH (USC)

BEng (HKU)

  • 1A-313, 3/F, Block 1, To Yuen Building
  • +852 3442-6661
  • +852 3442-0549
  • CityU Scholars
  • Lab Website
  • Genetic and molecular epidemiology • Systems Biology • Computational biology • Bioinformatics • Diseases prediction and prevention

Prof. Kei Hang Katie Chan obtained her Bachelor of Information Engineering degree from the University of Hong Kong. She then received her Master of Public Health in Epidemiology and Biostatistics from the University of Southern California. With the Burroughs Wellcome Fund Inter-school Training Program in Metabolic Diseases Fellowship, she attained the Doctor of Philosophy in Epidemiology from the University of California, Los Angeles (UCLA) studying the genetic architecture of metabolic diseases, particularly type 2 diabetes (T2D) and cardiovascular diseases (CVD). After several years of postdoctoral training at UCLA and Brown University, she identified several shared molecular pathways and gene networks between T2D and CVD. Then, she returned to her home town, Hong Kong and joined the Hong Kong Institute of Diabetes and Obesity in the Chinese University Hong Kong (CUHK) as a Research Assistant Professor in 2016. She is also an Adjunct Assistant Professor at the Center for Global Cardiometabolic Health in the Department of Epidemiology in Brown University. In 2017, she was invited to be engaged as Assistant Professor (by courtesy) in the Department of Medicine and Therapeutics in CUHK. While at CUHK, she mainly investigated the genetic determinants of type 2 diabetes and its comorbidities. In 2018, she joined the Departments of Biomedical Sciences and Electrical Engineering in the City University of Hong Kong.

Research Interests

Prof. Chan’s research interests include Genetic and Molecular Epidemiology, Systems Biology, Computational Biology and Bioinformatics. Her research focuses on studying the complex network of multifaceted diseases with major global burden by integrating variants in multiple omic levels, biomarkers and environmental data collected in diverse populations, which may deliver a novel preventive approach, diagnoses, and treatment. Below are her current research themes:

  1. Diseases determinants identification - including but not limited to genetic variants, copy number variations, molecular pathways, gene networks and biomarkers
  2. Diseases prediction and prevention
  3. Bioinformatics tools development

Publication List

  1. J. Liu, E. L. Chou, K. K. Lau, P. Y. M. Woo, T. K. Wan, R. Huang, K. K. Chan. Mendelian randomization-based exploration of red blood cell distribution width and mean corpuscular volume with risk of haemorrhagic strokes. Human Genetics and Genomics Advances. Volume 3, Issue 4, 13 October 2022, 100135.
  2. R. X. Huang, D. Siriwanna, W. C. Cho, X. T. Huang, T. K. Wan τ, Y. R. Du, A. N. Bennett τ, Q. E. He, J. Liu, K. K. Chan. Lung adenocarcinoma-related target gene prediction and drug repositioning. Front. Pharmacol., 23 August 2022. https://doi.org/10.3389/fphar.2022.936758
  3. Q. He, A. N. Bennett, J. Liu τ, B. Fan, X. Han, L. Cheng, Y. Chen, X. Yang, K. K. Chan. Exploring Lead Genetic Architecture shared Between Schizophrenia and Cardiometabolic Traits. BMC Genomics (in press).
  4. A. N. Bennett, J. Rainford, X. Huang, Q. He, K. K. Chan. Canary: An Automated tool for the conversion of MaCH Imputed Dosage files to PLINK files. BMC Bioinformatics. 2022 Jul 27;23(1):304.doi: 10.1186/s12859-022-04822-8.
  5. J. Liu, E. L. Chou, K. K. Lau, P. Y. M. Woo, J. Li, K. K Chan. Machine learning algorithms identify demographics, dietary features, and blood biomarkers associated with stroke records. J Neurol Sci. 2022 Jul 9;440:120335.doi: 10.1016/j.jns.2022.120335.
  6. J. Sheng, J. Liu, K. K. Chan. Evaluating the Causal Effects of Gestational Diabetes Mellitus, Heart Disease, and High Body Mass Index on Maternal Alzheimer’s disease and Dementia: Multivariable Mendelian Randomization. Front Genet. 2022 Jun 21;13:833734. doi: 10.3389/fgene.2022.833734. eCollection 2022.
  7. Q. He, A. N. Bennett, B. Fan, X. Han, J. Liu, K.C.H. Wu, R. Huang, J.C.N. Chan, K. K. Chan. Assessment of Bidirectional Relationships between Leisure Sedentary Behaviors and Neuropsychiatric Disorders: A Two-Sample Mendelian Randomization Study. Genes (Basel). 2022 May 27;13(6):962. doi: 10.3390/genes13060962.
  8. T. K. Wan, R. Huang, T. W,. Tulu, J. Liu, A. Vodencarevic, C. W. Wong, K. K. Chan. Identifying Predictors of COVID-19 Mortality Using Machine Learning. Life 2022, 12(4), 547; https://doi.org/10.3390/life12040547
  9. J. Li, Q. Yang, H. D. Sesso, V. W. Zhong, K. K. Chan, T. E. Madsen, G. D. Papandonatos, T. Zheng, W. C. Wu, Y. Song, X. Yu, S. Liu. Famine and Trajectories of Body Mass Index, Waist Circumference, and Blood Pressure in Two Generations: Results From CHNS From 1993-2015. Hypertension 2021 Dec. 7; HYPERTENSIONAHA12119022. Doi: 10.1161/HYPERTENSIONAHA.121.18022.
  10. The Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC), 405 authors, including, J. Chen, C. N. Spracklen, G. Marenne, A. Varshney, L. J. Corbin, J. Luan, S. M. Willems, Y. Wu, X. Zhang, M. Horikoshi, T. S. Boutin, R. M., J. Wage, R. Li-Gao, K. K. Chan, J. Yao, M. D. Anasanti, A. Y. Chu, A. Claringbould, J. Heikkinen, J. Hong, J. J, Hottenga, S. Huo, M. A. Kaakinen, T. Louie, W. März, H. Moreno-Macias, A. Ndungu, S. C. Nelson, I. M. Nolte, K. E. North, C. K. Raulerson, D. Ray, R. Rohde, D. Rybin, C. Schurmann, X. Sim, L. Southam, I. D. Stewart, C. A. Wang, Y. Wang, P. Wu, W. Zhang, T. S. Ahluwalia, E. V. R. Appel, L. F. Bielak, J. A. Brody, N. P. Burtt, C. P. Cabrera, B. E. Cade. The trans-ancestral genomic architecture of glycemic traits. Nature Genetics, 53(6), 31 May 2021, pp 840-860, doi: https://doi.org/10.1038/s41588-021-00852-9.
  11. K. Lo, Q. Liu, M. Allison, Y.Q. Feng, K. K. Chan, L. Phillips, J. Manson, S. Liu. Prospective associations of waist-to-height ratio with cardiovascular events of postmenopausal women. Diabetes Care, 2019.
  12. K.E. Grinde, Q. Qi, T.A. Thornton, S. Liu, A.H. Shadyab, K. K. Chan, A. P. Reiner, T. Sofer. Generalizing Polygenic Risk Scores from Europeans to Hispanics/Latinos. Genetic Epidemiology, 2019.
  13. X Lin, K. K. Chan, Y. T. Huang, X. Luo, L. Liang, J. Wilson, A. Correa, D. Levy, S. Liu. Genetic Determinants for Leisure-Time Physical Activity. Med Sci Sports Exerc. 2018 Aug;50(8):1620-1628.
  14. A. Goto, B. H. Chan, K. K. Chan, C. Lee, S. C. Nelson, A. Crenshaw, E. Bookman, K. L. Margolis, M. M. Sale, the MEDIA Consortium, M. C. Y. Ng, A. P. Reiner, S. Liu. Genetic variants in sex hormone pathways and the risk of type 2 diabetes among African-American, Hispanic-American, and European-American postmenopausal women in the United States. J. Diabetes. 8 Feb 2018. DOI: 10.1111/1753-0407.12648
  15. L. Shu*, K. K. Chan*, G. Zhang, T. Huan, Z. Kurt, Y. Zhao, V. Codoni, J. Yang, J. G. Wilson, X. Luo, D. Levy, A. J. Lusis, S. Liu, X. Yang. Shared genetic regulatory networks for cardiovascular disease and type 2 diabetes in multiple populations of diverse ethnicities in the United States. PLoS Genet. 2017 Sep 28;13(9):e1007040. doi: 10.1371/journal.pgen.1007040. *L. Shu and K.K. Chan contributed equally to the manuscript.
  16. J. M. Pedersen, E. Budtz-Jorgensen, A. D. Roos, L. Garcia, R. Lund, N. H. Rod, C. Kroenke, K. K. Chan, S. Liu, Y. Michael. Understanding the relation between socioeconomic position and inflammation in post-menopausal women: education, income and occupational prestige. Eur J Public Health. 2017 May 28. doi: https://doi.org/10.1093/eurpub/ckx070.
  17. M. Huang, J. Liu, X. Lin, A. Goto, Y. Song, L. F. Tinker, K. K. Chan, S. Liu. Relationship between dietary carbohydrates intake and circulating sex hormone-binding globulin levels in postmenopausal women. J Diabetes. 2017 Mar 17. doi: 10.1111/1753-0407.12550.
  18. R. Liu, Y. Zou, J. Hong, M. Cao, B. Cui, H. Zhang, M. Chen, J. Shi, T. Ning, S. Zhao, W. Liu, H. Xiong, C. Wei, Z. Qiu, W. Gu, Y. Zhang, Y. Zhang, W. Li, L. Miao, Y. Sun, M. Yang, R. Wang, Q. Ma, M. Xu, T. Wang, K. K. Chan, X. Zuo, H. Chen, L. Qu, X. Lai, S. Duan, B. Song, Y. Bi, S. Liu, W. Wang, G. Ning, J. Wang. Rare Loss-of-function Variants in NPC1 Predispose to Human Obesity. Diabetes. 2017 Jan 27. pii: db160877. doi: 10.2337/db16-0877.
  19. H. Zhou, J. Blangero, TD Dyer, K. K. Chan, K. Lange, EM Sobel. Fast Genome-wide QTL Association Mapping on Pedigree and Population Data. Genet Epidemiol. 2016 Dec 12. doi: 10.1002/gepi.21988.
  20. S.P. Sajuthi, N.I. Sharma, J.W. Chou, N.D. Palmer, D.R. McWilliams, J. Beal, M.E. Comeau, L. Ma, J. Calles-Escandon, J. Demons, S. Rogers, K. Chreery, L. Menon, E. Kouba, D. Davis, M. Burris, S.J. Byerly, M.C. Ng, N.M. Maruthur, S.R. Latel, L.F. Bielak, L.A. Lange, X. Guo, M.M. Sale, K. K. Chan, K.L. Monda, G.K. Chen, K. Taylor, C. Palmer, T.L. Edwards, K.E. North, C.A. Haiman, D.W. Bowden, B.I. Freedman, C.D. Langefeld, S.K. Das. Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity. Human Genetics. May 2016.
  21. M. Cora, S. Candille, Q. Duan, K. K. Chan, Y. Li, C. Kooperberg, A. Reiner, H. Tang. Leveraging Multi-Ethnic Evidence for Mapping Complex Traits in Minority Populations: An Empirical Bayes Approach. American Journal of Human Genetics. May 2015.
  22. K. K. Chan, S. Chacko, Y. Song, M. Cho, C. Eaton, W. Hu, S. Liu. Genetic variation in Magnesium-related ion channels may affect diabetes risk among African American and Hispanic American women. Journal of Nutrition. First published January 7, 2015. doi: 10.3945/jn.114.203489.
  23. K. K. Chan, Y. Huang, Q. Meng, C. Wu, A. Reiner, E. Sobel, L. Tinker, A. Lusis, X. Yang, S. Liu. Shared molecular pathways and gene networks for cardiovascular disease and type 2 diabetes in women across diverse ethnicities. Circ Cardiovasc Genet. 2014 Nov 4. pii: CIRCGENETICS. 114.000676.
  24. K. K. Chan*, T. Niu*, Y. Ma, N. You, Y. Song, E. Sobel, Y. Hsu, R. Balasubramanian, Y. Qiao, L. Tinker, S. Liu. Common Genetic Variants in Peroxisome Proliferator-Activated Receptor Gamma (PPARG) and Type 2 Diabetes Risk among Women’s Health Initiative Postmenopausal Women. J Clin Endocrinol Metab. 2013 Feb 5. *K.K. Chan and T. Niu contributed equally to the manuscript.
  25. K. K. Chan*, K. Brennan*, N. You, X. Lu, Y. Song, Y. Hsu, G. Chaudhuri, L. Nathan, L. tinker, S. Liu. Common variations in the genes encoding C-reactive protein, tumor necrosis factor-alpha, and interleukin-6, and the risk of clinical diabetes in the Women's Health Initiative Observational Study. Clin Chem. 2011 Feb; 57(2):317-25. *K.K. Chan and K. Brennan contributed equally to the manuscript.
  26. K. K. Chan, Y. Song, Y. Hsu, N. You, L. Tinker, S. Liu. Common Genetic Variants in Fatty Acid Binding Protein-4 (FABP4) and Clinical Diabetes Risk in the women’s Health Initiative Observational Study. Obesity (Silver Spring). 2010 Jan 28.
  27. S.K.P Lau, P.C.Y. Woo, M.Y. Mok, J.L.L. Teng, V.K.P. Tam, K.K. Chan, K.Y. Yuen. Haemophilus segnis is an important cause of ‘non-influenzae’ Haemophilus bacteremia: characterization by 16S RNA gene sequencing. Journal of Clinical Microbiology, Feb. 2004, pp. 877-880.

1 July 2024

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