Liu Lab

Publications

Preprints

# represents corresponding/senior author, * represents mentee  (student  or postdoc) under Dr. Liu's supervision

  1. Ye, T., Liu, Z., Sun, B., Tchetgen Tchetgen, E., (2023+). GENIUS-MAWII: For Robust Mendelian Randomization with Many Weak Invalid Instruments. (Minor Revision)
  2. Wang, L., Babushkin, N., Liu, Z., Liu, X.# (2023+). Trans-eQTL mapping in gene sets identifies network effects of genetic variants. BioRxiv. 
  3. Chuwdhury, G.,  Guo, Y.*,  Cheung, C.,   Lam, K.,  Kam, N.,  Liu, Z.#,  Dai, W.#, (2023+) ImmuneMirror: a Machine Learning-based Integrative Pipeline and Web Server for Neoantigen Prediction BioRxiv 2023.02.09.527828; doi: https://doi.org/10.1101/2023.02.09.527828 (Minor Revision)
  4. Yao, M.*, Miller, G.W., Vardarajan, B. N., Baccarelli, A. A., Guo, Z.#, and Liu, Z.# (2023). Robust mendelian randomization analysis by automatically selecting valid genetic instruments with applications to identify plasma protein biomarkers for Alzheimer's disease. medRxiv.
  5.  "All valid instruments are alike; each invalid instrument is invalid in its own way"-- Zhonghua Liu
  6. Chen, Y., Lam, K. F.,  Liu, Z. (2023). High-dimensional Feature Screening for Nonlinear Associations With Survival Outcome Using Restricted Mean Survival Time. arXiv preprint arXiv:2305.05199.
  7. Xihao Li, Han Chen, Margaret Sunitha Selvaraj, Eric Van Buren, Hufeng Zhou, Yuxuan Wang, Ryan Sun, Zachary R. McCaw, Zhi Yu, Donna K. Arnett, Joshua C. Bis, John Blangero, Eric Boerwinkle, Donald W. Bowden, Jennifer A. Brody, Brian E. Cade, April P. Carson, Jenna C. Carlson, Nathalie Chami, Yii-Der Ida Chen, Joanne E. Curran, Paul S. de Vries, Myriam Fornage, Nora Franceschini, Barry I. Freedman, Charles Gu, Nancy L. Heard-Costa, Jiang He, Lifang Hou, Yi-Jen Hung, Marguerite R. Irvin, Robert C. Kaplan, Sharon L.R. Kardia, Tanika Kelly, Iain Konigsberg, Charles Kooperberg, Brian G. Kral, Changwei Li, Ruth J.F. Loos, Michael C. Mahaney, Lisa W. Martin, Rasika A. Mathias, Ryan L. Minster, Braxton D. Mitchell, May E. Montasser, Alanna C. Morrison, Nicholette D. Palmer, Patricia A. Peyser, Bruce M. Psaty, Laura M. Raffield, Susan Redline, Alexander P. Reiner, Stephen S. Rich, Colleen M. Sitlani, Jennifer A. Smith, Kent D. Taylor, Hemant Tiwari, Ramachandran S. Vasan, Zhe Wang, Lisa R. Yanek, Bing Yu, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Kenneth M. Rice, Jerome I. Rotter, Gina M. Peloso, Pradeep Natarajan, Zilin Li#, Zhonghua Liu#, Xihong Lin# (2023+). A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. bioRxiv 2023.10.30.564764; doi: https://doi.org/10.1101/2023.10.30.564764
  8.  Jinglan Dai, Yixin Zhang, Zaiming Li, Hongru Li, Sha Du, Dongfang You, Ruyang Zhang, Yang Zhao, Zhonghua Liu, David C. Christiani, Feng Chen, Sipeng Shen. (2023+) Boosting the power of rare variant association studies by imputation using large-scale sequencing population. medRxiv 2023.10.28.23297722; doi: https://doi.org/10.1101/2023.10.28.23297722

Published

# represents corresponding author, * represents mentee  (student  or postdoc) under Dr. Liu's supervision

Statistical Methodology

Robust Mendelian Randomization for Causal Inference with Invalid Instruments 

  1. Sun, B.,  Liu, Z., Tchetgen Tchetgen, E., (2023). Semiparametric Efficient G-estimation with Invalid Instrumental Variables . Biometrika. Volume 110, Issue 4, December 2023, Pages 953–971,
  2.  Liu, Z., Ye, T., Sun, B., Schooling, M., Tchetgen Tchetgen, E., (2022). Mendelian randomization mixed-scale treatment effect robust identification and estimation for causal inference Biometrics, 79, 2208–2219.
  3. Xu, S.*, Wang P., Fung, W.K., Liu, Z.#, (2022). A Novel Penalized Inverse-Variance Weighted Estimator for Mendelian Randomization with Applications to COVID-19 Outcomes.  Biometrics, 79, 2184–2195.
  4. Wang, A*., Liu, W*, Liu, Z.#, (2022).  A Two-Sample Robust Bayesian Mendelian Randomization Method Accounting for Linkage Disequilibrium and Idiosyncratic Pleiotropy with Applications to the COVID-19 Outcome.  Genetic Epidemiology 46, 159– 169. https://doi.org/10.1002/gepi.22445
  5. Xu, S.*, Fung, W.K.#, Liu, Z.#, 2021.  MRCIP: A robust Mendelian randomization method accounting for correlated and idiosyncratic pleiotropy. Briefings in Bioinformatics. DOI: https://doi.org/10.1093/bib/bbab019.

Causal Mediation Analysis with Applications in Social and Biomedical Sciences

  1.  Xu, M.*, Feng, R.*, Liu, Z.*, Zhou, X.*,  Chen, Y., Cao, Y., Valeri, L. Li, Z., Liu, Z., Cao, S.,Liu, Q., Xie, S., Chang E., Jia, W., Shen, J., Yao, Y., Cai, Y., Zhegn, Y., Zhang, Z., Huang, G., Ernberg, I., Tang, M., Ye, W., Adami, H., Zeng, Y., Lin, X. (2023).  Host genetic variants, Epstein-Barr virus subtypes and the risk of nasopharyngeal carcinoma: An assessment of interaction and mediation. Cell Genomics (accepted). 
  2. Zhou, Y.*, Wang, W.*, Hu, T., Tong, J., Liu, Z#. (2023) Causal mediation analysis for an ordinal outcome with multiple mediators. Structural Equation Modeling-A Multidisciplinary Journal.
  3. Tian, P*, Yao, M*, Huang T, Liu Z#. (2022). CoxMKF: A knockoff  filter for high-dimensional mediation analysis with a survival outcome in epigenetic studies. Bioinformatics btac687, https://doi.org/10.1093/bioinformatics/btac687  
  4. Xu, S*., Liu, L.# and Liu, Z.#  (2022) DeepMed: Semiparametric causal mediation analysis with debiased deep learning.  The Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 35, pp. 28238-28251. (Acceptance rate: 25.6% with a total of 10,411 full paper submissions.)
  5. Wang, W.W.*,  Yu, P., Zhou, Y., Tong, T., Liu, Z., (2021). Equivalence of two least-squares estimators for indirect effects. Current Psychology. DOI: https://doi.org/10.1007/s12144-021-02034-6.
  6. Wang, W.W.*, Xu, J., Schwartz, J., Baccarelli, A., Liu, Z.#, (2021). Causal mediation analysis with latent subgroups.  Statistics in Medicine. 40( 25): 5628– 5641. DOI:  https://doi.org/10.1002/sim.9144.
  7. Liu, Z.#, Shen, J., Barfield, R., Schwartz, J., Baccarelli, A., Lin, X., (2021). Large-Scale hypothesis testing for causal mediation effects with applications in genome-wide epigenetic studies.  Journal of the American Statistical Association, 117(537), 67-81, DOI: 10.1080/01621459.2021.1914634 
  8. Luo, X., Schwartz, J., Baccarelli, A., Liu, Z.#, 2020. Testing cell-type-specific mediation effects in genome-wide epigenetic studies, Briefings in Bioinformatics, https://doi.org/10.1093/bib/bbaa131.

Statistical Genetics and Genomics, Genetic Epidemiology

  1.  Liu, Y., Liu, Z., Lin, X. Ensemble methods for testing a global null. (2023) Journal of the Royal Statistical Society: Series B (Statistical Methodology), qkad131, https://doi.org/10.1093/jrsssb/qkad131 
  2. Yang, J.*, Xu, Y.*, Yao, M.*, Wang G., Liu, Z.#. (2023). ERStruct: A Python Package for Inferring the Number of Top Principal Components from Whole Genome Sequencing Data. BMC Bioinformatics.
  3. Xu, Y.*, Liu, Z.#,  Yao, J., (2022). ERStruct: An eigenvalue ratio approach to inferring population structure from whole genome sequencing data. Biometrics, 79, 891–902.  https://doi.org/10.1111/biom.13691
  4. Tian, P*, Hu, Y, Liu, Z.# and Zhang, Y.# (2022). Grace-AKO: A Novel and Stable Knockoff Filter for Variable Selection Incorporating Gene Network Structures BMC Bioinformatics 23, 478.
  5.  Liu, W.*, Xu, Y.*, Wang, A*., Huang, T.#, Liu, Z.#, (2021). The Eigen Higher Criticism and Eigen Berk-Jones Tests for Multiple Trait Association Studies based on GWAS Summary Statistics.  Genetic Epidemiology, 46, 89– 104. https://doi.org/10.1002/gepi.22439
  6. Liu, Z., Barnett, I., Lin, X., 2020. A comparison of principal component methods between multiple phenotype regression and multiple SNP regression in genetic association studies, The Annals of Applied Statistics, 14(1), pp.433-451. 
  7. Liu, Z. and Lin, X., 2019. A geometric perspective on the power of principal component association tests in multiple phenotype studies,  Journal of the American Statistical Association, 114(527), pp.975-990. 
  8. Liu, Z. and Lin, X., 2018. Multiple phenotype association tests using summary statistics in genome-wide association studies. Biometrics, 74(1), pp.165-175.

Computer Science

  1. Wang W.W.*, Lu, J., Tong, T., Liu, Z. (2022). Debiased Learning and Forecasting of First Derivative. Knowledge-Based Systems.  DOI: https://doi.org/10.1016/j.knosys.2021.107781.  (IF=8.038, Computer Science-Artificial Intelligence 16 out of 139).

Health Science Research

  1.  Li, Y., Zhang, L, Zeng, Z.,  Zhuang, Z., Wang, W., Song, Z., Zhao, Y., Dong, X., Xiao, W., Huang, N., Jia, J., Liu, Z., Qi, L., Li, L., Huang, T., (2023). Polysocial and Polygenic Risk Scores and All-cause Dementia, Alzheimer's disease, and Vascular Dementia. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences, glad262, https://doi.org/10.1093/gerona/glad262.
  2. Kampaktsis P. N., Bohoran, T. A., McLaughlin L.,  Leb J., Liu Z., Moustakidis S., Siouras A., Singh A., McCann G. P., Giannakidis A. (2023). An attention-based deep learning method for right ventricular quantification using 2D echocardiography: feasibility and accuracy. Echocardiography Journal (accepted). 
  3. Song, Z, Wang, W, Zhao, Y, Xiao, W., Du, J., Liu, Z., Huang T., Tang Y. (2023). Observational and genetic associations of adiposity with cardiopulmonary multimorbidity: Linear and nonlinear Mendelian randomization analysis. Obesity (Silver Spring). 1-11. doi:10.1002/oby.23934
  4. Wang W, Huang N, Zhuang Z, Song Z, Li Y, Dong X, Xiao W, Zhao Y, Jia J, Liu Z, Qi L, Huang T.  (2023) Identifying Potential Causal Effects of Telomere Length on Health Outcomes: A Phenome-Wide Investigation and Mendelian Randomization Study, The Journals of Gerontology: Series A, 2023;, glad128, https://doi.org/10.1093/gerona/glad128
  5. Zhuang Z., Dong X., Jia J., Liu Z., Huang T., Qi L., PhD, (2023) Sleep patterns, plasma metabolome and risk of incident type 2 diabetes, The Journal of Clinical Endocrinology & Metabolism, dgad218, https://doi.org/10.1210/clinem/dgad218
  6. Huang X, Yao M*, Tian P, Wong J, Li, Z, Liu Z#, Zhao J#.  (2023). Shared genetic etiology and causality between COVID-19 and venous thromboembolism: evidence from genome-wide cross trait analysis and bi-directional Mendelian randomization study Communications Biology.
  7. Alameda L, Liu Z, Sham P, et al.(2023) Exploring the mediation of DNA methylation across the epigenome between childhood adversity and First Episode of Psychosis – findings from the EU-GEI study. Molecular Psychiatry, https://doi.org/10.1038/s41380-023-02044-9.
  8. Huang, N., Zhuang, Z., Song, Z., Wang, W., Li, Y., Zhao, Y., Xiao, W., Dong, X., Jia, J., Liu, Z. and Smith, C.E., Huang T. (2023 )Associations of Modified Healthy Aging Index With Major Adverse Cardiac Events, Major Coronary Events, and Ischemic Heart Disease. Journal of the American Heart Association.
  9. Yao M*, Huang X, Guo Y, Zhao J#, Liu Z#. (2023). Disentangling the common genetic architecture and causality of rheumatoid arthritis and systemic lupus erythematosus with COVID-19 outcomes: genome-wide cross trait analysis and bi-directional Mendelian randomization study  Journal of Medical Virology.
  10. Dong, X., Zhuang, Z., Zhao, Y., Song, Z., Xiao, W., Wang, W, Li, Y., Huang, N., Jia, J., Liu, Z., Qi, L., Huang, T. (2023). Unprocessed red meat and processed meat consumption, plasma metabolome, and risk of ischemic heart disease: a prospective cohort study of UK Biobank. Journal of the American Heart Association.
  11. Huang N, Zhuang Z,  Liu Z and  Huang T# (2022). Observational and genetic associations of modifiable risk factors with aortic valve stenosis: a prospective cohort study of 0.5 million participants. Nutrients, 14(11), 2273; https://doi.org/10.3390/nu14112273 
  12. Zhu Z, Wang K, Hao X, Chen L, Liu Z., Wang C#.  (2022). Causal graph between serum lipids and glycemic traits: a Mendelian randomization study. Diabetes (IF=7.720, Endocrinology and Metabolism 9 out of 143)
  13. Zhuang, Z.,  Li, N.,   Wang J.,  Yang, R.,   Wang, W.,  Liu, Z.,    Huang, T., (2022) GWAS-associated bacteria and their metabolites appear to be causally related to the development of inflammatory bowel disease. European Journal of Clinical Nutrition. https://doi.org/10.1038/s41430-022-01074-w
  14.  Chen J.,  Shen S., Li Y., Fan J., Xiong S., Xu J., Zhu C., Lin L., Dong X.,  Duan W., Zhao Y., Qian X., Liu Z., Wei Y.,  Christiani D., Zhang R.,  Chen F., APOLLO: An accurate and independently validated prediction model of lower-grade gliomas overall survival and a comparative study of model performance, EBioMedicine, Volume 79, 2022, 104007, ISSN 2352-3964, https://doi.org/10.1016/j.ebiom.2022.104007. (IF=8·143 , research and experimental medicine  17/140)
  15. Zhou, X., Cao, S.M., Cai, Y., Zhang, X., Zhang, S., Feng, G.F., Chen, Y., Feng, Q.S., Chen, Y., Chang, E.T., Liu, Z., Adami, H.O., Liu, J., Ye, W., Zhang, Z., Zeng, Y.X., Xu, M., 2021. A Comprehensive Risk Score for Effective Risk Stratification and Screening of Nasopharyngeal Carcinoma. Nature Communications 12 (1), 1-8.  (IF=14.919, Multidisciplinary Sciences 4 out of 73).
  16. Liu, W.*, Zhuang, Z., Wang, W., Huang, T#. and Liu, Z#. 2021. An Improved Genome-Wide Polygenic Score Model for Predicting the Risk of Type 2 Diabetes. Frontiers in Genetics. DOI:  https://doi.org/10.3389/fgene.2021.632385.
  17.  Wang, W., Wang, J., Zhuang, Z., Gao, M., Yang, R., Liu, Z., & Huang, T. (2021). Assessment of causality between modifiable factors and heart failure: A Mendelian randomization analysis. Asia Pacific Journal of Clinical Nutrition, 30(2). https://search.informit.org/doi/10.3316/informit.935636036920046
  18. Shen, S., Zhang, R., Jiang, Y., Li, Y., Lin, L., Liu, Z., Zhao, Y., Shen, H., Hu, Z., Wei, Y.# and Chen, F.#, 2021. Comprehensive analyses of m6A regulators and interactive coding and non-coding RNAs across 32 cancer types.  Molecular Cancer 20 (67). DOI: https://doi.org/10.1186/s12943-021-01362-2 (IF=15.302, Biochemistry & Molecular Biology 5 out of 297, Oncology 10 out of 244).
  19. Zhuang, Z.,Yao, M.*, Wong, J. Y.Y. , Liu, Z.#, Huang, T#., 2021. Shared genetic etiology and causality between body fat percentage and cardiovascular diseases: a large-scale genome-wide cross-trait analysis. BMC Medicine 19, 100. https://doi.org/10.1186/s12916-021-01972-z (IF=8.775, Medicine, General and Internal 10 out of 155).
  20. Liu, W.*, Guo, Y.*, and Liu, Z.#,  2021. An Omnibus Test for Detecting Multiple Phenotype Associations based on GWAS Summary Level Data. Frontiers in Genetics. DOI: https://doi.org/10.3389/fgene.2021.644419.
  21. Wei, Y., Huang, H., Zhang, R., Zhu, Z., Zhu, Y., Lin, L., Dong, X., Wei, L., Chen, X., Liu, Z., Zhao, Y., Su, L., Chen, F.# and Christiani, D.C.#, 2021. Association of Serum Mannose With Acute Respiratory Distress Syndrome Risk and Survival. JAMA Network Open, 4(1):e2034569. (IF=5.032)
  22. Zhuang, Z., Gao, M., Yang, R., Li, N., Liu, Z., Cao, W. and Huang, T., 2020. Association of physical activity, sedentary behaviours and sleep duration with cardiovascular diseases and lipid profiles: a Mendelian randomization analysis. Lipids in Health and Disease, 19, pp. 1-11.
  23. Zhuang, Z., Gao, M., Yang, R., Liu, Z., Cao, W., and Huang, T., 2020. Causal relationships between gut metabolites and Alzheimer’s disease: a bi-directional Mendelian randomization study. Neurobiology of Aging.  DOI: 10.1016/j.neurobiolaging.2020.10.022. 
  24. Bind, M.A., Rubin, D.B., Cardenas, A., Dhingra, R., Ward-Caviness, C., Liu, Z., Mirowsky, J., Schwartz, J.D., Diaz-Sanchez, D. and Devlin, R.B., 2020. Heterogeneous ozone effects on the DNA methylome of bronchial cells observed in a crossover study. Scientific Reports, 10(1), 1-15. 
  25. Jia, J., Dou, P., Gao, M., Kong, X., Li, C., Liu, Z.# and Huang, T.# , 2019.  Assessment of causal direction between gut microbiota-dependent metabolites and cardiometabolic health: A bi-directional Mendelian randomisation analysis. Diabetes., 68(9), pp.1747-1755. (IF=7.720, Endocrinology and Metabolism 9 out of 143)
  26. Peter Brown, RELISH Consortium, Yaoqi Zhou, Large expert-curated database for benchmarking document similarity detection in biomedical literature search, Database, Volume 2019, 2019, baz085, https://doi.org/10.1093/database/baz085
  27. Brunst, K.J., Tignor, N., Just, A., Liu, Z. , Lin, X., Hacker, M.R., Bosquet, E.M., Wright, R.O., Wang, P., Baccarelli, A.A. and Wright, R.J., 2018. Cumulative lifetime maternal stress and epigenome-wide placental DNA methylation in the PRISM cohort. Epigenetics. 13(6):665-681.
  28. Zhang, J., Liu, Z., Umukoro, P.E., Cavallari, J.M., Fang, S.C., Weisskopf, M.G., Lin, X., Mittleman, M.A. and Christiani, D.C., 2017. An epigenome-wide association analysis of cardiac autonomic responses among a population of welders. Epigenetics, 12(2), pp.71-76. 
  29. Liu, X.S., Liu, Z., Gerarduzzi, C., Choi, D.E., Ganapathy, S., Pandolfi, P.P. and Yuan, Z.M., 2016. Somatic human ZBTB7A zinc finger mutations promote cancer progression. Oncogene, 35(23), p.3071. (IF=7.971)
  30. Qi, Qibin, et al.  FTO genetic variants, dietary intake and body mass index: insights from 177 330 individuals. Human Molecular Genetics, 23.25 (2014): 6961-6972. (IF=5.101)
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