Publications

# denote co-first author; * denote the corresponding author.

Highlighted Work

• Cao, X., Sun, H., Feng, R., Mazumder, R., Najar, C., Li, Y. I., de Jager, P. L., The Alzheimer’s Disease Functional Genomics Consortium, Dey, K. K.*, & Wang, G.* (2026+). Integrative multi-omics QTL colocalization maps the regulatory architecture in the aging human brain. In revision at Nature Genetics. medRxiv software tutorials
• Cao, X.#, Zhu, L.#, Liang, X., Zhang, S. & Sha, Q.* (2026). Constructing genotype and phenotype network helps reveal disease heritability and phenome-wide association studies. BMC Genomics, 27, 56. doi software
• Cao, X., Zhang, S., & Sha, Q.* (2024). A novel method for multiple phenotype association studies based on genotype and phenotype network. PLoS Genetics. doi software
• Lee, H.#, Sun, H.#, Cao, X., Karaahmen, B., Li, Z., Hans, UK., Wang, G., de Jager, P. L., Bennett, D., Pinello, L., Jin, X., Mazumder R., & Dey, K. K.* (2026+). Mapping disease critical spatially variable gene programs by integrating spatial transcriptomics with human genetics. In revision at Nature Communications. bioRxiv software tutorials
• Buen Abad Najar, C. F.#, Feng, R.#, Dai, C.#, Fair, B., Hauck, Q., Li, J., Cao, X., Dey, K. K., De Jager, P., Bennett, D., The Alzheimer’s Disease Sequencing Project Functional Genomics Consortium, Liu, X., Wang, G.*, & Li, Y. I.* (2026+). Genetic and functional analysis of unproductive splicing using LeafCutter2. In revision at Nature Genetics. bioRxiv

Preprinted

• Li, R.#, Feng, R.#, Liu A., Cao, X., de Jager, P. L., Bennett, D., Jiang, T., The Alzheimer’s Disease Functional Genomics Consortium, Wen. J.*, & Wang, G.* (2026+). Neuroimaging-derived brain endophenotypes link molecular mechanisms to Alzheimer’s disease and aging. Preprinted in November 2025. medRxiv
• Liu, A.#, Jiang, R.#, Li, R., Cao, X., Qi, Z., Feng, R., Sun, H., Fujita, M., Commandante-Lou, N., Lakhani, C., Empawi, J., Knowles, D., Zhang, X., Dey, K., de Jager, P. L., Bennett, D., The Alzheimer’s Disease Functional Genomics Consortium, Wang, T.*, & Wang, G.* (2026+) Non-linear molecular QTLs in the human brain reveal context-dependent effects on aging and neurodegenerative disorders. Preprinted in November 2025. Research Square
• Qi, Z., Pelletier, A., Willwerscheid, J. Cao, X., Wen, X., Cruchaga, C., De Jager, P.L., TCW, J.* & Wang, G.* (2026+). Novel Missing Data Imputation Approaches Enhance Quantitative Trait Loci Discovery in Multi-Omics Analysis. Preprinted in November 2023. medRxiv

Statistical Genetics

• Cao, X.#, Zhang, L.#, Islam, M.K., Zhao, M., He, C., Zhang, K., Liu, S., Sha, Q.* & Wei, H.*, (2023). TGPred: efficient methods for predicting target genes of a transcription factor by integrating statistics, machine learning and optimization. NAR Genomics and Bioinformatics, 5(3), p.lqad083. doi software
• Cao, X., Wang, X., Zhang, S. & Sha, Q.* (2022). Gene-based association tests using GWAS summary statistics and incorporating eQTL. Scientific Reports. 12(1):3553. doi
• Cao, X., Liang, X., Zhang, S. & Sha, Q.* (2022). Gene selection by incorporating genetic networks into case-control association studies. European Journal of Human Genetics. doi
• Subedi, M#, Cao, X.#, Kim, B. & Sha, Q.* (2025). Network construction using Sparse Gaussian Graphical Model based on GWAS summary statistics. Scientific Reports, 15(1), 38601. doi
• Zhu, L., Yan, S., Cao, X., Sha, Q. & Zhang, S.* (2024). Integrating external controls by regression calibration for genome-wide association study. Genes. 15(1), 67. doi
• Xie, H., Cao, X., Zhang, S. & Sha, Q. (2023). Joint analysis of multiple phenotypes for extremely unbalanced case-control association studies using multi-layer network. Bioinformatics. 39(12), btad707. doi
• Wang, M., Cao, X., Zhang, S. & Sha, Q.* (2023). A clustering linear combination method for multiple phenotype association studies based on GWAS summary statistics. Scientific Reports. 13(1), p.3389. doi
• Xie, H., Cao, X., Zhang, S. & Sha, Q.* (2023). Joint analysis of multiple phenotypes for extremely unbalanced case-control association studies. Genetic Epidemiology. 47(2), pp.185-197. doi
• Liang, X., Cao, X., Sha, Q. & Zhang, S.* (2022). HCLC-FC: a Novel Statistical Method for Phenome-Wide Association Studies. PLOS ONE. 17(11): e0276646. doi

Collaborative Research

• Cao, X.#, Keyak, J.H.#, Sigurdsson, S., Zhao, C., Zhou, W., Liu, A., Lang, T.F., Deng, H.W., Guðnason, V.* & Sha, Q.* (2024). A New Hip Fracture Risk Index Derived from FEA-Computed Proximal Femur Fracture Loads and Energies-to-Failure. Osteoporosis International. 35, 785–794. doi
• Boby, N.#, Cao, X.#, Williams, K., Gadila, S.K.G., Shroyer, M.N., Didier, P.J., Srivastav, S.K., Das, A., Baker, K., Sha, Q. & Pahar, B.* (2022). Simian Immunodeficiency Virus Infection Mediated Changes in Jejunum and Peripheral SARS-CoV-2 Receptor ACE2 and Associated Proteins or Genes in Rhesus Macaques. Frontiers in Immunology. 13, p.835686. doi
• Boby, N.#, Cao, X.#, Ransom, A., Pace, B.T., Mabee, C., Shroyer, M.N., Das, A., Didier, P.J., Srivastav, S.K., Porter, E., Sha, Q. & Pahar, B.* (2021) Identification, Characterization, and Transcriptional Reprogramming of Epithelial Stem Cells and Intestinal Enteroids in Simian Immunodeficiency Virus Infected Rhesus Macaques. Frontiers in Immunology. 12, p.769990. doi
• Zhao, C.#, Su, K.#, Wu, C., Cao, X., Sha, Q., Li, W., Luo, Z., Qin, T., Qiu, C., Liu, A., Jiang, L., Zhang, X., Shen, H., Deng, H.W.* & Zhou, W.* (2024). Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics. Computers in biology and medicine. 179, p.108813. doi
• Zhao, C., Liu, A., Zhang, X., Cao, X., Ding, Z., Sha, Q., Shen, H., Deng, H.W.* & Zhou, W.* CLCLSA: Cross-omics Linked embedding with Contrastive Learning and Self Attention for multi-omics integration with incomplete multi-omics data. (2024). Computers in Biology and Medicine. doi
• Zhao, C.#, Keyak, J.H.#, Cao, X., Sha, Q., Wu, L., Luo, Z., Zhao, L., Tian, Q., Qiu, C., Su, R., Shen, H., Deng, H.W.* & Zhou, W.* (2023). Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength. Frontiers in Endocrinology, section Bone Research. doi