Weijia Zhang, Ph.D.

The primary research focus of my laboratory is the genetics, genomics, and digital pathology of kidney transplantation. Kidney transplantation is the optimal treatment for patients with end-stage kidney disease, substantially improving both survival and quality of life. However, major challenges remain, including the shortage of donor organs, limitations in the accuracy of clinical and pathological diagnosis, and limited therapeutic options for post-transplant complications.

To address these challenges, we integrate multi-omics technologies and artificial intelligence (AI) to identify genetic, genomic, and digital pathology biomarkers that can improve diagnostic accuracy, predict transplant outcomes, and optimize donor organ utilization. In parallel, we use experimental models and human biospecimens to investigate the molecular and cellular mechanisms underlying adverse transplant outcomes, with the ultimate goal of identifying novel therapeutic targets for the prevention and treatment of transplant complications.

1. Transcriptomic biomarkers: We apply bulk RNA sequencing, single-cell RNA sequencing, and spatial transcriptomics to characterize molecular changes in recipient’s blood and kidney allograft biopsies. Our studies aim to identify transcriptomic signatures associated with acute rejection, chronic allograft injury, and graft loss. By integrating molecular biomarkers with clinical and pathological information, we seek to develop noninvasive and tissue-based diagnostic and prognostic tools for early detection of allograft injury and prediction of long-term transplant outcomes.
2. Genetic association analysis: We investigate how recipient and donor genetic variation contributes to kidney transplant outcomes. Through genome-wide genetic association analyses across large transplant cohorts and biobanks, we identify genetic variants associated with rejection, chronic allograft injury, and graft loss. We further integrate genetic information with transcriptomic, clinical, and other molecular data to understand the biological mechanisms underlying genetic risk and to develop precision approaches for transplant risk stratification.
3. Innate Immunity and therapeutic targets: A major focus of our laboratory is understanding how dysregulated innate immune responses, particularly in macrophages and neutrophils, contribute to kidney allograft injury. Using human biospecimens, multi-omics analyses, in vitro cellular systems, and genetically engineered mouse models, we investigate the functional consequences of transplant-associated genetic variants and identify the molecular pathways through which they promote inflammation and tissue injury. These mechanistic studies are designed to identify actionable pathways and novel therapeutic targets for preventing or treating rejection and chronic allograft injury.
4. Pathology AI: We develop artificial intelligence and deep-learning approaches to extract quantitative and clinically meaningful information from PAS or H&E stained histopathology slides of kidney biopsies. Our research includes AI-based assessment of donor kidney quality, automated quantification of pathological lesions, and discovery of novel image features associated with post-transplant outcomes. By integrating digital pathology with clinical, genomic, and molecular data, we aim to improve diagnostic accuracy, predict graft outcomes, reduce unnecessary organ discard, and optimize donor kidney utilization.

Beyond kidney transplantation, we are also interested in genetic and genomic studies in other complex human diseases including chronic kidney diseases and cancer.

1. Sun Z, Yi Z, Wei C, Wang W, Ren T, Cravedi P, Tedla F, Ward SC, Azeloglu E, Schrider DR, Li Y, Khan A, Zanoni F, Fu J, Ali S, Liu S, Liang D, Liu T, Li H, Xi C, Vy TH, Mosoyan G, Sun Q, Kumar A, Zhang Z, Farouk S, Campell K, Ochando J, Lee K, Coca S, Xiang J, Connolly P, Gallon L, O'Connell PJ, Colvin R, Menon MC, Nadkarni G, He JC, Kraft M, Jiang X, Zhang X, Kiryluk K, Cherukuri A, Lakkis FG, Zhang W, Chen SH, Heeger PS, Zhang W. LILRB3 genetic variation is associated with kidney transplant failure in African American recipients. Nat Med. 2025 Mar 10. doi: 10.1038/s41591-025-03568-z. Epub ahead of print. PMID: 40065170.
2. Yi Z, Xi C, Menon MC, Cravedi P, Tedla F, Soto A, Sun Z, Liu K, Zhang J, Wei C, Chen M, Wang W, Veremis B, Garcia-Barros M, Kumar A, Haakinson D, Brody R, Azeloglu EU, Gallon L, O'Connell P, Naesens M, Shapiro R, Colvin RB, Ward S*, Salem F*, Zhang W*. A large-scale retrospective study enabled deep-learning based pathological assessment of frozen procurement kidney biopsies to predict graft loss and guide organ utilization. Kidney Int. 2024 Feb;105(2):281-292. doi: 10.1016/j.kint.2023.09.031. Epub 2023 Nov 3. PMID: 37923131; PMCID: PMC10892475. * co-corresponding authors
3. Sun Z, Zhang Z, Banu K, Gibson IW, Colvin RB, Yi Z, Zhang W, De Kumar B, Reghuvaran A, Pell J, Manes TD, Djamali A, Gallon L, O'Connell PJ, He JC, Pober JS, Heeger PS, Menon MC. Multiscale genetic architecture of donor-recipient differences reveals intronic LIMS1 mismatches associated with kidney transplant survival. J Clin Invest. 2023 Nov 1;133(21):e170420. doi: 10.1172/JCI170420. PMID: 37676733; PMCID: PMC10617779.
4. Sun Z, Zhang R, Zhang X, Sun Y, Liu P, Francoeur N, Han L, Lam WY, Yi Z, Sebra R, Walsh M, Yu J, Zhang W. LINE-1 promotes tumorigenicity and exacerbates tumor progression via stimulating metabolism reprogramming in non-small cell lung cancer. Mol Cancer. 2022 Jul 16;21(1):147. doi: 10.1186/s12943-022-01618-5.PMID: 35842613; PMCID: PMC9288060.
5. Sun Z, Zhang Z, Banu K, Azzi YA, Reghuvaran A, Fredericks S, Planoutene M, Hartzell S, Kim Y, Pell J, Tietjen G, Asch W, Kulkarni S, Formica R, Rana M, Maltzman JS, Zhang W, Akalin E, Heeger PS, Cravedi P, Menon MC. BloodTranscriptomes of SARS-CoV-2-Infected Kidney Transplant Recipients Associated with Immune Insufficiency Proportionate to Severity. J Am Soc Nephrol. 2022 Nov;33(11):2108-2122. doi: 10.1681/ASN.2022010125. Epub 2022 Aug 30. PMID: 36041788; PMCID: PMC9678030.
6. Yi Z, Salem F, Menon MC, Keung K, Xi C, Hultin S, Haroon Al Rasheed MR, Li L, Su F, Sun Z, Wei C, Huang W, Fredericks S, Lin Q, Banu K, Wong G, Rogers NM, Farouk S, Cravedi P, Shingde M, Smith RN, Rosales IA, O'Connell PJ, Colvin RB, Murphy B, Zhang W. Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies. Kidney Int. 2022 Feb;101(2):288-298. doi: 10.1016/j.kint.2021.09.028. Epub 2021 Oct 30. PMID:34757124.
7. Zhang Z, Sun Z, Fu J, Lin Q, Banu K, Chauhan K, Planoutene M, Wei C, Salem F, Yi Z, Liu R, Cravedi P, Cheng H, Hao K, O'Connell PJ, Ishibe S, Zhang W, Coca SG, Gibson IW, Colvin RB, He JC, Heeger PS, Murphy BT, Menon MC. Recipient APOL1 risk alleles associate with death-censored renal allograft survival and rejection episodes. J Clin Invest. 2021 Sep 9;. doi: 10.1172/JCI146643. [Epub ahead of print] PubMed PMID: 34499625
8. Yi Z, Keung KL, Li L, Hu M, Lu B, Nicholson L, Jimenez-Vera E, Menon MC, Wei C, Alexander S, Murphy B*, O'Connell PJ*, Zhang W*. Key driver genes as potential therapeutic targets in renal allograft rejection. JCI Insight. 2020 Aug 6;5(15):e136220. doi: 10.1172/jci.insight.136220. PMID: 32634125; PMCID:PMC7455082. *co-corresponding authors
9. Zhang Z, Menon MC, Zhang W, Stahl E, Loza BL, Rosales IA, Yi Z, Banu K, Garzon F, Sun Z, Wei C, Huang W, Lin Q, Israni A, Keating BJ, Colvin RB, Hao K, Murphy B. Genome-wide non-HLA donor-recipient genetic differences influence renal allograft survival via early allograft fibrosis. Kidney Int. 2020 Sep;98(3):758-768. doi: 10.1016/j.kint.2020.04.039. Epub 2020 May 23. PMID: 32454123; PMCID: PMC7483801.
10. Cravedi P, Fribourg M, Zhang W, Yi Z, Zaslavsky E, Nudelman G, Anderson L, Hartzell S, Brouard S, Heeger PS. Distinct peripheral blood molecular signature emerges with successful tacrolimus withdrawal in kidney transplant recipients. Am J Transplant. 2020 Dec;20(12):3477-3485. doi: 10.1111/ajt.15979. Epub 2020 May 27. PMID: 32459070; PMCID: PMC7704683.
11. Zhang R, Zhang F, Sun Z, Liu P, Zhang X, Ye Y, Cai B, Walsh MJ, Ren X, Hao X, Zhang W*, Yu J.* LINE-1 Retrotransposition Promotes the Development and Progression of Lung Squamous Cell Carcinoma by Disrupting the Tumor Suppressor Gene FGGY. Cancer Res. 2019 Jul 9. pii: canres.0076.2019. doi:10.1158/0008-5472.CAN-19-0076. [Epub ahead of print] PubMed PMID: 31289132. *co-corresponder
12. Zhang W, Yi Z, Keung KL, Shang H, Wei C, Cravedi P, Sun Z, Xi C, Woytovich C, Farouk S, Huang W, Banu K, Gallon L, Magee CN, Najafian N, Samaniego M, Djamali A, Alexander SI, Rosales IA, Smith RN, Xiang J, Lerut E, Kuypers D, Naesens M, O'Connell PJ, Colvin R, Menon MC, Murphy B. A Peripheral Blood Gene Expression Signature to Diagnose Subclinical Acute Rejection. J Am Soc Nephrol. 2019 Aug;30(8):1481-1494. doi: 10.1681/ASN.2018111098. Epub 2019 Jul 5. PubMed PMID:31278196.
13. Zhang W, Yi Z, Wei C, Keung KL, Sun Z, Xi C, Woytovich C, Farouk S, Gallon L, Menon MC, Magee C, Najafian N, Samaniego MD, Djamali A, Alexander SI, Rosales IA, Smith RN, O'Connell PJ, Colvin R, Cravedi P, Murphy B. Pretransplant transcriptomic signature in peripheral blood predicts early acute rejection. JCI Insight. 2019 Jun 6;4(11). pii: 127543. doi: 10.1172/jci.insight.127543. eCollection 2019 Jun 6. PubMed PMID: 31167967; PubMed Central PMCID: PMC6629121.
14. O'Connell PJ*, Zhang W*, Menon MC, Yi Z, Schröppel B, Gallon L, Luan Y, Rosales IA, Ge Y, Losic B, Xi C, Woytovich C, Keung KL, Wei C, Greene I, Overbey J, Bagiella E, Najafian N, Samaniego M, Djamali A, Alexander SI, Nankivell BJ,Chapman JR, Smith RN, Colvin R, Murphy B. Biopsy transcriptome expressionprofiling to identify kidney transplants at risk of chronic injury: a multicentre, prospective study. Lancet. 2016 Jul 21. pii: S0140-6736(16)30826-1. doi: 10.1016/S0140-6736(16)30826-1. *co-first authors