TY - JOUR
T1 - A cross-disease, pleiotropy-driven approach for therapeutic target prioritization and evaluation
AU - Bao, Chaohui
AU - Tan, Tingting
AU - Wang, Shan
AU - Gao, Chenxu
AU - Lu, Chang
AU - Yang, Siyue
AU - Diao, Yizhu
AU - Jiang, Lulu
AU - Jing, Duohui
AU - Chen, Liye
AU - Lv, Haitao
AU - Fang, Hai
N1 - We acknowledge funding from the National Natural Science Foundation of China (32170663 [H.F.] and 82300263 [C.B.]), the Shanghai Pujiang Program (21PJ1409600 [H.F.]), the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning (awarded to H.F.), the National Key Research and Development Program of China (2017YFC1308600 [H.L.]), the Natural Science Foundation of Shanghai (21ZR1431600 [H.L.]), the Versus Arthritis Career Development Award (22053 [L.C.]), the Academy of Medical Sciences Springboard Award (SBF0051134 [L.C.]), and the Innovative Research Team of High-Level Local Universities in Shanghai.
Publisher copyright:
© 2024 The Author(s). Published by Elsevier Inc.
PY - 2024/4/22
Y1 - 2024/4/22
N2 - Cross-disease genome-wide association studies (GWASs) unveil pleiotropic loci, mostly situated within the non-coding genome, each of which exerts pleiotropic effects across multiple diseases. However, the challenge ‘‘W-H-W’’ (namely, whether, how, and in which specific diseases pleiotropy can inform clinical therapeutics) calls for effective and integrative approaches and tools. We here introduce a pleiotropy-driven approach specifically designed for therapeutic target prioritization and evaluation from cross-disease GWAS summary data, with its validity demonstrated through applications to two systems of disorders (neuropsychiatric and inflammatory). We illustrate its improved performance in recovering clinical proofof-concept therapeutic targets. Importantly, it identifies specific diseases where pleiotropy informs clinical therapeutics. Furthermore, we illustrate its versatility in accomplishing advanced tasks, including pathway crosstalk identification and downstream crosstalk-based analyses. To conclude, our integrated solution helps bridge the gap between pleiotropy studies and therapeutics discovery.
AB - Cross-disease genome-wide association studies (GWASs) unveil pleiotropic loci, mostly situated within the non-coding genome, each of which exerts pleiotropic effects across multiple diseases. However, the challenge ‘‘W-H-W’’ (namely, whether, how, and in which specific diseases pleiotropy can inform clinical therapeutics) calls for effective and integrative approaches and tools. We here introduce a pleiotropy-driven approach specifically designed for therapeutic target prioritization and evaluation from cross-disease GWAS summary data, with its validity demonstrated through applications to two systems of disorders (neuropsychiatric and inflammatory). We illustrate its improved performance in recovering clinical proofof-concept therapeutic targets. Importantly, it identifies specific diseases where pleiotropy informs clinical therapeutics. Furthermore, we illustrate its versatility in accomplishing advanced tasks, including pathway crosstalk identification and downstream crosstalk-based analyses. To conclude, our integrated solution helps bridge the gap between pleiotropy studies and therapeutics discovery.
KW - Cross-disease pleiotropic association data
KW - computational medicine
KW - inflammatory disorders
KW - neuropsychiatric disorders
KW - pleiotropy informing prioritization and evaluation
KW - therapeutic targets
UR - http://www.scopus.com/inward/record.url?scp=85190586089&partnerID=8YFLogxK
U2 - 10.1016/j.crmeth.2024.100757
DO - 10.1016/j.crmeth.2024.100757
M3 - Journal article
SN - 2667-2375
VL - 4
JO - Cell Reports Methods
JF - Cell Reports Methods
IS - 4
M1 - 100757
ER -
