Feixiong Cheng, PhD
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Associate Editor
Term Expiration:
12/31/2025
Affiliation(s):
Cleveland Clinic
Areas of Interest:
age related dementias: Alzheimer's disease
Biography & Research:
Feixiong Cheng, Founding Director, Cleveland Clinic Genome Center, is a systems biologist and genomicist (Neurodegenerative disease) by training, with extensive expertise in developing and applying various systems biology and genomic medicine technologies, including genomics, transcriptomics (single-cell/nuclei), proteomics, metabolomics, and interactomics (protein-protein interactions [PPIs]), and patient iPSC-derived neuron and brain organoid models for translational neuro-therapeutic discovery and patient care with 15+ years’ experience. The primary goal of his lab is to create and combine tools from experimental network biology assays (PMID:36217030 [Nature Biotechnology 2024 & 2023]), neurogenetics/genomics (PMIDs:33558758 [Nature Genetics 2021], 33514395 [Genome Biology 2021], and 33627474 [Genome Research 2021]), artificial intelligence (PMID:35411337 [Nature Machine Intelligence 2022]), electronic health records (EHRs, 100 million electronic patient records, PMID:32984792 [Lancet Digital Health 2020]), systems pharmacology (PMIDs:35572351 [Nature Aging 2021], 31375661, 30002366 and 30867426 [Nature Communications 2018, 2019a and 2019b]), to address the challenging questions toward better understanding of Alzheimer’s disease (AD) and other AD-related dementia (ADRD), which could have a major impact in identifying real-world big data-driven diagnostic biomarkers and therapeutic targets for precision medicine and drug discovery in neurodegenerative diseases (PMIDs:36450252 [Cell Reports 2022], 33852912 [Cell 2021], 36331056 & 36254161 [Alzheimer's & Dementia 2022a and 2022b], and 30988527 [Nature Neuroscience 2019]). Dr. Cheng has played multiple roles in the Alzheimer's Disease Sequencing Project (ADSP) through applying machine learning and systems pharmacology approaches to identify drug targets and risk genes or networks for AD/ADRD form large-scale whole-genome/exome sequencing data and patient clinical databases. He has created multiple network systems medicine methodologies and successfully applied them for Alzheimer’s disease drug discovery: (1) in silico network medicine-based discovery combined with insurance records data mining and patient iPSC-derived neuron models identifies sildenafil (Viagra) as a candidate drug for Alzheimer’s disease (Nature Aging 2021, PMID:35572351) and a Phase II trial has been initialized; (2) multimodal single-cell/nucleus transcriptomics analysis combined with insurance records data mining identifies fluticasone and mometasone (approved asthma drugs) as candidate treatments for Alzheimer’s disease (Genome Research 2021, PMID:33627474); (3) insurance records data mining combined with mouse models identifies salsalate and diflunisal as candidate treatments for Alzheimer’s disease via reducing acetylated tau (Cell 2021, PMID:33852912); and (4) AI/ML-based multimodal analysis of genetic and genomic combined with EHR data identified pioglitazone (Alzheimer’s Research & Therapy 2022, PMID:35012639) and gemfibrozil (Cell Reports 2022, PMID:36450252) as candidate drugs for AD, and further identified Telmisartan as a potential treatment for African Americans with AD (Alzheimer and Dementia 2022, PMID: 36331056).
Along with the research background described above, he has gained the necessary leadership and mentorship experience that will be essential for the success training the next generation of scientists and physicians. Through the leadership position at the Molecular Medicine PhD program (Cleveland Clinic Lerner College of Medicine of CWRU), he is co-developing strategies and mentor PhD students. He has served as a mentor on the 2021 HHMI Gilliam Graduate Mentor Award (mentor graduate students under-represented science background). Over his career, Dr. Cheng has mentored postdoctoral (16, with 15 still actively involved in research fields), PhD and MD graduates (5 directly supervised, chair or service on 8 thesis committees) and undergraduate students (10).
An emerging area of his Neurodegenerative Medicine Discovery Laboratory is focused on developing cutting edge experimental systems biology (iPSC and brain organoids) and multi-omics technologies to identify novel drug targets and candidate treatments for Alzheimer’s disease and other neurodegenerative diseases.
Highlighted Publications:
a. Xiong D, Zhao J, Qiu Y, Zhou Y, Lee D, Gupta S, Lu W, Liang S, Kang JJ, Eng C, Loscalzo J, Cheng F# (Co-corresponding author), Yu H# (2024) A structurally informed human protein-protein interactome reveals proteome-wide perturbations caused by disease mutations. Nature Biotechnology, in press. doi: 10.1038/s41587-024-02428-4. PMID: 39448882
b. Zhou Y, Liu Y, Gupta S, Paramo M, Hou Y, Mao C, Luo Y, Judd J, Wierbowski S, Bertolotti M, Nerkar M, Jehi L, Drayman N, Nicolaescu V, Gula H, Tay S, Randall G, Lis TJ, Feschotte C, Erzurum CS, Cheng F# (Co-corresponding author), Yu H# (2023) A comprehensive SARS-CoV-2-human protein-protein interactome network identifies pathobiology and host-targeting therapies for COVID-19. Nature Biotechnology. 41(1):128-139. PMID: 36217030. PMCID: PMC9851973 (Journal cover)
c. Fang J, Zhang P, Zhou Y, Chiang WC, Tan J, Hou Y, Stauffer S, Li L, Pieper AA, Cummings J, Cheng F (2021) Endophenotype-based in-silico network medicine discovery combined with insurance records data mining identifies sildenafil as a candidate drug for Alzheimer’s disease. Nature Aging, 1, 1175–1188. PMCID: PMC9097949 (Highlighted by NIH/NIA Research News and 100+ major news outlets such as Washington Post, Newsweek, US News, BBC News, Fox News, UK Daily Mail)
d. Cheng F, Zhao J, Wang Y, Lu W, Liu Z, Zhou Y, Martin W, Wang R, Hao T, Yue H, Ma J, Fang J, Hou Y, Lathia JD, Keri R, Lightstone C.F., Antmam ME, Rabadan R, David H, Eng C, Vidal M, Loscalzo J (2021) Comprehensive characterization of protein-protein interactions perturbed by disease mutations. Nature Genetics, 53(3):342-353. PMCID: PMC8237108
