mFusion: a multiscale fusion method bridging neuroimages to genes through neurotransmissions in mental health disorders
Mental health disorders emerge from complex interactions among neurobiological processes across multiple scales, which poses challenges in uncovering pathological pathways from molecular dysfunction to neuroimaging changes. Here, we proposed a multiscale fusion (mFusion) method to evaluate the relevance of each gene to the neuroimaging traits of mental health disorders. We combined gene-neuroimaging associations with gene-positron emission tomography (PET) and PET-neuroimaging associations using protein-protein interaction networks, where various genes traced by PET maps are involved in neurotransmission. Compared with previous methods, the proposed algorithm identified more disease genes on both simulated and empirical data sets. Applying mFusion to eight mental health disorders, we found that these disorders formed three clusters with distinct associated genes. In summary, mFusion is a promising tool of prioritizing genes for mental health disorders by establishing gene-PET-neuroimaging pathways.
Authors
- Qiang Luo (ORCID: https://orcid.org/0000-0002-0426-6039)
- Zhenyi Wang (ORCID: https://orcid.org/0000-0002-9407-0135)
- Luolong Cao (ORCID: https://orcid.org/0009-0001-1638-9853)
- Zhiyuan Yuan (ORCID: https://orcid.org/0000-0002-9367-4236)
Institutions
- Shanghai Jiao Tong University (CN)
- Fudan University (CN)
- XinHua Hospital (CN)
- Ruijin Hospital (CN)
- Institut de Biologie systémique et synthétique (FR)
- Shanghai Research Center for Acupuncture and Meridians (CN)
- Shanghai Institute of Hematology (CN)
- Institute of Bioinformatics (IN)
- Children's Hospital of Fudan University (CN)
- Shanghai Children's Hospital (CN)
- Huashan Hospital (CN)
- State Key Laboratory of Medical Neurobiology
- Tsinghua University (CN)
Publication Details
- Journal
- Communications Biology
- Published
- 2024-12-25
- DOI
- https://doi.org/10.1038/s42003-024-07404-x
- Citations
- 2
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.47
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Fudan University
- National Postdoctoral Program for Innovative Talents
- National Key Research and Development Program of China
- Program of Shanghai Academic Research Leader