Individualized co-expression-like index (iCKI) enables gene–gene interactions as individual biomarkers for complex disease
When a single gene exhibits an insignificant association with complex disease, applying gene–gene interactions as biomarkers may achieve striking findings. However, it is still a barrier to measuring the strength of gene–gene interaction at the individual level and further applying gene–gene pairs as biomarkers. To overcome this challenge, we introduce iCKI, namely individualized co-expression-like index, quantifying the interaction strength of a gene–gene pair for each individual. The higher the absolute value of iCKI, the stronger the co-expression of two biomarkers. iCKI makes co-expression variations as novel individual biomarkers possible, enabling advanced applications in disease diagnosis, survival analysis, and more. Applying iCKI to rheumatoid arthritis early prediction and pancreatic cancer survival analysis, we demonstrated that co-expression achieved substantial improvements compared to single biomarkers. Overall, iCKI offers an innovative and efficient indicator for considering gene–gene interactions as biomarkers and represents a starting point for individual co-expression.
Authors
- Junxian Tao (ORCID: https://orcid.org/0000-0002-6992-0716)
- Yongshuai Jiang (ORCID: https://orcid.org/0000-0002-7163-6554)
- Siyu Wei (ORCID: https://orcid.org/0000-0002-7611-4528)
- Jing Xu (ORCID: https://orcid.org/0000-0001-8084-5609)
- Zhenwei Shang (ORCID: https://orcid.org/0009-0008-2365-8901)
- Chen Sun (ORCID: https://orcid.org/0000-0003-1017-2255)
- Ruilin Li (ORCID: https://orcid.org/0000-0001-9593-1235)
- Hongchao Lyu (ORCID: https://orcid.org/0000-0002-7748-7844)
- Wei She (ORCID: https://orcid.org/0000-0001-8876-3763)
- Haiyan Chen (ORCID: https://orcid.org/0000-0002-9312-7320)
- Mingming Zhang (ORCID: https://orcid.org/0000-0001-6907-4049)
- Linna Yuan
- Yuping Zou
- Fanwu Kong
- Wenhua Lyu
- Jiacheng Wang (ORCID: https://orcid.org/0000-0003-0738-4732)
- Guoping Tang (ORCID: https://orcid.org/0009-0002-4853-2180)
Institutions
- Zhejiang International Studies University (CN)
- Kunming University of Science and Technology (CN)
- Harbin Engineering University (CN)
- Harbin Medical University (CN)
- Endometriosis UK (GB)
- The First Hospital of Kunming (CN)
- Second Affiliated Hospital of Harbin Medical University (CN)
- University of Lomé (TG)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-08-12
- DOI
- https://doi.org/10.1186/s12859-025-06225-x
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Department of Education, Heilongjiang Province
- Natural Science Foundation of Zhejiang Province