Emerging Trends for Genome-Wide Association Studies in Complex Disease Genetics
A special issue of Current Issues in Molecular Biology (ISSN 1467-3045). This special issue belongs to the section "Bioinformatics and Systems Biology".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 20
Special Issue Editor
Interests: statistical genetics; bioinformatics; Bayesian and computational statistics; branching processes
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Genome-wide association studies (GWASs) have revolutionized the study of complex diseases by identifying thousands of genetic loci linked to human traits and diseases. Despite these advances, significant methodological challenges remain, including translating statistical associations into biological mechanisms, enhancing polygenic risk prediction across diverse populations, and effectively capturing rare and structural variants. Recent developments in GWAS methodology—such as sophisticated statistical modeling, multi-omics integration, and cutting-edge machine learning techniques—are beginning to address these limitations, offering deeper insights into disease etiology and paving the way for personalized medicine. Moreover, the growth of large-scale biobanks, advances in long-read sequencing, and AI-driven data interpretation are further accelerating genetic discovery.
We would like to invite you to contribute to this Special Issue, “Emerging Trends for Genome-Wide Association Studies in Complex Disease Genetics”. It highlights cutting-edge approaches that enhance the power, interpretability, and clinical applicability of GWASs, fostering innovation in research on complex disease genetics. In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Methodological innovations (e.g., rare variant analysis, cross-ancestry polygenic risk scores, AI/ML applications).
- Functional and causal inference (fine-mapping and Mendelian randomization).
- Clinical and translational applications (precision medicine and drug discovery).
- Emerging technologies (long-read sequencing, federated GWAS, and quantum computing).
We look forward to receiving your contributions.
Dr. Xiaowei Wu
Guest Editor
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Keywords
- GWAS
- polygenic risk scores
- rare variants
- structural variants
- multi-omics
- Mendelian randomization
- population structure and relatedness
- machine learning
- Bayesian models
- stochastic models
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