Integrating Polygenic Risk Scores with Microbiome Profiles for Depression Risk Prediction: Interpretability, Bias, and Real-World Performance, Implementation, and Equity Considerations

Nakawungu Catherine

Department of Pharmaceutical Microbiology and Biotechnology Kampala International University Uganda

Email: catherine.nakawungu@studwc.kiu.ac.ug

ABSTRACT

Depression is a complex and multifactorial disorder influenced by both genetic predisposition and gut microbiome composition. Polygenic risk scores (PRSs) capture the aggregate effect of thousands of genetic variants associated with depression, while microbiome profiles provide insight into gut microbial taxa and their neuroactive metabolite contributions. Integrating these modalities offers a promising approach for personalized mental health risk prediction. This review outlines conceptual foundations, methodological frameworks, and practical considerations for combining PRS and microbiome data, emphasizing interpretability, bias, equity, and real-world deployment. We discuss preprocessing, feature engineering, multimodal modeling approaches, and evaluation metrics, highlighting challenges such as population stratification, sampling bias, and cross-platform robustness. Ethical, legal, and social implications, including stigmatization, discrimination, and regulatory compliance, are critically examined. Case studies and simulation results illustrate enhanced predictive accuracy and clinical utility of integrated models. Finally, we provide recommendations for researchers and healthcare systems to advance responsible, equitable, and interpretable implementation of polygenic–microbiome integrative models for depression risk prediction.

Keywords: Depression risk prediction, polygenic risk scores (PRSs), Gut microbiome, Integrative modeling, Interpretability, and equity.

CITE AS: Nakawungu Catherine (2026). Integrating Polygenic Risk Scores with Microbiome Profiles for Depression Risk Prediction: Interpretability, Bias, and Real-World Performance, Implementation, and Equity Considerations. RESEARCH INVENTION JOURNAL OF SCIENTIFIC AND EXPERIMENTAL SCIENCES 6(1):44-54. https://doi.org/10.59298/RIJSES/2026/614454