The transformative role of single-cell analysis in multifactorial disorders research.

Multifactorial inherited disorders (MIDs) arise from complex interactions between polygenic risk and environmental exposures, presenting major challenges for mechanistic discovery, patient stratification, and targeted therapy development. While traditional approaches like genome-wide association studies (GWAS) and bulk omics profiling have identified broad associations, they often struggle to resolve the cellular context in which these interactions drive pathogenesis.Emergingsingle-cell technologies now offer unprecedented resolution to dissect tissue heterogeneity, define rare or transient disease-relevant cell states, and map dynamic trajectories across tissues and disease stages. This reviewprovides a comprehensive synthesis ofcurrent single-cell methodologies including transcriptomic, epigenomic, proteomic, and spatial techniques and their application to MID research. We explore how these toolsare revealingcell-type-specific regulatory circuits,contextualizingthe functional impact of inherited risk variants, andelucidatingcellular responses to environmental perturbations.We propose thatintegrating single-cell multi-omics data is critical for illuminating the mechanistic basis of complex traits and for advancing biomarker discovery. However, significant challenges remain, including technical variability, limited cohort scalability, difficulties in multi-modal data integration, and a lack of standardized analytical workflows for polygenic diseases. Overcoming these barriers will require harmonized study designs, robust computational frameworks, and the incorporation of longitudinal and environmental exposure data.Ultimately, we conclude thatsingle-cell analysis is poised to transform MID research, offering a powerful new paradigm for mechanistic insight, therapeutic innovation, and the realization of precision medicine.