Génszint

Génszint, literally “gene level” in Hungarian, refers to analytical approaches in genetics that focus on data aggregated at the level of individual genes rather than on single variants or broader pathways. In practice, génszint analysis groups variants by gene boundaries or coding regions and tests whether the cumulative effect of those variants is associated with a trait or disease. This contrasts with variant-level analyses, which test each variant separately, and pathway- or network-level analyses, which aggregate information across multiple genes.

Methods commonly used include gene-based association tests such as burden tests and sequence kernel association tests (SKAT). Researchers define gene boundaries using reference annotations (for example, Ensembl or GENCODE) and may decide whether to include regulatory regions upstream or downstream of the transcription start site. Data sources include whole-exome sequencing, whole-genome sequencing, and imputed genotypes in GWAS cohorts, as well as transcriptomic or functional annotation to interpret results.

Applications of génszint analysis include identifying genes harboring multiple rare or common variants contributing to complex traits, prioritizing candidate genes for functional studies, and integrating genetic data with expression or regulatory data to understand mechanism. Strengths include increased power when multiple variants affect a gene; limitations include sensitivity to gene boundary definitions, inclusion of promoter regions, and the assumption that variants within a gene act in a combined manner.

Overall, génszint provides a gene-centric perspective within genetic association studies and complements variant-level and pathway-based approaches.