Advancing Risk Gene Discovery Across the Allele Frequency Spectrum

TL;DR

This paper reviews strategies for identifying genetic risk genes across the entire allele frequency spectrum, emphasizing the need to improve detection of intermediate-frequency variants to bridge current gaps in human genetics research.

Contribution

It provides a comprehensive framework organizing methods by variant frequency, highlighting innovations and limitations to enhance risk gene discovery across the spectrum.

Findings

Innovations in variant annotation and joint modeling improve detection of intermediate-frequency variants.

Phenotype refinement and network inference extend discovery into the 'missing middle'.

A unifying conceptual map guides future research directions.

Abstract

The discovery of genetic risk factors has transformed human genetics, yet the pace of new gene identification has slowed despite the exponential expansion of sequencing and biobank resources. Current approaches are optimized for the extremes of the allele frequency spectrum: rare, high-penetrance variants identified through burden testing, and common, low-effect variants mapped by genome-wide association studies. Between these extremes lies variants of intermediate frequency and effect size where statistical power is limited, pathogenicity is often misclassified, and gene discovery lags behind empirical evidence of heritable contribution. This 'missing middle' represents a critical blind spot across disease areas, from neurodevelopmental and psychiatric disorders to cancer and aging. In this review, we organize strategies for risk gene identification by variant frequency class, highlighting methodological strengths and constraints at each scale. We draw on lessons across fields to illustrate how innovations in variant annotation, joint modeling, phenotype refinement, and network-based inference can extend discovery into the intermediate range. By framing the frequency spectrum as a unifying axis, we provide a conceptual map of current capabilities, their limitations, and emerging directions toward more comprehensive risk gene discovery.