Integrating axis quantitative trait loci looks beyond cell types and offers insights into brain-related traits

Research output: Contribution to journalArticlepeer-review

Abstract

Genome-wide association studies have identified many loci for brain disorders, but most non-coding variants fail to colocalize with bulk expression quantitative trait loci. Single-cell expression quantitative trait loci studies capture cell-type-specific regulation but are often underpowered. We developed Bulk And Single cell expression quantitative trait loci Integration across Cell states (BASIC) to combine bulk and single-cell expression quantitative trait loci through “axis-quantitative trait loci,” which decompose bulk-tissue effects along orthogonal axes of cell-type expression. BASIC better distinguishes shared versus cell-type-specific effects and increases power. Analyzing single-cell expression quantitative trait loci with cortex bulk data from MetaBrain using BASIC identified 5644 additional gene with quantitative trait loci (74.5%), equivalent to a 76.8% increase in sample size. Integrating axis-quantitative trait loci with 12 brain-related traits improved colocalization by 53.5% versus single-cell studies and 111% versus bulk studies, revealing risk genes such as DEDD for Alzheimer’s disease and drug candidates including cabergoline.

Original languageEnglish (US)
Article number10606
JournalNature communications
Volume16
Issue number1
DOIs
StatePublished - Dec 2025

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Biochemistry, Genetics and Molecular Biology
  • General
  • General Physics and Astronomy

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