A genetic common factor underlying self-reported math ability and highest math class taken

While genetic influences on general intelligence have been well documented, less is known about the genetics underlying narrower abilities ("group factors"). By applying structural equation modeling to results from several genome-wide association studies (GWAS), most critically of self-reported math ability (N = 564 698) and highest math class taken (N = 430 445), we identified 53 single-nucleotide polymorphisms (SNPs) associated with a latent trait, orthogonal by design with general intelligence, approximating the group factor of quantitative ability. The genes near these SNPs implicated the biological process of neuron projection development, and the genome-wide pattern of gene-set enrichment affirmed the involvement of brain development and synaptic function. We calculated a number of genetic correlations with this quantitative factor, finding negative associations with both internalizing and externalizing disorders and positive associations with STEM occupations such as computer programming. These results provide further evidence for genetic influences on traits other than general factors in human behavioral variation, point to the mechanisms mediating these genetic influences on quantitative ability and interests, and affirm the relationships of the latter traits with a number of real-world outcomes.

Authors

Institutions

Publication Details

Journal
Molecular Psychiatry
Published
2025-09-20
DOI
https://doi.org/10.1038/s41380-025-03237-0
Primary Topic
Cognitive and developmental aspects of mathematical skills
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A genetic common factor underlying self-reported math ability and highest math class taken

Emily A. Willoughby, James J. Lee, Tobias Edwards, Alexandros Giannelis et al.
Molecular Psychiatry
Cognitive and developmental aspects of mathematical skills
article

A genetic common factor underlying self-reported math ability and highest math class taken

Emily A. Willoughby, James J. Lee, Tobias Edwards, Alexandros Giannelis, Matt McGue
article en

Abstract

While genetic influences on general intelligence have been well documented, less is known about the genetics underlying narrower abilities ("group factors"). By applying structural equation modeling to results from several genome-wide association studies (GWAS), most critically of self-reported math ability (N = 564 698) and highest math class taken (N = 430 445), we identified 53 single-nucleotide polymorphisms (SNPs) associated with a latent trait, orthogonal by design with general intelligence, approximating the group factor of quantitative ability. The genes near these SNPs implicated the biological process of neuron projection development, and the genome-wide pattern of gene-set enrichment affirmed the involvement of brain development and synaptic function. We calculated a number of genetic correlations with this quantitative factor, finding negative associations with both internalizing and externalizing disorders and positive associations with STEM occupations such as computer programming. These results provide further evidence for genetic influences on traits other than general factors in human behavioral variation, point to the mechanisms mediating these genetic influences on quantitative ability and interests, and affirm the relationships of the latter traits with a number of real-world outcomes.

Molecular PsychiatryVol. 30(12)
University of Minnesota (US), Twin Cities Orthopedics (US), Erasmus University Rotterdam (NL)
Openalex Percentile: Top 76%
Cognitive and developmental aspects of mathematical skills
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.