From BioRxiv:

Abstract Socio-economic position (SEP) is a multi-dimensional construct reflecting (and influencing) multiple socio-cultural, physical, and environmental factors. Previous genome-wide association studies (GWAS) using household income as a marker of SEP have shown that common genetic variants account for 11% of its variation. Here, in a sample of 286,301 participants from UK Biobank, we identified 30 independent genome-wide significant loci, 29 novel, that are associated with household income. Using a recently-developed method to meta-analyze data that leverages power from genetically-correlated traits, we identified an additional 120 income-associated loci. These loci showed clear evidence of functional enrichment, with transcriptional differences identified across multiple cortical tissues, in addition to links with GABAergic and serotonergic neurotransmission. We identified neurogenesis and the components of the synapse as candidate biological systems that are linked with income. By combining our GWAS on income with data from eQTL studies and chromatin interactions, 24 genes were prioritized for follow up, 18 of which were previously associated with cognitive ability. Using Mendelian Randomization, we identified cognitive ability as one of the causal, partly-heritable phenotypes that bridges the gap between molecular genetic inheritance and phenotypic consequence in terms of income differences. Significant differences between genetic correlations indicated that, the genetic variants associated with income are related to better mental health than those linked to educational attainment (another commonly-used marker of SEP). Finally, we were able to predict 2.5% of income differences using genetic data alone in an independent sample. These results are important for understanding the observed socioeconomic inequalities in Great Britain today.

From the accompanying FAQ:

What did you find?

Our results suggest that, as we expected, the majority of the reasons that individuals differ in their level of household income was not genetic and likely to be environmental. However, there was some small association between genetic variation and variation in household income. …

We found that variation across all the SNPs in the DNA from this sample accounted for 7.4% of the variation in household income. The rest of the variation is likely due to environmental factors, types of genetic differences that we didn’t measure, and to errors of measurement. Therefore, the large majority of people’s differences in household income are likely to be environmental in origin, according to these results. We found that people’s genetic differences that were associated with higher household income (i.e. those that accounted for 7.4% of household income variation) overlapped with the genetic differences that were linked to better longevity, health, wellbeing, and intelligence (Figure 5C & Figure 5D). We found that the genetic effects linked to higher household income overlapped with the genetic differences that were protective against schizophrenia, ADHD, coronary artery disease, and feelings of tiredness and fatigue … We found evidence that being more intelligent is causally related to having a higher income in the UK at present. …

Have you found “the money gene”?

We have not found the ‘money gene’ or ‘genes for income’. Income variation is a complex social measure, with many influences. Some potential influences of income—such as some illnesses and some personal traits—are themselves partly heritable. It is possible that some genetic associations with such factors are also picked up in a GWAS study of income. Therefore, our GWAS results should not be interpreted as indicating that there are close causal links between genetic variations and income differences. Moreover, there were no ‘genes for income’ in the sense that there were no large associations between genetic variants and income differences. Genetic associations with factors such as household income (or intelligence, or some common illnesses) are composed of many thousands of genetic variants, each with a tiny association that adds up.