A positive relationship between brain volume and intelligence has been suspected since the 19th century, and empirical studies seem to support this hypothesis. However, this claim is controversial because of concerns about publication bias and the lack of systematic control for critical confounding factors (e.g., height, population structure). We conducted a preregistered study of the relationship between brain volume and cognitive performance using a new sample of adults from the United Kingdom that is about 70% larger than the combined samples of all previous investigations on this subject (N = 13,608). Our analyses systematically controlled for sex, age, height, socioeconomic status, and population structure, and our analyses were free of publication bias. We found a robust association between total brain volume and fluid intelligence (r = .19), which is consistent with previous findings in the literature after controlling for measurement quality of intelligence in our data. We also found a positive relationship between total brain volume and educational attainment (r = .12). These relationships were mainly driven by gray matter (rather than white matter or fluid volume), and effect sizes were similar for both sexes and across age groups.
The Social Science Genetic Association Consortium
We, the Social Science Genetic Association Consortium (SSGAC), aim to bring together the expertise of medical geneticists and social scientists to study how a range of health-relevant outcomes are influenced by specific genetic variants, the environment (including lifestyle), and their interaction. In accessing the U.K. Biobank data, we are specifically interested in the following health-relevant outcomes: cognitive function, dementia, depression, smoking, and alcohol drinking. Our research will contribute to quantifying how several risk factors (e.g. lifestyle, environment, genes), both separately and in combination, influence public health and well-being. Incorporating insights from the social sciences and investigating social scientific outcomes helps to achieve this objective. For example, a GWAS on subjective well-being in a very large sample could identify genetic factors associated with (absence of) depression that would not be possible to identify by studying depression directly in a much smaller sample. Furthermore, accurate polygenic risk scores can be used to study how lifestyle and environmental factors mediate genetic effects on health. We will use several methods, e.g.:
? Genomewide association studies (GWAS) that aim to identify individual genetic variants associated with a particular outcome.
? GWAS of a ?proxy phenotype??a biologically-distal phenotype available in larger samples?to identify candidate genetic variants for association with a health-relevant outcome available in smaller samples.
? Estimation of economic and statistical models of health-relevant outcomes as a function of genetic variants, environmental factors, and their interaction. We will typically use all available observations in the UKB that (i) are of European decent, (ii) have been successfully genotyped, and (iii) have measures of the phenotype(s) under investigation.
|Lead investigator:||Professor Daniel Benjamin|
|Lead institution:||National Bureau of Economic Research|
6 related Returns
|Return ID||App ID||Description||Archive Date|
|717||11425||Gemome-wide association study identifies 74 loci associated with educational attainment||17 Oct 2017|
|718||11425||Genetic variants associated with subjective well-being, depressive symptoms,and neuroticism identified through genome-wide analysis||17 Oct 2017|
|2159||11425||Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences||7 Apr 2020|
|2887||11425||Multi-trait analysis of genome-wide association summary statistics using MTAG||27 Nov 2020|
|1782||11425||Pleiotropy-robust Mendelian Randomization||30 Sep 2019|
|3586||11425||Resource Profile and User Guide of the Polygenic Index Repository||24 Jun 2021|
|3066||Are Bigger Brains Smarter? Evidence From a Large-Scale Preregistered Study||Nave et al||2018||Psychological Science (2018)|