Intelligence quotient is primarily determined by genetics
the verdict
CONTESTED PARTIAL
refutedsupported
the weight of evidence
6 sources for · 5 against
Scientific evidence shows that intelligence has substantial heritability, but environmental factors such as education and socioeconomic status also play a major role, making the claim that it is primarily genetically determined contested and nuanced.
General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53,949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10(-9), MIR2113; rs17522122, P=2.55 × 10(-8), AKAP6; rs10119, P=5.67 × 10(-9), APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10(-6)). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10(-17)). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C.
22 The heritability of general cognitive functioning in old age might decrease slightly from its levels in young and middle adulthood. Candidate gene studies have found that variation in APOE genotype is the only reliable individual genetic associate of cognitive function in older age, but that might apply especially to cognitive change rather than cognitive level in old age. 27 , 28 , 29 Using the genome-wide complex trait analysis procedure (GCTA), genome-wide association studies (GWAS) found that ~51% (the s.e.
SNPs were excluded based on imputation quality (IMPUTE info<0.4, MACH r 2 <0.3, BIMBAM r 2 <0.3) and minor allele frequency (<0.5%). Only SNPs that passed these QC criteria in >50% of individuals were included in the meta-analysis (2 478 500 SNPs). A meta-analysis of the 31 cohorts was performed using the METAL package with an inverse variance weighted model implemented and single genomic control applied ( http://www.sph.umich.edu/csg/abecasis/Metal ). SNP-based results were also compared to published results for educational attainment 35 (Social Science Genetic Association Consortium) and general cognitive function in childhood 36 (Childhood Intelligence Consortium).
79 Four of the 29 genes previously reported to be associated with AD 38 , 39 , 40 , 41 , 42 , 44 or neuropathological features of AD and related dementias 43 were associated with general cognitive function (at P <0.01). These were TOMM40 , APOE , MEF2C and ABCG1. These results suggest that there is overlap between the genetic contribution to ‘normal' and ‘pathological' cognitive variation in older age. A
80 reported no significant association of polygenic score for AD with general cognitive ability when using smaller sample sizes for both the creation of the polygenic score and the prediction analysis. All known cases of clinical dementia were removed from the contributing cohorts. Of course, some or all of the effects we found could be driven by the inadvertent inclusion of individuals in a prodromal stage of dementia, and that we have picked up the genetic effects on this. This is an important issue that is impossible to eliminate entirely.
These findings suggest that there is overlap between the genetic contribution to general cognitive function in late-middle and older age, and both educational attainment and childhood general cognitive function. This has also been explored in a study, which used education as a proxy phenotype for general cognitive function. 81 The bivariate heritability of educational attainment and general cognitive function has been previously estimated in GS using both pedigree-based and SNP-based methods (biv h 2 =0.78, N ~20 500 and biv h 2 =0.59, N ~6600, respectively).
The estimates calculated from the ARIC and HRS cohorts suggest that 29% (s.e.=0.05) and 28% (s.e.=0.07), respectively, of the variation in general cognitive function can be attributed to common SNPs that are in linkage disequilibrium with causal variants in these cohorts. Whereas these estimates are lower than a previously-published estimate from the Cognitive Ageing in Genetics in England and Scotland consortium in a smaller sample (51% s.e.=0.11; N =3511), 30 they are slightly higher than an estimate reported from a similar sample size in GS (21% s.e.=0.05; N =6648).
84 , 85 This is also demonstrated in the present study when compared with the previously published Cognitive Ageing in Genetics in England and Scotland consortium study ( N =3511), which reported no genome-wide significant SNP associations with general cognitive function in older age. 30 Phenotypic heterogeneity is a limitation of this study. Each cohort used a different set of cognitive tests to create the general cognitive function phenotype.
Figure 4 Forest plot of four GCTA-based estimates for the single-nucleotide polymorphism (SNP)-based heritability ( x axis) of general fluid cognitive function. The summary mean and s.e. were estimated using inverse-variance weighting. Abbreviations: ARIC, The Atherosclerosis Risk in Communities Study; CAGES, Cognitive Ageing Genetics in England and Scotland Consortium; 30 GS, Generation Scotland. 78 HRS, Health and Retirement Study.
OBJECTIVE: To examine whether the association between childhood IQ and later mortality risk was explained by early developmental advantages or mediated by adult sociodemographic factors and health behaviors. PARTICIPANTS AND METHODS: Participants were 10 620 men and women from the 1958 British Birth Cohort Study whose IQ was assessed at the age of 11 years and who were followed up to age 46. Childhood covariates included birth weight, childhood height at 11 years of age, problem behaviors, father's occupational class, parents' interest in child's education, family size, and family difficulties. Adult risk factors were assessed at ages 23, 33, and 42 years, and they included education, occupational class, marital status, smoking, BMI, alcohol use, and psychosomatic symptoms. RESULTS: Between ages 23 and 46 years, 192 participants died. Higher childhood IQ was related to lower mortality risk (standardized odds ratio [OR]: 0.80 [95% confidence interval (CI): 0.69-0.93]) with no gender differences (OR: 0.81 [95% CI: 0.67-0.98] [men] and 0.79 [95% CI: 0.63-0.98] [women]). Adjusting for parents' interest in child's education attenuated the IQ-mortality association by 15% to 20%, and adult education and psychosomatic symptoms both attenuated the association by 25%. Other covariates were less influential. CONCLUSIONS: In a cohort of British men and women, the most important explanatory factors for the lower mortality rate among individuals with high IQ were parental interest in child's education, high adult educational level, and low prevalence of psychosomatic symptoms. However, common sociodemographic risk factors and health behaviors may not be sufficient to explain the association between IQ and early mortality completely.
Intelligence is associated with important economic and health-related life outcomes. Despite intelligence having substantial heritability (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered. Here we report a meta-analysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL P < 5 × 10<sup>-8</sup>) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10<sup>-6</sup>), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10<sup>-6</sup>). Despite the well-known difference in twin-based heritability for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (r<sub>g</sub> = 0.89, LD score regression P = 5.4 × 10<sup>-29</sup>). These findings provide new insight into the genetic architecture of intelligence.
Despite the well-known difference in twin-based heritability for intelligence in childhood (0.45) and adulthood 2 (0.80), we show substantial genetic correlation ( r g =0.89, LD Score regression P =5.4×10 −29 ). These findings provide novel insight into the genetic architecture of intelligence. We combined GWAS data for intelligence in 78,308 unrelated individuals from 13 cohorts (Online Methods). Of these, full GWAS results for intelligence on N=48,698 have been published in two different studies 5 , 6 (N=12,441 and N=36,257 respectively), while GWAS results on the remaining 29,610 individuals have not been published previously.
The estimated r g was 0.89 (SE=0.08, P =5.4×10 −29 ), indicating substantial overlap between the genetic variants influencing intelligence in childhood and adulthood, and warranting a combined meta-analysis. The genetic correlations between all individual cohorts were generally larger than 0.80 except for those involving some of the smaller sized cohorts (N<4,000), which, given the large standard errors of the r g ’s, is likely due to the relatively low sample sizes in some of the individual cohorts ( Supplementary Table 2 ). The full meta-analysis of all 13 cohorts (maximum N=78,308) included 12,104,294 SNPs.
Given the high (0.70) but not perfect genetic correlation between EA and intelligence, these results strongly support the involvement of the proxy-replicated SNPs and genes in intelligence. The strongest emerging association with intelligence is with rs2490272 (6q21) in an intronic region of FOXO3 and neighboring SNPs in the promotor of the same gene. This gene is part of the insulin/insulin-like growth factor 1 signaling pathway and is believed to trigger apoptosis, including neuronal cell death as a result of oxidative stress 22 . Moreover, it has been shown to be associated with longevity 23 , 24 .
Many of the implicated genes are involved in neuronal function: DCC, APBA1, PRR7, ZFHX3, HCRTR1, NEGR1, MEF2C, SHANK3 and ATXN2 L (see Supplementary Note for the GeneCards summaries ). In conclusion, we conducted a meta-analysis GWAS and GWGAS for intelligence, including 13 cohorts and 78,308 individuals. We confirmed three loci and 12 genes, and identified 15 novel genomic loci and 40 novel genes for intelligence. Pathway analysis demonstrated the involvement of genes regulating cell development. We showed genetic overlap with several neuropsychiatric and metabolic disorders.
Meta-analysis Meta-analysis of the results of the 13 cohorts was performed in METAL 11 (see URLs). We did not include SNPs that were not present in the UK Biobank sample. The analysis was based on P -values, taking sample size and direction of effect into account using the samplesize scheme. Genetic correlations Genetic correlations (r g ) were calculated between intelligence and 32 other traits for which summary statistics from GWAS were publicly available, using LD Score regression (see URLs). This method corrects for sample overlap, by estimating the intercept of the bivariate regression.
We performed a sign concordance analysis for the 16 independent lead SNPs, using the exact binomial test. For each independent signal we determined whether either the lead SNP had a P -value smaller than 0.05/16 in the educational attainment analysis, or another (correlated) top SNP in the same locus if this was not the case. All 47 genes implicated in the GWGAS for intelligence were available for look-up in the EA sample. For each gene we determined whether it had a P -value smaller than 0.05/47 in the EA analysis.
( b ) Heatmap of gene-expression levels of genes for intelligence in 45 tissue types (see Supplementary Table 18 for N per tissue). A value above zero (red) depicts a relatively high expression level with respect to the mean expression level of the gene over all tissues, whereas a value below zero (blue) depicts a relatively low expression level. ( c ) Epigenetic states of genes. The bars denote the proportions of epigenetic states across 127 tissue types. ( d ) Genetic correlations between intelligence and 32 health-related outcomes. Error bars show 95% confidence intervals for estimates of r g .
Red bars represent the traits that showed a significant genetic correlation after correction for multiple testing ( P <1.56×10 −3 ), pink bars the traits that showed a nominal significant correlation ( P <0.05), and blue bars the traits that did not show a genetic correlation significantly different from zero. Note: as Alzheimer’s disease is an age-related disorder we calculated the r g with this phenotype across three age groups and found no difference in r g ’s ( Supplementary Note ). Table 1 Genomic loci and lead SNPs associated with intelligence in the meta-analysis based on N=78,308.
Intelligence test scores and educational duration are positively correlated. This correlation could be interpreted in two ways: Students with greater propensity for intelligence go on to complete more education, or a longer education increases intelligence. We meta-analyzed three categories of quasiexperimental studies of educational effects on intelligence: those estimating education-intelligence associations after controlling for earlier intelligence, those using compulsory schooling policy changes as instrumental variables, and those using regression-discontinuity designs on school-entry age cutoffs. Across 142 effect sizes from 42 data sets involving over 600,000 participants, we found consistent evidence for beneficial effects of education on cognitive abilities of approximately 1 to 5 IQ points for an additional year of education. Moderator analyses indicated that the effects persisted across the life span and were present on all broad categories of cognitive ability studied. Education appears to be the most consistent, robust, and durable method yet to be identified for raising intelligence.
We meta-analysed three categories of quasi-experimental studies of educational effects on intelligence: those estimating education-intelligence associations after controlling for earlier intelligence, those using compulsory schooling policy changes as instrumental variables, and those using regression-discontinuity designs on school-entry age cutoffs. Across 142 effect sizes from 42 datasets involving over 600,000 participants, we found consistent evidence for beneficial effects of education on cognitive abilities, of approximately 1 to 5 IQ points for an additional year of education.
Moderator analyses indicated that the effects persisted across the lifespan, and were present on all broad categories of cognitive ability studied. Education appears to be the most consistent, robust, and durable method yet to be identified for raising intelligence.
Advance online publication. https://doi.org/10.1177/0956797618774253 Ritchie, Stuart J ; Tucker-Drob, Elliot M. / How much does education improve intelligence? A meta-analysis . In: Psychological Science . 2018 ; Vol. 29, No. 8. pp. 1358-1369.
We meta-analysed three categories of quasi-experimental studies of educational effects on intelligence: those estimating education-intelligence associations after controlling for earlier intelligence, those using compulsory schooling policy changes as instrumental variables, and those using regression-discontinuity designs on school-entry age cutoffs. Across 142 effect sizes from 42 datasets involving over 600,000 participants, we found consistent evidence for beneficial effects of education on cognitive abilities, of approximately 1 to 5 IQ points for an additional year of education.
https://doi.org/10.1177/0956797618774253 How much does education improve intelligence? A meta-analysis. / Ritchie, Stuart J; Tucker-Drob, Elliot M. In: Psychological Science , Vol. 29, No. 8, 18.06.2018, p. 1358-1369. Research output : Contribution to journal › Article › peer-review TY - JOUR T1 - How much does education improve intelligence? A meta-analysis AU - Ritchie, Stuart J AU - Tucker-Drob, Elliot M PY - 2018/6/18 Y1 - 2018/6/18 N2 - Intelligence test scores and educational duration are positively correlated.
This correlation can be interpreted in two ways: students with greater propensity for intelligence go on to complete more education, or a longer education increases intelligence. We meta-analysed three categories of quasi-experimental studies of educational effects on intelligence: those estimating education-intelligence associations after controlling for earlier intelligence, those using compulsory schooling policy changes as instrumental variables, and those using regression-discontinuity designs on school-entry age cutoffs.
Across 142 effect sizes from 42 datasets involving over 600,000 participants, we found consistent evidence for beneficial effects of education on cognitive abilities, of approximately 1 to 5 IQ points for an additional year of education. Moderator analyses indicated that the effects persisted across the lifespan, and were present on all broad categories of cognitive ability studied. Education appears to be the most consistent, robust, and durable method yet to be identified for raising intelligence. AB - Intelligence test scores and educational duration are positively correlated.
This correlation can be interpreted in two ways: students with greater propensity for intelligence go on to complete more education, or a longer education increases intelligence. We meta-analysed three categories of quasi-experimental studies of educational effects on intelligence: those estimating education-intelligence associations after controlling for earlier intelligence, those using compulsory schooling policy changes as instrumental variables, and those using regression-discontinuity designs on school-entry age cutoffs.
Across 142 effect sizes from 42 datasets involving over 600,000 participants, we found consistent evidence for beneficial effects of education on cognitive abilities, of approximately 1 to 5 IQ points for an additional year of education. Moderator analyses indicated that the effects persisted across the lifespan, and were present on all broad categories of cognitive ability studied. Education appears to be the most consistent, robust, and durable method yet to be identified for raising intelligence.
KW - intelligence KW - education KW - meta-analysis KW - quasiexperimental KW - open data U2 - 10.1177/0956797618774253 DO - 10.1177/0956797618774253 M3 - Article SN - 0956-7976 VL - 29 SP - 1358 EP - 1369 JO - Psychological Science JF - Psychological Science IS - 8 ER - Ritchie SJ, Tucker-Drob EM. How much does education improve intelligence? A meta-analysis . Psychological Science . 2018 Jun 18;29(8):1358-1369. Epub 2018 Jun 18. doi: 10.1177/0956797618774253
Intelligence - the ability to learn, reason and solve problems - is at the forefront of behavioural genetic research. Intelligence is highly heritable and predicts important educational, occupational and health outcomes better than any other trait. Recent genome-wide association studies have successfully identified inherited genome sequence differences that account for 20% of the 50% heritability of intelligence. These findings open new avenues for research into the causes and consequences of intelligence using genome-wide polygenic scores that aggregate the effects of thousands of genetic variants.
<h4>Background</h4>Intelligence is defined as general mental capacity, which includes the abilities to reason, solve new problems, think abstractly, and learn quickly. Genetic factors explain a considerable fraction of inter-individual differences in intelligence. For many years, research on intelligence was limited to estimating the relative importance of genetic and environmental factors, without identifying any individual causal factors.<h4>Methods</h4>This review of the literature is based on pertinent original publications and reviews.<h4>Results</h4>Genome-wide association studies (GWAS) have shown that certain gene loci are associated with intelligence, as well as with educational attainment, which is known to be correlated with intelligence. As each individual gene locus accounts for only a very small part of the variance in intelligence ( < 0.02%), so-called "polygenic scores" (PGS) have been calculated in which thousands of genetic variants are summarized together. On the basis of the largest GWAS performed to date, it is estimated that 7-15% of inter-individual differences in educational attainment and 7-10% in intelligence among persons of European descent can be explained by genetic factors. These genetic effects are partly indirect. At the same time, the relative importance of genetic factors in determining complex features such as intelligence and educational attainment must always be seen against the background of individual environmental conditions. In the presence of difficult social conditions, for example, the influence of genetic factors is typically lower.<h4>Conclusion</h4>At present, the polygenic scores generated from genome-wide association studies are primarily of scientific interest, yet they are becoming increasingly informative and valid for individual prediction. There is, therefore, a need for broad social discussion about their future use.
today provides an intelligence quotient, not an MA. An intelligence quotient (IQ) is a number … neurotransmit¬ ters include noradrenaline, which is primarily involved in preparing the body for action … building blocks of heredity. Traits are determined by pairs of genes, with one gene in each
Studies conducted in developing countries have noted associations between concurrent stunting, social-emotional problems and poor cognitive ability in young children. However, the relative contribution of these variables in Latin America is likely changing as undernutrition rates decline and prevalence of childhood obesity rises. We conducted a cross-sectional study of 106 normal-weight and 109 obese preschool children to compare the relative contribution of early nutrition, sociodemographic factors and psychosocial variables on cognitive development in normal-weight and obese preschool children in Chile. The study variables were categorized as: (1) socio-demographic (age, sex, birth order and socioeconomic) (2) early nutrition (maternal height, birth weight, birth length and height at 5 years) (3) psychosocial factors (maternal depression, social-emotional wellbeing and home space sufficiency). In order to assess determinants of cognitive development at 4-5 years we measured intelligence quotient (IQ); variability in normal children was mostly explained by socio-demographic characteristics (r(2) = 0.26), while in obese children early nutritional factors had a significant effect (r(2) = 0.12) beyond socio-demographic factors (r(2) = 0.19). Normal-weight children, who were first born, of slightly better SES and height Z score >1, had an IQ ≥ 6 points greater than their counterparts (p < 0.05). Obese children who were first born with birth weight >4,000 g and low risk of socio-emotional problems had on average ≥5 IQ points greater than their peers (p < 0.05). We conclude that in Chile, a post-transitional country, IQ variability of normal children was mostly explained by socio-demographic characteristics; while in obese children, early nutrition also played a significant role.
The study variables were categorized as: (1) socio-demographic (age, sex, birth order and socioeconomic) (2) early nutrition (maternal height, birth weight, birth length and height at 5 years) (3) psychosocial factors (maternal depression, social-emotional wellbeing and home space sufficiency). In order to assess determinants of cognitive development at 4–5 years we measured intelligence quotient (IQ); variability in normal children was mostly explained by socio-demographic characteristics (r 2 = 0.26), while in obese children early nutritional factors had a significant effect (r 2 = 0.12) beyond socio-demographic factors (r 2 = 0.19).
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Although the American Psychological Association has taken a strong antiracism stance, scientific racism continues to be published in psychology journals and scholarly books. Recent articles claim that the folk categories of race are genetically meaningful divisions and that evolved genetic differences among races and nations are important for explaining immutable differences in cognitive ability, educational attainment, crime, sexual behavior, and wealth; all claims that are opposed by a strong scientific consensus to the contrary. These claims remain a serious source of harm through the naturalization of inequality and through support for the work of racial extremists. Contemporary "racial hereditarian research" claims to rest on modern genetics and evolutionary biology and to draw on their methods, such as genome-wide association studies. These new arguments fail to meet the evidentiary and ethical standards of these disciplines for the study of human variation. If psychology adopted standards from genetics and evolutionary biology, the current racial hereditarian work would be ineligible for publication. Actions that the American Psychological Association can take to deal with scientific racism are described. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
intelligence quotient (IQ) and the general intelligence factor (g factor), which have been the cornerstones of much research into human intelligence.
The Mismeasure of Man is a 1981 book by paleontologist Stephen Jay Gould. The book is both a history and critique of the statistical methods and cultural motivations underlying biological determinism, the belief that "the social and economic differences between human groups—primarily races, classes, and sexes—arise from inherited, inborn distinctions and that society, in this sense, is an accurate
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The Mismeasure of Man presents a historical evaluation of the concepts of the intelligence quotient (IQ) and of the general intelligence factor (g factor), which were and are the measures for intelligence used by psychologists. Gould proposed that most psychological studies have been heavily biased, by the belief that the human behavior of a race of people is best explained by genetic heredity. He cites the Burt Affair, about the oft-cited twin studies, by Cyril Burt (1883–1971), wherein Burt claimed that human intelligence is highly heritable.
Recently published maps have suggested a notable spatial association between soil fertility and the mean national intelligence quotient (MNIQ) across the globe. This raises intriguing questions about whether the nutritional impact of soil could influence human intellectual capacity on a worldwide scale. This study seeks to investigate these potential connections by examining the spatial relationships between soil fertility and MNIQ in 126 countries. A soil fertility index (SFI) was developed by integrating soil type and pH data, and its relationship with MNIQ was analyzed using regression and correlation techniques. Geostatistical methods were employed to explore the spatial relationships between MNIQ and SFI. The findings indicated a significant correlation (r = 0.58, P < 0.001) between SFI and MNIQ, accounting for 34% of the variability in MNIQ. Semivariograms for MNIQ, SFI, and their cross-semivariogram were modeled to assess their spatial interrelation. The isotropic semivariograms and cross-semivariogram showed considerable similarity in terms of nugget effect and geostatistical range, suggesting that similar spatial processes may govern the variability of soil fertility and human IQ globally. While these results offer valuable insights into the relationship between soil and human intelligence, it is crucial to recognize that this interplay is complex and influenced by various interconnected factors, including soil management practices, socioeconomic conditions, and cultural traditions. Therefore, collaborative efforts across multiple scientific disciplines and institutions are necessary to comprehensively understand the intricacies of this relationship.
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