Polygenic Scores for Cognitive Abilities and Their Association with Different Aspects of General Intelligence-A Deep Phenotyping Approach

Genetic modifiers of rare variants in monogenic developmental disorder loci

Rare damaging variants in a large number of genes are known to cause monogenic developmental disorders (DDs) and have also been shown to cause milder subclinical phenotypes in population cohorts. Here, we show that carrying multiple (2-5) rare damaging variants across 599 dominant DD genes has an additive adverse effect on numerous cognitive and socioeconomic traits in UK Biobank, which can be partially counterbalanced by a higher educational attainment polygenic score (EA-PGS). Phenotypic deviators from expected EA-PGS could be partly explained by the enrichment or depletion of rare DD variants. Among carriers of rare DD variants, those with a DD-related clinical diagnosis had a substantially lower EA-PGS and more severe phenotype than those without a clinical diagnosis. Our results suggest that the overall burden of both rare and common variants can modify the expressivity of a phenotype, which may then influence whether an individual reaches the threshold for clinical disease.

Evaluation of genomic factors and early childhood stimulation on intelligence in children from a Brazilian birth cohort: The primary role of independent factors

BACKGROUND

Childhood cognitive abilities are a predictor of health outcomes and adult income potential. Identifying factors associated with childhood intelligence and their interactions is essential in behavioral research. We assessed the impact of genetic variants and early child stimulation (ECS) on child intelligence and examined their possible interaction as potential modifiers of IQ in a population-based longitudinal study.

METHODS

Participants of the 2004 Pelotas Birth Cohort study (N = 4231) underwent intelligent quotient (IQ) by WISC-III assessment at 6 years of age. At 24 and 48-months, mothers answered five ECS marker questions, whose sum was used to create a score. The polygenic score for intelligence (IQ-PGS) was constructed from the GWAS-weighted estimate of cognition. Association was assessed using multiple linear regression models adjusted for maternal, family, and child confounding variables. To explore the possible influence of skin color and ethnoracial classification, the regression models were stratified according to the skin color variable, as a sensitivity analysis.

RESULTS

In the adjusted analysis, IQ-PGS (β = 0.79, 95% confidence interval [95% CI] 0.26;1.31) as well as ECS (β = 2.34; 95% CI: 1.76;2.92) were associated with IQ in this sample. The association between IQ-PGS and IQ was significant only in the white Brazilian group in the sensitivity analysis. However, there was no interaction between IQ-PGS and ECS on IQ (p(IQ-PGS x ECS) = 0.46).

CONCLUSIONS

ECS did not modify the impact of genetic potential on intellectual development during childhood, suggesting that genetic factors and ECS exert independent effects on the IQ levels of children.

Studying the relationship between intelligence quotient and schizophrenia polygenic scores in a family design with first-episode psychosis population

BACKGROUND

The intelligence quotient (IQ) of patients with first-episode psychosis (FEP) and their unaffected relatives may be related to the genetic burden of schizophrenia (SCZ). The polygenic score approach can be useful for testing this question.

AIM

To assess the contribution of the polygenic risk scores for SCZ (PGS-SCZ) and polygenic scores for IQ (PGS-IQ) to the individual IQ and its difference from the mean IQ of the family (named family-IQ) through a family-based design in an FEP sample.

METHODS

The PAFIP-FAMILIES sample (Spain) consists of 122 FEP patients, 131 parents, 94 siblings, and 176 controls. They all completed the WAIS Vocabulary subtest for IQ estimation and provided a DNA sample. We calculated PGS-SCZ and PGS-IQ using the continuous shrinkage method. To account for relatedness in our sample, we performed linear mixed models. We controlled for covariates potentially related to IQ, including age, years of education, sex, and ancestry principal components.

RESULTS

FEP patients significantly deviated from their family-IQ. FEP patients had higher PGS-SCZ than other groups, whereas the relatives had intermediate scores between patients and controls. PGS-IQ did not differ between groups. PGS-SCZ significantly predicted the deviation from family-IQ, whereas PGS-IQ significantly predicted individual IQ.

CONCLUSIONS

PGS-SCZ discriminated between different levels of genetic risk for the disorder and was specifically related to patients' lower IQ in relation to family-IQ. The genetic background of the disorder may affect neurocognition through complex pathological processes interacting with environmental factors that prevent the individual from reaching their familial cognitive potential.

Familiality of the Intelligence Quotient in First Episode Psychosis: Is the Degree of Family Resemblance Associated With Different Profiles?

BACKGROUND AND HYPOTHESIS

There is uncertainty about the relationship between the family intelligence quotient (IQ) deviation and the risk for schizophrenia spectrum disorders (SSD). This study tested the hypothesis that IQ is familial in first episode psychosis (FEP) patients and that their degree of familial resemblance is associated with different profiles.

STUDY DESIGN

The participants of the PAFIP-FAMILIAS project (129 FEP patients, 143 parents, and 97 siblings) completed the same neuropsychological battery. IQ-familiality was estimated through the Intraclass Correlation Coefficient (ICC). For each family, the intra-family resemblance score (IRS) was calculated as an index of familial similarity. The FEP patients were subgrouped and compared according to their IRS and IQ.

STUDY RESULTS

IQ-familiality was low-moderate (ICC = 0.259). A total of 44.9% of the FEP patients had a low IRS, indicating discordancy with their family-IQ. Of these patients, those with low IQ had more schizophrenia diagnosis and a trend towards poorer premorbid adjustment in childhood and early adolescence. Whereas FEP patients with low IQ closely resembling their family-IQ were characterized by having the lowest performance in executive functions.

CONCLUSIONS

The deviation from the familial cognitive performance may be related to a particular pathological process in SSD. Individuals with low IQ who do not reach their cognitive familial potential show difficulties in adjustment since childhood, probably influenced by environmental factors. Instead, FEP patients with high phenotypic family resemblance might have a more significant genetic burden for the disorder.

Structural architecture and brain network efficiency link polygenic scores to intelligence

Intelligence is highly heritable. Genome-wide association studies (GWAS) have shown that thousands of alleles contribute to variation in intelligence with small effect sizes. Polygenic scores (PGS), which combine these effects into one genetic summary measure, are increasingly used to investigate polygenic effects in independent samples. Whereas PGS explain a considerable amount of variance in intelligence, it is largely unknown how brain structure and function mediate this relationship. Here, we show that individuals with higher PGS for educational attainment and intelligence had higher scores on cognitive tests, larger surface area, and more efficient fiber connectivity derived by graph theory. Fiber network efficiency as well as the surface of brain areas partly located in parieto-frontal regions were found to mediate the relationship between PGS and cognitive performance. These findings are a crucial step forward in decoding the neurogenetic underpinnings of intelligence, as they identify specific regional networks that link polygenic predisposition to intelligence.

Intelligence Polygenic Score Is More Predictive of Crystallized Measures: Evidence From the Adolescent Brain Cognitive Development (ABCD) Study

Findings in adults have shown that crystallized measures of intelligence, which are more culturally sensitive than fluid intelligence measures, have greater heritability; however, these results have not been found in children. The present study used data from 8,518 participants between 9 and 11 years old from the Adolescent Brain Cognitive Development (ABCD) Study. We found that polygenic predictors of intelligence test performance (based on genome-wide association meta-analyses of data from 269,867 individuals) and of educational attainment (based on data from 1.1 million individuals) predicted neurocognitive performance. We found that crystallized measures were more strongly associated with both polygenic predictors than were fluid measures. This mirrored heritability differences reported previously in adults and suggests similar associations in children. This may be consistent with a prominent role of gene-environment correlation in cognitive development measured by crystallized intelligence tests. Environmental and experiential mediators may represent malleable targets for improving cognitive outcomes.

Polygenic indices for cognition in healthy aging; the role of brain measures

Background

Genome-wide association studies (GWAS) have identified large numbers of genetic variants associated with cognition. However, little is known about how these genetic discoveries impact cognitive aging.

Methods

We conducted polygenic-index (PGI) analysis of cognitive performance in n = 168 European-ancestry adults aged 20-80. We computed PGIs based on GWAS of cognitive performance in young/middle-aged and older adults. We tested associations of the PGI with cognitive performance, as measured through neuropsychological evaluation. We explored whether these associations were accounted for by magnetic resonance imaging (MRI) measures of brain-aging phenotypes: total gray matter volume (GM), cortical thickness (CT), and white matter hyperintensities burden (WMH).

Results

Participants with higher PGI values performed better on cognitive tests (B = 0.627, SE = 0.196, p = 0.002) (age, sex, and principal components as covariates). Associations remained significant with inclusion of covariates for MRI measures of brain aging; B = 0.439, SE: 0.198, p = 0.028). PGI associations were stronger in young and middle-aged (age<65) as compared to older adults. For further validation, linear regression for Cog PGI and cognition in the fully adjusted model and adding the interaction between age group and Cog PGI, showed significant results (B = 0.892, SE: 0.325, p = 0.007) driven by young and middle-aged adults (B = -0.403, SE: 0.193, p = 0.039). In ancillary analysis, the Cognitive PGI was not associated with any of the brain measures.

Conclusions

Genetics discovered in GWAS of cognition are associated with cognitive performance in healthy adults across age, but most strongly in young and middle-aged adults. Associations were not explained by brain-structural markers of brain aging. Genetics uncovered in GWAS of cognitive performance may contribute to individual differences established relatively early in life and may not reflect genetic mechanisms of cognitive aging.

Robust associations between white matter microstructure and general intelligence

Few tract-based spatial statistics (TBSS) studies have investigated the relations between intelligence and white matter microstructure in healthy (young) adults, and those have yielded mixed observations, yet white matter is fundamental for efficient and accurate information transfer throughout the human brain. We used a multicenter approach to identify white matter regions that show replicable structure-function associations, employing data from 4 independent samples comprising over 2000 healthy participants. TBSS indicated 188 voxels exhibited significant positive associations between g factor scores and fractional anisotropy (FA) in all 4 data sets. Replicable voxels formed 3 clusters, located around the left-hemispheric forceps minor, superior longitudinal fasciculus, and cingulum-cingulate gyrus with extensions into their surrounding areas (anterior thalamic radiation, inferior fronto-occipital fasciculus). Our results suggested that individual differences in general intelligence are robustly associated with white matter FA in specific fiber bundles distributed across the brain, consistent with the Parieto-Frontal Integration Theory of intelligence. Three possible reasons higher FA values might create links with higher g are faster information processing due to greater myelination, more direct information processing due to parallel, homogenous fiber orientation distributions, or more parallel information processing due to greater axon density.

Overlap between genetic variants associated with schizophrenia spectrum disorders and intelligence quotient: a systematic review

BACKGROUND

To study whether there is genetic overlap underlying the risk for schizophrenia spectrum disorders (SSDs) and low intelligence quotient (IQ), we reviewed and summarized the evidence on genetic variants associated with both traits.

METHODS

We performed this review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and preregistered it in PROSPERO. We searched the Medline databases via PubMed, PsycInfo, Web of Science and Scopus. We included studies in adults with a diagnosis of SSD that explored genetic variants (single nucleotide polymorphisms [SNPs], copy number variants [CNVs], genomic insertions or genomic deletions), estimated IQ and studied the relationship between genetic variability and both traits (SSD and IQ). We synthesized the results and assessed risk of bias using the Quality of Genetic Association Studies (Q-Genie) tool.

RESULTS

Fifty-five studies met the inclusion criteria (45 case-control, 9 cross-sectional, 1 cohort), of which 55% reported significant associations for genetic variants involved in IQ and SSD. The SNPs more frequently explored through candidate gene studies were in COMT, DTNBP1, BDNF and TCF4. Through genome-wide association studies, 2 SNPs in CHD7 and GATAD2A were associated with IQ in patients with SSD. The studies on CNVs suggested significant associations between structural variants and low IQ in patients with SSD.

LIMITATIONS

Overall, primary studies used heterogeneous IQ measurement tools and had small samples. Grey literature was not screened.

CONCLUSION

Genetic overlap between SSD and IQ supports the neurodevelopmental hypothesis of schizophrenia. Most of the risk polymorphisms identified were in genes relevant to brain development, neural proliferation and differentiation, and synaptic plasticity.

Inferring intelligence of ancient people based on modern genomic studies

Quantification of ancient human intelligence has become possible with recent advances in polygenic prediction. Intelligence is a complex trait that has both environmental and genetic components and high heritability. Large-scale genome-wide association studies based on ~270,000 individuals have demonstrated highly significant single-nucleotide polymorphisms (SNPs) associated with intelligence in present-day humans. We utilized those previously reported 12,037 SNPs to estimate a genetic component of intelligence in ancient Funadomari Jomon individual from 3700 years BP as well as four individuals of Afanasievo nuclear family from about 4100 years BP and who are considered anatomically modern humans. We have demonstrated that ancient individuals could have been not inferior in intelligence compared to present-day humans through assessment of the genetic component of intelligence. We have also confirmed that alleles associated with intelligence tend to spread equally between ancestral and derived origin suggesting that intelligence may be a neutral trait in human evolution.

The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children

Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9-10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC-AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (p_fdr  < .001, η p 2 $$ {\eta}_p^2 $$  = .011-.034; adjusted for covariates) and higher cognitive genome-wide polygenic scores (GPSs) (p_fdr  < .001, η p 2 $$ {\eta}_p^2 $$  < .005). Structural equation models revealed that the GPS-intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006-.009; p = .002-.022; sex-stratified analysis). The finding of the sex modulatory effect on the gene-brain-cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.

Genome-wide association study and polygenic risk score analysis for hearing measures in children

An efficient auditory system contributes to cognitive and psychosocial development. A right ear advantage in hearing thresholds (HTs) has been described in adults and atypical patterns of left/right hearing threshold asymmetry (HTA) have been described for psychiatric and neurodevelopmental conditions. Previous genome-wide association studies (GWASs) on HT have mainly been conducted in elderly participants whose hearing is more likely to be affected by external environmental factors. Here, we investigated HT and HTA in a children population cohort (ALSPAC, n = 6,743). Better hearing was associated with better cognitive performance and higher socioeconomic status. At the group level, HTA suggested a left ear advantage (mean = -0.28 dB) that was mainly driven by females. SNP heritability for HT and HTA was 0.13 and 0.02, respectively (n = 4,989). We found a modest negative genetic correlation between HT and reading ability. GWAS for HT (n = 5,344) did not yield significant hits but polygenic risk scores for higher educational attainment (EA, ß = -1,564.72, p = .008) and schizophrenia (ß = -241.14, p = .004) were associated with lower HT, that is, better hearing. In summary, we report new data supporting associations between hearing measures and cognitive abilities at the behavioral level. Genetic analysis suggests shared biological pathways between cognitive and sensory systems and provides evidence for a positive outcome of genetic risk for schizophrenia.