Genetic estimation of causalities between educational attainment with common digestive tract diseases and the mediating pathways.

BACKGROUND: The association between education, intelligence, and cognition with digestive tract diseases has been established. However, the specific contribution of each factor in the pathogenesis of these diseases are still uncertain. METHOD: This study employed multivariable Mendelian randomization (MR) to assess the independent effects of education, intelligence, and cognition on gastrointestinal conditions in the FinnGen and UK Biobank European-ancestry populations. A two-step MR approach was employed to assess the mediating effects of the association. RESULTS: Meta-analysis of MR estimates from FinnGen and UK Biobank showed that 1- SD (4.2 years) higher education was causally associated with lower risks of gastroesophageal reflux (OR: 0.58; 95% CI: 0.50, 0.66), peptic ulcer (OR: 0.57; 95% CI: 0.47, 0.69), irritable bowel syndrome (OR: 0.70; 95% CI: 0.56, 0.87), diverticular disease (OR: 0.69; 95% CI: 0.61, 0.78), cholelithiasis (OR: 0.68; 95% CI: 0.59, 0.79) and acute pancreatitis (OR: 0.54; 95% CI: 0.41, 0.72), independently of intelligence and cognition. These causal associations were mediating by body mass index (3.7-22.3%), waist-to-hip ratio (8.3-11.9%), body fat percentage (4.1-39.8%), fasting insulin (1.4-5.5%) and major depression (6.0-12.4%). CONCLUSION: Our findings demonstrate a causal and independent association between education and six common digestive tract diseases. Additionally, our study highlights five mediators as crucial targets for preventing digestive tract diseases associated with lower education levels.

Associations of childhood, adolescence, and midlife cognitive function with DNA methylation age acceleration in midlife.

Prior studies showed increased age acceleration (AgeAccel) is associated with worse cognitive function among old adults. We examine the associations of childhood, adolescence and midlife cognition with AgeAccel based on DNA methylation (DNAm) in midlife. Data are from 359 participants who had cognition measured in childhood and adolescence in the Child Health and Development study, and had cognition, blood based DNAm measured during midlife in the Disparities study. Childhood cognition was measured by Raven's Progressive Matrices and Peabody Picture Vocabulary Test (PPVT). Adolescent cognition was measured only by PPVT. Midlife cognition included Wechsler Test of Adult Reading (WTAR), Verbal Fluency (VF), Digit Symbol (DS). AgeAccel measures including Horvath, Hannum, PhenoAge, GrimAge and DunedinPACE were calculated from DNAm. Linear regressions adjusted for potential confounders were utilized to examine the association between each cognitive measure in relation to each AgeAccel. There are no significant associations between childhood cognition and midlife AgeAccel. A 1-unit increase in adolescent PPVT, which measures crystalized intelligence, is associated with 0.048-year decrease of aging measured by GrimAge and this association is attenuated after adjustment for adult socioeconomic status. Midlife crystalized intelligence measure WTAR is negatively associated with PhenoAge and DunedinPACE, and midlife fluid intelligence measure (DS) is negatively associated with GrimAge, PhenoAge and DunedinPACE. AgeAccel is not associated with VF in midlife. In conclusion, our study showed the potential role of cognitive functions at younger ages in the process of biological aging. We also showed a potential relationship of both crystalized and fluid intelligence with aging acceleration.

Irritability in young people with copy number variants associated with neurodevelopmental disorders (ND-CNVs).

A range of rare mutations involving micro-deletion or -duplication of genetic material (copy number variants (CNVs)) have been associated with high neurodevelopmental and psychiatric risk (ND-CNVs). Irritability is frequently observed in childhood neurodevelopmental conditions, yet its aetiology is largely unknown. Genetic variation may play a role, but there is a sparsity of studies investigating the presentation of irritability in young people with ND-CNVs. This study aimed to investigate whether there is a difference in irritability in young people with rare ND-CNVs compared to those without ND-CNVs, and to what extent irritability is associated with psychiatric diagnoses and cognitive ability (IQ). Irritability and broader psychopathology were assessed in 485 young people with ND-CNVs and 164 sibling controls, using the child and adolescent psychiatric assessment. Autism was assessed using the social communication questionnaire, and intelligence quotient (IQ) by the Wechsler abbreviated scale of intelligence. Fifty four percent of young people with ND-CNVs met the threshold for irritability; significantly more than controls (OR = 3.77, CI = 3.07-7.90, p = 5.31 × 10-11). When controlling for the presence of other psychiatric comorbidities, ND-CNV status was still associated with irritability. There was no evidence for a relationship between irritability and IQ. Irritability is an important aspect of the clinical picture in young people with ND-CNVs. This work shows that genetic variation is associated with irritability in young people with ND-CNVs, independent of psychiatric comorbidities or IQ impairment. Clinicians should be aware of this increased risk to inform management and interventions.

Thyroid function variations within the reference range and cognitive function: A two-sample Mendelian randomization study.

BACKGROUND: The causal relationship between thyroid function variations within the reference range and cognitive function remains unknown. We aimed to explore this causal relationship using a Mendelian randomization (MR) approach. METHODS: Summary statistics of a thyroid function genome-wide association study (GWAS) were obtained from the ThyroidOmics consortium, including reference range thyroid stimulating hormone (TSH) (N = 54,288) and reference range free thyroxine (FT4) (N = 49,269). GWAS summary statistics on cognitive function were obtained from the Social Science Genetic Association Consortium (SSGAC) and the UK Biobank, including cognitive performance (N = 257,841), prospective memory (N = 152,605), reaction time (N = 459,523), and fluid intelligence (N = 149,051). The primary method used was inverse-variance weighted (IVW), supplemented with weighted median, Mr-Egger regression, and MR-Pleiotropy Residual Sum and Outlier. Several sensitivity analyses were conducted to identify heterogeneity and pleiotropy. RESULTS: An increase in genetically associated TSH within the reference range was suggestively associated with a decline in cognitive performance (ß = -0.019; 95%CI: -0.034 to -0.003; P = 0.017) and significantly associated with longer reaction time (ß = 0.016; 95 % CI: 0.005 to 0.027; P = 0.004). Genetically associated FT4 levels within the reference range had a significant negative relationship with reaction time (ß = -0.030; 95%CI:-0.044 to -0.015; P = 4.85 × 10-5). These findings remained robust in the sensitivity analyses. CONCLUSIONS: Low thyroid function within the reference range may have a negative effect on cognitive function, but further research is needed to fully understand the nature of this relationship. LIMITATIONS: This study only used GWAS data from individuals of European descent, so the findings may not apply to other ethnic groups.

Mendelian randomization: causal inference leveraging genetic data.

Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples - the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.

The Causal Relationships Between Gut Microbiota, Brain Volume, and Intelligence: A Two-Step Mendelian Randomization Analysis.

BACKGROUND: Growing evidence indicates that dynamic changes in gut microbiome can affect intelligence; however, whether these relationships are causal remains elusive. We aimed to disentangle the poorly understood causal relationship between gut microbiota and intelligence. METHODS: We performed a 2-sample Mendelian randomization (MR) analysis using genetic variants from the largest available genome-wide association studies of gut microbiota (N = 18,340) and intelligence (N = 269,867). The inverse-variance weighted method was used to conduct the MR analyses complemented by a range of sensitivity analyses to validate the robustness of the results. Considering the close relationship between brain volume and intelligence, we applied 2-step MR to evaluate whether the identified effect was mediated by regulating brain volume (N = 47,316). RESULTS: We found a risk effect of the genus Oxalobacter on intelligence (odds ratio = 0.968 change in intelligence per standard deviation increase in taxa; 95% CI, 0.952-0.985; p = 1.88 × 10-4) and a protective effect of the genus Fusicatenibacter on intelligence (odds ratio = 1.053; 95% CI, 1.024-1.082; p = 3.03 × 10-4). The 2-step MR analysis further showed that the effect of genus Fusicatenibacter on intelligence was partially mediated by regulating brain volume, with a mediated proportion of 33.6% (95% CI, 6.8%-60.4%; p = .014). CONCLUSIONS: Our results provide causal evidence indicating the role of the microbiome in intelligence. Our findings may help reshape our understanding of the microbiota-gut-brain axis and development of novel intervention approaches for preventing cognitive impairment.

Gene-environment pathways to cognitive intelligence and psychotic-like experiences in children.

In children, psychotic-like experiences (PLEs) are related to risk of psychosis, schizophrenia, and other mental disorders. Maladaptive cognitive functioning, influenced by genetic and environmental factors, is hypothesized to mediate the relationship between these factors and childhood PLEs. Using large-scale longitudinal data, we tested the relationships of genetic and environmental factors (such as familial and neighborhood environment) with cognitive intelligence and their relationships with current and future PLEs in children. We leveraged large-scale multimodal data of 6,602 children from the Adolescent Brain and Cognitive Development Study. Linear mixed model and a novel structural equation modeling (SEM) method that allows estimation of both components and factors were used to estimate the joint effects of cognitive phenotypes polygenic scores (PGSs), familial and neighborhood socioeconomic status (SES), and supportive environment on NIH Toolbox cognitive intelligence and PLEs. We adjusted for ethnicity (genetically defined), schizophrenia PGS, and additionally unobserved confounders (using computational confound modeling). Our findings indicate that lower cognitive intelligence and higher PLEs are significantly associated with lower PGSs for cognitive phenotypes, lower familial SES, lower neighborhood SES, and less supportive environments. Specifically, cognitive intelligence mediates the effects of these factors on PLEs, with supportive parenting and positive school environments showing the strongest impact on reducing PLEs. This study underscores the influence of genetic and environmental factors on PLEs through their effects on cognitive intelligence. Our findings have policy implications in that improving school and family environments and promoting local economic development may enhance cognitive and mental health in children.

Childhood is a critical period for brain development. Difficult experiences during this developmental phase may contribute to reduced intelligence and poorer mental health later in life. Genetics and environmental factors also play roles. For example, having family support or a higher family income has been linked to better brain health outcomes for children. Delusions or hallucinations, or other psychotic-like experiences during childhood, are linked with poor mental health later in life. Children who experience psychotic-like episodes between the ages of nine and eleven have a higher risk of developing schizophrenia or related conditions. Environmental circumstances during childhood also appear to play a crucial role in shaping the risk of schizophrenia or related conditions. Park, Lee et al. show that positive parenting and supportive school and neighborhood environments boost child intelligence and mental health. In the experiments, Park, Lee et al. analyzed data on 6,602 children to determine how genetics and environmental factors shaped their intelligence and mental health. The models show that children with higher intelligence have a lower risk of psychosis. Both genetics and supportive environments contribute to higher intelligence. Complex interactions between biology and social factors shape children's intelligence and mental health. Beneficial genetics and coming from a family with more financial resources are helpful. Yet, social environments, such as having parents who use positive child-rearing practices, or having supportive schools or neighborhoods, have protective effects that can offset other disadvantages. Policies that help parents, encourage supportive school environments, and strengthen neighborhoods may boost children's intelligence and mental health later in life.

Evolutionary Trends of Polygenic Scores in European Populations From the Paleolithic to Modern Times.

This study examines the temporal and geographical evolution of polygenic scores (PGSs) across cognitive measures (Educational Attainment [EA], Intelligence Quotient [IQ]), Socioeconomic Status (SES), and psychiatric conditions (Autism Spectrum Disorder [ASD], schizophrenia [SCZ]) in various populations. Our findings indicate positive directional selection for EA, IQ, and SES traits over the past 12,000 years. Schizophrenia and autism, while similar, showed different temporal patterns, aligning with theories suggesting they are psychological opposites. We observed a decline in PGS for neuroticism and depression, likely due to their genetic correlations and pleiotropic effects on intelligence. Significant PGS shifts from the Upper Paleolithic to the Neolithic periods suggest lifestyle and cognitive demand changes, particularly during the Neolithic Revolution. The study supports a mild hypothesis of Gregory Clark's model, showing a noticeable rise in genetic propensities for intelligence, academic achievement and professional status across Europe from the Middle Ages to the present. While latitude strongly influenced height, its impact on schizophrenia and autism was smaller and varied. Contrary to the cold winters theory, the study found no significant correlation between latitude and intelligence.

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.

FMR1 Protein Expression Correlates with Intelligence Quotient in Both Peripheral Blood Mononuclear Cells and Fibroblasts from Individuals with an FMR1 Mutation.

Fragile X syndrome (FXS) is the most common heritable form of intellectual disability and is caused by CGG repeat expansions exceeding 200 (full mutation). Such expansions lead to hypermethylation and transcriptional silencing of the fragile X messenger ribonucleoprotein 1 (FMR1) gene. As a consequence, little or no FMR1 protein (FMRP) is produced; absence of the protein, which normally is responsible for neuronal development and maintenance, causes the syndrome. Previous studies have demonstrated the causal relationship between FMRP levels and cognitive abilities in peripheral blood mononuclear cells (PBMCs) and dermal fibroblast cell lines of patients with FXS. However, it is arguable whether PBMCs or fibroblasts would be the preferred surrogate for measuring molecular markers, particularly FMRP, to represent the cognitive impairment, a core symptom of FXS. To address this concern, CGG repeats, methylation status, FMR1 mRNA, and FMRP levels were measured in both PBMCs and fibroblasts derived from 66 individuals. The findings indicated a strong association between FMR1 mRNA expression levels and CGG repeat numbers in PBMCs of premutation males after correcting for methylation status. Moreover, FMRP expression levels from both PBMCs and fibroblasts of male participants with a hypermethylated full mutation and with mosaicism demonstrated significant association between the intelligence quotient levels and FMRP levels, suggesting that PBMCs may be preferable for FXS clinical studies, because of their greater accessibility.

Are Genetic and Environmental Risk Factors for Psychopathology Amplified in Children with Below-Average Intelligence? A Population-Based Twin Study.

There is a negative association between intelligence and psychopathology. We analyzed data on intelligence and psychopathology to assess this association in seven-year-old Dutch twin pairs (ranging from 616 to 14,150 depending on the phenotype) and estimated the degree to which genetic and environmental factors common to intelligence and psychopathology explain the association. Secondly, we examined whether genetic and environmental effects on psychopathology are moderated by intelligence. We found that intelligence, as assessed by psychometric IQ tests, correlated negatively with childhood psychopathology, as assessed by the DSM-oriented scales of the Child Behavior Check List (CBCL). The correlations ranged between - .09 and - .15 and were mainly explained by common genetic factors. Intelligence moderated genetic and environmental effects on anxiety and negative affect, but not those on ADHD, ODD, and autism. The heritability of anxiety and negative affect was greatest in individuals with below-average intelligence. We discuss mechanisms through which this effect could arise, and we end with some recommendations for future research.

Expanding the phenotype of Kleefstra syndrome: speech, language and cognition in 103 individuals.

OBJECTIVES: Speech and language impairments are core features of the neurodevelopmental genetic condition Kleefstra syndrome. Communication has not been systematically examined to guide intervention recommendations. We define the speech, language and cognitive phenotypic spectrum in a large cohort of individuals with Kleefstra syndrome. METHOD: 103 individuals with Kleefstra syndrome (40 males, median age 9.5 years, range 1-43 years) with pathogenic variants (52 9q34.3 deletions, 50 intragenic variants, 1 balanced translocation) were included. Speech, language and non-verbal communication were assessed. Cognitive, health and neurodevelopmental data were obtained. RESULTS: The cognitive spectrum ranged from average intelligence (12/79, 15%) to severe intellectual disability (12/79, 15%). Language ability also ranged from average intelligence (10/90, 11%) to severe intellectual disability (53/90, 59%). Speech disorders occurred in 48/49 (98%) verbal individuals and even occurred alongside average language and cognition. Developmental regression occurred in 11/80 (14%) individuals across motor, language and psychosocial domains. Communication aids, such as sign and speech-generating devices, were crucial for 61/103 (59%) individuals including those who were minimally verbal, had a speech disorder or following regression. CONCLUSIONS: The speech, language and cognitive profile of Kleefstra syndrome is broad, ranging from severe impairment to average ability. Genotype and age do not explain the phenotypic variability. Early access to communication aids may improve communication and quality of life.

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 (ß = 0.79, 95% confidence interval [95% CI] 0.26;1.31) as well as ECS (ß = 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.

The causality of physical activity status and intelligence: A bidirectional Mendelian randomization study.

BACKGROUND: Observational studies suggest physical activity (PA) enhances intelligence, while sedentary behavior (SB) poses a risk. However, causality remains unclear. METHODS: We extracted genetic instruments from large genome-wide association studies summary data and employed an inverse-variance weighted (IVW) approach within a random-effects model as the primary method of Mendelian randomization (MR) analysis to estimate the overall effect of various physical activity statuses on intelligence. To assess IVW stability and MR sensitivity, we also utilized supplementary methods including weighted median, MR-Egger, and MR-PRESSO. Furthermore, multivariable MR analysis was conducted to examine the independent effects of each physical activity trait on intelligence. RESULTS: The MR primary results indicated that LST was negatively associated with intelligence (ß = -0.133, 95%CI: -0.177 to -0.090, p = 1.34×10-9), while SBW (ß = 0.261, 95% CI: 0.059 to 0.463, p = 0.011) may have a positive effect on intelligence; however, MVPA and SC did not show significant effects on intelligence. Inverse causality analyses demonstrated intelligence significantly influenced all physical activity states. CONCLUSIONS: Our study highlights a bidirectional causal relationship between physical activity states and intelligence.

Shifting as an executive function separate from updating and inhibition in old age: Behavioral and genetic evidence.

This study aimed to examine the organization of executive functions (EFs), specifically working memory updating, prepotent response inhibition, and mental-set shifting in old age, with a particular focus on determining whether the shifting function was behaviorally and genetically separated from the other functions. A total of 248 healthy older Chinese individuals participated, and multiple measures of executive functions were collected. Additionally, measures of fluid intelligence were included to explore the varying relationships between the three executive functions and this higher-order cognitive ability. Furthermore, genetic data were gathered and analyzed to investigate the associations between EFs and six candidate single-nucleotide polymorphisms (SNPs) mapped to dopaminergic, serotonergic, or glutamatergic genes. The results indicated that both the three-factor model and the two-factor model, which combined updating and inhibition, demonstrated a good fit. Furthermore, shifting was found to be behaviorally separated from the other two functions, and the correlation between shifting and fluid intelligence was smaller compared to the correlations between updating and inhibition with fluid intelligence. Moreover, the DRD2 SNPs showed significant associations with shifting, rather than with updating and inhibition. These findings provide evidence that shifting is distinct and separate from updating and inhibition, highlighting the diversity of EFs among older adults.

Intelligence quotient-genotype association in dystrophinopathies: A systematic review and meta-analysis.

AIMS: Becker muscular dystrophy (BMD) and Duchenne muscular dystrophy (DMD) are associated with intelligence quotients (IQs) lower than the normative values, and it is suggested that IQ is negatively correlated with the number of affected isoforms (i.e., Dp427, Dp140 and Dp71). Therefore, the objective of this meta-analysis was to estimate the IQ, and the IQ-genotype association according to the altered dystrophin isoforms, in the population with BMD or DMD. METHODS: A systematic search in Medline, Web of Science, Scopus and the Cochrane Library was conducted from inception to March 2023. Observational studies that determined the IQ and/or the IQ by genotype in the population with BMD or DMD were included. Meta-analyses of IQ, IQ by genotype and IQ-genotype association by comparing IQ according to the genotype were conducted. The results are shown as the mean/mean differences and 95% confidence intervals. RESULTS: Fifty-one studies were included. The IQ in BMD was 89.92 (85.84, 94.01) and in DMD was 84.61 (82.97, 86.26). Moreover, the IQ for Dp427-/Dp140+/Dp71+ and Dp427-/Dp140-/Dp71+ was 90.62 (86.72, 94.53) and 80.73 (67.49, 93.98) in BMD, while the IQ for Dp427-/Dp140+/Dp71+, Dp427-/Dp140-/Dp71+ and Dp427-/Dp140-/Dp71- was 93.05 (89.42, 96.67), 81.78 (77.23, 86.32) and 49.19 (40.47, 57.90) in DMD. Finally, in DMD, Dp427-/Dp140-/Dp71+ vs Dp427-/Dp140+/Dp71+ and Dp427-/Dp140-/Dp71- vs Dp427-/Dp140-/Dp71+ were associated with -10.73 (-14.66, -6.81) and -36.14 (-48.87, -23.41) points, respectively. CONCLUSIONS: The IQ in BMD and DMD was lower than the normative values. Moreover, in DMD, there is a synergistic association between the number of affected isoforms and IQ.

Causal associations and genetic overlap between COVID-19 and intelligence.

OBJECTIVE: COVID-19 might cause neuroinflammation in the brain, which could decrease neurocognitive function. We aimed to evaluate the causal associations and genetic overlap between COVID-19 and intelligence. METHODS: We performed Mendelian randomization (MR) analyses to assess potential associations between three COVID-19 outcomes and intelligence (N = 269 867). The COVID phenotypes included severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (N = 2 501 486), hospitalized COVID-19 (N = 1 965 329) and critical COVID-19 (N = 743 167). Genome-wide risk genes were compared between the genome-wide association study (GWAS) datasets on hospitalized COVID-19 and intelligence. In addition, functional pathways were constructed to explore molecular connections between COVID-19 and intelligence. RESULTS: The MR analyses indicated that genetic liabilities to SARS-CoV-2 infection (odds ratio [OR]: 0.965, 95% confidence interval [CI]: 0.939-0.993) and critical COVID-19 (OR: 0.989, 95% CI: 0.979-0.999) confer causal effects on intelligence. There was suggestive evidence supporting the causal effect of hospitalized COVID-19 on intelligence (OR: 0.988, 95% CI: 0.972-1.003). Hospitalized COVID-19 and intelligence share 10 risk genes within 2 genomic loci, including MAPT and WNT3. Enrichment analysis showed that these genes are functionally connected within distinct subnetworks of 30 phenotypes linked to cognitive decline. The functional pathway revealed that COVID-19-driven pathological changes within the brain and multiple peripheral systems may lead to cognitive impairment. CONCLUSIONS: Our study suggests that COVID-19 may exert a detrimental effect on intelligence. The tau protein and Wnt signaling may mediate the influence of COVID-19 on intelligence.

A Longitudinal Analysis of Gene x Environment Interaction on Verbal Intelligence Across Adolescence and Early Adulthood.

The Scarr-Rowe hypothesis proposes that the heritability of intelligence is higher in more advantaged socioeconomic contexts. An early demonstration of this hypothesis was Rowe and colleagues (Rowe et al., Child Dev 70:1151-1162, 1999), where an interaction between the heritability of verbal intelligence and parental education was identified in adolescent siblings in Wave I of the National Longitudinal Study of Adolescent to Adult Health. The present study repeated their original analysis at Wave I using contemporary methods, replicated the finding during young adulthood at Wave III, and analyzed the interaction longitudinally utilizing multiple measurements. We examined parental education, family income, and peer academic environment as potential moderators. Results indicated increased heritability and decreased shared environmental variance of verbal intelligence at higher levels of parental education and peer academic environment in adolescence. Moreover, moderation by peer academic environment persisted into adulthood with its effect partially attributable to novel gene-environment interactions that arose in the process of cognitive development.

A Bivariate Twin Study of Cortical Surface Area and Verbal and Nonverbal Intellectual Skills in Adolescence.

Understanding the biological basis of cognitive differences between individuals is the goal in human intelligence research. The surface area of the cortex is considered to be a key determinant of human intelligence. Adolescence is a period of development characterized by physiological, emotional, behavioral, and psychosocial changes, which is related to the recombination and optimization of the cerebral cortex, and cognitive ability changes significantly in children and adolescents. This study examined the effects of common genetic and environmental factors between the surface area of the cerebral cortex and intelligence in typical developing adolescents (twins, n = 114, age 12-18 years old). Cortical surface area data were parsed into subregions (i.e., frontal, parietal, occipital, and temporal areas) and intelligence into verbal and nonverbal skills. We found a phenotypic correlation between regional surface areas and verbal intelligence. No correlation was observed between regional surface areas and nonverbal intelligence, except for the occipital lobe and the right hemisphere. In the bivariate twin analyses, the differences in phenotypic correlation between regional surface areas and verbal intelligence were not due to unshared environmental effects or measurement error, but to genetic effects. In summary, the current study has broadened the previous genetic investigations of cognitive ability and cortical surface area.

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.