Genetic and Environmental Influences of General Cognitive Ability: Is g a valid latent construct?

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

Metabolic-dysfunction associated steatotic liver disease-related diseases, cognition and dementia: A two-sample mendelian randomization study

BACKGROUND

The results of current studies on metabolic-dysfunction associated steatotic liver disease (MASLD)-related diseases, cognition and dementia are inconsistent. This study aimed to elucidate the effects of MASLD-related diseases on cognition and dementia.

METHODS

By using single-nucleotide polymorphisms (SNPs) associated with different traits of NAFLD (chronically elevated serum alanine aminotransferase levels [cALT], imaging-accessed and biopsy-proven NAFLD), metabolic dysfunction-associated steatohepatitis, and liver fibrosis and cirrhosis, we employed three methods of mendelian randomization (MR) analysis (inverse-variance weighted [IVW], weighted median, and MR-Egger) to determine the causal relationships between MASLD-related diseases and cognition and dementia. We used Cochran's Q test to examine the heterogeneity, and MR-PRESSO was used to identify outliers (NbDistribution = 10000). The horizontal pleiotropy was evaluated using the MR-Egger intercept test. A leave-one-out analysis was used to assess the impact of individual SNP on the overall MR results. We also repeated the MR analysis after excluding SNPs associated with confounding factors.

RESULTS

The results of MR analysis suggested positive causal associations between MASLD confirmed by liver biopsy (p of IVW = 0.020, OR = 1.660, 95%CI = 1.082-2.546) and liver fibrosis and cirrhosis (p of IVW = 0.009, OR = 1.849, 95%CI = 1.169-2.922) with vascular dementia (VD). However, there was no evidence of a causal link between MASLD-related diseases and cognitive performance and other types of dementia (any dementia, Alzheimer's disease, dementia with lewy bodies, and frontotemporal dementia). Sensitivity tests supported the robustness of the results.

CONCLUSIONS

This two-sample MR analysis suggests that genetically predicted MASLD and liver fibrosis and cirrhosis may increase the VD risk. Nonetheless, the causal effects of NAFLD-related diseases on VD need more in-depth research.

Exploring the Accuracy and Consistency of a School Readiness Assessment Tool for Preschoolers: Reliability, Validity and Measurement Invariance Analysis

This study focuses on examining the psychometric properties of the DIFER test, a widely used assessment tool for measuring school readiness. DIFER, which stands for Diagnostic Assessment Systems for Development, has gained prominence in Hungary and some European countries as an effective means of evaluating children's readiness for school. By investigating the reliability and validity of the DIFER test, this study aims to enhance the understanding of the suitability of the DIFER test for cross-cultural and longitudinal studies in assessing school readiness. Conducted as a survey study, the research involved 3050 Hungarian students from Slovakia and Hungary. Employing Rasch analysis and multi-group confirmatory factor analysis (MG-CFA) aid in verifying the precision of the DIFER test as a valuable assessment instrument for determining school readiness. The results revealed a strong alignment between the difficulty level of the test and students' actual abilities, demonstrating its reliability and validity. Importantly, the analysis found measurement invariance across various factors, including country, gender, and age. This indicates the consistent performance of the DIFER test in assessing school readiness across diverse groups. However, mean differences in latent abilities were observed among different age groups, indicating that older students exhibited notably higher proficiency in pre-mathematical skills compared to their younger counterparts. The findings offer valuable insights to educators, providing a reliable tool for assessing school readiness and identifying areas for improvement.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

The Garden of Forking Paths; An Evaluation of Joseph's 'A Reevaluation of the 1990 "Minnesota Study of Twins Reared Apart" IQ Study'

Joseph has written what purports to be a refutation of studies of Twins Reared-Apart (TRAs) with a singular focus on the Minnesota Study of Twins Reared-Apart (MISTRA). I show, in detail, that (a) his criticisms of previous TRA studies depend on sources that were discredited prior to MISTRA, as they all failed the test of replicability, (b) the list of biases he uses to invalidate MISTRA do not support his arguments, (c) the accusations of questionable research practices are unsubstantiated, (d) his claim that MISTRA should be evaluated in the context of psychology's replication crisis is refuted. The TRA studies are constructive replications. Like many other scholars, past and present, he has been misled by the variation introduced by small samples (sampling error) and the distortion created by walking in the garden of forking paths. His endeavor is a concatenation of elision and erroneous statistical/scientific reasoning.

Genetic insights into the causal relationship between physical activity and cognitive functioning

Physical activity and cognitive functioning are strongly intertwined. However, the causal relationships underlying this association are still unclear. Physical activity can enhance brain functions, but healthy cognition may also promote engagement in physical activity. Here, we assessed the bidirectional relationships between physical activity and general cognitive functioning using Latent Heritable Confounder Mendelian Randomization (LHC-MR). Association data were drawn from two large-scale genome-wide association studies (UK Biobank and COGENT) on accelerometer-measured moderate, vigorous, and average physical activity (N = 91,084) and cognitive functioning (N = 257,841). After Bonferroni correction, we observed significant LHC-MR associations suggesting that increased fraction of both moderate (b = 0.32, CI95% = [0.17,0.47], P = 2.89e - 05) and vigorous physical activity (b = 0.22, CI95% = [0.06,0.37], P = 0.007) lead to increased cognitive functioning. In contrast, we found no evidence of a causal effect of average physical activity on cognitive functioning, and no evidence of a reverse causal effect (cognitive functioning on any physical activity measures). These findings provide new evidence supporting a beneficial role of moderate and vigorous physical activity (MVPA) on cognitive functioning.

The collective effects of genetic variants and complex traits

Traditional approaches in studying the genetics of complex traits have focused on identifying specific genetic variants. However, the collective effects of variants have remained largely unexplored. Here, we evaluated whether traits could be influenced by the collective effects of variants across the entire protein coding-region of the genome or the entire genome. We studied the UK Biobank exome sequencing data of 167,246 individuals as well as the genome-wide SNP array data of 408,868 individuals. We calculated for each individual four different measures of genetic variation such as heterozygosity and number of variants and two different measures of the overall deleteriousness of all variants, and performed correlations with 17 representative traits that have been studied previously. Linear regression analysis was performed with adjustment for age, sex, and genetic principal components. The results showed a high correlation among the six different measures and an inverse association of two well-correlated traits (educational attainment and height) with the total number of all variants as well as the overall deleteriousness of all variants. We have also categorized the genes based on whether they are expressed in the brain and found that the association with educational attainment only held for the brain-expressed genes. No other traits examined showed a significant correlation with the brain-expressed genes. The study demonstrates that common traits could be studied by analyzing the overall genetic variation and suggests that educational attainment is inversely related to genetic variation.

Familial risk and heritability of intellectual disability: a population-based cohort study in Sweden

BACKGROUND

Intellectual disability (ID) aggregates in families, but factors affecting individual risk and heritability estimates remain unknown.

METHODS

A population-based family cohort study of 4,165,785 individuals born 1973-2013 in Sweden, including 37,787 ID individuals and their relatives. The relative risks (RR) of ID with 95% confidence intervals (95% CI) were obtained from stratified Cox proportional-hazards models. Relatives of ID individuals were compared to relatives of unaffected individuals. Structural equation modeling was used to estimate heritability.

RESULTS

Relatives of ID individuals were at increased risk of ID compared to individuals with unaffected relatives. The RR of ID among relatives increased proportionally to the degree of genetic relatedness with ID probands; 256.70(95% CI 161.30-408.53) for monozygotic twins, 16.47(13.32-20.38) for parents, 14.88(12.19-18.16) for children, 7.04(4.67-10.61) for dizygotic twins, 8.38(7.97-8.83) for full siblings, 4.56(4.02-5.16) for maternal, 2.90(2.49-3.37) for paternal half-siblings, 3.03(2.61-3.50) for nephews/nieces, 2.84(2.45-3.29) for uncles/aunts, and 2.04(1.91-2.20) for cousins. Lower RRs were observed for siblings of probands with chromosomal abnormalities (RR 5.53, 4.74-6.46) and more severe ID (mild RR 9.15, 8.55-9.78, moderate RR 8.13, 7.28-9.08, severe RR 6.80, 5.74-8.07, and profound RR 5.88, 4.52-7.65). Male sex of relative and maternal line of relationship with proband was related to higher risk (RR 1.33, 1.25-1.41 for brothers vs. sisters and RR 1.49, 1.34-1.68 for maternal vs. paternal half-siblings). ID was substantially heritable with 0.95(95% CI 0.93-0.98) of the variance in liability attributed to genetic influences.

CONCLUSIONS

The risk estimates will benefit researchers, clinicians, families in understanding the risk of ID in the family and the whole population. The higher risk of ID related to male sex and maternal linage will be of value for planning and interpreting etiological studies in ID.

The Need for a Specialized Neurocognitive Screen and Consistent Cognitive Impairment Criteria in Spinal Cord Injury: Analysis of the Suitability of the Neuropsychiatry Unit Cognitive Assessment Tool

The assessment of mild cognitive impairment (MCI) following spinal cord injury (SCI) is vital. However, there are no neurocognitive screens which have been developed specifically to meet the unique requirements for SCI, nor are there consistent MCI criteria applied to determine the rates of MCI. The aim of this study was to determine the suitability of a neurocognitive screen for assessing MCI in adults with SCI. A total of 127 participants were recruited. Socio-demographic and injury related variables were assessed. All participants completed the screen. Descriptive statistics are provided for total/domain screen scores and all items, and the screen’s ability to distinguish MCI was examined. Congeneric confirmatory factor analyses (CFA) were employed to investigate structural validity. The screen total score was sensitive to differences in neurocognitive capacity, as well as for time since the injury occurred (p < 0.01). The MCI rate ranged between 17−36%. CFA revealed attention and visuoconstruction domains had an adequate model fit and executive function had poor fit, while CFA models for memory and language did not fit the data (did not converge), hence could not be determined. While the screen differentiated between those with MCI and those without, and MCI as a function of time since injury, limitations of its suitability for assessing MCI after SCI exist, demonstrating the need for a specialized neurocognitive screen for adults with SCI.

Distinct Regionalization Patterns of Cortical Morphology are Associated with Cognitive Performance Across Different Domains

Cognitive performance in children is predictive of academic and social outcomes; therefore, understanding neurobiological mechanisms underlying individual differences in cognition during development may be important for improving quality of life. The belief that a single, psychological construct underlies many cognitive processes is pervasive throughout society. However, it is unclear if there is a consistent neural substrate underlying many cognitive processes. Here, we show that a distributed configuration of cortical surface area and apparent thickness, when controlling for global imaging measures, is differentially associated with cognitive performance on different types of tasks in a large sample (N = 10 145) of 9-11-year-old children from the Adolescent Brain and Cognitive DevelopmentSM (ABCD) study. The minimal overlap in these regionalization patterns of association has implications for competing theories about developing intellectual functions. Surprisingly, not controlling for sociodemographic factors increased the similarity between these regionalization patterns. This highlights the importance of understanding the shared variance between sociodemographic factors, cognition and brain structure, particularly with a population-based sample such as ABCD.

Causal relationships between genetically determined metabolites and human intelligence: a Mendelian randomization study

Intelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (P_IVW = 9.25 × 10^-5). The causal relationship was robust when sensitivity analyses were applied (P_MR-Egger = 0.0001, P_{Weighted median} = 6.29 × 10^-6, P_MR-PRESSO = 0.0007), and repeated analysis yielded consistent result (P_IVW = 0.0087). Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.

A general dimension of genetic sharing across diverse cognitive traits inferred from molecular data

It has been known since 1904 that, in humans, diverse cognitive traits are positively intercorrelated. This forms the basis for the general factor of intelligence (g). Here, we directly test whether there is a partial genetic basis for individual differences in g using data from seven different cognitive tests (n = 11,263-331,679) and genome-wide autosomal single-nucleotide polymorphisms. A genetic g factor accounts for an average of 58.4% (s.e. = 4.8%) of the genetic variance in the cognitive traits considered, with the proportion varying widely across traits (range, 9-95%). We distil genetic loci that are broadly relevant for many cognitive traits (g) from loci associated specifically with individual cognitive traits. These results contribute to elucidating the aetiology of a long-known yet poorly understood phenomenon, revealing a fundamental dimension of genetic sharing across diverse cognitive traits.

Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data

Human intelligence has always been a fascinating subject for scientists. Since the inception of Spearman's general intelligence in the early 1900s, there has been significant progress towards characterizing different aspects of intelligence and its relationship with structural and functional features of the brain. In recent years, the invention of sophisticated brain imaging devices using Diffusion-Weighted Imaging (DWI) and functional Magnetic Resonance Imaging (fMRI) has allowed researchers to test hypotheses about neural correlates of intelligence in humans.This review summarizes recent findings on the associations of human intelligence with neuroimaging data. To this end, first, we review the literature that has related brain morphometry to intelligence. Next, we elaborate on the applications of DWI and restingstate fMRI on the investigation of intelligence. Then, we provide a survey of literature that has used multimodal DWI-fMRI to shed light on intelligence. Finally, we discuss the state-of-the-art of individualized prediction of intelligence from neuroimaging data and point out future strategies. Future studies hold promising outcomes for machine learning-based predictive frameworks using neuroimaging features to estimate human intelligence.

Polygenic scores for schizophrenia and general cognitive ability: associations with six cognitive domains, premorbid intelligence, and cognitive composite score in individuals with a psychotic disorder and in healthy controls

Cognitive impairments are considered core features in schizophrenia and other psychotic disorders. Cognitive impairments are, to a lesser degree, also documented in healthy first-degree relatives. Although recent studies have shown (negative) genetic correlations between schizophrenia and general cognitive ability, the association between polygenic risk for schizophrenia and individual cognitive phenotypes remains unclear. We here investigated the association between a polygenic score for schizophrenia (SCZ_PGS) and six well-defined cognitive domains, in addition to a composite measure of cognitive ability and a measure of premorbid intellectual ability in 731 participants with a psychotic disorder and 851 healthy controls. We also investigated the association between a PGS for general cognitive ability (COG_PGS) and the same cognitive domains in the same sample. We found no significant associations between the SCZ_PGS and any cognitive phenotypes, in either patients with a psychotic disorder or healthy controls. For COG_PGS we observed stronger associations with cognitive phenotypes in healthy controls than in participants with psychotic disorders. In healthy controls, the association between COG_PGS (at the p value threshold of ≥0.01) and working memory remained significant after Bonferroni correction (β = 0.12, p = 8.6 × 10^-5). Altogether, the lack of associations between SCZ_PGS and COG_PGS with cognitive performance in participants with psychotic disorders suggests that either environmental factors or unassessed genetic factors play a role in the development of cognitive impairments in psychotic disorders. Working memory should be further studied as an important cognitive phenotype.

Estimating the heritability of psychological measures in the Human Connectome Project dataset

The Human Connectome Project (HCP) is a large structural and functional MRI dataset with a rich array of behavioral and genotypic measures, as well as a biologically verified family structure. This makes it a valuable resource for investigating questions about individual differences, including questions about heritability. While its MRI data have been analyzed extensively in this regard, to our knowledge a comprehensive estimation of the heritability of the behavioral dataset has never been conducted. Using a set of behavioral measures of personality, emotion and cognition, we show that it is possible to re-identify the same individual across two testing times (fingerprinting), and to identify identical twins significantly above chance. Standard heritability estimates of 37 behavioral measures were derived from twin correlations, and machine-learning models (univariate linear model, Ridge classifier and Random Forest model) were trained to classify monozygotic twins and dizygotic twins. Correlations between the standard heritability metric and each set of model weights ranged from 0.36 to 0.7, and questionnaire-based and task-based measures did not differ significantly in their heritability. We further explored the heritability of a smaller number of latent factors extracted from the 37 measures and repeated the heritability estimation; in this case, the correlations between the standard heritability and each set of model weights were lower, ranging from 0.05 to 0.43. One specific discrepancy arose for the general intelligence factor, which all models assigned high importance, but the standard heritability calculation did not. We present a thorough investigation of the heritabilities of the behavioral measures in the HCP as a resource for other investigators, and illustrate the utility of machine-learning methods for qualitative characterization of the differential heritability across diverse measures.

Motor timing training improves sustained attention performance but not fluid intelligence: near but not far transfer

Associations between cognitive and motor timing performance are documented in hundreds of studies. A core finding is a correlation of about - 0.3 to - 0.5 between psychometric intelligence and time interval production variability and reaction time, but the nature of the relationship remains unclear. Here, we investigated whether this relation is subject to near and far transfer across a battery of cognitive and timing tasks. These tasks were administered pre- and post-five daily 30 min sessions of sensorimotor synchronization training with feedback for every interval. The training group exhibited increased sustained attention performance in Conners' Continuous Performance Test II, but no change in the block design and figure weights subtests from the WAIS-IV. A passive control group exhibited no change in performance on any of the timing or cognitive tests. These findings provide evidence for a direct involvement of sustained attention in motor timing as well as near transfer from synchronization to unpaced serial interval production. Implications for the timing-cognition relationship are discussed in light of various putative timing mechanisms.

Gene and environment interplay in cognition: Evidence from twin and molecular studies, future directions and suggestions for effective candidate gene x environment (cGxE) research

Last decade of molecular research in the field of cognitive science has shown that no single approach can give satisfactory results as far as gene hunt is concerned. Cohesive theory of gene-environment interaction seems to be a rational idea for bridging the gap in our knowledge of disorders involving cognitive deficit. It may even be helpful to some extent in resolving issues of missing heritability. We review the current state of play in the area of cognition at genetic and environmental fronts. Evidence of apparent gene-environment (GxE) interactions from various studies has been mentioned with the aim of redirecting the focus of research community towards studying such interactions with the help of sensitive designs and molecular techniques. We re-evaluate candidate gene-environment research in order to emphasize its potential if carried out strategically.

Coupled cognitive changes in adulthood: A meta-analysis

With advancing age, healthy adults typically exhibit decreases in performance across many different cognitive abilities such as memory, processing speed, spatial ability, and abstract reasoning. However, there are marked individual differences in rates of cognitive decline, with some adults declining steeply and others maintaining high levels of functioning. To move toward a comprehensive understanding of cognitive aging, it is critical to know whether individual differences in longitudinal changes interrelate across different cognitive abilities. We identified 89 effect sizes representing shared variance in longitudinal cognitive change from 22 unique datasets composed of more than 30,000 unique individuals, which we meta-analyzed using a series of multilevel metaregression models. An average of 60% of the variation in cognitive changes was shared across cognitive abilities. Shared variation in changes increased with age, from approximately 45% at age 35 years to approximately 70% at age 85 years. There was a moderate-to-strong correspondence (r = .49, congruence coefficient = .98) between the extent to which a variable indicated general intelligence and the extent to which change in that variable indicated a general factor of aging-related change. Shared variation in changes did not differ substantially across cognitive ability domain classifications. In a sensitivity analysis based on studies that carefully controlled for dementia, shared variation in longitudinal cognitive changes remained at upward of 60%, and age-related increases in shared variation in cognitive changes continued to be evident. These results together provide strong evidence for a general factor of cognitive aging that strengthens with advancing adult age. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Genetic and Environmental Influences on Verbal Fluency in Middle Age: A Longitudinal Twin Study

Mounting evidence suggests that measures of phonemic fluency and semantic fluency are differentially associated with other cognitive and health phenotypes, but few studies have examined their shared and unique variance, especially using genetically-informative designs. In this study, 1464 middle-aged twins completed six fluency subtests at up to two time-points (mean age 56 and 62 years). Confirmatory factor analyses supported a two-factor solution: a General Fluency latent factor explained variation in all six subtests and a Semantic-Specific factor accounted for additional variance in semantic subtests. Both factors were explained primarily by genetic influences at both waves (a² = 0.57-0.76). There was considerable stability of individual differences over 6 years (r = .90 for General Fluency, r = .81 for Semantic-Specific), especially for genetic influences (r_g = .94 and 1.0, respectively). These results suggest that semantic fluency can be viewed as a combination of general and semantic-specific variance, but phonemic fluency is captured entirely by the general factor.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10^-8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

Strong genetic overlap between executive functions and intelligence

Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7 to 15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. (PsycINFO Database Record

Secular Slowing of Auditory Simple Reaction Time in Sweden (1959-1985)

There are indications that simple reaction time might have slowed in Western populations, based on both cohort- and multi-study comparisons. A possible limitation of the latter method in particular is measurement error stemming from methods variance, which results from the fact that instruments and experimental conditions change over time and between studies. We therefore set out to measure the simple auditory reaction time (SRT) of 7,081 individuals (2,997 males and 4,084 females) born in Sweden 1959-1985 (subjects were aged between 27 and 54 years at time of measurement). Depending on age cut-offs and adjustment for aging related slowing of SRT, the data indicate that SRT has increased by between 3 and 16 ms in the 27 birth years covered in the present sample. This slowing is unlikely to be explained by attrition, which was evaluated by comparing the general intelligence × birth-year interactions and standard deviations for both male participants and dropouts, utilizing military conscript cognitive ability data. The present result is consistent with previous studies employing alternative methods, and may indicate the operation of several synergistic factors, such as recent micro-evolutionary trends favoring lower g in Sweden and the effects of industrially produced neurotoxic substances on peripheral nerve conduction velocity.

Genetics and neuropsychology: A merger whose time has come

Genetics and neuropsychology have historically been 2 rather distant and unrelated fields. With the very rapid advances that have been taking place in genetics, research and treatment of disorders of cognition in the 21st century are likely to be increasingly informed by individual differences in genetics and epigenetics. Although neuropsychologists are not expected to become geneticists, it is our view that increased training in genetics should become more central to training in neuropsychology. This relationship should not be unidirectional. Here we note ways in which an understanding of genetics and epigenetics can inform neuropsychology. On the other hand, given the complexity of cognitive phenotypes, neuropsychology can also play a valuable role in informing and refining genetic studies. Greater integration of the 2 should advance both fields.

Is bigger always better? The importance of cortical configuration with respect to cognitive ability

General cognitive ability (GCA) has substantial explanatory power for behavioral and health outcomes, but its cortical substrate is still not fully established. GCA is highly polygenic and research to date strongly suggests that its cortical substrate is highly polyregional. We show in map-based and region-of-interest-based analyses of adult twins that a complex cortical configuration underlies GCA. Having relatively greater surface area in evolutionary and developmentally high-expanded prefrontal, lateral temporal, and inferior parietal regions is positively correlated with GCA, whereas relatively greater surface area in low-expanded occipital, medial temporal, and motor cortices is negatively correlated with GCA. Essentially the opposite pattern holds for relative cortical thickness. The phenotypic positive-to-negative gradients in our cortical-GCA association maps were largely driven by a similar pattern of genetic associations. The patterns are consistent with regional cortical stretching whereby relatively greater surface area is related to relatively thinner cortex in high-expanded regions. Thus, the typical "bigger is better" view does not adequately capture cortical-GCA associations. Rather, cognitive ability is influenced by complex configurations of cortical development patterns that are strongly influenced by genetic factors. Optimal cognitive ability appears to be driven both by the absolute size and the polyregional configuration of the entire cortex rather than by small, circumscribed regions.

Top 10 Replicated Findings From Behavioral Genetics

In the context of current concerns about replication in psychological science, we describe 10 findings from behavioral genetic research that have replicated robustly. These are "big" findings, both in terms of effect size and potential impact on psychological science, such as linearly increasing heritability of intelligence from infancy (20%) through adulthood (60%). Four of our top 10 findings involve the environment, discoveries that could have been found only with genetically sensitive research designs. We also consider reasons specific to behavioral genetics that might explain why these findings replicate.

Independent evidence for an association between general cognitive ability and a genetic locus for educational attainment

Cognitive deficits and reduced educational achievement are common in psychiatric illness; understanding the genetic basis of cognitive and educational deficits may be informative about the etiology of psychiatric disorders. A recent, large genome-wide association study (GWAS) reported a genome-wide significant locus for years of education, which subsequently demonstrated association to general cognitive ability ("g") in overlapping cohorts. The current study was designed to test whether GWAS hits for educational attainment are involved in general cognitive ability in an independent, large-scale collection of cohorts. Using cohorts in the Cognitive Genomics Consortium (COGENT; up to 20,495 healthy individuals), we examined the relationship between g and variants associated with educational attainment. We next conducted meta-analyses with 24,189 individuals with neurocognitive data from the educational attainment studies, and then with 53,188 largely independent individuals from a recent GWAS of cognition. A SNP (rs1906252) located at chromosome 6q16.1, previously associated with years of schooling, was significantly associated with g (P = 1.47 × 10(-4) ) in COGENT. The first joint analysis of 43,381 non-overlapping individuals for this a priori-designated locus was strongly significant (P = 4.94 × 10(-7) ), and the second joint analysis of 68,159 non-overlapping individuals was even more robust (P = 1.65 × 10(-9) ). These results provide independent replication, in a large-scale dataset, of a genetic locus associated with cognitive function and education. As sample sizes grow, cognitive GWAS will identify increasing numbers of associated loci, as has been accomplished in other polygenic quantitative traits, which may be relevant to psychiatric illness.

Genetic and environmental architecture of changes in episodic memory from middle to late middle age

Episodic memory is a complex construct at both the phenotypic and genetic level. Ample evidence supports age-related cognitive stability and change being accounted for by general and domain-specific factors. We hypothesized that general and specific factors would underlie change even within this single cognitive domain. We examined 6 measures from 3 episodic memory tests in a narrow age cohort at middle and late middle age. The factor structure was invariant across occasions. At both timepoints 2 of 3 test-specific factors (story recall, design recall) had significant genetic influences independent of the general memory factor. Phenotypic stability was moderate to high, and primarily accounted for by genetic influences, except for 1 test-specific factor (list learning). Mean change over time was nonsignificant for 1 test-level factor; 1 declined; 1 improved. The results highlight the phenotypic and genetic complexity of memory and memory change, and shed light on an understudied period of life.

What Does the Shipley-2 Measure for Children and Adolescents? Integrated and Conjoint Confirmatory Factor Analysis With the WISC-IV

We used integrated and conjoint confirmatory factor analysis of Shipley-2 and Wechsler Intelligence Scale for Children–Fourth Edition (WISC-IV) data to investigate constructs measured in the Shipley-2 for children and adolescents. We also estimated Shipley-2 composite reliability at the subtest level rather than the item level. The three Shipley-2 subtests for the most part measured what was described in the manual, although Block Patterns measured visual spatial ability in addition to fluid ability and Abstraction was best considered a measure of psychometric g. The g factors derived from the WISC-IV and Shipley-2 were similar but not identical. Internal reliability estimates for Shipley-2 composites that were based on correlations between the subtests were substantially lower than those based on the items. Last, based on WISC-IV derived g factors, 37% to 53% of the variance in Shipley-2 composites was explained by g. Some of the reliable variance in the Shipley-2 composites was due to something specific that the subtests had in common not explained by psychometric g.

Genetics and intelligence differences: five special findings

Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for 'positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century-Genome-wide Complex Trait Analysis (GCTA)-which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the 'missing heritability' gap.