Results of a "GWAS plus:" general cognitive ability is substantially heritable and massively polygenic

Association of Stmn1 Polymorphism and Cognitive Function: An Observational Study in the Chinese Adults

Background

Stathmin1 (Stmn1) is a protein highly expressed during the development of the central nervous system. The phosphorylation of Stmn1 involves microtubule dynamics, so Stmn1 plays a vital part in neurite outgrowth and synaptic plasticity. Previous studies reported that Stmn1 genetic variants influence fear and anxiety as well as cognitive-affective processing. However, no study reported on the relationship between Stmn1 gene polymorphism and cognition in Chinese. Thus, this association was investigated in the present study.

Methods

A total of 129 healthy Han Chinese were genotyped for Stmn1 rs182455 polymorphism by polymerase chain reaction and restriction fragment length polymorphism analyses. Cognitive function was assessed using the Stroop Color-Word Test (SCWT) and Hopkins Verbal Learning Test-Revised (HVLT-R).

Results

In the present sample, rs182455 CC, CT, and TT genotypes were found in 56 (43.41%), 65 (50.39%) and 8 (6.20%) cases, respectively. The genotype distribution did not deviate from Hardy-Weinberg equilibrium (χ2 = 3.715, p = 0.054). Significant differences were found between the three rs182455 genotypes and between the CC and (CT+TT) genotype groups in the Stroop Color (SC) scores of the SCWT (F = 3.322, 2.377; p = 0.039, 0.019, respectively) and the total recall (TR) scores on the HVLT-R (F = 3.118, 2.225; p = 0.048, 0.028, respectively). There was a female-specific difference in SC scores between the three rs182455 genotypes (F = 2.318, p = 0.023). The rs182455 genotype distribution showed no significant difference between two sexes (χ2 = 1.313, p = 0.519), whereas significant differences were seen in SC and TR scores between two sexes (t = -2.294, -2.490; p = 0.023, 0.014, respectively).

Conclusions

The findings suggest that rs182455 Stmn1 polymorphism might affect cognitive flexibility and immediate free recall in healthy Chinese individuals, especially females.

Postnatal Brain Trajectories and Maternal Intelligence Predict Childhood Outcomes in Complex CHD

Objective: To determine whether early structural brain trajectories predict early childhood neurodevelopmental deficits in complex CHD patients and to assess relative cumulative risk profiles of clinical, genetic, and demographic risk factors across early development. Study Design: Term neonates with complex CHDs were recruited at Texas Children's Hospital from 2005-2011. Ninety-five participants underwent three structural MRI scans and three neurodevelopmental assessments. Brain region volumes and white matter tract fractional anisotropy and radial diffusivity were used to calculate trajectories: perioperative, postsurgical, and overall. Gross cognitive, language, and visuo-motor outcomes were assessed with the Bayley Scales of Infant and Toddler Development and with the Wechsler Preschool and Primary Scale of Intelligence and Beery-Buktenica Developmental Test of Visual-Motor Integration. Multi-variable models incorporated risk factors. Results: Reduced overall period volumetric trajectories predicted poor language outcomes: brainstem ((β, 95% CI) 0.0977, 0.0382-0.1571; p = 0.0022) and white matter (0.0023, 0.0001-0.0046; p = 0.0397) at 5 years; brainstem (0.0711, 0.0157-0.1265; p = 0.0134) and deep grey matter (0.0085, 0.0011-0.0160; p = 0.0258) at 3 years. Maternal IQ was the strongest contributor to language variance, increasing from 37% at 1 year, 62% at 3 years, and 81% at 5 years. Genetic abnormality's contribution to variance decreased from 41% at 1 year to 25% at 3 years and was insignificant at 5 years. Conclusion: Reduced postnatal subcortical-cerebral white matter trajectories predicted poor early childhood neurodevelopmental outcomes, despite high contribution of maternal IQ. Maternal IQ was cumulative over time, exceeding the influence of known cardiac and genetic factors in complex CHD, underscoring the importance of heritable and parent-based environmental factors.

Utilizing maternal prenatal cognition as a predictor of newborn brain measures of intellectual development

Identifying reliable indicators of cognitive functioning prior to age five has been challenging. Prior studies have shown that maternal cognition, as indexed by intellectual quotient (IQ) and years of education, predict child intelligence at school age. We examined whether maternal full scale IQ, education, and inhibitory control (index of executive function) are associated with newborn brain measures and toddler language outcomes to assess potential indicators of early cognition. We hypothesized that maternal indices of cognition would be associated with brain areas implicated in intelligence in school-age children and adults in the newborn period. Thirty-seven pregnant women and their newborns underwent an MRI scan. T2-weighted images and surface-based morphometric analysis were used to compute local brain volumes in newborn infants. Maternal cognition indices were associated with local brain volumes for infants in the anterior and posterior cingulate, occipital lobe, and pre/postcentral gyrus - regions associated with IQ, executive function, or sensori-motor functions in children and adults. Maternal education and executive function, but not maternal intelligence, were associated with toddler language scores at 12 and 24 months. Newborn brain volumes did not predict language scores. Overall, the pre/postcentral gyrus and occipital lobe may be unique indicators of early intellectual development in the newborn period. Given that maternal executive function as measured by inhibitory control has robust associations with the newborn brain and is objective, brief, and easy to administer, it may be a useful predictor of early developmental and cognitive capacity for young children.

The impact of reproductive factors on the metabolic profile of females from menarche to menopause

We explore the relation between age at menarche, parity and age at natural menopause with 249 metabolic traits in over 65,000 UK Biobank women using multivariable regression, Mendelian randomization and negative control (parity only). Older age of menarche is related to a less atherogenic metabolic profile in multivariable regression and Mendelian randomization, which is largely attenuated when accounting for adult body mass index. In multivariable regression, higher parity relates to more particles and lipids in VLDL, which are not observed in male negative controls. In multivariable regression and Mendelian randomization, older age at natural menopause is related to lower concentrations of inflammation markers, but we observe inconsistent results for LDL-related traits due to chronological age-specific effects. For example, older age at menopause is related to lower LDL-cholesterol in younger women but slightly higher in older women. Our findings support a role of reproductive traits on later life metabolic profile and provide insights into identifying novel markers for the prevention of adverse cardiometabolic outcomes in women.

Genome-wide association study of population-standardised cognitive performance phenotypes in a rural South African community

Cognitive function is an indicator for global physical and mental health, and cognitive impairment has been associated with poorer life outcomes and earlier mortality. A standard cognition test, adapted to a rural-dwelling African community, and the Oxford Cognition Screen-Plus were used to capture cognitive performance as five continuous traits (total cognition score, verbal episodic memory, executive function, language, and visuospatial ability) for 2,246 adults in this population of South Africans. A novel common variant, rs73485231, reached genome-wide significance for association with episodic memory using data for ~14 million markers imputed from the H3Africa genotyping array data. Window-based replication of previously implicated variants and regions of interest support the discovery of African-specific associated variants despite the small population size and low allele frequency. This African genome-wide association study identifies suggestive associations with general cognition and domain-specific cognitive pathways and lays the groundwork for further genomic studies on cognition in Africa.

Genomic heritability and correlation between carcass traits in Japanese Black cattle evaluated under different ceilings of relatedness among individuals

The investigation of carcass traits to produce meat with high efficiency has been in focus on Japanese Black cattle since 1972. To implement a successful breeding program in carcass production, a comprehensive understanding of genetic characteristics and relationships between the traits is of paramount importance. In this study, genomic heritability and genomic correlation between carcass traits, including carcass weight (CW), rib eye area (REA), rib thickness (RT), subcutaneous fat thickness (SFT), yield rate (YI), and beef marbling score (BMS) were estimated using the genomic data of 9,850 Japanese Black cattle (4,142 heifers and 5,708 steers). In addition, we investigated the effect of genetic relatedness degree on the estimation of genetic parameters of carcass traits in sub-populations created based on different GRM-cutoff values. Genome-based restricted maximum likelihood (GREML) analysis was applied to estimate genetic parameters. Using all animal data, the heritability values for carcass traits were estimated as moderate to relatively high magnitude, ranging from 0.338 to 0.509 with standard errors, ranging from 0.014 to 0.015. The genetic correlations were obtained low and negative between SFT and REA [-0.198 (0.034)] and between SFT and BMS [-0.096 (0.033)] traits, and high and negative between SFT and YI [-0.634 (0.022)]. REA trait was genetically highly correlated with YI and BMS [0.811 (0.012) and 0.625 (0.022), respectively]. In sub-populations created based on the genetic-relatedness ceiling, the heritability estimates ranged from 0.212 (0.131) to 0.647 (0.066). At the genetic-relatedness ceiling of 0.15, the correlation values between most traits with low genomic correlation were overestimated while the correlations between the traits with relatively moderate to high correlations, ranging from 0.380 to 0.811, were underestimated. The values were steady at the ceilings of 0.30-0.95 (sample size of 5,443-9,850) for most of the highly correlated traits. The results demonstrated that there is considerable genetic variation and also favorable genomic correlations between carcass traits. Therefore, the genetic improvement for the traits can be simultaneously attained through genomic selection. In addition, we observed that depending on the degree of relationship between individuals and sample size, the genomic heritability and correlation estimates for carcass traits may be different.

General intelligence and executive functioning are overlapping but separable at genetic and molecular pathway levels: An analytical review of existing GWAS findings

Understanding the genomic architecture and molecular mechanisms of cognitive functioning in healthy individuals is critical for developing tailored interventions to enhance cognitive functioning, as well as for identifying targets for treating impaired cognition. There has been substantial progress in uncovering the genetic composition of the general cognitive ability (g). However, there is an ongoing debate whether executive functioning (EF)–another key predictor of cognitive health and performance, is separable from general g. To provide an analytical review on existing findings on genetic influences on the relationship between g and EF, we re-analysed a subset of genome-wide association studies (GWAS) from the GWAS catalogue that used measures of g and EF as outcomes in non-clinical populations. We identified two sets of single nucleotide polymorphisms (SNPs) associated with g (1,372 SNPs across 12 studies), and EF (300 SNPs across 5 studies) at p<5x10^-6. A comparative analysis of GWAS-identified g and EF SNPs in high linkage disequilibrium (LD), followed by pathway enrichment analyses suggest that g and EF are overlapping but separable at genetic variant and molecular pathway levels, however more evidence is required to characterize the genetic overlap/distinction between the two constructs. While not without limitations, these findings may have implications for navigating further research towards translatable genetic findings for cognitive remediation, enhancement, and augmentation.

Combining Structural-Equation Modeling with Genomic-Relatedness-Matrix Restricted Maximum Likelihood in OpenMx

There is a long history of fitting biometrical structural-equation models (SEMs) in the pregenomic behavioral-genetics literature of twin, family, and adoption studies. Recently, a method has emerged for estimating biometrical variance-covariance components based not upon the expected degree of genetic resemblance among relatives, but upon the observed degree of genetic resemblance among unrelated individuals for whom genome-wide genotypes are available-genomic-relatedness-matrix restricted maximum-likelihood (GREML). However, most existing GREML software is concerned with quickly and efficiently estimating heritability coefficients, genetic correlations, and so on, rather than with allowing the user to fit SEMs to multitrait samples of genotyped participants. We therefore introduce a feature in the OpenMx package, "mxGREML", designed to fit the biometrical SEMs from the pregenomic era in present-day genomic study designs. We explain the additional functionality this new feature has brought to OpenMx, and how the new functionality works. We provide an illustrative example of its use. We discuss the feature's current limitations, and our plans for its further development.

Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer's disease

Alzheimer's disease (AD) is a devastating neurological disorder characterized by changes in cell-type proportions and consequently marked alterations of the transcriptome. Here we use a data-driven systems biology meta-analytical approach across three human AD cohorts, encompassing six cortical brain regions, and integrate with multi-scale datasets comprising of DNA methylation, histone acetylation, transcriptome- and genome-wide association studies and quantitative trait loci to further characterize the genetic architecture of AD. We perform co-expression network analysis across more than 1200 human brain samples, identifying robust AD-associated dysregulation of the transcriptome, unaltered in normal human aging. We assess the cell-type specificity of AD gene co-expression changes and estimate cell-type proportion changes in human AD by integrating co-expression modules with single-cell transcriptome data generated from 27 321 nuclei from human postmortem prefrontal cortical tissue. We also show that genetic variants of AD are enriched in a microglial AD-associated module and identify key transcription factors regulating co-expressed modules. Additionally, we validate our results in multiple published human AD gene expression datasets, which can be easily accessed using our online resource (https://swaruplab.bio.uci.edu/consensusAD).

[A new look at the genetics of neurocognitive deficits in schizophrenia]

The article presents current literature data on genetic studies of neurocognitive deficit in schizophrenia, including the genes of neurotransmitter systems (dopaminergic, glutamatergic, and serotonergic); genes analyzed in genome-wide association studies (GWAS), as well as other genetic factors related to the pathophysiological mechanisms underlying schizophrenia and neurocognitive disorders.

Cortical Surfaces Mediate the Relationship Between Polygenic Scores for Intelligence and General Intelligence

Recent large-scale, genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with general intelligence. The cumulative influence of these loci on brain structure is unknown. We examined if cortical morphology mediates the relationship between GWAS-derived polygenic scores for intelligence (PSi) and g-factor. Using the effect sizes from one of the largest GWAS meta-analysis on general intelligence to date, PSi were calculated among 10 P value thresholds. PSi were assessed for the association with g-factor performance, cortical thickness (CT), and surface area (SA) in two large imaging-genetics samples (IMAGEN N = 1651; IntegraMooDS N = 742). PSi explained up to 5.1% of the variance of g-factor in IMAGEN (F1,1640 = 12.2-94.3; P < 0.005), and up to 3.0% in IntegraMooDS (F1,725 = 10.0-21.0; P < 0.005). The association between polygenic scores and g-factor was partially mediated by SA and CT in prefrontal, anterior cingulate, insula, and medial temporal cortices in both samples (PFWER-corrected < 0.005). The variance explained by mediation was up to 0.75% in IMAGEN and 0.77% in IntegraMooDS. Our results provide evidence that cumulative genetic load influences g-factor via cortical structure. The consistency of our results across samples suggests that cortex morphology could be a novel potential biomarker for neurocognitive dysfunction that is among the most intractable psychiatric symptoms.

Maternal and family factors differentiate profiles of psychiatric impairments in very preterm children at age 5-years

BACKGROUND

Very preterm (VPT; <30 weeks gestation) children are a heterogeneous group, yet the co-occurrence of psychiatric and neurodevelopmental impairments remains unclear. Moreover, the clinical and socio-environmental factors that promote resilient developmental outcomes among VPT children are poorly understood.

METHODS

One hundred and twenty five children (85 VPT and 40 full-term) underwent neurodevelopmental evaluation at age 5-years. Parents and teachers completed measures of internalizing, externalizing, attention-deficit/hyperactivity (ADHD), and autism symptoms. Psychiatric and neurodevelopmental measures were analyzed using Latent Profile Analysis. Multinomial regression examined the extent that infant, sociodemographic, and family factors, collected prospectively from birth to follow-up, independently differentiated resilient and impaired children.

RESULTS

Four latent profiles were identified, including a Typically Developing Group which represented 27.1% of the VPT group and 65.0% of the full-term group, an At-Risk Group with mild psychiatric and neurodevelopmental problems (VPT 44.7%, full-term 22.5%), a Psychiatric Group with moderate-to-severe psychiatric ratings (VPT 12.9%, full-term 10.0%), and a school-based Inattentive/Hyperactive Group (VPT 15.3%, full-term 2.5%). Clinical diagnoses were highest among the Psychiatric Group (80%). Factors that differentiated resilient and impaired subgroups of VPT children included prolonged exposure to maternal psychosocial distress (p ≤ .04), current family dysfunction (p ≤ .05), and maternal ADHD symptoms (p ≤ .02), whereas social risk index scores differentiated resilient and impaired full-term children (p < .03).

CONCLUSIONS

Lower levels of maternal distress, family dysfunction, and maternal ADHD symptoms were associated with resilience among VPT children. Maternal distress and family dysfunction are modifiable factors to be targeted as part of psychiatric interventions embedded in the long-term care of VPT children.

The genetic relationship between educational attainment and cognitive performance in major psychiatric disorders

Cognitive deficits are a core feature of psychiatric disorders like schizophrenia and bipolar disorder. Evidence supports a genome-wide polygenic score (GPS) for educational attainment (GPSEDU) can be used to explain variability in cognitive performance. We aimed to identify different cognitive domains associated with GPSEDU in a transdiagnostic clinical cohort of chronic psychiatric patients with known cognitive deficits. Bipolar and schizophrenia patients from the PsyCourse cohort (N = 730; 43% female) were used. Likewise, we tested whether GPSs for schizophrenia (GPSSZ) and bipolar disorder (GPSBD) were associated with cognitive outcomes. GPSEDU explained 1.5% of variance in the backward verbal digit span, 1.9% in the number of correctly recalled words of the Verbal Learning and Memory Test, and 1.1% in crystallized intelligence. These effects were robust to the influences of treatment and diagnosis. No significant associations between GPSSZ or GPSBD with cognitive outcomes were found. Furthermore, these risk scores did not confound the effect of GPSEDU on cognitive outcomes. GPSEDU explains a small fraction of cognitive performance in adults with psychiatric disorders, specifically for domains related to linguistic learning and working memory. Investigating such a proxy-phenotype longitudinally, could give intriguing insight into the disease course, highlighting at what time genes play a more influential role on cognitive performance. Better understanding the origin of these deficits might help identify those patients at risk for lower levels of functioning and poor social outcomes. Polygenic estimates may in the future be part of predictive models for more personalized interventions.

Genome-Wide Association Study of Latent Cognitive Measures in Adolescence: Genetic Overlap With Intelligence and Education

Individual differences in executive functions (EF) are heritable and predictive of academic attainment (AA). However, little is known about genetic contributions to EFs or their genetic relationship with AA and intelligence. We conducted genome-wide association analyses for processing speed (PS) and the latent EF measures of working memory (WM) and inhibitory control (IC) in 4,611 adolescents from the Avon Longitudinal Study of Parents and Children. While no loci reached genome-wide significance, common genetic variants explained 30% of the variance in WM and 19% in PS. In contrast, we failed to find common genetic contributions to IC. Finally, we examined shared genetic effects between EFs and general intelligence, AA and ADHD. We identified significant genetic correlations between WM, intelligence, and AA. A more specific pattern was observed for PS, with modest genetic overlap with intelligence. Together these findings highlight diversity in the genetic contributions to specific cognitive functions and their genetic relationship with educational and psychiatric outcomes.

Childhood growth and neurocognition are associated with distinct sets of metabolites

BACKGROUND

Undernutrition is a serious global problem that contributes to increased child morbidity and mortality, impaired neurocognitive development, and decreased educational and economic attainment. Current interventions are only marginally effective, and identification of associated metabolic pathways can offer new strategies for intervention.

METHODS

Plasma samples were collected at 9 and 36 months from a subset of the PROVIDE child cohort (n = 130). Targeted metabolomics was performed on bile acids, acylcarnitines, amino acids, phosphatidylcholines, and sphingomyelins. Metabolic associations with linear growth and neurocognitive outcomes at four years were evaluated using correlation and penalized-linear regression analysis as well as conditional random forest modeling.

FINDINGS

Different metabolites were associated with growth and neurocognitive outcomes. Improved growth outcomes were associated with higher concentrations of hydroxy-sphingomyelin and essential amino acids and lower levels of acylcarnitines and bile acid conjugation. Neurocognitive scores were largely associated with phosphatidylcholine species and early metabolic indicators of inflammation. All metabolites identified explain ~45% of growth and neurocognitive variation.

INTERPRETATION

Growth outcomes were predominantly associated with metabolites measured early in life (9 months), many of which were biomarkers of insufficient diet, environmental enteric dysfunction, and microbiome disruption. Hydroxy-sphingomyelin was a significant predictor of improved growth. Neurocognitive outcome was predominantly associated with 36 month phosphatidylcholines and inflammatory metabolites, which may serve as important biomarkers of optimal neurodevelopment. The distinct sets of metabolites associated with growth and neurocognition suggest that intervention may require targeted approaches towards distinct metabolic pathways. FUND: Bill & Melinda Gates Foundation (OP1173478); National Institutes of Health (AI043596, CA044579).

Aberrant structural and functional connectivity and neurodevelopmental impairment in preterm children

Background

Despite advances in antenatal and neonatal care, preterm birth remains a leading cause of neurological disabilities in children. Infants born prematurely, particularly those delivered at the earliest gestational ages, commonly demonstrate increased rates of impairment across multiple neurodevelopmental domains. Indeed, the current literature establishes that preterm birth is a leading risk factor for cerebral palsy, is associated with executive function deficits, increases risk for impaired receptive and expressive language skills, and is linked with higher rates of co-occurring attention deficit hyperactivity disorder, anxiety, and autism spectrum disorders. These same infants also demonstrate elevated rates of aberrant cerebral structural and functional connectivity, with persistent changes evident across advanced magnetic resonance imaging modalities as early as the neonatal period. Emerging findings from cross-sectional and longitudinal investigations increasingly suggest that aberrant connectivity within key functional networks and white matter tracts may underlie the neurodevelopmental impairments common in this population.

Main body

This review begins by highlighting the elevated rates of neurodevelopmental disorders across domains in this clinical population, describes the patterns of aberrant structural and functional connectivity common in prematurely-born infants and children, and then reviews the increasingly established body of literature delineating the relationship between these brain abnormalities and adverse neurodevelopmental outcomes. We also detail important, typically understudied, clinical, and social variables that may influence these relationships among preterm children, including heritability and psychosocial risks.

Conclusion

Future work in this domain should continue to leverage longitudinal evaluations of preterm infants which include both neuroimaging and detailed serial neurodevelopmental assessments to further characterize relationships between imaging measures and impairment, information necessary for advancing our understanding of modifiable risk factors underlying these disorders and best practices for improving neurodevelopmental trajectories in this high-risk clinical population.

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

Pedigree-based analyses of intelligence have reported that genetic differences account for 50-80% of the phenotypic variation. For personality traits these effects are smaller, with 34-48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20,000 individuals in the Generation Scotland family cohort genotyped for ~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance.

Moderating effect of mode of delivery on the genetics of intelligence: Explorative genome-wide analyses in ALSPAC

INTRODUCTION

Intelligence is a core construct of individual differences in cognitive abilities and a strong predictor of important life outcomes. Within recent years, rates of cesarean section have substantially increased globally, though little is known about its effect on neurodevelopmental trajectories. Thus, we aimed to investigate the influence of delivery by cesarean section on the genetics of intelligence in children.

METHODS

Participants were recruited through the Avon Longitudinal Study of Parents and Children (ALSPAC). Intelligence was measured by the Wechsler Intelligence Scale for Children (WISC). Genotyping was performed using the Illumina Human Hap 550 quad genome-wide SNP genotyping platform and was followed by imputation using MACH software. Genome-wide interaction analyses were conducted using linear regression.

RESULTS

A total of 2,421 children and 2,141,747 SNPs were subjected to the genome-wide interaction analyses. No variant reached genome-wide significance. The strongest interaction was observed at rs17800861 in the GRIN2A gene (β = -3.43, 95% CI = -4.74 to -2.12, p = 2.98E-07). This variant is predicted to be located within active chromatin compartments in the hippocampus and may influence binding of the NF-kappaB transcription factor.

CONCLUSIONS

Our results may indicate that mode of delivery might have a moderating effect on genetic disposition of intelligence in children. Studies of considerable sizes (>10,000) are likely required to more robustly detect variants governing such interaction. In summary, the presented findings prompt the need for further studies aimed at increasing our understanding of effects various modes of delivery may have on health outcomes in children.

Genetic Overlap between General Cognitive Function and Schizophrenia: A Review of Cognitive GWASs

General cognitive (intelligence) function is substantially heritable, and is a major determinant of economic and health-related life outcomes. Cognitive impairments and intelligence decline are core features of schizophrenia which are evident before the onset of the illness. Genetic overlaps between cognitive impairments and the vulnerability for the illness have been suggested. Here, we review the literature on recent large-scale genome-wide association studies (GWASs) of general cognitive function and correlations between cognitive function and genetic susceptibility to schizophrenia. In the last decade, large-scale GWASs (n > 30,000) of general cognitive function and schizophrenia have demonstrated that substantial proportions of the heritability of the cognitive function and schizophrenia are explained by a polygenic component consisting of many common genetic variants with small effects. To date, GWASs have identified more than 100 loci linked to general cognitive function and 108 loci linked to schizophrenia. These genetic variants are mostly intronic or intergenic. Genes identified around these genetic variants are densely expressed in brain tissues. Schizophrenia-related genetic risks are consistently correlated with lower general cognitive function (rg = -0.20) and higher educational attainment (rg = 0.08). Cognitive functions are associated with many of the socioeconomic and health-related outcomes. Current treatment strategies largely fail to improve cognitive impairments of schizophrenia. Therefore, further study is needed to understand the molecular mechanisms underlying both cognition and schizophrenia.

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10-8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

Maternal intelligence quotient (IQ) predicts IQ and language in very preterm children at age 5 years

BACKGROUND

Sociodemographic factors are linked to cognitive outcomes in children born very preterm (VPT; ≤30 weeks gestation). The influence of maternal intellectual ability, a heritable trait, is unknown. Also undetermined is the extent to which associations between maternal and child intellectual ability vary according to parenting behaviors that target cognitive stimulation in the home.

METHODS

At age 5 years, 84 VPT and 38 demographically matched full-term (FT) children underwent neurodevelopmental assessment. Children's intellectual ability was assessed using The Wechsler Preschool Primary Scale of Intelligence-III, and language was assessed with the Clinical Evaluation of Language Fundamentals Preschool-2. The Wechsler Test of Adult Reading estimated maternal intellectual ability. The StimQ-Preschool questionnaire provided a measure of cognitive stimulation in the home. Linear mixed-effects models examined independent effects and interactions between maternal intellectual ability and cognitive stimulation on children's outcomes.

RESULTS

After covariate adjustment, maternal intellectual ability was associated with child intellectual (p < .001) and language (p = .002) abilities. Stronger associations were observed in FT mother-child dyads (B = .63, p = .04) than VPT dyads (B = .42, p = .01). Mothers of VPT children reported lower levels of Parental Involvement in Developmental Advance (p = .007) and Parental Verbal Responsiveness (p = .04). Group differences in Parental Involvement in Developmental Advance, but not Parental Verbal Responsivity, persisted after adjusting for social background (p = .03). There was no evidence of an interaction between maternal intellectual ability and Parental Involvement in Developmental Advance (p = .34). Instead, maternal intellectual ability (p < .001) and Parental Involvement in Developmental Advance (p = .05) independently predicted VPT children's outcomes.

CONCLUSIONS

Maternal intellectual ability is an important trait linked to VPT and FT children's intellectual and language outcomes. Prematurity increases variation in the heritability of intellectual ability and shifts children from the expected range based on maternal ability. Parental involvement in activities that help children master new skills may promote cognitive development in VPT children born to mothers of lower intellectual ability.

Heritability of Neuropsychological Measures in Schizophrenia and Nonpsychiatric Populations: A Systematic Review and Meta-analysis

Schizophrenia is characterized by neuropsychological deficits across many cognitive domains. Cognitive phenotypes with high heritability and genetic overlap with schizophrenia liability can help elucidate the mechanisms leading from genes to psychopathology. We performed a meta-analysis of 170 published twin and family heritability studies of >800 000 nonpsychiatric and schizophrenia subjects to accurately estimate heritability across many neuropsychological tests and cognitive domains. The proportion of total variance of each phenotype due to additive genetic effects (A), shared environment (C), and unshared environment and error (E), was calculated by averaging A, C, and E estimates across studies and weighting by sample size. Heritability ranged across phenotypes, likely due to differences in genetic and environmental effects, with the highest heritability for General Cognitive Ability (32%-67%), Verbal Ability (43%-72%), Visuospatial Ability (20%-80%), and Attention/Processing Speed (28%-74%), while the lowest heritability was observed for Executive Function (20%-40%). These results confirm that many cognitive phenotypes are under strong genetic influences. Heritability estimates were comparable in nonpsychiatric and schizophrenia samples, suggesting that environmental factors and illness-related moderators (eg, medication) do not substantially decrease heritability in schizophrenia samples, and that genetic studies in schizophrenia samples are informative for elucidating the genetic basis of cognitive deficits. Substantial genetic overlap between cognitive phenotypes and schizophrenia liability (average rg = -.58) in twin studies supports partially shared genetic etiology. It will be important to conduct comparative studies in well-powered samples to determine whether the same or different genes and genetic variants influence cognition in schizophrenia patients and the general population.

A Dopamine Receptor genetic variant enhances perceptual speed in cognitive healthy subjects

Introduction

Cognition is under strong genetic control, yet the specific genes are unknown.

Methods

One hundred and fifty-three cognitive healthy European subjects from the Reference Abilities Study (RANN) were genotyped for 1,160 variants within 446 neuropsychiatric genes. Adjusted linear regression models evaluated the association between the genetic variants and four reference abilities (Vocabulary, Episodic Memory, Perceptual Speed, and Reasoning).

Results

One hundred and fifty-nine variants nominally were found significant in the RANN cohort and re-evaluated in an independent cohort of 868 cognitive healthy subjects from the Religious Orders Study and Rush Memory Aging Project. Meta-analysis yielded a Bonferroni adjusted statistically significant association between perceptual speed and a variant located in the promoter of the dopamine receptor D4 gene, rs3756450 (β = 0.23, standard error = 0.05, P_meta = 2.3 × 10⁻⁵).

Discussion

Our data suggest that genetic variation in a dopamine pathway gene influences perceptual speed performance in cognitively healthy individuals.

Detection and validation of genomic regions associated with resistance to rust diseases in a worldwide hexaploid wheat landrace collection using BayesR and mixed linear model approaches

BayesR and MLM association mapping approaches in common wheat landraces were used to identify genomic regions conferring resistance to Yr, Lr, and Sr diseases. Deployment of rust resistant cultivars is the most economically effective and environmentally friendly strategy to control rust diseases in wheat. However, the highly evolving nature of wheat rust pathogens demands continued identification, characterization, and transfer of new resistance alleles into new varieties to achieve durable rust control. In this study, we undertook genome-wide association studies (GWAS) using a mixed linear model (MLM) and the Bayesian multilocus method (BayesR) to identify QTL contributing to leaf rust (Lr), stem rust (Sr), and stripe rust (Yr) resistance. Our study included 676 pre-Green Revolution common wheat landrace accessions collected in the 1920-1930s by A.E. Watkins. We show that both methods produce similar results, although BayesR had reduced background signals, enabling clearer definition of QTL positions. For the three rust diseases, we found 5 (Lr), 14 (Yr), and 11 (Sr) SNPs significant in both methods above stringent false-discovery rate thresholds. Validation of marker-trait associations with known rust QTL from the literature and additional genotypic and phenotypic characterisation of biparental populations showed that the landraces harbour both previously mapped and potentially new genes for resistance to rust diseases. Our results demonstrate that pre-Green Revolution landraces provide a rich source of genes to increase genetic diversity for rust resistance to facilitate the development of wheat varieties with more durable rust resistance.

'Mr Cummings clearly does not understand the science of genetics and should maybe go back to school on the subject': an exploratory content analysis of the online comments beneath a controversial news story

An article published in the UK Guardian on 11/10/2013 with the headline 'Genetics outweighs teaching, Gove advisor tells his boss' reported a leaked document written by special advisor Dominic Cummings to the then UK Secretary of State for Education, Michael Gove. The article generated 3008 on-line reader comments from the public. These reader comments offer a naturalistic opportunity to understand public opinion regarding Cummings' controversial suggestions and ideas. We conducted a content analysis of n = 800 reader comments, coding them on the basis of level of agreement with the ideas and opinions expressed in the article. Of all aspects of education mentioned, Cummings' reported views on genetics were commented upon most frequently and were subject to the most opposition from commenters, but also the most support. Findings offer some insight into the challenges involved in conducting public discourse about the relevance of genes in education. We discuss the accuracy with which Cummings' views were presented and the effect this may have had on reader responses to the points being raised.

Single Nucleotide Polymorphism Heritability of a General Psychopathology Factor in Children

OBJECTIVE

Co-occurrence of mental disorders is commonly observed, but the etiology underlying this observation is poorly understood. Studies in adolescents and adults have identified a general psychopathology factor associated with a high risk for different psychiatric disorders. We defined a multi-informant general psychopathology factor in school-aged children and estimated its single nucleotide polymorphism (SNP) heritability. The goal was to test the hypothesis that child behavioral and emotional problems are under the influence of highly pleiotropic common autosomal genetic variants that nonspecifically increase the risk for different dimensions of psychopathology.

METHOD

Children from the Generation R cohort were repeatedly assessed between ages 6 to 8 years. Child behavior problems were reported by parents, teachers, and children. Confirmatory factor analysis estimated a general psychopathology factor across informants using various psychiatric problem scales. Validation of the general psychopathology factor was based on IQ and temperamental measures. Genome-wide complex trait analysis (GCTA) was used to estimate the SNP heritability (N = 2,115).

RESULTS

The general psychopathology factor was associated with lower IQ, higher negative affectivity, and lower effortful control, but not with surgency. Importantly, the general psychopathology factor showed a significant SNP heritability of 38% (SE = 0.16, p = .008).

CONCLUSION

Common autosomal SNPs are pleiotropically associated with internalizing, externalizing, and other child behavior problems, and underlie a general psychopathology factor in childhood.

Age-Dependent Pleiotropy Between General Cognitive Function and Major Psychiatric Disorders

BACKGROUND

General cognitive function predicts psychiatric illness across the life course. This study examines the role of pleiotropy in explaining the link between cognitive function and psychiatric disorder.

METHODS

We used two large genome-wide association study data sets on cognitive function-one from older age, n = 53,949, and one from childhood, n = 12,441. We also used genome-wide association study data on educational attainment, n = 95,427, to examine the validity of its use as a proxy phenotype for cognitive function. Using a new method, linkage disequilibrium regression, we derived genetic correlations, free from the confounding of clinical state between psychiatric illness and cognitive function.

RESULTS

We found a genetic correlation of .711 (p = 2.26e-12) across the life course for general cognitive function. We also showed a positive genetic correlation between autism spectrum disorder and cognitive function in childhood (rg = .360, p = .0009) and for educational attainment (rg = .322, p = 1.37e-5) but not in older age. In schizophrenia, we found a negative genetic correlation between older age cognitive function (rg = -.231, p = 3.81e-12) but not in childhood or for educational attainment. For Alzheimer's disease, we found negative genetic correlations with childhood cognitive function (rg = -.341, p = .001), educational attainment (rg = -.324, p = 1.15e-5), and with older age cognitive function (rg = -.324, p = 1.78e-5).

CONCLUSIONS

The pleiotropy exhibited between cognitive function and psychiatric disorders changed across the life course. These age-dependent associations might explain why negative selection has not removed variants causally associated with autism spectrum disorder or schizophrenia.

The interface between genetics and psychology: lessons from developmental dyslexia

Developmental dyslexia runs in families, and twin studies have confirmed that there is a substantial genetic contribution to poor reading. The way in which discoveries in molecular genetics are reported can be misleading, encouraging us to think that there are specific genes that might be used to screen for disorder. However, dyslexia is not a classic Mendelian disorder that is caused by a mutation in a single gene. Rather, like many other common disorders, it appears to involve combined effects of many genes and environmental factors, each of which has a small influence, possibly supplemented by rare variants that have larger effects but apply to only a minority of cases. Furthermore, to see clearer relationships between genotype and phenotype, we may need to move beyond the clinical category of dyslexia to look at underlying cognitive deficits that may be implicated in other neurodevelopmental disorders.

Examining non-syndromic autosomal recessive intellectual disability (NS-ARID) genes for an enriched association with intelligence differences

Two themes are emerging regarding the molecular genetic aetiology of intelligence. The first is that intelligence is influenced by many variants and those that are tagged by common single nucleotide polymorphisms account for around 30% of the phenotypic variation. The second, in line with other polygenic traits such as height and schizophrenia, is that these variants are not randomly distributed across the genome but cluster in genes that work together. Less clear is whether the very low range of cognitive ability (intellectual disability) is simply one end of the normal distribution describing individual differences in cognitive ability across a population. Here, we examined 40 genes with a known association with non-syndromic autosomal recessive intellectual disability (NS-ARID) to determine if they are enriched for common variants associated with the normal range of intelligence differences. The current study used the 3511 individuals of the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium. In addition, a text mining analysis was used to identify gene sets biologically related to the NS-ARID set. Gene-based tests indicated that genes implicated in NS-ARID were not significantly enriched for quantitative trait loci (QTL) associated with intelligence. These findings suggest that genes in which mutations can have a large and deleterious effect on intelligence are not associated with variation across the range of intelligence differences.

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Only three loci have been associated with intelligence.

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In traits such as height common variants are found in the same genes as rare variants.

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We hypothesise that intelligence may also follow this trend.

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We examine genes where rare variants can produce large deleterious effects on IQ.

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No enrichment was found for the non-syndromic intellectual disability gene set.