Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance.

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRSs) for schizophrenia (SCZ) and a clinical diagnosis of SCZ, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures in the patient-derived neurons that implicated altered Na+ channel function, action potential interspike interval, and gamma-aminobutyric acid-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these SCZ patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

Antipsychotic medication-mediated cognitive change in schizophrenia and polygenic score for cognitive ability.

Cognitive symptoms of schizophrenia are reported to be minimally responsive to treatment with antipsychotic medications, though variability exists and many prior studies have significant confounds. Here, we examined the response of cognitive symptoms to antipsychotic medications in 71 inpatients with schizophrenia on and off antipsychotic medications in a blinded, placebo-controlled, cross-over study design. Patients received either antipsychotic medication monotherapy or placebo for 4-6 weeks before switching conditions. Neuropsychological testing, including working memory, intelligence, episodic memory, and verbal fluency tests, was administered during each condition. Additionally, we assessed whether polygenic scores for cognitive ability (PGScog) related to variability in antipsychotic medication-induced changes in cognitive performance. Overall, significant changes in cognition were not observed in response to medications (p's > 0.05) except for in episodic memory (p = 0.01), which showed a medication-related improvement. Some antipsychotic medication-related cognitive changes were associated with genetic predisposition to cognitive ability: PGScog showed positive correlations with medication-induced improvements in verbal list learning (p = 0.02) and category fluency (p = 0.03). Our primary results reinforce the notion that in general, cognitive measures are minimally responsive to antipsychotic medication. However, PGScog results suggest that genetic variation may influence the ability of current treatments to affect cognitive change within this patient population. This study underscores the need for development of novel treatment options specifically targeting cognitive symptoms as well as the importance of genetic variability in treatment response for patients with schizophrenia.

Neanderthal-derived genetic variation in living humans relates to schizophrenia diagnosis, to psychotic symptom severity, and to dopamine synthesis.

Schizophrenia has been hypothesized to be a human-specific condition, but experimental approaches to testing this idea have been limited. Because Neanderthals, our closest evolutionary relatives, interbred with modern humans prior to their disappearance from the fossil record, leaving a residual echo that survives in our DNA today, we leveraged new discoveries about ancient hominid DNA to explore this hypothesis in living people in three converging ways. First, in four independent case-control datasets totaling 9,362 individuals, individuals with schizophrenia had less Neanderthal-derived genetic variation than controls (p = .044). Second, in 49 unmedicated inpatients with schizophrenia, having more Neanderthal admixture predicted less severe positive symptoms (p = .046). Finally, using 18 F-fluorodopa PET scanning in 172 healthy individuals, having greater Neanderthal introgression was significantly associated with lower dopamine synthesis capacity in the striatum and pons (p's < 2 × 10-5 ), which is fundamentally important in the pathophysiology and treatment of psychosis. These results may help to elucidate the evolutionary history of a devastating neuropsychiatric disease by supporting the notion of schizophrenia as a human-specific condition. Additionally, the relationship between Neanderthal admixture and dopamine function suggests a potential mechanism whereby Neanderthal admixture may have affected our gene pool to alter schizophrenia risk and/or course.

Association Between Cardiovascular Risk Factors and Cognitive Impairment in People With Schizophrenia: A Systematic Review and Meta-analysis.

Importance: Schizophrenia is associated with cognitive dysfunction and cardiovascular risk factors, including metabolic syndrome (MetS) and its constituent criteria. Cognitive dysfunction and cardiovascular risk factors can worsen cognition in the general population and may contribute to cognitive impairment in schizophrenia. Objective: To study the association between cognitive dysfunction and cardiovascular risk factors and cognitive impairment in individuals with schizophrenia. Data Sources: A search was conducted of Embase, Scopus, MEDLINE, PubMed, and Cochrane databases from inception to February 25, 2020, using terms that included synonyms of schizophrenia AND metabolic adversities AND cognitive function. Conference proceedings, clinical trial registries, and reference lists of relevant publications were also searched. Study Selection: Studies were included that (1) examined cognitive functioning in patients with schizophrenia or schizoaffective disorder; (2) investigated the association of cardiovascular disease risk factors, including MetS, diabetes, obesity, overweight, obesity or overweight, hypertension, dyslipidemia, and insulin resistance with outcomes; and (3) compared cognitive performance of patients with schizophrenia/schizoaffective disorder between those with vs without cardiovascular disease risk factors. Data Extraction and Synthesis: Extraction of data was conducted by 2 to 3 independent reviewers per article. Data were meta-analyzed using a random-effects model. Main Outcomes and Measures: The primary outcome was global cognition, defined as a test score using clinically validated measures of overall cognitive functioning. Results: Twenty-seven studies involving 10 174 individuals with schizophrenia were included. Significantly greater global cognitive deficits were present in patients with schizophrenia who had MetS (13 studies; n = 2800; effect size [ES] = 0.31; 95% CI, 0.13-0.50; P = .001), diabetes (8 studies; n = 2976; ES = 0.32; 95% CI, 0.23-0.42; P < .001), or hypertension (5 studies; n = 1899; ES = 0.21; 95% CI, 0.11-0.31; P < .001); nonsignificantly greater deficits were present in patients with obesity (8 studies; n = 2779; P = .20), overweight (8 studies; n = 2825; P = .41), and insulin resistance (1 study; n = 193; P = .18). Worse performance in specific cognitive domains was associated with cognitive dysfunction and cardiovascular risk factors regarding 5 domains in patients with diabetes (ES range, 0.23 [95% CI, 0.12-0.33] to 0.40 [95% CI, 0.20-0.61]) and 4 domains with MetS (ES range, 0.15 [95% CI, 0.03-0.28] to 0.40 [95% CI, 0.20-0.61]) and hypertension (ES range, 0.15 [95% CI, 0.04-0.26] to 0.27 [95% CI, 0.15-0.39]). Conclusions and Relevance: In this systematic review and meta-analysis, MetS, diabetes, and hypertension were significantly associated with global cognitive impairment in people with schizophrenia.

Distinct Polygenic Score Profiles in Schizophrenia Subgroups With Different Trajectories of Cognitive Development.

OBJECTIVE: Different cognitive development histories in schizophrenia may reflect variation across dimensions of genetic influence. The authors derived and characterized cognitive development trajectory subgroups within a schizophrenia sample and profiled the subgroups across polygenic scores (PGSs) for schizophrenia, cognition, educational attainment, and attention deficit hyperactivity disorder (ADHD). METHODS: Demographic, clinical, and genetic data were collected at the National Institute of Mental Health from 540 schizophrenia patients, 247 unaffected siblings, and 844 control subjects. Cognitive trajectory subgroups were derived through cluster analysis using estimates of premorbid and current IQ. PGSs were generated using standard methods. Associations were tested using general linear models and logistic regression. RESULTS: Cluster analyses identified three cognitive trajectory subgroups in the schizophrenia group: preadolescent cognitive impairment (19%), adolescent disruption of cognitive development (44%), and cognitively stable adolescent development (37%). Together, the four PGSs significantly predicted 7.9% of the variance in subgroup membership. Subgroup characteristics converged with genetic patterns. Cognitively stable individuals had the best adult clinical outcomes and differed from control subjects only in schizophrenia PGSs. Those with adolescent disruption of cognitive development showed the most severe symptoms after diagnosis and were cognitively impaired. This subgroup had the highest schizophrenia PGSs and had disadvantageous cognitive PGSs relative to control subjects and cognitively stable individuals. Individuals showing preadolescent impairment in cognitive and academic performance and poor adult outcome exhibited a generalized PGS disadvantage relative to control subjects and were the only subgroup to differ significantly in education and ADHD PGSs. CONCLUSIONS: Subgroups derived from patterns of premorbid and current IQ showed different premorbid and clinical characteristics, which converged with broad genetic profiles. Simultaneous analysis of multiple PGSs may contribute to useful clinical stratification in schizophrenia.

Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways.

Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways.

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

Multi-Trait Analysis of GWAS and Biological Insights Into Cognition: A Response to Hill (2018).

Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'.

Role of gamma-amino-butyric acid in the dorsal anterior cingulate in age-associated changes in cognition.

GABAergic mechanisms have been shown to contribute to cognitive aging in animal models, but there is currently limited in vivo evidence to support this relationship in humans. It is also unclear whether aging is associated with changes in GABA levels measured with proton magnetic resonance spectroscopy (MRS). Spectral-editing MRS at 3 T was used to measure GABA in the dorsal anterior cingulate cortex (dACC) for a large sample of healthy volunteers (N = 229) aged 18-55. In a subset of 171 participants, age effects on several cognitive tasks were studied. We formally tested whether the MRS measures mediated the relationship between age and cognition. Robust associations of age with performance were found for the Wisconsin Card Sorting Test ([WCST], p < 0.0001). Age was also significantly associated with declining levels of GABA in the dACC (p < 0.001), and GABA levels significantly predicted WCST performance (p < 0.0004). Mediation analysis revealed that GABA in the dACC mediated the effect of age on WCST performance (p < 0.01). Other metabolites were similarly associated with age, but only GABA and creatine levels were significantly associated with WCST performance. No association with age or cognitive performance was found in a frontal white matter control region in a subset of participants. The association of GABA with WCST performance was not related to the amount of brain atrophy associated with aging as measured by the proportion of CSF, gray, and white matter in the MRS voxel. These results implicate GABAergic and possibly energetic metabolism in the dACC as mechanisms of age effects in executive function.

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence.

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

A method for determining haploid and triploid genotypes and their association with vascular phenotypes in Williams syndrome and 7q11.23 duplication syndrome.

BACKGROUND: Williams syndrome ([WS], 7q11.23 hemideletion) and 7q11.23 duplication syndrome (Dup7) show contrasting syndromic symptoms. However, within each group there is considerable interindividual variability in the degree to which these phenotypes are expressed. Though software exists to identify areas of copy number variation (CNV) from commonly-available SNP-chip data, this software does not provide non-diploid genotypes in CNV regions. Here, we describe a method for identifying haploid and triploid genotypes in CNV regions, and then, as a proof-of-concept for applying this information to explain clinical variability, we test for genotype-phenotype associations. METHODS: Blood samples for 25 individuals with WS and 13 individuals with Dup7 were genotyped with Illumina-HumanOmni5M SNP-chips. PennCNV and in-house code were used to make genotype calls for each SNP in the 7q11.23 locus. We tested for association between the presence of aortic arteriopathy and genotypes of the remaining (haploid in WS) or duplicated (triploid in Dup7) alleles. RESULTS: Haploid calls in the 7q11.23 region were made for 99.0% of SNPs in the WS group, and triploid calls for 98.8% of SNPs in those with Dup7. The G allele of SNP rs2528795 in the ELN gene was associated with aortic stenosis in WS participants (p < 0.0049) while the A allele of the same SNP was associated with aortic dilation in Dup7. CONCLUSIONS: Commonly available SNP-chip information can be used to make haploid and triploid calls in individuals with CNVs and then to relate variability in specific genes to variability in syndromic phenotypes, as demonstrated here using aortic arteriopathy. This work sets the stage for similar genotype-phenotype analyses in CNVs where phenotypes may be more complex and/or where there is less information about genetic mechanisms.

Attacking Heterogeneity in Schizophrenia by Deriving Clinical Subgroups From Widely Available Symptom Data.

Previous research has identified (1) a "deficit" subtype of schizophrenia characterized by enduring negative symptoms and diminished emotionality and (2) a "distress" subtype associated with high emotionality-including anxiety, depression, and stress sensitivity. Individuals in deficit and distress categories differ sharply in development, clinical course and behavior, and show distinct biological markers, perhaps signaling different etiologies. We tested whether deficit and distress subtypes would emerge from a simple but novel data-driven subgrouping analysis, based on Positive and Negative Syndrome Scale (PANSS) negative and distress symptom dimensions, and whether subgrouping was informative regarding other facets of behavior and brain function. PANSS data, and other assessments, were available for 549 people with schizophrenia diagnoses. Negative and distress symptom composite scores were used as indicators in 2-step cluster analyses, which divided the sample into low symptom (n = 301), distress (n = 121), and deficit (n = 127) subgroups. Relative to the low-symptom group, the deficit and distress subgroups had comparably higher total PANSS symptoms (Ps < .001) and were similarly functionally impaired (eg, global functioning [GAF] Ps < .001), but showed markedly different patterns on symptom, cognitive and personality variables, among others. Initial analyses of functional magnetic resonance imaging (fMRI) data from a 182-participant subset of the full sample also suggested distinct patterns of neural recruitment during working memory. The field seeks more neuroscience-based systems for classifying psychiatric conditions, but these are inescapably behavioral disorders. More effective parsing of clinical and behavioral traits could identify homogeneous target groups for further neural system and molecular studies, helping to integrate clinical and neuroscience approaches.

Symptom dimensions and subgroups in childhood-onset schizophrenia.

OBJECTIVE: This study investigated symptom dimensions and subgroups in the National Institute of Mental Health (NIMH) childhood-onset schizophrenia (COS) cohort and their similarities to adult-onset schizophrenia (AOS) literature. METHOD: Scores from the Scales for the Assessment of Positive and Negative Symptoms (SAPS & SANS) from 125 COS patients were assessed for fit with previously established symptom dimensions from AOS literature using confirmatory factor analysis (CFA). K-means cluster analysis of each individual's scores on the best fitting set of dimensions was used to form patient clusters, which were then compared using demographic and clinical data. RESULTS: CFA showed the SAPS & SANS data was well suited to a 2-dimension solution, including positive and negative dimensions, out of five well established models. Cluster analysis identified three patient groups characterized by different dimension scores: (1) low scores on both dimensions, (2) high negative, low positive scores, and (3) high scores on both dimensions. These groups had different Full scale IQ, Children's Global Assessment Scale (CGAS) scores, ages of onset, and prevalence of some co-morbid behavior disorders (all p<3.57E-03). CONCLUSION: Our analysis found distinct symptom-based subgroups within the NIMH COS cohort using an established AOS symptom structure. These findings confirm the heterogeneity of COS and were generally consistent with AOS literature.

Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets.

Here, we present a large (n = 107,207) genome-wide association study (GWAS) of general cognitive ability ("g"), further enhanced by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with general cognitive ability. Results showed significant enrichment for genes causing Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis implicated the biological processes of neurogenesis and synaptic regulation, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker, and LY97241, a potassium channel inhibitor. Transcriptome-wide and epigenome-wide analysis revealed that the implicated loci were enriched for genes expressed across all brain regions (most strongly in the cerebellum). Enrichment was exclusive to genes expressed in neurons but not oligodendrocytes or astrocytes. Finally, we report genetic correlations between cognitive ability and disparate phenotypes including psychiatric disorders, several autoimmune disorders, longevity, and maternal age at first birth.

Neanderthal-Derived Genetic Variation Shapes Modern Human Cranium and Brain.

Before their disappearance from the fossil record approximately 40,000 years ago, Neanderthals, the ancient hominin lineage most closely related to modern humans, interbred with ancestors of present-day humans. The legacy of this gene flow persists through Neanderthal-derived variants that survive in modern human DNA; however, the neural implications of this inheritance are uncertain. Here, using MRI in a large cohort of healthy individuals of European-descent, we show that the amount of Neanderthal-originating polymorphism carried in living humans is related to cranial and brain morphology. First, as a validation of our approach, we demonstrate that a greater load of Neanderthal-derived genetic variants (higher "NeanderScore") is associated with skull shapes resembling those of known Neanderthal cranial remains, particularly in occipital and parietal bones. Next, we demonstrate convergent NeanderScore-related findings in the brain (measured by gray- and white-matter volume, sulcal depth, and gyrification index) that localize to the visual cortex and intraparietal sulcus. This work provides insights into ancestral human neurobiology and suggests that Neanderthal-derived genetic variation is neurologically functional in the contemporary population.

Late-Onset Alzheimer's Disease Polygenic Risk Profile Score Predicts Hippocampal Function.

BACKGROUND: We explored the cumulative effect of several late-onset Alzheimer's disease (LOAD) risk loci using a polygenic risk profile score (RPS) approach on measures of hippocampal function, cognition, and brain morphometry. METHODS: In a sample of 231 healthy control subjects (19-55 years of age), we used an RPS to study the effect of several LOAD risk loci reported in a recent meta-analysis on hippocampal function (determined by its engagement with blood oxygen level-dependent functional magnetic resonance imaging during episodic memory) and several cognitive metrics. We also studied effects on brain morphometry in an overlapping sample of 280 subjects. RESULTS: There was almost no significant association of LOAD-RPS with cognitive or morphometric measures. However, there was a significant negative relationship between LOAD-RPS and hippocampal function (familywise error [small volume correction-hippocampal region of interest] p < .05). There were also similar associations for risk score based on APOE haplotype, and for a combined LOAD-RPS + APOE haplotype risk profile score (p < .05 familywise error [small volume correction-hippocampal region of interest]). Of the 29 individual single nucleotide polymorphisms used in calculating LOAD-RPS, variants in CLU, PICALM, BCL3, PVRL2, and RELB showed strong effects (p < .05 familywise error [small volume correction-hippocampal region of interest]) on hippocampal function, though none survived further correction for the number of single nucleotide polymorphisms tested. CONCLUSIONS: There is a cumulative deleterious effect of LOAD risk genes on hippocampal function even in healthy volunteers. The effect of LOAD-RPS on hippocampal function in the relative absence of any effect on cognitive and morphometric measures is consistent with the reported temporal characteristics of LOAD biomarkers with the earlier manifestation of synaptic dysfunction before morphometric and cognitive changes.

Brain-Derived Neurotrophic Factor Val66Met Polymorphism Affects the Relationship Between an Anxiety-Related Personality Trait and Resting Regional Cerebral Blood Flow.

Brain-derived neurotrophic factor (BDNF) is an important modulator of constitutive stress responses mediated by limbic frontotemporal circuits, and its gene contains a functional polymorphism (Val66Met) that may influence trait stress sensitivity. Reports of an association of this polymorphism with anxiety-related personality traits have been controversial and without clear neurophysiological support. We, therefore, determined the relationship between resting regional cerebral blood flow (rCBF) and a well-validated measure of anxiety-related personality, the TPQ Harm Avoidance (HA) scale, as a function of BDNF Val66Met genotype. Sixty-four healthy participants of European ancestry underwent resting H215O positron emission tomography scans. For each genotype group separately, we first determined the relationship between participants' HA scores and their resting rCBF values in each voxel across the entire brain, and then directly compared these HA-rCBF relationships between Val66Met genotype groups. HA-rCBF relationships differed between Val homozygotes and Met carriers in several regions relevant to stress regulation: subgenual cingulate, orbital frontal cortex, and the hippocampal/parahippocampal region. In each of these areas, the relationship was positive in Val homozygotes and negative in Met carriers. These data demonstrate a coupling between trait anxiety and basal resting blood flow in frontolimbic neurocircuitry that may be determined in part by genetically mediated BDNF signaling.

Regional Variations in Brain Gyrification Are Associated with General Cognitive Ability in Humans.

Searching for a neurobiological understanding of human intellectual capabilities has long occupied those very capabilities. Brain gyrification, or folding of the cortex, is as highly evolved and variable a characteristic in humans as is intelligence. Indeed, gyrification scales with brain size, and relationships between brain size and intelligence have been demonstrated in humans [1-3]. However, gyrification shows a large degree of variability that is independent from brain size [4-6], suggesting that the former may independently contribute to cognitive abilities and thus supporting a direct investigation of this parameter in the context of intelligence. Moreover, uncovering the regional pattern of such an association could offer insights into evolutionary and neural mechanisms. We tested for this brain-behavior relationship in two separate, independently collected, large cohorts-440 healthy adults and 662 healthy children-using high-resolution structural neuroimaging and comprehensive neuropsychometric batteries. In both samples, general cognitive ability was significantly associated (pFDR < 0.01) with increasing gyrification in a network of neocortical regions, including large portions of the prefrontal cortex, inferior parietal lobule, and temporoparietal junction, as well as the insula, cingulate cortex, and fusiform gyrus, a regional distribution that was nearly identical in both samples (Dice similarity coefficient = 0.80). This neuroanatomical pattern is consistent with an existing, well-known proposal, the Parieto-Frontal Integration Theory of intelligence [7], and is also consistent with research in comparative evolutionary biology showing rapid neocortical expansion of these regions in humans relative to other species. These data provide a framework for understanding the neurobiology of human cognitive abilities and suggest a potential neurocellular association.