Personal recovery in first-episode psychosis: Beyond clinical and functional recovery.

BACKGROUND: The concept of personal recovery after psychotic illness focuses more on patients' social and existential needs compared to traditional outcome measures including clinical and functional recovery. This research aims to contribute to a broad framework on (personal) recovery and associated factors. METHODS: Data from 203 persons with symptomatic remission of their first-episode psychosis from the ongoing HAMLETT study were analyzed. To determine the relative importance of several biological, clinical, psychological, and social factors in explaining personal recovery as measured by the Recovery Assessment Scale (RAS), partial Spearman correlations (controlling for clinical recovery (PANSS) and functional recovery (WHODAS 2.0)) and a bootstrapped multiple regression were performed. Indirect effects on personal recovery within these factors, clinical recovery, and functional recovery were explored using a regularized partial correlation network. RESULTS: Of the factors that explained personal recovery beyond the effects of clinical and functional recovery, social support was the strongest predictor, followed by self-esteem, internalized stigma, and insecure attachment, collectively explaining 48.2 % of the variance. Anhedonia/apathy showed a trend towards a negative correlation. Age at onset, sex, early trauma/neglect, cognition, and being married/cohabiting did not significantly correlate with personal recovery. The network (n = 143) was consistent with these findings and indicated possible mediation pathways for early trauma/neglect, insecure attachment, cognition, and being married/cohabiting. CONCLUSIONS: Personal recovery is an important addition to traditional measures of outcome after psychosis. Various quality of life indicators, such as self-esteem and social support, explain variance in personal recovery over clinical and functional recovery.

Childhood trauma is associated with reduced frontal gray matter volume: a large transdiagnostic structural MRI study.

BACKGROUND: Childhood trauma increases risk for psychopathology and cognitive impairment. Prior research mainly focused on the hippocampus and amygdala in single diagnostic categories. However, other brain regions may be impacted by trauma as well, and effects may be independent of diagnosis. This cross-sectional study investigated cortical and subcortical gray matter volume in relation to childhood trauma severity. METHODS: We included 554 participants: 250 bipolar-I patients, 84 schizophrenia-spectrum patients and 220 healthy individuals without a psychiatric history. Participants filled in the Childhood Trauma Questionnaire. Anatomical T1 MRI scans were acquired at 3T, regional brain morphology was assessed using Freesurfer. RESULTS: In the total sample, trauma-related gray matter reductions were found in the frontal lobe (ß = -0.049, p = 0.008; q = 0.048), this effect was driven by the right medial orbitofrontal, paracentral, superior frontal regions and the left precentral region. No trauma-related volume reductions were observed in any other (sub)cortical lobes nor the hippocampus or amygdala, trauma-by-group (i.e. both patient groups and healthy subjects) interaction effects were absent. A categorical approach confirmed a pattern of more pronounced frontal gray matter reductions in individuals reporting multiple forms of trauma and across quartiles of cumulative trauma scores. Similar dose-response patterns were revealed within the bipolar and healthy subgroups, but did not reach significance in schizophrenia-spectrum patients. CONCLUSIONS: Findings show that childhood trauma is linked to frontal gray matter reductions, independent of psychiatric morbidity. Our results indicate that childhood trauma importantly contributes to the neurobiological changes commonly observed across psychiatric disorders. Frontal volume alterations may underpin affective and cognitive disturbances observed in trauma-exposed individuals.

Occurrence and phenomenology of hallucinations in the general population: A large online survey.

Although epidemiological studies report that hallucinations occur in 6-15% of the general population, little is known about their phenomenology. To overcome this paucity, this study investigates the phenomenological characteristics of hallucinations in the general population, by using a nationally promoted online survey to assess hallucination phenomenology in four sensory modalities, through a self-report version of the Questionnaire for Psychotic Experiences (QPE), in 10,448 participants (aged 14-88 years). The phenomenology of hallucinations was assessed if hallucinations reportedly occurred in the past month. In the past month, auditory hallucinations were reported most frequently (29.5%), followed by visual (21.5%), tactile (19.9%), and olfactory hallucinations (17.3%); hallucinations in two or more modalities were reported by 47.6%. Substantial numbers of participants rated their hallucinations as severe, due to negative content (16.0-31.6%), previous bothersome experiences (14.8-20.2%), ensuing distress (10.5-16.8%), and/or ensuing disfunctioning (12.7-17.3%). Decreased insight was found in 10.2-11.4%. Hypnagogia was reported by 9.0-10.6%, and bereavement hallucinations by 2.8%. Despite a low prevalence of delusions (7.0%), these phenomena were significantly associated with recent hallucinations, observed in up to 13.4% of the participants with hallucinations during the past week (p < 0.001). Our results indicate a wide variety of the phenomenology of hallucinations in the general population and support the existence of a phenomenological continuum.

DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia.

We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.

Functional connectome differences in individuals with hallucinations across the psychosis continuum.

Hallucinations may arise from an imbalance between sensory and higher cognitive brain regions, reflected by alterations in functional connectivity. It is unknown whether hallucinations across the psychosis continuum exhibit similar alterations in functional connectivity, suggesting a common neural mechanism, or whether different mechanisms link to hallucinations across phenotypes. We acquired resting-state functional MRI scans of 483 participants, including 40 non-clinical individuals with hallucinations, 99 schizophrenia patients with hallucinations, 74 bipolar-I disorder patients with hallucinations, 42 bipolar-I disorder patients without hallucinations, and 228 healthy controls. The weighted connectivity matrices were compared using network-based statistics. Non-clinical individuals with hallucinations and schizophrenia patients with hallucinations exhibited increased connectivity, mainly among fronto-temporal and fronto-insula/cingulate areas compared to controls (P < 0.001 adjusted). Differential effects were observed for bipolar-I disorder patients with hallucinations versus controls, mainly characterized by decreased connectivity between fronto-temporal and fronto-striatal areas (P = 0.012 adjusted). No connectivity alterations were found between bipolar-I disorder patients without hallucinations and controls. Our results support the notion that hallucinations in non-clinical individuals and schizophrenia patients are related to altered interactions between sensory and higher-order cognitive brain regions. However, a different dysconnectivity pattern was observed for bipolar-I disorder patients with hallucinations, which implies a different neural mechanism across the psychosis continuum.

Minimum spanning tree analysis of the human connectome.

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models.

Novel genetic loci associated with hippocampal volume.

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.

Changes in White Matter Organization in Adolescent Offspring of Schizophrenia Patients.

Schizophrenia is associated with frontostriatal network impairments underlying clinical and cognitive symptoms. We previously found disruptions in anatomical pathways, including the tract connecting the left nucleus accumbens and left dorsolateral prefrontal cortex (DLPFC). Similar deficits are observed in unaffected siblings of schizophrenia patients, indicating that these deficits are linked to a genetic vulnerability for the disorder. Frontostriatal tract disruptions may arise during adolescence, preceding the clinical manifestation of the disorder. However, to date, no studies have been performed to investigate frontostriatal tract connections in adolescents who are at increased familial risk for schizophrenia. In this study, we investigate the impact of familial risk on frontostriatal tract connections using diffusion tensor imaging in 27 adolescent offspring of schizophrenia patients and 32 matched control adolescents, aged 10-18 years. Mean fractional anisotropy (FA) was calculated for the tracts connecting the striatum (caudate nucleus, putamen, nucleus accumbens) and frontal cortex regions (DLPFC, medial orbital frontal cortex, inferior frontal gyrus). As expected, based on siblings data, we found an impact of familial risk on frontostriatal development: schizophrenia offspring showed increased FA in the tracts connecting nucleus accumbens and DLPFC as compared with control adolescents. Moreover, while FA increased across age in control adolescents, it did not in schizophrenia offspring. We did not find differences in FA in other frontostriatal tracts. These results indicate altered development of white matter in subjects who are at familial risk for schizophrenia and may precede frontostriatal white matter alterations in adult schizophrenia patients and siblings.

Novel genetic loci underlying human intracranial volume identified through genome-wide association.

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation.

BACKGROUND: Schizophrenia is a highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. RESULTS: We performed a multi-stage epigenome-wide association study, quantifying genome-wide patterns of DNA methylation in a total of 1714 individuals from three independent sample cohorts. We have identified multiple differentially methylated positions and regions consistently associated with schizophrenia across the three cohorts; these effects are independent of important confounders such as smoking. We also show that epigenetic variation at multiple loci across the genome contributes to the polygenic nature of schizophrenia. Finally, we show how DNA methylation quantitative trait loci in combination with Bayesian co-localization analyses can be used to annotate extended genomic regions nominated by studies of schizophrenia, and to identify potential regulatory variation causally involved in disease. CONCLUSIONS: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological approach that can be used to inform epigenome-wide association study analyses of other complex traits and diseases. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with etiological variation, and of using DNA methylation quantitative trait loci to refine the functional and regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation.

Genetic Variation in Schizophrenia Liability is Shared With Intellectual Ability and Brain Structure.

BACKGROUND: Alterations in intellectual ability and brain structure are important genetic markers for schizophrenia liability. How variations in these phenotypes interact with variance in schizophrenia liability due to genetic or environmental factors is an area of active investigation. Studying these genetic markers using a multivariate twin modeling approach can provide novel leads for (genetic) pathways of schizophrenia development. METHODS: In a sample of 70 twins discordant for schizophrenia and 130 healthy control twins, structural equation modeling was applied to quantify unique contributions of genetic and environmental factors on human brain structure (cortical thickness, cortical surface and global white matter fractional anisotropy [FA]), intellectual ability and schizophrenia liability. RESULTS: In total, up to 28.1% of the genetic variance (22.8% of total variance) in schizophrenia liability was shared with intelligence quotient (IQ), global-FA, cortical thickness, and cortical surface. The strongest contributor was IQ, sharing on average 16.4% of the genetic variance in schizophrenia liability, followed by cortical thickness (6.3%), global-FA (4.7%) and cortical surface (0.5%). Furthermore, we found that up to 57.4% of the variation due to environmental factors (4.6% of total variance) in schizophrenia was shared with IQ (34.2%) and cortical surface (13.4%). CONCLUSIONS: Intellectual ability, FA and cortical thickness show significant and independent shared genetic variance with schizophrenia liability. This suggests that measuring brain-imaging phenotypes helps explain genetic variance in schizophrenia liability that is not captured by variation in IQ.

Structural Brain Connectivity as a Genetic Marker for Schizophrenia.

IMPORTANCE: Schizophrenia is accompanied by a loss of integrity of white matter connections that compose the structural brain network, which is believed to diminish the efficiency of information transfer among brain regions. However, it is unclear to what extent these abnormalities are influenced by the genetic liability for developing the disease. OBJECTIVE: To determine whether white matter integrity is associated with the genetic liability for developing schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: In 70 individual twins discordant for schizophrenia and 130 matched individual healthy control twins, structural equation modeling was applied to quantify unique contributions of genetic and environmental factors on brain connectivity and disease liability. The data for this study were collected from October 1, 2008, to September 30, 2013. The data analysis was performed between November 1, 2013, and March 30, 2015. MAIN OUTCOME MEASURES: Structural connectivity and network efficiency were assessed through diffusion-weighted imaging, measuring fractional anisotropy (FA) and streamlines. RESULTS: The sample included 30 monozygotic twins matched to 72 control participants and 40 dizygotic twins matched to 58 control participants. Lower global FA was significantly correlated with increased schizophrenia liability (phenotypic correlation, -0.25; 95% CI, -0.38 to -0.10; P = .001), with 83.4% explained by common genes. In total, 8.1% of genetic variation in global FA was shared with genetic variance in schizophrenia liability. Local reductions in network connectivity (as defined by FA-weighted local efficiency) of frontal, striatal, and thalamic regions encompassed 85.7% of genetically affected areas. Multivariate genetic modeling revealed that global FA contributed independently of other genetic markers, such as white matter volume and cortical thickness, to schizophrenia liability. CONCLUSIONS AND RELEVANCE: Global reductions in white matter integrity in schizophrenia are largely explained by the genetic risk of developing the disease. Network analysis revealed that genetic liability for schizophrenia is primarily associated with reductions in connectivity of frontal and subcortical regions, indicating a loss of integrity along the white matter fibers in these regions. The reported reductions in white matter integrity likely represent a separate and novel genetic vulnerability marker for schizophrenia.

Topology of genetic associations between regional gray matter volume and intellectual ability: Evidence for a high capacity network.

Intelligence is associated with a network of distributed gray matter areas including the frontal and parietal higher association cortices and primary processing areas of the temporal and occipital lobes. Efficient information transfer between gray matter regions implicated in intelligence is thought to be critical for this trait to emerge. Genetic factors implicated in intelligence and gray matter may promote a high capacity for information transfer. Whether these genetic factors act globally or on local gray matter areas separately is not known. Brain maps of phenotypic and genetic associations between gray matter volume and intelligence were made using structural equation modeling of 3T MRI T1-weighted scans acquired in 167 adult twins of the newly acquired U-TWIN cohort. Subsequently, structural connectivity analyses (DTI) were performed to test the hypothesis that gray matter regions associated with intellectual ability form a densely connected core. Gray matter regions associated with intellectual ability were situated in the right prefrontal, bilateral temporal, bilateral parietal, right occipital and subcortical regions. Regions implicated in intelligence had high structural connectivity density compared to 10,000 reference networks (p=0.031). The genetic association with intelligence was for 39% explained by a genetic source unique to these regions (independent of total brain volume), this source specifically implicated the right supramarginal gyrus. Using a twin design, we show that intelligence is genetically represented in a spatially distributed and densely connected network of gray matter regions providing a high capacity infrastructure. Although genes for intelligence have overlap with those for total brain volume, we present evidence that there are genes for intelligence that act specifically on the subset of brain areas that form an efficient brain network.

Structural Brain Network Disturbances in the Psychosis Spectrum.

BACKGROUND: Individuals with subclinical psychotic symptoms provide a unique window on the pathophysiology of psychotic experiences as these individuals are free of confounders such as hospitalization, negative and cognitive symptoms and medication use. Brain network disturbances of white matter connections are thought to play a central role in the pathophysiology of psychosis. Based on the structural network disconnection hypothesis in schizophrenia, we expect less and weaker connections, and altered brain network organization in individuals with clinical and those with subclinical psychotic symptoms. METHODS: We used diffusion tensor imaging to study 35 patients with a psychotic disorder, 35 subjects with subclinical psychotic symptoms, and 36 healthy controls. The structural brain network was analyzed on 3 levels: connection density, white matter microstructure (fractional anisotropy, mean diffusivity, and magnetic transfer ratio), and network organization. Network organization was studied with minimum spanning tree analysis, a method to reconstruct a backbone of structural highways in the brain. RESULTS: Decreased fractional anisotropy and increased mean diffusivity was found in both groups with psychotic symptoms, while their network topology showed decreased overlap with a healthy reference network. Decreased centrality was found in several brain regions, including parietal hubs and language areas, in both groups with psychotic symptoms. Deviation of network characteristics was more apparent in clinical subjects than in subclinical subjects. DISCUSSION: Weaker connections and decreased centrality of parietal hubs characterize the structural brain network in subjects with psychotic symptoms. These differences are more notable in clinical than in subclinical subjects with psychotic experiences.

Common genetic variants influence human subcortical brain structures.

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Reduced fronto-striatal white matter integrity in schizophrenia patients and unaffected siblings: a DTI study.

BACKGROUND: Schizophrenia is characterized by impairments in the fronto-striatal network. Underlying these impairments may be disruptions in anatomical pathways connecting frontal and striatal regions. However, the specifics of these disruptions remain unclear and whether these impairments are related to the genetic vulnerability of schizophrenia is not known. METHODS: Here, we investigated fronto-striatal tract connections in 24 schizophrenia patients, 30 unaffected siblings, and 58 healthy controls using diffusion tensor imaging. Mean fractional anisotropy (FA) was calculated for tracts connecting the striatum with frontal cortex regions including the dorsolateral prefrontal cortex (DLPFC), medial orbital frontal cortex, and inferior frontal gyrus. Specifically, the striatum was divided into three subregions (caudate nucleus, putamen, and nucleus accumbens) and mean FA was computed for tracts originating from these striatal subregions. RESULTS: We found no differences between patients, siblings, and controls in mean FA when taking the whole striatum as a seed region. However, subregion analyses showed reduced FA in the tract connecting the left nucleus accumbens and left DLPFC in both patients (P=0.0003) and siblings (P=0.0008) compared with controls. CONCLUSIONS: The result of reduced FA in the tract connecting the left nucleus accumbens and left DLPFC indicates a possible reduction of white matter integrity, commonly associated with schizophrenia. As both patients and unaffected siblings show reduced FA, this may represent a vulnerability factor for schizophrenia.

GABA and glutamate in schizophrenia: a 7 T ¹H-MRS study.

Schizophrenia is characterized by loss of brain volume, which may represent an ongoing pathophysiological process. This loss of brain volume may be explained by reduced neuropil rather than neuronal loss, suggesting abnormal synaptic plasticity and cortical microcircuitry. A possible mechanism is hypofunction of the NMDA-type of glutamate receptor, which reduces the excitation of inhibitory GABAergic interneurons, resulting in a disinhibition of glutamatergic pyramidal neurons. Disinhibition of pyramidal cells may result in excessive stimulation by glutamate, which in turn could cause neuronal damage or death through excitotoxicity. In this study, GABA/creatine ratios, and glutamate, NAA, creatine and choline concentrations in the prefrontal and parieto-occipital cortices were measured in 17 patients with schizophrenia and 23 healthy controls using proton magnetic resonance spectroscopy at an ultra-high magnetic field strength of 7 T. Significantly lower GABA/Cr ratios were found in patients with schizophrenia in the prefrontal cortex as compared to healthy controls, with GABA/Cr ratios inversely correlated with cognitive functioning in the patients. No significant change in the GABA/Cr ratio was found between patients and controls in the parieto-occipital cortex, nor were levels of glutamate, NAA, creatine, and choline differed in patients and controls in the prefrontal and parieto-occipital cortices. Our findings support a mechanism involving altered GABA levels distinguished from glutamate levels in the medial prefrontal cortex in schizophrenia, particularly in high functioning patients. A (compensatory) role for GABA through altered inhibitory neurotransmission in the prefrontal cortex may be ongoing in (higher functioning) patients with schizophrenia.

Heritability of structural brain network topology: a DTI study of 156 twins.

Individual variation in structural brain network topology has been associated with heritable behavioral phenotypes such as intelligence and schizophrenia, making it a candidate endophenotype. However, little is known about the genetic influences on individual variation in structural brain network topology. Moreover, the extent to which structural brain network topology overlaps with heritability for integrity and volume of white matter remains unknown. In this study, structural network topology was examined using diffusion tensor imaging at 3T. Binary connections between 82 structurally defined brain regions per subject were traced, allowing for estimation of individual topological network properties. Heritability of normalized characteristic path length (λ), normalized clustering coefficient (γ), microstructural integrity (FA), and volume of the white matter were estimated using a twin design, including 156 adult twins from the newly acquired U-TWIN cohort. Both γ and λ were estimated to be under substantial genetic influence. The heritability of γ was estimated to be 68%, the heritability estimate for λ was estimated to be 57%. Genetic influences on network measures were found to be partly overlapping with volumetric and microstructural properties of white matter, but the largest component of genetic variance was unique to both network traits. Normalized clustering coefficient and normalized characteristic path length are substantially heritable, and influenced by independent genetic factors that are largely unique to network measures, but partly also implicated in white matter directionality and volume. Thus, network measures provide information about genetic influence on brain structure, independent of global white matter characteristics such as volume and microstructural directionality.

Genes contributing to subcortical volumes and intellectual ability implicate the thalamus.

It has been shown that brain volume and general intellectual ability are to a significant extent influenced by the same genetic factors. Several cortical regions of the brain also show a genetic correlation with intellectual ability, demonstrating that intellectual functioning is probably represented in a heritable distributed network of cortical regions throughout the brain. This study is the first to investigate a genetic association between subcortical volumes and intellectual ability, taking into account the thalamus, caudate nucleus, putamen, globus pallidus, hippocampus, amygdala, and nucleus accumbens using an extended twin design. Genetic modeling was performed on a healthy adult twin sample consisting of 106 twin pairs and 30 of their siblings, IQ data was obtained from 132 subjects. Our results demonstrate that of all subcortical volumes measured, only thalamus volume is significantly correlated with intellectual functioning. Importantly, the association found between thalamus volume and intellectual ability is significantly influenced by a common genetic factor. This genetic factor is also implicated in cerebral brain volume. The thalamus, with its widespread cortical connections, may thus play a key role in human intelligence.