8 research outputs found
Genetic underpinnings of left superior temporal gyrus thickness in patients with schizophrenia
<div><p></p><p><i>Objectives.</i> Schizophrenia is a highly disabling psychiatric disorder with a heterogeneous phenotypic appearance. We aimed to further the understanding of some of the underlying genetics of schizophrenia, using left superior temporal gyrus (STG) grey matter thickness reduction as an endophenoptype in a genome-wide association (GWA) study. <i>Methods.</i> Structural magnetic resonance imaging (MRI) and genetic data of the Mind Clinical Imaging Consortium (MCIC) study of schizophrenia were used to analyse the interaction effects between 1,067,955 single nucleotide polymorphisms (SNPs) and disease status on left STG thickness in 126 healthy controls and 113 patients with schizophrenia. We next used a pathway approach to detect underlying pathophysiological pathways that may be related to schizophrenia. <i>Results.</i> No SNP by diagnosis interaction effect reached genome-wide significance (5 × 10<sup>–8</sup>) in our GWA study, but 10 SNPs reached <i>P</i>-values less than 10<sup>–6</sup>. The most prominent pathways included those involved in insulin, calcium, PI3K-Akt and MAPK signalling. <i>Conclusions.</i> Our strongest findings in the GWA study and pathway analysis point towards an involvement of glucose metabolism in left STG thickness reduction in patients with schizophrenia only. These results are in line with recently published studies, which showed an increased prevalence of psychosis among patients with metabolic syndrome-related illnesses including diabetes.</p></div
Effect of <i>NRGN</i> risk variant on brain function.
<p>Functional map illustrating increased neural activity in rs12541 TT homozygotes compared to C carriers. SSC, somatosensory cortex; CC, cingulate cortex. Results were cluster-corrected and z-values are represented according to the color code.</p
Effect of <i>NRGN</i> risk variant on cortical thickness and ACC volume.
<p>a) Cortical statistical map illustrating reduced cortical thickness for rs12807809 C carriers compared to TT homozygotes. The -log(CWP-value) is represented according to the color code. b) Boxplot showing mean and two standard errors of the standardized residuals for the effects of <i>NRGN</i> rs12807809 genotype on left rostal ACC volume controlled for intracranial volume, age, gender, diagnosis and scanner field strength.</p
Demographic variables of the MCIC sample.
<p>Means and standard deviations (SD) are given. HC = healthy control, SZ = patient with schizophrenia. Ethnicity was defined as described under Methods. WRAT3-RT = Wide Range Achievement Test 3 – Reading Test. Parental SES (socioeconomic status) was classified according to Hollingshead, and handedness determined using the Annett Scale of Hand Preference.</p>a<p>significantly different between HC and SZ on basis of Chi-Square (p<0.05).</p>b<p>significantly different between HC and SZ on basis of Welch (p<0.05).</p
Quantile-quantile plot for MCIC association results.
<p>The empirical and theoretical distributions are shown as dots and line, respectively.</p
Linkage disequilibrium (LD) plot of all MCIC main hits on chromosome 19.
<p>LD is given based on r<sup>2</sup> estimated using the current dataset. Each diamond indicates the pairwise magnitude of LD, with dark grey/black indicating strong LD (r<sup>2</sup>>0.8). Figure prepared with <i>HaploView</i> (Barrett et al. 2005).</p
Genome-wide association results for SNPs associated with hippocampal volume in the MCIC sample.
<p>SNP IDs with chromosome (CHR), basepair position (BP), minor (A1) and major allele (A2), minor allele frequency (MAF), regression coefficient (BETA), coefficient (STAT) and asymptotic p-value for t-statistic, and corresponding gene regions: <i>KIF26B</i> (kinesin family member 26B), <i>TRPM8</i> (transient receptor potential cation channel, subfamily M, member 8), <i>LOC283089</i> (uncharacterized), <i>NR2F6</i> (nuclear receptor subfamily 2, group F, member 6), <i>USHBP1</i> (Usher syndrome 1C binding protein 1), and <i>BABAM1</i> (BRISC and BRCA1 A complex member 1). For additional information see Table S3 in File S1.</p
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Common genetic variants influence human subcortical brain structures
The highly complex structure of the human brain is strongly shaped by genetic influences1. Subcortical brain regions form circuits with cortical areas to coordinate movement2, learning, memory3 and motivation4, and altered circuits can lead to abnormal behaviour and disease2. 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 volume5 and intracranial volume6. 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