Publications

Abstract

Genes of the Major Histocompatibility Complex (MHC) have recently been shown to have neuronal functions in the thalamus and hippocampus. Common genetic variants in the Human Leukocyte Antigens (HLA) region, human homologue of the MHC locus, are associated with small effects on susceptibility to schizophrenia, while volumetric changes of the thalamus and hippocampus have also been linked to schizophrenia. We therefore investigated whether common variants of the HLA would affect volumetric variation of the thalamus and hippocampus. We analyzed thalamus and hippocampus volumes, as measured using structural magnetic resonance imaging, in 1.265 healthy participants. These participants had also been genotyped using genome-wide single nucleotide polymorphism (SNP) arrays. We imputed genotypes for single nucleotide polymorphisms at high density across the HLA locus, as well as HLA allotypes and HLA amino acids, by use of a reference population dataset that was specifically targeted to the HLA region. We detected a significant association of the SNP rs17194174 with thalamus volume (nominal P=0.0000017, corrected P=0.0039), as well as additional SNPs within the same region of linkage disequilibrium. This effect was largely lateralized to the left thalamus and is localized within a genomic region previously associated with schizophrenia. The associated SNPs are also clustered within a potential regulatory element, and a region of linkage disequilibrium that spans genes expressed in the thalamus, including HLA-A. Our data indicate that genetic variation within the HLA region influences the volume and asymmetry of the human thalamus. The molecular mechanisms underlying this association may relate to HLA influences on susceptibility to schizophrenia

Abstract

Lateralizations of brain structure and motor behavior have been observed in humans as early as the first trimester of gestation, and are likely to arise from asymmetrical genetic–developmental programs, as in other animals. Studies of gene expression levels in postmortem tissue samples, comparing the left and right sides of the human cerebral cortex, have generally not revealed striking transcriptional differences between the hemispheres. This is likely due to lateralization of gene expression being subtle and quantitative. However, a recent re-analysis and meta-analysis of gene expression data from the adult superior temporal and auditory cortex found lateralization of transcription of genes involved in synaptic transmission and neuronal electrophysiology. Meanwhile, human subcortical mid- and hindbrain structures have not been well studied in relation to lateralization of gene activity, despite being potentially important developmental origins of asymmetry. Genetic polymorphisms with small effects on adult brain and behavioral asymmetries are beginning to be identified through studies of large datasets, but the core genetic mechanisms of lateralized human brain development remain unknown. Identifying subtly lateralized genetic networks in the brain will lead to a new understanding of how neuronal circuits on the left and right are differently fine-tuned to preferentially support particular cognitive and behavioral functions.

Abstract

The genetic determinants of cerebral asymmetries are unknown. Sex differences in asymmetry of the planum temporale, that overlaps Wernicke’s classical language area, have been inconsistently reported. Meta-analysis of previous studies has suggested that publication bias established this sex difference in the literature. Using probabilistic definitions of cortical regions we screened over the cerebral cortex for sexual dimorphisms of asymmetry in 2337 healthy subjects, and found the planum temporale to show the strongest sex-linked asymmetry of all regions, which was supported by two further datasets, and also by analysis with the Freesurfer package that performs automated parcellation of cerebral cortical regions. We performed a genome-wide association scan meta-analysis of planum temporale asymmetry in a pooled sample of 3095 subjects, followed by a candidate-driven approach which measured a significant enrichment of association in genes of the ´steroid hormone receptor activity´ and 'steroid metabolic process' pathways. Variants in the genes and pathways identified may affect the role of the planum temporale in language cognition.

Abstract

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

Abstract

Lateralization is an important aspect of the functional brain architecture for language and other cognitive faculties. The molecular genetic basis of human brain lateralization is unknown, and recent studies have suggested that gene expression in the cerebral cortex is bilaterally symmetrical. Here we have re-analyzed two transcriptomic datasets derived from post mortem human cerebral cortex, with a specific focus on superior temporal and auditory language cortex in adults. We applied an empirical Bayes approach to model differential left-right expression, together with gene ontology analysis and meta-analysis. There was robust and reproducible lateralization of individual genes and gene ontology groups that are likely to fine-tune the electrophysiological and neurotransmission properties of cortical circuits, most notably synaptic transmission, nervous system development and glutamate receptor activity. Our findings anchor the cerebral biology of language to the molecular genetic level. Future research in model systems may determine how these molecular signatures of neurophysiological lateralization effect fine-tuning of cerebral cortical function, differently in the two hemispheres.

Abstract

Population-based linkage analysis is a new method for analysing genomewide single nucleotide polymorphism (SNP) genotype data in case-control samples, which does not assume a common disease, common variant model. The genome is scanned for extended segments that show increased identity-by-descent sharing within case-case pairs, relative to case-control or control-control pairs. The method is robust to allelic heterogeneity and is suited to mapping genes which contain multiple, rare susceptibility variants of relatively high penetrance. We analysed genomewide SNP datasets for two schizophrenia case-control cohorts, collected in Aberdeen (461 cases, 459 controls) and Munich (429 cases, 428 controls). Population-based linkage testing must be performed within homogeneous samples and it was therefore necessary to analyse the cohorts separately. Each cohort was first subjected to several procedures to improve genetic homogeneity, including identity-by-state outlier detection and multidimensional scaling analysis. When testing only cases who reported a positive family history of major psychiatric disease, consistent with a model of strongly penetrant susceptibility alleles, we saw a distinct peak on chromosome 19q in both cohorts that appeared in meta-analysis (P=0.000016) to surpass the traditional level for genomewide significance for complex trait linkage. The linkage signal was also present in a third case-control sample for familial bipolar disorder, such that meta-analysing all three datasets together yielded a linkage P=0.0000026. A model of rare but highly penetrant disease alleles may be more applicable to some instances of major psychiatric diseases than the common disease common variant model, and we therefore suggest that other genome scan datasets are analysed with this new, complementary method.

Abstract

The Abelson helper integration site 1 (AHI1) gene locus on chromosome 6q23 is among a group of candidate loci for schizophrenia susceptibility that were initially identified by linkage followed by linkage disequilibrium mapping, and subsequent replication of the association in an independent sample. Here, we present results of a replication study of AHI1 locus markers, previously implicated in schizophrenia, in a large European sample (in total 3907 affected and 7429 controls). Furthermore, we perform a meta-analysis of the implicated markers in 4496 affected and 18,920 controls. Both the replication study of new samples and the meta-analysis show evidence for significant overrepresentation of all tested alleles in patients compared with controls (meta-analysis; P = 8.2 x 10(-5)-1.7 x 10(-3), common OR = 1.09-1.11). The region contains two genes, AHI1 and C6orf217, and both genes-as well as the neighbouring phosphodiesterase 7B (PDE7B)-may be considered candidates for involvement in the genetic aetiology of schizophrenia.

Abstract

Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

Abstract

Major depressive disorder (MDD) is a highly prevalent disorder with substantial heritability. Heritability has been shown to be substantial and higher in the variant of MDD characterized by recurrent episodes of depression. Genetic studies have thus far failed to identify clear and consistent evidence of genetic risk factors for MDD. We conducted a genome-wide association study (GWAS) in two independent datasets. The first GWAS was performed on 1022 recurrent MDD patients and 1000 controls genotyped on the Illumina 550 platform. The second was conducted on 492 recurrent MDD patients and 1052 controls selected from a population-based collection, genotyped on the Affymetrix 5.0 platform. Neither GWAS identified any SNP that achieved GWAS significance. We obtained imputed genotypes at the Illumina loci for the individuals genotyped on the Affymetrix platform, and performed a meta-analysis of the two GWASs for this common set of approximately half a million SNPs. The meta-analysis did not yield genome-wide significant results either. The results from our study suggest that SNPs with substantial odds ratio are unlikely to exist for MDD, at least in our datasets and among the relatively common SNPs genotyped or tagged by the half-million-loci arrays. Meta-analysis of larger datasets is warranted to identify SNPs with smaller effects or with rarer allele frequencies that contribute to the risk of MDD.

Abstract

The molecular, developmental, and evolutionary bases of human brain asymmetry are almost completely unknown. Genetic linkage and association mapping have pin-pointed a gene called LRRTM1 (leucine-rich repeat transmembrane neuronal 1) that may contribute to variability in human handedness. Here I describe how LRRTM1's involvement in handedness was discovered, and also the latest knowledge of its functions in brain development and disease. The association of LRRTM1 with handedness was derived entirely from the paternally inherited gene, and follow-up analysis of gene expression confirmed that LRRTM1 is one of a small number of genes that are imprinted in the human genome, for which the maternally inherited copy is suppressed. The same variation at LRRTM1 that was associated paternally with mixed-/left-handedness was also over-transmitted paternally to schizophrenic patients in a large family study.
LRRTM1 is expressed in specific regions of the developing and adult forebrain by post-mitotic neurons, and the protein may be involved in axonal trafficking. Thus LRRTM1 has a probable role in neurodevelopment, and its association with handedness suggests that one of its functions may be in establishing or consolidating human brain asymmetry.
LRRTM1 is the first gene for which allelic variation has been associated with human handedness. The genetic data also suggest indirectly that the epigenetic regulation of this gene may yet prove more important than DNA sequence variation for influencing brain development and disease.
Intriguingly, the parent-of-origin activity of LRRTM1 suggests that men and women have had conflicting interests in relation to the outcome of lateralized brain development in their offspring.

Abstract

Francks et al. (2007) performed a recent study in which the first putative genetic effect on human handedness was identified (the imprinted locus LRRTM1 on human chromosome 2). In this issue of Laterality, Tim Crow and colleagues present a critique of that study. The present paper presents a personal response to that critique which argues that Francks et al. (2007) published a substantial body of evidence implicating LRRTM1 in handedness and schizophrenia. Progress will now be achieved by others trying to validate, refute, or extend those findings, rather than by further armchair discussion.

Abstract

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater “load” of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens.

Abstract

Bipolar disorder (BP) is a disabling and often life-threatening disorder that affects approximately 1% of the population worldwide. To identify genetic variants that increase the risk of BP, we genotyped on the Illumina HumanHap550 Beadchip 2,076 bipolar cases and 1,676 controls of European ancestry from the National Institute of Mental Health Human Genetics Initiative Repository, and the Prechter Repository and samples collected in London, Toronto, and Dundee. We imputed SNP genotypes and tested for SNP-BP association in each sample and then performed meta-analysis across samples. The strongest association P value for this 2-study meta-analysis was 2.4 x 10(-6). We next imputed SNP genotypes and tested for SNP-BP association based on the publicly available Affymetrix 500K genotype data from the Wellcome Trust Case Control Consortium for 1,868 BP cases and a reference set of 12,831 individuals. A 3-study meta-analysis of 3,683 nonoverlapping cases and 14,507 extended controls on >2.3 M genotyped and imputed SNPs resulted in 3 chromosomal regions with association P approximately 10(-7): 1p31.1 (no known genes), 3p21 (>25 known genes), and 5q15 (MCTP1). The most strongly associated nonsynonymous SNP rs1042779 (OR = 1.19, P = 1.8 x 10(-7)) is in the ITIH1 gene on chromosome 3, with other strongly associated nonsynonymous SNPs in GNL3, NEK4, and ITIH3. Thus, these chromosomal regions harbor genes implicated in cell cycle, neurogenesis, neuroplasticity, and neurosignaling. In addition, we replicated the reported ANK3 association results for SNP rs10994336 in the nonoverlapping GSK sample (OR = 1.37, P = 0.042). Although these results are promising, analysis of additional samples will be required to confirm that variant(s) in these regions influence BP risk.