Publications

Abstract

Understanding the genetic factors underlying neurodevelopmental and neuropsychiatric disorders is a major challenge given their prevalence and potential severity for quality of life. While large-scale genomic screens have made major advances in this area, for many disorders the genetic underpinnings are complex and poorly understood. To date the field has focused predominantly on protein coding variation, but given the importance of tightly controlled gene expression for normal brain development and disorder, variation that affects non-coding regulatory regions of the genome is likely to play an important role in these phenotypes. Herein we show the importance of 3 prime untranslated region (3'UTR) non-coding regulatory variants across neurodevelopmental and neuropsychiatric disorders. We devised a pipeline for identifying and functionally validating putatively pathogenic variants from next generation sequencing (NGS) data. We applied this pipeline to a cohort of children with severe specific language impairment (SLI) and identified a functional, SLI-associated variant affecting gene regulation in cells and post-mortem human brain. This variant and the affected gene (ARHGEF39) represent new putative risk factors for SLI. Furthermore, we identified 3′UTR regulatory variants across autism, schizophrenia and bipolar disorder NGS cohorts demonstrating their impact on neurodevelopmental and neuropsychiatric disorders. Our findings show the importance of investigating non-coding regulatory variants when determining risk factors contributing to neurodevelopmental and neuropsychiatric disorders. In the future, integration of such regulatory variation with protein coding changes will be essential for uncovering the genetic causes of complex neurological disorders and the fundamental mechanisms underlying health and disease

Abstract

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here the ENIGMA consortium presents the largest ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (N = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified, and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.

Abstract

Left-right laterality is an important aspect of human –and in fact all vertebrate– brain organization for which the genetic basis is poorly understood. Using RNA sequencing data we contrasted gene expression in left- and right-sided samples from several structures of the anterior central nervous systems of post mortem human embryos and foetuses. While few individual genes stood out as significantly lateralized, most structures showed evidence of laterality of their overall transcriptomic profiles. These left-right differences showed overlap with age-dependent changes in expression, indicating lateralized maturation rates, but not consistently in left-right orientation over all structures. Brain asymmetry may therefore originate in multiple locations, or if there is a single origin, it is earlier than 5 weeks post conception, with structure-specific lateralized processes already underway by this age. This pattern is broadly consistent with the weak correlations reported between various aspects of adult brain laterality, such as language dominance and handedness.

Abstract

Left-right asymmetry is subtle but pervasive in the human central nervous system. This asymmetry is initiated early during development, but its mechanisms are poorly known. Forebrains and midbrains were dissected from six human embryos at Carnegie stages 15 or 16, one of which was female. The structures were divided into left and right sides, and RNA was isolated. RNA was sequenced with 100 base-pair paired ends using Illumina Hiseq 4000. After quality control, five paired brain sides were available for midbrain and forebrain. A paired analysis between left- and right sides of a given brain structure across the embryos identified left-right differences. The dataset, consisting of Fastq files and a read count table, can be further used to study early development of the human brain

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

Several quantitative trait loci (QTLs) that influence developmental dyslexia (reading disability [RD]) have been mapped to chromosome regions by linkage analysis. The most consistently replicated area of linkage is on chromosome 6p23-21.3. We used association analysis in 223 siblings from the United Kingdom to identify an underlying QTL on 6p22.2. Our association study implicates a 77-kb region spanning the gene TTRAP and the first four exons of the neighboring uncharacterized gene KIAA0319. The region of association is also directly upstream of a third gene, THEM2. We found evidence of these associations in a second sample of siblings from the United Kingdom, as well as in an independent sample of twin-based sibships from Colorado. One main RD risk haplotype that has a frequency of ∼12% was found in both the U.K. and U.S. samples. The haplotype is not distinguished by any protein-coding polymorphisms, and, therefore, the functional variation may relate to gene expression. The QTL influences a broad range of reading-related cognitive abilities but has no significant impact on general cognitive performance in these samples. In addition, the QTL effect may be largely limited to the severe range of reading disability.

Abstract

Attention-deficit/hyperactivity disorder (ADHD) and reading disability (RD) are common highly heritable disorders of childhood, which frequently co-occur. Data from twin and family studies suggest that this overlap is, in part, due to shared genetic underpinnings. Here, we report the first genome-wide linkage analysis of measures of reading ability in children with ADHD, using a sample of 233 affected sibling pairs who previously participated in a genome-wide scan for susceptibility loci in ADHD. Quantitative trait locus (QTL) analysis of a composite reading factor defined from three highly correlated reading measures identified suggestive linkage (multipoint maximum lod score, MLS>2.2) in four chromosomal regions. Two regions (16p, 17q) overlap those implicated by our previous genome-wide scan for ADHD in the same sample: one region (2p) provides replication for an RD susceptibility locus, and one region (10q) falls approximately 35 cM from a modestly highlighted region in an independent genome-wide scan of siblings with ADHD. Investigation of an individual reading measure of Reading Recognition supported linkage to putative RD susceptibility regions on chromosome 8p (MLS=2.4) and 15q (MLS=1.38). Thus, the data support the existence of genetic factors that have pleiotropic effects on ADHD and reading ability--as suggested by shared linkages on 16p, 17q and possibly 10q--but also those that appear to be unique to reading--as indicated by linkages on 2p, 8p and 15q that coincide with those previously found in studies of RD. Our study also suggests that reading measures may represent useful phenotypes in ADHD research. The eventual identification of genes underlying these unique and shared linkages may increase our understanding of ADHD, RD and the relationship between the two.

Abstract

We completed fine mapping of nine positional candidate regions for attention-deficit/hyperactivity disorder (ADHD) in an extended population sample of 308 affected sibling pairs (ASPs), constituting the largest linkage sample of families with ADHD published to date. The candidate chromosomal regions were selected from all three published genomewide scans for ADHD, and fine mapping was done to comprehensively validate these positional candidate regions in our sample. Multipoint maximum LOD score (MLS) analysis yielded significant evidence of linkage on 6q12 (MLS 3.30; empiric P=.024) and 17p11 (MLS 3.63; empiric P=.015), as well as suggestive evidence on 5p13 (MLS 2.55; empiric P=.091). In conjunction with the previously reported significant linkage on the basis of fine mapping 16p13 in the same sample as this report, the analyses presented here indicate that four chromosomal regions—5p13, 6q12, 16p13, and 17p11—are likely to harbor susceptibility genes for ADHD. The refinement of linkage within each of these regions lays the foundation for subsequent investigations using association methods to detect risk genes of moderate effect size.