Publications

Abstract

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 (genetic = 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 provide genetic support for theories on brain reserve and brain overgrowth.

Abstract

Genome-wide association screens aim to identify common genetic variants contributing to the phenotypic variability of complex traits, such as human height or brain morphology. The identified genetic variants are mostly within noncoding genomic regions and the biology of the genotype–phenotype association typically remains unclear. In this article, we propose a complementary targeted strategy to reveal the genetic underpinnings of variability in subcortical brain volumes, by specifically selecting genomic loci that are experimentally validated forebrain enhancers, active in early embryonic development. We hypothesized that genetic variation within these enhancers may affect the development and ultimately the structure of subcortical brain regions in adults. We tested whether variants in forebrain enhancer regions showed an overall enrichment of association with volumetric variation in subcortical structures of >13,000 healthy adults. We observed significant enrichment of genomic loci that affect the volume of the hippocampus within forebrain enhancers (empirical P = 0.0015), a finding which robustly passed the adjusted threshold for testing of multiple brain phenotypes (cutoff of P < 0.0083 at an alpha of 0.05). In analyses of individual single nucleotide polymorphisms (SNPs), we identified an association upstream of the ID2 gene with rs7588305 and variation in hippocampal volume. This SNP-based association survived multiple-testing correction for the number of SNPs analyzed but not for the number of subcortical structures. Targeting known regulatory regions offers a way to understand the underlying biology that connects genotypes to phenotypes, particularly in the context of neuroimaging genetics. This biology-driven approach generates testable hypotheses regarding the functional biology of identified associations.

Abstract

Recent genome wide association scans (GWAS) for reading and language abilities have pin-pointed promising new candidate loci. However, the potential contributions of these loci remain to be validated. In the present study, we tested 17 of the most significantly associated single nucleotide polymorphisms (SNPs) from these GWAS studies (p < 10−6 in the original studies) in a new independent population dataset from the Netherlands: known as FIOLA (Familial Influences On Literacy Abilities). This dataset comprised 483 children from 307 nuclear families, plus 505 adults (including parents of participating children), and provided adequate statistical power to detect the effects that were previously reported. The following measures of reading and language performance were collected: word reading fluency, nonword reading fluency, phonological awareness, and rapid automatized naming. Two SNPs (rs12636438, rs7187223) were associated with performance in multivariate and univariate testing, but these did not remain significant after correction for multiple testing. Another SNP (rs482700) was only nominally associated in the multivariate test. For the rest of the SNPs we did not find supportive evidence of association. The findings may reflect differences between our study and the previous investigations in respects such as the language of testing, the exact tests used, and the recruitment criteria. Alternatively, most of the prior reported associations may have been false positives. A larger scale GWAS meta-analysis than those previously performed will likely be required to obtain robust insights into the genomic architecture underlying reading and language.

Abstract

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders

Abstract

Background

Reading and language skills have overlapping genetic bases, most of which are still unknown. Part of the missing heritability may be caused by copy number variants (CNVs).
Methods

In a dataset of children recruited for a history of reading disability (RD, also known as dyslexia) or attention deficit hyperactivity disorder (ADHD) and their siblings, we investigated the effects of CNVs on reading and language performance. First, we called CNVs with PennCNV using signal intensity data from Illumina OmniExpress arrays (~723,000 probes). Then, we computed the correlation between measures of CNV genomic burden and the first principal component (PC) score derived from several continuous reading and language traits, both before and after adjustment for performance IQ. Finally, we screened the genome, probe-by-probe, for association with the PC scores, through two complementary analyses: we tested a binary CNV state assigned for the location of each probe (i.e., CNV+ or CNV−), and we analyzed continuous probe intensity data using FamCNV.
Results

No significant correlation was found between measures of CNV burden and PC scores, and no genome-wide significant associations were detected in probe-by-probe screening. Nominally significant associations were detected (p~10−2–10−3) within CNTN4 (contactin 4) and CTNNA3 (catenin alpha 3). These genes encode cell adhesion molecules with a likely role in neuronal development, and they have been previously implicated in autism and other neurodevelopmental disorders. A further, targeted assessment of candidate CNV regions revealed associations with the PC score (p~0.026–0.045) within CHRNA7 (cholinergic nicotinic receptor alpha 7), which encodes a ligand-gated ion channel and has also been implicated in neurodevelopmental conditions and language impairment. FamCNV analysis detected a region of association (p~10−2–10−4) within a frequent deletion ~6 kb downstream of ZNF737 (zinc finger protein 737, uncharacterized protein), which was also observed in the association analysis using CNV calls.
Conclusions

These data suggest that CNVs do not underlie a substantial proportion of variance in reading and language skills. Analysis of additional, larger datasets is warranted to further assess the potential effects that we found and to increase the power to detect CNV effects on reading and language.

Abstract

Pinpointing genes involved in non-right-handedness has the potential to clarify developmental contributions to human brain lateralization. Major-gene models have been considered for human handedness which allow for phenocopy and reduced penetrance, i.e. an imperfect correspondence between genotype and phenotype. However, a recent genome-wide association scan did not detect any common polymorphisms with substantial genetic effects. Previous linkage studies in families have also not yielded significant findings. Genetic heterogeneity and/or polygenicity are therefore indicated, but it remains possible that relatively rare, or even unique, major-genetic effects may be detectable in certain extended families with many non-right-handed members. Here we applied whole exome sequencing to 17 members from a single, large consanguineous family from Pakistan. Multipoint linkage analysis across all autosomes did not yield clear candidate genomic regions for involvement in the trait and single-point analysis of exomic variation did not yield clear candidate mutations/genes. Any genetic contribution to handedness in this unusual family is therefore likely to have a complex etiology, as at the population level.

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.

Abstract

OBJECTIVE: Recent research has provided evidence for a genetically mediated association between language or reading-related cognitive deficits and impaired motor coordination. Other studies have identified relationships between lateralization of hand skill and cognitive abilities. With a large sample, the authors aimed to investigate genetic relationships between measures of reading-related cognition, hand motor skill, and hand skill lateralization.

METHOD: The authors applied univariate and bivariate correlation and familiality analyses to a range of measures. They also performed genomewide linkage analysis of hand motor skill in a subgroup of 195 sibling pairs.

RESULTS: Hand motor skill was significantly familial (maximum heritability=41%), as were reading-related measures. Hand motor skill was weakly but significantly correlated with reading-related measures, such as nonword reading and irregular word reading. However, these correlations were not significantly familial in nature, and the authors did not observe linkage of hand motor skill to any chromosomal regions implicated in susceptibility to dyslexia. Lateralization of hand skill was not correlated with reading or cognitive ability.

CONCLUSIONS: The authors confirmed a relationship between lower motor ability and poor reading performance. However, the genetic effects on motor skill and reading ability appeared to be largely or wholly distinct, suggesting that the correlation between these traits may have arisen from environmental influences. Finally, the authors found no evidence that reading disability and/or low general cognitive ability were associated with ambidexterity.

Abstract

Schizophrenia and non-right-handedness are moderately associated, and both traits are often accompanied by abnormalities of asymmetrical brain morphology or function. We have found linkage previously of chromosome 2p12-q11 to a quantitative measure of handedness, and we have also found linkage of schizophrenia/schizoaffective disorder to this same chromosomal region in a separate study. Now, we have found that in one of our samples (191 reading-disabled sibling pairs), the relative hand skill of siblings was correlated more strongly with paternal than maternal relative hand skill. This led us to re-analyse 2p12-q11 under parent-of-origin linkage models. We found linkage of relative hand skill in the RD siblings to 2p12-q11 with P=0.0000037 for paternal identity-by-descent sharing, whereas the maternally inherited locus was not linked to the trait (P>0.2). Similarly, in affected-sib-pair analysis of our schizophrenia dataset (241 sibling pairs), we found linkage to schizophrenia for paternal sharing with LOD=4.72, P=0.0000016, within 3 cM of the peak linkage to relative hand skill. Maternal linkage across the region was weak or non-significant. These similar paternal-specific linkages suggest that the causative genetic effects on 2p12-q11 are related. The linkages may be due to a single maternally imprinted influence on lateralized brain development that contains common functional polymorphisms.

Abstract

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits.

Abstract

Attention-deficit/hyperactivity disorder (ADHD [MIM 143465]) is a common, highly heritable neurobehavioral disorder of childhood onset, characterized by hyperactivity, impulsivity, and/or inattention. As part of an ongoing study of the genetic etiology of ADHD, we have performed a genomewide linkage scan in 204 nuclear families comprising 853 individuals and 270 affected sibling pairs (ASPs). Previously, we reported genomewide linkage analysis of a “first wave” of these families composed of 126 ASPs. A follow-up investigation of one region on 16p yielded significant linkage in an extended sample. The current study extends the original sample of 126 ASPs to 270 ASPs and provides linkage analyses of the entire sample, using polymorphic microsatellite markers that define an ∼10-cM map across the genome. Maximum LOD score (MLS) analysis identified suggestive linkage for 17p11 (MLS=2.98) and four nominal regions with MLS values >1.0, including 5p13, 6q14, 11q25, and 20q13. These data, taken together with the fine mapping on 16p13, suggest two regions as highly likely to harbor risk genes for ADHD: 16p13 and 17p11. Interestingly, both regions, as well as 5p13, have been highlighted in genomewide scans for autism.