Andrew Kirby

Patterns and rates of exonic de novo mutations in autism spectrum disorders

Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case–control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

Efficient Control of Population Structure in Model Organism Association Mapping

Genomewide association mapping in model organisms such as inbred mouse strains is a promising approach for the identification of risk factors related to human diseases. However, genetic association studies in inbred model organisms are confronted by the problem of complex population structure among strains. This induces inflated false positive rates, which cannot be corrected using standard approaches applied in human association studies such as genomic control or structured association. Recent studies demonstrated that mixed models successfully correct for the genetic relatedness in association mapping in maize and Arabidopsis panel data sets. However, the currently available mixed-model methods suffer from computational inefficiency. In this article, we propose a new method, efficient mixed-model association (EMMA), which corrects for population structure and genetic relatedness in model organism association mapping. Our method takes advantage of the specific nature of the optimization problem in applying mixed models for association mapping, which allows us to substantially increase the computational speed and reliability of the results. We applied EMMA to in silico whole-genome association mapping of inbred mouse strains involving hundreds of thousands of SNPs, in addition to Arabidopsis and maize data sets. We also performed extensive simulation studies to estimate the statistical power of EMMA under various SNP effects, varying degrees of population structure, and differing numbers of multiple measurements per strain. Despite the limited power of inbred mouse association mapping due to the limited number of available inbred strains, we are able to identify significantly associated SNPs, which fall into known QTL or genes identified through previous studies while avoiding an inflation of false positives. An R package implementation and webserver of our EMMA method are publicly available.

Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease

More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohns disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohns disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 × 10−16, odds ratio ≈ 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models.

The mosaic structure of variation in the laboratory mouse genome

Most inbred laboratory mouse strains are known to have originated from a mixed but limited founder population in a few laboratories. However, the effect of this breeding history on patterns of genetic variation among these strains and the implications for their use are not well understood. Here we present an analysis of the fine structure of variation in the mouse genome, using single nucleotide polymorphisms (SNPs). When the recently assembled genome sequence from the C57BL/6J strain is aligned with sample sequence from other strains, we observe long segments of either extremely high (∼40 SNPs per 10u2009kb) or extremely low (∼0.5 SNPs per 10u2009kb) polymorphism rates. In all strain-to-strain comparisons examined, only one-third of the genome falls into long regions (averaging >1u2009Mb) of a high SNP rate, consistent with estimated divergence rates between Mus musculus domesticus and either M. m. musculus or M. m. castaneus. These data suggest that the genomes of these inbred strains are mosaics with the vast majority of segments derived from domesticus and musculus sources. These observations have important implications for the design and interpretation of positional cloning experiments.

A high-density screen for linkage in multiple sclerosis.

To provide a definitive linkage map for multiple sclerosis, we have genotyped the Illumina BeadArray linkage mapping panel (version 4) in a data set of 730 multiplex families of Northern European descent. After the application of stringent quality thresholds, data from 4,506 markers in 2,692 individuals were included in the analysis. Multipoint nonparametric linkage analysis revealed highly significant linkage in the major histocompatibility complex (MHC) on chromosome 6p21 (maximum LOD score [MLS] 11.66) and suggestive linkage on chromosomes 17q23 (MLS 2.45) and 5q33 (MLS 2.18). This set of markers achieved a mean information extraction of 79.3% across the genome, with a Mendelian inconsistency rate of only 0.002%. Stratification based on carriage of the multiple sclerosis-associated DRB1*1501 allele failed to identify any other region of linkage with genomewide significance. However, ordered-subset analysis suggested that there may be an additional locus on chromosome 19p13 that acts independent of the main MHC locus. These data illustrate the substantial increase in power that can be achieved with use of the latest tools emerging from the Human Genome Project and indicate that future attempts to systematically identify susceptibility genes for multiple sclerosis will have to involve large sample sizes and an association-based methodology.

Support for involvement of neuregulin 1 in schizophrenia pathophysiology

Schizophrenia is a common, multigenic psychiatric disorder. Linkage studies, including a recent meta-analysis of genome scans, have repeatedly implicated chromosome 8p12-p23.1 in schizophrenia susceptibility. More recently, significant association with a candidate gene on 8p12, neuregulin 1 (NRG1), has been reported in several European and Chinese samples. We investigated NRG1 for association in schizophrenia patients of Portuguese descent to determine whether this gene is a risk factor in this population. We tested NRG1 markers and haplotypes for association in 111 parent-proband trios, 321 unrelated cases, and 242 control individuals. Associations were found with a haplotype that overlaps the risk haplotype originally reported in the Icelandic population (‘HapICE’), and two haplotypes located in the 3′ end of NRG1 (all P<0.05). However, association was not detected with HapICE itself. Comparison of NRG1 transcript expression in peripheral leukocytes from schizophrenia patients and unaffected siblings identified 3.8-fold higher levels of the SMDF variant in patients (P=0.039). Significant positive correlations (P<0.001) were found between SMDF and HRG-beta 2 expression and between HRG-gamma and ndf43 expression, suggesting common transcriptional regulation of NRG1 variants. In summary, our results suggest that haplotypes across NRG1 and multiple NRG1 variants are involved in schizophrenia.

Characterization of the MODY3 phenotype. Early-onset diabetes caused by an insulin secretion defect.

Maturity-onset diabetes of the young (MODY) type 3 is a dominantly inherited form of diabetes, which is often misdiagnosed as non-insulin-dependent diabetes mellitus (NIDDM) or insulin-dependent diabetes mellitus (IDDM). Phenotypic analysis of members from four large Finnish MODY3 kindreds (linked to chromosome 12q with a maximum lod score of 15) revealed a severe impairment in insulin secretion, which was present also in those normoglycemic family members who had inherited the MODY3 gene. In contrast to patients with NIDDM, MODY3 patients did not show any features of the insulin resistance syndrome. They could be discriminated from patients with IDDM by lack of glutamic acid decarboxylase antibodies (GAD-Ab). Taken together with our recent findings of linkage between this region on chromosome 12 and an insulin-deficient form of NIDDM (NIDDM2), the data suggest that mutations at the MODY3/NIDDM2 gene(s) result in a reduced insulin secretory response, that subsequently progresses to diabetes and underlines the importance of subphenotypic classification in studies of diabetes.

Genomewide Linkage Analysis of Stature in Multiple Populations Reveals Several Regions with Evidence of Linkage to Adult Height

Genomewide linkage analysis has been extremely successful at identification of the genetic variation underlying single-gene disorders. However, linkage analysis has been less successful for common human diseases and other complex traits in which multiple genetic and environmental factors interact to influence disease risk. We hypothesized that a highly heritable complex trait, in which the contribution of environmental factors was relatively limited, might be more amenable to linkage analysis. We therefore chose to study stature (adult height), for which heritability is approximately 75%-90% (Phillips and Matheny 1990; Carmichael and McGue 1995; Preece 1996; Silventoinen et al. 2000). We reanalyzed genomewide scans from four populations for which genotype and height data were available, using a variance-components method implemented in GENEHUNTER 2.0 (Pratt et al. 2000). The populations consisted of 408 individuals in 58 families from the Botnia region of Finland, 753 individuals in 183 families from other parts of Finland, 746 individuals in 179 families from Southern Sweden, and 420 individuals in 63 families from the Saguenay-Lac-St.-Jean region of Quebec. Four regions showed evidence of linkage to stature: 6q24-25, multipoint LOD score 3.85 at marker D6S1007 in Botnia (genomewide P<.06), 7q31.3-36 (LOD 3.40 at marker D7S2195 in Sweden, P<.02), 12p11.2-q14 (LOD 3.35 at markers D12S10990-D12S398 in Finland, P<.05) and 13q32-33 (LOD 3.56 at markers D13S779-D13S797 in Finland, P<.05). In a companion article (Perola et al. 2001 [in this issue]), strong supporting evidence is obtained for linkage to the region on chromosome 7. These studies suggest that highly heritable complex traits such as stature may be genetically tractable and provide insight into the genetic architecture of complex traits.

Genomewide Search for Type 2 Diabetes Mellitus Susceptibility Loci in Finnish Families: The Botnia Study

Type 2 diabetes mellitus is a heterogeneous inherited disorder characterized by chronic hyperglycemia resulting from pancreatic beta-cell dysfunction and insulin resistance. Although the pathogenic mechanisms are not fully understood, manifestation of the disease most likely requires interaction between both environmental and genetic factors. In the search for such susceptibility genes, we have performed a genomewide scan in 58 multiplex families (comprising 440 individuals, 229 of whom were affected) from the Botnia region in Finland. Initially, linkage between chromosome 12q24 and impaired insulin secretion had been reported, by Mahtani et al., in a subsample of 26 families. In the present study, we extend the initial genomewide scan to include 32 additional families, update the affectation status, and fine map regions of interest, and we try to replicate the initial stratification analysis. In our analysis of all 58 families, we identified suggestive linkage to one region, chromosome 9p13-q21 (nonparametric linkage [NPL] score 3.9; P<.0002). Regions with nominal P values <.05 include chromosomes 2p11 (NPL score 2.0 [P<.03]), 3p24-p22 (NPL score 2.2 [P<.02]), 4q32-q33 (NPL score 2.5 [P<.01]), 12q24 (NPL score 2.1 [P<.03]), 16p12-11 (NPL score 1.7 [P<.05]), and 17p12-p11 (NPL score 1.9 [P<.03]). When chromosome 12q24 was analyzed in only the 32 additional families, a nominal P value <.04 was observed. Together with data from other published genomewide scans, these findings lend support to the hypothesis that regions on chromosome 9p13-q21 and 12q24 may harbor susceptibility genes for type 2 diabetes.

Mutations causing medullary cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing

Although genetic lesions responsible for some mendelian disorders can be rapidly discovered through massively parallel sequencing of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing and de novo assembly did we find that each of six families with MCKD1 harbors an equivalent but apparently independently arising mutation in sequence markedly under-represented in massively parallel sequencing data: the insertion of a single cytosine in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (∼1.5–5 kb), GC-rich (>80%) coding variable-number tandem repeat (VNTR) sequence in the MUC1 gene encoding mucin 1. These results provide a cautionary tale about the challenges in identifying the genes responsible for mendelian, let alone more complex, disorders through massively parallel sequencing.