Allelic heterogeneity at the serotonin transporter locus (SLC6A4) confers susceptibility to autism and rigid-compulsive behaviors

Autism is a spectrum of neurodevelopmental disorders with a primarily genetic etiology exhibiting deficits in (1) development of language and (2) social relationships and (3) patterns of repetitive, restricted behaviors or interests and resistance to change. Elevated platelet serotonin (5-HT) in 20%-25% of cases and efficacy of selective 5-HT reuptake inhibitors (SSRIs) in treating anxiety, depression, and repetitive behaviors points to the 5-HT transporter (5-HTT; SERT) as a strong candidate gene. Association studies involving the functional insertion/deletion polymorphism in the promoter (5-HTTLPR) and a polymorphism in intron 2 are inconclusive, possibly because of phenotypic heterogeneity. Nonetheless, mounting evidence for genetic linkage of autism to the chromosome 17q11.2 region that harbors the SERT locus (SLC6A4) supports a genetic effect at or near this gene. We confirm recent reports of sex-biased genetic effects in 17q by showing highly significant linkage driven by families with only affected males. Association with common alleles fails to explain observed linkage; therefore, we hypothesized that preferential transmission of multiple alleles does explain it. From 120 families, most contributing to linkage at 17q11.2, we found four coding substitutions at highly conserved positions and 15 other variants in 5' noncoding and other intronic regions transmitted in families exhibiting increased rigid-compulsive behaviors. In the aggregate, these variants show significant linkage to and association with autism. Our data provide strong support for a collection of multiple, often rare, alleles at SLC6A4 as imposing risk of autism.     

Opposite risk patterns for autism and schizophrenia are associated with normal variation in birth size: phenotypic support for hypothesized diametric gene-dosage effects

Opposite phenotypic and behavioural traits associated with copy number variation and disruptions to imprinted genes with parent-of-origin effects have led to the hypothesis that autism and schizophrenia share molecular risk factors and pathogenic mechanisms, but a direct phenotypic comparison of how their risks covary has not been attempted. Here, we use health registry data collected on Denmark''s roughly 5 million residents between 1978 and 2009 to detect opposing risks of autism and schizophrenia depending on normal variation (mean ± 1 s.d.) in adjusted birth size, which we use as a proxy for diametric gene-dosage variation in utero. Above-average-sized babies (weight, 3691–4090 g; length, 52.8–54.3 cm) had significantly higher risk for autism spectrum (AS) and significantly lower risk for schizophrenia spectrum (SS) disorders. By contrast, below-average-sized babies (2891–3290 g; 49.7–51.2 cm) had significantly lower risk for AS and significantly higher risk for SS disorders. This is the first study directly comparing autism and schizophrenia risks in the same population, and provides the first large-scale empirical support for the hypothesis that diametric gene-dosage effects contribute to these disorders. Only the kinship theory of genomic imprinting predicts the opposing risk patterns that we discovered, suggesting that molecular research on mental disease risk would benefit from considering evolutionary theory.     

Genome Sequencing of Autism-Affected Families Reveals Disruption of Putative Noncoding Regulatory DNA

We performed whole-genome sequencing (WGS) of 208 genomes from 53 families affected by simplex autism. For the majority of these families, no copy-number variant (CNV) or candidate de novo gene-disruptive single-nucleotide variant (SNV) had been detected by microarray or whole-exome sequencing (WES). We integrated multiple CNV and SNV analyses and extensive experimental validation to identify additional candidate mutations in eight families. We report that compared to control individuals, probands showed a significant (p = 0.03) enrichment of de novo and private disruptive mutations within fetal CNS DNase I hypersensitive sites (i.e., putative regulatory regions). This effect was only observed within 50 kb of genes that have been previously associated with autism risk, including genes where dosage sensitivity has already been established by recurrent disruptive de novo protein-coding mutations (ARID1B, SCN2A, NR3C2, PRKCA, and DSCAM). In addition, we provide evidence of gene-disruptive CNVs (in DISC1, WNT7A, RBFOX1, and MBD5), as well as smaller de novo CNVs and exon-specific SNVs missed by exome sequencing in neurodevelopmental genes (e.g., CANX, SAE1, and PIK3CA). Our results suggest that the detection of smaller, often multiple CNVs affecting putative regulatory elements might help explain additional risk of simplex autism.     

Multifactor dimensionality reduction-phenomics: a novel method to capture genetic heterogeneity with use of phenotypic variables

Complex human diseases do not have a clear inheritance pattern, and it is expected that risk involves multiple genes with modest effects acting independently or interacting. Major challenges for the identification of genetic effects are genetic heterogeneity and difficulty in analyzing high-order interactions. To address these challenges, we present MDR-Phenomics, a novel approach based on the multifactor dimensionality reduction (MDR) method, to detect genetic effects in pedigree data by integration of phenotypic covariates (PCs) that may reflect genetic heterogeneity. The P value of the test is calculated using a permutation test adjusted for multiple tests. To validate MDR-Phenomics, we compared it with two MDR-based methods: (1) traditional MDR pedigree disequilibrium test (PDT) without consideration of PCs (MDR-PDT) and (2) stratified phenotype (SP) analysis based on PCs, with use of MDR-PDT with a Bonferroni adjustment (SP-MDR). Using computer simulations, we examined the statistical power and type I error of the different approaches under several genetic models and sampling scenarios. We conclude that MDR-Phenomics is more powerful than MDR-PDT and SP-MDR when there is genetic heterogeneity, and the statistical power is affected by sample size and the number of PC levels. We further compared MDR-Phenomics with conditional logistic regression (CLR) for testing interactions across single or multiple loci with consideration of PC. The results show that CLR with PC has only slightly smaller power than does MDR-Phenomics for single-locus analysis but has considerably smaller power for multiple loci. Finally, by applying MDR-Phenomics to autism, a complex disease in which multiple genes are believed to confer risk, we attempted to identify multiple gene effects in two candidate genes of interest—the serotonin transporter gene (SLC6A4) and the integrin beta 3 gene (ITGB3) on chromosome 17. Analyzing four markers in SLC6A4 and four markers in ITGB3 in 117 white family triads with autism and using sex of the proband as a PC, we found significant interaction between two markers—rs1042173 in SLC6A4 and rs3809865 in ITGB3.     

Neurexins, neuroligins and LRRTMs: synaptic adhesion getting fishy

Recent studies have identified the leucine rich repeat protein LRRTM2 as a post-synaptic ligand of Neurexins. Neurexins also bind the post-synaptic adhesion molecules, Neuroligins. All three families of genes have been implicated in the etiologies of neurodevelopmental disorders, specifically autism spectrum disorders and schizophrenia. Does the binding promiscuity of Neurexins now suggest complex cooperativity or redundancy at the synapse? While recent studies in primary neuronal cultures and also systematic extracellular protein interaction screens suggest summative effects of these systems, we propose that studying these interactions in the developing zebrafish embryo or larvae may shed more light on their functions during synaptogenesis in vivo. These gene families have recently been extensively characterized in zebrafish, demonstrating high sequence conservation with the human genes. The simpler circuitry of the zebrafish, together with the characterization of the expression patterns down to single, identifiable neurons and the ability to knock-down or over-express multiple genes in a rapid way lend themselves to dissecting complex interaction pathways. Furthermore, the capability of performing high-throughput drug screens suggests that these small vertebrates may prove extremely useful in identifying pharmacological approaches to treating autism spectrum disorders.     

Intellectual Disability Is Associated with Increased Runs of Homozygosity in Simplex Autism

Intellectual disability (ID), often attributed to autosomal-recessive mutations, occurs in 40% of autism spectrum disorders (ASDs). For this reason, we conducted a genome-wide analysis of runs of homozygosity (ROH) in simplex ASD-affected families consisting of a proband diagnosed with ASD and at least one unaffected sibling. In these families, probands with an IQ ≤ 70 show more ROH than their unaffected siblings, whereas probands with an IQ > 70 do not show this excess. Although ASD is far more common in males than in females, the proportion of females increases with decreasing IQ. Our data do support an association between ROH burden and autism diagnosis in girls; however, we are not able to show that this effect is independent of low IQ. We have also discovered several autism candidate genes on the basis of finding (1) a single gene that is within an ROH interval and that is recurrent in autism or (2) a gene that is within an autism ROH block and that harbors a homozygous, rare deleterious variant upon analysis of exome-sequencing data. In summary, our data suggest a distinct genetic architecture for participants with autism and co-occurring intellectual disability and that this architecture could involve a role for recessively inherited loci for this autism subgroup.     

High-throughput sequencing of mGluR signaling pathway genes reveals enrichment of rare variants in autism

Identification of common molecular pathways affected by genetic variation in autism is important for understanding disease pathogenesis and devising effective therapies. Here, we test the hypothesis that rare genetic variation in the metabotropic glutamate-receptor (mGluR) signaling pathway contributes to autism susceptibility. Single-nucleotide variants in genes encoding components of the mGluR signaling pathway were identified by high-throughput multiplex sequencing of pooled samples from 290 non-syndromic autism cases and 300 ethnically matched controls on two independent next-generation platforms. This analysis revealed significant enrichment of rare functional variants in the mGluR pathway in autism cases. Higher burdens of rare, potentially deleterious variants were identified in autism cases for three pathway genes previously implicated in syndromic autism spectrum disorder, TSC1, TSC2, and SHANK3, suggesting that genetic variation in these genes also contributes to risk for non-syndromic autism. In addition, our analysis identified HOMER1, which encodes a postsynaptic density-localized scaffolding protein that interacts with Shank3 to regulate mGluR activity, as a novel autism-risk gene. Rare, potentially deleterious HOMER1 variants identified uniquely in the autism population affected functionally important protein regions or regulatory sequences and co-segregated closely with autism among children of affected families. We also identified rare ASD-associated coding variants predicted to have damaging effects on components of the Ras/MAPK cascade. Collectively, these findings suggest that altered signaling downstream of mGluRs contributes to the pathogenesis of non-syndromic autism.     

Defining the Contribution of CNTNAP2 to Autism Susceptibility

Multiple lines of genetic evidence suggest a role for CNTNAP2 in autism. To assess its population impact we studied 2148 common single nucleotide polymorphisms (SNPs) using transmission disequilibrium test (TDT) across the entire ~3.3 Mb CNTNAP2 locus in 186 (408 trios) multiplex and 323 simplex families with autistic spectrum disorder (ASD). This analysis yielded two SNPs with nominal statistical significance (rs17170073, p = 2.0 x 10^-4; rs2215798, p = 1.6 x 10^-4) that did not survive multiple testing. In a combined analysis of all families, two highly correlated (r ² = 0.99) SNPs in intron 14 showed significant association with autism (rs2710093, p = 9.0 x 10^-6; rs2253031, p = 2.5 x 10^-5). To validate these findings and associations at SNPs from previous autism studies (rs7794745, rs2710102 and rs17236239) we genotyped 2051 additional families (572 multiplex and 1479 simplex). None of these variants were significantly associated with ASD after corrections for multiple testing. The analysis of Mendelian errors within each family did not indicate any segregating deletions. Nevertheless, a study of CNTNAP2 gene expression in brains of autistic patients and of normal controls, demonstrated altered expression in a subset of patients (p = 1.9 x10^-5). Consequently, this study suggests that although CNTNAP2 dysregulation plays a role in some cases, its population contribution to autism susceptibility is limited.     

Newborn umbilical cord blood DNA methylation and gene expression levels exhibit limited association with birth weight

Most cases of fetal growth retardation are unexplained. These newborns are at high risk of serious illness or death in the neonatal period and exhibit significantly increased risk of specific chronic illnesses later in life. While there are several hypotheses to explain the well-established association between low birth weight and later risk of disease, the true etiology is unknown. To search for molecular patterns that may explain the biological basis for reduced fetal growth in a clinically normal cohort, and possibly provide clues for the lifelong increased risk of disease, we surveyed genome-wide DNA methylation and gene expression patterns in the umbilical cord blood of newborns born in Shelby County, TN. While we did not find genome-wide significant associations of birth weight with either leukocytic gene expression or DNA methylation, we did find suggestive associations in several genes with known effects on pre- or postnatal growth and health. As with previous molecular epidemiological studies of birth weight, we did not sample the most biologically relevant tissues in the newborn. However, our discovery of biologically plausible associations in a peripheral tissue suggests that further studies of tissues key to fetal growth regulation are warranted.     

The Roles of FMRP-Regulated Genes in Autism Spectrum Disorder: Single- and Multiple-Hit Genetic Etiologies

Autism spectrum disorder (ASD) is a highly heritable complex neurodevelopmental condition characterized by impairments in social interaction and communication and restricted and repetitive behaviors. Although roles for both de novo and familial genetic variation have been documented, the underlying disease mechanisms remain poorly elucidated. In this study, we defined and explored distinct etiologies of genetic variants that affect genes regulated by Fragile-X mental retardation protein (FMRP), thought to play a key role in neuroplasticity and neuronal translation, in ASD-affected individuals. In particular, we developed the Trend test, a pathway-association test that is able to robustly detect multiple-hit etiologies and is more powerful than existing approaches. Exploiting detailed spatiotemporal maps of gene expression within the human brain, we identified four discrete FMRP-target subpopulations that exhibit distinct functional biases and contribute to ASD via different types of genetic variation. We also demonstrated that FMRP target genes are more likely than other genes with similar expression patterns to contribute to disease. We developed the hypothesis that FMRP targets contribute to ASD via two distinct etiologies: (1) ultra-rare and highly penetrant single disruptions of embryonically upregulated FMRP targets (“single-hit etiology”) or (2) the combination of multiple less penetrant disruptions of nonembryonic, synaptic FMRP targets (“multiple-hit etiology”). The Trend test provides rigorous support for a multiple-hit genetic etiology in a subset of autism cases and is easily extendible to combining information from multiple types of genetic variation (i.e., copy-number and exome variants), increasing its value to next-generation sequencing approaches.     

Detection of parent-of-origin effects based on complete and incomplete nuclear families with multiple affected children

Parent-of-origin effects are important in studying genetic traits. More than 1% of all mammalian genes are believed to show parent-of-origin effects. Some statistical methods may be ineffective or fail to detect linkage or association for a gene with parent-of-origin effects. Based on case-parents trios, the parental-asymmetry test (PAT) is simple and powerful in detecting parent-of-origin effects. However, it is common in practice to collect nuclear families with both parents as well as nuclear families with only one parent. In this paper, when only one parent is available for each family with an arbitrary number of affected children, we firstly develop a new test statistic 1-PAT to test for parent-of-origin effects in the presence of association between an allele at the marker locus under study and a disease gene. Then we extend the PAT to accommodate complete nuclear families each with one or more affected children. Combining families with both parents and families with only one parent, the C-PAT is proposed to detect parent-of-origin effects. The validity of the test statistics is verified by simulation in various scenarios of parameter values. A power study shows that using the additional information from incomplete nuclear families in the analysis greatly improves the power of the tests, compared to that based on only complete nuclear families. Also, utilizing all affected children in each family, the proposed tests have a higher power than when only one affected child from each family is selected. Additional power comparison also demonstrates that the C-PAT is more powerful than a number of other tests for detecting parent-of-origin effects.     

Whole-Exome Sequencing of 2,000 Danish Individuals and the Role of Rare Coding Variants in Type 2 Diabetes

It has been hypothesized that, in aggregate, rare variants in coding regions of genes explain a substantial fraction of the heritability of common diseases. We sequenced the exomes of 1,000 Danish cases with common forms of type 2 diabetes (including body mass index > 27.5 kg/m² and hypertension) and 1,000 healthy controls to an average depth of 56×. Our simulations suggest that our study had the statistical power to detect at least one causal gene (a gene containing causal mutations) if the heritability of these common diseases was explained by rare variants in the coding regions of a limited number of genes. We applied a series of gene-based tests to detect such susceptibility genes. However, no gene showed a significant association with disease risk after we corrected for the number of genes analyzed. Thus, we could reject a model for the genetic architecture of type 2 diabetes where rare nonsynonymous variants clustered in a modest number of genes (fewer than 20) are responsible for the majority of disease risk.     

Complex segregation analysis of autism.

A complex segregation analysis of autism in 185 Utah families was carried out using the mixed model. The 209 affected individuals in these families represent nearly complete ascertainment of the autistic cases born in Utah between 1965 and 1984. The sibling recurrence risk for autism was 4.5% (95% confidence limits 2.8%-6.2%). Likelihoods were maximized for major-gene models, a polygenic model, a sibling-effect model, and a mixed model consisting of major-gene and shared-sibling effects. The analysis provided no evidence for major-locus inheritance of autism. Subdivision of the sample according to the probands' IQ levels showed that sibling recurrence risk did not vary consistently with IQ level. A segregation analysis of families in which the proband had an IQ less than 50 also failed to provide evidence for a major locus. However, because of the etiologic heterogeneity of this disorder, genetic analysis of other meaningful subsets of families could prove informative.     

Back to the future: museum specimens in population genetics

Museums and other natural history collections (NHC) worldwide house millions of specimens. With the advent of molecular genetic approaches these collections have become the source of many fascinating population studies in conservation genetics that contrast historical with present-day genetic diversity. Recent developments in molecular genetics and genomics and the associated statistical tools have opened up the further possibility of studying evolutionary change directly. As we discuss here, we believe that NHC specimens provide a largely underutilized resource for such investigations. However, because DNA extracted from NHC samples is degraded, analyses of such samples are technically demanding and many potential pitfalls exist. Thus, we propose a set of guidelines that outline the steps necessary to begin genetic investigations using specimens from NHC.     

Complex segregation analysis of hypospadias

Hypospadias, when the urethra opens on the ventral side of the penis, is a common malformation seen in about 3 per 1000 male births. It is considered a complex disorder with both genetic and environmental factors involved in the pathogenesis. Low birth weight is known to be an important risk factor for hypospadias, but several observations speak in favour of genetic factors as well. In order to delineate the relative contribution of the genetic factors behind hypospadias, we performed a complex segregation analysis of 2005 pedigrees in Sweden. The probands were ascertained through the departments of paediatric surgery and departments of plastic surgery and urology in Sweden where boys with hypospadias undergo surgery. In 7% of the ascertained families one or more additional cases of hypospadias were present. The complex segregation analysis showed a heritability of 0.99 and evidence for multifactorial inheritance. The results suggest that hypospadias might be due to monogenic effects in a small proportion of the families, but that there is a multifactorial cause for the majority of the cases.     

Genetic effects on an animal model of anxiety

Genetic effects on behavioural measures thought to model anxiety have been reported on 15 mouse chromosomes. In general the individual effect from each locus is small, contributing to 10% or less of the total variation, but through use of crosses between inbred rodents the power to detect such effects is high: 39 loci have been reported at stringent levels of significance. Novel multivariate analyses of these data go some way to characterizing the genetic architecture of anxiety and also to validating the tests that are used for its measurement. However, we are still some way from finding the molecular variants that explain the heritability of the trait.     

Statistical approaches in landscape genetics: an evaluation of methods for linking landscape and genetic data

The goal of landscape genetics is to detect and explain landscape effects on genetic diversity and structure. Despite the increasing popularity of landscape genetic approaches, the statistical methods for linking genetic and landscape data remain largely untested. This lack of method evaluation makes it difficult to compare studies utilizing different statistics, and compromises the future development and application of the field. To investigate the suitability and comparability of various statistical approaches used in landscape genetics, we simulated data sets corresponding to five landscape-genetic scenarios. We then analyzed these data with eleven methods, and compared the methods based on their statistical power, type-1 error rates, and their overall ability to lead researchers to accurate conclusions about landscape-genetic relationships. Results suggest that some of the most commonly applied techniques (e.g. Mantel and partial Mantel tests) have high type-1 error rates, and that multivariate, non-linear methods are better suited for landscape genetic data analysis. Furthermore, different methods generally show only moderate levels of agreement. Thus, analyzing a data set with only one method could yield method-dependent results, potentially leading to erroneous conclusions. Based on these findings, we give recommendations for choosing optimal combinations of statistical methods, and identify future research needs for landscape genetic data analyses.     

Molecular genetic analysis of the FMR-1 gene in a large collection of autistic patients

A genetic etiology in autism is now strongly supported by family and twin studies. A 3:1 ratio of affected males to females suggests the involvement of at least one X-linked locus in the disease. Several reports have indicated an association of the fragile X chromosomal anomaly at Xq27.3 (FRAXA) with autism, whereas others have not supported this finding. We have so far collected blood from 105 simplex and 18 multiplex families and have assessed 141 patients by using the Autism Diagnostic Interview-Revised (ADI-R), the Autism Diagnostic Observation Scale, and psychometric tests. All four ADI-R algorithm criteria were met by 131 patients (93%), whereas 10 patients (7%) showed a broader phenotype of autism. Southern blot analysis was performed with three different enzymes, and filters were hybridized to an FMR-1-specific probe to detect amplification of the CCG repeat at FRAXA, to the complete FMR-1 cDNA probe, and to additional probes from the neighborhood of the gene. No significant changes were found in 139 patients (99%) from 122 families, other than the normal variations in the population. In the case of one multiplex familiy with three children showing no dysmorphic features of the fragile X syndrome (one male meeting 3 out of 4 ADI-algorithm criteria, one normal male with slight learning disability but negative ADI-R testing, and one fully autistic female), the FRAXA full-mutation-specific CCG-repeat expansion in the genotype was not correlated with the autism phenotype. Further analysis revealed a mosaic pattern of methylation at the FMR-1 gene locus in the two sons of the family, indicating at least a partly functional gene. Therefore, we conclude that the association of autism with fragile X at Xq27.3 is non-existent and exclude this location as a candidate gene region for autism. Received: 25 October 1996 / Accepted: 10 March 1997     

Identification of Rare Causal Variants in Sequence-Based Studies: Methods and Applications to VPS13B,a Gene Involved in Cohen Syndrome and Autism

Pinpointing the small number of causal variants among the abundant naturally occurring genetic variation is a difficult challenge, but a crucial one for understanding precise molecular mechanisms of disease and follow-up functional studies. We propose and investigate two complementary statistical approaches for identification of rare causal variants in sequencing studies: a backward elimination procedure based on groupwise association tests, and a hierarchical approach that can integrate sequencing data with diverse functional and evolutionary conservation annotations for individual variants. Using simulations, we show that incorporation of multiple bioinformatic predictors of deleteriousness, such as PolyPhen-2, SIFT and GERP++ scores, can improve the power to discover truly causal variants. As proof of principle, we apply the proposed methods to VPS13B, a gene mutated in the rare neurodevelopmental disorder called Cohen syndrome, and recently reported with recessive variants in autism. We identify a small set of promising candidates for causal variants, including two loss-of-function variants and a rare, homozygous probably-damaging variant that could contribute to autism risk.