Assessing the impact of a combined analysis of four common low-risk genetic variants on autism risk

Early Screening of Autism Spectrum Disorder: Recommendations for Practice and Research

This article reviews current evidence for autism spectrum disorder (ASD) screening based on peer-reviewed articles published to December 2013. Screening provides a standardized process to ensure that children are systematically monitored for early signs of ASD to promote earlier diagnosis. The current review indicates that screening in children aged 18 to 24 months can assist in early detection, consistent with current American Academy of Pediatrics' recommendations. We identify ASD-specific and broadband screening tools that have been evaluated in large community samples which show particular promise in terms of accurate classification and clinical utility. We also suggest strategies to help overcome challenges to implementing ASD screening in community practice, as well as priorities for future research.

Early Identification of Autism Spectrum Disorder: Recommendations for Practice and Research

Early identification of autism spectrum disorder (ASD) is essential to ensure that children can access specialized evidence-based interventions that can help to optimize long-term outcomes. Early identification also helps shorten the stressful "diagnostic odyssey" that many families experience before diagnosis. There have been important advances in research into the early development of ASDs, incorporating prospective designs and new technologies aimed at more precisely delineating the early emergence of ASD. Thus, an updated review of the state of the science of early identification of ASD was needed to inform best practice. These issues were the focus of a multidisciplinary panel of clinical practitioners and researchers who completed a literature review and reached consensus on current evidence addressing the question "What are the earliest signs and symptoms of ASD in children aged ≤24 months that can be used for early identification?" Summary statements address current knowledge on early signs of ASD, potential contributions and limitations of prospective research with high-risk infants, and priorities for promoting the incorporation of this knowledge into clinical practice and future research.

A neurogenetics approach to defining differential susceptibility to institutional care

An individual's neurodevelopmental and cognitive sequelae to negative early experiences may, in part, be explained by genetic susceptibility. We examined whether extreme differences in the early caregiving environment, defined as exposure to severe psychosocial deprivation associated with institutional care compared to normative rearing, interacted with a biologically informed genoset comprising BDNF (rs6265), COMT (rs4680), and SIRT1 (rs3758391) to predict distinct outcomes of neurodevelopment at age 8 (N = 193, 97 males and 96 females). Ethnicity was categorized as Romanian (71%), Roma (21%), unknown (7%), or other (1%). We identified a significant interaction between early caregiving environment (i.e., institutionalized versus never institutionalized children) and the a priori defined genoset for full-scale IQ, two spatial working memory tasks, and prefrontal cortex gray matter volume. Model validation was performed using a bootstrap resampling procedure. Although we hypothesized that the effect of this genoset would operate in a manner consistent with differential susceptibility, our results demonstrate a complex interaction where vantage susceptibility, diathesis stress, and differential susceptibility are implicated.

Mitochondrial Aspartate/Glutamate Carrier SLC25A12 and Autism Spectrum Disorder: a Meta-Analysis

Mitochondrial dysfunction has been reported to be involved in the pathophysiology of autism spectrum disorder (ASD). Studies investigating the possible association between ASD and polymorphism in SLC25A12, which encodes the mitochondrial aspartate/glutamate carrier, have yielded inconsistent results. We conducted a systematic review and meta-analysis of such studies to elucidate if and which SLC25A12 single nucleotide polymorphisms (SNPs) are associated with ASD. We searched PubMed, Ovid, Web of Science, and ERIC databases through September 20th, 2014. Odds ratios (ORs) were aggregated using random effect models. Sensitivity analyses were conducted based on study design (family-based or case-control). Fifteen out of 79 non-duplicate records were retained for qualitative synthesis. We pooled 10 datasets from 9 studies with 2001 families, 735 individuals with ASD and 632 typically developing (TD) individuals for the meta-analysis of rs2292813, as well as 11 datasets from 10 studies with 2016 families, 852 individuals with ASD and 1058 TD individuals for the meta-analysis of rs2056202. We found a statistically significant association between ASD and variant in rs2292813 (OR = 1.190, 95% CI 1.052-1.346, P = 0.006) as well as in rs2056202 (OR = 1.206, 95% CI 1.035-1.405, P = 0.016). Sensitivity analyses including only studies with family-based design demonstrated significant association between ASD and polymorphism in rs2292813 (OR = 1.216, 95% CI 1.075-1.376, P = 0.002) and rs2056202 (OR = 1.267, 95% CI 1.041-1.542, P = 0.018). In contrast, sensitivity analyses including case-control design studies only failed to find a significant association. Further research on the role of SLC25A12 and ASD may pave the way for potential innovative therapeutic interventions.

Association study in siblings and case-controls of serotonin- and oxytocin-related genes with high functioning autism

Background

Autism spectrum disorder (ASD) is heritable and neurodevelopmental with unknown causes. The serotonergic and oxytocinergic systems are of interest in autism for several reasons: (i) Both systems are implicated in social behavior, and abnormal levels of serotonin and oxytocin have been found in people with ASD; (ii) treatment with selective serotonin reuptake inhibitors and oxytocin can yield improvements; and (iii) previous association studies have linked the serotonin transporter (SERT; SLC6A4), serotonin receptor 2A (HTR2A), and oxytocin receptor (OXTR) genes with ASD. We examined their association with high functioning autism (HFA) including siblings and their interaction.

Methods

In this association study with HFA children (IQ > 80), siblings, and controls, participants were genotyped for four single nucleotide polymorphisms (SNPs) in OXTR (rs2301261, rs53576, rs2254298, rs2268494) and one in HTR2A (rs6311) as well as the triallelic HTTLPR (SERT polymorphism).

Results

We identified a nominal significant association with HFA for the HTTLPR s allele (consisting of S and L_G alleles) (p = .040; odds ratio (OR) = 1.697, 95% CI 1.191–2.204)). Four polymorphisms (HTTLPR, HTR2A rs6311, OXTR rs2254298 and rs53576) in combination conferred nominal significant risk for HFA with a genetic score of ≥4 (OR = 2.09, 95% CI 1.05–4.18, p = .037). The resulting area under the receiver operating characteristic curve was 0.595 (p = .033).

Conclusions

Our findings, combined with those of previous reports, indicate that ASD, in particular HFA, is polygenetic rather than monogenetic and involves the serotonergic and oxytocin pathways, probably in combination with other factors.

Electronic supplementary material

The online version of this article (doi:10.1186/2049-9256-2-1) contains supplementary material, which is available to authorized users.

Does epilepsy in multiplex autism pedigrees define a different subgroup in terms of clinical characteristics and genetic risk?

BACKGROUND

Autism spectrum disorders (ASD) and epilepsy frequently occur together. Prevalence rates are variable, and have been attributed to age, gender, comorbidity, subtype of pervasive developmental disorder (PDD) and risk factors. Recent studies have suggested disparate clinical and genetic settings depending on simplex or multiplex autism. The aim of this study was to assess: 1) the prevalence of epilepsy in multiplex autism and its association with genetic and non-genetic risk factors of major effect, intellectual disability and gender; and 2) whether autism and epilepsy cosegregate within multiplex autism families.

METHODS

We extracted from the Autism Genetic Resource Exchange (AGRE) database (n = 3,818 children from 1,264 families) all families with relevant medical data (n = 664 children from 290 families). The sample included 478 children with ASD and 186 siblings without ASD. We analyzed the following variables: seizures, genetic and non-genetic risk factors, gender, and cognitive functioning as assessed by Raven's Colored Progressive Matrices (RCPM) and Vineland Adaptive Behavior Scales (VABS).

RESULTS

The prevalence of epilepsy was 12.8% in cases with ASD and 2.2% in siblings without ASD (P <10-5). With each RCPM or VABS measure, the risk of epilepsy in multiplex autism was significantly associated with intellectual disability, but not with gender. Identified risk factors (genetic or non-genetic) of autism tended to be significantly associated with epilepsy (P = 0.052). When children with prematurity, pre- or perinatal insult, or cerebral palsy were excluded, a genetic risk factor was reported for 6/59 (10.2%) of children with epilepsy and 12/395 (3.0%) of children without epilepsy (P = 0.002). Finally, using a permutation test, there was significant evidence that the epilepsy phenotype co-segregated within families (P <10-4).

CONCLUSIONS

Epilepsy in multiplex autism may define a different subgroup in terms of clinical characteristics and genetic risk.

Power and predictive accuracy of polygenic risk scores

Polygenic scores have recently been used to summarise genetic effects among an ensemble of markers that do not individually achieve significance in a large-scale association study. Markers are selected using an initial training sample and used to construct a score in an independent replication sample by forming the weighted sum of associated alleles within each subject. Association between a trait and this composite score implies that a genetic signal is present among the selected markers, and the score can then be used for prediction of individual trait values. This approach has been used to obtain evidence of a genetic effect when no single markers are significant, to establish a common genetic basis for related disorders, and to construct risk prediction models. In some cases, however, the desired association or prediction has not been achieved. Here, the power and predictive accuracy of a polygenic score are derived from a quantitative genetics model as a function of the sizes of the two samples, explained genetic variance, selection thresholds for including a marker in the score, and methods for weighting effect sizes in the score. Expressions are derived for quantitative and discrete traits, the latter allowing for case/control sampling. A novel approach to estimating the variance explained by a marker panel is also proposed. It is shown that published studies with significant association of polygenic scores have been well powered, whereas those with negative results can be explained by low sample size. It is also shown that useful levels of prediction may only be approached when predictors are estimated from very large samples, up to an order of magnitude greater than currently available. Therefore, polygenic scores currently have more utility for association testing than predicting complex traits, but prediction will become more feasible as sample sizes continue to grow.

Recently there has been much interest in combining multiple genetic markers into a single score for predicting disease risk. Even if many of the individual markers have no detected effect, the combined score could be a strong predictor of disease. This has allowed researchers to demonstrate that some diseases have a strong genetic basis, even if few actual genes have been identified, and it has also revealed a common genetic basis for distinct diseases. These analyses have so far been performed opportunistically, with mixed results. Here I derive formulae based on the heritability of disease and size of the study, allowing researchers to plan their analyses from a more informed position. I show that discouraging results in some previous studies were due to the low number of subjects studied, but a modest increase in study size would allow more successful analysis. However, I also show that, for genetics to become useful for predicting individual risk of disease, hundreds of thousands of subjects may be needed to estimate the gene effects. This is larger than most existing studies, but will become more common in the near future, so that gene scores will become more useful for predicting disease than has appeared to date.

Complex epigenetic regulation of engrailed-2 (EN-2) homeobox gene in the autism cerebellum

The elucidation of epigenetic alterations in the autism brain has potential to provide new insights into the molecular mechanisms underlying abnormal gene expression in this disorder. Given strong evidence that engrailed-2 (EN-2) is a developmentally expressed gene relevant to cerebellar abnormalities and autism, the epigenetic evaluation of this candidate gene was undertaken in 26 case and control post-mortem cerebellar samples. Assessments included global DNA methylation, EN-2 promoter methylation, EN-2 gene expression and EN-2 protein levels. Chromatin immunoprecipitation was used to evaluate trimethylation status of histone H3 lysine 27 (H3K27) associated with gene downregulation and histone H3 lysine 4 (H3K4) associated with gene activation. The results revealed an unusual pattern of global and EN-2 promoter region DNA hypermethylation accompanied by significant increases in EN-2 gene expression and protein levels. Consistent with EN-2 overexpression, histone H3K27 trimethylation mark in the EN-2 promoter was significantly decreased in the autism samples relative to matched controls. Supporting a link between reduced histone H3K27 trimethylation and increased EN-2 gene expression, the mean level of histone H3K4 trimethylation was elevated in the autism cerebellar samples. Together, these results suggest that the normal EN-2 downregulation that signals Purkinje cell maturation during late prenatal and early-postnatal development may not have occurred in some individuals with autism and that the postnatal persistence of EN-2 overexpression may contribute to autism cerebellar abnormalities.

Predicting white matter integrity from multiple common genetic variants

Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20-30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ≈ 6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.

Autism risk assessment in siblings of affected children using sex-specific genetic scores

Background

The inheritance pattern in most cases of autism is complex. The risk of autism is increased in siblings of children with autism and previous studies have indicated that the level of risk can be further identified by the accumulation of multiple susceptibility single nucleotide polymorphisms (SNPs) allowing for the identification of a higher-risk subgroup among siblings. As a result of the sex difference in the prevalence of autism, we explored the potential for identifying sex-specific autism susceptibility SNPs in siblings of children with autism and the ability to develop a sex-specific risk assessment genetic scoring system.

Methods

SNPs were chosen from genes known to be associated with autism. These markers were evaluated using an exploratory sample of 480 families from the Autism Genetic Resource Exchange (AGRE) repository. A reproducibility index (RI) was proposed and calculated in all children with autism and in males and females separately. Differing genetic scoring models were then constructed to develop a sex-specific genetic score model designed to identify individuals with a higher risk of autism. The ability of the genetic scores to identify high-risk children was then evaluated and replicated in an independent sample of 351 affected and 90 unaffected siblings from families with at least 1 child with autism.

Results

We identified three risk SNPs that had a high RI in males, two SNPs with a high RI in females, and three SNPs with a high RI in both sexes. Using these results, genetic scoring models for males and females were developed which demonstrated a significant association with autism (P = 2.2 × 10^-6 and 1.9 × 10^-5, respectively).

Conclusions

Our results demonstrate that individual susceptibility associated SNPs for autism may have important differential sex effects. We also show that a sex-specific risk score based on the presence of multiple susceptibility associated SNPs allow for the identification of subgroups of siblings of children with autism who have a significantly higher risk of autism.

Risk factors for autism: translating genomic discoveries into diagnostics

Autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in communication and reciprocal social interaction, and the presence of restricted and repetitive behaviors. The spectrum of autistic features is variable, with severity of symptoms ranging from mild to severe, sometimes with poor clinical outcomes. Twin and family studies indicate a strong genetic basis for ASD susceptibility. Recent progress in defining rare highly penetrant mutations and copy number variations as ASD risk factors has prompted early uptake of these research findings into clinical diagnostics, with microarrays becoming a 'standard of care' test for any ASD diagnostic work-up. The ever-changing landscape of the generation of genomic data coupled with the vast heterogeneity in cause and expression of ASDs (further influenced by issues of penetrance, variable expressivity, multigenic inheritance and ascertainment) creates complexity that demands careful consideration of how to apply this knowledge. Here, we discuss the scientific, ethical, policy and communication aspects of translating the new discoveries into clinical and diagnostic tools for promoting the well-being of individuals and families with ASDs.

Genetic risk in autism: new associations and clinical testing

INTRODUCTION

Autism spectrum disorder (ASD) is prevalent in ∼ 1% of the population worldwide. It is also understood, through twin studies, that ASD has a heritability of 70 - 90%. Molecular genetic studies have presented some genetic risk factors associated with ASD that have potential implications in its diagnosis and genetic testing.

AREAS COVERED

In this selective review, the author refers to previous systematic reviews that consecutively cited all the published papers on ASD at that time. The article presents the replicated genetic risk factors for ASD and the clinical relevance of these findings focusing on rare copy number variations and single gene mutations. The author provides the reader with a deeper insight into the complexity of ASD genetics and its implications for diagnostic genetic testing in ASD. The author also provides the reader with an algorithm for clinical genetic testing in individuals who are clinically diagnosed with ASD.

EXPERT OPINION

Despite the high heritability of ASD and several replicated genetic risk factors, there is no clinical genetic test available that covers most genetic risk factors. Also, validity analyses on most available genetic testing procedures have not been performed so far. The variable risk genotypes, as well as related strongly variable phenotypes, have to be taken into account by genetic counseling.