No evidence that common genetic risk variation is shared between schizophrenia and autism

Longitudinal follow-up of subsequent psychiatric comorbidities among children and adolescents with autism spectrum disorder

BACKGROUND

The mental health of children and adolescents with autism spectrum disorder (ASD) is a concern of recent years. However, a large-scale longitudinal study investigating the risk and the time course of subsequent psychiatric comorbidities is still lacking.

METHODS

Using the Taiwan National Health Insurance Research Database, 13,382 children and adolescents with ASD, and 53,528 age- and sex-matched non-ASD controls were enrolled between 2001 and 2009, and followed to the end of 2011. The adjusted hazard ratio (HR) with a corresponding 95 % confidence interval for psychiatric comorbidities among children and adolescents with ASD vs matched controls was estimated. The subjects who developed schizophrenia, bipolar disorder, depressive disorder, anxiety disorder, and obsessive-compulsive disorder (OCD) were identified during the follow-up.

RESULTS

Children and adolescents with ASD compared with controls were more likely to be diagnosed with schizophrenia (19.21; 13.74, 26.88), bipolar disorder (17.59; 12.66, 24.44), depressive disorder (5.56; 4.72, 6.56), anxiety disorder (5.01; 4.49, 5.59), and OCD (16.12; 11.66, 22.30) later in life. The time course of subsequent psychiatric comorbidity showed that anxiety disorder occurred first, usually in late childhood, with psychotic and affective disorders proceeding in adolescence. Those with ASD and anxiety disorder had an additionally increased likelihood of developing subsequent psychiatric comorbidity compared with those with ASD only.

LIMITATION

In claims data analysis, clinical parameters or possible confounders may not be fully captured.

CONCLUSION

Patients with ASD are predisposed to the development of anxiety disorder in late childhood, as well as schizophrenia, bipolar disorder, depressive disorder, and OCD in adolescence.

Autism spectrum disorder and schizophrenia: An updated conceptual review

Autism spectrum disorder (ASD) and schizophrenia (SCZ) are separate disorders, with distinct clinical profiles and natural histories. ASD, typically diagnosed in childhood, is characterized by restricted or repetitive interests or behaviors and impaired social communication, and it tends to have a stable course. SCZ, typically diagnosed in adolescence or adulthood, is characterized by hallucinations and delusions, and tends to be associated with declining function. However, youth with ASD are three to six times more likely to develop SCZ than their neurotypical counterparts, and increasingly, research has shown that ASD and SCZ converge at several levels. We conducted a systematic review of studies since 2013 relevant to understanding this convergence, and present here a narrative synthesis of key findings, which we have organized into four broad categories: symptoms and behavior, perception and cognition, biomarkers, and genetic and environmental risk. We then discuss opportunities for future research into the phenomenology and neurobiology of overlap between ASD and SCZ. Understanding this overlap will allow for researchers, and eventually clinicians, to understand the factors that may make a child with ASD vulnerable to developing SCZ. LAY SUMMARY: Autism spectrum disorder and schizophrenia are distinct diagnoses, but people with autism and people with schizophrena share several characteristics. We review recent studies that have examined these areas of overlap, and discuss the kinds of studies we will need to better understand how these disorders are related. Understanding this will be important to help us identify which autistic children are at risk of developing schizophrenia.

A Unifying Theory for Autism: The Pathogenetic Triad as a Theoretical Framework

This paper presents a unifying theory for autism by applying the framework of a pathogenetic triad to the scientific literature. It proposes a deconstruction of autism into three contributing features (an autistic personality dimension, cognitive compensation, and neuropathological risk factors), and delineates how they interact to cause a maladaptive behavioral phenotype that may require a clinical diagnosis. The autistic personality represents a common core condition, which induces a set of behavioral issues when pronounced. These issues are compensated for by cognitive mechanisms, allowing the individual to remain adaptive and functional. Risk factors, both exogenous and endogenous ones, show pathophysiological convergence through their negative effects on neurodevelopment. This secondarily affects cognitive compensation, which disinhibits a maladaptive behavioral phenotype. The triad is operationalized and methods for quantification are presented. With respect to the breadth of findings in the literature that it can incorporate, it is the most comprehensive model yet for autism. Its main implications are that (1) it presents the broader autism phenotype as a non-pathological core personality domain, which is shared across the population and uncoupled from associated features such as low cognitive ability and immune dysfunction, (2) it proposes that common genetic variants underly the personality domain, and that rare variants act as risk factors through negative effects on neurodevelopment, (3) it outlines a common pathophysiological mechanism, through inhibition of neurodevelopment and cognitive dysfunction, by which a wide range of endogenous and exogenous risk factors lead to autism, and (4) it suggests that contributing risk factors, and findings of immune and autonomic dysfunction are clinically ascertained rather than part of the core autism construct.

Psychiatric Polygenic Risk Scores as Predictor for Attention Deficit/Hyperactivity Disorder and Autism Spectrum Disorder in a Clinical Child and Adolescent Sample

Neurodevelopmental disorders such as attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are highly heritable and influenced by many single nucleotide polymorphisms (SNPs). SNPs can be used to calculate individual polygenic risk scores (PRS) for a disorder. We aim to explore the association between the PRS for ADHD, ASD and for Schizophrenia (SCZ), and ADHD and ASD diagnoses in a clinical child and adolescent population. Based on the most recent genome wide association studies of ADHD, ASD and SCZ, PRS of each disorder were calculated for individuals of a clinical child and adolescent target sample (N = 688) and for adult controls (N = 943). We tested with logistic regression analyses for an association with (1) a single diagnosis of ADHD (N = 280), (2) a single diagnosis of ASD (N = 295), and (3) combining the two diagnoses, thus subjects with either ASD, ADHD or both (N = 688). Our results showed a significant association of the ADHD PRS with ADHD status (OR 1.6, P = 1.39 × 10⁻⁰⁷) and with the combined ADHD/ASD status (OR 1.36, P = 1.211 × 10⁻⁰⁵), but not with ASD status (OR 1.14, P = 1). No associations for the ASD and SCZ PRS were observed. In sum, the PRS of ADHD is significantly associated with the combined ADHD/ASD status. Yet, this association is primarily driven by ADHD status, suggesting disorder specific genetic effects of the ADHD PRS.

Essential genetic findings in neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) represent a growing medical challenge in modern societies. Ever-increasing sophisticated diagnostic tools have been continuously revealing a remarkably complex architecture that embraces genetic mutations of distinct types (chromosomal rearrangements, copy number variants, small indels, and nucleotide substitutions) with distinct frequencies in the population (common, rare, de novo). Such a network of interacting players creates difficulties in establishing rigorous genotype-phenotype correlations. Furthermore, individual lifestyles may also contribute to the severity of the symptoms fueling a large spectrum of gene-environment interactions that have a key role on the relationships between genotypes and phenotypes.Herein, a review of the genetic discoveries related to NDDs is presented with the aim to provide useful general information for the medical community.

The use of polygenic risk scores to identify phenotypes associated with genetic risk of schizophrenia: Systematic review

Studying the phenotypic manifestations of increased genetic liability for schizophrenia can increase our understanding of this disorder. Specifically, information from alleles identified in genome-wide association studies can be collapsed into a polygenic risk score (PRS) to explore how genetic risk is manifest within different samples. In this systematic review, we provide a comprehensive assessment of studies examining associations between schizophrenia PRS (SZ-PRS) and several phenotypic measures. We searched EMBASE, Medline and PsycINFO (from August 2009-14th March 2016) plus references of included studies, following PRISMA guidelines. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. Overall, SZ-PRS was associated with increased risk for psychiatric disorders such as depression and bipolar disorder, lower performance IQ and negative symptoms. SZ-PRS explained up to 6% of genetic variation in psychiatric phenotypes, compared to <0.7% in measures of cognition. Future gains from using the PRS approach may be greater if used for examining phenotypes that are more closely related to biological substrates, for scores based on gene-pathways, and where PRSs are used to stratify individuals for study of treatment response. As it was difficult to interpret findings across studies due to insufficient information provided by many studies, we propose a framework to guide robust reporting of PRS associations in the future.

Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations

Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD), autism (AUT), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SZ), are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS) was computed. Two independent general populations (N = 360 and N = 323) were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity. Consistent altered functional connectivity was found with the bilateral insula: for the left supplementary motor area and the left superior temporal gyrus with the cross-disorder PGRS, for the left insula and right middle and superior temporal lobe associated with the PGRS for autism, for the bilateral midbrain, posterior cingulate, cuneus, and precuneus associated with the PGRS for BD, and for the left angular gyrus and the left dorsolateral prefrontal cortex associated with the PGRS for schizophrenia. No significant functional connectivity was found associated with the PGRS for ADHD and MDD. Our findings indicated that genetic effects on the cross-disorder and disorder-specific neural connectivity of common genetic risk loci are detectable in the general population. Our findings also indicated that polygenic risk contributes to the main neurobiological phenotypes of psychiatric disorders and that identifying cross-disorder and specific functional connectivity related to polygenic risks may elucidate the neural pathways for these disorders.

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Altered cross-disorder functional connectivity related to PGRSs is detected.

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Altered disorder-specific functional connectivity related to PGRSs is detected.

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Altered functional connectivity related to PGRSs is involved in brain networks.

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Polygenic risk contributes to neurobiological phenotypes of psychiatric disorders.

Common polygenic variation and risk for childhood-onset schizophrenia

Childhood-onset schizophrenia (COS) is a rare and severe form of the disorder, with more striking abnormalities with respect to prepsychotic developmental disorders and abnormities in the brain development compared with later-onset schizophrenia. We previously documented that COS patients, compared with their healthy siblings and with adult-onset patients (AOS), carry significantly more rare chromosomal copy number variations, spanning large genomic regions (>100 kb) (Ahn et al. 2014). Here, we interrogated the contribution of common polygenic variation to the genetic susceptibility for schizophrenia. We examined the association between a direct measure of genetic risk of schizophrenia in 130 COS probands and 103 healthy siblings. Using data from the schizophrenia and autism GWAS of the Psychiatric Genomic Consortia, we selected three risk-related sets of single nucleotide polymorphisms from which we conducted polygenic risk score comparisons for COS probands and their healthy siblings. COS probands had higher genetic risk scores of both schizophrenia and autism than their siblings (P<0.05). Given the small sample size, these findings suggest that COS patients have more salient genetic risk than do AOS.

Polygenic risk scores in imaging genetics: Usefulness and applications

Genetic factors account for up to 80% of the liability for schizophrenia and bipolar disorder. Genome-wide association studies (GWAS) have successfully identified several single nucleotide polymorphisms (SNPs) and genes associated with increased risk for both disorders. Single SNP analyses alone do not address the overall genomic or polygenic architecture of psychiatric disorders as the amount of phenotypic variation explained by each GWAS-supported SNP is small whereas the number of SNPs/regions underlying risk for illness is thought to be very large. The polygenic risk score models the aggregate effect of alleles associated with disease status present in each individual and allows us to utilise the power of large GWAS to be applied robustly in small samples. Here we make the case that risk prediction, intervention and personalised medicine can only benefit with the inclusion of polygenic risk scores in imaging genetics research.

The association between autism and schizophrenia spectrum disorders: A review of eight alternate models of co-occurrence

Although now believed to be two distinct disorders, autism spectrum disorders (ASD) and schizophrenia spectrum disorders (SSD) share multiple phenotypic similarities and risk factors, and have been reported to co-occur at elevated rates. In this narrative review, we give a brief overview of the phenomenological, genetic, environmental, and imaging evidence for the overlap between ASD and SSD, highlighting similarities and areas of distinction. We examine eight possible alternate models of explanation for the association and comorbidity between the disorders, and set out a research agenda to test these models. Understanding how and why these disorders co-occur has important implications for diagnosis, treatment, and prognosis, as well as for developing fundamental aetiological models of the disorders.

Research review: Polygenic methods and their application to psychiatric traits

BACKGROUND

Despite evidence from twin and family studies for an important contribution of genetic factors to both childhood and adult onset psychiatric disorders, identifying robustly associated specific DNA variants has proved challenging. In the pregenomics era the genetic architecture (number, frequency and effect size of risk variants) of complex genetic disorders was unknown. Empirical evidence for the genetic architecture of psychiatric disorders is emerging from the genetic studies of the last 5 years.

METHODS AND SCOPE

We review the methods investigating the polygenic nature of complex disorders. We provide mini-guides to genomic profile (or polygenic) risk scoring and to estimation of variance (or heritability) from common SNPs; a glossary of key terms is also provided. We review results of applications of the methods to psychiatric disorders and related traits and consider how these methods inform on missing heritability, hidden heritability and still-missing heritability.

FINDINGS

Genome-wide genotyping and sequencing studies are providing evidence that psychiatric disorders are truly polygenic, that is they have a genetic architecture of many genetic variants, including risk variants that are both common and rare in the population. Sample sizes published to date are mostly underpowered to detect effect sizes of the magnitude presented by nature, and these effect sizes may be constrained by the biological validity of the diagnostic constructs.

CONCLUSIONS

Increasing the sample size for genome wide association studies of psychiatric disorders will lead to the identification of more associated genetic variants, as already found for schizophrenia. These loci provide the starting point of functional analyses that might eventually lead to new prevention and treatment options and to improved biological validity of diagnostic constructs. Polygenic analyses will contribute further to our understanding of complex genetic traits as sample sizes increase and as sample resources become richer in phenotypic descriptors, both in terms of clinical symptoms and of nongenetic risk factors.

Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

BACKGROUND AND AIMS

A strong correlation exists between smoking and the use of alcohol and cannabis. This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors. Those scores reflect a combined effect of selected risk alleles for smoking.

METHODS

Summary-level P-values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (n between 22,000 and 70,000 subjects). Using different P-value thresholds (0.1, 0.2 and 0.5) from the meta-analysis, sets of 'risk alleles' were defined and used to generate a polygenic risk score (weighted sum of the alleles) for each subject in an independent target sample from the Netherlands Twin Register (n = 1583). The association between polygenic smoking scores and alcohol/cannabis use was investigated with regression analysis.

RESULTS

The polygenic scores for 'cigarettes per day' were associated significantly with the number of glasses alcohol per week (P = 0.005, R2 = 0.4-0.5%) and cannabis initiation (P = 0.004, R2 = 0.6-0.9%). The polygenic scores for 'age at onset of smoking' were associated significantly with 'age at regular drinking' (P = 0.001, R2 = 1.1-1.5%), while the scores for 'smoking initiation' and 'smoking cessation' did not significantly predict alcohol or cannabis use.

CONCLUSIONS

Smoking, alcohol and cannabis use are influenced by aggregated genetic risk factors shared between these substances. The many common genetic variants each have a very small individual effect size.

Genetically modified mice related to schizophrenia and other psychoses: seeking phenotypic insights into the pathobiology and treatment of negative symptoms

Modelling negative symptoms in any animal model, particularly in mice mutant for genes related to schizophrenia, is complicated by the absence of the following key elements that might assist in developing validation criteria: clinical clarity surrounding this symptom constellation; any clear association between negative symptoms and pathological signature(s) in the brain; and therapeutic strategies with material clinical efficacy against these symptoms. In this review, the application of mutant mouse models to the study of negative symptoms is subjected to critical evaluation, focussing on the following challenges: (a) conceptual issues relating to negative symptoms and their evaluation in mutant models; (b) measurement of negative symptoms in mice, in terms of social behaviour, motivational deficits/avolition and anhedonia; (c) studies in mutants with disruption of genes either regulating aspects of neurotransmission implicated in schizophrenia or associated with risk for psychotic illness; (d) the disaggregation of behavioural phenotypes into underlying pathobiological processes, as a key to the development of new therapeutic strategies for negative symptoms. Advances in genetic and molecular technologies are facilitating these processes, such that more accurate models of putative schizophrenia-linked genetic abnormalities are becoming feasible. This progress in terms of mimicking the genetic contribution to distinct domains of psychopathology associated with psychotic illness must be matched by advances in conceptual/clinical relevance and sensitivity/specificity of phenotypic assessments at the level of behaviour.

Genomic insights into the overlap between psychiatric disorders: implications for research and clinical practice

Psychiatric disorders such as schizophrenia, bipolar disorder, major depressive disorder, attention-deficit/hyperactivity disorder and autism spectrum disorder are common and result in significant morbidity and mortality. Although currently classified into distinct disorder categories, they show clinical overlap and familial co-aggregation, and share genetic risk factors. Recent advances in psychiatric genomics have provided insight into the potential mechanisms underlying the overlap between these disorders, implicating genes involved in neurodevelopment, synaptic plasticity, learning and memory. Furthermore, evidence from copy number variant, exome sequencing and genome-wide association studies supports a gradient of neurodevelopmental psychopathology indexed by mutational load or mutational severity, and cognitive impairment. These findings have important implications for psychiatric research, highlighting the need for new approaches to stratifying patients for research. They also point the way for work aiming to advance our understanding of the pathways from genotype to clinical phenotype, which will be required in order to inform new classification systems and to develop novel therapeutic strategies.

Using genetic findings in autism for the development of new pharmaceutical compounds

RATIONALE

The main reason for the current lack of effective treatments for the core symptoms of autism is our limited understanding of the biological mechanisms underlying this heterogeneous group of disorders. A primary value of genetic research is enhancing our insight into the biology of autism through the study of identified autism risk genes.

OBJECTIVES

In the current review we discuss (1) the genes and loci that are associated with autism, (2) how these provide us with essential cues as to what neurobiological mechanisms may be involved, and (3) how these mechanisms may be used as targets for novel treatments. Next, we provide an overview of currently ongoing clinical trials registered at clinicaltrials.gov with a variety of compounds. Finally, we review current approaches used to translate knowledge derived from gene discovery into novel pharmaceutical compounds and discuss their pitfalls and problems.

CONCLUSIONS

An increasing number of genetic variants associated with autism have been identified. This will generate new ideas about the biological mechanisms involved in autism, which in turn may provide new leads for the development of novel pharmaceutical compounds. To optimize this pipeline of drug discovery, large-scale international collaborations are needed for gene discovery, functional validation of risk genes, and improvement of clinical outcome measures and clinical trial methodology in autism.

Next-generation sequencing in schizophrenia and other neuropsychiatric disorders

Schizophrenia is a debilitating lifelong illness that lacks a cure and poses a worldwide public health burden. The disease is characterized by a heterogeneous clinical and genetic presentation that complicates research efforts to identify causative genetic variations. This review examines the potential of current findings in schizophrenia and in other related neuropsychiatric disorders for application in next-generation technologies, particularly whole-exome sequencing (WES) and whole-genome sequencing (WGS). These approaches may lead to the discovery of underlying genetic factors for schizophrenia and may thereby identify and target novel therapeutic targets for this devastating disorder.

Genetic causes of developmental disorders

PURPOSE OF REVIEW

Developmental disorders, including intellectual disability, autism and attention deficit hyperactivity disorder (ADHD), are neuropsychiatric disorders that manifest in early childhood as deviations from the normal development. At present, in the majority of cases a cause cannot be found. However, in the past 5 years major advances have been made in the identification of specific genetic causes of these disorders. Here, we review these findings and discuss possible implications for our current understanding of the cause of developmental disorders.

RECENT FINDINGS

In addition to the disorders with known genetic cause that are associated with intellectual disability, autism and ADHD, an increasing number of novel recurrent structural variants are identified in association with these developmental disorders. These variants, as well as the genetic variants identified through sequencing approaches indicate the involvement of a large number of genes.

SUMMARY

Similar to what is the case for intellectual disability, recent genetic studies indicate a large degree of genetic heterogeneity for autism and ADHD. Many of the disease risk variants display incomplete penetrance, indicating that additional genetic, and possibly nongenetic, factors are relevant. Despite the high number of causative or contributing genes, functional studies of these genes indicate a large degree of convergence into a smaller number of neurobiological pathways. Elucidating these shared biological mechanisms is a crucial step towards the rational development of novel therapeutic interventions.