Dissecting Autism and Schizophrenia Through Neuroimaging Genomics

Clara A. Moreau; Armin Raznahan; Pierre Bellec; Mallar Chakravarty; Paul M. Thompson; Sebastien Jacquemont;


Brain. 2021;144(7):1943-1957. 

In This Article

Abstract and Introduction


Neuroimaging genomic studies of autism spectrum disorder and schizophrenia have mainly adopted a 'top-down' approach, beginning with the behavioural diagnosis, and moving down to intermediate brain phenotypes and underlying genetic factors. Advances in imaging and genomics have been successfully applied to increasingly large case-control studies. As opposed to diagnostic-first approaches, the bottom-up strategy begins at the level of molecular factors enabling the study of mechanisms related to biological risk, irrespective of diagnoses or clinical manifestations. The latter strategy has emerged from questions raised by top-down studies: why are mutations and brain phenotypes over-represented in individuals with a psychiatric diagnosis? Are they related to core symptoms of the disease or to comorbidities? Why are mutations and brain phenotypes associated with several psychiatric diagnoses? Do they impact a single dimension contributing to all diagnoses?

In this review, we aimed at summarizing imaging genomic findings in autism and schizophrenia as well as neuropsychiatric variants associated with these conditions.

Top-down studies of autism and schizophrenia identified patterns of neuroimaging alterations with small effect-sizes and an extreme polygenic architecture. Genomic variants and neuroimaging patterns are shared across diagnostic categories suggesting pleiotropic mechanisms at the molecular and brain network levels. Although the field is gaining traction; characterizing increasingly reproducible results, it is unlikely that top-down approaches alone will be able to disentangle mechanisms involved in autism or schizophrenia.

In stark contrast with top-down approaches, bottom-up studies showed that the effect-sizes of high-risk neuropsychiatric mutations are equally large for neuroimaging and behavioural traits. Low specificity has been perplexing with studies showing that broad classes of genomic variants affect a similar range of behavioural and cognitive dimensions, which may be consistent with the highly polygenic architecture of psychiatric conditions.

The surprisingly discordant effect sizes observed between genetic and diagnostic first approaches underscore the necessity to decompose the heterogeneity hindering case-control studies in idiopathic conditions. We propose a systematic investigation across a broad spectrum of neuropsychiatric variants to identify putative latent dimensions underlying idiopathic conditions. Gene expression data on temporal, spatial and cell type organization in the brain have also considerable potential for parsing the mechanisms contributing to these dimensions' phenotypes. While large neuroimaging genomic datasets are now available in unselected populations, there is an urgent need for data on individuals with a range of psychiatric symptoms and high-risk genomic variants. Such efforts together with more standardized methods will improve mechanistically informed predictive modelling for diagnosis and clinical outcomes.


Introduction: Clinical Diversity in Autism and Schizophrenia

Evolving Boundaries

The nature and definition of autism spectrum disorder (ASD) and schizophrenia have been highly debated for decades. Classifications evolved over time, merging and splitting clinical manifestations. The broadening of diagnostic criteria together with improved clinical awareness has resulted in an increase of ASD prevalence in the past decades, reaching estimates of 1 in 59.[1] In contrast, the schizophrenia population prevalence of ~1% has remained relatively stable.[2] Clinical diversity in schizophrenia was already reported by Bleuler, who described schizophrenia as a 'group of schizophrenia(s)' suggesting that this was a disorder with many possible clinical manifestations. Autism was introduced as a term in 1911 as one of four 'types of impairment in SZ with affectivity, association, and ambivalence'.[3] Autism was later described by Kanner[4] and Asperger,[5] to refer to a dimension of schizoid disorders. By the 1970s, researchers had clearly defined autism and childhood schizophrenia as separate conditions.[6]

The introduction of positive and negative symptoms in the 1980s helped to delineate subgroups of schizophrenia-like manifestations and therefore subgroups of patients. Negative symptoms in schizophrenia (such as social avoidance and emotional flatness) are also partially found in autism where they may be referred to as impairments in communication and motivation.[7] Patients with either ASD or schizophrenia present difficulties in interpreting social cues associated with eye gaze, as well as deficits in theory of mind tasks.[8] Schizophrenia is now defined as a severe mental illness involving disordered thought and perception, with a characteristic onset in late adolescence or early adulthood.[9]

To help distinguish both conditions, a 'trumping rule' accompanied autism in the DSM-III: autism should not be diagnosed in the presence of delusions, hallucinations, and incoherence. Today (DSM-V), spectrum terminology in ASD unifies three previously separate (DSM-IV) diagnoses: autistic's disorder, Asperger's disorder, and pervasive developmental disorder-not otherwise specified (PDD-NOS). Childhood-onset schizophrenia is now a recognized subtype of schizophrenia, defined by an onset before the age of 13 years. Approximately 30% of children and adolescents with childhood-onset schizophrenia also have ASD.[10–12]

It has been suggested that ASD and schizophrenia are extreme representations of symptomatic dimensions that extend into the normal range,[13,14] but these putative dimensions have not yet been identified. Measures of autistic-like traits have been developed (e.g. the Social Responsiveness Scale) to examine subthreshold autistic features in other psychiatric conditions (such as schizophrenia) and non-psychiatric populations.[15] Measures of social communication performed in the general population are genetically correlated with both ASD (during middle childhood) and schizophrenia (later adolescence).[16] These approaches are in line with dimensional models such as the National Institute of Mental Health's Research Domain Criteria Project (RDoC).[13]

Comorbidities are Major Pitfalls in Top-down Studies

Psychiatric comorbidities, which are common in neuropsychiatric disorders, present major caveats for any diagnosis-first studies. When a major diagnosis is assigned to an individual, it will guide treatment and enrolment in future research projects, often ignoring comorbidities. Neuroimaging and genetics findings may relate to core features of the diagnosis of interest or the spectrum of accompanying comorbidities.

Indeed, over a third of patients with ASD meet criteria for other conditions such as obsessive-compulsive disorder (OCD), anxiety, mood disorders, intellectual disability, attention deficit hyperactivity disorder (ADHD), or epilepsy.[17,18] Although 15–25% of youth with ADHD meet the criteria for ASD, and 50–70% of those with ASD present comorbid ADHD,[19] diagnostic criteria for ADHD and ASD did not allow their simultaneous diagnosis until the latest revision of the DSM-V.[20] Intellectual disability, classified as an ASD specifier in the DSM-V, is likewise observed in ~35% of individuals with ASD and can confound diagnostic instruments.[21,22] A study of comorbidity within mental disorders in 5.9 million Danish individuals showed that a prior diagnosis of schizophrenia increased the risk of additional developmental disorders (including autism and intellectual disability, hazard ratio > 15), substance use, as well as personality and behavioural disorders (hazard ratio > 10).[23] A prior diagnosis of developmental disorders increased the risk for intellectual disability (hazard ratio = 50), organic and behavioural disorders (hazard ratio > 15), and schizophrenia (hazard ratio = 8).

Comorbidities are also sex-dependent.[24] For example, adult females with ASD are more likely to be diagnosed with comorbid OCD, mood, or eating disorders, rather than ASD, thereby underestimating the rate of ASD in young females.