Family history of schizophrenia and bipolar disorder as risk factors for autism

3-generation family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions associated with autism: An open-source catalog of findings

The relatively few conditions and family member types (e.g., sibling, parent) considered in investigations of family health history in autism spectrum disorder (ASD, or autism) limits understanding of the role of family history in autism etiology. For more comprehensive understanding and hypothesis-generation, we produced an open-source catalog of autism associations with family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions. All live births in Denmark, 1980-2012, of Denmark-born parents (1,697,231 births), and their 3-generation family members were followed through April 10, 2017 for each of 90 diagnoses (including autism), emigration or death. Adjusted hazard ratios (aHR) were estimated via Cox regression for each diagnosis-family member type combination, adjusting for birth year, sex, birth weight, gestational age, parental ages at birth, and number of family member types of index person; aHRs also calculated for sex-specific co-occurrence of each disorder. We obtained 6462 individual family history aHRS across autism overall (26,840 autistic persons; 1.6% of births), by sex, and considering intellectual disability (ID); and 350 individual co-occurrence aHRS. Results are cataloged in interactive heat maps and down-loadable data files: https://ncrr-au.shinyapps.io/asd-riskatlas/ and interactive graphic summaries: https://public.tableau.com/app/profile/diana.schendel/viz/ASDPlots_16918786403110/e-Figure5. While primarily for reference material or use in other studies (e.g., meta-analyses), results revealed considerable breadth and variation in magnitude of familial health history associations with autism by type of condition, family member type, sex of the family member, side of the family, sex of the index person, and ID status, indicative of diverse genetic, familial, and nongenetic autism etiologic pathways. Careful attention to sources of autism likelihood in family health history, aided by our open data resource, may accelerate understanding of factors underlying neurodiversity.

Progress and Implications from Genetic Studies of Bipolar Disorder

With the advancements in gene sequencing technologies, including genome-wide association studies, polygenetic risk scores, and high-throughput sequencing, there has been a tremendous advantage in mapping a detailed blueprint for the genetic model of bipolar disorder (BD). To date, intriguing genetic clues have been identified to explain the development of BD, as well as the genetic association that might be applied for the development of susceptibility prediction and pharmacogenetic intervention. Risk genes of BD, such as CACNA1C, ANK3, TRANK1, and CLOCK, have been found to be involved in various pathophysiological processes correlated with BD. Although the specific roles of these genes have yet to be determined, genetic research on BD will help improve the prevention, therapeutics, and prognosis in clinical practice. The latest preclinical and clinical studies, and reviews of the genetics of BD, are analyzed in this review, aiming to summarize the progress in this intriguing field and to provide perspectives for individualized, precise, and effective clinical practice.

Family history of psychiatric conditions and development of siblings of children with autism

Younger siblings (SIBS) of children with autism exhibit a wide range of clinical and subclinical symptoms including social, cognitive, language, and adaptive functioning delays. Identifying factors linked with this phenotypic heterogeneity is essential for improving understanding of the underlying biology of the heterogenous outcomes and for early identification of the most vulnerable SIBS. Prevalence of neurodevelopmental (NDD) and neuropsychiatric disorders (NPD) is significantly elevated in families of children with autism. It remains unknown, however, if the family history associates with the developmental outcomes among the SIBS. We quantified history of the NDDs and NPDs commonly reported in families of children with autism using a parent interview and assessed autism symptoms, verbal, nonverbal, and adaptive skills in a sample of 229 SIBS. Multiple regression analyses were used to examine links between family history and phenotypic outcomes, whereas controlling for birth year, age, sex, demographics, and parental education. Results suggest that family history of schizophrenia, depression, anxiety, bipolar disorder, and intellectual disability associate robustly with dimensional measures of social affect, verbal and nonverbal IQ, and adaptive functioning in the SIBS. Considering family history of these disorders may improve efforts to predict long-term outcomes in younger siblings of children with autism and inform about familial factors contributing to high phenotypic heterogenetity in this cohort.

Prevalence of Developmental, Psychiatric, and Neurologic Conditions in Older Siblings of Children with and without Autism Spectrum Disorder: Study to Explore Early Development

This study evaluated developmental, psychiatric, and neurologic conditions among older siblings of children with and without autism spectrum disorder (ASD) to understand the extent of familial clustering of these diagnoses. Using data from the Study to Explore Early Development, a large multi-site case-control study, the analyses included 2,963 children aged 2-5 years with ASD, other developmental disabilities (DD group), and a population-based control group (POP). Percentages of index children with older siblings with select developmental, psychiatric, and neurologic conditions were estimated and compared across index child study groups using chi-square tests and multivariable modified Poisson regression. In adjusted analyses, children in the ASD group were significantly more likely than children in the POP group to have one or more older siblings with ASD, developmental delay, attention-deficit/hyperactivity disorder, intellectual disability, sensory integration disorder (SID), speech/language delays, or a psychiatric diagnosis (adjusted prevalence ratio [aPR] range: 1.4-3.7). Children in the DD group were significantly more likely than children in the POP group to have an older sibling with most of the aforementioned conditions, except for intellectual disability and psychiatric diagnosis (aPR range: 1.4-2.2). Children in the ASD group were significantly more likely than children in the DD group to have one or more older siblings with ASD, developmental delay, SID, or a psychiatric diagnosis (aPR range: 1.4-1.9). These findings suggest that developmental disorders cluster in families. Increased monitoring and screening for ASD and other DDs may be warranted when an older sibling has a DD diagnosis or symptoms.

Molecular profiling of the hippocampus of children with autism spectrum disorder

Several lines of evidence point to a key role of the hippocampus in Autism Spectrum Disorders (ASD). Altered hippocampal volume and deficits in memory for person and emotion related stimuli have been reported, along with enhanced ability for declarative memories. Mouse models have demonstrated a critical role of the hippocampus in social memory dysfunction, associated with ASD, together with decreased synaptic plasticity. Chondroitin sulfate proteoglycans (CSPGs), a family of extracellular matrix molecules, represent a potential key link between neurodevelopment, synaptic plasticity, and immune system signaling. There is a lack of information regarding the molecular pathology of the hippocampus in ASD. We conducted RNAseq profiling on postmortem human brain samples containing the hippocampus from male children with ASD (n = 7) and normal male children (3-14 yrs old), (n = 6) from the NIH NeuroBioBank. Gene expression profiling analysis implicated molecular pathways involved in extracellular matrix organization, neurodevelopment, synaptic regulation, and immune system signaling. qRT-PCR and Western blotting were used to confirm several of the top markers identified. The CSPG protein BCAN was examined with multiplex immunofluorescence to analyze cell-type specific expression of BCAN and astrocyte morphology. We observed decreased expression of synaptic proteins PSD95 (p < 0.02) and SYN1 (p < 0.02), increased expression of the extracellular matrix (ECM) protease MMP9 (p < 0.03), and decreased expression of MEF2C (p < 0.03). We also observed increased BCAN expression with astrocytes in children with ASD, together with altered astrocyte morphology. Our results point to alterations in immune system signaling, glia cell differentiation, and synaptic signaling in the hippocampus of children with ASD, together with alterations in extracellular matrix molecules. Furthermore, our results demonstrate altered expression of genes implicated in genetic studies of ASD including SYN1 and MEF2C.

Adverse Childhood Experiences and Autism: A Meta-Analysis

Evidence suggests that autistic children have a higher probability of experiencing adverse childhood experiences (ACEs) compared to their non-autistic peers. This meta-analysis (PROSPERO: CRD42022262635) aimed to quantify the association of autism and ACEs. Eight databases and Google Scholar were searched for studies that reported dichotomous outcomes regarding the associations between ACEs and autistic individuals, compared to non-autistic individuals. A random-effects model was used to calculate the average Odds Ratio (OR) of the relationship between a diagnosis of autism and ACEs. A total of 40 studies with 5,619,584 participants were included, generating an overall average OR 2.11 (CI 1.61, 2.77). Significant differences in the magnitude of association were found across studies with regards to the type of ACEs studied, comparison groups, and population type. Overall, moderate certainty evidence (downgraded for bias) indicates that autistic individuals are at greater risk of experiencing ACEs, compared to non-autistic individuals. Appropriate support for autistic individuals and their families are required to prevent ACEs and treat the impact of ACEs.

Understanding copy number variations through their genes: a molecular view on 16p11.2 deletion and duplication syndromes

Neurodevelopmental disorders (NDDs) include a broad spectrum of pathological conditions that affect >4% of children worldwide, share common features and present a variegated genetic origin. They include clinically defined diseases, such as autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD), motor disorders such as Tics and Tourette's syndromes, but also much more heterogeneous conditions like intellectual disability (ID) and epilepsy. Schizophrenia (SCZ) has also recently been proposed to belong to NDDs. Relatively common causes of NDDs are copy number variations (CNVs), characterised by the gain or the loss of a portion of a chromosome. In this review, we focus on deletions and duplications at the 16p11.2 chromosomal region, associated with NDDs, ID, ASD but also epilepsy and SCZ. Some of the core phenotypes presented by human carriers could be recapitulated in animal and cellular models, which also highlighted prominent neurophysiological and signalling alterations underpinning 16p11.2 CNVs-associated phenotypes. In this review, we also provide an overview of the genes within the 16p11.2 locus, including those with partially known or unknown function as well as non-coding RNAs. A particularly interesting interplay was observed between MVP and MAPK3 in modulating some of the pathological phenotypes associated with the 16p11.2 deletion. Elucidating their role in intracellular signalling and their functional links will be a key step to devise novel therapeutic strategies for 16p11.2 CNVs-related syndromes.

3-generation family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions associated with autism: an open-source catalogue of findings

The relatively few conditions and family members investigated in autism family health history limits etiologic understanding. For more comprehensive understanding and hypothesis-generation we produced an open-source catalogue of autism associations with family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions. All live births in Denmark, 1980-2012, of Denmark-born parents (1,697,231 births), and their 3-generation family members were followed through April 10, 2017 for each of 90 diagnoses (including autism), emigration or death. Adjusted hazard ratios (aHR) were estimated via Cox regression for each diagnosis-family member type combination, adjusting for birth year, sex, birth weight, gestational age, parental ages at birth, and number of family member types of index person; aHRs also calculated for sex-specific co-occurrence of each disorder. We obtained 6,462 individual family history aHRS across autism overall (26,840 autistic persons; 1.6% of births), by sex, and considering intellectual disability (ID); and 350 individual co-occurrence aHRS. Results are catalogued in interactive heat maps and down-loadable data files: https://ncrr-au.shinyapps.io/asd-riskatlas/ and interactive graphic summaries: https://public.tableau.com/views/ASDPlots_16918786403110/e-Figure5. While primarily for reference material or use in other studies (e.g., meta-analyses), results revealed considerable breadth and variation in magnitude of familial health history associations with autism by type of condition, family member type, sex of the family member, side of the family, sex of the index person, and ID status, indicative of diverse genetic, familial, and non-genetic autism etiologic pathways. Careful attention to sources of autism likelihood in family health history, aided by our open data resource, may accelerate understanding of factors underlying neurodiversity.

Shared Genetic Determinants of Schizophrenia and Autism Spectrum Disorder Implicate Opposite Risk Patterns: A Genome-Wide Analysis of Common Variants

BACKGROUND AND HYPOTHESIS

The synaptic pruning hypothesis posits that schizophrenia (SCZ) and autism spectrum disorder (ASD) may represent opposite ends of neurodevelopmental disorders: individuals with ASD exhibit an overabundance of synapses and connections while SCZ was characterized by excessive pruning of synapses and a reduction. Given the strong genetic predisposition of both disorders, we propose a shared genetic component, with certain loci having differential regulatory impacts.

STUDY DESIGN

Genome-Wide single nucleotide polymorphism (SNP) data of European descent from SCZ (N cases = 53 386, N controls = 77 258) and ASD (N cases = 18 381, N controls = 27 969) were analyzed. We used genetic correlation, bivariate causal mixture model, conditional false discovery rate method, colocalization, Transcriptome-Wide Association Study (TWAS), and Phenome-Wide Association Study (PheWAS) to investigate the genetic overlap and gene expression pattern.

STUDY RESULTS

We found a positive genetic correlation between SCZ and ASD (rg = .26, SE = 0.01, P = 7.87e-14), with 11 genomic loci jointly influencing both conditions (conjFDR <0.05). Functional analysis highlights a significant enrichment of shared genes during early to mid-fetal developmental stages. A notable genetic region on chromosome 17q21.31 (lead SNP rs2696609) showed strong evidence of colocalization (PP.H4.abf = 0.85). This SNP rs2696609 is linked to many imaging-derived brain phenotypes. TWAS indicated opposing gene expression patterns (primarily pseudogenes and long noncoding RNAs [lncRNAs]) for ASD and SCZ in the 17q21.31 region and some genes (LRRC37A4P, LINC02210, and DND1P1) exhibit considerable variation in the cerebellum across the lifespan.

CONCLUSIONS

Our findings support a shared genetic basis for SCZ and ASD. A common genetic variant, rs2696609, located in the Chr17q21.31 locus, may exert differential risk regulation on SCZ and ASD by altering brain structure. Future studies should focus on the role of pseudogenes, lncRNAs, and cerebellum in synaptic pruning and neurodevelopmental disorders.

Assortative mating and parental genetic relatedness contribute to the pathogenicity of variably expressive variants

We examined more than 97,000 families from four neurodevelopmental disease cohorts and the UK Biobank to identify phenotypic and genetic patterns in parents contributing to neurodevelopmental disease risk in children. We identified within- and cross-disorder correlations between six phenotypes in parents and children, such as obsessive-compulsive disorder (R = 0.32-0.38, p < 10-126). We also found that measures of sub-clinical autism features in parents are associated with several autism severity measures in children, including biparental mean Social Responsiveness Scale scores and proband Repetitive Behaviors Scale scores (regression coefficient = 0.14, p = 3.38 × 10-4). We further describe patterns of phenotypic similarity between spouses, where spouses show correlations for six neurological and psychiatric phenotypes, including a within-disorder correlation for depression (R = 0.24-0.68, p < 0.001) and a cross-disorder correlation between anxiety and bipolar disorder (R = 0.09-0.22, p < 10-92). Using a simulated population, we also found that assortative mating can lead to increases in disease liability over generations and the appearance of "genetic anticipation" in families carrying rare variants. We identified several families in a neurodevelopmental disease cohort where the proband inherited multiple rare variants in disease-associated genes from each of their affected parents. We further identified parental relatedness as a risk factor for neurodevelopmental disorders through its inverse relationship with variant pathogenicity and propose that parental relatedness modulates disease risk by increasing genome-wide homozygosity in children (R = 0.05-0.26, p < 0.05). Our results highlight the utility of assessing parent phenotypes and genotypes toward predicting features in children who carry rare variably expressive variants and implicate assortative mating as a risk factor for increased disease severity in these families.

Knowledge, attitudes, and behaviours towards schizophrenia, bipolar disorder, and autism: a pilot study

OBJECTIVES

Lack of knowledge and discriminatory attitudes and behaviours towards individuals with mental disorders is a worldwide problem but may be particularly damaging for young people. This pilot study examined knowledge, attitudes and behaviours towards schizophrenia, bipolar disorder and autism within a large sample of adults in Ireland, a country with the youngest population in Europe, in order to better understand public views on these groups.

METHODS

In a correlational, cross-sectional design, 307 adults in Ireland over the age of 18 completed a questionnaire over Google Forms examining knowledge, attitudes and behaviours towards schizophrenia, bipolar disorder and autism. Responses to questions specifically relating to each diagnosis were compared using trimmed mean ANOVA to examine whether responses to questions differed depending on diagnosis.

RESULTS

Results indicate varied knowledge, attitudes and behaviours towards these groups, but a majority believe it should be a research priority. ANOVA and post hoc tests revealed significant differences in knowledge, attitudes and behaviours towards each of schizophrenia, bipolar disorder, and autism (p < 0.005), and reported attitudes and behaviours towards schizophrenia were more negative than either bipolar disorder or autism. A majority of participants (54.8%) felt not informed enough about mental health by the media.

CONCLUSIONS

In our Irish sample, type and level of stigma varies according to mental health diagnosis. Our sample also report feeling inadequately informed about mental health by the media. Thus future policy and campaigns could consider targeting individual mental health diagnoses, with a focus on increasing familiarity and knowledge.

Autistic symptoms in unaffected first-degree relatives of people with schizophrenia: results from the Italian Network for Research on Psychoses multicenter study

BACKGROUND

Autistic symptoms represent a frequent feature in schizophrenia spectrum disorders (SSD). However, the prevalence and the cognitive and functional correlates of autistic symptoms in unaffected first-degree relatives of people with SSD remain to be assessed.

METHODS

A total of 342 unaffected first-degree relatives related to 247 outpatients with schizophrenia were recruited as part of the multicenter study of the Italian Network for Research on Psychoses (NIRP). Autistic features were measured with the PANSS Autism Severity Scale. Three groups of participants, defined on the presence and severity of autistic symptoms, were compared on a wide array of cognitive and functional measures.

RESULTS

Of the total sample, 44.9% presented autistic symptoms; 22.8% showed moderate levels of autistic symptoms, which can be observed in the majority of people with SSD. Participants with higher levels of autistic symptoms showed worse performance on Working Memory (p = 0.014) and Social Cognition (p = 0.025) domains and in the Global Cognition composite score (p = 0.008), as well as worse on functional capacity (p = 0.001), global psychosocial functioning (p < 0.001), real-world interpersonal relationships (p < 0.001), participation in community activities (p = 0.017), and work skills (p = 0.006).

CONCLUSIONS

A high prevalence of autistic symptoms was observed in first-degree relatives of people with SSD. Autistic symptoms severity showed a negative correlation with cognitive performance and functional outcomes also in this population and may represent a diagnostic and treatment target of considerable scientific and clinical interest in both patients and their first-degree relatives.

Autistic traits distribution in different psychiatric conditions: A cluster analysis on the basis of the Adult Autism Subthreshold Spectrum (AdAS Spectrum) questionnaire

Increasing interest is being paid on full-threshold and sub-threshold autism spectrum conditions among adults. Sub-threshold autistic traits (AT) seem to be distributed in a continuum from the clinical to the general population, being particularly higher among subjects with other psychiatric disorders. The aim of the present study was to evaluate the distribution of AT in a sample of subjects with different psychiatric conditions by means of a cluster analysis on the basis of the score reported to the AdAS Spectrum instrument. A total of 738 subjects recruited by seven Italian Universities were divided in 5 groups depending on the clinical diagnosis: Autism spectrum disorder (ASD), subthreshold ASD symptoms (partial ASD), Bipolar disorder (BD), Feeding and eating disorders (FED), and controls (CTLs). All subjects were assessed with the AdAS Spectrum. The cluster analysis identified 3 clusters: the high, medium and low autism clusters. The Restricted interests and rumination domain reported the highest influence in forming the clusters. The high, medium and low autism clusters were respectively more represented in the ASD, partial ASD and CTL groups. The clusters were represented intermediately in the FED and BD groups, confirming the presence of intermediate levels of AT in these clinical populations.

Assortative mating and parental genetic relatedness drive the pathogenicity of variably expressive variants

We examined more than 38,000 spouse pairs from four neurodevelopmental disease cohorts and the UK Biobank to identify phenotypic and genetic patterns in parents associated with neurodevelopmental disease risk in children. We identified correlations between six phenotypes in parents and children, including correlations of clinical diagnoses such as obsessive-compulsive disorder (R=0.31-0.49, p<0.001), and two measures of sub-clinical autism features in parents affecting several autism severity measures in children, such as bi-parental mean Social Responsiveness Scale (SRS) scores affecting proband SRS scores (regression coefficient=0.11, p=0.003). We further describe patterns of phenotypic and genetic similarity between spouses, where spouses show both within- and cross-disorder correlations for seven neurological and psychiatric phenotypes, including a within-disorder correlation for depression (R=0.25-0.72, p<0.001) and a cross-disorder correlation between schizophrenia and personality disorder (R=0.20-0.57, p<0.001). Further, these spouses with similar phenotypes were significantly correlated for rare variant burden (R=0.07-0.57, p<0.0001). We propose that assortative mating on these features may drive the increases in genetic risk over generations and the appearance of "genetic anticipation" associated with many variably expressive variants. We further identified parental relatedness as a risk factor for neurodevelopmental disorders through its inverse correlations with burden and pathogenicity of rare variants and propose that parental relatedness drives disease risk by increasing genome-wide homozygosity in children (R=0.09-0.30, p<0.001). Our results highlight the utility of assessing parent phenotypes and genotypes in predicting features in children carrying variably expressive variants and counseling families carrying these variants.

Assessment of vulnerability dimensions considering Family History and environmental interplay in Autism Spectrum Disorder

BACKGROUND

Despite previous studies have recently shown Autism Spectrum Disorders (ASD) as having a strong genetics background, over a minimum environmental background, no study up to date has investigated the interplay between genetics and environment.

METHODS

We have collected data regarding Family History (FH) and Environmental Factors (EF) from 2,141 individuals with ASD and their caretakers throughout Brazil, based on an online questionnaire. Most of the ASD individuals were males (81%) and the average age was 02 years minimum for males and females, and the maximum age was 41 years for males and 54 for females. People from all states in Brazil have answered the questionnaire. Genetic inheritance was obtained based on the declared FH of Psychiatric and Neurological diagnosis. As for EF, exposure to risk factors during pregnancy was considered, like infections, diabetes, drugs/chemicals exposure, socioeconomic, and psychological factors. Respondents were invited to answer the questionnaire in lectures given throughout Brazil, and by the social networks of the NGO "The Tooth Fairy Project". A Multiple Correspondence Analysis (MCA) was conducted to search vulnerability dimensions, and a Cluster Analysis was conducted to classify and identify the subgroups.

RESULTS

Regarding EF, social and psychological exposures contributed to the first two dimensions. Concerning FH, the first dimension represented psychiatric FH, while the second represented neurological FH. When analyzed together, EF and FH contributed to two new dimensions: 1. psychiatric FH, and 2. a psychosocial component. Using Cluster Analysis, it was not possible to isolate subgroups by genetic vulnerability or environmental exposure. Instead, a gradient of psychiatric FH with similar contributions of EF was observed.

CONCLUSION

In this study, it was not possible to isolate groups of patients that correspond to only one component, but rather a continuum with different compositions of genetic and environmental interplay.

Neural responses to biological motion distinguish autistic and schizotypal traits

Difficulties in social interactions characterize both autism and schizophrenia and are correlated in the neurotypical population. It is unknown whether this represents a shared etiology or superficial phenotypic overlap. Both conditions exhibit atypical neural activity in response to the perception of social stimuli and decreased neural synchronization between individuals. This study investigated if neural activity and neural synchronization associated with biological motion perception are differentially associated with autistic and schizotypal traits in the neurotypical population. Participants viewed naturalistic social interactions while hemodynamic brain activity was measured with fMRI, which was modeled against a continuous measure of the extent of biological motion. General linear model analysis revealed that biological motion perception was associated with neural activity across the action observation network. However, intersubject phase synchronization analysis revealed neural activity to be synchronized between individuals in occipital and parietal areas but desynchronized in temporal and frontal regions. Autistic traits were associated with decreased neural activity (precuneus and middle cingulate gyrus), and schizotypal traits were associated with decreased neural synchronization (middle and inferior frontal gyri). Biological motion perception elicits divergent patterns of neural activity and synchronization, which dissociate autistic and schizotypal traits in the general population, suggesting that they originate from different neural mechanisms.

The Autism Spectrum: Behavioral, Psychiatric and Genetic Associations

Autism spectrum disorder (ASD) consists of a group of heterogeneous genetic neurobehavioral disorders associated with developmental impairments in social communication skills and stereotypic, rigid or repetitive behaviors. We review common behavioral, psychiatric and genetic associations related to ASD. Autism affects about 2% of children with 4:1 male-to-female ratio and a heritability estimate between 70 and 90%. The etiology of ASD involves a complex interplay between inheritance and environmental factors influenced by epigenetics. Over 800 genes and dozens of genetic syndromes are associated with ASD. Novel gene–protein interactions with pathway and molecular function analyses have identified at least three functional pathways including chromatin modeling, Wnt, Notch and other signaling pathways and metabolic disturbances involving neuronal growth and dendritic spine profiles. An estimated 50% of individuals with ASD are diagnosed with chromosome deletions or duplications (e.g., 15q11.2, BP1-BP2, 16p11.2 and 15q13.3), identified syndromes (e.g., Williams, Phelan-McDermid and Shprintzen velocardiofacial) or single gene disorders. Behavioral and psychiatric conditions in autism impacted by genetics influence clinical evaluations, counseling, diagnoses, therapeutic interventions and treatment approaches. Pharmacogenetics testing is now possible to help guide the selection of psychotropic medications to treat challenging behaviors or co-occurring psychiatric conditions commonly seen in ASD. In this review of the autism spectrum disorder, behavioral, psychiatric and genetic observations and associations relevant to the evaluation and treatment of individuals with ASD are discussed.

Risk of autism spectrum disorder in offspring with parental schizophrenia: a systematic review and meta-analysis

BACKGROUND

The effect of parental schizophrenia on the risk of Autism Spectrum Disorders (ASD) in offspring has been evaluated in previous studies. However, to our knowledge, no systematic review and meta-analysis have assessed this association. In this study, we aimed to evaluate the risk of ASD in offspring with parental schizophrenia.

METHODS

The electronic databases EMBASE, PubMed, and Scopus were systematically searched. We administered the Newcastle Ottawa quality assessment scale (NOS) to assess the quality of all selected studies. Combined effect values, as well as their 95% confidence intervals (CI), were calculated. We evaluated heterogeneity using Q and I² statistics. The publication bias was evaluated by funnel plot and Egger's regression test. In addition, a leave-one-out sensitivity analysis was performed to assess the robustness of the finding.

RESULTS

A total of 12 observational studies (10 cohorts and two case-control) were included. Our study found a high risk of ASD in offspring exposed to parental schizophrenia [RR = 2.38 (CI%95 2.0-2.83)]. Subgroup and sensitivity analysis confirmed the robustness of our main analysis.

CONCLUSION

The risk of ASD is considerably higher in offspring with parental schizophrenia. Our findings may suggest a shared pathologic pathway between schizophrenia and ASD.

Attention-deficit/hyperactivity disorder and other neurodevelopmental disorders in offspring of parents with depression and bipolar disorder

BACKGROUND

Offspring of parents with major mood disorders (MDDs) are at increased risk for early psychopathology. We aim to compare the rates of neurodevelopmental disorders in offspring of parents with bipolar disorder, major depressive disorder, and controls.

METHOD

We established a lifetime diagnosis of neurodevelopmental disorders [attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disabilities, specific learning disorders, and motor disorders] using the Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime Version in 400 participants (mean age 11.3 + s.d. 3.9 years), including 93 offspring of parents with bipolar disorder, 182 offspring of parents with major depressive disorder, and 125 control offspring of parents with no mood disorder.

RESULTS

Neurodevelopmental disorders were elevated in offspring of parents with bipolar disorder [odds ratio (OR) 2.34, 95% confidence interval (CI) 1.23-4.47, p = 0.010] and major depressive disorder (OR 1.87, 95% CI 1.03-3.39, p = 0.035) compared to controls. This difference was driven by the rates of ADHD, which were highest among offspring of parents with bipolar disorder (30.1%), intermediate in offspring of parents with major depressive disorder (24.2%), and lowest in controls (14.4%). There were no significant differences in frequencies of other neurodevelopmental disorders between the three groups. Chronic course of mood disorder in parents was associated with higher rates of any neurodevelopmental disorder and higher rates of ADHD in offspring.

CONCLUSIONS

Our findings suggest monitoring for ADHD and other neurodevelopmental disorders in offspring of parents with MDDs may be indicated to improve early diagnosis and treatment.

Findings of a Multidisciplinary Assessment of Children Referred for Possible Neurodevelopmental Disorders: Insights from a Retrospective Chart Review Study

Children with ASD have a wide spectrum of functional deficits in multiple neurodevelopmental domains. A multidisciplinary team assessment (MDT) is required to assess those deficits to help construct a multimodal intervention plan. This is a retrospective chart review of the assessment for children who were referred for an assessment of potential neurodevelopmental disorders. We reviewed 221 participants' charts from January 2019 to January 2020. The mean age of the children was 7.95 ± 3.69, while the mean age of the fathers and mothers was 37.31 ± 8.57 and 31.95 ± 6.93, respectively. Consanguinity was as high as 37.9% for the referred children with developmental delay who were first-degree related, and 13.2% of the parents were second-degree relatives. Approximately 26.6% of children had a family history of mental illness in first-degree relatives. ASD was the most commonly reported diagnosis post-assessment, and ADHD was the most common reported comorbidity at 64.3% and 88.5%, respectively. The MDT findings showed that 58% of children required moderate or higher assistance with toileting, 79.2% were unable to answer yes/no questions, and 86.8% were unable to understand "wh" questions. Only 26% of the nonverbal children had average IQ testing results, and 31% of verbal children did. In conclusion, the mean age of the children when assessed was above that recommended for early screening and intervention. An increased paternal and maternal age was noticeable. Consanguinity and a family history of mental disorders in first-degree relatives were high, attesting to a possible genetic risk.

Diagnostic progression to schizophrenia: A nationwide cohort study of 11 170 adolescents and young adults with autism spectrum disorder

AIMS

Previous studies have suggested an increased risk of developing schizophrenia later in life in children with autism spectrum disorder (ASD). This study aims to investigate the diagnosis stability and the potential predictors for progression to schizophrenia in ASD.

METHODS

We recruited 11 170 adolescents (10-19 years) and young adults (20-29 years) with ASD between 2001 and 2010. They were followed up to the end of 2011 to identify newly diagnosed schizophrenia. The Kaplan-Meier method and Cox regression with age as a time scale were employed to estimate incidence rates and the significance of candidate predictors.

RESULTS

The progression rate from ASD to schizophrenia was 10.26% for 10 years of follow-up. Among 860 progressors, 580 (67.44%) occurred within the first 3 years after a diagnosis of ASD. The identified predictors were age (reported as hazard ratio with 95% confidence interval: 1.13; 1.11-1.15), depressive disorder (1.36; 1.09-1.69), alcohol use disorder (3.05; 2.14-4.35), substance use disorder (1.91; 1.18-3.09), cluster A personality disorder (2.95; 1.79-4.84), cluster B personality disorder (1.86; 1.05-3.28), and a family history of schizophrenia (2.12; 1.65-2.74).

CONCLUSION

More than two-thirds of the progressors developed schizophrenia within the first 3 years. Demographic characteristics, physical and psychiatric comorbidities, and psychiatric family history were significant predictors of progression.

Associations between parental psychiatric disorders and autism spectrum disorder in the offspring

Whether parental psychiatric disorders are associated with autism spectrum disorder (ASD) in offspring has remained inconclusive. We examined the associations of parental psychiatric disorders with ASD in offspring. This population-based case-control study used Taiwan's National Health Insurance Research Database to identify a cohort of children born from 2004 to 2017 and their parents. A total of 24,279 children with ASD (diagnostic ICD-9-CM code: 299.x or ICD-10 code F84.x) and 97,715 matched controls were included. Parental psychiatric disorders, including depressive disorders, bipolar spectrum disorders, anxiety disorders, obsessive-compulsive disorder, schizophrenia, substance use disorders, autism spectrum disorder, attention-deficit hyperactivity disorder (ADHD), and adjustment disorders were identified. Conditional logistic regressions with covariate adjustment were performed. The results suggest that parental diagnosis with any of the psychiatric disorders is associated with ASD in offspring (adjusted odds ratio [AOR] = 1.45, 95%CI: 1.40-1.51 for mothers; and AOR = 1.12, 95%CI: 1.08-1.17 for fathers). ASD in offspring was associated with schizophrenia, depressive disorders, obsessive-compulsive disorder, adjustment disorders, ADHD and ASD in both parents. The relationship between parental psychiatric disorders and the timing of the child's birth and ASD diagnosis varied across the different psychiatric disorders. The present study provides supportive evidence that parental psychiatric disorders are associated with autistic children. Furthermore, because the associations between parental psychiatric disorders and the timing of child's birth and ASD diagnosis varied across psychiatric disorders, the observed relationships may be affected by both genetic and environmental factors. Future studies are needed to disentangle the potential influence of genetic and environmental factors on the observed associations.

Cross-Disorder Analysis of Genic and Regulatory Copy Number Variations in Bipolar Disorder, Schizophrenia, and Autism Spectrum Disorder

BACKGROUND

We aimed to determine the similarities and differences in the roles of genic and regulatory copy number variations (CNVs) in bipolar disorder (BD), schizophrenia (SCZ), and autism spectrum disorder (ASD).

METHODS

Based on high-resolution CNV data from 8708 Japanese samples, we performed to our knowledge the largest cross-disorder analysis of genic and regulatory CNVs in BD, SCZ, and ASD.

RESULTS

In genic CNVs, we found an increased burden of smaller (<100 kb) exonic deletions in BD, which contrasted with the highest burden of larger (>500 kb) exonic CNVs in SCZ/ASD. Pathogenic CNVs linked to neurodevelopmental disorders were significantly associated with the risk for each disorder, but BD and SCZ/ASD differed in terms of the effect size (smaller in BD) and subtype distribution of CNVs linked to neurodevelopmental disorders. We identified 3 synaptic genes (DLG2, PCDH15, and ASTN2) as risk factors for BD. Whereas gene set analysis showed that BD-associated pathways were restricted to chromatin biology, SCZ and ASD involved more extensive and similar pathways. Nevertheless, a correlation analysis of gene set results indicated weak but significant pathway similarities between BD and SCZ or ASD (r = 0.25-0.31). In SCZ and ASD, but not BD, CNVs were significantly enriched in enhancers and promoters in brain tissue.

CONCLUSIONS

BD and SCZ/ASD differ in terms of CNV burden, characteristics of CNVs linked to neurodevelopmental disorders, and regulatory CNVs. On the other hand, they have shared molecular mechanisms, including chromatin biology. The BD risk genes identified here could provide insight into the pathogenesis of BD.

Integrated entitymetrics analysis for health information on bipolar disorder using social media data and scientific literature

Purpose

This study aimed to examine the mental health information entities and associations between the biomedical, psychological and social domains of bipolar disorder (BD) by analyzing social media data and scientific literature.

Design/methodology/approach

Reddit posts and full-text papers from PubMed Central (PMC) were collected. The text analysis was used to create a psychological dictionary. The text mining tools were applied to extract BD entities and their relationships in the datasets using a dictionary- and rule-based approach. Lastly, social network analysis and visualization were employed to view the associations.

Findings

Mental health information on the drug side effects entity was detected frequently in both datasets. In the affective category, the most frequent entities were “depressed” and “severe” in the social media and PMC data, respectively. The social and personal concerns entities that related to friends, family, self-attitude and economy were found repeatedly in the Reddit data. The relationships between the biomedical and psychological processes, “afraid” and “Lithium” and “schizophrenia” and “suicidal,” were identified often in the social media and PMC data, respectively.

Originality/value

Mental health information has been increasingly sought-after, and BD is a mental illness with complicated factors in the clinical picture. This paper has made an original contribution to comprehending the biological, psychological and social factors of BD. Importantly, these results have highlighted the benefit of mental health informatics that can be analyzed in the laboratory and social media domains.

Paternal and maternal psychiatric disorders associated with offspring autism spectrum disorders: A case-control study

A family history of psychiatric diseases was suggested as one risk factor for autism spectrum disorders (ASD). Our aim was to assess the association of paternal and maternal diagnosis of psychiatric disorders with the risk of ASD in offspring in Taiwan. We conducted a population-based case-control study. Using several linked national databases, we obtained 1,000,939 singleton birth records born between 2004 and 2008. We followed these children up to 2015 for cases of ASD, using diagnostic codes in the National Health Insurance databases. There were 8,933 ASD cases and each case was matched to ten controls by sex and year of birth. We extracted their parental diagnosis of psychiatric disorders and performed conditional logistic regression models to assess the association of interest. Our sample included 8,933 cases and 89,330 controls. Eighty-six percent of the sample were boys. After adjustment for parental age, family income, and urbanization, we found that parental psychiatric diseases were significantly associated with ASD, including schizophrenic and psychotic disorders, mood, anxiety and personality disorders, with adjusted odds ratios ranging from 1.32 to 2.39. Notably, the effect estimates were all larger for maternal diagnosis than paternal diagnosis when stratified by mothers or fathers. Cases of ASD are more likely to be born to parents with psychiatric disorders than their counterparts. Maternal psychiatric diagnosis seems to have a larger influence than paternal diagnosis. Both genetics and maternal environmental factors may contribute to the association observed between parental psychiatric diseases and child ASD.

Familial coaggregation of major psychiatric disorders in first-degree relatives of individuals with autism spectrum disorder: a nationwide population-based study

BACKGROUND

Family coaggregation of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD) and schizophrenia have been presented in previous studies. The shared genetic and environmental factors among psychiatric disorders remain elusive.

METHODS

This nationwide population-based study examined familial coaggregation of major psychiatric disorders in first-degree relatives (FDRs) of individuals with ASD. Taiwan's National Health Insurance Research Database was used to identify 26 667 individuals with ASD and 67 998 FDRs of individuals with ASD. The cohort was matched in 1:4 ratio to 271 992 controls. The relative risks (RRs) and 95% confidence intervals (CI) of ADHD, ASD, BD, MDD and schizophrenia were assessed among FDRs of individuals with ASD and ASD with intellectual disability (ASD-ID).

RESULTS

FDRs of individuals with ASD have higher RRs of major psychiatric disorders compared with controls: ASD 17.46 (CI 15.50-19.67), ADHD 3.94 (CI 3.72-4.17), schizophrenia 3.05 (CI 2.74-3.40), BD 2.22 (CI 1.98-2.48) and MDD 1.88 (CI 1.76-2.00). Higher RRs of schizophrenia (4.47, CI 3.95-5.06) and ASD (18.54, CI 16.18-21.23) were observed in FDRs of individuals with both ASD-ID, compared with ASD only.

CONCLUSIONS

The risk for major psychiatric disorders was consistently elevated across all types of FDRs of individuals with ASD. FDRs of individuals with ASD-ID are at further higher risk for ASD and schizophrenia. Our results provide leads for future investigation of shared etiologic pathways of ASD, ID and major psychiatric disorders and highlight the importance of mental health care delivered to at-risk families for early diagnoses and interventions.

Characterization of cell-cell communication in autistic brains with single-cell transcriptomes

BACKGROUND

Autism spectrum disorder is a neurodevelopmental disorder, affecting 1-2% of children. Studies have revealed genetic and cellular abnormalities in the brains of affected individuals, leading to both regional and distal cell communication deficits.

METHODS

Recent application of single-cell technologies, especially single-cell transcriptomics, has significantly expanded our understanding of brain cell heterogeneity and further demonstrated that multiple cell types and brain layers or regions are perturbed in autism. The underlying high-dimensional single-cell data provides opportunities for multilevel computational analysis that collectively can better deconvolute the molecular and cellular events altered in autism. Here, we apply advanced computation and pattern recognition approaches on single-cell RNA-seq data to infer and compare inter-cell-type signaling communications in autism brains and controls.

RESULTS

Our results indicate that at a global level, there are cell-cell communication differences in autism in comparison with controls, largely involving neurons as both signaling senders and receivers, but glia also contribute to the communication disruption. Although the magnitude of changes is moderate, we find that excitatory and inhibitor neurons are involved in multiple intercellular signaling that exhibits increased strengths in autism, such as NRXN and CNTN signaling. Not all genes in the intercellular signaling pathways show differential expression, but genes in the affected pathways are enriched for axon guidance, synapse organization, neuron migration, and other critical cellular functions. Furthermore, those genes are highly connected to and enriched for genes previously associated with autism risks.

CONCLUSIONS

Overall, our proof-of-principle computational study using single-cell data uncovers key intercellular signaling pathways that are potentially disrupted in the autism brains, suggesting that more studies examining cross-cell type effects can be valuable for understanding autism pathogenesis.

Association and epistatic analysis of white matter related genes across the continuum schizophrenia and autism spectrum disorders: The joint effect of NRG1-ErbB genes

BACKGROUND

Schizophrenia-spectrum disorders (SSD) and Autism spectrum disorders (ASD) are neurodevelopmental disorders that share clinical, cognitive, and genetic characteristics, as well as particular white matter (WM) abnormalities. In this study, we aimed to investigate the role of a set of oligodendrocyte/myelin-related (OMR) genes and their epistatic effect on the risk for SSD and ASD.

METHODS

We examined 108 SNPs in a set of 22 OMR genes in 1749 subjects divided into three independent samples (187 SSD trios, 915 SSD cases/control, and 91 ASD trios). Genetic association and gene-gene interaction analyses were conducted with PLINK and MB-MDR, and permutation procedures were implemented in both.

RESULTS

Some OMR genes showed an association trend with SSD, while after correction, the ones that remained significantly associated were MBP, ERBB3, and AKT1. Significant gene-gene interactions were found between (i) NRG1*MBP (perm p-value = 0.002) in the SSD trios sample, (ii) ERBB3*AKT1 (perm p-value = 0.001) in the SSD case-control sample, and (iii) ERBB3*QKI (perm p-value = 0.0006) in the ASD trios sample.

DISCUSSION

Our results suggest the implication of OMR genes in the risk for both SSD and ASD and highlight the role of NRG1 and ERBB genes. These findings are in line with the previous evidence and may suggest pathophysiological mechanisms related to NRG1/ERBBs signalling in these disorders.

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.

What Do We Know About the Genetic Architecture of Psychopathology?

In the second half of the twentieth century, twin and family studies established beyond a reasonable doubt that all forms of psychopathology are substantially heritable and highly polygenic. These conclusions were simultaneously an important theoretical advance and a difficult methodological obstacle, as it became clear that heritability is universal and undifferentiated across forms of psychopathology, and the radical polygenicity of genetic effects limits the biological insight provided by genetically informed studies at the phenotypic level. The paradigm-shifting revolution brought on by the Human Genome Project has recapitulated the great methodological promise and the profound theoretical difficulties of the twin study era. We review these issues using the rubric of genetic architecture, which we define as a search for specific genetic insight that adds to the general conclusion that psychopathology is heritable and polygenic. Although significant problems remain, we see many promising avenues for progress.

Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Antipsychotic use in pregnancy and risk of attention/deficit-hyperactivity disorder and autism spectrum disorder: a Nordic cohort study

Background

Antipsychotics are increasingly used among women of childbearing age and during pregnancy.

Objective

To determine whether children exposed to antipsychotics in utero are at increased risk of attention-deficit/hyperactivity disorder (ADHD) or autism spectrum disorder (ASD), accounting for maternal diagnoses of bipolar, psychotic and other psychiatric disorders.

Design

Population-based cohort study, including a sibling analysis.

Setting

Nationwide data on all pregnant women and their live-born singletons in Denmark (1997-2017), Finland (1996-2016), Iceland (2004-2017), Norway (2004-2017), and Sweden (2006-2016).

Participants

4 324 086 children were eligible for inclusion to the study cohort.

Intervention

Antipsychotic exposure in utero, assessed by pregnancy trimester, type of antipsychotic, and varying patterns of use.

Main outcome measures

Non-mutually exclusive diagnoses of ADHD and ASD. We used Cox proportional hazard models to calculate hazard ratios (HRs) controlling for maternal psychiatric disorders and other potential confounding factors.

Findings

Among 4 324 086 singleton births, 15 466 (0.4%) were exposed to antipsychotics in utero. During a median follow-up of 10 years, we identified 72 257 children with ADHD and 38 674 children with ASD. Unadjusted HRs were raised for both outcomes but shifted substantially towards the null after adjustment; 1.10 (95%CI 1.00 to 1.27) for ADHD and 1.12 (0.97 to 1.29) for ASD. Adjusted HRs remained consistent by trimester of exposure and type of antipsychotic. Comparing in utero exposure with pre-pregnancy use yielded HRs of 0.74 (0.62 to 0.87) for ADHD and 0.88 (0.70 to 1.10) for ASD. Sibling analyses yielded HRs of 1.14 (0.79 to 1.64) for ADHD and 1.34 (0.75 to 2.39) for ASD.

Discussion

Our findings suggest little or no increased risk of child ADHD or ASD after in utero exposure to antipsychotics.

Clinical implications

Results regarding child neurodevelopment are reassuring for women who need antipsychotics during pregnancy.

Familial and genetic associations between autism spectrum disorder and other neurodevelopmental and psychiatric disorders

BACKGROUND

Familial and genetic associations between autism spectrum disorder (ASD) and other neurodevelopmental and psychiatric disorders have been reported, sometimes with conflicting results. We estimated familial and genetic associations between ASD and nine disorder groups, and explored differences in these associations for ASD in the context of intellectual disability, epilepsy, chromosomal abnormalities, and congenital malformations.

METHODS

Individuals born between 1985 and 2009 living in Sweden on their seventh birthday were linked to their biological parents in order to identify different types of relatives. We retrieved information on all the disorders considered from the National Patient Register. Logistic regression was used to estimate the familial association between ASD and other neurodevelopmental and psychiatric disorders in the different groups of relatives. Structural equation modeling was used to estimate phenotypic (r_p ) and genetic associations (r_g ), as well as the contribution of genetic influences to r_p .

RESULTS

The study included 2,398,608 individuals. Among relatives of individuals diagnosed with ASD, there was an increased risk of the disorders considered, compared to relatives of individuals who were not diagnosed with ASD. Stronger associations were detected for ASD without any additional diagnosis of intellectual disability, epilepsy, chromosomal abnormalities, and congenital malformations. The strongest genetic correlation was estimated between ASD and other neurodevelopmental disorders (r_g  = 0.73; 95% CI = 0.66-0.79). Moderate genetic correlations were estimated for anxiety disorders (r_g  = 0.47; 95% CI = 0.33-0.61), depression (r_g  = 0.52; 95% CI = 0.37-0.66), and intentional self-harm (r_g  = 0.54; 95% CI = 0.36-0.71).

CONCLUSIONS

ASD shows familial and genetic association not only with other neurodevelopmental disorders, but also with other psychiatric disorders, such as anxiety, depression, and intentional self-harm. Family history of ASD comorbid with intellectual disability, epilepsy, congenital malformations, or chromosomal abnormalities is less related to other psychiatric disorders, potentially suggesting a different etiology for this subgroup of patients.

Shared genetic architecture across psychiatric disorders

Psychiatric disorders overlap substantially at the genetic level, with family-based methods long pointing toward transdiagnostic risk pathways. Psychiatric genomics has progressed rapidly in the last decade, shedding light on the biological makeup of cross-disorder risk at multiple levels of analysis. Over a hundred genetic variants have been identified that affect multiple disorders, with many more to be uncovered as sample sizes continue to grow. Cross-disorder mechanistic studies build on these findings to cluster transdiagnostic variants into meaningful categories, including in what tissues or when in development these variants are expressed. At the upper-most level, methods have been developed to estimate the overall shared genetic signal across pairs of traits (i.e. single-nucleotide polymorphism-based genetic correlations) and subsequently model these relationships to identify overarching, genomic risk factors. These factors can subsequently be associated with external traits (e.g. functional imaging phenotypes) to begin to understand the makeup of these transdiagnostic risk factors. As psychiatric genomic efforts continue to expand, we can begin to gain even greater insight by including more fine-grained phenotypes (i.e. symptom-level data) and explicitly considering the environment. The culmination of these efforts will help to inform bottom-up revisions of our current nosology.

Evidence of shared and distinct functional and structural brain signatures in schizophrenia and autism spectrum disorder

Schizophrenia (SZ) and autism spectrum disorder (ASD) share considerable clinical features and intertwined historical roots. It is greatly needed to explore their similarities and differences in pathophysiologic mechanisms. We assembled a large sample size of neuroimaging data (about 600 SZ patients, 1000 ASD patients, and 1700 healthy controls) to study the shared and unique brain abnormality of the two illnesses. We analyzed multi-scale brain functional connectivity among functional networks and brain regions, intra-network connectivity, and cerebral gray matter density and volume. Both SZ and ASD showed lower functional integration within default mode and sensorimotor domains, but increased interaction between cognitive control and default mode domains. The shared abnormalties in intra-network connectivity involved default mode, sensorimotor, and cognitive control networks. Reduced gray matter volume and density in the occipital gyrus and cerebellum were observed in both illnesses. Interestingly, ASD had overall weaker changes than SZ in the shared abnormalities. Interaction between visual and cognitive regions showed disorder-unique deficits. In summary, we provide strong neuroimaging evidence of the convergent and divergent changes in SZ and ASD that correlated with clinical features.

Unique Morphometric Features of the Cerebellum and Cerebellocerebral Structural Correlation Between Autism Spectrum Disorder and Schizophrenia

Background

Although cerebellar morphological involvement has been increasingly recognized in autism spectrum disorder (ASD) and schizophrenia (SZ), the extent to which there are morphological differences between them has not been definitively quantified. Furthermore, although previous studies have demonstrated increased anatomical cerebellocerebral correlations in both conditions, differences between their associations have not been well characterized.

Methods

We compared cerebellar volume between males with ASD (n = 31), males with SZ (n = 28), and typically developing males (n = 49). A total of 31 cerebellar subregions were investigated with the cerebellum segmented into their constituent lobules, in gray matter (GM) and white matter (WM) separately. Additionally, structural correlations with the contralateral cerebrum were analyzed for each cerebellar lobule.

Results

We found significantly larger WM volume in the bilateral lobules VI and Crus I in the ASD group than in other groups. While WM or GM volumes of these right lobules had positive associations with ASD symptoms, there was a negative association between GM volume of the right Crus I and SZ symptoms. We further observed, in the ASD group specifically, significant correlations between WM of the right lobule VI and WM of the left frontal pole (r = 0.67) and between GM of the right lobule VI and the left caudate (r = 0.60).

Conclusions

Our findings support evidence that cerebellar morphology is involved in ASD and SZ with different mechanisms. Furthermore, this study showed that these biological differences require consideration when determining diagnostic criteria and treatment for these disorders.

Prediction of Autism Risk From Family Medical History Data Using Machine Learning: A National Cohort Study From Denmark

Background

A family history of specific disorders (e.g., autism, depression, epilepsy) has been linked to risk for autism spectrum disorder (ASD). This study examines whether family history data could be used for ASD risk prediction.

Methods

We followed all Danish live births, from 1980 to 2012, of Denmark-born parents for an ASD diagnosis through April 10, 2017 (N = 1,697,231 births; 26,840 ASD cases). Linking each birth to three-generation family members, we identified 438 morbidity indicators, comprising 73 disorders reported prospectively for each family member. We tested various models using a machine learning approach. From the best-performing model, we calculated a family history risk score and estimated odds ratios and 95% confidence intervals for the risk of ASD.

Results

The best-performing model comprised 41 indicators: eight mental conditions (e.g., ASD, attention-deficit/hyperactivity disorder, neurotic/stress disorders) and nine nonmental conditions (e.g., obesity, hypertension, asthma) across six family member types; model performance was similar in training and test subsamples. The highest risk score group had 17.0% ASD prevalence and a 15.3-fold (95% confidence interval, 14.0-17.1) increased ASD risk compared with the lowest score group, which had 0.6% ASD prevalence. In contrast, individuals with a full sibling with ASD had 9.5% ASD prevalence and a 6.1-fold (95% confidence interval, 5.9-6.4) higher risk than individuals without an affected sibling.

Conclusions

Family history of multiple mental and nonmental conditions can identify more individuals at highest risk for ASD than only considering the immediate family history of ASD. A comprehensive family history may be critical for a clinically relevant ASD risk prediction framework in the future.

Autistic traits in psychotic disorders: prevalence, familial risk, and impact on social functioning

BACKGROUND

Prevalence estimates of autistic traits in individuals with psychotic disorders (PD) vary greatly and it is unclear whether individuals with a familial risk (FR) for psychosis have an increased propensity to display autistic traits. Furthermore, it is unknown whether the presence of comorbid autism traits disproportionally affects the cognitive and behavioral aspects of social functioning in PD.

METHODS

In total, 504 individuals with PD, 587 unaffected siblings with FR, and 337 typical comparison (TC) individuals (16-50 years) were included. Autistic and psychotic traits were measured with the Autism Spectrum Quotient (AQ) and the Community Assessment of Psychic Experiences (CAPE). Social cognition was assessed with the Picture Sequencing Task (PST) and social behavior with the Social Functioning Scale (SFS).

RESULTS

For PD 6.5% scored above AQ clinical cut-off (⩾32), 1.0% for FR, and 1.2% for TC. After accounting for age, sex, and IQ, the PD group showed significantly more autistic traits and alterations in social behavior and cognition, while FR and TC only displayed marginal differences. Within the PD group autistic traits were a robust predictor of social behavior and there were no interactions with positive psychotic symptoms.

CONCLUSIONS

Levels of autistic traits are substantially elevated in PD and have a profoundly negative association with social functioning. In contrast, autistic traits above the clinical cut-off are not elevated in those with FR, and only marginally on a dimensional level. These findings warrant specific clinical guidelines for psychotic patients who present themselves with autistic comorbidity to help address their social needs.

Autistic traits in offspring of schizophrenic patients in comparison to those of normal population: a case-control study

Background

Autism is not a discreet condition and those families members with autistic propend are more likely to display autistic symptoms with a wide range of severity, even below the threshold for diagnosis of autism spectrum disorders. Even with a parental history of schizophrenia, the likelihood of autistic spectrum disorder was found to be 3-fold greater. The aim of this study is to assess autistic traits among offspring of schizophrenic patients in the age group from 4 to 11 years and compare it in the offspring of normal individuals, and its association with the sociodemographic data. To determine whether schizophrenic parents are a risk factor to autistic traits in their children.

Results

There was a statistically significant (P < 0.05*) increase in Autism Quotient Child scores of the case group where 47.2% had a score equal or more than the cutoff point (76), while only 17 19.4% of the control group had the same score with odds = 3.71 indicating that children of schizophrenic parents 18 were three times likely to have Autism Quotient-Child score greater than or equal to the cutoff point (76) than 19 children of healthy parents. No statistically significant association (P ≥ 0.05) was found between all 20 sociodemographic characteristics and Autism Quotient-Child scores among the case group except for family 21 income and social class where there was a statistically significant association (P < 0.05) between insufficient income 22 and low social class and higher Autism Quotient-Child score (≥ 76).

Conclusions

Children of schizophrenic parents are at high risk to have autistic traits than children of normal parents.

Cross-Disorder Analysis of De Novo Mutations in Neuropsychiatric Disorders

The clinical similarity among different neuropsychiatric disorders (NPDs) suggested a shared genetic basis. We catalogued 23,109 coding de novo mutations (DNMs) from 6511 patients with autism spectrum disorder (ASD), 4,293 undiagnosed developmental disorder (UDD), 933 epileptic encephalopathy (EE), 1022 intellectual disability (ID), 1094 schizophrenia (SCZ), and 3391 controls. We evaluated that putative functional DNMs contribute to 38.11%, 34.40%, 33.31%, 10.98% and 6.91% of patients with ID, EE, UDD, ASD and SCZ, respectively. Consistent with phenotype similarity and heterogeneity in different NPDs, they show different degree of genetic association. Cross-disorder analysis of DNMs prioritized 321 candidate genes (FDR < 0.05) and showed that genes shared in more disorders were more likely to exhibited specific expression pattern, functional pathway, genetic convergence, and genetic intolerance.

Psychiatric Neural Networks and Precision Therapeutics by Machine Learning

Learning and environmental adaptation increase the likelihood of survival and improve the quality of life. However, it is often difficult to judge optimal behaviors in real life due to highly complex social dynamics and environment. Consequentially, many different brain regions and neuronal circuits are involved in decision-making. Many neurobiological studies on decision-making show that behaviors are chosen through coordination among multiple neural network systems, each implementing a distinct set of computational algorithms. Although these processes are commonly abnormal in neurological and psychiatric disorders, the underlying causes remain incompletely elucidated. Machine learning approaches with multidimensional data sets have the potential to not only pathologically redefine mental illnesses but also better improve therapeutic outcomes than DSM/ICD diagnoses. Furthermore, measurable endophenotypes could allow for early disease detection, prognosis, and optimal treatment regime for individuals. In this review, decision-making in real life and psychiatric disorders and the applications of machine learning in brain imaging studies on psychiatric disorders are summarized, and considerations for the future clinical translation are outlined. This review also aims to introduce clinicians, scientists, and engineers to the opportunities and challenges in bringing artificial intelligence into psychiatric practice.

Examining the association between childhood autistic traits and adolescent hypomania: a longitudinal twin study

BACKGROUND

There is evidence that autism spectrum disorders (ASDs) co-occur with bipolar disorder (BD) relatively frequently. Individuals with BD often report symptoms of mania and hypomania during adolescence, prior to the age of onset for BD. It is unknown whether these symptoms are associated with ASDs. We examined whether diagnoses of ASDs and autistic traits were associated with hypomania in a large, population-based Swedish twin sample.

METHODS

Parental structured interviews assessed autistic traits, and were used to assign screening diagnoses of ASDs, when twins were aged 9 or 12 (N = 13 533 pairs). Parents then completed questionnaires assessing hypomania when the twins were aged 15 and 18 (N = 3852 pairs at age 15, and 3013 pairs at age 18). After investigating the phenotypic associations between these measures, we used the classical twin design to test whether genetic and environmental influences on autistic traits influence variation in adolescent hypomania.

RESULTS

Autistic traits and ASD diagnoses in childhood were associated with elevated scores on the measures of adolescent hypomania. Twin analyses indicated that 6-9% of the variance in hypomania was explained by genetic influences that were shared with autistic traits in childhood. When repeating these analyses for specific autistic trait domains, we found a stronger association between social interaction difficulties and hypomania than for other autistic trait domains.

CONCLUSIONS

These results indicate a genetic link between autistic traits and hypomania in adolescence. This adds to the growing evidence base of genetic factors associated with ASDs showing links with psychiatric outcomes across childhood and into adulthood.

Dynamic functional network reconfiguration underlying the pathophysiology of schizophrenia and autism spectrum disorder

The dynamics of the human brain span multiple spatial scales, from connectivity associated with a specific region/network to the global organization, each representing different brain mechanisms. Yet brain reconfigurations at different spatial scales are seldom explored and whether they are associated with the neural aspects of brain disorders is far from understood. In this study, we introduced a dynamic measure called step-wise functional network reconfiguration (sFNR) to characterize how brain configuration rewires at different spatial scales. We applied sFNR to two independent datasets, one includes 160 healthy controls (HCs) and 151 patients with schizophrenia (SZ) and the other one includes 314 HCs and 255 individuals with autism spectrum disorder (ASD). We found that both SZ and ASD have increased whole-brain sFNR and sFNR between cerebellar and subcortical/sensorimotor domains. At the ICN level, the abnormalities in SZ are mainly located in ICNs within subcortical, sensory, and cerebellar domains, while the abnormalities in ASD are more widespread across domains. Interestingly, the overlap SZ-ASD abnormality in sFNR between cerebellar and sensorimotor domains was correlated with the reasoning-problem-solving performance in SZ (r = -.1652, p = .0058) as well as the Autism Diagnostic Observation Schedule in ASD (r = .1853, p = .0077). Our findings suggest that dynamic reconfiguration deficits may represent a key intersecting point for SZ and ASD. The investigation of brain dynamics at different spatial scales can provide comprehensive insights into the functional reconfiguration, which might advance our knowledge of cognitive decline and other pathophysiology in brain disorders.

Risk in Relatives, Heritability, SNP-Based Heritability, and Genetic Correlations in Psychiatric Disorders: A Review

The genetic contribution to psychiatric disorders is observed through the increased rates of disorders in the relatives of those diagnosed with disorders. These increased rates are observed to be nonspecific; for example, children of those with schizophrenia have increased rates of schizophrenia but also a broad range of other psychiatric diagnoses. While many factors contribute to risk, epidemiological evidence suggests that the genetic contribution carries the highest risk burden. The patterns of inheritance are consistent with a polygenic architecture of many contributing risk loci. The genetic studies of the past decade have provided empirical evidence identifying thousands of DNA variants associated with psychiatric disorders. Here, we describe how these latest results are consistent with observations from epidemiology. We provide an R tool (CHARRGe) to calculate genetic parameters from epidemiological parameters and vice versa. We discuss how the single nucleotide polymorphism-based estimates of heritability and genetic correlation relate to those estimated from family records.

Functional genomics links genetic origins to pathophysiology in neurodegenerative and neuropsychiatric disease

Neurodegenerative and neuropsychiatric disorders are pervasive and debilitating conditions characterized by diverse clinical syndromes and comorbidities, whose origins are as complex and heterogeneous as their associated phenotypes. Risk for these disorders involves substantial genetic liability, which has fueled large-scale genetic studies that have led to a flood of discoveries. In turn, these discoveries have exposed substantial gaps in our knowledge with regards to the complicated genetic architecture of each disorder and the substantial amount of genetic overlap among disorders, which implies some degree of shared pathophysiology underlying these clinically distinct, multifactorial disorders. Understanding the role of specific genetic variants will involve resolving the connections between molecular pathways, heterogeneous cell types, specific circuits and disease pathogenesis at the tissue and patient level. We consider the current known genetic basis of these disorders and highlight the utility of molecular systems approaches that establish the function of genetic variation in the context of specific neurobiological networks, cell-types, and life stages. Beyond expanding our knowledge of disease mechanisms, understanding these relationships provides promise for early detection and potential therapeutic interventions.

An intervention to improve the quality of life in children of parents with serious mental illness: the Young SMILES feasibility RCT

BACKGROUND

Quality of life for children and adolescents living with serious parental mental illness can be impaired, but evidence-based interventions to improve it are scarce.

OBJECTIVE

Co-production of a child-centred intervention [called Young Simplifying Mental Illness plus Life Enhancement Skills (SMILES)] to improve the health-related quality of life of children and adolescents living with serious parental mental illness, and evaluating its acceptability and feasibility for delivery in NHS and community settings.

DESIGN

Qualitative and co-production methods informed the development of the intervention (Phase I). A feasibility randomised controlled trial was designed to compare Young SMILES with treatment as usual (Phase II). Semistructured qualitative interviews were used to explore acceptability among children and adolescents living with their parents, who had serious mental illness, and their parents. A mixture of semistructured qualitative interviews and focus group research was used to examine feasibility among Young SMILES facilitators and referrers/non-referrers.

SETTING

Randomisation was conducted after baseline measures were collected by the study co-ordinator, ensuring that the blinding of the statistician and research team was maintained to reduce detection bias.

PARTICIPANTS

Phase I: 14 children and adolescents living with serious parental mental illness, seven parents and 31 practitioners from social, educational and health-related sectors. Phase II: 40 children and adolescents living with serious parental mental illness, 33 parents, five referrers/non-referrers and 16 Young SMILES facilitators.

INTERVENTION

Young SMILES was delivered at two sites: (1) Warrington, supported by the National Society for the Prevention of Cruelty to Children (NSPCC), and (2) Newcastle, supported by the NHS and Barnardo's. An eight-session weekly group programme was delivered, with four to six children and adolescents living with serious parental mental illness per age-appropriate group (6-11 and 12-16 years). At week 4, a five-session parallel weekly programme was offered to the parents/carers. Sessions lasted 2 hours each and focused on improving mental health literacy, child-parent communication and children's problem-solving skills.

MAIN OUTCOME MEASURES

Phase ll children and parents completed questionnaires at randomisation and then again at 4 and 6 months post randomisation. Quality of life was self-reported by children and proxy-reported by parents using the Paediatric Quality of Life questionnaire and KIDSCREEN. Semistructured interviews with parents (n = 14) and children (n = 17) who participated in the Young SMILES groups gathered information about their motivation to sign up to the study, their experiences of participating in the group sessions, and their perceived changes in themselves and their family members following intervention. Further interviews with individual referrers (n = 5) gathered information about challenges to recruitment and randomisation. Two focus groups (n = 16) with practitioners who facilitated the intervention explored their views of the format and content of the Young SMILES manual and their suggestions for changes.

RESULTS

A total of 35 families were recruited: 20 were randomly allocated to Young SMILES group and 15 to treatment as usual. Of those, 28 families [15/20 (75%) in the intervention group and 13/15 (87%) in the control group] gave follow-up data at the primary end point (4 months post baseline). Participating children had high adherence to the intervention and high completion rates of the questionnaires. Children and adolescents living with their parents, who had serious mental illness, and their parents were mainly very positive and enthusiastic about Young SMILES, both of whom invoked the benefits of peer support and insight into parental difficulties. Although facilitators regarded Young SMILES as a meaningful and distinctive intervention having great potential, referrers identified several barriers to referring families to the study. One harm was reported by a parent, which was dealt with by the research team and the NSPCC in accordance with the standard operating procedures.

LIMITATIONS

The findings from our feasibility study are not sufficient to recommend a fully powered trial of Young SMILES in the near future. Although it was feasible to randomise children and adolescents living with serious parental mental illness of different ages to standardised, time-limited groups in both NHS and non-NHS settings, an intervention like Young SMILES is unlikely to address underlying core components of the vulnerability that children and adolescents living with serious parental mental illness express as a population over time.

CONCLUSIONS

Young SMILES was widely valued as unique in filling a recognised gap in need. Outcome measures in future studies of interventions for children and adolescents living with serious parental mental illness are more likely to capture change in individual risk factors for reduced quality of life by considering their unmet need, rather than on an aggregate construct of health-related quality of life overall, which may not reflect these young people's needs.

FUTURE WORK

A public health approach to intervention might be best. Most children and adolescents living with serious parental mental illness remain well most of the time, so, although their absolute risks are low across outcomes (and most will remain resilient most of the time), consistent population estimates find their relative risk to be high compared with unexposed children. A public health approach to intervention needs to be both tailored to the particular needs of children and adolescents living with serious parental mental illness and agile to these needs so that it can respond to fluctuations over time.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN36865046.

FUNDING

This project was funded by the National Institute of Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 59. See the NIHR Journals Library website for further project information.

LRP8 (rs5177) and CEP85L (rs11756438) are contributed to schizophrenia susceptibility in Iranian population

Introduction Schizophrenia is recognized as one of the most important mental illnesses of the last century. Many genetic and environmental factors are involved in this condition. Recently, the genome-wide association study identified two significant genes LRP8 and CEP85L associated with psychiatric disorders. LRP8 (low-density lipoprotein receptor-related protein 8) acts as a cytoplasmic receptor for Reelin. Many studies have revealed that LRP8 was significantly related to schizophrenia and bipolar disorder in Chinese population. CEP85L standing for 'centrosomal protein 85 kDa-like' is another gene, which has been reportedly associated with BPD. Methods We performed a case-control study to analyze the association between rs5177 single-nucleotide polymorphism in the LRP8 gene plus the single-nucleotide polymorphism rs11756438 in the CEP85L gene and schizophrenia in the Iranian population. The genotype for rs5177 was determined by ARMS PCR method, while for rs11756438 genotype, it was determined by PCR-RFLP method after which statistical analysis was performed for each polymorphism. In rs5177, the CC genotype was susceptible to the disease while G allele was associated with disease protection. Results and Conclusion In rs11756438, the AA genotype was associated with disease susceptibility, while allele A did not have a significant association with the disease.

Implications of germline copy-number variations in psychiatric disorders: review of large-scale genetic studies

Copy number variants (CNVs), defined as genome sequences of ≥50 bp that differ in copy number from that in a reference genome, are a common form of structural variation. Germline CNVs account for some of the missing heritability that single nucleotide polymorphisms could not account for. Recent technological advances have had a huge impact on CNV research. Microarray technology enables relatively low-cost, high-throughput, genome-wide measurements, and short-read sequencing technology enables the detection of short CNVs that cannot be detected by microarrays. As a result, large-scale genetic studies have been able to identify a variety of common and rare germline CNVs and their associations with diseases. Rare germline CNVs have been reported to be associated with neuropsychiatric disorders. In this review, we focused on germline CNVs and briefly described their functional characteristics, formation mechanisms, detection methods, related databases, and the latest findings. Finally, we introduced recent large-scale genetic studies to assess associations of CNVs with diseases, especially psychiatric disorders, and discussed the use of CNV-based animal models to investigate the molecular and cellular mechanisms underlying these disorders. The development and implementation of improved detection methods, such as long-read single-molecule sequencing, are expected to provide additional insight into the molecular basis of psychiatric disorders and other complex diseases, thus facilitating basic and clinical research on CNVs.

Overlapping but Asymmetrical Relationships Between Schizophrenia and Autism Revealed by Brain Connectivity

Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. The authors quantified and visualized the relationship between ASD and SSD using dual classifiers that discriminate patients from healthy controls (HCs) based on resting-state functional connectivity magnetic resonance imaging. To develop a reliable SSD classifier, sophisticated machine-learning algorithms that automatically selected SSD-specific functional connections were applied to Japanese datasets from Kyoto University Hospital (N = 170) including patients with chronic-stage SSD. The generalizability of the SSD classifier was tested by 2 independent validation cohorts, and 1 cohort including first-episode schizophrenia. The specificity of the SSD classifier was tested by 2 Japanese cohorts of ASD and major depressive disorder. The weighted linear summation of the classifier's functional connections constituted the biological dimensions representing neural classification certainty for the disorders. Our previously developed ASD classifier was used as ASD dimension. Distributions of individuals with SSD, ASD, and HCs s were examined on the SSD and ASD biological dimensions. We found that the SSD and ASD populations exhibited overlapping but asymmetrical patterns in the 2 biological dimensions. That is, the SSD population showed increased classification certainty for the ASD dimension but not vice versa. Furthermore, the 2 dimensions were correlated within the ASD population but not the SSD population. In conclusion, using the 2 biological dimensions based on resting-state functional connectivity enabled us to discover the quantified relationships between SSD and ASD.

An integrative gene network-based approach to uncover the cellular and molecular infrastructures of schizophrenia

AIMS

High phenotypic and endophenotypic heritability of schizophrenia indicates substantial involvement of genetic elements in the occurrence of this disorder. Multiplicity of hypotheses about the genetic basis of schizophrenia pathogenesis suggests that there is still no integrated image from cellular and molecular infrastructure of this disorder.

MATERIALS AND METHODS

Here, we aimed to gain an integrated insight into the genetic basis of schizophrenia through gene set enrichment and network analysis to find the most important developmental stages/brain regions, chromosomal locations and metabolic pathways involved in the pathogenesis of schizophrenia. We investigated major mental disorders whose genetic bases are significantly overlapping with the schizophrenia gene set.

KEY FINDINGS

Enrichment analyses uncovered 60 developmental stages/brain regions, 21 chromosomal hotspots and 16 pathways which are significantly associated with the found gene set. Our results demonstrated early mid-fetal/cortex as the most prominent developmental stage/brain region, chr16q22 as the most significant cytoband and the neuroactive ligand-receptor interaction as the most central pathway associated with schizophrenia. Further analyses revealed that autistic disorder has the most shared genes with schizophrenia. Moreover, mitogen-activated protein kinase-3 (MAPK3), calcium voltage-gated channel subunit alpha1 C (CACNA1C), solute carrier family 6 member 4 (SLC6A4) and 5-hydroxytryptamine receptor 2A (HTR2A) genes are the most central genes in the pathogenesis of schizophrenia.

SIGNIFICANCE

In addition to summarizing what has been found on schizophrenia-associated genes in an integrative holistic framework, our results may help identify principle schizophrenia-associated cellular and molecular infrastructures, and provide support for further investigation on potential diagnostic and therapeutic biomarkers for schizophrenia.