Pharmacogenomic medicine in autism: challenges and opportunities

Pharmacological treatment in autism: a proposal for guidelines on common co-occurring psychiatric symptoms

BACKGROUND

The prevalence of autism spectrum disorder (ASD) has surged, with an estimated 1 in 36 eight-year-olds in the United States meeting criteria for ASD in 2020. Autistic individuals face elevated rates of co-occurring medical, psychiatric, and behavioral conditions compared to non-autistic individuals. The rising ASD-patient demand is increasingly outpacing the capacity of ASD-specialty clinics, resulting in urgent need for autism-competent providers in general practice settings. This work aims to empower healthcare providers, especially primary care providers (PCPs), with guidelines for the recognition and safe pharmacologic management of common co-occurring psychiatric and behavioral conditions in ASD.

METHODS

Lurie Center for Autism medical providers, who have extensive experience in ASD care, delineated approaches for recognition and pharmacological treatment of sleep disturbances, attention-deficit/hyperactivity disorder (ADHD), anxiety, depression, and irritability tailored to ASD patients. Pharmacological guidelines were iteratively refined until consensus was reached. Treatment differences relative to standard of care (SOC) of non-autistic individuals are noted. Key literature and clinical trial results were reviewed to supplement clinical experience.

RESULTS

The pharmacological treatment pathways reflect how appropriate medication options for ASD patients can depend on many factors unique to the patient and can differ from established non-autistic SOC. Key takeaways include: For sleep disturbances in ASD, initial strategies align with non-autistic SOC, emphasizing sleep hygiene and melatonin use. First-line recommendations for treating ADHD, anxiety, and depression in ASD differ from non-autistic SOC; α2-adrenergic agonists are more suitable than stimulants for some ASD-ADHD patients, buspirone and mirtazapine are preferred to selective serotonin reuptake inhibitors (SSRIs) for anxiety, and duloxetine, mirtazapine, bupropion, and vortioxetine are recommended ahead of SSRIs for depression. Addressing irritability in ASD requires interdisciplinary evaluation of contributing factors, and guanfacine, risperidone, or aripiprazole may be appropriate, depending on severity.

CONCLUSIONS

Recognition and treatment of co-occurring psychiatric and behavioral conditions in autistic patients must account for differences in clinical presentation and medication effectiveness and tolerability. Drawing on evidence-based clinical insights, these guidelines seek to support PCPs in making informed decisions when prescribing medications for ASD patients with co-occurring psychiatric and behavioral conditions, ultimately enhancing access to timely, comprehensive care for all individuals with ASD.

Targeting epigenetic dysregulation in autism spectrum disorders

Autism spectrum disorders (ASD) comprise a range of neurodevelopmental pathologies characterized by deficits in social interaction and repetitive behaviors, collectively affecting almost 1% of the worldwide population. Deciphering the etiology of ASD has proven challenging due to the intricate interplay of genetic and environmental factors and the variety of molecular pathways affected. Epigenomic alterations have emerged as key players in ASD etiology. Their research has led to the identification of biomarkers for diagnosis and pinpointed specific gene targets for therapeutic interventions. This review examines the role of epigenetic alterations, resulting from both genetic and environmental influences, as a central causative factor in ASD, delving into its contribution to pathogenesis and treatment strategies.

Pharmacogenetic Testing in Patients with Autism Spectrum Disorder Evaluated in a Precision Medicine Clinic

OBJECTIVE

This study investigated outcomes of pharmacogenetic testing of youth with autism spectrum disorder (ASD) referred to a precision medicine clinic and explored associations between patient characteristics and pharmacogenomic testing results.

METHODS

Records for patients diagnosed with ASD and subsequently referred to a pediatric hospital's precision medicine clinic between July 1, 2010, and June 30, 2020, were reviewed. Pharmacogenetic testing results were abstracted focusing on CYP2D6 and CYP2C19. In addition, we compiled counts of patients' co-occurring diagnoses, histories of adverse drug reactions (ADRs), previously trialed ineffective medications, and previous psychiatric medication changes. Logistic regression models were fit to examine CYP2C19 and CYP2D6 metabolizer status as functions of patient demographics and prereferral medication histories.

RESULTS

Of 202 patients (mean age = 12.18 yrs), 66% were referred to precision medicine because of poor medication response. Among patients with pharmacogenomic testing results for CYP2D6, 9% were classified as poor metabolizers; among patients with results for CYP2C19, 10% were classified as rapid/ultrarapid metabolizers. Patient demographics and medication response history did not predict pharmacogenomic results. However, the number of co-occurring diagnoses positively predicted the number of nonpsychiatric ADRs and a higher probability of CYP2D6 poor metabolizer status; moreover, nonpsychiatric ADRs positively predicted CYP2C19 rapid/ultrarapid metabolizer status.

CONCLUSION

In one of the largest reported samples of youth with ASD clinically referred for pharmacogenetic testing, we observed high variability in medication response and yield for actionable results. Our findings suggest potential clinical utility for pharmacogenetic testing and introduce possible clinical profiles associated with metabolizer status.

Perceptions of the Professionals and Parents of Children with Autism Spectrum Disorders About Autism Services; A Qualitative Study

In this qualitative study, we aimed to explore the challenges of providing services and supports for children with autism spectrum disorders (ASD) and their families from the perceptions of professionals and parents of children with ASD. We classified the results of the study into three key categories including shortcomings in the management of children with ASD; shortcomings of supportive programs and facilities for children with ASD and their families; and organizational challenges in providing services for these children. We analyzed data using the content analysis method. The results showed that there is a wide range of challenges in providing sufficient and high-quality services for children with ASD and empowerment programs for their parents.

Drug repurposing candidates to treat core symptoms in autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by high heritability and clinical heterogeneity. The main core symptoms are social communication deficits. There are no medications approved for the treatment of these symptoms, and medications used to treat non-specific symptoms have serious side effects. To identify potential drugs for repurposing to effectively treat ASD core symptoms, we studied ASD risk genes within networks of protein-protein interactions of gene products. We first defined an ASD network from network-based analyses, and identified approved drugs known to interact with proteins within this network. Thereafter, we evaluated if these drugs can change ASD-associated gene expression perturbations in genes in the ASD network. This was done by analyses of drug-induced versus ASD-associated gene expression, where opposite gene expression perturbations in drug versus ASD indicate that the drug could counteract ASD-associated perturbations. Four drugs showing significant (p < 0.05) opposite gene expression perturbations in drug versus ASD were identified: Loperamide, bromocriptine, drospirenone, and progesterone. These drugs act on ASD-related biological systems, indicating that these drugs could effectively treat ASD core symptoms. Based on our bioinformatics analyses of ASD genetics, we shortlist potential drug repurposing candidates that warrant clinical translation to treat core symptoms in ASD.

Psychotropic prescribing rates and pharmacogenomic testing implications for autism in the Canadian primary care sentinel surveillance network

OBJECTIVE

To estimate prescribing rates of psychotropic drugs to individuals with autism and the proportion of these individuals who could benefit from pharmacogenetic testing.

METHODS

Prescribing data for 92 psychotropic drugs, including 31 antidepressants, 22 antipsychotics, 14 mood stabilizer/antiepileptics, 17 anxiolytic/hypnotics and eight antiadrenergic/psychostimulant were retrieved from medical records of 787 (613 males) autistic individuals who sought treatment from a primary care office enrolled in the Canadian Primary Care Sentinel Surveillance Network between 2012 and 2014. Each prescribed drug was cross-referenced with pharmacogenomic-based prescribing guidelines published by the Clinical Pharmacogenetics Implementation Consortium, the Dutch Pharmacogenetics Working Group, and the Canadian Pharmacogenomics Network for Drug Safety.

RESULTS

More than half (58%) of the participants were prescribed a psychotropic drug and 37% were prescribed two or more psychotropic drugs concurrently. Among the 83 psychotropic drugs examined, 54 (65%) were prescribed to one or more participants during the study's observation period. The ten most frequently prescribed psychotropics were methylphenidate (16.3%), risperidone (12.8%), lorazepam (12.1%), fluoxetine (7.9%), sertraline (7.1%), quetiapine (6.9%), aripiprazole (6.1%), lisdexamfetamine (5.8%), citalopram (5.6%) and clonazepam (4.8%). Seventeen (32%) of the 54 psychotropic drugs prescribed were linked to a pharmacogenomic-based prescribing guideline, including risperidone, sertraline, aripiprazole and citalopram.

CONCLUSIONS

Our findings suggest primary care providers in Canada prescribe a wide range of psychotropics to their patients with autism, some of which may benefit from the integration of pharmacogenomic information into their treatment planning.

Practitioner's review: medication for children and adolescents with autism spectrum disorder (ASD) and comorbid conditions

Alleviating the multiple problems of children with autism spectrum disorder (ASD) and its comorbid conditions presents major challenges for the affected children, parents, and therapists. Because of a complex psychopathology, structured therapy and parent training are not always sufficient, especially for those patients with intellectual disability (ID) and multiple comorbidities. Moreover, structured therapy is not available for a large number of patients, and pharmacological support is often needed, especially in those children with additional attention deficit/hyperactivity and oppositional defiant, conduct, and sleep disorders.

Identifying Subgroups of Patients With Autism by Gene Expression Profiles Using Machine Learning Algorithms

Objectives: The identification of subgroups of autism spectrum disorder (ASD) may partially remedy the problems of clinical heterogeneity to facilitate the improvement of clinical management. The current study aims to use machine learning algorithms to analyze microarray data to identify clusters with relatively homogeneous clinical features. Methods: The whole-genome gene expression microarray data were used to predict communication quotient (SCQ) scores against all probes to select differential expression regions (DERs). Gene set enrichment analysis was performed for DERs with a fold-change >2 to identify hub pathways that play a role in the severity of social communication deficits inherent to ASD. We then used two machine learning methods, random forest classification (RF) and support vector machine (SVM), to identify two clusters using DERs. Finally, we evaluated how accurately the clusters predicted language impairment. Results: A total of 191 DERs were initially identified, and 54 of them with a fold-change >2 were selected for the pathway analysis. Cholesterol biosynthesis and metabolisms pathways appear to act as hubs that connect other trait-associated pathways to influence the severity of social communication deficits inherent to ASD. Both RF and SVM algorithms can yield a classification accuracy level >90% when all 191 DERs were analyzed. The ASD subtypes defined by the presence of language impairment, a strong indicator for prognosis, can be predicted by transcriptomic profiles associated with social communication deficits and cholesterol biosynthesis and metabolism. Conclusion: The results suggest that both RF and SVM are acceptable options for machine learning algorithms to identify AD subgroups characterized by clinical homogeneity related to prognosis.

Target Genes of Autism Risk Loci in Brain Frontal Cortex

Autism spectrum disorder (ASD) is a complex neuropsychiatric disorder. A number of genetic risk loci have been identified for ASD from genome-wide association studies (GWAS); however, their target genes in relevant tissues and cell types remain to be investigated. The frontal cortex is a key region in the human brain for communication and cognitive function. To identify risk genes contributing to potential dysfunction in the frontal cortex of ASD patients, we took an in silico approach integrating multi-omics data. We first found genes with expression in frontal cortex tissue that correlates with ASD risk loci by leveraging expression quantitative trait loci (eQTLs) information. Among these genes, we then identified 76 genes showing significant differential expression in the frontal cortex between ASD cases and controls in microarray datasets and further replicated four genes with RNA-seq data. Among the ASD GWAS single nucleotide polymorphisms (SNPs) correlating with the 76 genes, 20 overlap with histone marks and 40 are associated with gene methylation level. Thus, through multi-omics data analyses, we identified genes that may work as target genes of ASD risk loci in the brain frontal cortex.

Neonatal Oxytocin Treatment Ameliorates Autistic-Like Behaviors and Oxytocin Deficiency in Valproic Acid-Induced Rat Model of Autism

Autism spectrum disorder (ASD) is characterized by impaired social communication and repetitive/stereotyped behaviors. The neuropeptide oxytocin (OXT) plays a critical role in regulating social behaviors in the central nervous system, as indicated in both human and animal studies. We hypothesized that central OXT deficit is one of causes of etiology of ASD, which may be responsible for the social impairments. To test our hypothesis, central OXT system was examined in valproic acid (VPA)-induced rat model of autism (VPA rat). Our results showed that adolescent VPA rats exhibited a lower level of OXT mRNA and fewer OXT-ir cells in the hypothalamus than control rats. Additionally, OXT concentration in cerebrospinal fluid (CSF) was reduced. The number of OXT-ir cells in the supraoptic nucleus (SON) of neonatal VPA rats was also lower. Autistic-like behaviors were observed in these animals as well. We found that an acute intranasal administration of exogenous OXT restored the social preference of adolescent VPA rats. Additionally, early postnatal OXT treatment had long-term effects ameliorating the social impairments and repetitive behaviors of VPA rats until adolescence. This was accompanied by an increase in OXT-ir cells. Taken together, we demonstrated there was central OXT deficiency in the VPA-induced rat model of autism, and showed evidence that early postnatal OXT treatment had a long-term therapeutic effect on the autistic-like behaviors in VPA rats.

Pharmacogenomic testing: aiding in the management of psychotropic therapy for adolescents with autism spectrum disorders

Adolescents with autism have higher rates of anxiety than the general adolescent population. They often struggle to express psychological symptoms verbally where their symptoms may manifest as withdrawal and agitation. Adolescent patients with autism have higher rates of polypharmacy and high-risk psychiatric medication use (eg, atypical antipsychotics) than other patients with psychiatric illness. Primary care pediatricians are at the front lines of psychiatric management for patients with autism. Yet, they have inadequate access to pediatric psychiatry for complex medication management. Pharmacogenomic testing can provide personalized drug metabolism profiles for a majority of psychotropic medications. Primary care based pharmacogenomic testing for adolescents with autism on one or more psychiatric medications may help individualize and optimize complex medication regimens, while promoting drug safety.

A de novo splice site mutation in EHMT1 resulting in Kleefstra syndrome with pharmacogenomics screening and behavior therapy for regressive behaviors

Background

Kleefstra syndrome (KS) is a rare autosomal dominant developmental disability, caused by microdeletions or intragenic mutations within the epigenetic regulator gene EHMT1 (euchromatic histone lysine N‐methyltransferase 1). In addition to common features of autism, young adult regressive behaviors have been reported. However, the genetic downstream effects of the reported deletions or mutations on KS phenotype have not yet been completely explored. While genetic backgrounds affecting drug metabolism can have a profound effect on therapeutic interventions, pharmacogenomic variations are seldom considered in directing psychotropic therapies.

Methods

In this report, we used next‐generation sequencing (exome sequencing and high‐throughput RNA sequencing) in a patient and his parents to identify causative genetic variants followed by pharmacogenomics‐guided clinical decision‐making for making positive changes toward his treatment strategies. The patient had an early autism diagnosis and showed significant regressive behaviors and physical aberrations at age 23.

Results

Exome sequencing identified a novel, de novo splice site variant NM_024757.4: c.2750‐1G>T in EHMT1, a candidate gene for Kleefstra syndrome, in the patient that results in exon skipping and downstream frameshift and termination. Gene expression results from the patient showed, when compared to his parents, there was a significant decreased expression of several reported gene variants associated with autism risk. Further, using a pharmacogenomics genotyping panel, we discovered that the patient had the CYP2D6 nonfunctioning variant genotype *4/*4 that results in very low metabolic activity on a number of psychotropic drugs, including fluvoxamine which he was prescribed. As reported here, a change in psychotropic drugs and intense behavior therapies resulted in a significant reversal of the regressive behaviors and physical aberrations.

Conclusion

These results demonstrate an individualized approach that integrated genetic information and behavior therapies, resulting in a dramatic improvement in regressive behaviors associated with KS.

Pharmacogenomic Study Reveals New Variants of Drug Metabolizing Enzyme and Transporter Genes Associated with Steady-State Plasma Concentrations of Risperidone and 9-Hydroxyrisperidone in Thai Autism Spectrum Disorder Patients

The present study sought to investigate the genetic variants in drug metabolizing enzyme and transporter (DMET) genes associated with steady-state plasma concentrations of risperidone among Thai autism spectrum disorder (ASD) patients. ASD patients taking risperidone for at least 1 month were enrolled for this pharmacogenomic study. Genotyping profile was obtained using Affymetrix DMET Plus array interrogating 1931 variants in 231 genes. Steady-state plasma risperidone and 9-hydroxyrisperidone were measured using liquid chromatography/tandem mass spectrometry assay. The final analysis included 483 markers for 167 genes. Six variants, ABCB11 (c.3084A > G, c.^∗420A > G, c.^∗368G > A, and c.^∗236G > A) and ADH7 (c.690G > A and c.-5360G > A), were found to be associated with plasma concentrations of risperidone. 9-Hydroxyrisperidone and the total active-moiety levels were associated with six gene variants, SCLO1B1 (c.-11187G > A and c.521T > C), SLCO1B3 (c.334G > T, c.699A > G, and c.1557G > A), and SLC7A5 c.^∗438C > G. Polymorphisms in UGT2B4 c.^∗448A > G and CYP2D6 (c.1661G > C, c.4180G > C, and c.-2178G > A) showed considerable but not significant associations with metabolic ratio. This pharmacogenomic study identifies new genetic variants of DMET genes in monitoring risperidone therapy.

The Macaque Social Responsiveness Scale (mSRS): A Rapid Screening Tool for Assessing Variability in the Social Responsiveness of Rhesus Monkeys (Macaca mulatta)

Understanding the biological mechanisms underlying human neuropsychiatric disorders, such as autism spectrum disorder (ASD), has been hindered by the lack of a robust, translational animal model. Rhesus monkeys (Macaca mulatta) display many of the same social behaviors that are affected in ASD, making them an excellent animal species in which to model social impairments. However, the social impairments associated with ASD may reflect extreme ends of a continuous distribution of traits. Thus, to validate the rhesus monkey as an animal model for studying social impairments that has strong translational relevance for ASD, researchers need an easily-implemented measurement tool that can quantify variation in social behavior dimensionally. The Social Responsiveness Scale (SRS) is a 65-item survey that identifies both typical and atypical social behaviors in humans that covary with ASD symptom severity. A chimpanzee SRS has already been validated and the current study adapted this tool for use in the rhesus monkey (mSRS). Fifteen raters completed the mSRS for 105 rhesus monkeys living at the Yerkes National Primate Research Center. The mSRS scores showed a unimodal distribution with a positive skew that identified 6 statistical outliers. Inter-rater reliability was very strong, but only 17 of the 36 questions showed positive intra-item reliability. The results of an exploratory factor analysis identified 3 factors that explained over 60% of the variance, with 12 items significantly loading onto the primary factor. These items reflected behaviors associated with social avoidance, social anxiety or inflexibility and social confidence. These initial findings are encouraging and suggest that variability in the social responsiveness of rhesus monkeys can be quantified using the mSRS: a tool that has strong translational relevance for human disorders. With further modification, the mSRS may provide an promising new direction for research on the biological mechanisms underlying social impairments.

Risk factors in autism: Thinking outside the brain

Autism spectrum disorders (ASD) are complex neurodevelopmental conditions that have been rising markedly in prevalence for the past 30 years, now thought to affect 1 in 68 in the United States. This has prompted the search for possible explanations, and has even resulted in some controversy regarding the "true" prevalence of autism. ASD are influenced by a variety of genetic, environmental, and possibly immunological factors that act during critical periods to alter key developmental processes. This can affect multiple systems and manifests as the social and behavioral deficits that define these disorders. The interaction of environmental exposures in the context of an individual's genetic susceptibilities manifests differently in each case, leading to heterogeneous phenotypes and varied comorbid symptoms within the disorder. This has also made it very difficult to elucidate underlying genes and exposure profiles, but progress is being made in this area. Some pharmaceutical drugs, toxicants, and metabolic and nutritional factors have been identified in epidemiological studies as increasing autism risk, especially during the prenatal period. Immunologic risk factors, including maternal infection during pregnancy, autoantibodies to fetal brain proteins, and familial autoimmune disease, have consistently been observed across multiple studies, as have immune abnormalities in individuals with ASD. Mechanistic research using animal models and patient-derived stem cells will help researchers to understand the complex etiology of these neurodevelopmental disorders, which will lead to more effective therapies and preventative strategies. Proposed therapies that need more investigation include special diets, probiotics, immune modulation, oxytocin, and personalized pharmacogenomic targets. The ongoing search for biomarkers and better treatments will result in earlier identification of ASD and provide much needed help and relief for afflicted families.