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Key Points A rapidly growing list of rare genetic causes of autism spectrum disorders (ASDs) is being identified, giving insights into the underlying biology of these disorders. Contrary to what is generally assumed, existing genetic findings are already able to inform our current clinical practice. Genetic findings have great potential to improve the quality of health care provided to individuals with an ASD and to improve their quality of life. However, several initiatives are needed to support the translation of this knowledge into health care. It is important to promote the education of the relevant health care professionals about clinical genetic testing and its possible benefits. We must also adopt a broader view of ASDs that recognizes psychiatric and somatic comorbidity. The field would benefit greatly from unprecedented global cooperation to improve sharing of genotype–phenotype data from cross-sectional and longitudinal studies. Furthermore, researchers and clinicians must work in partnership with the autism community regarding the genetics and health care research agenda. Finally, genetic information should be used to develop future treatments and interventions for psychiatric and somatic comorbidity, and should be evaluated in clinical trials. The question is not so much when ASD genetics will start to influence our clinical practice but rather how we can optimally use the knowledge that we already have and what is required to use its full clinical potential in the future. Various large studies have provided unprecedented insights into the genetics of autism spectrum disorders (ASDs). This Review discusses the challenges and opportunities of translating genetic and biological insights into clinical progress for ASDs, in areas including genetic testing, ASD classification, genetic counselling, comorbidities and therapeutics. Genetic studies have revealed the involvement of hundreds of gene variants in autism. Their risk effects are highly variable, and they are frequently related to other conditions besides autism. However, many different variants converge on common biological pathways. These findings indicate that aetiological heterogeneity, variable penetrance and genetic pleiotropy are pervasive characteristics of autism genetics. Although this advancing insight should improve clinical care, at present there is a substantial discrepancy between research knowledge and its clinical application. In this Review, we discuss the current challenges and opportunities for the translation of autism genetics knowledge into clinical practice.

Early diagnostic assessments of neurodivergent disorders (NDD), remains a major clinical challenge. We address this problem by pursuing the hypothesis that there is important cognitive information about NDD conditions contained in the way individuals move, when viewed at millisecond time scales. We approach the NDD assessment problem in two complementary ways. First, we applied supervised deep learning (DL) techniques to identify participants with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), comorbid ASD + ADHD, and neurotypical (NT) development. We measured linear and angular kinematic variables, using high-definition kinematic Bluetooth sensors, while participants performed the reaching protocol to targets appearing on a touch screen monitor. The DL technique was carried out only on the raw kinematic data. The area under the receiver operator characteristics curve suggests that we can predict, with high accuracy, NDD participant’s conditions. Second, we filtered the high frequency electronic sensor noise in the recorded kinematic data leaving the participants’ physiological characteristic random fluctuations. We quantified these fluctuations by their biometric Fano Factor and Shannon Entropy from a histogram distribution built from the magnitude difference between consecutive extrema unique to each participant, suggesting a relationship to the severity of their condition. The DL may be used as complementary tools for early evaluation of new participants by providers and the new biometrics allow for quantitative subtyping of NDDs according to severity.

The National Institute of Mental Health (NIMH) ‘fast-fail’ approach seeks to improve too-often-misleading early-phase drug development methods by incorporating biomarker-based proof-of-mechanism (POM) testing in phase 2a. This first comprehensive application of the fast-fail approach evaluated the potential of κ-opioid receptor (KOR) antagonism for treating anhedonia with a POM study determining whether robust target engagement favorably impacts the brain circuitry hypothesized to mediate clinical effects. Here we report the results from a multicenter, 8-week, double-blind, placebo-controlled, randomized trial in patients with anhedonia and a mood or anxiety disorder (selective KOR antagonist (JNJ-67953964, 10 mg; n  = 45) and placebo ( n  = 44)). JNJ-67953964 significantly increased functional magnetic resonance imaging (fMRI) ventral striatum activation during reward anticipation (primary outcome) as compared to placebo (baseline-adjusted mean: JNJ-67953964, 0.72 (s.d. = 0.67); placebo, 0.33 (s.d. = 0.68); F (1,86) = 5.58, P  < 0.01; effect size = 0.58 (95% confidence interval, 0.13–0.99)). JNJ-67953964, generally well tolerated, was not associated with any serious adverse events. This study supports proceeding with assessment of the clinical impact of target engagement and serves as a model for implementing the ‘fast-fail’ approach. A phase 2 proof-of-mechanism trial shows that a κ-opioid receptor antagonist improves reward-related functioning in the brain and a clinical measure of anhedonia in patients with mood and anxiety disorders, serving as a model for implementing the ‘fast-fail’ approach to psychiatric treatment development.

Recent genome-wide association studies (GWAS) have identified genetic markers of post-traumatic stress disorder (PTSD) in civilian and military populations. However, studies have yet to examine the genetics of PTSD while factoring in risk for alcohol dependence, which commonly co-occur. We examined genome-wide associations for DSM-IV PTSD among 4,978 trauma-exposed participants (31% with alcohol dependence, 50% female, 30% African ancestry) from the Collaborative Study on the Genetics of Alcoholism (COGA). We also examined associations of polygenic risk scores (PRS) derived from the Psychiatric Genomics Consortium (PGC)-PTSD Freeze 2 ( N  = 3533) and Million Veterans Program GWAS of PTSD ( N  = 5200) with PTSD and substance dependence in COGA, and moderating effects of sex and alcohol dependence. 7.3% of COGA participants met criteria for PTSD, with higher rates in females (10.1%) and those with alcohol dependence (12.3%). No independent loci met genome-wide significance in the PTSD meta-analysis of European (EA) and African ancestry (AA) participants. The PGC-PTSD PRS was associated with increased risk for PTSD ( B  = 0.126, p  < 0.001), alcohol dependence ( B  = 0.231, p  < 0.001), and cocaine dependence ( B  = 0.086, p  < 0.01) in EA individuals. A significant interaction was observed, such that EA individuals with alcohol dependence and higher polygenic risk for PTSD were more likely to have PTSD ( B  = 0.090, p  < 0.01) than those without alcohol dependence. These results further support the importance of examining substance dependence, specifically alcohol dependence, and PTSD together when investigating genetic influence on these disorders.

Excessive alcohol consumption is one of the leading causes of preventable death in the United States. Approximately 14% of those who use alcohol meet criteria during their lifetime for alcohol dependence, which is characterized by tolerance, withdrawal, inability to stop drinking, and continued drinking despite serious psychological or physiological problems. We explored genetic influences on alcohol dependence among 1,897 European-American and African-American subjects with alcohol dependence compared with 1,932 unrelated, alcohol-exposed, nondependent controls. Constitutional DNA of each subject was genotyped using the Illumina 1M beadchip. Fifteen SNPs yielded P < 10⁻⁵, but in two independent replication series, no SNP passed a replication threshold of P < 0.05. Candidate gene GABRA2, which encodes the GABA receptor α2 subunit, was evaluated independently. Five SNPs at GABRA2 yielded nominal (uncorrected) P < 0.05, with odds ratios between 1.11 and 1.16. Further dissection of the alcoholism phenotype, to disentangle the influence of comorbid substance-use disorders, will be a next step in identifying genetic variants associated with alcohol dependence.

Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia. We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33 332 cases and 27 888 controls of European ancestory. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples. SNPs at four loci surpassed the cutoff for genome-wide significance (p<5×10−8) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers. Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause. National Institute of Mental Health.

Anhedonia remains a major clinical issue for which there is few effective interventions. Untreated or poorly controlled anhedonia has been linked to worse disease course and increased suicidal behavior across disorders. Taking a proof-of-mechanism approach under the auspices of the National Institute of Mental Health FAST-FAIL initiative, we were the first to show that, in a transdiagnostic sample screened for elevated self-reported anhedonia, 8 weeks of treatment with a kappa-opioid receptor (KOR) antagonist resulted in significantly higher reward-related activation in one of the core hubs of the brain reward system (the ventral striatum), better reward learning in the Probabilistic Reward Task (PRT), and lower anhedonic symptoms, relative to 8 weeks of placebo. Here, we performed secondary analyses of the PRT data to investigate the putative effects of KOR antagonism on anhedonic behavior with more precision by using trial-level model-based Bayesian computational modeling and probability analyses. We found that, relative to placebo, KOR antagonism resulted in significantly higher learning rate (i.e., ability to learn from reward feedback) and a more sustained preference toward the more frequently rewarded stimulus, but unaltered reward sensitivity (i.e., the hedonic response to reward feedback). Collectively, these findings provide novel evidence that in a transdiagnostic sample characterized by elevated anhedonia, KOR antagonism improved the ability to modulate behavior as a function of prior rewards. Together with confirmation of target engagement in the primary report (Krystal et al., Nat Med, 2020), the current findings suggest that further transdiagnostic investigation of KOR antagonism for anhedonia is warranted.

Contemporary genome-wide association study (GWAS) methods typically do not account for variability in genetic effects throughout development. We applied genomic structural equation modeling to combine developmentally-informative phenotype data and GWAS to create polygenic scores (PGS) for alcohol use frequency that are specific to developmental stage. Longitudinal cohort studies targeted for gene-identification analyses include the Collaborative Study on the Genetics of Alcoholism (adolescence n = 1,118, early adulthood n = 2,762, adulthood n = 5,255), the National Longitudinal Study of Adolescent to Adult Health (adolescence n = 3,089, early adulthood n = 3,993, adulthood n = 5,149), and the Avon Longitudinal Study of Parents and Children (ALSPAC; adolescence n = 5,382, early adulthood n = 3,613). PGS validation analyses were conducted in the COGA sample using an alternate version of the discovery analysis with COGA removed. Results suggest that genetic liability for alcohol use frequency in adolescence may be distinct from genetic liability for alcohol use frequency later in developmental periods. The age-specific PGS predicts an increase of 4 drinking days per year per PGS standard deviation when modeled separately from the common factor PGS in adulthood. The current work was underpowered at all steps of the analysis plan. Though small sample sizes and low statistical power limit the substantive conclusions that can be drawn regarding these research questions, this work provides a foundation for future genetic studies of developmental variability in the genetic underpinnings of alcohol use behaviors and genetically-informed, age-matched phenotype prediction.

Genome-wide association studies (GWAS) in admixed populations such as African Americans (AA) have limited sample sizes, resulting in poor performance of polygenic risk scores (PRS). Based on the observations that many disease-causing genes are shared between AA and European ancestry (EA) populations, and some disease-causing variants are located within the boundaries of these genes, we proposed a novel gene-based PRS framework (PRS gene ) by using variants located within disease-associated genes. Using the AA GWAS of alcohol use disorder (AUD) from the Million Veteran Program and the EA GWAS of problematic alcohol use as the discovery GWAS, we identified 858 variants from 410 genes that were AUD-related in both AA and EA. PRS gene calculated using these variants were significantly associated with AUD in three AA target datasets ( P -values ranged from 7.61E−05 to 6.27E−03; Betas ranged from 0.15 to 0.21) and outperformed PRS calculated using all variants ( P -values ranged from 7.28E−03 to 0.16; Betas ranged from 0.06 to 0.18). PRS gene were also associated with AUD in an EA target dataset ( P -value = 0.02, Beta = 0.11). In AA, individuals in the highest PRS gene decile had an odds ratio of 1.76 (95% CI: 1.32–2.34) to develop AUD compared to those in the lowest decile. The 410 genes were enriched in 54 Gene Ontology biological processes, including ethanol oxidation and processes involving the synaptic system, which are known to be AUD-related. In addition, 26 genes were targets of drugs used to treat AUD or other diseases that might be considered for repurposing to treat AUD. Our study demonstrated that the gene-based PRS had improved performance in evaluating AUD risk in AA and provided new insight into AUD genetics.