A framework for the investigation of rare genetic disorders in neuropsychiatry

Methods for Neuroscience Drug Development: Guidance on Standardization of the Process for Defining Clinical Outcome Strategies in Clinical Trials

Neurosciences clinical trials continue to have notoriously high failure rates. Appropriate outcomes selection in early clinical trials is key to maximizing the likelihood of identifying new treatments in psychiatry and neurology. The field lacks good standards for designing outcome strategies, therefore The Outcomes Research Group was formed to develop and promote good practices in outcome selection. This article describes the first published guidance on the standardization of the process for clinical outcomes in neuroscience. A minimal step process is defined starting as early as possible, covering key activities for evidence generation in support of content validity, patient-centricity, validity requirements and considerations for regulatory acceptance. Feedback from expert members is provided, regarding the risks of shortening the process and examples supporting the recommended process are summarized. This methodology is now available to researchers in industry, academia or clinics aiming to implement consensus-based standard practices for clinical outcome selection, contributing to maximizing the efficiency of clinical research.

Functional neurogenomics in autism spectrum disorders: A decade of progress

Advances in autism spectrum disorder (ASD) genetics have identified many genetic causes, reflecting remarkable progress while at the same time identifying challenges such as heterogeneity and pleiotropy, which complicate attempts to connect genetic risk to mechanisms. High-throughput functional genomic approaches have yielded progress by defining a molecular pathology in the brain of individuals with ASD and in identifying convergent biological pathways through which risk genes are predicted to act. These studies indicate that ASD genetic risk converges in early brain development, primarily during the period of cortical neurogenesis. Over development, genetic perturbations in turn lead to broad neuronal signaling dysregulation, most prominent in glutamatergic cortical-cortical projecting neurons and somatostatin positive interneurons, which is accompanied by glial dyshomeostasis throughout the cerebral cortex. Connecting these developmental perturbations to disrupted neuronal and glial function in the postnatal brain is an important direction in current research. Coupling functional genomic approaches with advances in induced pluripotent stem cell-derived neural organoid development provides a promising avenue for connecting brain pathology to developmental mechanisms.

X-chromosome inactivation in human iPSCs provides insight into X-regulated gene expression in autosomes

BACKGROUND

Variation in X chromosome inactivation (XCI) in human-induced pluripotent stem cells (hiPSCs) can impact their ability to model biological sex biases. The gene-wise landscape of X chromosome gene dosage remains unresolved in female hiPSCs. To characterize patterns of de-repression and escape from inactivation, we performed a systematic survey of allele specific expression in 165 female hiPSC lines.

RESULTS

XCI erosion is non-random and primarily affects genes that escape XCI in human tissues. Individual genes and cell lines vary in the frequency and degree of de-repression. Bi-allelic expression increases gradually after modest decrease of XIST in cultures, whose loss is commonly used to mark lines with eroded XCI. We identify three clusters of female lines at different stages of XCI. Increased XCI erosion amplifies female-biased expression at hypomethylated sites and regions normally occupied by repressive histone marks, lowering male-biased differences in the X chromosome. In autosomes, erosion modifies sex differences in a dose-dependent way. Male-biased genes are enriched for hypermethylated regions, and de-repression of XIST-bound autosomal genes in female lines attenuates normal male-biased gene expression in eroded lines. XCI erosion can compensate for a dominant loss of function effect in several disease genes.

CONCLUSIONS

We present a comprehensive view of X chromosome gene dosage in hiPSCs and implicate a direct mechanism for XCI erosion in regulating autosomal gene expression in trans. The uncommon and variable reactivation of X chromosome genes in female hiPSCs can provide insight into X chromosome's role in regulating gene expression and sex differences in humans.

Deep exome sequencing identifies enrichment of deleterious mosaic variants in neurodevelopmental disorder genes and mitochondrial tRNA regions in bipolar disorder

Bipolar disorder (BD) is a global medical issue, afflicting around 1% of the population with manic and depressive episodes. Despite various genetic studies, the genetic architecture and pathogenesis of BD have not been fully resolved. Besides germline variants, postzygotic mosaic variants are proposed as new candidate mechanisms contributing to BD. Here, we performed extensive deep exome sequencing (DES, ~300×) and validation experiments to investigate the roles of mosaic variants in BD with 235 BD cases (194 probands of trios and 41 single cases) and 39 controls. We found an enrichment of developmental disorder (DD) genes in the genes hit by deleterious mosaic variants in BD (P = 0.000552), including a ClinVar-registered pathogenic variant in ARID2. An enrichment of deleterious mosaic variants was also observed for autism spectrum disorder (ASD) genes (P = 0.000428). The proteins coded by the DD/ASD genes with non-synonymous mosaic variants in BD form more protein-protein interaction than expected, suggesting molecular mechanisms shared with DD/ASD but restricted to a subset of cells in BD. We also found significant enrichment of mitochondrial heteroplasmic variants, another class of mosaic variants, in mitochondrial tRNA genes in BD (P = 0.0102). Among them, recurrent m.3243 A > G variants known as causal for mitochondrial diseases were found in two unrelated BD probands with allele fractions of 5-12%, lower than in mitochondrial diseases. Despite the limitation of using peripheral tissues, our DES investigation supports the possible contribution of deleterious mosaic variants in the nuclear genome responsible for severer phenotypes, such as DD/ASD, to the risk of BD and further demonstrates that the same paradigm can be applied to the mitochondrial genome. These results, as well as the enrichment of heteroplasmic mitochondrial tRNA variants in BD, add a new piece to the understanding of the genetic architecture of BD and provide general insights into the pathological roles of mosaic variants in human diseases.

Unraveling the Multifaceted Role of the Golgi Apparatus: Insights into Neuronal Plasticity, Development, Neurogenesis, Alzheimer's Disease, and SARS-CoV-2 Interactions

This article critically evaluates the multifunctional role of the Golgi apparatus within neurological paradigms. We succinctly highlight its influence on neuronal plasticity, development, and the vital trafficking and sorting mechanisms for proteins and lipids. The discourse further navigates to its regulatory prominence in neurogenesis and its implications in Alzheimer's Disease pathogenesis. The emerging nexus between the Golgi apparatus and SARS-CoV-2 underscores its potential in viral replication processes. This consolidation accentuates the Golgi apparatus's centrality in neurobiology and its intersections with both neurodegenerative and viral pathologies. In essence, understanding the Golgi's multifaceted functions harbors profound implications for future therapeutic innovations in neurological and viral afflictions.

Subcortical Brain Alterations in Carriers of Genomic Copy Number Variants

OBJECTIVE

Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs), including autism (ASD) and schizophrenia. Little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, the authors investigated gross volume, vertex-level thickness, and surface maps of subcortical structures in 11 CNVs and six NPDs.

METHODS

Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (CNVs at 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2; age range, 6-80 years; 340 males) and 782 control subjects (age range, 6-80 years; 387 males) as well as ENIGMA summary statistics for ASD, schizophrenia, attention deficit hyperactivity disorder, obsessive-compulsive disorder, bipolar disorder, and major depression.

RESULTS

All CNVs showed alterations in at least one subcortical measure. Each structure was affected by at least two CNVs, and the hippocampus and amygdala were affected by five. Shape analyses detected subregional alterations that were averaged out in volume analyses. A common latent dimension was identified, characterized by opposing effects on the hippocampus/amygdala and putamen/pallidum, across CNVs and across NPDs. Effect sizes of CNVs on subcortical volume, thickness, and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and schizophrenia.

CONCLUSIONS

The findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions, as well distinct effects, with some CNVs clustering with adult-onset conditions and others with ASD. These findings provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD and why a single CNV increases the risk for a diverse set of NPDs.

Functional Characterization of MC4R Variants in Chinese Morbid Obese Patients and Weight Loss after Bariatric Surgery

Mutations in MC4R are the most common genetic cause of obesity. In the reported Chinese morbid obesity cohort, 10 out of 59 harbor six MC4R variants, including Y35C, T53I, V103I, R165W, G233S, and C277X, among which V103I has a relatively high frequency, while other five variants are rare in the population. The prevalence of MC4R carriers in Chinese morbid obese patients (body mass index ≥ 45 kg m-2 ) is detected as 16.9% in this study. R165W and C277X are loss-of-function variants. The patient with R165W achieves excess weight loss (%EWL) as high as 20.6% and 50.3% at 1 and 8 months after surgery, respectively. G233S is reported for the first time in Asia obese population. The patient harboring G233S has a %EWL as 23.3% one month postsurgery. It is concluded that morbid obese patients with rare MC4R variants can benefit from metabolic surgery. More importantly, the choice of surgery procedure and MC4R variant should be taken into consideration for personalized treatment. In the future, a larger size cohort, accompanied with regular and longer follow-up, would be helpful.

X- vs. Y-Chromosome Influences on Human Behavior: A Deep Phenotypic Comparison of Psychopathology in XXY and XYY Syndromes

Do different genetic disorders impart different psychiatric risk profiles? This question has major implications for biological and translational aspects of psychiatry, but has been difficult to tackle given limited access to shared batteries of fine-grained clinical data across genetic disorders. Using a new suite of generalizable analytic approaches, we examine gold-standard diagnostic ratings, scores on 66 dimensional measures of psychopathology, and measures of cognition and functioning in two different sex chromosome aneuploidies (SCAs) - Klinefelter (XXY/KS) and XYY syndrome (n=102 and 64 vs. n=74 and 60 matched XY controls, total n=300). We focus on SCAs for their high collective prevalence, informativeness regarding differential X- vs. Y-chromosome effects, and potential relevance for normative sex differences. We show that XXY/KS elevates rates for most psychiatric diagnoses as previously reported for XYY, but disproportionately so for anxiety disorders. Fine-mapping across all 66 traits provides a detailed profile of psychopathology in XXY/KS which is strongly correlated with that of XYY (r=.75 across traits) and robust to ascertainment biases, but reveals: (i) a greater penetrance of XYY than KS/XXY for most traits except mood/anxiety problems, and (ii) a disproportionate impact of XYY vs. XXY/KS on social problems. XXY/KS and XXY showed a similar coupling of psychopathology with adaptive function and caregiver strain, but not IQ. This work provides new tools for deep-phenotypic comparisons of genetic disorders in psychiatry and uses these to detail unique and shared effects of the X- and Y-chromosome on human behavior.

Rare CNVs and phenome-wide profiling highlight brain structural divergence and phenotypical convergence

Copy number variations (CNVs) are rare genomic deletions and duplications that can affect brain and behaviour. Previous reports of CNV pleiotropy imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, existing studies have primarily examined single CNV loci in small clinical cohorts. It remains unknown, for example, how distinct CNVs escalate vulnerability for the same developmental and psychiatric disorders. Here we quantitatively dissect the associations between brain organization and behavioural differentiation across 8 key CNVs. In 534 CNV carriers, we explored CNV-specific brain morphology patterns. CNVs were characteristic of disparate morphological changes involving multiple large-scale networks. We extensively annotated these CNV-associated patterns with ~1,000 lifestyle indicators through the UK Biobank resource. The resulting phenotypic profiles largely overlap and have body-wide implications, including the cardiovascular, endocrine, skeletal and nervous systems. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.

Characterization of Gene Regulatory Elements in Human Fetal Cortical Development: Enhancing Our Understanding of Neurodevelopmental Disorders and Evolution

The neocortex is the region that most distinguishes human brain from other mammals and primates [Annu Rev Genet. 2021 Nov;55(1):555-81]. Studying the development of human cortex is important in understanding the evolutionary changes occurring in humans relative to other primates, as well as in elucidating mechanisms underlying neurodevelopmental disorders. Cortical development is a highly regulated process, spatially and temporally coordinated by expression of essential transcriptional factors in response to signaling pathways [Neuron. 2019 Sep;103(6):980-1004]. Enhancers are the most well-understood cis-acting, non-protein-coding regulatory elements that regulate gene expression [Nat Rev Genet. 2014 Apr;15(4):272-86]. Importantly, given the conservation of both DNA sequence and molecular function of the majority of proteins across mammals [Genome Res. 2003 Dec;13(12):2507-18], enhancers [Science. 2015 Mar;347(6226):1155-9], which are far more divergent at the sequence level, likely account for the phenotypes that distinguish the human brain by changing the regulation of gene expression. In this review, we will revisit the conceptual framework of gene regulation during human brain development, as well as the evolution of technologies to study transcriptional regulation, with recent advances in genome biology that open a window allowing us to systematically characterize cis-regulatory elements in developing human brain [Hum Mol Genet. 2022 Oct;31(R1):R84-96]. We provide an update on work to characterize the suite of all enhancers in the developing human brain and the implications for understanding neuropsychiatric disorders. Finally, we discuss emerging therapeutic ideas that utilize our emerging knowledge of enhancer function.

Multimodal charting of molecular and functional cell states via in situ electro-sequencing

Paired mapping of single-cell gene expression and electrophysiology is essential to understand gene-to-function relationships in electrogenic tissues. Here, we developed in situ electro-sequencing (electro-seq) that combines flexible bioelectronics with in situ RNA sequencing to stably map millisecond-timescale electrical activity and profile single-cell gene expression from the same cells across intact biological networks, including cardiac and neural patches. When applied to human-induced pluripotent stem-cell-derived cardiomyocyte patches, in situ electro-seq enabled multimodal in situ analysis of cardiomyocyte electrophysiology and gene expression at the cellular level, jointly defining cell states and developmental trajectories. Using machine-learning-based cross-modal analysis, in situ electro-seq identified gene-to-electrophysiology relationships throughout cardiomyocyte development and accurately reconstructed the evolution of gene expression profiles based on long-term stable electrical measurements. In situ electro-seq could be applicable to create spatiotemporal multimodal maps in electrogenic tissues, potentiating the discovery of cell types and gene programs responsible for electrophysiological function and dysfunction.

Genesis, modelling and methodological remedies to autism heterogeneity

Diagnostic criteria used in autism research have undergone a shift towards the inclusion of a larger population, paralleled by increasing, but variable, estimates of autism prevalence across clinical settings and continents. A categorical diagnosis of autism spectrum disorder is now consistent with large variations in language, intelligence, comorbidity, and severity, leading to a heterogeneous sample of individuals, increasingly distant from the initial prototypical descriptions. We review the history of autism diagnosis and subtyping, and the evidence of heterogeneity in autism at the cognitive, neurological, and genetic levels. We describe two strategies to address the problem of heterogeneity: clustering, and truncated-compartmentalized enrollment strategy based on prototype recognition. The advances made using clustering methods have been modest. We present an alternative, new strategy for dissecting autism heterogeneity, emphasizing incorporation of prototypical samples in research cohorts, comparison of subgroups defined by specific ranges of values for the clinical specifiers, and retesting the generality of neurobiological results considered to be acquired from the entire autism spectrum on prototypical cohorts defined by narrow specifiers values.

Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder

The mechanisms underlying phenotypic heterogeneity in autism spectrum disorder (ASD) are not well understood. Using a large neuroimaging dataset, we identified three latent dimensions of functional brain network connectivity that predicted individual differences in ASD behaviors and were stable in cross-validation. Clustering along these three dimensions revealed four reproducible ASD subgroups with distinct functional connectivity alterations in ASD-related networks and clinical symptom profiles that were reproducible in an independent sample. By integrating neuroimaging data with normative gene expression data from two independent transcriptomic atlases, we found that within each subgroup, ASD-related functional connectivity was explained by regional differences in the expression of distinct ASD-related gene sets. These gene sets were differentially associated with distinct molecular signaling pathways involving immune and synapse function, G-protein-coupled receptor signaling, protein synthesis and other processes. Collectively, our findings delineate atypical connectivity patterns underlying different forms of ASD that implicate distinct molecular signaling mechanisms.

Structured tracking of alcohol reinforcement (STAR) for basic and translational alcohol research

There is inherent tension between methodologies developed to address basic research questions in model species and those intended for preclinical to clinical translation: basic investigations require flexibility of experimental design as hypotheses are rapidly tested and revised, whereas preclinical models emphasize standardized protocols and specific outcome measures. This dichotomy is particularly relevant in alcohol research, which spans a diverse range of basic sciences in addition to intensive efforts towards understanding the pathophysiology of alcohol use disorder (AUD). To advance these goals there is a great need for approaches that facilitate synergy across basic and translational areas of nonhuman alcohol research. In male and female mice, we establish a modular alcohol reinforcement paradigm: Structured Tracking of Alcohol Reinforcement (STAR). STAR provides a robust platform for quantitative assessment of AUD-relevant behavioral domains within a flexible framework that allows direct crosstalk between translational and mechanistically oriented studies. To achieve cross-study integration, despite disparate task parameters, a straightforward multivariate phenotyping analysis is used to classify subjects based on propensity for heightened alcohol consumption and insensitivity to punishment. Combining STAR with extant preclinical alcohol models, we delineate longitudinal phenotype dynamics and reveal putative neuro-biomarkers of heightened alcohol use vulnerability via neurochemical profiling of cortical and brainstem tissues. Together, STAR allows quantification of time-resolved biobehavioral processes essential for basic research questions simultaneous with longitudinal phenotyping of clinically relevant outcomes, thereby providing a framework to facilitate cohesion and translation in alcohol research.

The foundation and architecture of precision medicine in neurology and psychiatry

Neurological and psychiatric diseases have high degrees of genetic and pathophysiological heterogeneity, irrespective of clinical manifestations. Traditional medical paradigms have focused on late-stage syndromic aspects of these diseases, with little consideration of the underlying biology. Advances in disease modeling and methodological design have paved the way for the development of precision medicine (PM), an established concept in oncology with growing attention from other medical specialties. We propose a PM architecture for central nervous system diseases built on four converging pillars: multimodal biomarkers, systems medicine, digital health technologies, and data science. We discuss Alzheimer's disease (AD), an area of significant unmet medical need, as a case-in-point for the proposed framework. AD can be seen as one of the most advanced PM-oriented disease models and as a compelling catalyzer towards PM-oriented neuroscience drug development and advanced healthcare practice.

Subcortical brain alterations in carriers of genomic copy number variants

Objectives

Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs) including autism (ASD) and schizophrenia (SZ). Overall, little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, we investigated gross volume, and vertex level thickness and surface maps of subcortical structures in 11 different CNVs and 6 different NPDs.

Methods

Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (at the following loci: 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2) and 782 controls (Male/Female: 727/730; age-range: 6-80 years) as well as ENIGMA summary-statistics for ASD, SZ, ADHD, Obsessive-Compulsive-Disorder, Bipolar-Disorder, and Major-Depression.

Results

Nine of the 11 CNVs affected volume of at least one subcortical structure. The hippocampus and amygdala were affected by five CNVs. Effect sizes of CNVs on subcortical volume, thickness and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and SZ. Shape analyses were able to identify subregional alterations that were averaged out in volume analyses. We identified a common latent dimension - characterized by opposing effects on basal ganglia and limbic structures - across CNVs and across NPDs.

Conclusion

Our findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions. We also observed distinct effects with some CNVs clustering with adult conditions while others clustered with ASD. This large cross-CNV and NPDs analysis provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD, as well as why a single CNV increases the risk for a diverse set of NPDs.

Deep phenotypic analysis of psychiatric features in genetically defined cohorts: application to XYY syndrome

BACKGROUND

Recurrent gene dosage disorders impart substantial risk for psychopathology. Yet, understanding that risk is hampered by complex presentations that challenge classical diagnostic systems. Here, we present a suite of generalizable analytic approaches for parsing this clinical complexity, which we illustrate through application to XYY syndrome.

METHOD

We gathered high-dimensional measures of psychopathology in 64 XYY individuals and 60 XY controls, plus additional interviewer-based diagnostic data in the XYY group. We provide the first comprehensive diagnostic description of psychiatric morbidity in XYY syndrome and show how diagnostic morbidity relates to functioning, subthreshold symptoms, and ascertainment bias. We then map behavioral vulnerabilities and resilience across 67 behavioral dimensions before borrowing techniques from network science to resolve the mesoscale architecture of these dimensions and links to observable functional outcomes.

RESULTS

Carriage of an extra Y-chromosome increases risk for diverse psychiatric diagnoses, with clinically impactful subthreshold symptomatology. Highest rates are seen for neurodevelopmental and affective disorders. A lower bound of < 25% of carriers are free of any diagnosis. Dimensional analysis of 67 scales details the profile of psychopathology in XYY, which survives control for ascertainment bias, specifies attentional and social domains as the most impacted, and refutes stigmatizing historical associations between XYY and violence. Network modeling compresses all measured symptom scales into 8 modules with dissociable links to cognitive ability, adaptive function, and caregiver strain. Hub modules offer efficient proxies for the full symptom network.

CONCLUSIONS

This study parses the complex behavioral phenotype of XYY syndrome by applying new and generalizable analytic approaches for analysis of deep-phenotypic psychiatric data in neurogenetic disorders.

Relating pathogenic loss-of-function mutations in humans to their evolutionary fitness costs

Causal loss-of-function (LOF) variants for Mendelian and severe complex diseases are enriched in 'mutation intolerant' genes. We show how such observations can be interpreted in light of a model of mutation-selection balance and use the model to relate the pathogenic consequences of LOF mutations at present to their evolutionary fitness effects. To this end, we first infer posterior distributions for the fitness costs of LOF mutations in 17,318 autosomal and 679 X-linked genes from exome sequences in 56,855 individuals. Estimated fitness costs for the loss of a gene copy are typically above 1%; they tend to be largest for X-linked genes, whether or not they have a Y homolog, followed by autosomal genes and genes in the pseudoautosomal region. We compare inferred fitness effects for all possible de novo LOF mutations to those of de novo mutations identified in individuals diagnosed with one of six severe, complex diseases or developmental disorders. Probands carry an excess of mutations with estimated fitness effects above 10%; as we show by simulation, when sampled in the population, such highly deleterious mutations are typically only a couple of generations old. Moreover, the proportion of highly deleterious mutations carried by probands reflects the typical age of onset of the disease. The study design also has a discernible influence: a greater proportion of highly deleterious mutations is detected in pedigree than case-control studies, and for autism, in simplex than multiplex families and in female versus male probands. Thus, anchoring observations in human genetics to a population genetic model allows us to learn about the fitness effects of mutations identified by different mapping strategies and for different traits.

Comparing ability and norm-referenced scores as clinical trial outcomes for neurodevelopmental disabilities: a simulation study

BACKGROUND

For genetic conditions associated with neurodevelopmental disorder (GCAND), developmental domains such as motor ability, thinking and learning, social abilities, and communication are potential intervention targets. Performance on measures of developmental concepts can be expressed using several types of scores. Norm-referenced scores are intended for the diagnostic context, allowing for the identification of impairment relative to age-based expectations, and can exhibit dramatic floor effects when used in individuals with more significant limitations. Person ability scores, which are derived via Rasch analysis or item response theory, are available on many standardized tests and are intended to measure within-person change. However, they have not been used or evaluated as primary endpoints in GCAND clinical trials. In this study, we simulated a series of parallel-arm clinical trials under several chronological age and impairment conditions, to compare empirically the power and type I error rate of operationalizing test performance using ability scores rather than norm-referenced scores.

RESULTS

Using the Vineland Adaptive Behavior Scales as the example, we demonstrated an advantage in statistical power of ability scores over norm-referenced scores at extreme levels of impairment. This advantage was at least partially driven by floor effects in norm-referenced scores. For simulated conditions where impairment was less severe, ability scores outperformed norm-referenced scores, but they were more similar. The type I error rate closely approximated the nominal type I error rate of 5% for both scores.

CONCLUSION

The results of this simulation demonstrate a substantial power and interpretative advantage of ability scores over norm-referenced scores for studies of GCAND that will enroll participants with high levels of impairment. These results are expected to generalize to studies of developmental concepts, regardless of the etiology or specific test. However, the relative advantage of ability scores is expected to be even greater for tests with a higher floor than the Vineland.

A genetics-first approach to understanding autism and schizophrenia spectrum disorders: the 22q11.2 deletion syndrome

Recently, increasing numbers of rare pathogenic genetic variants have been identified that are associated with variably elevated risks of a range of neurodevelopmental outcomes, notably including Autism Spectrum Disorders (ASD), Schizophrenia Spectrum Disorders (SSD), and Intellectual Disability (ID). This review is organized along three main questions: First, how can we unify the exclusively descriptive basis of our current psychiatric diagnostic classification system with the recognition of an identifiable, highly penetrant genetic risk factor in an increasing proportion of patients with ASD or SSD? Second, what can be learned from studies of individuals with ASD or SSD who share a common genetic basis? And third, what accounts for the observed variable penetrance and pleiotropy of neuropsychiatric phenotypes in individuals with the same pathogenic variant? In this review, we focus on findings of clinical and preclinical studies of the 22q11.2 deletion syndrome (22q11DS). This particular variant is not only one of the most common among the increasing list of known rare pathogenic variants, but also one that benefits from a relatively long research history. Consequently, 22q11DS is an appealing model as it allows us to: (1) elucidate specific genotype-phenotype associations, (2) prospectively study behaviorally defined classifications, such as ASD or SSD, in the context of a known, well-characterized genetic basis, and (3) elucidate mechanisms underpinning variable penetrance and pleiotropy, phenomena with far-reaching ramifications for research and clinical practice. We discuss how findings from animal and in vitro studies relate to observations in human studies and can help elucidate factors, including genetic, environmental, and stochastic, that impact the expression of neuropsychiatric phenotypes in 22q11DS, and how this may inform mechanisms underlying neurodevelopmental expression in the general population. We conclude with research priorities for the field, which may pave the way for novel therapeutics.

The molecular basis of p21-activated kinase-associated neurodevelopmental disorders: From genotype to phenotype

Although the identification of numerous genes involved in neurodevelopmental disorders (NDDs) has reshaped our understanding of their etiology, there are still major obstacles in the way of developing therapeutic solutions for intellectual disability (ID) and other NDDs. These include extensive clinical and genetic heterogeneity, rarity of recurrent pathogenic variants, and comorbidity with other psychiatric traits. Moreover, a large intragenic mutational landscape is at play in some NDDs, leading to a broad range of clinical symptoms. Such diversity of symptoms is due to the different effects DNA variations have on protein functions and their impacts on downstream biological processes. The type of functional alterations, such as loss or gain of function, and interference with signaling pathways, has yet to be correlated with clinical symptoms for most genes. This review aims at discussing our current understanding of how the molecular changes of group I p21-activated kinases (PAK1, 2 and 3), which are essential actors of brain development and function; contribute to a broad clinical spectrum of NDDs. Identifying differences in PAK structure, regulation and spatio-temporal expression may help understanding the specific functions of each group I PAK. Deciphering how each variation type affects these parameters will help uncover the mechanisms underlying mutation pathogenicity. This is a prerequisite for the development of personalized therapeutic approaches.

Autism spectrum disorder symptom expression in individuals with 3q29 deletion syndrome

BACKGROUND

The 1.6 Mb 3q29 deletion is associated with neurodevelopmental and neuropsychiatric phenotypes, including a 19-fold increased risk for autism spectrum disorder (ASD). Previous work by our team identified elevated social disability in this population via parent-report questionnaires. However, clinical features of ASD in this population have not been explored in detail.

METHODS

Thirty-one individuals with 3q29 deletion syndrome (3q29del, 61.3% male) were evaluated using two gold-standard clinical ASD evaluations: the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), and the Autism Diagnostic Interview, Revised (ADI-R). Four matched comparators for each subject were ascertained from the National Database for Autism Research. Item-level scores on the ADOS-2 and ADI-R were compared between subjects with 3q29del and matched comparators.

RESULTS

Subjects with 3q29del and no ASD (3q29del-ASD) had greater evidence of social disability compared to typically developing (TD) comparison subjects across the ADOS-2. Subjects with 3q29del and ASD (3q29del + ASD) were largely indistinguishable from non-syndromic ASD (nsASD) subjects on the ADOS-2. 3q29del + ASD performed significantly better on social communication on the ADI-R than nsASD (3q29 + ASD mean = 11.36; nsASD mean = 15.70; p = 0.01), and this was driven by reduced deficits in nonverbal communication (3q29 + ASD mean = 1.73; nsASD mean = 3.63; p = 0.03). 3q29del + ASD reported significantly later age at the first two-word phrase compared to nsASD (3q29del + ASD mean = 43.89 months; nsASD mean = 37.86 months; p = 0.01). However, speech delay was not related to improved nonverbal communication in 3q29del + ASD.

LIMITATIONS

There were not enough TD comparators with ADI-R data in NDAR to include in the present analysis. Additionally, our relatively small sample size made it difficult to assess race and ethnicity effects.

CONCLUSIONS

3q29del is associated with significant social disability, irrespective of ASD diagnosis. 3q29del + ASD have similar levels of social disability to nsASD, while 3q29del-ASD have significantly increased social disability compared to TD individuals. However, social communication is reasonably well preserved in 3q29del + ASD relative to nsASD. It is critical that verbal ability and social disability be examined separately in this population to ensure equal access to ASD and social skills evaluations and services.

Neuroimaging Findings in Neurodevelopmental Copy Number Variants: Identifying Molecular Pathways to Convergent Phenotypes

Genomic copy number variants (CNVs) are associated with a high risk of neurodevelopmental disorders. A growing body of genetic studies suggests that these high-risk genetic variants converge in common molecular pathways and that common pathways also exist across clinically distinct disorders, such as schizophrenia and autism spectrum disorder. A key question is how common molecular mechanisms converge into similar clinical outcomes. We review emerging evidence for convergent cognitive and brain phenotypes across distinct CNVs. Multiple CNVs were shown to have similar effects on core sensory, cognitive, and motor traits. Emerging data from multisite neuroimaging studies have provided valuable information on how these CNVs affect brain structure and function. However, most of these studies examined one CNV at a time, making it difficult to fully understand the proportion of shared brain effects. Recent studies have started to combine neuroimaging data from multiple CNV carriers and identified similar brain effects across CNVs. Some early findings also support convergence in CNV animal models. Systems biology, through integration of multilevel data, provides new insights into convergent molecular mechanisms across genetic risk variants (e.g., altered synaptic activity). However, the link between such key molecular mechanisms and convergent psychiatric phenotypes is still unknown. To better understand this link, we need new approaches that integrate human molecular data with neuroimaging, cognitive, and animal model data, while taking into account critical developmental time points. Identifying risk mechanisms across genetic loci can elucidate the pathophysiology of neurodevelopmental disorders and identify new therapeutic targets for cross-disorder applications.

Rare coding variation provides insight into the genetic architecture and phenotypic context of autism

Some individuals with autism spectrum disorder (ASD) carry functional mutations rarely observed in the general population. We explored the genes disrupted by these variants from joint analysis of protein-truncating variants (PTVs), missense variants and copy number variants (CNVs) in a cohort of 63,237 individuals. We discovered 72 genes associated with ASD at false discovery rate (FDR) ≤ 0.001 (185 at FDR ≤ 0.05). De novo PTVs, damaging missense variants and CNVs represented 57.5%, 21.1% and 8.44% of association evidence, while CNVs conferred greatest relative risk. Meta-analysis with cohorts ascertained for developmental delay (DD) (n = 91,605) yielded 373 genes associated with ASD/DD at FDR ≤ 0.001 (664 at FDR ≤ 0.05), some of which differed in relative frequency of mutation between ASD and DD cohorts. The DD-associated genes were enriched in transcriptomes of progenitor and immature neuronal cells, whereas genes showing stronger evidence in ASD were more enriched in maturing neurons and overlapped with schizophrenia-associated genes, emphasizing that these neuropsychiatric disorders may share common pathways to risk.

Neurodevelopmental copy-number variants: A roadmap to improving outcomes by uniting patient advocates, researchers, and clinicians for collective impact

Copy-number variants and structural variants (CNVs/SVs) drive many neurodevelopmental-related disorders. While many neurodevelopmental-related CNVs/SVs give rise to complex phenotypes, the overlap in phenotypic presentation between independent CNVs can be extensive and provides a motivation for shared approaches. This confluence at the level of clinical phenotype implies convergence in at least some aspects of the underlying genomic mechanisms. With this perspective, our Commission on Novel Technologies for Neurodevelopmental CNVs asserts that the time has arrived to approach neurodevelopmental-related CNVs/SVs as a class of disorders that can be identified, investigated, and treated on the basis of shared mechanisms and/or pathways (e.g., molecular, neurological, or developmental). To identify common etiologic mechanisms among uncommon neurodevelopmental-related disorders and to potentially identify common therapies, it is paramount for teams of scientists, clinicians, and patients to unite their efforts. We bring forward novel, collaborative, and integrative strategies to translational CNV/SV research that engages diverse stakeholders to help expedite therapeutic outcomes. We articulate a clear vision for piloted roadmap strategies to reduce patient/caregiver burden and redundancies, increase efficiency, avoid siloed data, and accelerate translational discovery across CNV/SV-based syndromes.

Rapid assessment of the temporal function and phenotypic reversibility of neurodevelopmental disorder risk genes in Caenorhabditis elegans

Recent studies have indicated that some phenotypes caused by decreased function of select neurodevelopmental disorder (NDD) risk genes can be reversed by restoring gene function in adulthood. However, few of the hundreds of risk genes have been assessed for adult phenotypic reversibility. We developed a strategy to rapidly assess the temporal requirements and phenotypic reversibility of NDD risk gene orthologs using a conditional protein degradation system and machine-vision phenotypic profiling in Caenorhabditis elegans. We measured how degrading and re-expressing orthologs of EBF3, BRN3A and DYNC1H1 at multiple periods throughout development affect 30 morphological, locomotor, sensory and learning phenotypes. We found that phenotypic reversibility was possible for each gene studied. However, the temporal requirements of gene function and degree of rescue varied by gene and phenotype. This work highlights the critical need to assess multiple windows of degradation and re-expression and a large number of phenotypes to understand the many roles a gene can have across the lifespan. This work also demonstrates the benefits of using a high-throughput model system to prioritize NDD risk genes for re-expression studies in other organisms.

Summary: We identified diverse temporal functional windows and phenotypic reversibility profiles for three neurodevelopmental disorder risk genes: EBF3•unc-3, BRN3A•unc-86 and DYNC1H1•dhc-1. Re-expression of certain genes could rescue multiple phenotypes later in life, prioritizing them for study.

Neuroligins in neurodevelopmental conditions: how mouse models of de novo mutations can help us link synaptic function to social behavior

Neurodevelopmental conditions (or neurodevelopmental disorders, NDDs) are highly heterogeneous with overlapping characteristics and shared genetic etiology. The large symptom variability and etiological heterogeneity have made it challenging to understand the biological mechanisms underpinning NDDs. To accommodate this individual variability, one approach is to move away from diagnostic criteria and focus on distinct dimensions with relevance to multiple NDDs. This domain approach is well suited to preclinical research, where genetically modified animal models can be used to link genetic variability to neurobiological mechanisms and behavioral traits. Genetic factors associated with NDDs can be grouped functionally into common biological pathways, with one prominent functional group being genes associated with the synapse. These include the neuroligins (Nlgns), a family of postsynaptic transmembrane proteins that are key modulators of synaptic function. Here, we review how research using Nlgn mouse models has provided insight into how synaptic proteins contribute to behavioral traits associated with NDDs. We focus on how mutations in different Nlgns affect social behaviors, as differences in social interaction and communication are a common feature of most NDDs. Importantly, mice carrying distinct mutations in Nlgns share some neurobiological and behavioral phenotypes with other synaptic gene mutations. Comparing the functional implications of mutations in multiple synaptic proteins is a first step towards identifying convergent neurobiological pathways in multiple brain regions and circuits.

Variegation of autism related traits across seven neurogenetic disorders

Gene dosage disorders (GDDs) constitute a major class of genetic risks for psychopathology, but there is considerable debate regarding the extent to which different GDDs induce different psychopathology profiles. The current research speaks to this debate by compiling and analyzing dimensional measures of several autism-related traits (ARTs) across seven diverse GDDs. The sample included 350 individuals with one of 7 GDDs, as well as reference idiopathic autism spectrum disorder (ASD; n = 74) and typically developing control (TD; n = 171) groups. The GDDs were: Down, Williams-Beuren, and Smith-Magenis (DS, WS, SMS) syndromes, and varying sex chromosome aneuploidies ("plusX", "plusXX", "plusY", "plusXY"). The Social Responsiveness Scale (SRS-2) was used to measure ARTs at different levels of granularity-item, subscale, and total. General linear models were used to examine ART profiles in GDDs, and machine learning was used to predict genotype from SRS-2 subscales and items. These analyses were completed with and without covariation for cognitive impairment. Twelve of all possible 21 pairwise GDD group contrasts showed significantly different ART profiles (7/21 when co-varying for IQ, all Bonferroni-corrected). Prominent GDD-ART associations in post hoc analyses included relatively preserved social motivation in WS and relatively low levels of repetitive behaviors in plusX. Machine learning revealed that GDD group could be predicted with plausible accuracy (~60-80%) even after controlling for IQ. GDD effects on ARTs are influenced by GDD subtype and ART dimension. This observation has consequences for mechanistic, clinical, and translational aspects of psychiatric neurogenetics.

Improving clinical trial readiness to accelerate development of new therapeutics for Rett syndrome

Rett syndrome is associated with severe functional impairments and many comorbidities, each in urgent need of treatments. Mutations in the MECP2 gene were identified as causing Rett syndrome in 1999. Over the past 20 years there has been an abundance of preclinical research with some studies leading to human clinical trials. Despite this, few viable therapeutic options have emerged from this investment of effort. Reasons for this lack of success as they relate both to preclinical research and the clinical trial landscape are discussed. Considering what needs to be done to promote further success in the field, we take a positive and constructive approach and introduce the concept of clinical trial readiness and its necessary ingredients for Rett syndrome. These include: listening to the needs of families; support from advocacy groups; optimising use of existing clinic infrastructures and available natural history data; and, finally, the validation of existing outcome measures and/or the development and validation of new measures. We conclude by reiterating the need for a collaborative and coordinated approach amongst the many different stakeholder groups and the need to engage in new types of trial design which could be much more efficient, less costly and much less burdensome on families.

Genes To Mental Health (G2MH): A Framework to Map the Combined Effects of Rare and Common Variants on Dimensions of Cognition and Psychopathology

Rare genomic disorders (RGDs) confer elevated risk for neurodevelopmental psychiatric disorders. In this era of intense genomics discoveries, the landscape of RGDs is rapidly evolving. However, there has not been comparable progress to date in scalable, harmonized phenotyping methods. As a result, beyond associations with categorical diagnoses, the effects on dimensional traits remain unclear for many RGDs. The nature and specificity of RGD effects on cognitive and behavioral traits is an area of intense investigation: RGDs are frequently associated with more than one psychiatric condition, and those studied to date affect, to varying degrees, a broad range of developmental and cognitive functions. Although many RGDs have large effects, phenotypic expression is typically influenced by additional genomic and environmental factors. There is emerging evidence that using polygenic risk scores in individuals with RGDs offers opportunities to refine prediction, thus allowing for the identification of those at greatest risk of psychiatric illness. However, translation into the clinic is hindered by roadblocks, which include limited genetic testing in clinical psychiatry, and the lack of guidelines for following individuals with RGDs, who are at high risk of developing psychiatric symptoms. The Genes to Mental Health Network (G2MH) is a newly funded National Institute of Mental Health initiative that will collect, share, and analyze large-scale data sets combining genomics and dimensional measures of psychopathology spanning diverse populations and geography. The authors present here the most recent understanding of the effects of RGDs on dimensional behavioral traits and risk for psychiatric conditions and discuss strategies that will be pursued within the G2MH network, as well as how expected results can be translated into clinical practice to improve patient outcomes.

Altered canonical and striatal-frontal resting state functional connectivity in children with pathogenic variants in the Ras/mitogen-activated protein kinase pathway

Mounting evidence supports the role of the Ras/mitogen-activated protein kinase (Ras/MAPK) pathway in neurodevelopmental disorders. Here, the authors used a genetics-first approach to examine how Ras/MAPK pathogenic variants affect the functional organization of the brain and cognitive phenotypes including weaknesses in attention and inhibition. Functional MRI was used to examine resting state functional connectivity (RSFC) in association with Ras/MAPK pathogenic variants in children with Noonan syndrome (NS). Participants (age 4-12 years) included 39 children with NS (mean age 8.44, SD = 2.20, 25 females) and 49 typically developing (TD) children (mean age 9.02, SD = 9.02, 33 females). Twenty-eight children in the NS group and 46 in the TD group had usable MRI data and were included in final analyses. The results indicated significant hyperconnectivity for the NS group within canonical visual, ventral attention, left frontoparietal and limbic networks (p < 0.05 FWE). Higher connectivity within canonical left frontoparietal and limbic networks positively correlated with cognitive function within the NS but not the TD group. Further, the NS group demonstrated significant group differences in seed-based striatal-frontal connectivity (Z > 2.6, p < 0.05 FWE). Hyperconnectivity within canonical brain networks may represent an intermediary phenotype between Ras/MAPK pathogenic variants and cognitive phenotypes, including weaknesses in attention and inhibition. Altered striatal-frontal connectivity corresponds with smaller striatal volume and altered white matter connectivity previously documented in children with NS. These results may indicate delayed maturation and compensatory mechanisms and they are important for understanding the pathophysiology underlying cognitive phenotypes in NS and in the broader population of children with neurodevelopmental disorders.

Metabolic effects of the schizophrenia-associated 3q29 deletion

The 1.6 Mb 3q29 deletion is associated with developmental and psychiatric phenotypes, including a 40-fold increased risk for schizophrenia. Reduced birth weight and a high prevalence of feeding disorders in patients suggest underlying metabolic dysregulation. We investigated 3q29 deletion-induced metabolic changes using our previously generated heterozygous B6.Del16^+/Bdh1-Tfrc mouse model. Animals were provided either standard chow (STD) or high-fat diet (HFD). Growth curves were performed on HFD mice to assess weight change (n = 30-50/group). Indirect calorimetry and untargeted metabolomics were performed on STD and HFD mice to evaluate metabolic phenotypes (n = 8-14/group). A behavioral battery was performed on STD and HFD mice to assess behavior change after the HFD challenge (n = 5-13/group). We found that B6.Del16^+/Bdh1-Tfrc animals preferentially use dietary lipids as an energy source. Untargeted metabolomics of liver tissue showed a strong sex-dependent effect of the 3q29 deletion on fat metabolism. A HFD partially rescued the 3q29 deletion-associated weight deficit in females, but not males. Untargeted metabolomics of liver tissue after HFD revealed persistent fat metabolism alterations in females. The HFD did not affect B6.Del16^+/Bdh1-Tfrc behavioral phenotypes, suggesting that 3q29 deletion-associated metabolic and behavioral outcomes are uncoupled. Our data suggest that dietary interventions to improve weight phenotypes in 3q29 deletion syndrome patients are unlikely to exacerbate behavioral manifestations. Our study also highlights the importance of assessing sex in metabolic studies and suggests that mechanisms underlying 3q29 deletion-associated metabolic phenotypes are sex-specific.

The Current Progress of Psychiatric Genomics

Psychiatric disorders such as bipolar disorder and schizophrenia are highly heritable. While the genetic contribution to psychiatric disorders is quite sure, specific genetic factors contributing to particular conditions have long been a mystery. Empowered by the initial report of the Human Genome Project, the analysis of the comprehensive set of the human genome, called "genomics," became possible. Subsequent development of large-scale genomic technologies enabled us to elucidate various disease-related genetic information, accelerating our understanding of various diseases. Genomic research on psychiatric disorders is not an exception. In this Review, I introduce significant advancements in psychiatric genomics with a special focus on our investigation of bipolar disorder. International consortiums and advocacy groups accelerate psychiatric genomics, increasing the sample size and statistical power for robust findings. The genetic architecture of schizophrenia has been elucidated in both common and rare variant studies. The genetic architecture of autism spectrum disorder (ASD) has been elucidated mainly by rare variant analysis. As to bipolar disorder, common variant analysis precedes rare variant analysis, but we are struggling to elucidate relevant rare variants. While the genomic approach has explained specific genetic factors for particular disorders, overlapping risk genes or pleiotropy has been observed more than expected. The boundary in the current nosology of psychiatric disorders is more or less challenged. To understand the genotype-phenotype relation more deeply, an attempt to understand phenotypes based on genotypes, called the "genotype first" approach, has started. I discuss this new approach for better understanding and treatment of psychiatric disorders.

A matter of space and time: Emerging roles of disease-associated proteins in neural development

Recent genetic studies of neurodevelopmental disorders point to synaptic proteins and ion channels as key contributors to disease pathogenesis. Although many of these proteins, such as the L-type calcium channel Cav1.2 or the postsynaptic scaffolding protein SHANK3, have well-studied functions in mature neurons, new evidence indicates that they may subserve novel, distinct roles in immature cells as the nervous system is assembled in prenatal development. Emerging tools and technologies, including single-cell sequencing and human cellular models of disease, are illuminating differential isoform utilization, spatiotemporal expression, and subcellular localization of ion channels and synaptic proteins in the developing brain compared with the adult, providing new insights into the regulation of developmental processes. We propose that it is essential to consider the temporally distinct and cell-specific roles of these proteins during development and maturity in our framework for understanding neuropsychiatric disorders.

Harnessing rare variants in neuropsychiatric and neurodevelopment disorders-a Keystone Symposia report

Neurodevelopmental neuropsychiatric disorders, such as autism spectrum disorder and schizophrenia, have strong genetic risk components, but the underlying mechanisms have proven difficult to decipher. Rare, high-risk variants may offer an opportunity to delineate the biological mechanisms responsible more clearly for more common idiopathic diseases. Indeed, different rare variants can cause the same behavioral phenotype, demonstrating genetic heterogeneity, while the same rare variant can cause different behavioral phenotypes, demonstrating variable expressivity. These observations suggest convergent underlying biological and neurological mechanisms; identification of these mechanisms may ultimately reveal new therapeutic targets. At the 2021 Keystone eSymposium "Neuropsychiatric and Neurodevelopmental Disorders: Harnessing Rare Variants" a panel of experts in the field described significant progress in genomic discovery and human phenotyping and raised several consistent issues, including the need for detailed natural history studies of rare disorders, the challenges in cohort recruitment, and the importance of viewing phenotypes as quantitative traits that are impacted by rare variants.

Patterns of delay in early gross motor and expressive language milestone attainment in probands with genetic conditions versus idiopathic ASD from SFARI registries

BACKGROUND

Recent large-scale initiatives have led to systematically collected phenotypic data for several rare genetic conditions implicated in autism spectrum disorder (ASD). The onset of developmentally expected skills (e.g. walking, talking) serve as readily quantifiable aspects of the behavioral phenotype. This study's aims were: (a) describe the distribution of ages of attainment of gross motor and expressive language milestones in several rare genetic conditions, and (b) characterize the likelihood of delays in these conditions compared with idiopathic ASD.

METHODS

Participants aged 3 years and older were drawn from two Simons Foundation Autism Research Initiative registries that employed consistent phenotyping protocols. Inclusion criteria were a confirmed genetic diagnosis of one of 16 genetic conditions (Simons Searchlight) or absence of known pathogenic genetic findings in individuals with ASD (SPARK). Parent-reported age of acquisition of three gross motor and two expressive language milestones was described and categorized as on-time or delayed, relative to normative expectations.

RESULTS

Developmental milestone profiles of probands with genetic conditions were marked by extensive delays (including nonattainment), with highest severity in single gene conditions and more delays than idiopathic ASD in motor skills. Compared with idiopathic ASD, the median odds of delay among the genetic groups were higher by 8.3 times (IQR 5.8-16.3) for sitting, 12.4 times (IQR 5.3-19.5) for crawling, 26.8 times (IQR 7.7-41.1) for walking, 2.7 times (IQR 1.7-5.5) for single words, and 5.7 times (IQR 2.7-18.3) for combined words.

CONCLUSIONS

Delays in developmental milestones, particularly in gross motor skills, are frequent and may be among the earliest indicators of differentially affected developmental processes in specific genetically defined conditions associated with ASD, as compared with those with clinical diagnoses of idiopathic ASD. The possibility of different developmental pathways leading to ASD-associated phenotypes should be considered when deciding how to employ specific genetic conditions as models for ASD.

Lessons Learned From Neuroimaging Studies of Copy Number Variants: A Systematic Review

Pathogenic copy number variants (CNVs) and aneuploidies alter gene dosage and are associated with neurodevelopmental psychiatric disorders such as autism spectrum disorder and schizophrenia. Brain mechanisms mediating genetic risk for neurodevelopmental psychiatric disorders remain largely unknown, but there is a rapid increase in morphometry studies of CNVs using T1-weighted structural magnetic resonance imaging. Studies have been conducted one mutation at a time, leaving the field with a complex catalog of brain alterations linked to different genomic loci. Our aim was to provide a systematic review of neuroimaging phenotypes across CNVs associated with developmental psychiatric disorders including autism and schizophrenia. We included 76 structural magnetic resonance imaging studies on 20 CNVs at the 15q11.2, 22q11.2, 1q21.1 distal, 16p11.2 distal and proximal, 7q11.23, 15q11-q13, and 22q13.33 (SHANK3) genomic loci as well as aneuploidies of chromosomes X, Y, and 21. Moderate to large effect sizes on global and regional brain morphometry are observed across all genomic loci, which is in line with levels of symptom severity reported for these variants. This is in stark contrast with the much milder neuroimaging effects observed in idiopathic psychiatric disorders. Data also suggest that CNVs have independent effects on global versus regional measures as well as on cortical surface versus thickness. Findings highlight a broad diversity of regional morphometry patterns across genomic loci. This heterogeneity of brain patterns provides insight into the weak effects reported in magnetic resonance imaging studies of cognitive dimension and psychiatric conditions. Neuroimaging studies across many more variants will be required to understand links between gene function and brain morphometry.

Extended Phenotyping and Functional Validation Facilitate Diagnosis of a Complex Patient Harboring Genetic Variants in MCCC1 and GNB5 Causing Overlapping Phenotypes

Identifying multiple ultra-rare genetic syndromes with overlapping phenotypes is a diagnostic conundrum in clinical genetics. This study investigated the pathogenicity of a homozygous missense variant in GNB5 (GNB5L; NM_016194.4: c.920T > G (p. Leu307Arg); GNB5S; NM_006578.4: c.794T > G (p. Leu265Arg)) identified through exome sequencing in a female child who also had 3-methylcrotonyl-CoA carboxylase (3-MCC) deficiency (newborn screening positive) and hemoglobin E trait. The proband presented with early-onset intellectual disability, the severity of which was more in keeping with GNB5-related disorder than 3-MCC deficiency. She later developed bradycardia and cardiac arrest, and upon re-phenotyping showed cone photo-transduction recovery deficit, all known only to GNB5-related disorders. Patient-derived fibroblast assays showed preserved GNB5S expression, but bioluminescence resonance energy transfer assay showed abolished function of the variant reconstituted Gβ5S containing RGS complexes for deactivation of D2 dopamine receptor activity, confirming variant pathogenicity. This study highlights the need for precise phenotyping and functional assays to facilitate variant classification and clinical diagnosis in patients with complex medical conditions.

Dissecting autism and schizophrenia through neuroimaging genomics

Neuroimaging genomic studies of autism spectrum disorder and schizophrenia have mainly adopted a 'top-down' approach, beginning with the behavioural diagnosis, and moving down to intermediate brain phenotypes and underlying genetic factors. Advances in imaging and genomics have been successfully applied to increasingly large case-control studies. As opposed to diagnostic-first approaches, the bottom-up strategy begins at the level of molecular factors enabling the study of mechanisms related to biological risk, irrespective of diagnoses or clinical manifestations. The latter strategy has emerged from questions raised by top-down studies: why are mutations and brain phenotypes over-represented in individuals with a psychiatric diagnosis? Are they related to core symptoms of the disease or to comorbidities? Why are mutations and brain phenotypes associated with several psychiatric diagnoses? Do they impact a single dimension contributing to all diagnoses? In this review, we aimed at summarizing imaging genomic findings in autism and schizophrenia as well as neuropsychiatric variants associated with these conditions. Top-down studies of autism and schizophrenia identified patterns of neuroimaging alterations with small effect-sizes and an extreme polygenic architecture. Genomic variants and neuroimaging patterns are shared across diagnostic categories suggesting pleiotropic mechanisms at the molecular and brain network levels. Although the field is gaining traction; characterizing increasingly reproducible results, it is unlikely that top-down approaches alone will be able to disentangle mechanisms involved in autism or schizophrenia. In stark contrast with top-down approaches, bottom-up studies showed that the effect-sizes of high-risk neuropsychiatric mutations are equally large for neuroimaging and behavioural traits. Low specificity has been perplexing with studies showing that broad classes of genomic variants affect a similar range of behavioural and cognitive dimensions, which may be consistent with the highly polygenic architecture of psychiatric conditions. The surprisingly discordant effect sizes observed between genetic and diagnostic first approaches underscore the necessity to decompose the heterogeneity hindering case-control studies in idiopathic conditions. We propose a systematic investigation across a broad spectrum of neuropsychiatric variants to identify putative latent dimensions underlying idiopathic conditions. Gene expression data on temporal, spatial and cell type organization in the brain have also considerable potential for parsing the mechanisms contributing to these dimensions' phenotypes. While large neuroimaging genomic datasets are now available in unselected populations, there is an urgent need for data on individuals with a range of psychiatric symptoms and high-risk genomic variants. Such efforts together with more standardized methods will improve mechanistically informed predictive modelling for diagnosis and clinical outcomes.

A white paper on a neurodevelopmental framework for drug discovery in autism and other neurodevelopmental disorders

In the last decade there has been a revolution in terms of genetic findings in neurodevelopmental disorders (NDDs), with many discoveries critical for understanding their aetiology and pathophysiology. Clinical trials in single-gene disorders such as fragile X syndrome highlight the challenges of investigating new drug targets in NDDs. Incorporating a developmental perspective into the process of drug development for NDDs could help to overcome some of the current difficulties in identifying and testing new treatments. This paper provides a summary of the proceedings of the 'New Frontiers Meeting' on neurodevelopmental disorders organised by the European College of Neuropsychopharmacology in conjunction with the Innovative Medicines Initiative-sponsored AIMS-2-TRIALS consortium. It brought together experts in developmental genetics, autism, NDDs, and clinical trials from academia and industry, regulators, patient and family associations, and other stakeholders. The meeting sought to provide a platform for focused communication on scientific insights, challenges, and methodologies that might be applicable to the development of CNS treatments from a neurodevelopmental perspective. Multidisciplinary translational consortia to develop basic and clinical research in parallel could be pivotal to advance knowledge in the field. Although implementation of clinical trials for NDDs in paediatric populations is widely acknowledged as essential, safety concerns should guide each aspect of their design. Industry and academia should join forces to improve knowledge of the biology of brain development, identify the optimal timing of interventions, and translate these findings into new drugs, allowing for the needs of users and families, with support from regulatory agencies.

A cross-comparison of cognitive ability across 8 genomic disorders

Genomic disorders result from rearrangement of the human genome. Most genomic disorders are caused by copy number variants (CNV), deletions or duplications of several hundred kilobases. Many CNV loci are associated with autism, schizophrenia, and most commonly, intellectual disability (ID). However, there is little comparison of cognitive ability measures across these CNV disorders. This study aims to understand whether existing data can be leveraged for a cross-comparison of cognitive ability among multiple CNV. We found there is a lack of harmonization among assessment instruments and little standardization for reporting summary data across studies. Despite these limitations, we identified a differential impact of CNV loci on cognitive ability. Our data suggest that future cross-comparisons of CNV disorders will reveal meaningful differences across the phenotypic spectrum, especially if standardized phenotypic assessment is achieved.

A resource to explore the discovery of rare diseases and their causative genes

Here, we describe a dataset with information about monogenic, rare diseases with a known genetic background, supplemented with manually extracted provenance for the disease itself and the discovery of the underlying genetic cause. We assembled a collection of 4166 rare monogenic diseases and linked them to 3163 causative genes, annotated with OMIM and Ensembl identifiers and HGNC symbols. The PubMed identifiers of the scientific publications, which for the first time described the rare diseases, and the publications, which found the genes causing the diseases were added using information from OMIM, PubMed, Wikipedia, whonamedit.com, and Google Scholar. The data are available under CC0 license as spreadsheet and as RDF in a semantic model modified from DisGeNET, and was added to Wikidata. This dataset relies on publicly available data and publications with a PubMed identifier, but by our effort to make the data interoperable and linked, we can now analyse this data. Our analysis revealed the timeline of rare disease and causative gene discovery and links them to developments in methods.

All for one and one for all: heterogeneity of genetic etiologies in neurodevelopmental psychiatric disorders

Alexandre Dumas' famous phrase All for One and One for All recapitulates our current understanding of the genomic architecture of neurodevelopmental psychiatric disorders (NPD), like autism Spectrum disorder, bipolar disorder, and schizophrenia. Many rare genomic variants of large effect size have been identified; all of them together can explain a significant proportion of NPD. In parallel, one rare genomic variant can cause all of the above NPD. Finally, common genomic variants of individually small effect size can be combined to further explain risk for NPD. How do we reconcile different genomic variants accounting for one clinical diagnosis, and different clinical diagnoses arising from a single genomic variant? Here, we discuss a framework to understand genetic and clinical heterogeneity in NPD.