Large mosaic copy number variations confer autism risk

Medial prefrontal cortex circuitry and social behaviour in autism

Autism spectrum disorder (ASD) has proven to be highly enigmatic due to the diversity of its underlying genetic causes and the huge variability in symptom presentation. Uncovering common phenotypes across people with ASD and pre-clinical models allows us to better understand the influence on brain function of the many different genetic and cellular processes thought to contribute to ASD aetiology. One such feature of ASD is the convergent evidence implicating abnormal functioning of the medial prefrontal cortex (mPFC) across studies. The mPFC is a key part of the 'social brain' and may contribute to many of the changes in social behaviour observed in people with ASD. Here we review recent evidence for mPFC involvement in both ASD and social behaviours. We also highlight how pre-clinical mouse models can be used to uncover important cellular and circuit-level mechanisms that may underly atypical social behaviours in ASD. This article is part of the Special Issue on "PFC circuit function in psychiatric disease and relevant models".

Increased somatic mosaicism in autosomal and X chromosomes for suicide death

Mosaic chromosomal alterations (mCAs) are classified as mosaic deletions (loss), copy-neutral loss of heterozygosity (CN-LOH), and duplications (gain), attracting special attention as biological aging-related acquired genetic alterations. While these mCAs have been linked with aging and various diseases, no study has investigated their association with suicide risk which is associated with abnormal biological aging. Here, we examined the association between suicide deaths and mCAs, including mosaic loss of the X (mLOX) and Y chromosomes, by leveraging blood-derived single nucleotide polymorphism-array data. The first (410 suicide decedents and 88,870 controls) and the second (363 suicide decedents and 88,870 controls) cohorts were analyzed and integrated using meta-analyses (773 suicide decedents and 177,740 controls). Total mCAs in autosomal chromosomes were significantly increased in suicide (p = 1.28 × 10-6, odds ratio [OR] = 1.78), mostly driven by loss (p = 4.05 × 10-9, OR = 2.70) and gain (p = 1.08 × 10-3, OR = 2.23). mLOX were significantly increased in female suicide (p = 2.66 × 10-21, OR = 4.00). The directions of effects of all mCAs in autosomal and sex chromosomes on suicide were the same in the first and second sets. Subgroup analyses suggest that our findings were mostly driven by suicide itself, and not confounded by comorbid psychiatric disorders or physical diseases, smoking status, sample location, or postmortem sample status. In conclusion, we provide the first evidence for aberrant mCAs in somatic autosomal and X chromosomes in suicide, which may contribute to an improved understanding of the genomic pathophysiology underlying suicide.

Low-level brain somatic mutations in exonic regions are collectively implicated in autism with germline mutations in autism risk genes

Low-level somatic mutations in the human brain are implicated in various neurological disorders. The contribution of low-level brain somatic mutations to autism spectrum disorder (ASD), however, remains poorly understood. Here, we performed high-depth exome sequencing with an average read depth of 559.3x in 181 cortical, cerebellar, and peripheral tissue samples to identify brain somatic single nucleotide variants (SNVs) in 24 ASD subjects and 31 controls. We detected ~2.4 brain somatic SNVs per exome per single brain region, with a variant allele frequency (VAF) as low as 0.3%. The mutational profiles, including the number, signature, and type, were not significantly different between the ASD patients and controls. Intriguingly, when considering genes with low-level brain somatic SNVs and ASD risk genes with damaging germline SNVs together, the merged set of genes carrying either somatic or germline SNVs in ASD patients was significantly involved in ASD-associated pathophysiology, including dendrite spine morphogenesis (p = 0.025), mental retardation (p = 0.012), and intrauterine growth retardation (p = 0.012). Additionally, the merged gene set showed ASD-associated spatiotemporal expression in the early and mid-fetal cortex, striatum, and thalamus (all p < 0.05). Patients with damaging mutations in the merged gene set had a greater ASD risk than did controls (odds ratio = 3.92, p = 0.025, 95% confidence interval = 1.12-14.79). The findings of this study suggest that brain somatic SNVs and germline SNVs may collectively contribute to ASD-associated pathophysiology.

The Contribution of Mosaic Chromosomal Alterations to Schizophrenia

BACKGROUND

Mosaic chromosomal alterations are implicated in neuropsychiatric disorders, but the contribution to schizophrenia (SCZ) risk for somatic copy number variations (sCNVs) emerging in early developmental stages has not been fully established.

METHODS

We analyzed blood-derived genotype arrays from 9715 patients with SCZ and 28,822 control participants of Chinese descent using a computational tool (MoChA) based on long-range chromosomal information to detect mosaic chromosomal alterations. We focused on probable early developmental sCNVs through stringent filtering. We assessed the burden of sCNVs across varying cell fraction cutoffs, as well as the frequency with which genes were involved in sCNVs. We integrated this data with the PGC (Psychiatric Genomics Consortium) dataset, which comprises 12,834 SCZ cases and 11,648 controls of European descent, and complemented it with genotyping data from postmortem brain tissue of 936 participants (449 cases and 487 controls).

RESULTS

Patients with SCZ had a significantly higher somatic losses detection rate than control participants (1.00% vs. 0.52%; odds ratio = 1.91; 95% CI, 1.47-2.49; two-sided Fisher's exact test, p = 1.49 × 10-6). Further analysis indicated that the odds ratios escalated proportionately (from 1.91 to 2.78) with the increment in cell fraction cutoffs. Recurrent sCNVs associated with SCZ (odds ratio > 8; Fisher's exact test, p < .05) were identified, including notable regions at 10q21.1 (ZWINT), 3q26.1 (SLITRK3), 1q31.1 (BRINP3) and 12q21.31-21.32 (MGAT4C and NTS) in the Chinese cohort, and some regions were validated with PGC data. Cross-tissue validation pinpointed somatic losses at loci like 1p35.3-35.2 and 19p13.3-13.2.

CONCLUSIONS

The study highlights the significant impact of mosaic chromosomal alterations on SCZ, suggesting their pivotal role in the disorder's genetic etiology.

Genomic Mosaicism of the Brain: Origin, Impact, and Utility

Genomic mosaicism describes the phenomenon where some but not all cells within a tissue harbor unique genetic mutations. Traditionally, research focused on the impact of genomic mosaicism on clinical phenotype-motivated by its involvement in cancers and overgrowth syndromes. More recently, we increasingly shifted towards the plethora of neutral mosaic variants that can act as recorders of cellular lineage and environmental exposures. Here, we summarize the current state of the field of genomic mosaicism research with a special emphasis on our current understanding of this phenomenon in brain development and homeostasis. Although the field of genomic mosaicism has a rich history, technological advances in the last decade have changed our approaches and greatly improved our knowledge. We will provide current definitions and an overview of contemporary detection approaches for genomic mosaicism. Finally, we will discuss the impact and utility of genomic mosaicism.

Strategies for dissecting the complexity of neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) are associated with a wide range of clinical features, affecting multiple pathways involved in brain development and function. Recent advances in high-throughput sequencing have unveiled numerous genetic variants associated with NDDs, which further contribute to disease complexity and make it challenging to infer disease causation and underlying mechanisms. Herein, we review current strategies for dissecting the complexity of NDDs using model organisms, induced pluripotent stem cells, single-cell sequencing technologies, and massively parallel reporter assays. We further highlight single-cell CRISPR-based screening techniques that allow genomic investigation of cellular transcriptomes with high efficiency, accuracy, and throughput. Overall, we provide an integrated review of experimental approaches that can be applicable for investigating a broad range of complex disorders.

Cell type-specific enrichment of somatic aneuploidy in the mammalian brain

Somatic mutations alter the genomes of a subset of an individual's brain cells1-3, impacting gene regulation and contributing to disease processes4,5. Mosaic single nucleotide variants have been characterized with single-cell resolution in the brain2,3, but we have limited information about large-scale structural variation, including whole-chromosome duplication or loss1,6,7. We used a dataset of over 415,000 single-cell DNA methylation and chromatin conformation profiles across the adult mouse brain to identify aneuploid cells comprehensively. Whole-chromosome loss or duplication occurred in <1% of cells, with rates up to 1.8% in non-neuronal cell types, including oligodendrocyte precursors and pericytes. Among all aneuploidies, we observed a strong enrichment of trisomy on chromosome 16, which is syntenic with human chromosome 21 and constitutively trisomic in Down syndrome. Chromosome 16 trisomy occurred in multiple cell types and across brain regions, suggesting that nondisjunction is a recurrent feature of somatic variation in the brain.

Genomic data resources of the Brain Somatic Mosaicism Network for neuropsychiatric diseases

Somatic mosaicism is defined as an occurrence of two or more populations of cells having genomic sequences differing at given loci in an individual who is derived from a single zygote. It is a characteristic of multicellular organisms that plays a crucial role in normal development and disease. To study the nature and extent of somatic mosaicism in autism spectrum disorder, bipolar disorder, focal cortical dysplasia, schizophrenia, and Tourette syndrome, a multi-institutional consortium called the Brain Somatic Mosaicism Network (BSMN) was formed through the National Institute of Mental Health (NIMH). In addition to genomic data of affected and neurotypical brains, the BSMN also developed and validated a best practices somatic single nucleotide variant calling workflow through the analysis of reference brain tissue. These resources, which include >400 terabytes of data from 1087 subjects, are now available to the research community via the NIMH Data Archive (NDA) and are described here.

Increased cerebral lactate levels in adults with autism spectrum disorders compared to non-autistic controls: a magnetic resonance spectroscopy study

INTRODUCTION

Autism spectrum disorder (ASD) encompasses a heterogeneous group with varied phenotypes and etiologies. Identifying pathogenic subgroups could facilitate targeted treatments. One promising avenue is investigating energy metabolism, as mitochondrial dysfunction has been implicated in a subgroup of ASD. Lactate, an indicator of energy metabolic anomalies, may serve as a potential biomarker for this subgroup. This study aimed to examine cerebral lactate (Lac+) levels in high-functioning adults with ASD, hypothesizing elevated mean Lac+ concentrations in contrast to neurotypical controls (NTCs).

MATERIALS AND METHODS

Magnetic resonance spectroscopy (MRS) was used to study cerebral Lac+ in 71 adults with ASD and NTC, focusing on the posterior cingulate cortex (PCC). After quality control, 64 ASD and 58 NTC participants remained. Lac+ levels two standard deviations above the mean of the control group were considered elevated.

RESULTS

Mean PCC Lac+ levels were significantly higher in the ASD group than in the NTC group (p = 0.028; Cohen's d = 0.404), and 9.4% of the ASD group had elevated levels as compared to 0% of the NTCs (p = 0.029). No significant correlation was found between blood serum lactate levels and MRS-derived Lac+ levels.

LIMITATIONS

A cautious interpretation of our results is warranted due to a p value of 0.028. In addition, a higher than anticipated proportion of data sets had to be excluded due to poor spectral quality.

CONCLUSION

This study confirms the presence of elevated cerebral Lac+ levels in a subgroup of adults with ASD, suggesting the potential of lactate as a biomarker for mitochondrial dysfunction in a subgroup of ASD. The lower-than-expected prevalence (20% was expected) and moderate increase require further investigation to elucidate the underlying mechanisms and relationships with mitochondrial function.

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.

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)-present in some but not all cells-remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e-4), with recurrent somatic deletions of exons 1-5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5' deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk.

Mosaic Chromosomal Alterations Are Associated With Increased Lung Cancer Risk: Insight From the INTEGRAL-ILCCO Cohort Analysis

INTRODUCTION

Mosaic chromosomal alterations (mCAs) detected in white blood cells represent a type of clonal hematopoiesis (CH) that is understudied compared with CH-related somatic mutations. A few recent studies indicated their potential link with nonhematological cancers, especially lung cancer.

METHODS

In this study, we investigated the association between mCAs and lung cancer using the high-density genotyping data from the OncoArray study of INTEGRAL-ILCCO, the largest single genetic study of lung cancer with 18,221 lung cancer cases and 14,825 cancer-free controls.

RESULTS

We identified a comprehensive list of autosomal mCAs, ChrX mCAs, and mosaic ChrY (mChrY) losses from these samples. Autosomal mCAs were detected in 4.3% of subjects, in addition to ChrX mCAs in 3.6% of females and mChrY losses in 9.6% of males. Multivariable logistic regression analysis indicated that the presence of autosomal mCAs in white blood cells was associated with an increased lung cancer risk after adjusting for key confounding factors, including age, sex, smoking status, and race. This association was mainly driven by a specific type of mCAs: copy-neutral loss of heterozygosity on autosomal chromosomes. The association between autosome copy-neutral loss of heterozygosity and increased risk of lung cancer was further confirmed in two major histologic subtypes, lung adenocarcinoma and squamous cell carcinoma. In addition, we observed a significant increase of ChrX mCAs and mChrY losses in smokers compared with nonsmokers and racial differences in certain types of mCA events.

CONCLUSIONS

Our study established a link between mCAs in white blood cells and increased risk of lung cancer.

The human brain through the lens of somatic mosaicism

Every cell in the human brain possesses a unique genome that is the product of the accumulation of somatic mutations starting from the first postzygotic cell division and continuing throughout life. Somatic mosaicism in the human brain has been the focus of several recent efforts that took advantage of key technological innovations to start elucidating brain development, aging and disease directly in human tissue. On one side, somatic mutation occurring in progenitor cells has been used as a natural barcoding system to address cell phylogenies of clone formation and cell segregation in the brain lineage. On the other side, analyses of mutation rates and patterns in the genome of brain cells have revealed mechanisms of brain aging and disorder predisposition. In addition to the study of somatic mosaicism in the normal human brain, the contribution of somatic mutation has been investigated in both developmental neuropsychiatric and neurodegenerative disorders. This review starts with a methodological perspective on the study of somatic mosaicism to then cover the most recent findings in brain development and aging, and ends with the role of somatic mutations in brain disease. Thus, this review underlies what we have learned and what is still possible to discover by looking at somatic mosaicism in the brain genome.

Molecular diagnosis of 405 individuals with autism spectrum disorder

Autism spectrum disorder (ASD) is caused by combined genetic and environmental factors. Genetic heritability in ASD is estimated as 60-90%, and genetic investigations have revealed many monogenic factors. We analyzed 405 patients with ASD using family-based exome sequencing to detect disease-causing single-nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variations (CNVs) for molecular diagnoses. All candidate variants were validated by Sanger sequencing or quantitative polymerase chain reaction and were evaluated using the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines for molecular diagnosis. We identified 55 disease-causing SNVs/indels in 53 affected individuals and 13 disease-causing CNVs in 13 affected individuals, achieving a molecular diagnosis in 66 of 405 affected individuals (16.3%). Among the 55 disease-causing SNVs/indels, 51 occurred de novo, 2 were compound heterozygous (in one patient), and 2 were X-linked hemizygous variants inherited from unaffected mothers. The molecular diagnosis rate in females was significantly higher than that in males. We analyzed affected sibling cases of 24 quads and 2 quintets, but only one pair of siblings shared an identical pathogenic variant. Notably, there was a higher molecular diagnostic rate in simplex cases than in multiplex families. Our simulation indicated that the diagnostic yield is increasing by 0.63% (range 0-2.5%) per year. Based on our simple simulation, diagnostic yield is improving over time. Thus, periodical reevaluation of ES data should be strongly encouraged in undiagnosed ASD patients.

Genomic strategies to untangle the etiology of autism: A primer

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in communication, diminished social skills, and restrictive and repetitive behaviors and interests. ASD affects approximately 2.3% of the population and is highly heterogeneous, both phenotypically and genetically. As genomic technologies advance, our understanding of the genetic architecture of ASD is becoming clearer, encompassing spontaneous and inherited alterations throughout the genome, and delineating alterations that are either rare or common in the population. This commentary provides an overview of the genomic strategies and resulting major findings of genetic alterations associated with ASD.

Somatic genetic variation in healthy tissue and non-cancer diseases

Somatic genetic variants have been studied for several years mostly concerning cancer, where they contribute to its origin and development. It is also clear that the somatic variants load is greater in aged individuals in comparison to younger ones, pointing to a cause/consequence of the senescence process. More recently, researchers have focused on the role of this type of variation in healthy tissue and its dynamics in cell lineages and different organs. In addition, somatic variants have been described to contribute to monogenic diseases, and the number of evidences of their role in complex disorders is also increasing. Thanks to recent advances in next-generation sequencing technologies, this type of genetic variation can be now more easily studied than in the past, although we still face some important limitations. Novel strategies for sampling, sequencing and filtering are being investigated to detect these variants, although validating them with an orthogonal approach will most likely still be needed. In this review, we aim to update our knowledge of somatic variation detection and its relation to healthy tissue and non-cancer diseases.

Scalable approaches for functional analyses of whole-genome sequencing non-coding variants

Non-coding genetic variants outside of protein-coding genome regions play an important role in genetic and epigenetic regulation. It has become increasingly important to understand their roles, as non-coding variants often make up the majority of top findings of genome-wide association studies (GWAS). In addition, the growing popularity of disease-specific whole-genome sequencing (WGS) efforts expands the library of and offers unique opportunities for investigating both common and rare non-coding variants, which are typically not detected in more limited GWAS approaches. However, the sheer size and breadth of WGS data introduce additional challenges to predicting functional impacts in terms of data analysis and interpretation. This review focuses on the recent approaches developed for efficient, at-scale annotation and prioritization of non-coding variants uncovered in WGS analyses. In particular, we review the latest scalable annotation tools, databases and functional genomic resources for interpreting the variant findings from WGS based on both experimental data and in silico predictive annotations. We also review machine learning-based predictive models for variant scoring and prioritization. We conclude with a discussion of future research directions which will enhance the data and tools necessary for the effective functional analyses of variants identified by WGS to improve our understanding of disease etiology.

CRISPR-mediated activation of autism gene Itgb3 restores cortical network excitability via mGluR5 signaling

Many mutations in autism spectrum disorder (ASD) affect a single allele, indicating a key role for gene dosage in ASD susceptibility. Recently, haplo-insufficiency of ITGB3, the gene encoding the extracellular matrix receptor β3 integrin, was associated with ASD. Accordingly, Itgb3 knockout (KO) mice exhibit autism-like phenotypes. The pathophysiological mechanisms of Itgb3 remain, however, unknown, and the potential of targeting this gene for developing ASD therapies uninvestigated. By combining molecular, biochemical, imaging, and pharmacological analyses, we establish that Itgb3 haplo-insufficiency impairs cortical network excitability by promoting extra-synaptic over synaptic signaling of the metabotropic glutamate receptor mGluR5, which is similarly dysregulated in fragile X syndrome, the most frequent monogenic form of ASD. To assess the therapeutic potential of regulating Itgb3 gene dosage, we implemented CRISPR activation and compared its efficacy with that of a pharmacological rescue strategy for fragile X syndrome. Correction of neuronal Itgb3 haplo-insufficiency by CRISPR activation rebalanced network excitability as effectively as blockade of mGluR5 with the selective antagonist MPEP. Our findings reveal an unexpected functional interaction between two ASD genes, thereby validating the pathogenicity of ITGB3 haplo-insufficiency. Further, they pave the way for exploiting CRISPR activation as gene therapy for normalizing gene dosage and network excitability in ASD.

Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS (myeloid ectopic viral integration site) transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

Longer metaphase and fewer chromosome segregation errors in modern human than Neanderthal brain development

Since the ancestors of modern humans separated from those of Neanderthals, around 100 amino acid substitutions spread to essentially all modern humans. The biological significance of these changes is largely unknown. Here, we examine all six such amino acid substitutions in three proteins known to have key roles in kinetochore function and chromosome segregation and to be highly expressed in the stem cells of the developing neocortex. When we introduce these modern human-specific substitutions in mice, three substitutions in two of these proteins, KIF18a and KNL1, cause metaphase prolongation and fewer chromosome segregation errors in apical progenitors of the developing neocortex. Conversely, the ancestral substitutions cause shorter metaphase length and more chromosome segregation errors in human brain organoids, similar to what we find in chimpanzee organoids. These results imply that the fidelity of chromosome segregation during neocortex development improved in modern humans after their divergence from Neanderthals.

Genomics, convergent neuroscience and progress in understanding autism spectrum disorder

More than a hundred genes have been identified that, when disrupted, impart large risk for autism spectrum disorder (ASD). Current knowledge about the encoded proteins - although incomplete - points to a very wide range of developmentally dynamic and diverse biological processes. Moreover, the core symptoms of ASD involve distinctly human characteristics, presenting challenges to interpreting evolutionarily distant model systems. Indeed, despite a decade of striking progress in gene discovery, an actionable understanding of pathobiology remains elusive. Increasingly, convergent neuroscience approaches have been recognized as an important complement to traditional uses of genetics to illuminate the biology of human disorders. These methods seek to identify intersection among molecular-level, cellular-level and circuit-level functions across multiple risk genes and have highlighted developing excitatory neurons in the human mid-gestational prefrontal cortex as an important pathobiological nexus in ASD. In addition, neurogenesis, chromatin modification and synaptic function have emerged as key potential mediators of genetic vulnerability. The continued expansion of foundational 'omics' data sets, the application of higher-throughput model systems and incorporating developmental trajectories and sex differences into future analyses will refine and extend these results. Ultimately, a systems-level understanding of ASD genetic risk holds promise for clarifying pathobiology and advancing therapeutics.

Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology

Advances in genome sequencing technologies have unlocked new possibilities in identifying disease-associated and causative genetic markers, which may in turn enhance disease diagnosis and improve prognostication and management strategies. With the capability of examining genetic variations ranging from single-nucleotide mutations to large structural variants, whole-genome sequencing (WGS) is an increasingly adopted approach to dissect the complex genetic architecture of neurologic diseases. There is emerging evidence for different structural variants and their roles in major neurologic and neurodevelopmental diseases. This review first describes different structural variants and their implicated roles in major neurologic and neurodevelopmental diseases, and then discusses the clinical relevance of WGS applications in neurology. Notably, WGS-based detection of structural variants has shown promising potential in enhancing diagnostic power of genetic tests in clinical settings. Ongoing WGS-based research in structural variations and quantifying mutational constraints can also yield clinical benefits by improving variant interpretation and disease diagnosis, while supporting biomarker discovery and therapeutic development. As a result, wider integration of WGS technologies into health care will likely increase diagnostic yields in difficult-to-diagnose conditions and define potential therapeutic targets or intervention points for genome-editing strategies.

Genetic mosaicism in the human brain: from lineage tracing to neuropsychiatric disorders

Genetic mosaicism is the result of the accumulation of somatic mutations in the human genome starting from the first postzygotic cell generation and continuing throughout the whole life of an individual. The rapid development of next-generation and single-cell sequencing technologies is now allowing the study of genetic mosaicism in normal tissues, revealing unprecedented insights into their clonal architecture and physiology. The somatic variant repertoire of an adult human neuron is the result of somatic mutations that accumulate in the brain by different mechanisms and at different rates during development and ageing. Non-pathogenic developmental mutations function as natural barcodes that once identified in deep bulk or single-cell sequencing can be used to retrospectively reconstruct human lineages. This approach has revealed novel insights into the clonal structure of the human brain, which is a mosaic of clones traceable to the early embryo that contribute differentially to the brain and distinct areas of the cortex. Some of the mutations happening during development, however, have a pathogenic effect and can contribute to some epileptic malformations of cortical development and autism spectrum disorder. In this Review, we discuss recent findings in the context of genetic mosaicism and their implications for brain development and disease.

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.

Towards accurate and reliable resolution of structural variants for clinical diagnosis

Structural variants (SVs) are a major source of human genetic diversity and have been associated with different diseases and phenotypes. The detection of SVs is difficult, and a diverse range of detection methods and data analysis protocols has been developed. This difficulty and diversity make the detection of SVs for clinical applications challenging and requires a framework to ensure accuracy and reproducibility. Here, we discuss current developments in the diagnosis of SVs and propose a roadmap for the accurate and reproducible detection of SVs that includes case studies provided from the FDA-led SEquencing Quality Control Phase II (SEQC-II) and other consortium efforts.

Somatic Mosaicism and Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a genetically heterogenous neurodevelopmental disorder. In the early years of next-generation sequencing, de novo germline variants were shown to contribute to ASD risk. These germline mutations are present in all of the cells of an affected individual and can be detected in any tissue, including clinically accessible DNA sources such as blood or saliva. In recent years, studies have also implicated de novo somatic variants in ASD risk. These somatic mutations arise postzygotically and are present in only a subset of the cells of an affected individual. Depending on the developmental time and progenitor cell in which a somatic mutation occurs, it may be detectable in some tissues and not in others. Somatic mutations detectable at relatively low sequencing coverage in clinically accessible tissues are suggested to contribute to 3-5% of simplex ASD diagnoses, and "brain limited" somatic mutations have been identified in postmortem ASD brain tissue. Somatic mutations likely represent the genetic diagnosis in a proportion of otherwise unexplained individuals with ASD, and brain limited somatic mutations can be used as markers to discover risk genes, cell types, brain regions, and cellular pathways important for ASD pathogenesis and to potentially target for therapeutics.

Rates and patterns of clonal oncogenic mutations in the normal human brain

While oncogenic mutations have been found in non-diseased, proliferative non-neural tissues, their prevalence in the human brain is unknown. Targeted sequencing of genes implicated in brain tumors in 418 samples derived from 110 individuals of varying ages, without tumor diagnoses, detected oncogenic somatic single-nucleotide variants (sSNVs) in 5.4% of the brains, including IDH1 R132H. These mutations were largely present in subcortical white matter and enriched in glial cells, and surprisingly, were less common in older individuals. A depletion of high-allele frequency sSNVs representing macroscopic clones with age was replicated by analysis of bulk RNAseq data from 1,816 non-diseased brain samples ranging from fetal to old age. We also describe large clonal copy number variants, and that sSNVs show mutational signatures resembling those found in gliomas, suggesting that mutational processes of the normal brain drive early glial oncogenesis. This study helps understand the origin and early evolution of brain tumors.

Genetics of autosomal mosaic chromosomal alteration (mCA)

Mosaic chromosomal alterations (mCAs) are frequently observed in cancer cells and are regarded as one of the common features of cancers. Strikingly, accumulating studies demonstrated that mCAs are also prevalent in elderly individuals without cancer, implying mCA could be a feature of aging and not necessarily a cancerous state. However, the genetic basis of mCA has been mostly unknown. Recent studies of autosomal mCA based on biobank-scale datasets, including UK Biobank and Biobank Japan, provided a glimpse into the underlying genetic mechanism. In this concise review, we briefly introduced mCA, its link with cancer and aging, and the emerging genetic mechanisms of this phenomenon. We highlighted the following aspects: (1) the interplay between somatic and inherited germline mutations in generating mosaicism; (2) monogenic and polygenic architectures of mCA; and (3) population-specific profiles of mCA. We provided a future perspective emphasizing the need to understand the connection between mCA and other characteristics of aging, in particular, the epigenetic and immunologic features.

Decoding and rejuvenating human ageing genomes: Lessons from mosaic chromosomal alterations

One of the most curious findings emerged from genome-wide studies over the last decade was that genetic mosaicism is a dominant feature of human ageing genomes. The clonal dominance of genetic mosaicism occurs preceding the physiological and physical ageing and associates with propensity for diseases including cancer, Alzheimer's disease, cardiovascular disease and diabetes. These findings are revolutionizing the ways biologists thinking about health and disease pathogenesis. Among all mosaic mutations in ageing genomes, mosaic chromosomal alterations (mCAs) have the most significant functional consequences because they can produce intercellular genomic variations simultaneously involving dozens to hundreds or even thousands genes, and therefore have most profound effects in human ageing and disease etiology. Here, we provide a comprehensive picture of the landscapes, causes, consequences and rejuvenation of mCAs at multiple scales, from cell to human population, by reviewing data from cytogenetic, genetic and genomic studies in cells, animal models (fly and mouse) and, more frequently, large-cohort populations. A detailed decoding of ageing genomes with a focus on mCAs may yield important insights into the genomic architecture of human ageing, accelerate the risk stratification of age-related diseases (particularly cancers) and development of novel targets and strategies for delaying or rejuvenating human (genome) ageing.

Somatic copy number variants in neuropsychiatric disorders

Copy number variants (CNVs) have been implicated in neuropsychiatric disorders, with rare-inherited and de novo CNVs (dnCNVs) having large effects on disease liability. Recent studies started exploring a class of dnCNVs that occur post-zygotically, and are therefore present in some but not all cells of the body. Analogous to conditional mutations in animal models, the presence of risk mutations in a fraction of cells has the potential to enlighten how damaging mutations affect cell-type/cell-circuit specific pathologies leading to neuropsychiatric manifestations. Although mosaic CNVs appear to contribute to a modest fraction of risk (0.3-0.5%), expanding our insights about them with more sensitive experimental and statistical methods, has the potential to help clarify mechanisms of neuropsychiatric disease.