Genetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders.

We characterized the genetic architecture of the attention-deficit hyperactivity disorder-substance use disorder (ADHD-SUD) relationship by investigating genetic correlation, causality, pleiotropy, and common polygenic risk. Summary statistics from genome-wide association studies (GWAS) were used to investigate ADHD (Neff = 51,568), cannabis use disorder (CanUD, Neff = 161,053), opioid use disorder (OUD, Neff = 57,120), problematic alcohol use (PAU, Neff = 502,272), and problematic tobacco use (PTU, Neff = 97,836). ADHD, CanUD, and OUD GWAS meta-analyses included cohorts with case definitions based on different diagnostic criteria. PAU GWAS combined information related to alcohol use disorder, alcohol dependence, and the items related to alcohol problematic consequences assessed by the alcohol use disorders identification test. PTU GWAS was generated a multi-trait analysis including information regarding Fagerström Test for Nicotine Dependence and cigarettes per day. Linkage disequilibrium score regression analyses indicated positive genetic correlation with CanUD, OUD, PAU, and PTU. Genomic structural equation modeling showed that these genetic correlations were related to two latent factors: one including ADHD, CanUD, and PTU and the other with OUD and PAU. The evidence of a causal effect of PAU and PTU on ADHD was stronger than the reverse in the two-sample Mendelian randomization analysis. Conversely, similar strength of evidence was found between ADHD and CanUD. CADM2 rs62250713 was a pleiotropic SNP between ADHD and all SUDs. We found seven, one, and twenty-eight pleiotropic variants between ADHD and CanUD, PAU, and PTU, respectively. Finally, OUD, CanUD, and PAU PRS were associated with increased odds of ADHD. Our findings demonstrated the contribution of multiple pleiotropic mechanisms to the comorbidity between ADHD and SUDs.

The pleiotropic contribution of genes in dopaminergic and serotonergic pathways to addiction and related behavioral traits.

Introduction: Co-occurrence of substance use disorders (SUD) and other behavioral conditions, such as stress-related, aggressive or risk-taking behaviors, in the same individual has been frequently described. As dopamine (DA) and serotonin (5-HT) have been previously identified as key neurotransmitters for some of these phenotypes, we explored the genetic contribution of these pathways to SUD and these comorbid phenotypes in order to better understand the genetic relationship between them. Methods: We tested the association of 275 dopaminergic genes and 176 serotonergic genes with these phenotypes by performing gene-based, gene-set and transcriptome-wide association studies in 11 genome-wide association studies (GWAS) datasets on SUD and related behaviors. Results: At the gene-wide level, 68 DA and 27 5-HT genes were found to be associated with at least one GWAS on SUD or related behavior. Among them, six genes had a pleiotropic effect, being associated with at least three phenotypes: ADH1C, ARNTL, CHRNA3, HPRT1, HTR1B and DRD2. Additionally, we found nominal associations between the DA gene sets and SUD, opioid use disorder, antisocial behavior, irritability and neuroticism, and between the 5-HT-core gene set and neuroticism. Predicted gene expression correlates in brain were also found for 19 DA or 5-HT genes. Discussion: Our study shows a pleiotropic contribution of dopaminergic and serotonergic genes to addiction and related behaviors such as anxiety, irritability, neuroticism and risk-taking behavior, highlighting a role for DA genes, which could explain, in part, the co-occurrence of these phenotypes.

Molecular genetics of cocaine use disorders in humans.

Drug addiction, one of the major health problems worldwide, is characterized by the loss of control in drug intake, craving, and withdrawal. At the individual level, drugs of abuse produce serious consequences on health and have a negative impact on the family environment and on interpersonal and work relationships. At a wider scale, they have significant socio-economic and public health consequences and they cause delinquency and citizen insecurity. Cocaine, a psychostimulant substance, is one of the most used illicit drugs, especially in America, Western Europe, and Australia. Cocaine use disorders (CUD) are complex multifactorial conditions driven by both genetic and environmental influences. Importantly, not all people who use cocaine develop CUD, and this is due, at least in part, to biological factors that are encoded in the genome of individuals. Acute and repeated use of cocaine induces epigenetic and gene expression changes responsible for the neuronal adaptations and the remodeling of brain circuits that lead to the transition from use to abuse or dependence. The purpose of this review is to delineate such factors, which should eventually help to understand the inter-individual variability in the susceptibility to cocaine addiction. Heritability estimates for CUD are high and genetic risk factors for cocaine addiction have been investigated by candidate gene association studies (CGAS) and genome-wide association studies (GWAS), reviewed here. Also, the high comorbidity that exists between CUD and several other psychiatric disorders is well known and includes phenotypes like schizophrenia, aggression, antisocial or risk-taking behaviors. Such comorbidities are associated with a worse lifetime trajectory, and here we report shared genetic factors that may contribute to them. Gene expression changes and epigenetic modifications induced by cocaine use and chronic abuse in humans are addressed by reviewing transcriptomic studies performed on neuronal cells and on postmortem brains. We report some genes which expression is altered by cocaine that also bear genetic risk variants for the disorder. Finally, we have a glance to the pharmacogenetics of CUD treatments, still in early stages. A better understanding of the genetic underpinnings of CUD will foster the search of effective treatments and help to move forward to personalized medicine.

Full-length isoform transcriptome of the developing human brain provides further insights into autism.

Alternative splicing plays an important role in brain development, but its global contribution to human neurodevelopmental diseases (NDDs) requires further investigation. Here we examine the relationships between splicing isoform expression in the brain and de novo loss-of-function mutations from individuals with NDDs. We analyze the full-length isoform transcriptome of the developing human brain and observe differentially expressed isoforms and isoform co-expression modules undetectable by gene-level analyses. These isoforms are enriched in loss-of-function mutations and microexons, are co-expressed with a unique set of partners, and have higher prenatal expression. We experimentally test the effect of splice-site mutations and demonstrate exon skipping in five NDD risk genes, including SCN2A, DYRK1A, and BTRC. Our results suggest that the splice site mutation in BTRC reduces translational efficiency, likely affecting Wnt signaling through impaired degradation of ß-catenin. We propose that functional effects of mutations should be investigated at the isoform- rather than gene-level resolution.

De novo Mutations From Whole Exome Sequencing in Neurodevelopmental and Psychiatric Disorders: From Discovery to Application.

Neurodevelopmental and psychiatric disorders are a highly disabling and heterogeneous group of developmental and mental disorders, resulting from complex interactions of genetic and environmental risk factors. The nature of multifactorial traits and the presence of comorbidity and polygenicity in these disorders present challenges in both disease risk identification and clinical diagnoses. The genetic component has been firmly established, but the identification of all the causative variants remains elusive. The development of next-generation sequencing, especially whole exome sequencing (WES), has greatly enriched our knowledge of the precise genetic alterations of human diseases, including brain-related disorders. In particular, the extensive usage of WES in research studies has uncovered the important contribution of de novo mutations (DNMs) to these disorders. Trio and quad familial WES are a particularly useful approach to discover DNMs. Here, we review the major WES studies in neurodevelopmental and psychiatric disorders and summarize how genes hit by discovered DNMs are shared among different disorders. Next, we discuss different integrative approaches utilized to interrogate DNMs and to identify biological pathways that may disrupt brain development and shed light on our understanding of the genetic architecture underlying these disorders. Lastly, we discuss the current state of the transition from WES research to its routine clinical application. This review will assist researchers and clinicians in the interpretation of variants obtained from WES studies, and highlights the need to develop consensus analytical protocols and validated lists of genes appropriate for clinical laboratory analysis, in order to reach the growing demands.

bigSCale: an analytical framework for big-scale single-cell data.

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin (Reln)-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets.

Paternally inherited cis-regulatory structural variants are associated with autism.

The genetic basis of autism spectrum disorder (ASD) is known to consist of contributions from de novo mutations in variant-intolerant genes. We hypothesize that rare inherited structural variants in cis-regulatory elements (CRE-SVs) of these genes also contribute to ASD. We investigated this by assessing the evidence for natural selection and transmission distortion of CRE-SVs in whole genomes of 9274 subjects from 2600 families affected by ASD. In a discovery cohort of 829 families, structural variants were depleted within promoters and untranslated regions, and paternally inherited CRE-SVs were preferentially transmitted to affected offspring and not to their unaffected siblings. The association of paternal CRE-SVs was replicated in an independent sample of 1771 families. Our results suggest that rare inherited noncoding variants predispose children to ASD, with differing contributions from each parent.

Comprehensive Analyses of Tissue-Specific Networks with Implications to Psychiatric Diseases.

Recent advances in genome sequencing and "omics" technologies are opening new opportunities for improving diagnosis and treatment of human diseases. The precision medicine initiative in particular aims at developing individualized treatment options that take into account individual variability in genes and environment of each person. Systems biology approaches that group genes, transcripts and proteins into functionally meaningful networks will play crucial role in the future of personalized medicine. They will allow comparison of healthy and disease-affected tissues and organs from the same individual, as well as between healthy and disease-afflicted individuals. However, the field faces a multitude of challenges ranging from data integration to statistical and combinatorial issues in data analyses. This chapter describes computational approaches developed by us and the others to tackle challenges in tissue-specific network analyses, with the main focus on psychiatric diseases.

Mutation Spectrum in the CACNA1A Gene in 49 Patients with Episodic Ataxia.

Episodic ataxia is an autosomal dominant ion channel disorder characterized by episodes of imbalance and incoordination. The disease is genetically heterogeneous and is classified as episodic ataxia type 2 (EA2) when it is caused by a mutation in the CACNA1A gene, encoding the α1A subunit of the P/Q-type voltage-gated calcium channel Cav2.1. The vast majority of EA2 disease-causing variants are loss-of-function (LoF) point changes leading to decreased channel currents. CACNA1A exonic deletions have also been reported in EA2 using quantitative approaches. We performed a mutational screening of the CACNA1A gene, including the promoter and 3'UTR regions, in 49 unrelated patients diagnosed with episodic ataxia. When pathogenic variants were not found by sequencing, we performed a copy number variant (CNV) analysis to screen for duplications or deletions. Overall, sequencing screening allowed identification of six different point variants (three nonsense and three missense changes) and two coding indels, one of them found in two unrelated patients. Additionally, CNV analysis identified a deletion in a patient spanning exon 35 as a result of a recombination event between flanking intronic Alu sequences. This study allowed identification of potentially pathogenic alterations in our sample, five of them novel, which cover 20% of the patients (10/49). Our data suggest that most of these variants are disease-causing, although functional studies are required.

Spatiotemporal 16p11.2 protein network implicates cortical late mid-fetal brain development and KCTD13-Cul3-RhoA pathway in psychiatric diseases.

The psychiatric disorders autism and schizophrenia have a strong genetic component, and copy number variants (CNVs) are firmly implicated. Recurrent deletions and duplications of chromosome 16p11.2 confer a high risk for both diseases, but the pathways disrupted by this CNV are poorly defined. Here we investigate the dynamics of the 16p11.2 network by integrating physical interactions of 16p11.2 proteins with spatiotemporal gene expression from the developing human brain. We observe profound changes in protein interaction networks throughout different stages of brain development and/or in different brain regions. We identify the late mid-fetal period of cortical development as most critical for establishing the connectivity of 16p11.2 proteins with their co-expressed partners. Furthermore, our results suggest that the regulation of the KCTD13-Cul3-RhoA pathway in layer 4 of the inner cortical plate is crucial for controlling brain size and connectivity and that its dysregulation by de novo mutations may be a potential determinant of 16p11.2 CNV deletion and duplication phenotypes.

A proteome-scale map of the human interactome network.

Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism.

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.

Evaluation of common variants in 16 genes involved in the regulation of neurotransmitter release in ADHD.

Attention-deficit hyperactivity disorder (ADHD) is a neurobehavioral disorder characterized by inappropriate difficulties to sustain attention, control impulses and modulate activity level. Although ADHD is one of the most prevalent childhood psychiatric disorders, it also persists into adulthood in around 30-50% of the cases. Based on the effect of psychostimulants used in the pharmacological treatment of ADHD, dysfunctions in neuroplasticity mechanisms and synapses have been postulated to be involved in the pathophysiology of ADHD. With this background, we evaluated, both in childhood and adulthood ADHD, the role of several genes involved in the control of neurotransmitter release through synaptic vesicle docking, fusion and recycling processes by means of a population-based association study. We analyzed single nucleotide polymorphisms across 16 genes in a clinical sample of 950 ADHD patients (506 adults and 444 children) and 905 controls. Single and multiple-marker analyses identified several significant associations after correcting for multiple testing with a false discovery rate (FDR) of 15%: (i) the SYT2 gene was strongly associated with both adulthood and childhood ADHD (p=0.001, OR=1.49 (1.18-1.89) and p=0.007, OR=1.37 (1.09-1.72), respectively) and (ii) STX1A was found associated with ADHD only in adults (p=0.0041; OR=1.28 (1.08-1.51)). These data provide preliminary evidence for the involvement of genes that participate in the control of neurotransmitter release in the genetic predisposition to ADHD through a gene-system association study. Further follow-up studies in larger cohorts and deep-sequencing of the associated genomic regions are required to identify sequence variants directly involved in ADHD.

Screening of CACNA1A and ATP1A2 genes in hemiplegic migraine: clinical, genetic, and functional studies.

Hemiplegic migraine (HM) is a rare and severe subtype of autosomal dominant migraine, characterized by a complex aura including some degree of motor weakness. Mutations in four genes (CACNA1A, ATP1A2, SCN1A and PRRT2) have been detected in familial and in sporadic cases. This genetically and clinically heterogeneous disorder is often accompanied by permanent ataxia, epileptic seizures, mental retardation, and chronic progressive cerebellar atrophy. Here we report a mutation screening in the CACNA1A and ATP1A2 genes in 18 patients with HM. Furthermore, intragenic copy number variant (CNV) analysis was performed in CACNA1A using quantitative approaches. We identified four previously described missense CACNA1A mutations (p.Ser218Leu, p.Thr501Met, p.Arg583Gln, and p.Thr666Met) and two missense changes in the ATP1A2 gene, the previously described p.Ala606Thr and the novel variant p.Glu825Lys. No structural variants were found. This genetic screening allowed the identification of more than 30% of the disease alleles, all present in a heterozygous state. Functional consequences of the CACNA1A-p.Thr501Met mutation, previously described only in association with episodic ataxia, and ATP1A2-p.Glu825Lys, were investigated by means of electrophysiological studies, cell viability assays or Western blot analysis. Our data suggest that both these variants are disease-causing.

Whole-genome sequencing in autism identifies hot spots for de novo germline mutation.

De novo mutation plays an important role in autism spectrum disorders (ASDs). Notably, pathogenic copy number variants (CNVs) are characterized by high mutation rates. We hypothesize that hypermutability is a property of ASD genes and may also include nucleotide-substitution hot spots. We investigated global patterns of germline mutation by whole-genome sequencing of monozygotic twins concordant for ASD and their parents. Mutation rates varied widely throughout the genome (by 100-fold) and could be explained by intrinsic characteristics of DNA sequence and chromatin structure. Dense clusters of mutations within individual genomes were attributable to compound mutation or gene conversion. Hypermutability was a characteristic of genes involved in ASD and other diseases. In addition, genes impacted by mutations in this study were associated with ASD in independent exome-sequencing data sets. Our findings suggest that regional hypermutation is a significant factor shaping patterns of genetic variation and disease risk in humans.

SNP variants within the vanilloid TRPV1 and TRPV3 receptor genes are associated with migraine in the Spanish population.

The transient receptor potential (TRP) superfamily of non-selective cationic channels are involved in several processes plausibly relevant to migraine pathophysiology, including multimodal sensory and pain perception, central and peripheral sensitization, and regulation of calcium homeostasis. With the aim of identifying single nucleotide polymorphisms (SNPs) in TRP genes that may confer increased genetic susceptibility to migraine, we carried out a case-control genetic association study with replication, including a total of 1,040 cases and 1,037 controls. We genotyped 149 SNPs covering 14 TRP genes with known brain expression. The two-stage study comprised samples of 555 and 485 Spanish, Caucasian patients, selected according to the ICHD-II criteria for the diagnosis of migraine without aura (MO) or migraine with aura (MA). In the discovery sample, 19 SNPs in ten TRP genes showed nominal association (P < 0.05) with MO, MA, or overall migraine. In the replication sample, nominal association was confirmed for TRPV3 rs7217270 in MA and TRPV1 rs222741 in the overall migraine group. Risk haplotypes were identified for seven of the genes showing nominal association in the discovery set, but none of them was replicated. The present findings suggest that members of the vanilloid TRPV subfamily of receptors contribute to the genetic susceptibility to migraine in the Spanish population.

Candidate pathway association study in cocaine dependence: the control of neurotransmitter release.

OBJECTIVES: Cocaine is the second most used illegal drug in Europe. The transition from use to dependence involves both genetic and environmental factors. Genetic variation in neurotransmitter systems is involved in the susceptibility to cocaine dependence. We examined the possible contribution to cocaine dependence of 16 genes involved in the cellular machinery that controls neurotransmitter release: genes encoding proteins of the SNARE complex (STX1A, SNAP25, VAMP1 and VAMP2), fusion control elements (SYT1, SYT2, CPLX1, CPLX2, CPLX3 and CPLX4) and regulatory elements (STXBP1, SYP, SNPH, NSF, NAPA and RAB3A). METHODS: We genotyped 121 SNPs, selected according to genetic coverage criteria, in 360 cocaine-dependent patients and 360 controls from Spain. RESULTS: Single and multiple-marker analyses revealed a strong association between cocaine dependence and the NSF gene, encoding the N-ethylmaleimide-sensitive factor (P = 5.1e-04, OR = 2.44 (1.45-4.00) and P = 0.001, OR = 1.82 (1.28-2.59), respectively). The presence and absence of psychotic symptoms were also studied. Interestingly, when we considered the time between initial consumption and the onset of cocaine dependence, we observed that the association was mainly restricted to the group of patients that rapidly developed drug dependence (≤ 2 years; P = 2.98e-06, OR = 1.33 (1.20-1.47)). CONCLUSIONS: Our data show preliminary evidence that NSF may predispose not only to cocaine dependence, but also to an early onset of the dependence.

Duplications of the neuropeptide receptor gene VIPR2 confer significant risk for schizophrenia.

Rare copy number variants (CNVs) have a prominent role in the aetiology of schizophrenia and other neuropsychiatric disorders. Substantial risk for schizophrenia is conferred by large (>500-kilobase) CNVs at several loci, including microdeletions at 1q21.1 (ref. 2), 3q29 (ref. 3), 15q13.3 (ref. 2) and 22q11.2 (ref. 4) and microduplication at 16p11.2 (ref. 5). However, these CNVs collectively account for a small fraction (2-4%) of cases, and the relevant genes and neurobiological mechanisms are not well understood. Here we performed a large two-stage genome-wide scan of rare CNVs and report the significant association of copy number gains at chromosome 7q36.3 with schizophrenia. Microduplications with variable breakpoints occurred within a 362-kilobase region and were detected in 29 of 8,290 (0.35%) patients versus 2 of 7,431 (0.03%) controls in the combined sample. All duplications overlapped or were located within 89 kilobases upstream of the vasoactive intestinal peptide receptor gene VIPR2. VIPR2 transcription and cyclic-AMP signalling were significantly increased in cultured lymphocytes from patients with microduplications of 7q36.3. These findings implicate altered vasoactive intestinal peptide signalling in the pathogenesis of schizophrenia and indicate the VPAC2 receptor as a potential target for the development of new antipsychotic drugs.

A mutation in the first intracellular loop of CACNA1A prevents P/Q channel modulation by SNARE proteins and lowers exocytosis.

Familial hemiplegic migraine (FHM)-causing mutations in the gene encoding the P/Q Ca(2+) channel alpha(1A) subunit (CACNA1A) locate to the pore and voltage sensor regions and normally involve gain-of-channel function. We now report on a mutation identified in the first intracellular loop of CACNA1A (alpha(1A(A454T))) that does not cause FHM but is associated with the absence of sensorimotor symptoms in a migraine with aura pedigree. Alpha(1A(A454T)) channels showed weakened regulation of voltage-dependent steady-state inactivation by Ca(V)beta subunits. More interestingly, A454T mutation suppressed P/Q channel modulation by syntaxin 1A or SNAP-25 and decreased exocytosis. Our findings reveal the importance of I-II loop structural integrity in the functional interaction between P/Q channel and proteins of the vesicle-docking/fusion machinery, and that genetic variation in CACNA1A may be not only a cause but also a modifier of migraine phenotype.