Genetic associations with psychosis and affective disturbance in Alzheimer's disease.

INTRODUCTION: Individuals with Alzheimer's disease (AD) commonly experience neuropsychiatric symptoms of psychosis (AD+P) and/or affective disturbance (depression, anxiety, and/or irritability, AD+A). This study's goal was to identify the genetic architecture of AD+P and AD+A, as well as their genetically correlated phenotypes. METHODS: Genome-wide association meta-analysis of 9988 AD participants from six source studies with participants characterized for AD+P AD+A, and a joint phenotype (AD+A+P). RESULTS: AD+P and AD+A were genetically correlated. However, AD+P and AD+A diverged in their genetic correlations with psychiatric phenotypes in individuals without AD. AD+P was negatively genetically correlated with bipolar disorder and positively with depressive symptoms. AD+A was positively correlated with anxiety disorder and more strongly correlated than AD+P with depressive symptoms. AD+P and AD+A+P had significant estimated heritability, whereas AD+A did not. Examination of the loci most strongly associated with the three phenotypes revealed overlapping and unique associations. DISCUSSION: AD+P, AD+A, and AD+A+P have both shared and divergent genetic associations pointing to the importance of incorporating genetic insights into future treatment development. Highlights: It has long been known that psychotic and affective symptoms are often comorbid in individuals diagnosed with Alzheimer's disease. Here we examined for the first time the genetic architecture underlying this clinical observation, determining that psychotic and affective phenotypes in Alzheimer's disease are genetically correlated.Nevertheless, psychotic and affective phenotypes in Alzheimer's disease diverged in their genetic correlations with psychiatric phenotypes assessed in individuals without Alzheimer's disease. Psychosis in Alzheimer's disease was negatively genetically correlated with bipolar disorder and positively with depressive symptoms, whereas the affective phenotypes in Alzheimer's disease were positively correlated with anxiety disorder and more strongly correlated than psychosis with depressive symptoms.Psychosis in Alzheimer's disease, and the joint psychotic and affective phenotype, had significant estimated heritability, whereas the affective in AD did not.Examination of the loci most strongly associated with the psychotic, affective, or joint phenotypes revealed overlapping and unique associations.

Evaluating and improving health equity and fairness of polygenic scores.

Polygenic scores (PGSs) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. One such method is Lassosum, which inherits the model selection advantages of Lasso to select a meaningful subset of the GWAS single-nucleotide polymorphisms as predictors from their association statistics. However, even efficient scores like Lassosum, when derived from European-based GWASs, are poor predictors of phenotype for subjects of non-European ancestry; that is, they have limited portability to other ancestries. To increase the portability of Lassosum, when GWAS information and estimates of linkage disequilibrium are available for both ancestries, we propose Joint-Lassosum (JLS). In the simulation settings we explore, JLS provides more accurate PGSs compared to other methods, especially when measured in terms of fairness. In analyses of UK Biobank data, JLS was computationally more efficient but slightly less accurate than a Bayesian comparator, SDPRX. Like all PGS methods, JLS requires selection of predictors, which are determined by data-driven tuning parameters. We describe a new approach to selecting tuning parameters and note its relevance for model selection for any PGS. We also draw connections to the literature on algorithmic fairness and discuss how JLS can help mitigate fairness-related harms that might result from the use of PGSs in clinical settings. While no PGS method is likely to be universally portable, due to the diversity of human populations and unequal information content of GWASs for different ancestries, JLS is an effective approach for enhancing portability and reducing predictive bias.

Heritable Composite Phenotypes Defined by Combinations of Conduct Problem, Depression, and Temperament Features: Contributions to risk for Alcohol Problems.

The genetic architectures underlying symptoms of conduct problems and depression have largely been examined separately and without incorporating temperament, despite evidence for their genetic overlap. We examined how symptoms and temperament dimensions were transmitted together in families to identify highly heritable composite phenotypes, and how these composite phenotypes predicted alcohol outcomes in young adulthood. Participants (N = 486) were drawn from the third generation of families oversampled for alcohol use disorder in the first generation. Conduct problems, depression, and temperament were reported at 11-19 years old and alcohol outcomes at 18-26 years old. Using principal components of heritability analysis, we found seven highly heritable composite phenotypes, five of which predicted alcohol outcomes: three characterized by co-occurring conduct problems and depression and two by conduct problems. Novel composite phenotypes that were characterized by both conduct problems and depression showed different types of symptoms, temperament features, and genetic underpinnings. Children manifesting differing composite phenotypes might benefit from distinct treatments based on their unique etiologies.

Comparison of gene expression in living and postmortem human brain.

Molecular mechanisms of neuropsychiatric disorders are challenging to study in human brain. For decades, the preferred model has been to study postmortem human brain samples despite the limitations they entail. A recent study generated RNA sequencing data from biopsies of prefrontal cortex from living patients with Parkinson's Disease and compared gene expression to postmortem tissue samples, from which they found vast differences between the two. This led the authors to question the utility of postmortem human brain studies. Through re-analysis of the same data, we unexpectedly found that the living brain tissue samples were of much lower quality than the postmortem samples across multiple standard metrics. We also performed simulations that illustrate the effects of ignoring RNA degradation in differential gene expression analyses, showing the effects can be substantial and of similar magnitude to what the authors find. For these reasons, we believe the authors' conclusions are unjustified. To the contrary, while opportunities to study gene expression in the living brain are welcome, evidence that this eclipses the value of postmortem analyses is not apparent.

Evaluating and Improving Health Equity and Fairness of Polygenic Scores.

Polygenic scores (PGS) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. One such method is Lassosum, which inherits the model selection advantages of Lasso to select a meaningful subset of the GWAS single nucleotide polymorphisms as predictors from their association statistics. However, even efficient scores like Lassosum, when derived from European-based GWAS, are poor predictors of phenotype for subjects of non-European ancestry; that is, they have limited portability to other ancestries. To increase the portability of Lassosum, when GWAS information and estimates of linkage disequilibrium are available for both ancestries, we propose Joint-Lassosum. In the simulation settings we explore, Joint-Lassosum provides more accurate PGS compared with other methods, especially when measured in terms of fairness. Like all PGS methods, Joint-Lassosum requires selection of predictors, which are determined by data-driven tuning parameters. We describe a new approach to selecting tuning parameters and note its relevance for model selection for any PGS. We also draw connections to the literature on algorithmic fairness and discuss how Joint-Lassosum can help mitigate fairness-related harms that might result from the use of PGS scores in clinical settings. While no PGS method is likely to be universally portable, due to the diversity of human populations and unequal information content of GWAS for different ancestries, Joint-Lassosum is an effective approach for enhancing portability and reducing predictive bias.

Direct additive genetics and maternal effect contribute to the risk of Tourette disorder.

BACKGROUND: Risk for Tourette disorder, and chronic motor or vocal tic disorders (referenced here inclusively as CTD), arise from a combination of genetic and environmental factors. While multiple studies have demonstrated the importance of direct additive genetic variation for CTD risk, little is known about the role of cross-generational transmission of genetic risk, such as maternal effect, which is not transmitted via the inherited parental genomes. Here, we partition sources of variation on CTD risk into direct additive genetic effect (narrow-sense heritability) and maternal effect. METHODS: The study population consists of 2 522 677 individuals from the Swedish Medical Birth Register, who were born in Sweden between 1 January 1973 and 31 December 2000, and followed for a diagnosis of CTD through 31 December, 2013. We used generalised linear mixed models to partition the liability of CTD into: direct additive genetic effect, genetic maternal effect and environmental maternal effect. RESULTS: We identified 6227 (0.2%) individuals in the birth cohort with a CTD diagnosis. A study of half-siblings showed that maternal half-siblings had twice higher risk of developing a CTD compared with paternal ones. We estimated 60.7% direct additive genetic effect (95% credible interval, 58.5% to 62.4%), 4.8% genetic maternal effect (95% credible interval, 4.4% to 5.1%) and 0.5% environmental maternal effect (95% credible interval, 0.2% to 7%). CONCLUSIONS: Our results demonstrate genetic maternal effect contributes to the risk of CTD. Failure to account for maternal effect results in an incomplete understanding of the genetic risk architecture of CTD, as the risk for CTD is impacted by maternal effect which is above and beyond the risk from transmitted genetic effect.

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.

Schizophrenia-associated differential DNA methylation in brain is distributed across the genome and annotated to MAD1L1, a locus at which DNA methylation and transcription phenotypes share genetic variation with schizophrenia risk.

DNA methylation (DNAm), the addition of a methyl group to a cytosine in DNA, plays an important role in the regulation of gene expression. Single-nucleotide polymorphisms (SNPs) associated with schizophrenia (SZ) by genome-wide association studies (GWAS) often influence local DNAm levels. Thus, DNAm alterations, acting through effects on gene expression, represent one potential mechanism by which SZ-associated SNPs confer risk. In this study, we investigated genome-wide DNAm in postmortem superior temporal gyrus from 44 subjects with SZ and 44 non-psychiatric comparison subjects using Illumina Infinium MethylationEPIC BeadChip microarrays, and extracted cell-type-specific methylation signals by applying tensor composition analysis. We identified SZ-associated differential methylation at 242 sites, and 44 regions containing two or more sites (FDR cutoff of q = 0.1) and determined a subset of these were cell-type specific. We found mitotic arrest deficient 1-like 1 (MAD1L1), a gene within an established GWAS risk locus, harbored robust SZ-associated differential methylation. We investigated the potential role of MAD1L1 DNAm in conferring SZ risk by assessing for colocalization among quantitative trait loci for methylation and gene transcripts (mQTLs and tQTLs) in brain tissue and GWAS signal at the locus using multiple-trait-colocalization analysis. We found that mQTLs and tQTLs colocalized with the GWAS signal (posterior probability >0.8). Our findings suggest that alterations in MAD1L1 methylation and transcription may mediate risk for SZ at the MAD1L1-containing locus. Future studies to identify how SZ-associated differential methylation affects MAD1L1 biological function are indicated.

The Genetic Architecture of Obsessive-Compulsive Disorder: Contribution of Liability to OCD From Alleles Across the Frequency Spectrum.

OBJECTIVE: Obsessive-compulsive disorder (OCD) is known to be substantially heritable; however, the contribution of genetic variation across the allele frequency spectrum to this heritability remains uncertain. The authors used two new homogeneous cohorts to estimate the heritability of OCD from inherited genetic variation and contrasted the results with those of previous studies. METHODS: The sample consisted of 2,090 Swedish-born individuals diagnosed with OCD and 4,567 control subjects, all genotyped for common genetic variants, specifically >400,000 single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) ≥0.01. Using genotypes of these SNPs to estimate distant familial relationships among individuals, the authors estimated the heritability of OCD, both overall and partitioned according to MAF bins. RESULTS: Narrow-sense heritability of OCD was estimated at 29% (SE=4%). The estimate was robust, varying only modestly under different models. Contrary to an earlier study, however, SNPs with MAF between 0.01 and 0.05 accounted for 10% of heritability, and estimated heritability per MAF bin roughly followed expectations based on a simple model for SNP-based heritability. CONCLUSIONS: These results indicate that common inherited risk variation (MAF ≥0.01) accounts for most of the heritable variation in OCD. SNPs with low MAF contribute meaningfully to the heritability of OCD, and the results are consistent with expectation under the "infinitesimal model" (also referred to as the "polygenic model"), where risk is influenced by a large number of loci across the genome and across MAF bins.

How rare and common risk variation jointly affect liability for autism spectrum disorder.

BACKGROUND: Genetic studies have implicated rare and common variations in liability for autism spectrum disorder (ASD). Of the discovered risk variants, those rare in the population invariably have large impact on liability, while common variants have small effects. Yet, collectively, common risk variants account for the majority of population-level variability. How these rare and common risk variants jointly affect liability for individuals requires further study. METHODS: To explore how common and rare variants jointly affect liability, we assessed two cohorts of ASD families characterized for rare and common genetic variations (Simons Simplex Collection and Population-Based Autism Genetics and Environment Study). We analyzed data from 3011 affected subjects, as well as two cohorts of unaffected individuals characterized for common genetic variation: 3011 subjects matched for ancestry to ASD subjects and 11,950 subjects for estimating allele frequencies. We used genetic scores, which assessed the relative burden of common genetic variation affecting risk of ASD (henceforth "burden"), and determined how this burden was distributed among three subpopulations: ASD subjects who carry a potentially damaging variant implicated in risk of ASD ("PDV carriers"); ASD subjects who do not ("non-carriers"); and unaffected subjects who are assumed to be non-carriers. RESULTS: Burden harbored by ASD subjects is stochastically greater than that harbored by control subjects. For PDV carriers, their average burden is intermediate between non-carrier ASD and control subjects. Both carrier and non-carrier ASD subjects have greater burden, on average, than control subjects. The effects of common and rare variants likely combine additively to determine individual-level liability. LIMITATIONS: Only 305 ASD subjects were known PDV carriers. This relatively small subpopulation limits this study to characterizing general patterns of burden, as opposed to effects of specific PDVs or genes. Also, a small fraction of subjects that are categorized as non-carriers could be PDV carriers. CONCLUSIONS: Liability arising from common and rare risk variations likely combines additively to determine risk of any individual diagnosed with ASD. On average, ASD subjects carry a substantial burden of common risk variation, even if they also carry a rare PDV affecting risk.

Prevalence and phenotypic impact of rare potentially damaging variants in autism spectrum disorder.

BACKGROUND: The Autism Sequencing Consortium identified 102 high-confidence autism spectrum disorder (ASD) genes, showing that individuals with ASD and with potentially damaging single nucleotide variation (pdSNV) in these genes had lower cognitive levels and delayed age at walking, when compared to ASD participants without pdSNV. Here, we made use of a Swedish sample of individuals with ASD (called PAGES, for Population-Based Autism Genetics & Environment Study) to evaluate the frequency of pdSNV and their impact on medical and psychiatric phenotypes, using an epidemiological frame and universal health reporting. We then combine findings with those for potentially damaging copy number variation (pdCNV). METHODS: SNV and CNV calls were generated from whole-exome sequencing and chromosome microarray data, respectively. Birth and medical register data were used to collect phenotypes. RESULTS: Of 808 individuals assessed by sequencing, 69 (9%) had pdSNV in the 102 ASC genes, and 144 (18%) had pdSNV in the 102 ASC genes or in a larger set of curated neurodevelopmental genes (from the Deciphering Developmental Disorders study, the gene2phenotype database, and the Radboud University gene lists). Three or more individuals had pdSNV in GRIN2B, POGZ, SATB1, DYNC1H1, SCN8A, or CREBBP. In comparison, out of the 996 individuals from whom CNV were called, 105 (11%) carried one or more pdCNV, including four or more individuals with CNV in the recurrent 15q11q13, 22q11.2, and 16p11.2 loci. Carriers of pdSNV were more likely to have intellectual disability (ID) and epilepsy, while carriers of pdCNV showed increased rates of congenital anomalies and scholastic skill disorders. Carriers of either pdSNV or pdCNV were more likely to have ID, scholastic skill disorders, and epilepsy. LIMITATIONS: The cohort only included individuals with autistic disorder, the more severe form of ASD, and phenotypes are defined from medical registers. Not all genes studied are definitively ASD genes, and we did not have de novo information to aid in classification. CONCLUSIONS: In this epidemiological sample, rare pdSNV were more common than pdCNV and the combined yield of potentially damaging variation was substantial at 27%. The results provide compelling rationale for the use of high-throughout sequencing as part of routine clinical workup for ASD and support the development of precision medicine in ASD.

Genome-wide association identifies the first risk loci for psychosis in Alzheimer disease.

Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer disease (AD with psychosis, AD + P). AD + P affects ~50% of individuals with AD, identifies a subgroup with poor outcomes, and is associated with a greater degree of cognitive impairment and depressive symptoms, compared to subjects without psychosis (AD - P). Although the estimated heritability of AD + P is 61%, genetic sources of risk are unknown. We report a genome-wide meta-analysis of 12,317 AD subjects, 5445 AD + P. Results showed common genetic variation accounted for a significant portion of heritability. Two loci, one in ENPP6 (rs9994623, O.R. (95%CI) 1.16 (1.10, 1.22), p = 1.26 × 10-8) and one spanning the 3'-UTR of an alternatively spliced transcript of SUMF1 (rs201109606, O.R. 0.65 (0.56-0.76), p = 3.24 × 10-8), had genome-wide significant associations with AD + P. Gene-based analysis identified a significant association with APOE, due to the APOE risk haplotype ε4. AD + P demonstrated negative genetic correlations with cognitive and educational attainment and positive genetic correlation with depressive symptoms. We previously observed a negative genetic correlation with schizophrenia; instead, we now found a stronger negative correlation with the related phenotype of bipolar disorder. Analysis of polygenic risk scores supported this genetic correlation and documented a positive genetic correlation with risk variation for AD, beyond the effect of ε4. We also document a small set of SNPs likely to affect risk for AD + P and AD or schizophrenia. These findings provide the first unbiased identification of the association of psychosis in AD with common genetic variation and provide insights into its genetic architecture.

Transcriptome alterations are enriched for synapse-associated genes in the striatum of subjects with obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) is a chronic and severe psychiatric disorder for which effective treatment options are limited. Structural and functional neuroimaging studies have consistently implicated the orbitofrontal cortex (OFC) and striatum in the pathophysiology of the disorder. Recent genetic evidence points to involvement of components of the excitatory synapse in the etiology of OCD. However, the transcriptional alterations that could link genetic risk to known structural and functional abnormalities remain mostly unknown. To assess potential transcriptional changes in the OFC and two striatal regions (caudate nucleus and nucleus accumbens) of OCD subjects relative to unaffected comparison subjects, we sequenced messenger RNA transcripts from these brain regions. In a joint analysis of all three regions, 904 transcripts were differentially expressed between 7 OCD versus 8 unaffected comparison subjects. Region-specific analyses highlighted a smaller number of differences, which concentrated in caudate and nucleus accumbens. Pathway analyses of the 904 differentially expressed transcripts showed enrichment for genes involved in synaptic signaling, with these synapse-associated genes displaying lower expression in OCD subjects relative to unaffected comparison subjects. Finally, we estimated that cell type fractions of medium spiny neurons were lower whereas vascular cells and astrocyte fractions were higher in tissue of OCD subjects. Together, these data provide the first unbiased examination of differentially expressed transcripts in both OFC and striatum of OCD subjects. These transcripts encoded synaptic proteins more often than expected by chance, and thus implicate the synapse as a vulnerable molecular compartment for OCD.

Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5-years apart.

Pioneering studies have shown that individual correlation measures from resting-state functional magnetic resonance imaging studies can identify another scan from that same individual. This method is known as "connectotyping" or functional connectome "fingerprinting." We analyzed a unique dataset of 12-30 years old (N = 140) individuals who had two distinct resting state scans on the same day and again 12-18 months later to assess the sensitivity and specificity of fingerprinting accuracy across different time scales (same day, ~1.5 years apart) and developmental periods (youths, adults). Sensitivity and specificity to identify one's own scan was high (average AUC = 0.94), although it was significantly higher in the same day (average AUC = 0.97) than 1.5-years later (average AUC = 0.91). Accuracy in youths (average AUC = 0.93) was not significantly different from adults (average AUC = 0.96). Multiple statistical methods revealed select connections from the Frontoparietal, Default, and Dorsal Attention networks enhanced the ability to identify an individual. Identification of these features generalized across datasets and improved fingerprinting accuracy in a longitudinal replication data set (N = 208). These results provide a framework for understanding the sensitivity and specificity of fingerprinting accuracy in adolescents and adults at multiple time scales. Importantly, distinct features of one's "fingerprint" contribute to one's uniqueness, suggesting that cognitive and default networks play a primary role in the individualization of one's connectome.

Whole-Genome and RNA Sequencing Reveal Variation and Transcriptomic Coordination in the Developing Human Prefrontal Cortex.

Gene expression levels vary across developmental stage, cell type, and region in the brain. Genomic variants also contribute to the variation in expression, and some neuropsychiatric disorder loci may exert their effects through this mechanism. To investigate these relationships, we present BrainVar, a unique resource of paired whole-genome and bulk tissue RNA sequencing from the dorsolateral prefrontal cortex of 176 individuals across prenatal and postnatal development. Here we identify common variants that alter gene expression (expression quantitative trait loci [eQTLs]) constantly across development or predominantly during prenatal or postnatal stages. Both "constant" and "temporal-predominant" eQTLs are enriched for loci associated with neuropsychiatric traits and disorders and colocalize with specific variants. Expression levels of more than 12,000 genes rise or fall in a concerted late-fetal transition, with the transitional genes enriched for cell-type-specific genes and neuropsychiatric risk loci, underscoring the importance of cataloging developmental trajectories in understanding cortical physiology and pathology.

Maternal Effects as Causes of Risk for Obsessive-Compulsive Disorder.

BACKGROUND: While genetic variation has a known impact on the risk for obsessive-compulsive disorder (OCD), there is also evidence that there are maternal components to this risk. Here, we partitioned sources of variation, including direct genetic and maternal effects, on risk for OCD. METHODS: The study population consisted of 822,843 individuals from the Swedish Medical Birth Register, born in Sweden between January 1, 1982, and December 31, 1990, and followed for a diagnosis of OCD through December 31, 2013. Diagnostic information about OCD was obtained using the Swedish National Patient Register. RESULTS: A total of 7184 individuals in the birth cohort (0.87%) were diagnosed with OCD. After exploring various generalized linear mixed models to fit the diagnostic data, genetic maternal effects accounted for 7.6% (95% credible interval: 6.9%-8.3%) of the total variance in risk for OCD for the best model, and direct additive genetics accounted for 35% (95% credible interval: 32.3%-36.9%). These findings were robust under alternative models. CONCLUSIONS: Our results establish genetic maternal effects as influencing risk for OCD in offspring. We also show that additive genetic effects in OCD are overestimated when maternal effects are not modeled.

Age dependent association of inbreeding with risk for schizophrenia in Egypt.

BACKGROUND: Self-reported consanguinity is associated with risk for schizophrenia (SZ) in several inbred populations, but estimates using DNA-based coefficients of inbreeding are unavailable. Further, it is not known whether recessively inherited risk mutations can be identified through homozygosity by descent (HBD) mapping. METHODS: We studied self-reported and DNA-based estimates of inbreeding among Egyptian patients with SZ (n = 421, DSM IV criteria) and adult controls without psychosis (n = 301), who were evaluated using semi-structured diagnostic interview schedules and genotyped using the Illumina Infinium PsychArray. Following quality control checks, coefficients of inbreeding (F) and regions of homozygosity (ROH) were estimated using PLINK software for HBD analysis. Exome sequencing was conducted in selected cases. RESULTS: Inbreeding was associated with schizophrenia based on self-reported consanguinity (χ2 = 4.506, 1 df, p = 0.034) and DNA-based estimates for inbreeding (F); the latter with a significant F × age interaction (ß = 32.34, p = 0.0047). The association was most notable among patients older than age 40 years. Eleven ROH were over-represented in cases on chromosomes 1, 3, 6, 11, and 14; all but one region is novel for schizophrenia risk. Exome sequencing identified six recessively-acting genes in ROH with loss-of-function variants; one of which causes primary hereditary microcephaly. CONCLUSIONS: We propose consanguinity as an age-dependent risk factor for SZ in Egypt. HBD mapping is feasible for SZ in adequately powered samples.

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism.

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

Cohort profile: Epidemiology and Genetics of Obsessive-compulsive disorder and chronic tic disorders in Sweden (EGOS).

PURPOSE: The EGOS study (Epidemiology and Genetics of Obsessive-compulsive disorder and chronic tic disorders in Sweden) is a large-scale, epidemiological, prospective cohort that is used to identify genetic and environmental risk factors in the etiology of obsessive-compulsive disorder (OCD) and chronic tic disorders (CTD). METHODS: Individuals born between January 1954 and December 1998 with at least two diagnoses of OCD or CTD at different timepoints in the National Patient Register (NPR), and followed between January 1997 and December 2012, represent the EGOS source population (n = 20,374). The Swedish Multi-Generation Registry (MGR) are then used to define family relatedness for all cases and additional phenotypic and demographic data added to the resultant database. To create an epidemiologically valid subset of the source cohort that also includes biospecimens and additional phenotyping, we contact cases from within the source population. To date, 6832 invitations have been sent out and 1853 (27%) have elected to participate in the EGOS biospecimen collection. RESULTS: To date, 1608 biological samples have been collected, of which 1249 are genotyped and 832 supplementary Obsessive-Compulsive Inventory-Revised (OCI-R) and/or Florida Obsessive-Compulsive Inventory (FOCI) have been completed by individuals with OCD and/or CTD, age 16-64 years. DNA samples are genotyped using Infinium Global Screening Array and will undergo whole-exome sequencing in the future. Detailed information is available for each individual through linkage to the Swedish national registers, e.g., identification of additional psychiatric diagnoses, medical diagnoses, birth-related variables, and relevant demographic and social data. CONCLUSION: EGOS benefits from a genetically homogeneous sample with epidemiological ascertainment, minimizing the risk of confounding due to population stratification on ascertainment bias. In addition, this study is built upon clinical diagnoses of OCD and CTD in specialized psychiatric care, which reduces further biases and case misclassification.

Identification of common genetic risk variants for autism spectrum disorder.

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.