An immunogenetic investigation of 30 autoimmune and autoinflammatory diseases and their links to psychiatric disorders in a nationwide sample.

Autoimmune and autoinflammatory diseases (AIIDs) involve a deficit in an individual's immune system function, whereby the immune reaction is directed against self-antigens. Many AIIDs have a strong genetic component, but they can also be triggered by environmental factors. AIIDs often have a highly negative impact on the individual's physical and mental wellbeing. Understanding the genetic underpinning of AIIDs is thus crucial both for diagnosis and for identifying individuals at high risk of an AIID and mental illness as a result thereof. The aim of the present study was to perform systematic statistical and genetic analyses to assess the role of human leukocyte antigen (HLA) alleles in 30 AIIDs and to study the links between AIIDs and psychiatric disorders. We leveraged the Danish iPSYCH Consortium sample comprising 65 534 individuals diagnosed with psychiatric disorders or selected as part of a random population sample, for whom we also had genetic data and diagnoses of AIIDs. We employed regression analysis to examine comorbidities between AIIDs and psychiatric disorders and associations between AIIDs and HLA alleles across seven HLA genes. Our comorbidity analyses showed that overall AIID and five specific AIIDs were associated with having a psychiatric diagnosis. Our genetic analyses found 81 significant associations between HLA alleles and AIIDs. Lastly, we show connections across AIIDs, psychiatric disorders and infection susceptibility through network analysis of significant HLA associations in these disease classes. Combined, our results include both novel associations as well as replications of previously reported associations in a large sample, and highlight the genetic and epidemiological links between AIIDs and psychiatric disorders.

Genetic and epidemiological analyses of infection load and its relationship with psychiatric disorders.

Severe infections and psychiatric disorders have a large impact on both society and the individual. Studies investigating these conditions and the links between them are therefore important. Most past studies have focused on binary phenotypes of particular infections or overall infection, thereby losing some information regarding susceptibility to infection as reflected in the number of specific infection types, or sites, which we term infection load. In this study we found that infection load was associated with increased risk for attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, schizophrenia and overall psychiatric diagnosis. We obtained a modest but significant heritability for infection load (h2 = 0.0221), and a high degree of genetic correlation between it and overall psychiatric diagnosis (rg = 0.4298). We also found evidence supporting a genetic causality for overall infection on overall psychiatric diagnosis. Our genome-wide association study for infection load identified 138 suggestive associations. Our study provides further evidence for genetic links between susceptibility to infection and psychiatric disorders, and suggests that a higher infection load may have a cumulative association with psychiatric disorders, beyond what has been described for individual infections.

Genome-wide association study identifies 16 genomic regions associated with circulating cytokines at birth.

Circulating inflammatory markers are essential to human health and disease, and they are often dysregulated or malfunctioning in cancers as well as in cardiovascular, metabolic, immunologic and neuropsychiatric disorders. However, the genetic contribution to the physiological variation of levels of circulating inflammatory markers is largely unknown. Here we report the results of a genome-wide genetic study of blood concentration of ten cytokines, including the hitherto unexplored calcium-binding protein (S100B). The study leverages a unique sample of neonatal blood spots from 9,459 Danish subjects from the iPSYCH initiative. We estimate the SNP-heritability of marker levels as ranging from essentially zero for Erythropoietin (EPO) up to 73% for S100B. We identify and replicate 16 associated genomic regions (p < 5 x 10-9), of which four are novel. We show that the associated variants map to enhancer elements, suggesting a possible transcriptional effect of genomic variants on the cytokine levels. The identification of the genetic architecture underlying the basic levels of cytokines is likely to prompt studies investigating the relationship between cytokines and complex disease. Our results also suggest that the genetic architecture of cytokines is stable from neonatal to adult life.

A family-based study of genetic and epigenetic effects across multiple neurocognitive, motor, social-cognitive and social-behavioral functions.

Many psychiatric and neurodevelopmental disorders are known to be heritable, but studies trying to elucidate the genetic architecture of such traits often lag behind studies of somatic traits and diseases. The reasons as to why relatively few genome-wide significant associations have been reported for such traits have to do with the sample sizes needed for the detection of small effects, the difficulty in defining and characterizing the phenotypes, partially due to overlaps in affected underlying domains (which is especially true for cognitive phenotypes), and the complex genetic architectures of the phenotypes, which are not wholly captured in traditional case-control GWAS designs. We aimed to tackle the last two issues by performing GWASs of eight quantitative neurocognitive, motor, social-cognitive and social-behavioral traits, which may be considered endophenotypes for a variety of psychiatric and neurodevelopmental conditions, and for which we employed models capturing both general genetic association and parent-of-origin effects, in a family-based sample comprising 402 children and their parents (mostly family trios). We identified 48 genome-wide significant associations across several traits, of which 3 also survived our strict study-wide quality criteria. We additionally performed a functional annotation of implicated genes, as most of the 48 associations were with variants within protein-coding genes. In total, our study highlighted associations with five genes (TGM3, CACNB4, ANKS1B, CSMD1 and SYNE1) associated with measures of working memory, processing speed and social behavior. Our results thus identify novel associations, including previously unreported parent-of-origin associations with relevant genes, and our top results illustrate new potential gene → endophenotype → disorder pathways.

A large-scale investigation into the role of classical HLA loci in multiple types of severe infections, with a focus on overlaps with autoimmune and mental disorders.

BACKGROUND: Infections are a major disease burden worldwide. While they are caused by external pathogens, host genetics also plays a part in susceptibility to infections. Past studies have reported diverse associations between human leukocyte antigen (HLA) alleles and infections, but many were limited by small sample sizes and/or focused on only one infection. METHODS: We performed an immunogenetic association study examining 13 categories of severe infection (bacterial, viral, central nervous system, gastrointestinal, genital, hepatitis, otitis, pregnancy-related, respiratory, sepsis, skin infection, urological and other infections), as well as a phenotype for having any infection, and seven classical HLA loci (HLA-A, B, C, DPB1, DQA1, DQB1 and DRB1). Additionally, we examined associations between infections and specific alleles highlighted in our previous studies of psychiatric disorders and autoimmune disease, as these conditions are known to be linked to infections. RESULTS: Associations between HLA loci and infections were generally not strong. Highlighted associations included associations between DQB1*0302 and DQB1*0604 and viral infections (P = 0.002835 and P = 0.014332, respectively), DQB1*0503 and sepsis (P = 0.006053), and DQA1*0301 with "other" infections (a category which includes infections not included in our main categories e.g. protozoan infections) (P = 0.000369). Some HLA alleles implicated in autoimmune diseases showed association with susceptibility to infections, but the latter associations were generally weaker, or with opposite trends (in the case of HLA-C alleles, but not with alleles of HLA class II genes). HLA alleles associated with psychiatric disorders did not show association with susceptibility to infections. CONCLUSIONS: Our results suggest that classical HLA alleles do not play a large role in the etiology of severe infections. The discordant association trends with autoimmune disease for some alleles could contribute to mechanistic theories of disease etiology.

Genetic factors underlying the bidirectional relationship between autoimmune and mental disorders - Findings from a Danish population-based study.

BACKGROUND: Previous studies have indicated the bidirectionality between autoimmune and mental disorders. However, genetic studies underpinning the co-occurrence of the two disorders have been lacking. In this study, we examined the potential genetic contribution to the association between autoimmune and mental disorders and investigated the genetic basis of overall autoimmune disease. METHODS: We used diagnostic information from patients with seven autoimmune diseases and six mental disorders from the Danish population-based case-cohort sample (iPSYCH2012). We explored the epidemiological association using survival analysis and modelled the effect of polygenic risk scores (PRSs) on autoimmune and mental diseases. Genetic factors were investigated using GWAS and imputed HLA alleles in the iPSYCH cohort. RESULTS: Of 64,039 individuals, a total of 43,902 (68.6%) were diagnosed with mental disorders and 1383 (2.2%) with autoimmune diseases. There was a significant comorbidity between the two disease classes (P = 2.67 × 10-7, OR = 1.38, 95%CI = 1.22-1.56), with an overall bidirectional association, wherein individuals with autoimmune diseases had an increased risk of subsequent mental disorders (HR = 1.13, 95%CI: 1.07-1.21, P = 7.95 × 10-5) and vice versa (HR = 1.27, 95%CI = 1.16-1.39, P = 8.77 × 10-15). Adding PRSs to these adjustment models did not have an impact on the associations. PRSs for autoimmune diseases were only slightly associated with increased risk of mental disorders (HR = 1.01, 95%CI: 1.00-1.02, p = 0.038), whereas PRSs for mental disorders were not associated with autoimmune diseases overall. Our GWAS highlighted 12 loci on chromosome 6 (minimum P = 2.74 × 10-36, OR = 1.80, 95% CI: 1.64-1.96), which were implicated in gene regulation through bioinformatic functional analyses, thereby identifying new candidate genes for overall autoimmune disease. Moreover, we observed 20 human leukocyte antigen (HLA) alleles strongly associated, either positively or negatively, with overall autoimmune disease, but we did not find significant evidence of their associations with overall mental disorders. A GWAS of a comorbid diagnosis of an autoimmune disease and a mental disorder identified a genome-wide significant locus on chromosome 7 as well (P = 1.43 × 10-8, OR = 10.65, 95%CI = 3.21-35.36). CONCLUSIONS: Our findings confirm the overall comorbidity and bidirectionality between autoimmune diseases and mental disorders and identify HLA genes which are significantly associated with overall autoimmune disease. Additionally, we identified several new candidate genes for overall autoimmune disease and ranked them based on their association with the investigated diseases.

Genetics of suicide attempts in individuals with and without mental disorders: a population-based genome-wide association study.

Family studies have shown an aggregation of suicidal behavior in families. Yet, molecular studies are needed to identify loci accounting for genetic heritability. We conducted a genome-wide association study and estimated single nucleotide polymorphisms (SNP) heritability for a suicide attempt. In a case-cohort study, national data on all individuals born in Denmark after 1981 and diagnosed with severe mental disorders prior to 2013 (n = 57,377) and individuals from the general population (n = 30,000) were obtained. After quality control, the sample consisted of 6024 cases with an incidence of suicide attempt and 44,240 controls with no record of a suicide attempt. Suggestive associations between SNPs, rs6880062 (p-value: 5.4 × 10-8) and rs6880461 (p-value: 9.5 × 10-8), and suicide attempt were identified when adjusting for socio-demographics. Adjusting for mental disorders, three significant associations, all on chromosome 20, were identified: rs4809706 (p-value: 2.8 × 10-8), rs4810824 (p-value: 3.5 × 10-8), and rs6019297 (p-value: 4.7 × 108). Sub-group analysis of cases with affective disorders revealed SNPs associated with suicide attempts when compared to the general population for gene PDE4B. All SNPs explained 4.6% [CI-95: 2.9-6.3%] of the variation in suicide attempt. Controlling for mental disorders reduced the heritability to 1.9% [CI-95: 0.3-3.5%]. Affective and autism spectrum disorders exhibited a SNP heritability of 5.6% [CI-95: 1.9-9.3%] and 9.6% [CI-95: 1.1-18.1%], respectively. Using the largest sample to date, we identified significant SNP associations with suicide attempts and support for a genetic transmission of suicide attempt, which might not solely be explained by mental disorders.

A large population-based investigation into the genetics of susceptibility to gastrointestinal infections and the link between gastrointestinal infections and mental illness.

Gastrointestinal infections can be life threatening, but not much is known about the host's genetic contribution to susceptibility to gastrointestinal infections or the latter's association with psychiatric disorders. We utilized iPSYCH, a genotyped population-based sample of individuals born between 1981 and 2005 comprising 65,534 unrelated Danish individuals (45,889 diagnosed with mental disorders and 19,645 controls from a random population sample) in which all individuals were linked utilizing nationwide population-based registers to estimate the genetic contribution to susceptibility to gastrointestinal infections, identify genetic variants associated with gastrointestinal infections, and examine the link between gastrointestinal infections and psychiatric and neurodevelopmental disorders. The SNP heritability of susceptibility to gastrointestinal infections ranged from 3.7% to 6.4% on the liability scale. Significant correlations were found between gastrointestinal infections and the combined group of mental disorders (OR = 2.09; 95% CI: 1.82-2.4, P = 1.87 × 10-25). Correlations with autism spectrum disorder, attention deficit hyperactivity disorder, and depression were also significant. We identified a genome-wide significant locus associated with susceptibility to gastrointestinal infections (OR = 1.13; 95% CI: 1.08-1.18, P = 2.9 × 10-8), where the top SNP was an eQTL for the ABO gene. The risk allele was associated with reduced ABO expression, providing, for the first time, genetic evidence to support previous studies linking the O blood group to gastrointestinal infections. This study also highlights the importance of integrative work in genetics, psychiatry, infection, and epidemiology on the road to translational medicine.

Quantitative genome-wide association analyses of receptive language in the Danish High Risk and Resilience Study.

BACKGROUND: One of the most basic human traits is language. Linguistic ability, and disability, have been shown to have a strong genetic component in family and twin studies, but molecular genetic studies of language phenotypes are scarce, relative to studies of other cognitive traits and neurodevelopmental phenotypes. Moreover, most genetic studies examining such phenotypes do not incorporate parent-of-origin effects, which could account for some of the heritability of the investigated trait. We performed a genome-wide association study of receptive language, examining both child genetic effects and parent-of-origin effects. RESULTS: Using a family-based cohort with 400 children with receptive language scores, we found a genome-wide significant paternal parent-of-origin effect with a SNP, rs11787922, on chromosome 9q21.31, whereby the T allele reduced the mean receptive language score by ~ 23, constituting a reduction of more than 1.5 times the population SD (P = 1.04 × 10-8). We further confirmed that this association was not driven by broader neurodevelopmental diagnoses in the child or a family history of psychiatric diagnoses by incorporating covariates for the above and repeating the analysis. CONCLUSIONS: Our study reports a genome-wide significant association for receptive language skills; to our knowledge, this is the first documented genome-wide significant association for this phenotype. Furthermore, our study illustrates the importance of considering parent-of-origin effects in association studies, particularly in the case of cognitive or neurodevelopmental traits, in which parental genetic data are not always incorporated.

MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search.

The MalaCards human disease database (http://www.malacards.org/) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ∼20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards' affiliation with the GeneCards Suite of databases. MalaCards' capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a 'flat' disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny.

Increased Power for Detection of Parent-of-Origin Effects via the Use of Haplotype Estimation.

Parent-of-origin (or imprinting) effects relate to the situation in which traits are influenced by the allele inherited from only one parent and the allele from the other parent has little or no effect. Given SNP genotype data from case-parent trios, the parent of origin of each allele in the offspring can often be deduced unambiguously; however, this is not true when all three individuals are heterozygous. Most existing methods for investigating parent-of-origin effects operate on a SNP-by-SNP basis and either perform some sort of averaging over the possible parental transmissions or else discard ambiguous trios. If the correct parent of origin at a SNP could be determined, this would provide extra information and increase the power for detecting the effects of imprinting. We propose making use of the surrounding SNP information, via haplotype estimation, to improve estimation of parent of origin at a test SNP for case-parent trios, case-mother duos, and case-father duos. This extra information is then used in a multinomial modeling approach for estimating parent-of-origin effects at the test SNP. We show through computer simulations that our approach has increased power over previous approaches, particularly when the data consist only of duos. We apply our method to two real datasets and find a decrease in significance of p values in genomic regions previously thought to possibly harbor imprinting effects, thus weakening the evidence that such effects actually exist in these regions, although some regions retain evidence of significant effects.

Exome sequencing in an admixed isolated population indicates NFXL1 variants confer a risk for specific language impairment.

Children affected by Specific Language Impairment (SLI) fail to acquire age appropriate language skills despite adequate intelligence and opportunity. SLI is highly heritable, but the understanding of underlying genetic mechanisms has proved challenging. In this study, we use molecular genetic techniques to investigate an admixed isolated founder population from the Robinson Crusoe Island (Chile), who are affected by a high incidence of SLI, increasing the power to discover contributory genetic factors. We utilize exome sequencing in selected individuals from this population to identify eight coding variants that are of putative significance. We then apply association analyses across the wider population to highlight a single rare coding variant (rs144169475, Minor Allele Frequency of 4.1% in admixed South American populations) in the NFXL1 gene that confers a nonsynonymous change (N150K) and is significantly associated with language impairment in the Robinson Crusoe population (p = 2.04 × 10-4, 8 variants tested). Subsequent sequencing of NFXL1 in 117 UK SLI cases identified four individuals with heterozygous variants predicted to be of functional consequence. We conclude that coding variants within NFXL1 confer an increased risk of SLI within a complex genetic model.

Rational confederation of genes and diseases: NGS interpretation via GeneCards, MalaCards and VarElect.

BACKGROUND: A key challenge in the realm of human disease research is next generation sequencing (NGS) interpretation, whereby identified filtered variant-harboring genes are associated with a patient's disease phenotypes. This necessitates bioinformatics tools linked to comprehensive knowledgebases. The GeneCards suite databases, which include GeneCards (human genes), MalaCards (human diseases) and PathCards (human pathways) together with additional tools, are presented with the focus on MalaCards utility for NGS interpretation as well as for large scale bioinformatic analyses. RESULTS: VarElect, our NGS interpretation tool, leverages the broad information in the GeneCards suite databases. MalaCards algorithms unify disease-related terms and annotations from 69 sources. Further, MalaCards defines hierarchical relatedness-aliases, disease families, a related diseases network, categories and ontological classifications. GeneCards and MalaCards delineate and share a multi-tiered, scored gene-disease network, with stringency levels, including the definition of elite status-high quality gene-disease pairs, coming from manually curated trustworthy sources, that includes 4500 genes for 8000 diseases. This unique resource is key to NGS interpretation by VarElect. VarElect, a comprehensive search tool that helps infer both direct and indirect links between genes and user-supplied disease/phenotype terms, is robustly strengthened by the information found in MalaCards. The indirect mode benefits from GeneCards' diverse gene-to-gene relationships, including SuperPaths-integrated biological pathways from 12 information sources. We are currently adding an important information layer in the form of "disease SuperPaths", generated from the gene-disease matrix by an algorithm similar to that previously employed for biological pathway unification. This allows the discovery of novel gene-disease and disease-disease relationships. The advent of whole genome sequencing necessitates capacities to go beyond protein coding genes. GeneCards is highly useful in this respect, as it also addresses 101,976 non-protein-coding RNA genes. In a more recent development, we are currently adding an inclusive map of regulatory elements and their inferred target genes, generated by integration from 4 resources. CONCLUSIONS: MalaCards provides a rich big-data scaffold for in silico biomedical discovery within the gene-disease universe. VarElect, which depends significantly on both GeneCards and MalaCards power, is a potent tool for supporting the interpretation of wet-lab experiments, notably NGS analyses of disease. The GeneCards suite has thus transcended its 2-decade role in biomedical research, maturing into a key player in clinical investigation.

VarElect: the phenotype-based variation prioritizer of the GeneCards Suite.

BACKGROUND: Next generation sequencing (NGS) provides a key technology for deciphering the genetic underpinnings of human diseases. Typical NGS analyses of a patient depict tens of thousands non-reference coding variants, but only one or very few are expected to be significant for the relevant disorder. In a filtering stage, one employs family segregation, rarity in the population, predicted protein impact and evolutionary conservation as a means for shortening the variation list. However, narrowing down further towards culprit disease genes usually entails laborious seeking of gene-phenotype relationships, consulting numerous separate databases. Thus, a major challenge is to transition from the few hundred shortlisted genes to the most viable disease-causing candidates. RESULTS: We describe a novel tool, VarElect ( http://ve.genecards.org ), a comprehensive phenotype-dependent variant/gene prioritizer, based on the widely-used GeneCards, which helps rapidly identify causal mutations with extensive evidence. The GeneCards suite offers an effective and speedy alternative, whereby >120 gene-centric automatically-mined data sources are jointly available for the task. VarElect cashes on this wealth of information, as well as on GeneCards' powerful free-text Boolean search and scoring capabilities, proficiently matching variant-containing genes to submitted disease/symptom keywords. The tool also leverages the rich disease and pathway information of MalaCards, the human disease database, and PathCards, the unified pathway (SuperPaths) database, both within the GeneCards Suite. The VarElect algorithm infers direct as well as indirect links between genes and phenotypes, the latter benefitting from GeneCards' diverse gene-to-gene data links in GenesLikeMe. Finally, our tool offers an extensive gene-phenotype evidence portrayal ("MiniCards") and hyperlinks to the parent databases. CONCLUSIONS: We demonstrate that VarElect compares favorably with several often-used NGS phenotyping tools, thus providing a robust facility for ranking genes, pointing out their likelihood to be related to a patient's disease. VarElect's capacity to automatically process numerous NGS cases, either in stand-alone format or in VCF-analyzer mode (TGex and VarAnnot), is indispensable for emerging clinical projects that involve thousands of whole exome/genome NGS analyses.

Circulating S100B levels at birth and risk of six major neuropsychiatric or neurological disorders: a two-sample Mendelian Randomization Study.

Circulating levels of the astrocytic marker S100B have been associated with risk of neuropsychiatric or neurological disorders. However, reported effects have been inconsistent, and no causal relations have yet been established. We applied two-sample Mendelian Randomization (MR) on the association statistics from genome-wide association studies (GWAS) for circulating S100B levels measured 5-7 days after birth (the iPSYCH sample) and in an older adult sample (mean age, 72.5 years; the Lothian sample), upon those derived from major depression disorder (MDD), schizophrenia (SCZ), bipolar disorder (BIP), autism spectral disorder (ASD), Alzheimer's disease (AD), and Parkinson's disease (PD). We studied the causal relations in the two S100B datasets for risk of these six neuropsychiatric disorders. MR suggested increased S100B levels 5-7 days after birth to causally increase the risk of MDD (OR = 1.014; 95%CI = 1.007-1.022; FDR-corrected p = 6.43×10-4). In older adults, MR suggested increased S100B levels to have a causal relation to the risk of BIP (OR = 1.075; 95%CI = 1.026-1.127; FDR-corrected p = 1.35×10-2). No significant causal relations were found for the other five disorders. We did not observe any evidence for reverse causality of these neuropsychiatric or neurological disorders on altered S100B levels. Sensitivity analyses using more stringent SNP-selection criteria and three alternative MR models suggested the results are robust. Altogether, our findings imply a small cause-effect relation for the previously reported associations of S100B and mood disorders. Such findings may provide a novel avenue for the diagnosis and management of disorders.

Developmental language disorder - a comprehensive study of more than 46,000 individuals.

Developmental language disorder (DLD) is characterized by enduring low language abilities with a significant functional impact, in the absence of biomedical conditions in which language impairment is part of a complex of impairments. There is a lack of awareness of DLD even among healthcare professionals. Here we estimated the prevalence of DLD and its links to reading and learning difficulties and physical and mental health in the Danish Blood Donor Study (N = 46,547), where DLD-related information is based on questionnaires (self-report). We compared the questionnaire-derived DLD status with the relevant language-related diagnoses from hospital registers. We also investigated the genetic architecture of DLD in a subset of the cohort (N = 18,380). DLD was significantly associated with reading and learning difficulties and poorer mental and physical health. DLD prevalence was 3.36%-3.70% based on questionnaires, compared with 0.04% in hospital registers. Our genetic analyses identified one genome-wide significant locus, but not a significant heritability estimate. Our study shows that DLD has health-related implications that may last into adulthood, and that DLD may be undiagnosed in general healthcare. Furthermore, DLD is likely more genetically heterogeneous than narrower developmental language phenotypes. Our results emphasize the need to raise awareness of DLD and consider criteria for molecular studies of DLD to reduce case heterogeneity.

A study of the genetic architecture of social responsiveness in families with parental schizophrenia or bipolar disorder and population-based controls.

Twin-studies of social responsiveness have reported moderate to high heritabilities, but studies using parent-child data are lacking. Additionally, social impairments have been suggested as a vulnerability marker for schizophrenia and bipolar disorder, but the heritability of social responsiveness in this context is unknown. This study is part of the Danish High Risk and Resilience Study - VIA, comprising families with one parent with schizophrenia (n = 202) or bipolar disorder (n = 120) and population-based controls (PBC, n = 200). Social responsiveness was assessed with The Social Responsiveness Scale, Second Edition (SRS-2). Heritability was estimated from variance components, and a polygenic risk score (PRS) for autism spectrum disorder (ASD) was calculated to assess the genetic relationship between ASD and SRS-2. SRS-2 heritability was moderate to high and significantly different from zero in all groups when the children were rated by the primary caregiver. With teacher ratings, the heritability was lower and only significant in the full cohort and PBC. We found no significant association between SRS-2 and PRS for ASD. Our study confirms that social responsiveness is heritable, but that heritability estimates are affected by the child-respondent relation and familial risk of mental illness. This has implications for clinical practice and research using SRS-2 and provides insight on the familial transmission of mental illness.

Maternal pregnancy-related infections and autism spectrum disorder-the genetic perspective.

Autism spectrum disorder (ASD) refers to a group of neurodevelopmental disorders which include deficits in behavior, social interaction and communication. ASD has a complex genetic architecture, and it is also influenced by certain environmental exposures. Both types of predisposing factors may be related to immunological mechanisms, involving, for example, immune system genes and infections. Past studies have shown an association between infections occurring during the pregnancy in the mother and increased risk of ASD in the child, an observation which has received recent support from experimental animal studies of ASD-like behavior. The aim of this study was to study the genetic contribution to this effect. We employed genetic correlation analyses across potential ASD subtypes stratified on the basis of maternal pregnancy-related infections within the iPSYCH ASD case-cohort sample, as well as a case-case GWAS. We validated the trends of the genetic correlation analyses observed in our sample using GWAS summary statistics from the PGC ASD study (excluding iPSYCH). The genetic correlation between ASD with a history of maternal pregnancy-related infections and ASD without a history of maternal infections in iPSYCH was rg = 0.3811. We obtained a similar estimate between the former and the PGC ASD phenotype (rg = 0.3997). Both estimates are lower compared to the genetic correlation between ASD without a history of maternal infections and the PGC ASD phenotype (rg = 0.6735), and between ASD with a history of maternal infections occurring only more than 2 months following childbirth and the PGC ASD phenotype (rg = 0.6293). Additionally, we observed genetic variance between the two main ASD phenotypes using summary statistics from the case-case GWAS in iPSYCH (h2cc = 0.1059), indicating genome-wide differences between the phenotypes. Our results suggest potentially different etiologies of ASD based on a history of maternal pregnancy-related infections, which may, in part, be genetic. This highlights the relevance of maternal pregnancy-related infections to genetic studies of ASD and provides new insights into the molecular underpinnings of ASD.