COSGAP: COntainerized Statistical Genetics Analysis Pipelines.

Summary: The collection and analysis of sensitive data in large-scale consortia for statistical genetics is hampered by multiple challenges, due to their non-shareable nature. Time-consuming issues in installing software frequently arise due to different operating systems, software dependencies, and limited internet access. For federated analysis across sites, it can be challenging to resolve different problems, including format requirements, data wrangling, setting up analysis on high-performance computing (HPC) facilities, etc. Easier, more standardized, automated protocols and pipelines can be solutions to overcome these issues. We have developed one such solution for statistical genetic data analysis using software container technologies. This solution, named COSGAP: "COntainerized Statistical Genetics Analysis Pipelines," consists of already established software tools placed into Singularity containers, alongside corresponding code and instructions on how to perform statistical genetic analyses, such as genome-wide association studies, polygenic scoring, LD score regression, Gaussian Mixture Models, and gene-set analysis. Using provided helper scripts written in Python, users can obtain auto-generated scripts to conduct the desired analysis either on HPC facilities or on a personal computer. COSGAP is actively being applied by users from different countries and projects to conduct genetic data analyses without spending much effort on software installation, converting data formats, and other technical requirements. Availability and implementation: COSGAP is freely available on GitHub (https://github.com/comorment/containers) under the GPLv3 license.

Quantifying the Relative Importance of Genetics and Environment on the Comorbidity between Mental- and Cardiometabolic Disorders: A Comprehensive Analysis of National Register Data from 17 million Scandinavians.

Mental disorders (MDs) are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders (CMDs). Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and complete genealogies of Denmark and Sweden (n=17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six MDs and 14 CMDs. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with CMDs, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with CMDs was mainly or fully driven by environmental factors. These findings provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.

Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease.

Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Using genomic data, this study elucidates biological mechanisms, key risk factors, and causal pathways underlying their comorbidity. We show that CVDs share a large proportion of their genetic risk factors with MDD. Multivariate genome-wide association analysis of the shared genetic liability between MDD and atherosclerotic CVD (ASCVD) revealed seven novel loci and distinct patterns of tissue and brain cell-type enrichments, suggesting a role for the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic, and psychosocial/lifestyle risk factors. Finally, we found support for causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and demonstrated that the causal effects were partly explained by metabolic and psychosocial/lifestyle factors. The distinct signature of MDD-ASCVD comorbidity aligns with the idea of an immunometabolic sub-type of MDD more strongly associated with CVD than overall MDD. In summary, we identify plausible biological mechanisms underlying MDD-CVD comorbidity, as well as key modifiable risk factors for prevention of CVD in individuals with MDD.

Key pathways and genes that are altered during treatment with hyperbaric oxygen in patients with sepsis due to necrotizing soft tissue infection (HBOmic study).

BACKGROUND: For decades, the basic treatment strategies of necrotizing soft tissue infections (NSTI) have remained unchanged, primarily relying on aggressive surgical removal of infected tissue, broad-spectrum antibiotics, and supportive intensive care. One treatment strategy that has been proposed as an adjunctive measure to improve patient outcomes is hyperbaric oxygen (HBO2) treatment. HBO2 treatment has been linked to several immune modulatory effects; however, investigating these effects is complicated due to the disease's acute life-threatening nature, metabolic and cell homeostasis dependent variability in treatment effects, and heterogeneity with respect to both patient characteristics and involved pathogens. To embrace this complexity, we aimed to explore the underlying biological mechanisms of HBO2 treatment in patients with NSTI on the gene expression level. METHODS: We conducted an observational cohort study on prospective collected data, including 85 patients admitted to the intensive care unit (ICU) for NSTI. All patients were treated with one or two HBO2 treatments and had one blood sample taken before and after the intervention. Total RNAs from blood samples were extracted and mRNA purified with rRNA depletion, followed by whole-transcriptome RNA sequencing with a targeted sequencing depth of 20 million reads. A model for differentially expressed genes (DEGs) was fitted, and the functional aspects of the obtained set of genes was predicted with GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of genes and Genomes) enrichment analyses. All analyses were corrected for multiple testing with FDR. RESULTS: After sequential steps of quality control, a final of 160 biological replicates were included in the present study. We found 394 protein coding genes that were significantly DEGs between the two conditions with FDR < 0.01, of which 205 were upregulated and 189 were downregulated. The enrichment analysis of these DEGs revealed 20 GO terms in biological processes and 12 KEGG pathways that were significantly overrepresented in the upregulated DEGs, of which the term; "adaptive immune response" (GO:0002250) (FDR = 9.88E-13) and "T cell receptor signaling pathway" (hsa04660) (FDR = 1.20E-07) were the most significant. Among the downregulated DEGs two biological processes were significantly enriched, of which the GO term "apoptotic process" (GO:0006915) was the most significant (FDR = 0.001), followed by "Positive regulation of T helper 1 cell cytokine production" (GO:2000556), and "NF-kappa B signaling pathway" (hsa04064) was the only KEGG pathway that was significantly overrepresented (FDR = 0.001). CONCLUSIONS: When one or two sessions of HBO2 treatment were administered to patients with a dysregulated immune response and systemic inflammation due to NSTI, the important genes that were regulated during the intervention were involved in activation of T helper cells and downregulation of the disease-induced highly inflammatory pathway NF-κB, which was associated with a decrease in the mRNA level of pro-inflammatory factors. TRIAL REGISTRATION: Biological material was collected during the INFECT study, registered at ClinicalTrials.gov (NCT01790698).

Population-based Risk of Psychiatric Disorders Associated with Recurrent CNVs.

Recurrent copy number variants (rCNVs) are associated with increased risk of neuropsychiatric disorders but their pathogenic population-level impact is unknown. We provide population-based estimates of rCNV-associated risk of neuropsychiatric disorders for 34 rCNVs in the iPSYCH2015 case-cohort sample (n=120,247). Most observed significant increases in rCNV-associated risk for ADHD, autism or schizophrenia were moderate (HR:1.42-5.00), and risk estimates were highly correlated across these disorders, the most notable exception being high autism-associated risk with Prader-Willi/Angelman Syndrome duplications (HR=20.8). No rCNV was associated with significant increase in depression risk. Also, rCNV-associated risk was positively correlated with locus size and gene constraint. Comparison with published rCNV studies suggests that prevalence of some rCNVs is higher, and risk of psychiatric disorders lower, than previously estimated. In an era where genetics is increasingly being clinically applied, our results highlight the importance of population-based risk estimates for genetics-based predictions.

Psychiatric disorders and subsequent risk of cardiovascular disease: a longitudinal matched cohort study across three countries.

Background: Several psychiatric disorders have been associated with increased risk of cardiovascular disease (CVD), however, the role of familial factors and the main disease trajectories remain unknown. Methods: In this longitudinal cohort study, we identified a cohort of 900,240 patients newly diagnosed with psychiatric disorders during January 1, 1987 and December 31, 2016, their 1,002,888 unaffected full siblings, and 1:10 age- and sex-matched reference population from nationwide medical records in Sweden, who had no prior diagnosis of CVD at enrolment. We used flexible parametric models to determine the time-varying association between first-onset psychiatric disorders and incident CVD and CVD death, comparing rates of CVD among patients with psychiatric disorders to the rates of unaffected siblings and matched reference population. We also used disease trajectory analysis to identify main disease trajectories linking psychiatric disorders to CVD. Identified associations and disease trajectories of the Swedish cohort were validated in a similar cohort from nationwide medical records in Denmark (N = 875,634 patients, same criteria during January 1, 1969 and December 31, 2016) and in Estonian cohorts from the Estonian Biobank (N = 30,656 patients, same criteria during January 1, 2006 and December 31, 2020), respectively. Findings: During up to 30 years of follow-up of the Swedish cohort, the crude incidence rate of CVD was 9.7, 7.4 and 7.0 per 1000 person-years among patients with psychiatric disorders, their unaffected siblings, and the matched reference population. Compared with their siblings, patients with psychiatric disorders experienced higher rates of CVD during the first year after diagnosis (hazard ratio [HR], 1.88; 95% confidence interval [CI], 1.79-1.98) and thereafter (1.37; 95% CI, 1.34-1.39). Similar rate increases were noted when comparing with the matched reference population. These results were replicated in the Danish cohort. We identified several disease trajectories linking psychiatric disorders to CVD in the Swedish cohort, with or without mediating medical conditions, including a direct link between psychiatric disorders and hypertensive disorder, ischemic heart disease, venous thromboembolism, angina pectoris, and stroke. These trajectories were validated in the Estonian Biobank cohort. Interpretation: Independent of familial factors, patients with psychiatric disorders are at an elevated risk of subsequent CVD, particularly during first year after diagnosis. Increased surveillance and treatment of CVDs and CVD risk factors should be considered as an integral part of clinical management, in order to reduce risk of CVD among patients with psychiatric disorders. Funding: This research was supported by EU Horizon 2020 Research and Innovation Action Grant, European Research Council Consolidator grant, Icelandic Research fund, Swedish Research Council, US NIMH, the Outstanding Clinical Discipline Project of Shanghai Pudong, the Fundamental Research Funds for the Central Universities, and the European Union through the European Regional Development Fund; the Research Council of Norway; the South-East Regional Health Authority, the Stiftelsen Kristian Gerhard Jebsen, and the EEA-RO-NO-2018-0535.

Epidemiological overview of major depressive disorder in Scandinavia using nationwide registers.

Background: Major depressive disorder (MDD) is a common psychiatric disorder associated with a high disease burden. This study gives a comprehensive overview of the prevalence, outcomes, treatment, and genetic epidemiology of MDD within and across the Scandinavian countries. Methods: This study has aimed to assess and compare across Norway, Denmark, and Sweden 1) the prevalence and trajectories of MDD and comorbidity, 2) outcomes and treatment, and 3) heritability (Denmark and Sweden only). The analyses leveraged data on 272,944 MDD cases (and 6.2 million non-cases) from Norway, Sweden, and Denmark in specialist care in national longitudinal health registers covering 1975-2013. Relying on harmonized public data global comparisons of socioeconomic and health metrics were performed to assess to what extent findings are generalizable. Findings: MDD ranked among the most prevalent psychiatric disorders. For many cases, the disorder trajectory was severe, with varying proportions experiencing recurrence, developing comorbid disorders, requiring inpatient treatment, or dying of suicide. Important country differences in specialist care prevalence and treatment were observed. Heritability estimates were moderate (35-48%). In terms of socioeconomic and health indices, the Scandinavian nations were comparable to one another and grouped with other Western nations. Interpretation: The Scandinavian countries were similar with regards to MDD epidemiological measures, but we show that differences in health care organization need to be taken into consideration when comparing countries. This study demonstrates the utility of using comprehensive population-wide registry data, outlining possibilities for other applications. The findings will be of use to policy makers for developing better prevention and intervention strategies. Funding: Swedish Research Council (Vetenskapsrådet, award D0886501 to PFS), US National Institutes of Mental HealthR01 MH123724 (to PFS), European Union's Horizon 2020 Research and Innovation Program (847776 and 964874, to OA) and European Research Council grant (grant agreement ID 101042183, to YL).

Genome-wide association study of school grades identifies genetic overlap between language ability, psychopathology and creativity.

Cognitive functions of individuals with psychiatric disorders differ from that of the general population. Such cognitive differences often manifest early in life as differential school performance and have a strong genetic basis. Here we measured genetic predictors of school performance in 30,982 individuals in English, Danish and mathematics via a genome-wide association study (GWAS) and studied their relationship with risk for six major psychiatric disorders. When decomposing the school performance into math and language-specific performances, we observed phenotypically and genetically a strong negative correlation between math performance and risk for most psychiatric disorders. But language performance correlated positively with risk for certain disorders, especially schizophrenia, which we replicate in an independent sample (n = 4547). We also found that the genetic variants relating to increased risk for schizophrenia and better language performance are overrepresented in individuals involved in creative professions (n = 2953) compared to the general population (n = 164,622). The findings together suggest that language ability, creativity and psychopathology might stem from overlapping genetic roots.

Multiallelic Copy Number Variation in ORM1 is Associated with Plasma Cell-Free DNA Levels as an Intermediate Phenotype for Venous Thromboembolism.

Venous thromboembolism (VTE) is a common disease with high heritability. However, only a small portion of the genetic variance of VTE can be explained by known genetic risk factors. Neutrophil extracellular traps (NETs) have been associated with prothrombotic activity. Therefore, the genetic basis of NETs could reveal novel risk factors for VTE. A recent genome-wide association study of plasma cell-free DNA (cfDNA) levels in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT-2) Project showed a significant associated locus near ORM1. We aimed to further explore this candidate region by next-generation sequencing, copy number variation (CNV) quantification, and expression analysis using an extreme phenotype sampling design involving 80 individuals from the GAIT-2 Project. The RETROVE study with 400 VTE cases and 400 controls was used to replicate the results. A total of 105 genetic variants and a multiallelic CNV (mCNV) spanning ORM1 were identified in GAIT-2. Of these, 17 independent common variants, a region of 22 rare variants, and the mCNV were significantly associated with cfDNA levels. In addition, eight of these common variants and the mCNV influenced ORM1 expression. The association of the mCNV and cfDNA levels was replicated in RETROVE (p-value = 1.19 × 10-6). Additional associations between the mCNV and thrombin generation parameters were identified. Our results reveal that increased mCNV dosages in ORM1 decreased gene expression and upregulated cfDNA levels. Therefore, the mCNV in ORM1 appears to be a novel marker for cfDNA levels, which could contribute to VTE risk.

Associations of psychiatric disorders with sex chromosome aneuploidies in the Danish iPSYCH2015 dataset: a case-cohort study.

BACKGROUND: Increased prevalence of mental illness has been reported in clinical studies of sex chromosome aneuploidies, but accurate population-based estimates of the prevalence and clinical detection rate of sex chromosome aneuploidies and the associated risks of psychiatric disorders are needed. In this study, we provide such estimates, valid for children and young adults of the contemporary Danish population. METHODS: We used the iPSYCH2015 case-cohort dataset, which is based on a source population of single-born individuals born in Denmark between May 1, 1981, and Dec 31, 2008. The case sample comprises all individuals from the source population with a diagnosis of any index psychiatric disorder (schizophrenia spectrum disorder, bipolar disorder, major depressive disorder, autism spectrum disorder, or ADHD) by the end of follow-up (Dec 31, 2015), registered in the hospital-based Danish Psychiatric Central Research Register. The cohort consists of individuals randomly selected from the source population, and overlaps with the case sample. Biobanked blood samples for individuals in the case and cohort samples underwent genotyping and quality-control filtering, after which we analysed microarray data to detect sex chromosome aneuploidy karyotypes (45,X, 47,XXX, 47,XXY, and 47,XYY). We estimated the population-valid prevalence of these karyotypes from the cohort sample. Weighted Cox proportional hazards models were used to estimate the risks of each index psychiatric disorder associated with each sex chromosome aneuploidy karyotype, by use of date of first hospitalisation with the index disorder in the respective case group and the cohort as outcome. The clinical detection rate was determined by comparing records of clinical diagnoses of genetic conditions from the Danish National Patient Register with sex chromosome aneuploidy karyotype determined by our study. FINDINGS: The assessed sample comprised 119 481 individuals (78 726 in the case sample and 43 326 in the cohort) who had genotyped and quality-control-filtered blood samples, including 64 533 (54%) people of gonadal male sex and 54 948 (46%) of gonadal female sex. Age during follow-up ranged from 0 to 34·7 years (mean 10·9 years [SD 3·5 years]). Information on ethnicity was not available. We identified 387 (0·3%) individuals as carriers of sex chromosome aneuploidies. The overall prevalence of sex chromosome aneuploidies was 1·5 per 1000 individuals. Each sex chromosome aneuploidy karyotype was associated with an increased risk of at least one index psychiatric disorder, with hazard ratios (HRs) of 2·20 (95% CI 1·42-3·39) for 47,XXY; 2·73 (1·25-6·00) for 47,XXX; 3·56 (1·01-12·53) for 45,X; and 4·30 (2·48-7·55) for 47,XYY. All karyotypes were associated with an increased risk of ADHD (HRs ranging from 1·99 [1·24-3·19] to 6·15 [1·63-23·19]), autism spectrum disorder (2·72 [1·72-4·32] to 8·45 [2·49-28·61]), and schizophrenia spectrum disorder (1·80 [1·15-2·80] to 4·60 [1·57-13·51]). Increased risk of major depressive disorder was found for individuals with 47,XXY (1·88 [1·07-3·33]) and 47,XYY (2·65 [1·12-5·90]), and of bipolar disorder for those with 47,XXX (4·32 [1·12-16·62]). The proportion of sex chromosome aneuploidy carriers who had been clinically diagnosed was 93% for 45,X, but lower for 47,XXY (22%), 47,XXX (15%), and 47,XYY (15%). Among carriers, the risk of diagnosis of at least one index psychiatric disorder did not significantly differ between those who had and had not been clinically diagnosed with sex chromosome aneuploidies (p=0·65). INTERPRETATION: Increased risks of psychiatric disorders associated with sex chromosome aneuploidies, combined with low rates of clinical diagnosis of sex chromosome aneuploidies, compromise the adequate provision of necessary health care and counselling to affected individuals and their families, which might be helped by increased application of genetic testing in clinical settings. FUNDING: Lundbeck Foundation and National Institutes of Health.

Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks.

Sample recruitment for research consortia, biobanks, and personal genomics companies span years, necessitating genotyping in batches, using different technologies. As marker content on genotyping arrays varies, integrating such datasets is non-trivial and its impact on haplotype estimation (phasing) and whole genome imputation, necessary steps for complex trait analysis, remains under-evaluated. Using the iPSYCH dataset, comprising 130,438 individuals, genotyped in two stages, on different arrays, we evaluated phasing and imputation performance across multiple phasing methods and data integration protocols. While phasing accuracy varied by choice of method and data integration protocol, imputation accuracy varied mostly between data integration protocols. We demonstrate an attenuation in imputation accuracy within samples of non-European origin, highlighting challenges to studying complex traits in diverse populations. Finally, imputation errors can bias association tests, reduce predictive utility of polygenic scores. Carefully optimized data integration strategies enhance accuracy and replicability of complex trait analyses in complex biobanks.

Investigating the Effects of Hyperbaric Oxygen Treatment in Necrotizing Soft Tissue Infection With Transcriptomics and Machine Learning (the HBOmic Study): Protocol for a Prospective Cohort Study With Data Validation.

BACKGROUND: Necrotizing soft tissue infections (NSTIs) are complex multifactorial diseases characterized by rapid bacterial proliferation and progressive tissue death. Treatment is multidisciplinary, including surgery, broad-spectrum antibiotics, and intensive care; adjunctive treatment with hyperbaric oxygen (HBO2) may also be applied. Recent advances in molecular technology and biological computation have given rise to new approaches to infectious diseases based on identifying target groups defined by activated pathophysiological mechanisms. OBJECTIVE: We aim to capture NSTI disease signatures and mechanisms and responses to treatment in patients that receive the highest standard of care; therefore, we set out to investigate genome-wide transcriptional responses to HBO2 treatment during NSTI in the host and bacteria. METHODS: The Effects of Hyperbaric Oxygen Treatment Studied with Omics (HBOmic) study is a prospective cohort study including 95 patients admitted for NSTI at the intensive care unit of Copenhagen University Hospital (Rigshospitalet), Denmark, between January 2013 and June 2017. All participants were treated according to a local protocol for management of NSTI, and biological samples were obtained and stored according to a standard operational procedure. In the proposed study, we will generate genome-wide expression profiles of whole-blood samples and samples of infected tissue taken before and after HBO2 treatment administered during the initial acute phase of infection, and we will analyze the profiles with unsupervised hierarchical clustering and machine learning. Differential gene expression will be compared in samples taken before and after HBO2 treatment (N=85), and integration of profiles from blood and tissue samples will be performed. Furthermore, findings will be compared to NSTI patients who did not receive HBO2 treatment (N=10). Transcriptomic data will be integrated with clinical data to investigate associations and predictors. RESULTS: The first participant was enrolled on July 27, 2021, and data analysis is expected to begin during autumn 2022, with publication of results immediately thereafter. CONCLUSIONS: The HBOmic study will provide new insights into personalized patient management in NSTIs. TRIAL REGISTRATION: ClinicalTrials.gov NCT01790698; https://clinicaltrials.gov/ct2/show/NCT01790698. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39252.

Parent-of-Origin inference for biobanks.

Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.

Cross-trait assortative mating is widespread and inflates genetic correlation estimates.

The observation of genetic correlations between disparate human traits has been interpreted as evidence of widespread pleiotropy. Here, we introduce cross-trait assortative mating (xAM) as an alternative explanation. We observe that xAM affects many phenotypes and that phenotypic cross-mate correlation estimates are strongly associated with genetic correlation estimates (R2=74%). We demonstrate that existing xAM plausibly accounts for substantial fractions of genetic correlation estimates and that previously reported genetic correlation estimates between some pairs of psychiatric disorders are congruent with xAM alone. Finally, we provide evidence for a history of xAM at the genetic level using cross-trait even/odd chromosome polygenic score correlations. Together, our results demonstrate that previous reports have likely overestimated the true genetic similarity between many phenotypes.

Integrated GWAS and Gene Expression Suggest ORM1 as a Potential Regulator of Plasma Levels of Cell-Free DNA and Thrombosis Risk.

Plasma cell-free DNA (cfDNA) is a surrogate marker of neutrophil extracellular traps (NETs) that contribute to immunothrombosis. There is growing interest about the mechanisms underlying NET formation and elevated cfDNA, but little is known about the factors involved. We aimed to identify genes involved in the regulation of cfDNA levels using data from the Genetic Analysis of Idiopathic Thrombophilia (GAIT-2) Project.Imputed genotypes, whole blood RNA-Seq data, and plasma cfDNA quantification were available for 935 of the GAIT-2 participants from 35 families with idiopathic thrombophilia. We performed heritability and GWAS analysis for cfDNA. The heritability of cfDNA was 0.26 (p = 3.7 × 10-6), while the GWAS identified a significant association (rs1687391, p = 3.55 × 10-10) near the ORM1 gene, on chromosome 9. An eQTL (expression quantitative trait loci) analysis revealed a significant association between the lead GWAS variant and the expression of ORM1 in whole blood (p = 6.14 × 10-9). Additionally, ORM1 expression correlated with levels of cfDNA (p = 4.38 × 10-4). Finally, genetic correlation analysis between cfDNA and thrombosis identified a suggestive association (ρ g = 0.43, p = 0.089).All in all, we show evidence of the role of ORM1 in regulating cfDNA levels in plasma, which might contribute to the susceptibility to thrombosis through mechanisms of immunothrombosis.

A comprehensive map of genetic relationships among diagnostic categories based on 48.6 million relative pairs from the Danish genealogy.

For more than half a century, Denmark has maintained population-wide demographic, health care, and socioeconomic registers that provide detailed information on the interaction between all residents and the extensive national social services system. We leverage this resource to reconstruct the genealogy of the entire nation based on all individuals legally residing in Denmark since 1968. We cross-reference 6,691,426 individuals with nationwide health care registers to estimate heritability and genetic correlations of 10 broad diagnostic categories involving all major organs and systems. Heritability estimates for mental disorders were consistently the highest across demographic cohorts (average h2 = 0.406, 95% CI = [0.403, 0.408]), whereas estimates for cancers were the lowest (average h2 = 0.130, 95% CI = [0.125, 0.134]). The average genetic correlation of each of the 10 diagnostic categories with the other nine was highest for gastrointestinal conditions (average rg = 0.567, 95% CI = [0.566, 0.567]) and lowest for urogenital conditions (average rg = 0.386, 95% CI = [0.385, 0.388]). Mental, pulmonary, gastrointestinal, and neurological conditions had similar genetic correlation profiles.

Genome-wide association study of febrile seizures implicates fever response and neuronal excitability genes.

Febrile seizures represent the most common type of pathological brain activity in young children and are influenced by genetic, environmental and developmental factors. In a minority of cases, febrile seizures precede later development of epilepsy. We conducted a genome-wide association study of febrile seizures in 7635 cases and 83 966 controls identifying and replicating seven new loci, all with P < 5 × 10-10. Variants at two loci were functionally related to altered expression of the fever response genes PTGER3 and IL10, and four other loci harboured genes (BSN, ERC2, GABRG2, HERC1) influencing neuronal excitability by regulating neurotransmitter release and binding, vesicular transport or membrane trafficking at the synapse. Four previously reported loci (SCN1A, SCN2A, ANO3 and 12q21.33) were all confirmed. Collectively, the seven novel and four previously reported loci explained 2.8% of the variance in liability to febrile seizures, and the single nucleotide polymorphism heritability based on all common autosomal single nucleotide polymorphisms was 10.8%. GABRG2, SCN1A and SCN2A are well-established epilepsy genes and, overall, we found positive genetic correlations with epilepsies (rg = 0.39, P = 1.68 × 10-4). Further, we found that higher polygenic risk scores for febrile seizures were associated with epilepsy and with history of hospital admission for febrile seizures. Finally, we found that polygenic risk of febrile seizures was lower in febrile seizure patients with neuropsychiatric disease compared to febrile seizure patients in a general population sample. In conclusion, this largest genetic investigation of febrile seizures to date implicates central fever response genes as well as genes affecting neuronal excitability, including several known epilepsy genes. Further functional and genetic studies based on these findings will provide important insights into the complex pathophysiological processes of seizures with and without fever.

Pleiotropy between language impairment and broader behavioral disorders-an investigation of both common and rare genetic variants.

BACKGROUND: Language plays a major role in human behavior. For this reason, neurodevelopmental and psychiatric disorders in which linguistic ability is impaired could have a big impact on the individual's social interaction and general wellbeing. Such disorders tend to have a strong genetic component, but most past studies examined mostly the linguistic overlaps across these disorders; investigations into their genetic overlaps are limited. The aim of this study was to assess the potential genetic overlap between language impairment and broader behavioral disorders employing methods capturing both common and rare genetic variants. METHODS: We employ polygenic risk scores (PRS) trained on specific language impairment (SLI) to evaluate genetic overlap across several disorders in a large case-cohort sample comprising ~13,000 autism spectrum disorder (ASD) cases, including cases of childhood autism and Asperger's syndrome, ~15,000 attention deficit/hyperactivity disorder (ADHD) cases, ~3000 schizophrenia cases, and ~21,000 population controls. We also examine rare variants in SLI/language-related genes in a subset of the sample that was exome-sequenced using the SKAT-O method. RESULTS: We find that there is little evidence for genetic overlap between SLI and ADHD, schizophrenia, and ASD, the latter being in line with results of linguistic analyses in past studies. However, we observe a small, significant genetic overlap between SLI and childhood autism specifically, which we do not observe for SLI and Asperger's syndrome. Moreover, we observe that childhood autism cases have significantly higher SLI-trained PRS compared to Asperger's syndrome cases; these results correspond well to the linguistic profiles of both disorders. Our rare variant analyses provide suggestive evidence of association for specific genes with ASD, childhood autism, and schizophrenia. CONCLUSIONS: Our study provides, for the first time, to our knowledge, genetic evidence for ASD subtypes based on risk variants for language impairment.

Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction.

A promise of genomics in precision medicine is to provide individualized genetic risk predictions. Polygenic risk scores (PRS), computed by aggregating effects from many genomic variants, have been developed as a useful tool in complex disease research. However, the application of PRS as a tool for predicting an individual's disease susceptibility in a clinical setting is challenging because PRS typically provide a relative measure of risk evaluated at the level of a group of people but not at individual level. Here, we introduce a machine-learning technique, Mondrian Cross-Conformal Prediction (MCCP), to estimate the confidence bounds of PRS-to-disease-risk prediction. MCCP can report disease status conditional probability value for each individual and give a prediction at a desired error level. Moreover, with a user-defined prediction error rate, MCCP can estimate the proportion of sample (coverage) with a correct prediction.