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

Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts

Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systematic and non-cohort dependent manner. By extracting phenotype information from the free-text in such records we demonstrate that we can extend the information contained in the structured record data, and use it for producing fine-grained patient stratification and disease co-occurrence statistics. The approach uses a dictionary based on the International Classification of Disease ontology and is therefore in principle language independent. As a use case we show how records from a Danish psychiatric hospital lead to the identification of disease correlations, which subsequently can be mapped to systems biology frameworks

Elevated polygenic burden for autism is associated with differential DNA methylation at birth

This is the final version of the article. Available from BioMed Central via the DOI in this record.Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder characterized by deficits in social communication and restricted, repetitive behaviors, interests, or activities. The etiology of ASD involves both inherited and environmental risk factors, with epigenetic processes hypothesized as one mechanism by which both genetic and non-genetic variation influence gene regulation and pathogenesis. The aim of this study was to identify DNA methylation biomarkers of ASD detectable at birth.This study was supported by grant HD073978 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Environmental Health Sciences, and National Institute of Neurological Disorders and Stroke; and by the Beatrice and Samuel A. Seaver Foundation. We acknowledge iPSYCH and The Lundbeck Foundation for providing samples and funding. The iPSYCH (The Lundbeck Foundation Initiative for Integrative Psychiatric Research) team acknowledges funding from The Lundbeck Foundation (grant numbers R102-A9118 and R155–2014-1724), the Stanley Medical Research Institute, the European Research Council (project number 294838), the Novo Nordisk Foundation for supporting the Danish National Biobank resource, and grants from Aarhus and Copenhagen Universities and University Hospitals, including support to the iSEQ Center, the GenomeDK HPC facility, and the CIRRAU Center. This research has been conducted using the Danish National Biobank resource, supported by the Novo Nordisk Foundation. JM is supported by funding from the UK Medical Research Council (MR/K013807/1) and a Distinguished Investigator Award from the Brain & Behavior Research Foundation. The SEED study was supported by Centers for Disease Control and Prevention (CDC) Cooperative Agreements announced under the RFAs 01086, 02199, DD11–002, DD06–003, DD04–001, and DD09–002 and the SEED DNA methylation measurements were supported by Autism Speaks Award #7659 to MDF. SA was supported by the Burroughs-Wellcome Trust training grant: Maryland, Genetics, Epidemiology and Medicine (MD-GEM). The SSC was supported by Simons Foundation (SFARI) award and NIH grant MH089606, both awarded to STW

Restless legs syndrome is associated with major comorbidities in a population of Danish blood donors.

BACKGROUND: Restless Legs Syndrome (RLS) is characterized by uncomfortable nocturnal sensations in the legs making sedentary activities and sleep difficult, and is thus linked with psychosocial distress. Due to the symptomatology and neurobiology of RLS (disrupting brain iron and dopamine) it is likely that RLS associates with poorer health-related quality of life (HRQL) and depressive disorder. The objective of this study was to investigate the RLS-HRQL and the RLS-depressive disorder links in a generally healthy population that is not biased by medications. METHODS: Complete data, including the Cambridge-Hopkins RLS questionnaire, the 12-item short-form standardized health survey (SF-12), the Major Depression Inventory (MDI), body mass index, smoking status, alcohol consumption, and education were available for 24,707 participants enrolled in the Danish Blood Donor Study from May 1, 2015 to February 1, 2017. Information on quality of sleep was available for all RLS cases. T-tests and multivariable logistic regression models were applied to examine the associations of RLS and MDI scores, and the physical and mental component scores (PCS and MCS) of SF-12, respectively. Analyses were conducted separately for men and women. RESULTS: RLS associated with poorer MCS and poorer PCS. Moreover, Participants with RLS were more likely to classify with depressive disorder. Poor quality of sleep was associated with depressive disorder and poorer MCS among RLS cases, and with poorer PCS in female RLS cases. CONCLUSION: Thus, we demonstrated that RLS is associated with a significantly lower HRQL and a higher prevalence of depressive disorder among otherwise healthy individuals