Prevalence of rearrangements in the 22q11.2 region and population-based risk of neuropsychiatric and developmental disorders in a Danish population: a case-cohort study.

BACKGROUND: Although the pathogenic nature of copy number variants (CNVs) on chromosome 22q11.2 has been recognised for decades, unbiased estimates of their population prevalence, mortality, disease risks, and diagnostic trajectories are absent. We aimed to provide the true population prevalence of 22q11.2 CNVs and associated trajectory of disease risk and mortality by use of the unbiased, representative Danish iPSYCH population case cohort. METHODS: This case-cohort study was done on a population of 86 189 individuals selected from the iPSYCH case cohort of 1 472 762 singletons born in Denmark between May 1, 1981, and Dec 31, 2005, who have a known mother from the Danish Civil Registration System, were residents in Denmark at 1 year of age, and enrolled in the iPSYCH Initiative. We used epidemiological methods in conjunction with nationwide hospital registers to analyse the iPSYCH case cohort of individuals with attention-deficit hyperactivity disorder (ADHD), major depressive disorder, schizophrenia, autism, or bipolar disorder and a random population-based sample. The main outcomes assessed were the population prevalence of 22q11.2 rearrangements, and associated unbiased, population-adjusted estimates and 31-year disease risk trajectories for major neuropsychiatric disorders. FINDINGS: Population prevalence in the Danish population was one in 3672 (seven of 25 704 [0·027%; 95% CI 0·012-0·057]) for deletions and one in 1606 (17 of 25 704 [0·066%; 0·040-0·107]) for duplications. Mortality after the age of 1 year among carriers was zero, and hazard ratios for neuropsychiatric disorders ranged from 2·60 to 82·44 for both rearrangements. By the age of 32 years, about 10% of individuals with deletions or duplications had developed ADHD, autism, or intellectual disability, and deletion carriers had higher probability than duplication carriers of co-occurring intellectual disability or epilepsy. INTERPRETATION: The significantly different prevalence of 22q11.2 duplications and deletions indicates distinct selective pressures on these rearrangements. Although risk of congenital abnormalities, developmental delay, and intellectual disability is elevated in deletion carriers, the overall prevalence of neuropsychiatric disorders is higher in duplication carriers, which implies that identification and clinical monitoring should extend beyond congenital traits and into child and adolescent psychiatry. FUNDING: Capital Region's Research Foundation for Mental Health Research, The Lundbeck Foundation, and US National Institutes of Health.

Altered auditory processing and effective connectivity in 22q11.2 deletion syndrome.

22q11.2 deletion syndrome (22q11.2DS) is one of the most common copy number variants and confers a markedly increased risk for schizophrenia. As such, 22q11.2DS is a homogeneous genetic liability model which enables studies to delineate functional abnormalities that may precede disease onset. Mismatch negativity (MMN), a brain marker of change detection, is reduced in people with schizophrenia compared to healthy controls. Using dynamic causal modelling (DCM), previous studies showed that top-down effective connectivity linking the frontal and temporal cortex is reduced in schizophrenia relative to healthy controls in MMN tasks. In the search for early risk-markers for schizophrenia we investigated the neural basis of change detection in a group with 22q11.2DS. We recorded high-density EEG from 19 young non-psychotic 22q11.2 deletion carriers, as well as from 27 healthy non-carriers with comparable age distribution and sex ratio, while they listened to a sequence of sounds arranged in a roving oddball paradigm. Despite finding no significant reduction in the MMN responses, whole-scalp spatiotemporal analysis of responses to the tones revealed a greater fronto-temporal N1 component in the 22q11.2 deletion carriers. DCM showed reduced intrinsic connection within right primary auditory cortex as well as in the top-down, connection from the right inferior frontal gyrus to right superior temporal gyrus for 22q11.2 deletion carriers although not surviving correction for multiple comparison. We discuss these findings in terms of reduced adaptation and a general increased sensitivity to tones in 22q11.2DS.

Evaluation of shared genetic susceptibility loci between autoimmune diseases and schizophrenia based on genome-wide association studies.

BACKGROUND: Epidemiological studies have documented higher than expected comorbidity (or, in some cases, inverse comorbidity) between schizophrenia and several autoimmune disorders. It remains unknown whether this comorbidity reflects shared genetic susceptibility loci. AIMS: The present study aimed to investigate whether verified genome wide significant variants of autoimmune disorders confer risk of schizophrenia, which could suggest a common genetic basis. METHODS: Seven hundred and fourteen genome wide significant risk variants of 25 autoimmune disorders were extracted from the NHGRI GWAS catalogue and examined for association to schizophrenia in the Psychiatric Genomics Consortium schizophrenia GWAS samples (36,989 cases and 113,075 controls). RESULTS: Two independent loci at 4q24 and 6p21.32-33 originally identified from GWAS of autoimmune diseases were found genome wide associated with schizophrenia (1.7 × 10-8 ≥ p ≥ 4.0 × 10-21). While these observations confirm the existence of shared genetic susceptibility loci between schizophrenia and autoimmune diseases, the findings did not show a significant enrichment. CONCLUSION: The findings do not support a genetic overlap in common SNPs between autoimmune diseases and schizophrenia that in part could explain the observed comorbidity from epidemiological studies.

The Danish 22q11 research initiative.

BACKGROUND: Neurodevelopmental brain disorders such as schizophrenia, autism and attention deficit hyperactivity disorder are complex disorders with heterogeneous etiologies. Schizophrenia and autism are difficult to treat and often cause major individual suffering largely owing to our limited understanding of the disease biology. Thus our understanding of the biological pathogenesis needs to be substantiated to enable development of more targeted treatment options with improved efficacy. Insights into the pre-morbid disease dynamics, the morbid condition and the underlying biological disease mechanisms may come from studies of subjects with homogenous etiologies. Breakthroughs in psychiatric genetics have shown that several genetic anomalies predispose for neurodevelopmental brain disorders. We have established a Danish research initiative to study the common microdeletion at chromosome 22q11.2, which is one of the genetic anomalies that confer high risk of schizophrenia, autism and attention deficit hyperactivity disorder. METHODS/DESIGN: The study applies a "cause-to-outcome" strategy to identify pre-morbid pathogenesis and underlying biological disease mechanisms of psychosis and secondarily the morbid condition of autism and attention deficit hyperactivity disorder. We use a population based epidemiological design to inform on disease prevalence, environmental risk factors and familial disposition for mental health disorders and a case control study design to map the functional effects across behavioral and neurophysiological traits of the 22q11 deletion in a recruited sample of Danish individuals. DISCUSSION: Identification of predictive pre-morbid clinical, cognitive, functional and structural brain alterations in 22q11 deletion carriers may alter current clinical practice from symptomatic therapy of manifest mental illness into early intervention strategies, which may also be applicable to at risk subjects without known etiology. Hopefully new insights into the biological disease mechanisms, which are mandatory for novel drug developments, can improve the outcome of the pharmacological interventions in psychiatry.

Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients.

A key prerequisite for precision medicine is the estimation of disease progression from the current patient state. Disease correlations and temporal disease progression (trajectories) have mainly been analysed with focus on a small number of diseases or using large-scale approaches without time consideration, exceeding a few years. So far, no large-scale studies have focused on defining a comprehensive set of disease trajectories. Here we present a discovery-driven analysis of temporal disease progression patterns using data from an electronic health registry covering the whole population of Denmark. We use the entire spectrum of diseases and convert 14.9 years of registry data on 6.2 million patients into 1,171 significant trajectories. We group these into patterns centred on a small number of key diagnoses such as chronic obstructive pulmonary disease (COPD) and gout, which are central to disease progression and hence important to diagnose early to mitigate the risk of adverse outcomes. We suggest such trajectory analyses may be useful for predicting and preventing future diseases of individual patients.

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.