Familial phenotype differences in PKD1111See Editorial, p. 344.

Familial phenotype differences in PKD1.BackgroundMutations within the PKD1 gene are responsible for the most common and most severe form of autosomal dominant polycystic kidney disease (ADPKD). Although it is known that there is a wide range of disease severity within PKD1 families, it is uncertain whether differences in clinical severity also occur among PKD1 families.MethodsTen large South Wales ADPKD families with at least 12 affected members were included in the study. From affected members, clinical information was obtained, including survival data and the presence of ADPKD-associated complications. Family members who were at risk of having inherited ADPKD but were proven to be non-affected were included as controls. Linkage and haplotype analysis were performed with highly polymorphic microsatellite markers closely linked to the PKD1 gene. Survival data were analyzed by the Kaplan–Meier method and the log rank test. Logistic regression analysis was used to test for differences in complication rates between families.ResultsHaplotype analysis revealed that each family had PKD1-linked disease with a unique disease-associated haplotype. Interfamily differences were observed in overall survival (P = 0.0004), renal survival (P = 0.0001), hypertension prevalence (P = 0.013), and hernia (P = 0.048). Individuals with hypertension had significantly worse overall (P = 0.0085) and renal (P = 0.03) survival compared with those without hypertension. No statistically significant differences in the prevalence of hypertension and hernia were observed among controls.ConclusionWe conclude that phenotype differences exist between PKD1 families, which, on the basis of having unique disease-associated haplotypes, are likely to be associated with a heterogeneous range of underlying PKD1 mutations

RNA-Seq of Huntington's disease patient myeloid cells reveals innate transcriptional dysregulation associated with proinflammatory pathway activation

Innate immune activation beyond the central nervous system is emerging as a vital component of the pathogenesis of neurodegeneration. Huntington's disease (HD) is a fatal neurodegenerative disorder caused by a CAG repeat expansion in the huntingtin gene. The systemic innate immune system is thought to act as a modifier of disease progression; however, the molecular mechanisms remain only partially understood. Here we use RNA-sequencing to perform whole transcriptome analysis of primary monocytes from thirty manifest HD patients and thirty-three control subjects, cultured with and without a proinflammatory stimulus. In contrast with previous studies that have required stimulation to elicit phenotypic abnormalities, we demonstrate significant transcriptional differences in HD monocytes in their basal, unstimulated state. This includes previously undetected increased resting expression of genes encoding numerous proinflammatory cytokines, such as IL6 Further pathway analysis revealed widespread resting enrichment of proinflammatory functional gene sets, while upstream regulator analysis coupled with Western blotting suggests that abnormal basal activation of the NFĸB pathway plays a key role in mediating these transcriptional changes. That HD myeloid cells have a proinflammatory phenotype in the absence of stimulation is consistent with a priming effect of mutant huntingtin, whereby basal dysfunction leads to an exaggerated inflammatory response once a stimulus is encountered. These data advance our understanding of mutant huntingtin pathogenesis, establish resting myeloid cells as a key source of HD immune dysfunction, and further demonstrate the importance of systemic immunity in the potential treatment of HD and the wider study of neurodegeneration

Reduced Cancer Incidence in Huntington's Disease: Analysis in the Registry Study

BACKGROUND: People with Huntington\u27s disease (HD) have been observed to have lower rates of cancers. OBJECTIVE: To investigate the relationship between age of onset of HD, CAG repeat length, and cancer diagnosis. METHODS: Data were obtained from the European Huntington\u27s disease network REGISTRY study for 6540 subjects. Population cancer incidence was ascertained from the GLOBOCAN database to obtain standardised incidence ratios of cancers in the REGISTRY subjects. RESULTS: 173/6528 HD REGISTRY subjects had had a cancer diagnosis. The age-standardised incidence rate of all cancers in the REGISTRY HD population was 0.26 (CI 0.22-0.30). Individual cancers showed a lower age-standardised incidence rate compared with the control population with prostate and colorectal cancers showing the lowest rates. There was no effect of CAG length on the likelihood of cancer, but a cancer diagnosis within the last year was associated with a greatly increased rate of HD onset (Hazard Ratio 18.94, p < 0.001). CONCLUSIONS: Cancer is less common than expected in the HD population, confirming previous reports. However, this does not appear to be related to CAG length in HTT. A recent diagnosis of cancer increases the risk of HD onset at any age, likely due to increased investigation following a cancer diagnosis

Parameter Estimation and Quantitative Parametric Linkage Analysis with GENEHUNTER-QMOD

Objective: We present a parametric method for linkage analysis of quantitative phenotypes. The method provides a test for linkage as well as an estimate of different phenotype parameters. We have implemented our new method in the program GENEHUNTER-QMOD and evaluated its properties by performing simulations. Methods: The phenotype is modeled as a normally distributed variable, with a separate distribution for each genotype. Parameter estimates are obtained by maximizing the LOD score over the normal distribution parameters with a gradient-based optimization called PGRAD method. Results: The PGRAD method has lower power to detect linkage than the variance components analysis (VCA) in case of a normal distribution and small pedigrees. However, it outperforms the VCA and Haseman-Elston regression for extended pedigrees, nonrandomly ascertained data and non-normally distributed phenotypes. Here, the higher power even goes along with conservativeness, while the VCA has an inflated type I error. Parameter estimation tends to underestimate residual variances but performs better for expectation values of the phenotype distributions. Conclusion: With GENEHUNTER-QMOD, a powerful new tool is provided to explicitly model quantitative phenotypes in the context of linkage analysis. It is freely available at http://www.helmholtz-muenchen.de/genepi/downloads. Copyright (C) 2012 S. Karger AG, Base

A computational analysis of abnormal belief-updating processes and their association with psychotic experiences and childhood trauma in a UK birth cohort

BACKGROUND: Psychotic experiences emerge from abnormalities in perception and belief formation, and occur more commonly in those experiencing childhood trauma. Yet, which precise aspects of belief formation are atypical in psychosis is not well understood. We used a computational modelling approach to characterise belief-updating in young adults in the general population, examine their relationship with psychotic outcomes and trauma, and the extent to which they mediate the trauma-psychosis relationship. METHODS: We used data from 3,360 individuals from the Avon Longitudinal Study of Parents and Children birth cohort who completed assessments for psychotic outcomes, depression, anxiety, and two belief-updating tasks at age 24, and had data available on traumatic events assessed from birth to late adolescence. Unadjusted and adjusted regression and counterfactual mediation methods were used for the analyses. RESULTS: Basic behavioural measures of belief-updating ('draws to decision' and 'disconfirmatory updating') were not associated with psychotic experiences. However, computational modelling revealed an association between increased decision noise with both psychotic experiences and trauma exposure, although <3% of the trauma-psychotic experience association was mediated by decision noise. Belief-updating measures were also associated with intelligence and socio-demographic characteristics, confounding most of the associations with psychotic experiences. There was little evidence that belief-updating parameters were differentially associated with delusions compared to hallucinations, or that they were differentially associated with psychotic outcomes compared to depression or anxiety. CONCLUSIONS: These findings challenge the hypothesis that atypical belief-updating mechanisms (as indexed by the computational models and behavioural measures we employed) underlie the development of psychotic phenomena

Pathway analysis for family data using nested random-effects models

Recently we proposed a novel two-step approach to test for pathway effects in disease progression. The goal of this approach is to study the joint effect of multiple single-nucleotide polymorphisms that belong to certain genes. By using random effects, our approach acknowledges the correlations within and between genes when testing for pathway effects. Gene-gene and gene-environment interactions can be included in the model. The method can be implemented with standard software, and the distribution of the test statistics under the null hypothesis can be approximated by using standard chi-square distributions. Hence no extensive permutations are needed for computations of the p-value. In this paper we adapt and apply the method to family data, and we study its performance for sequence data from Genetic Analysis Workshop 17. For the set of unrelated subjects, the performance of the new test was disappointing. We found a power of 6% for the binary outcome and of 18% for the quantitative trait Q1. For family data the new approach appears to perform well, especially for the quantitative outcome. We found a power of 39% for the binary outcome and a power of 89% for the quantitative trait Q1

High loading of polygenic risk for ADHD in children with comorbid aggression

Objective: Although attention deficit hyperactivity disorder (ADHD) is highly heritable, genome-wide association studies (GWAS) have not yet identified any common genetic variants that contribute to risk. There is evidence that aggression or conduct disorder in children with ADHD indexes higher genetic loading and clinical severity. The authors examine whether common genetic variants considered en masse as polygenic scores for ADHD are especially enriched in children with comorbid conduct disorder. Method: Polygenic scores derived from an ADHD GWAS meta-analysis were calculated in an independent ADHD sample (452 case subjects, 5,081 comparison subjects). Multivariate logistic regression analyses were employed to compare polygenic scores in the ADHD and comparison groups and test for higher scores in ADHD case subjects with comorbid conduct disorder relative to comparison subjects and relative to those without comorbid conduct disorder. Association with symptom scores was tested using linear regression. Results: Polygenic risk for ADD, derived from the meta-analysis, was higher in the independent ADHD group than in the comparison group. Polygenic score was significantly higher in ADHD case subjects with conduct disorder relative to ADHD case subjects without conduct disorder. ADHD polygenic score showed significant association with comorbid conduct disorder symptoms. This relationship was explained by,the aggression items. Conclusions: Common genetic variation is relevant to ADHD, especially in individuals with comorbid aggression. The findings suggest that the previously published ADHD GWAS meta-analysis contains weak but true associations with common variants, support for which falls below genome-wide significance levels. The findings also highlight the fact that aggression in ADHD indexes genetic as well as clinical severity

Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders