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

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

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

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

Comparison of Pathway Analysis Approaches Using Lung Cancer GWAS Data Sets

Pathway analysis has been proposed as a complement to single SNP analyses in GWAS. This study compared pathway analysis methods using two lung cancer GWAS data sets based on four studies: one a combined data set from Central Europe and Toronto (CETO); the other a combined data set from Germany and MD Anderson (GRMD). We searched the literature for pathway analysis methods that were widely used, representative of other methods, and had available software for performing analysis. We selected the programs EASE, which uses a modified Fishers Exact calculation to test for pathway associations, GenGen (a version of Gene Set Enrichment Analysis (GSEA)), which uses a Kolmogorov-Smirnov-like running sum statistic as the test statistic, and SLAT, which uses a p-value combination approach. We also included a modified version of the SUMSTAT method (mSUMSTAT), which tests for association by averaging χ2 statistics from genotype association tests. There were nearly 18000 genes available for analysis, following mapping of more than 300,000 SNPs from each data set. These were mapped to 421 GO level 4 gene sets for pathway analysis. Among the methods designed to be robust to biases related to gene size and pathway SNP correlation (GenGen, mSUMSTAT and SLAT), the mSUMSTAT approach identified the most significant pathways (8 in CETO and 1 in GRMD). This included a highly plausible association for the acetylcholine receptor activity pathway in both CETO (FDR≤0.001) and GRMD (FDR = 0.009), although two strong association signals at a single gene cluster (CHRNA3-CHRNA5-CHRNB4) drive this result, complicating its interpretation. Few other replicated associations were found using any of these methods. Difficulty in replicating associations hindered our comparison, but results suggest mSUMSTAT has advantages over the other approaches, and may be a useful pathway analysis tool to use alongside other methods such as the commonly used GSEA (GenGen) approach

FAN1 modifies Huntington's disease progression by stabilising the expanded HTT CAG repeat

Huntington's disease (HD) is an inherited neurodegenerative disease caused by an expanded CAG repeat in the HTT gene. CAG repeat length explains around half of the variation in age-at-onset, but genetic variation elsewhere in the genome accounts for a significant proportion of the remainder. Genome-wide association studies have identified a bidirectional signal on chromosome 15, likely underlain by FAN1 (FANCD2 and FANCI Associated Nuclease 1), a nuclease involved in DNA interstrand cross link repair. Here we show that increased FAN1 expression is significantly associated with delayed age-at-onset and slower progression of HD suggesting FAN1 is protective in the context of an expanded HTT CAG repeat. FAN1 overexpression in human cells reduces CAG repeat expansion in exogenously expressed mutant HTT exon 1, and in patient-derived stem cells and differentiated medium spiny neurons, FAN1 knockdown increases CAG repeat expansion. The stabilising effect is FAN1 concentration and CAG repeat length dependent. We show that FAN1 binds to the expanded HTT CAG repeat DNA and its nuclease activity is not required for protection against CAG repeat expansion. These data shed new mechanistic insights into how the genetic modifiers of HD act to alter disease progression, and show that FAN1 affects somatic expansion of the CAG repeat through a nuclease-independent mechanism. This provides new avenues for therapeutic interventions in HD and potentially other triplet repeat disorders

A genetic association study of glutamine-encoding DNA sequence structures, somatic CAG expansion, and DNA repair gene variants, with Huntington disease clinical outcomes

BACKGROUND: Huntington disease (HD) is caused by an unstable CAG/CAA repeat expansion encoding a toxic polyglutamine tract. Here, we tested the hypotheses that HD outcomes are impacted by somatic expansion of, and polymorphisms within, the HTT CAG/CAA glutamine-encoding repeat, and DNA repair genes. METHODS: The sequence of the glutamine-encoding repeat and the proportion of somatic CAG expansions in blood DNA from participants inheriting 40 to 50 CAG repeats within the TRACK-HD and Enroll-HD cohorts were determined using high-throughput ultra-deep-sequencing. Candidate gene polymorphisms were genotyped using kompetitive allele-specific PCR (KASP). Genotypic associations were assessed using time-to-event and regression analyses. FINDINGS: Using data from 203 TRACK-HD and 531 Enroll-HD participants, we show that individuals with higher blood DNA somatic CAG repeat expansion scores have worse HD outcomes: a one-unit increase in somatic expansion score was associated with a Cox hazard ratio for motor onset of 3·05 (95% CI = 1·94 to 4·80, p = 1·3 × 10-6). We also show that individual-specific somatic expansion scores are associated with variants in FAN1 (pFDR = 4·8 × 10-6), MLH3 (pFDR = 8·0 × 10-4), MLH1 (pFDR = 0·004) and MSH3 (pFDR = 0·009). We also show that HD outcomes are best predicted by the number of pure CAGs rather than total encoded-glutamines. INTERPRETATION: These data establish pure CAG length, rather than encoded-glutamine, as the key inherited determinant of downstream pathophysiology. These findings have implications for HD diagnostics, and support somatic expansion as a mechanistic link for genetic modifiers of clinical outcomes, a driver of disease, and potential therapeutic target in HD and related repeat expansion disorders. FUNDING: CHDI Foundation