Convergent genetic and expression data implicate immunity in Alzheimer's disease

© 2015, Elsevier Inc. All rights reserved. Background: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. Methods: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10-12 after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10-11), cholesterol transport (P = 2.96 × 10-9), and proteasome-ubiquitin activity (P = 1.34 × 10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P =.002-.05). Conclusions: The immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics.Medical Research Council, Alzheimer’s Research UK, and theWelsh Assembly Government. ADGC and CHARGE were supported by the National Institutes of Health, National Institute on Aging (NIH-NIA). CHARGE was also supported by Erasmus Medical Center and Erasmus University. IGAP was funded by the French National Foundation on Alzheimer’s Disease and Related Disorders, the Centre National de Genotypage and the Institut Pasteur de Lille, Inserm, FRC (Fondation pour la Recherche sur le Cerveau), and Rotary. This work has been developed and supported by the LABEX (Laboratory of Excellence Program Investment for the Future) DISTALZ grant (Development of Innovative Strategies for a Transdisciplinary approach to ALZheimer’s disease).Peer Reviewe

Covariate linkage analysis of GAW14 simulated data incorporating subclinical phenotype, sex, population, parent-of-origin, and interaction

BACKGROUND: We evaluate a method for the incorporation of covariates into linkage analysis using the Genetic Analysis Workshop 14 simulated data. Focusing on a randomly chosen replicate (42) we investigated the effect of the 12 subclinical phenotypes, sex, population, and parent-of-origin on the linkage signal from a model-free linkage analysis of Kofendrerd Personality Disorder. RESULTS: We detected a linkage peak on chromosome 1, at about 175 cM, which varied depending upon individuals' status for subclinical phenotype b. A linkage peak on chromosome 3 (310 cM) was found not to depend upon subclinical phenotype status. Further peaks were found on chromosomes 5 (12 cM), 9 (4 cM), and 10 (95 cM), depending on the status of subclinical phenotypes a, k, and c/d/g, respectively. CONCLUSION: Retrospective comparison of our results with the simulation model showed correct identification of disease loci D1-5 on chromosomes 1, 3, 5, 9 and 10, respectively

Large-scale linkage analysis of 1302 affected relative pairs with rheumatoid arthritis

Rheumatoid arthritis is the most common systematic autoimmune disease and its etiology is believed to have both strong genetic and environmental components. We demonstrate the utility of including genetic and clinical phenotypes as covariates within a linkage analysis framework to search for rheumatoid arthritis susceptibility loci. The raw genotypes of 1302 affected relative pairs were combined from four large family-based samples (North American Rheumatoid Arthritis Consortium, United Kingdom, European Consortium on Rheumatoid Arthritis Families, and Canada). The familiality of the clinical phenotypes was assessed. The affected relative pairs were subjected to autosomal multipoint affected relative-pair linkage analysis. Covariates were included in the linkage analysis to take account of heterogeneity within the sample. Evidence of familiality was observed with age at onset (p << 0.001) and rheumatoid factor (RF) IgM (p << 0.001), but not definite erosions (p = 0.21). Genome-wide significant evidence for linkage was observed on chromosome 6. Genome-wide suggestive evidence for linkage was observed on chromosomes 13 and 20 when conditioning on age at onset, chromosome 15 conditional on gender, and chromosome 19 conditional on RF IgM after allowing for multiple testing of covariates

Combining linkage data sets for meta-analysis and mega-analysis: the GAW15 rheumatoid arthritis data set

We have used the genome-wide marker genotypes from Genetic Analysis Workshop 15 Problem 2 to explore joint evidence for genetic linkage to rheumatoid arthritis across several samples. The data consisted of four high-density genome scans on samples selected for rheumatoid arthritis. We cleaned the data, removed intermarker linkage disequilibrium, and assembled the samples onto a common genetic map using genome sequence positions as a reference for map interpolation. The individual studies were combined first at the genotype level (mega-analysis) prior to a multipoint linkage analysis on the combined sample, and second using the genome scan meta-analysis method after linkage analysis of each sample. The two approaches were compared, and give strong support to the HLA locus on chromosome 6 as a susceptibility locus. Other regions of interest include loci on chromosomes 11, 2, and 12

Genetic modifiers of Mendelian disease: Huntington's disease and the trinucleotide repeat disorders

In the decades since the genes and mutations associated with the commoner Mendelian disorders were first discovered, technological advances in genetic analysis have made finding genomic variation a much less onerous task. Recently, the global efforts to collect subjects with Mendelian disorders, to better define the disorders and to empower appropriate clinical trials, along with improved genetic technologies, have allowed the identification of genetic variation that does not cause disease, but substantially modifies disease presentation. The advantage of this is it identifies biological pathways and molecules, that, if modified in people, might alter disease presentation. In Huntington’s disease (HD), caused by an expanded CAG repeat tract in HTT, genetic variation has been uncovered that is associated with change in the onset or progression of disease. Some of this variation lies in genes that are part of the DNA damage response, previously suggested to be important in modulating expansion of the repeat tract in germline and somatic cells. The genetic evidence implicates a DNA damage response-related pathway in modulating the pathogenicity of the repeat tracts in HD, and possibly, in other trinucleotide repeat disorders. These findings offer new targets for drug development in these currently intractable disorders

Pathway Analyses Implicate Glial Cells in Schizophrenia

Background: The quest to understand the neurobiology of schizophrenia and bipolar disorder is ongoing with multiple lines of evidence indicating abnormalities of glia, mitochondria, and glutamate in both disorders. Despite high heritability estimates of 81% for schizophrenia and 75% for bipolar disorder, compelling links between findings from neurobiological studies, and findings from large-scale genetic analyses, are only beginning to emerge. Method Ten publically available gene sets (pathways) related to glia, mitochondria, and glutamate were tested for association to schizophrenia and bipolar disorder using MAGENTA as the primary analysis method. To determine the robustness of associations, secondary analyses were performed with: ALIGATOR, INRICH, and Set Screen. Data from the Psychiatric Genomics Consortium (PGC) were used for all analyses. There were 1,068,286 SNP-level p-values for schizophrenia (9,394 cases/12,462 controls), and 2,088,878 SNP-level p-values for bipolar disorder (7,481 cases/9,250 controls). Results: The Glia-Oligodendrocyte pathway was associated with schizophrenia, after correction for multiple tests, according to primary analysis (MAGENTA p = 0.0005, 75% requirement for individual gene significance) and also achieved nominal levels of significance with INRICH (p = 0.0057) and ALIGATOR (p = 0.022). For bipolar disorder, Set Screen yielded nominally and method-wide significant associations to all three glial pathways, with strongest association to the Glia-Astrocyte pathway (p = 0.002). Conclusions: Consistent with findings of white matter abnormalities in schizophrenia by other methods of study, the Glia-Oligodendrocyte pathway was associated with schizophrenia in our genomic study. These findings suggest that the abnormalities of myelination observed in schizophrenia are at least in part due to inherited factors, contrasted with the alternative of purely environmental causes (e.g. medication effects or lifestyle). While not the primary purpose of our study, our results also highlight the consequential nature of alternative choices regarding pathway analysis, in that results varied somewhat across methods, despite application to identical datasets and pathways

Molecular genetic contribution to the developmental course of attention-deficit hyperactivity disorder

Objective: The developmental trajectory of attention-deficit hyperactivity disorder (ADHD) is variable. Utilizing a longitudinally assessed sample, we investigated the contribution of susceptibility gene variants, previously implicated through pooled or meta-analyses, to the developmental course of Attention-Deficit Hyperactivity Disorder over time. Methods: 151 children (aged 6–12) who met diagnostic criteria for ADHD were assessed using research diagnostic interviews during childhood and 5 years later in adolescence. Severity was defined as total number of ADHD symptoms at baseline and reassessment. Association with variants at DRD4, DRD5, and the dopamine transporter gene, DAT was analyzed using linear regression. Results: As expected, affected individuals showed a decline in ADHD severity over time. The DRD4 48 bp VNTR 7-repeat and DRD5 CA(n) microsatellite marker 148 bp risk alleles were associated with persistent ADHD. Those possessing the DRD4 7 repeat risk allele showed less of a decline in severity at reassessment than those without the risk allele. Conclusions: Those carrying the DRD4 7 risk allele showed greater symptom severity at follow-up and less ADHD reduction over time. These findings support the hypothesis that some susceptibility genes for ADHD also influence its developmental course

Dynamic expression of genes associated with schizophrenia and bipolar disorder across development

Common genetic variation contributes a substantial proportion of risk for both schizophrenia and bipolar disorder. Furthermore, there is evidence of significant, but not complete, overlap in genetic risk between the two disorders. It has been hypothesised that genetic variants conferring risk for these disorders do so by influencing brain development, leading to the later emergence of symptoms. The comparative profile of risk gene expression for schizophrenia and bipolar disorder across development over different brain regions however remains unclear. Using genotypes derived from genome-wide associations studies of the largest available cohorts of patients and control subjects, we investigated whether genes enriched for schizophrenia and bipolar disorder association show a bias for expression across any of 13 developmental stages in prefrontal cortical and subcortical brain regions. We show that genetic association with schizophrenia is positively correlated with expression in the prefrontal cortex during early midfetal development and early infancy, and negatively correlated with expression during late childhood, which stabilises in adolescence. In contrast, risk-associated genes for bipolar disorder did not exhibit a bias towards expression at any prenatal stage, although the pattern of postnatal expression was similar to that of schizophrenia. These results highlight the dynamic expression of genes harbouring risk for schizophrenia and bipolar disorder across prefrontal cortex development and support the hypothesis that prenatal neurodevelopmental events are more strongly associated with schizophrenia than bipolar disorder

A Population-Based Cohort Study Examining the Incidence and Impact of Psychotic Experiences From Childhood to Adulthood, and Prediction of Psychotic Disorder.

OBJECTIVE: The authors investigated the incidence, course, and outcome of psychotic experiences from childhood through early adulthood in the general population and examined prediction of psychotic disorder. METHODS: This was a population-based cohort study using the semistructured Psychosis-Like Symptoms Interview at ages 12, 18, and 24 (N=7,900 with any data). Incidence rates were estimated using flexible parametric modeling, and positive predictive values (PPVs), sensitivity, specificity, and area under the curve were estimated for prediction. RESULTS: The incidence rate of psychotic experiences increased between ages 13 and 24, peaking during late adolescence. Of 3,866 participants interviewed at age 24, 313 (8.1%, 95% CI=7.2, 9.0) had a definite psychotic experience since age 12. A total of 109 individuals (2.8%) met criteria for a psychotic disorder up to age 24, of whom 70% had sought professional help. Prediction of current psychotic disorder at age 24 (N=47, 1.2%), by both self-report and interviewer-rated measures of psychotic experiences at age 18 (PPVs, 2.9% and 10.0%, respectively), was improved by incorporating information on frequency and distress (PPVs, 13.3% and 20.0%, respectively), although sensitivities were low. The PPV of an at-risk mental state at age 18 predicting incident disorder at ages 18-24 was 21.1% (95% CI=6.1, 45.6) (sensitivity, 14.3%, 95% CI=4.0, 32.7). CONCLUSIONS: The study results show a peak in incidence of psychotic experiences during late adolescence as well as an unmet need for care in young people with psychotic disorders. Because of the low sensitivity, targeting individuals in non-help-seeking samples based only on more severe symptom cutoff thresholds will likely have little impact on population levels of first-episode psychosis.The UK Medical Research Council and Wellcome (Grant ref: 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. This study was funded by the Medical Research Council (MRC) Grant MR/M006727/1. The following authors acknowledge support: S.Z by the NIHR Biomedical Research Centre (BRC) at University Hospitals Bristol NHS Foundation Trust and the University of Bristol; A.S.D and G.H by the NIHR BRC at University College London Hospital; P.B.J. by the NIHR CLAHRC East of England, NIHR PGfAR RP-PG-0616-20003 (TYPPEX) and the Wellcome Trust Neuroscience in Psychiatry Network (095844/Z/11/Z); PCF by the Wellcome Trust (206368/Z/17/Z) and the Bernard Wolfe health Neuroscience Fund; M.C. by a European Research Council Consolidator Award (iHEAR 724809). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Car