Biology subjects

Ryten, M.

Publications and source records attributed to Ryten, M..

5 recordsLinked to original sources

bioRxiv2018

Moving beyond neurons: the role of cell type-specific gene regulation in Parkinson’s disease heritability

Parkinsons disease (PD), with its characteristic loss of nigrostriatal dopaminergic neurons and deposition of -synuclein in neurons, is often considered a neuronal disorder. However, in recent years substantial evidence has emerged to implicate glial cell types, such as astrocytes and microglia. In this study, we used stratified LD score regression and expression-weighted cell-type enrichment together with several brain-related and cell-type-specific genomic annotations to connect human genomic PD findings to specific brain cell types. We found that PD heritability does not enrich in global and regional brain annotations or brain-related cell-type-specific annotations. Likewise, we found no enrichment of PD susceptibility genes in brain-related cell types. In contrast, we demonstrated a significant enrichment of PD heritability in a curated lysosomal gene set specifically expressed in astrocytic and microglial subtypes. Our results suggest that PD risk loci do not lie in specific cell types or individual brain regions, but rather in global cellular processes to which cell types may have varying vulnerability.

genomics↗

bioRxiv2018

Genetic variability in response to Aβ deposition influences Alzheimer’s risk

Genetic analysis of late-onset Alzheimers disease risk has previously identified a network of largely microglial genes that form a transcriptional network. In transgenic mouse models of amyloid deposition we have previously shown that the expression of many of the mouse orthologs of these genes are co-ordinately up-regulated by amyloid deposition. Here we investigate whether systematic analysis of other members of this mouse amyloid-responsive network predicts other Alzheimers risk loci. This statistical comparison of the mouse amyloid-response network with Alzheimers disease genome-wide association studies identifies 5 other genetic risk loci for the disease (OAS1, CXCL10, LAPTM5, ITGAM and LILRB4). This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimers risk.\n\nOne Sentence SummaryIdentification of 5 new risk loci for Alzheimers by statistical comparison of mouse A{beta} microglial response with gene-based SNPs from human GWAS

neuroscience↗

bioRxiv2018

Variation at the TRIM11 locus modifies Progressive Supranuclear Palsy phenotype

ObjectiveThe basis for clinical variation related to underlying Progressive Supranuclear Palsy (PSP) pathology is unknown. We performed a genome wide association study (GWAS) to identify genetic determinants of PSP phenotype.\n\nMethodsTwo independent pathological and clinically diagnosed PSP cohorts were genotyped and phenotyped to create Richardsons syndrome (RS) and non-RS groups. We carried out separate logistic regression GWAS to compare RS and non-RS groups and then combined datasets to carry out a whole cohort analysis (RS=367, non-RS=130). We validated our findings in a third cohort by referring to data from 100 deeply phenotyped cases from a recent GWAS. We assessed the expression/co-expression patterns of our identified genes and used our data to carry out gene-based association testing.\n\nResultsOur lead single nucleotide polymorphism (SNP), rs564309, showed an association signal in both cohorts, reaching genome wide significance in our whole cohort analysis - OR 5.5 (3.2-10.0), p-value 1.7x10-9. rs564309 is an intronic variant of the tripartite motif-containing protein 11 (TRIM11) gene, a component of the ubiquitin proteasome system (UPS). In our third cohort, minor allele frequencies of surrogate SNPs in high linkage disequilibrium with rs564309 replicated our findings. Gene based association testing confirmed an association signal at TRIM11. We found that TRIM11 is predominantly expressed neuronally, in the cerebellum and basal ganglia.\n\nInterpretationOur study suggests that the TRIM11 locus is a genetic modifier of PSP phenotype and potentially adds further evidence for the UPS having a key role in tau pathology, therefore representing a target for disease modifying therapies.

neuroscience↗

bioRxiv2018

G2P: Using machine learning to understand and predict genes causing rare neurological disorders

To facilitate precision medicine and neuroscience research, we developed a machine-learning technique that scores the likelihood that a gene, when mutated, will cause a neurological phenotype. We analysed 1126 genes relating to 25 subtypes of Mendelian neurological disease defined by Genomics England (March 2017) together with 154 gene-specific features capturing genetic variation, gene structure and tissue-specific expression and co-expression. We randomly re-sampled genes with no known disease association to develop bootstrapped decision-tree models, which were integrated to generate a decision tree-based ensemble for each disease subtype. Genes generating larger numbers of distinct transcripts and with higher probability of having missense mutations in normal individuals were significantly more likely to cause neurological diseases. Using mouse-mutant phenotypic data we tested the accuracy of gene-phenotype predictions and found that for 88% of all disease subtypes there was a significant enrichment of relevant phenotypic abnormalities when predicted genes were mutated in mice and in many cases mutations produced specific and matching phenotypes. Furthermore, using only newly identified genes included in the Genomics England November 2017 release, we assessed our gene-phenotype predictions and showed an 8.3 fold enrichment relative to chance for correct predictions. Thus, we demonstrate both the explanatory and predictive power of machine-learning-based models in neurological disease.

genetics↗

bioRxiv2018

A comprehensive assessment of benign genetic variability for neurodegenerative disorders

1AbstractOver the last few years, as more and more sequencing studies have been performed, it has become apparent that the identification of pathogenic mutations is, more often than not, a complex issue. Here, with a focus on neurodegenerative diseases, we have performed a survey of coding genetic variability that is unlikely to be pathogenic.\n\nWe have performed whole-exome sequencing in 478 samples derived from several brain banks in the United Kingdom and the United States of America. Samples were included when subjects were, at death, over 60 years of age, had no signs of neurological disease and were subjected to a neuropathological examination, which revealed no evidence of neurodegeneration. This information will be valuable to studies of genetic variability as a causal factor for neurodegenerative syndromes. We envisage it will be particularly relevant for diagnostic laboratories as a filter step to the results being produced by either genome-wide or gene-panel sequencing. We have made this data publicly available at www.alzforum.org/exomes/hex.

genomics↗