Informing disease modelling with brain-relevant functional genomic annotations

The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two

Heritability enrichment implicates microglia in Parkinson's disease pathogenesis

OBJECTIVE: Understanding how different parts of the immune system contribute to pathogenesis in Parkinson's disease is a burning challenge with important therapeutic implications. We studied enrichment of common variant heritability for Parkinson's disease stratified by immune and brain cell types. METHODS: We used summary statistics from the most recent meta-analysis of genome-wide association studies in Parkinson's disease and partitioned heritability using linkage disequilibrium score regression, stratified for specific cell types as defined by open chromatin regions. We also validated enrichment results using a polygenic risk score approach and intersected disease-associated variants with epigenetic data and expression quantitative loci to nominate and explore a putative microglial locus. RESULTS: We found significant enrichment of Parkinson's disease risk heritability in open chromatin regions of microglia and monocytes. Genomic annotations overlapped substantially between these two cell types, and only the enrichment signal for microglia remained significant in a joint model. We present evidence suggesting P2RY12, a key microglial gene and target for the anti-thrombotic agent clopidogrel, as the likely driver of a significant Parkinson's disease association signal on chromosome 3. INTERPRETATION: Our results provide further support for the importance of immune mechanisms in PD pathogenesis, highlight microglial dysregulation as a contributing etiological factor and nominate a targetable microglial gene candidate as a pathogenic player. Immune processes can be modulated by therapy, with potentially important clinical implications for future treatment in Parkinson's disease

Are Interaction-free Measurements Interaction Free?

In 1993 Elitzur and Vaidman introduced the concept of interaction-free measurements which allowed finding objects without ``touching'' them. In the proposed method, since the objects were not touched even by photons, thus, the interaction-free measurements can be called as ``seeing in the dark''. Since then several experiments have been successfully performed and various modifications were suggested. Recently, however, the validity of the term ``interaction-free'' has been questioned. The criticism of the name is briefly reviewed and the meaning of the interaction-free measurements is clarified.Comment: 11 pages, 3 eps figures. Contribution to the ICQO 2000, Raubichi, Belaru

A pilot randomised double blind controlled trial of the efficacy of purified fatty acids for the treatment of women with endometriosis-associated pain (PurFECT):study protocol

Abstract Background Endometriosis affects 6–10% of women and is associated with debilitating pelvic pain. It costs the UK > £2.8 billion per year in loss of productivity. Endometriosis can be managed by surgical excision or medically by ovarian suppression. However, ~ 75% symptoms recur after surgery and available medical treatments have undesirable side effects and are contraceptive. Omega-3 purified fatty acids (PUFA) have been shown in animal models to reduce factors that are thought to lead to endometriosis-associated pain, have minimal side effects, and no effects on fertility. This paper presents a protocol for a two-arm, pilot parallel randomised controlled trial (RCT) which aims to inform the planning of a future multicentre trial to evaluate the efficacy of Omega-3 PUFA in the management of endometriosis-associated pain in women. Methods The study will recruit women with endometriosis over a 12-month period in the National Health Service (NHS) Lothian, UK, and randomise them to 8 weeks of treatment with Omega-3 PUFA or comparator (olive oil). The primary objective is to assess recruitment and retention rates. The secondary objectives are to determine the effectiveness/acceptability to participants of the proposed methods of recruitment/randomisation/treatments/questionnaires, to inform the sample size calculation and to refine the research methodology for a future large randomised controlled trial. Response to treatment will be monitored by pain scores and questionnaires assessing physical and emotional function compared at baseline and 8 weeks. Discussion We recognise that there may be potential difficulties in mounting a large randomised controlled trial for endometriosis to assess Omega-3 PUFA because they are a dietary supplement readily available over the counter and already used by women with endometriosis. We have therefore designed this pilot study to assess practical feasibility and following the ‘Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials’ recommendations for the design of chronic pain trials. Trial registration ISRCTN4420234

CoExp: A Web Tool for the Exploitation of Co-expression Networks

Gene co-expression networks are a powerful type of analysis to construct gene groupings based on transcriptomic profiling. Co-expression networks make it possible to discover modules of genes whose mRNA levels are highly correlated across samples. Subsequent annotation of modules often reveals biological functions and/or evidence of cellular specificity for cell types implicated in the tissue being studied. There are multiple ways to perform such analyses with weighted gene co-expression network analysis (WGCNA) amongst one of the most widely used R packages. While managing a few network models can be done manually, it is often more advantageous to study a wider set of models derived from multiple independently generated transcriptomic data sets (e.g., multiple networks built from many transcriptomic sources). However, there is no software tool available that allows this to be easily achieved. Furthermore, the visual nature of co-expression networks in combination with the coding skills required to explore networks, makes the construction of a web-based platform for their management highly desirable. Here, we present the CoExp Web application, a user-friendly online tool that allows the exploitation of the full collection of 109 co-expression networks provided by the CoExpNets suite of R packages. We describe the usage of CoExp, including its contents and the functionality available through the family of CoExpNets packages. All the tools presented, including the web front- and back-ends are available for the research community so any research group can build its own suite of networks and make them accessible through their own CoExp Web application. Therefore, this paper is of interest to both researchers wishing to annotate their genes of interest across different brain network models and specialists interested in the creation of GCNs looking for a tool to appropriately manage, use, publish, and share their networks in a consistent and productive manner

Incomplete annotation has a disproportionate impact on our understanding of Mendelian and complex neurogenetic disorders

Growing evidence suggests that human gene annotation remains incomplete; however, it is unclear how this affects different tissues and our understanding of different disorders. Here, we detect previously unannotated transcription from Genotype-Tissue Expression RNA sequencing data across 41 human tissues. We connect this unannotated transcription to known genes, confirming that human gene annotation remains incomplete, even among well-studied genes including 63% of the Online Mendelian Inheritance in Man–morbid catalog and 317 neurodegeneration-associated genes. We find the greatest abundance of unannotated transcription in brain and genes highly expressed in brain are more likely to be reannotated. We explore examples of reannotated disease genes, such as SNCA, for which we experimentally validate a previously unidentified, brain-specific, potentially protein-coding exon. We release all tissue-specific transcriptomes through vizER: http://rytenlab.com/browser/app/vizER. We anticipate that this resource will facilitate more accurate genetic analysis, with the greatest impact on our understanding of Mendelian and complex neurogenetic disorders

Differential glucocorticoid metabolism in patients with persistent versus resolving inflammatory arthritis

Introduction: Impairment in the ability of the inflamed synovium to generate cortisol has been proposed to be a factor in the persistence and severity of inflammatory arthritis. In the inflamed synovium, cortisol is generated from cortisone by the 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) enzyme. The objective of this study was to determine the role of endogenous glucocorticoid metabolism in the development of persistent inflammatory arthritis. Methods: Urine samples were collected from patients with early arthritis (symptoms ≤12 weeks duration) whose final diagnostic outcomes were established after clinical follow-up and from patients with established rheumatoid arthritis (RA). All patients were free of disease-modifying anti-rheumatic drugs at the time of sample collection. Systemic measures of glucocorticoid metabolism were assessed in the urine samples by gas chromatography/mass spectrometry. Clinical data including CRP and ESR were also collected at baseline. Results: Systemic measures of 11β-HSD1 activity were significantly higher in patients with early arthritis whose disease went on to persist, and also in the subgroup of patients with persistent disease who developed RA, when compared with patients whose synovitis resolved over time. We observed a significant positive correlation between systemic 11β-HSD1 activity and ESR/CRP in patients with established RA but not in any of the early arthritis patients group. Conclusions: The present study demonstrates that patients with a new onset of synovitis whose disease subsequently resolved had significantly lower levels of systemic 11β-HSD1 activity when compared with patients whose synovitis developed into RA or other forms of persistent arthritis. Low absolute levels of 11β-HSD1 activity do not therefore appear to be a major contributor to the development of RA and it is possible that a high total body 11β-HSD1 activity during early arthritis may reduce the probability of disease resolution

Human-lineage-specific genomic elements are associated with neurodegenerative disease and APOE transcript usage.

Knowledge of genomic features specific to the human lineage may provide insights into brain-related diseases. We leverage high-depth whole genome sequencing data to generate a combined annotation identifying regions simultaneously depleted for genetic variation (constrained regions) and poorly conserved across primates. We propose that these constrained, non-conserved regions (CNCRs) have been subject to human-specific purifying selection and are enriched for brain-specific elements. We find that CNCRs are depleted from protein-coding genes but enriched within lncRNAs. We demonstrate that per-SNP heritability of a range of brain-relevant phenotypes are enriched within CNCRs. We find that genes implicated in neurological diseases have high CNCR density, including APOE, highlighting an unannotated intron-3 retention event. Using human brain RNA-sequencing data, we show the intron-3-retaining transcript to be more abundant in Alzheimer's disease with more severe tau and amyloid pathological burden. Thus, we demonstrate potential association of human-lineage-specific sequences in brain development and neurological disease

A genetic link between risk for Alzheimer's disease and severe COVID-19 outcomes via the OAS1 gene

Recently, we reported oligoadenylate synthetase 1 (OAS1) contributed to the risk of Alzheimer's disease, by its enrichment in transcriptional networks expressed by microglia. However, the function of OAS1 within microglia was not known. Using genotyping from 1313 individuals with sporadic Alzheimer's disease and 1234 control individuals, we confirm the OAS1 variant, rs1131454, is associated with increased risk for Alzheimer's disease. The same OAS1 locus has been recently associated with severe coronavirus disease 2019 (COVID-19) outcomes, linking risk for both diseases. The single nucleotide polymorphisms rs1131454(A) and rs4766676(T) are associated with Alzheimer's disease, and rs10735079(A) and rs6489867(T) are associated with severe COVID-19, where the risk alleles are linked with decreased OAS1 expression. Analysing single-cell RNA-sequencing data of myeloid cells from Alzheimer's disease and COVID-19 patients, we identify co-expression networks containing interferon (IFN)-responsive genes, including OAS1, which are significantly upregulated with age and both diseases. In human induced pluripotent stem cell-derived microglia with lowered OAS1 expression, we show exaggerated production of TNF-α with IFN-γ stimulation, indicating OAS1 is required to limit the pro-inflammatory response of myeloid cells. Collectively, our data support a link between genetic risk for Alzheimer's disease and susceptibility to critical illness with COVID-19 centred on OAS1, a finding with potential implications for future treatments of Alzheimer's disease and COVID-19, and development of biomarkers to track disease progression