Identifying collagen VI as a target of fibrotic diseases regulated by CREBBP/EP300.

Fibrotic diseases remain a major cause of morbidity and mortality, yet there are few effective therapies. The underlying pathology of all fibrotic conditions is the activity of myofibroblasts. Using cells from freshly excised disease tissue from patients with Dupuytren's disease (DD), a localized fibrotic disorder of the palm, we sought to identify new therapeutic targets for fibrotic disease. We hypothesized that the persistent activity of myofibroblasts in fibrotic diseases might involve epigenetic modifications. Using a validated genetics-led target prioritization algorithm (Pi) of genome wide association studies (GWAS) data and a broad screen of epigenetic inhibitors, we found that the acetyltransferase CREBBP/EP300 is a major regulator of contractility and extracellular matrix production via control of H3K27 acetylation at the profibrotic genes, ACTA2 and COL1A1 Genomic analysis revealed that EP300 is highly enriched at enhancers associated with genes involved in multiple profibrotic pathways, and broad transcriptomic and proteomic profiling of CREBBP/EP300 inhibition by the chemical probe SGC-CBP30 identified collagen VI (Col VI) as a prominent downstream regulator of myofibroblast activity. Targeted Col VI knockdown results in significant decrease in profibrotic functions, including myofibroblast contractile force, extracellular matrix (ECM) production, chemotaxis, and wound healing. Further evidence for Col VI as a major determinant of fibrosis is its abundant expression within Dupuytren's nodules and also in the fibrotic foci of idiopathic pulmonary fibrosis (IPF). Thus, Col VI may represent a tractable therapeutic target across a range of fibrotic disorders.

Genomic Insights into Myasthenia Gravis Identify Distinct Immunological Mechanisms in Early and Late Onset Disease.

OBJECTIVE: The purpose of this study was to identify disease relevant genes and explore underlying immunological mechanisms that contribute to early and late onset forms of myasthenia gravis. METHODS: We used a novel genomic methodology to integrate genomewide association study (GWAS) findings in myasthenia gravis with cell-type specific information, such as gene expression patterns and promotor-enhancer interactions, in order to identify disease-relevant genes. Subsequently, we conducted additional genomic investigations, including an expression quantitative analysis of 313 healthy people to provide mechanistic insights. RESULTS: We identified several genes that were specifically linked to early onset myasthenia gravis including TNIP1, ORMDL3, GSDMB, and TRAF3. We showed that regulators of toll-like receptor 4 signaling were enriched among these early onset disease genes (fold enrichment = 3.85, p = 6.4 × 10-3 ). In contrast, T-cell regulators CD28 and CTLA4 were exclusively linked to late onset disease. We identified 2 causal genetic variants (rs231770 and rs231735; posterior probability = 0.98 and 0.91) near the CTLA4 gene. Subsequently, we demonstrated that these causal variants result in low expression of CTLA4 (rho = -0.66, p = 1.28 × 10-38 and rho = -0.52, p = 7.01 × 10-22 , for rs231735 and rs231770, respectively). INTERPRETATION: The disease-relevant genes identified in this study are a unique resource for many disciplines, including clinicians, scientists, and the pharmaceutical industry. The distinct immunological pathways linked to early and late onset myasthenia gravis carry important implications for drug repurposing opportunities and for future studies of drug development. ANN NEUROL 2021;90:455-463.

A flavanoid component of chocolate quickly reverses an imposed memory deficit.

The ability to remember is influenced by environmental and lifestyle factors, such as stress and diet. A flavanol contained in chocolate, epicatechin (Epi), has been shown to enhance long-term memory (LTM) formation in Lymnaea. Combining two stressors (low-calcium pond water and crowding) blocks learning and all forms of memory; that is, this combination of environmentally relevant stressors creates a memory-unfriendly state. We tested the hypothesis that Epi will immediately reverse the memory-unfriendly state, i.e. that snails in the memory-deficit state when trained in Epi will immediately become competent to learn and form memory. We found that Epi not only reverses the memory-deficit state but also further enhances LTM formation. Thus, a naturally occurring bioactive plant compound can overcome a memory-unfriendly state. This supports the idea that bioactive substances may mitigate memory-making deficits that, for example, occur with ageing.

The flavonol epicatechin reverses the suppressive effects of a stressor on long-term memory formation.

Learning and subsequent memory formation are influenced by both environmental and lifestyle factors, such as stress and diet. Epicatechin, a plant flavonol found in cocoa, red wine and green tea enhances long-term memory (LTM) formation in Lymnaea. By contrast, an ecologically relevant stressor, low-calcium pond water, suppresses LTM formation. We tested the hypothesis that epicatechin overcomes the suppressive effects of the stressor on LTM formation in the continued presence of the stressor. Snails trained in low-calcium pond water exhibit learning but not LTM. Epicatechin (15 mg l(-1)) in control pond water enhances LTM formation. When epicatechin was added to the low-calcium pond water an enhanced LTM similar to that seen in control pond water was observed. Thus, a naturally occurring bioactive plant compound was able to overcome the suppressive effects of an ecologically relevant stressor on LTM formation.

Low external environmental calcium levels prevent forgetting in Lymnaea.

Forgetting may allow an animal to react more appropriately to current conditions, rather than continuing to exhibit a previously learned, possibly maladaptive behaviour based on previous experience. One theory is that forgetting is an active process, whereby the previously learnt response is replaced by new learning that interferes with the older memory. Hence, we hypothesized that an appropriately timed environmental stressor that blocks long-term memory (LTM) formation would also block forgetting. Lymnaea stagnalis (L.) is a freshwater snail, which requires environmental calcium of at least 20 mg l(-1) to meet its requirements. Low environmental Ca(2+) (i.e. 20 mg l(-1)) in their environment acts as a stressor, and prevents LTM formation. Here, we asked whether a low Ca(2+) environment would also prevent forgetting, concordant with the retrograde interference model of Jenkins and Dallenbach. Snails were operantly conditioned to reduce aerial respiration in hypoxia. When maintained in standard conditions (80 mg l(-1) Ca(2+)), snails demonstrated LTM following training lasting 24 h, but not 72 h; however, when trained in standard conditions then exposed to a low Ca(2+) environment (20 mg l(-1)) immediately following training, they retained memory for at least 96 h, indicating that forgetting had been blocked. Thus, when exposed to low environmental Ca(2+), Lymnaea will fail to form new memories, but will also continue to retain information previously learned and remembered as the low calcium blocks forgetting.

A genetics-led approach defines the drug target landscape of 30 immune-related traits.

Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection1. Drug targets with genetic support are more likely to be therapeutically valid2,3, but the translational use of genome-scale data such as from genome-wide association studies for drug target discovery in complex diseases remains challenging4-6. Here, we show that integration of functional genomic and immune-related annotations, together with knowledge of network connectivity, maximizes the informativeness of genetics for target validation, defining the target prioritization landscape for 30 immune traits at the gene and pathway level. We demonstrate how our genetics-led drug target prioritization approach (the priority index) successfully identifies current therapeutics, predicts activity in high-throughput cellular screens (including L1000, CRISPR, mutagenesis and patient-derived cell assays), enables prioritization of under-explored targets and allows for determination of target-level trait relationships. The priority index is an open-access, scalable system accelerating early-stage drug target selection for immune-mediated disease.

XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits.

BACKGROUND: Biological interpretation of genomic summary data such as those resulting from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is one of the major bottlenecks in medical genomics research, calling for efficient and integrative tools to resolve this problem. RESULTS: We introduce eXploring Genomic Relations (XGR), an open source tool designed for enhanced interpretation of genomic summary data enabling downstream knowledge discovery. Targeting users of varying computational skills, XGR utilises prior biological knowledge and relationships in a highly integrated but easily accessible way to make user-input genomic summary datasets more interpretable. We show how by incorporating ontology, annotation, and systems biology network-driven approaches, XGR generates more informative results than conventional analyses. We apply XGR to GWAS and eQTL summary data to explore the genomic landscape of the activated innate immune response and common immunological diseases. We provide genomic evidence for a disease taxonomy supporting the concept of a disease spectrum from autoimmune to autoinflammatory disorders. We also show how XGR can define SNP-modulated gene networks and pathways that are shared and distinct between diseases, how it achieves functional, phenotypic and epigenomic annotations of genes and variants, and how it enables exploring annotation-based relationships between genetic variants. CONCLUSIONS: XGR provides a single integrated solution to enhance interpretation of genomic summary data for downstream biological discovery. XGR is released as both an R package and a web-app, freely available at http://galahad.well.ox.ac.uk/XGR .