The Decay of Disease Association with Declining Linkage Disequilibrium: A Fine Mapping Theorem

Several important and fundamental aspects of disease genetics models have yet to be described. One such property is the relationship of disease association statistics at a marker site closely linked to a disease causing site. A complete description of this two-locus system is of particular importance to experimental efforts to fine map association signals for complex diseases. Here, we present a simple relationship between disease association statistics and the decline of linkage disequilibrium from a causal site. Specifically, the ratio of Chi-square disease association statistics at a marker site and causal site is equivalent to the standard measure of pairwise linkage disequilibrium, r2. A complete derivation of this relationship from a general disease model is shown. Quite interestingly, this relationship holds across all modes of inheritance. Extensive Monte Carlo simulations using a disease genetics model applied to chromosomes subjected to a standard model of recombination are employed to better understand the variation around this fine mapping theorem due to sampling effects. We also use this relationship to provide a framework for estimating properties of a non-interrogated causal site using data at closely linked markers. Lastly, we apply this way of examining association data from high-density genotyping in a large, publicly-available data set investigating extreme BMI. We anticipate that understanding the patterns of disease association decay with declining linkage disequilibrium from a causal site will enable more powerful fine mapping methods and provide new avenues for identifying causal sites/genes from fine-mapping studies

Pathogenic Mutations in Cancer-Predisposing Genes: A Survey of 300 Patients with Whole-Genome Sequencing and Lifetime Electronic Health Records

Background: It is unclear whether and how whole-genome sequencing (WGS) data can be used to implement genomic medicine. Our objective is to retrospectively evaluate whether WGS can facilitate improving prevention and care for patients with susceptibility to cancer syndromes. Methods and Findings: We analyzed genetic mutations in 60 autosomal dominant cancer-predisposition genes in 300 deceased patients with WGS data and nearly complete long-term (over 30 years) medical records. To infer biological insights from massive amounts of WGS data and comprehensive clinical data in a short period of time, we developed an in-house analysis pipeline within the SeqHBase software framework to quickly identify pathogenic or likely pathogenic variants. The clinical data of the patients who carried pathogenic and/or likely pathogenic variants were further reviewed to assess their clinical conditions using their lifetime EHRs. Among the 300 participants, 5 (1.7%) carried pathogenic or likely pathogenic variants in 5 cancer-predisposing genes: one in APC, BRCA1, BRCA2, NF1, and TP53 each. When assessing the clinical data, each of the 5 patients had one or more different types of cancers, fully consistent with their genetic profiles. Among these 5 patients, 2 died due to cancer while the others had multiple disorders later in their lifetimes; however, they may have benefited from early diagnosis and treatment for healthier lives, had the patients had genetic testing in their earlier lifetimes. Conclusions: We demonstrated a case study where the discovery of pathogenic or likely pathogenic germline mutations from population-wide WGS correlates with clinical outcome. The use of WGS may have clinical impacts to improve healthcare delivery

Identification of LIMK2 as a therapeutic target in castration resistant prostate cancer

This study identified LIMK2 kinase as a disease-specific target in castration resistant prostate cancer (CRPC) pathogenesis, which is upregulated in response to androgen deprivation therapy, the current standard of treatment for prostate cancer. Surgical castration increases LIMK2 expression in mouse prostates due to increased hypoxia. Similarly, human clinical specimens showed highest LIMK2 levels in CRPC tissues compared to other stages, while minimal LIMK2 was observed in normal prostates. Most notably, inducible knockdown of LIMK2 fully reverses CRPC tumorigenesis in castrated mice, underscoring its potential as a clinical target for CRPC. We also identified TWIST1 as a direct substrate of LIMK2, which uncovered the molecular mechanism of LIMK2-induced malignancy. TWIST1 is strongly associated with CRPC initiation, progression and poor prognosis. LIMK2 increases TWIST1 mRNA levels upon hypoxia; and stabilizes TWIST1 by direct phosphorylation. TWIST1 also stabilizes LIMK2 by inhibiting its ubiquitylation. Phosphorylation-dead TWIST1 acts as dominant negative and fully prevents EMT and tumor formation in vivo, thereby highlighting the significance of LIMK2-TWIST1 signaling axis in CRPC. As LIMK2 null mice are viable, targeting LIMK2 should have minimal collateral toxicity, thereby improving the overall survival of CRPC patients

Genome-scale metabolic model of the rat liver predicts effects of diet restriction.

Mapping network analysis in cells and tissues can provide insights into metabolic adaptations to changes in external environment, pathological conditions, and nutrient deprivation. Here, we reconstructed a genome-scale metabolic network of the rat liver that will allow for exploration of systems-level physiology. The resulting in silico model (iRatLiver) contains 1,882 reactions, 1,448 metabolites, and 994 metabolic genes. We then used this model to characterize the response of the liver\u27s energy metabolism to a controlled perturbation in diet. Transcriptomics data were collected from the livers of Sprague Dawley rats at 4 or 14 days of being subjected to 15%, 30%, or 60% diet restriction. These data were integrated with the iRatLiver model to generate condition-specific metabolic models, allowing us to explore network differences under each condition. We observed different pathway usage between early and late time points. Network analysis identified several highly connected hub genes (Pklr, Hadha, Tkt, Pgm1, Tpi1, and Eno3) that showed differing trends between early and late time points. Taken together, our results suggest that the liver\u27s response varied with short- and long-term diet restriction. More broadly, we anticipate that the iRatLiver model can be exploited further to study metabolic changes in the liver under other conditions such as drug treatment, infection, and disease

CRISPRi-based radiation modifier screen identifies long non-coding RNA therapeutic targets in glioma.

BackgroundLong non-coding RNAs (lncRNAs) exhibit highly cell type-specific expression and function, making this class of transcript attractive for targeted cancer therapy. However, the vast majority of lncRNAs have not been tested as potential therapeutic targets, particularly in the context of currently used cancer treatments. Malignant glioma is rapidly fatal, and ionizing radiation is part of the current standard-of-care used to slow tumor growth in both adult and pediatric patients.ResultsWe use CRISPR interference (CRISPRi) to screen 5689 lncRNA loci in human glioblastoma (GBM) cells, identifying 467 hits that modify cell growth in the presence of clinically relevant doses of fractionated radiation. Thirty-three of these lncRNA hits sensitize cells to radiation, and based on their expression in adult and pediatric gliomas, nine of these hits are prioritized as lncRNA Glioma Radiation Sensitizers (lncGRS). Knockdown of lncGRS-1, a primate-conserved, nuclear-enriched lncRNA, inhibits the growth and proliferation of primary adult and pediatric glioma cells, but not the viability of normal brain cells. Using human brain organoids comprised of mature neural cell types as a three-dimensional tissue substrate to model the invasive growth of glioma, we find that antisense oligonucleotides targeting lncGRS-1 selectively decrease tumor growth and sensitize glioma cells to radiation therapy.ConclusionsThese studies identify lncGRS-1 as a glioma-specific therapeutic target and establish a generalizable approach to rapidly identify novel therapeutic targets in the vast non-coding genome to enhance radiation therapy

Don’t turn your back on the symptoms of psychosis : a proof-of-principle, quasi-experimental public health trial to reduce the duration of untreated psychosis in Birmingham, UK

Background: Reducing the duration of untreated psychosis (DUP) is an aspiration of international guidelines for first episode psychosis; however, public health initiatives have met with mixed results. Systematic reviews suggest that greater focus on the sources of delay within care pathways, (which will vary between healthcare settings) is needed to achieve sustainable reductions in DUP (BJP 198: 256-263; 2011). Methods/Design: A quasi-experimental trial, comparing a targeted intervention area with a ‘detection as usual’ area in the same city. A proof-of–principle trial, no a priori assumptions are made regarding effect size; key outcome will be an estimate of the potential effect size for a definitive trial. DUP and number of new cases will be collected over an 18-month period in target and control areas and compared; historical data on DUP collected in both areas over the previous three years, will serve as a benchmark. The intervention will focus on reducing two significant DUP component delays within the overall care pathway: delays within the mental health service and help-seeking delay. Discussion: This pragmatic trial will be the first to target known delays within the care pathway for those with a first episode of psychosis. If successful, this will provide a generalizable methodology that can be implemented in a variety of healthcare contexts with differing sources of delay. Trial registration: http://www.controlled-trials.com/ISRCTN45058713 Keywords: Public mental health campaign, First-episode psychosis, Early detection, Duration of untreated psychosis, Youth mental healt

Complete analysis of the B-cell response to a protein antigen, from in vivo germinal centre formation to 3-D modelling of affinity maturation

Somatic hypermutation of immunoglobulin variable region genes occurs within germinal centres (GCs) and is the process responsible for affinity maturation of antibodies during an immune response. Previous studies have focused almost exclusively on the immune response to haptens, which may be unrepresentative of epitopes on protein antigens. In this study, we have exploited a model system that uses transgenic B and CD4<sup>+</sup> T cells specific for hen egg lysozyme (HEL) and a chicken ovalbumin peptide, respectively, to investigate a tightly synchronized immune response to protein antigens of widely differing affinities, thus allowing us to track many facets of the development of an antibody response at the antigen-specific B cell level in an integrated system <i>in</i> <i>vivo</i>. Somatic hypermutation of immunoglobulin variable genes was analysed in clones of transgenic B cells proliferating in individual GCs in response to HEL or the cross-reactive low-affinity antigen, duck egg lysozyme (DEL). Molecular modelling of the antibody–antigen interface demonstrates that recurring mutations in the antigen-binding site, selected in GCs, enhance interactions of the antibody with DEL. The effects of these mutations on affinity maturation are demonstrated by a shift of transgenic serum antibodies towards higher affinity for DEL in DEL-cOVA immunized mice. The results show that B cells with high affinity antigen receptors can revise their specificity by somatic hypermutation and antigen selection in response to a low-affinity, cross-reactive antigen. These observations shed further light on the nature of the immune response to pathogens and autoimmunity and demonstrate the utility of this novel model for studies of the mechanisms of somatic hypermutation

Development of 'synthetic lethal' strategies to target BRCA1-deficient breast cancer

Recent clinical trials demonstrating the efficacy of poly(ADP-ribose) polymerase (PARP) inhibitors for the treatment of BRCA1-deficient breast cancer have provided support for the 'synthetic lethal' concept of targeted cancer therapeutics. A new study provides further preclinical validation of this concept by demonstrating that BRCA1-deficient mouse mammary tumor cells are selectively sensitive to an inhibitor of the polycomb gene EZH2. The development of polycomb gene inhibitors may provide a novel approach to selectively exploit the molecular alterations in BRCA1-deficient breast tumors

Untargeted Metabolomic Characterization of Glioblastoma Intra-Tumor Heterogeneity Using OrbiSIMS

Glioblastoma (GBM) is an incurable brain cancer with a median survival of less than two years from diagnosis. The standard treatment of GBM is multimodality therapy comprising surgical resection, radiation, and chemotherapy. However, prognosis remains poor, and there is an urgent need for effective anticancer drugs. Since different regions of a single GBM contain multiple cancer subpopulations ("intra-tumor heterogeneity"), this likely accounts for therapy failure as certain cancer cells can escape from immune surveillance and therapeutic threats. Here, we present metabolomic data generated using the Orbitrap secondary ion mass spectrometry (OrbiSIMS) technique to investigate brain tumor metabolism within its highly heterogeneous tumor microenvironment. Our results demonstrate that an OrbiSIMS-based untargeted metabolomics method was able to discriminate morphologically distinct regions (viable, necrotic, and non-cancerous) within single tumors from formalin-fixed paraffin-embedded tissue archives. Specifically, cancer cells from necrotic regions were separated from viable GBM cells based on a set of metabolites including cytosine, phosphate, purine, xanthine, and 8-hydroxy-7-methylguanine. Moreover, we mapped ubiquitous metabolites across necrotic and viable regions into metabolic pathways, which allowed for the discovery of tryptophan metabolism that was likely essential for GBM cellular survival. In summary, this study first demonstrated the capability of OrbiSIMS for in situ investigation of GBM intra-tumor heterogeneity, and the acquired information can potentially help improve our understanding of cancer metabolism and develop new therapies that can effectively target multiple subpopulations within a tumor