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Chen, E.

Publications and source records attributed to Chen, E..

At least 109 records · Page 6Linked to original sources

Chemical inhibition of ENL/AF9 YEATS domains in acute leukemia

Transcriptional co-regulators, which mediate chromatin-dependent transcriptional signaling, represent tractable targets to modulate tumorigenic gene expression programs with small molecules. Genetic loss-of-function studies have recently implicated the transcriptional co-activator, ENL, as a selective requirement for the survival of acute leukemia and highlighted an essential role for its chromatin reader YEATS domain. Motivated by these discoveries, we executed a screen of nearly 300,000 small molecules and identified an amido-imidazopyridine inhibitor of the ENL YEATS domain (IC50 = 7 {micro}M). Leveraging a SuFEx-based high-throughput approach to medicinal chemistry optimization, we discovered SR-0813 (IC50 = 25 nM), a potent and selective ENL/AF9 YEATS domain inhibitor that exclusively inhibits the growth of ENL-dependent leukemia cell lines. Armed with this tool and a first-in-class ENL PROTAC, SR-1114, we detailed the response of AML cells to pharmacological ENL disruption for the first time. Most notably, displacement of ENL from chromatin by SR-0813 elicited a strikingly selective suppression of ENL target genes, including HOXA9/10, MYB, MYC and a number of other leukemia proto-oncogenes. Our study reproduces a number of key observations previously made by CRISPR/Cas9 loss of function and dTAG-mediated degradation, and therefore, both reinforces ENL as an emerging leukemia target and validates SR-0813 as a high-quality chemical probe.

cancer biology↗

The effects of low-carbohydrate diets on the metabolic response to androgen-deprivation therapy in prostate cancer

Prostate cancer (PC) is the second most lethal cancer for men and metastatic PC is treated by androgen deprivation therapy (ADT). While effective, ADT has many metabolic side effects. Previously, serum metabolome analysis showed that ADT reduced androsterone sulfate, 3-hydroxybutyric acid, acyl-carnitines while increased serum glucose. Since ADT reduced ketogenesis, we speculate that low-carbohydrate diets (LCD) may reverse many ADT-induced metabolic abnormalities in animals and humans. To test this possibility, we conducted a multi-center trial of PC patients initiating ADT randomized to no diet change (control) or LCD. We previously showed LCD led to significant weight loss, reduced fat mass, improved insulin resistance and lipid profiles. To determine whether and how LCD affects ADT-induced metabolic effects, we analyzed serum metabolites after 3-, and 6-months of ADT on LCD vs. control. We found androsterone sulfate was most consistently reduced by ADT, and was slightly further reduced by LCD. Contrastingly, LCD increased 3-hydroxybutyric acid and various acyl-carnitines, counteracting their reduction during ADT. LCD also reversed the ADT-reduced lactic acid, alanine and S-adenosyl Methionine (SAM), elevating glycolysis metabolites, amino acids and sulfur-containing metabolites. While the degree of ADT-reduced androsterone was strongly correlated with glucose and indole-3-carboxaldehyde, LCD disrupted such correlation. However, many LCD-induced changes were seen at 3-but not 6-month, suggesting metabolic adaption. Together, LCD significantly reversed many ADT-induced metabolic changes while slightly enhancing androgen reduction. Future research is needed to confirm these findings and determine whether LCD can mitigate ADT-linked comorbidities and possibly delaying disease progression by further lowering androgens. Statement of translational relevanceProstate cancer (PC) is the most common non-skin cancer and second leading cause of cancer-related death in men. While androgen deprivation therapy (ADT) is the main treatment for metastatic PC, it has many metabolic side effects. Previous serum metabolome analysis of PC patients receiving ADT identified reduced ketogenesis. Therefore, low-carbohydrate diets (LCD), ketogenic in nature, may reverse many ADT-induced metabolic abnormalities. We conducted a 6-month multi-center trial of no diet change (control) vs. LCD in men initiating ADT. We found that LCD reversed many ADT-induced metabolic abnormalities while slightly further reducing androgen levels. Also, LCD disrupted the diabetogenic effects of ADT, but some effects seen at 3-month were lost at 6-month, suggesting metabolic adaptation to LCD. These data suggest the potential metabolic benefits of LCD with potential to enhance ADT efficacy. Larger studies testing whether LCDs mitigate metabolic side effects and slow disease progression are warranted given acceptable safety profiles, metabolic benefits, and possibly lowered androgens.

cancer biology↗

Discovery of a Novel Inhibitor of Coronavirus 3CL Protease as a Clinical Candidate for the Potential Treatment of COVID-19

COVID-19 caused by the SARS-CoV-2 virus has become a global pandemic. 3CL protease is a virally encoded protein that is essential across a broad spectrum of coronaviruses with no close human analogs. The designed phosphate prodrug PF-07304814 is metabolized to PF-00835321 which is a potent inhibitor in vitro of the coronavirus family 3CL pro, with selectivity over human host protease targets. Furthermore, PF-00835231 exhibits potent in vitro antiviral activity against SARS-CoV-2 as a single agent and it is additive/synergistic in combination with remdesivir. We present the ADME, safety, in vitro, and in vivo antiviral activity data that supports the clinical evaluation of this compound as a potential COVID-19 treatment.

pharmacology and toxicology↗

Cell-free DNA as a biomarker for prostate cancer: elevated concentration and decreased fragment size

PurposeProstate cancer is the most commonly diagnosed neoplasm in American men. Although existing biomarkers may detect localized prostate cancer, additional strategies are necessary for improving detection and identifying aggressive disease that may require further intervention. One promising, minimally invasive biomarker is cell-free DNA (cfDNA), which consist of short DNA fragments released into circulation by dying or lysed cells that may reflect underlying cancer. Here we investigated whether differences in cfDNA concentration and cfDNA fragment size could improve the sensitivity for detecting more advanced and aggressive prostate cancer. Materials and MethodsThis study included 268 individuals: 34 healthy controls, 112 men with localized prostate cancer who underwent radical prostatectomy (RP), and 122 men with metastatic castration-resistant prostate cancer (mCRPC). Plasma cfDNA concentration and fragment size were quantified with the Qubit 3.0 and the 2100 Bioanalyzer. The potential relationship between cfDNA concentration or fragment size and localized or mCRPC prostate cancer was evaluated with descriptive statistics, logistic regression, and area under the curve analysis with cross-validation. ResultsPlasma cfDNA concentrations were elevated in mCRPC patients in comparison to localized disease (OR5 ng/mL = 1.34, P = 0.027) or to being a control (OR5 ng/mL = 1.69, P = 0.034). Decreased average fragment size was associated with an increased risk of localized disease compared to controls (OR5bp = 0.77, P = 0.0008). ConclusionThis study suggests that cfDNA concentration and average cfDNA fragment size may provide a quick, cost-effective approach to help determine which patients will benefit most from further screening and/or disease monitoring to help improve prostate cancer outcomes.

cancer biology↗

Oral drug repositioning candidates and synergistic remdesivir combinations for the prophylaxis and treatment of COVID-19

The ongoing pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates strategies to identify prophylactic and therapeutic drug candidates for rapid clinical deployment. A high-throughput, high-content imaging assay of human HeLa cells expressing the SARS-CoV-2 receptor ACE2 was used to screen ReFRAME, a best-in-class drug repurposing library. From nearly 12,000 compounds, we identified 66 compounds capable of selectively inhibiting SARS-CoV-2 replication in human cells. Twenty-four of these drugs show additive activity in combination with the RNA-dependent RNA polymerase inhibitor remdesivir and may afford increased in vivo efficacy. We also identified synergistic interaction of the nucleoside analog riboprine and a folate antagonist 10-deazaaminopterin with remdesivir. Overall, seven clinically approved drugs (halofantrine, amiodarone, nelfinavir, simeprevir, manidipine, ozanimod, osimertinib) and 19 compounds in other stages of development may have the potential to be repurposed as SARS-CoV-2 oral therapeutics based on their potency, pharmacokinetic and human safety profiles.

microbiology↗

The specificity of sperm-mediated paternal effects in threespined sticklebacks

Parental effects can help offspring cope with challenging environments, but whether these effects are unique to specific environmental conditions is largely unknown. Parental effects may evolve via a core pathway that generally prepares offspring for risky environments or could be stimuli-specific, with offspring developing phenotypes that are tailored to specific environmental challenges. We exposed threespined sticklebacks (Gasterosteus aculeatus) fathers to a potentially threatening stimulus (net) versus native predator (sculpin). Offspring of sculpin-exposed fathers were more responsive (greater change in activity) to a simulated predator attack, while offspring of net-exposed fathers were less responsive (lower plasma cortisol and fewer antipredator behaviors). To evaluate offspring response to native and non-native stimuli, we sequentially exposed offspring of net-exposed, sculpin-exposed or control fathers to a net, native sculpin model, or non-native trout model. Paternal treatment did not influence offspring response to stimuli; instead, offspring were more responsive to the native sculpin predator compared to nets or non-native trout predator. Collectively, we demonstrate that sperm-mediated paternal effects in response to different, potentially stressful stimuli result in distinct offspring phenotypes. This specificity may be key to understanding the evolution of adaptive parental effects and how parents prime offspring for encountering both evolved and novel environmental stimuli.Competing Interest StatementThe authors have declared no competing interest.View Full Text

animal behavior and cognition↗

Strain-dependent modifier genes determine survival in Zfp423 mice

Zfp423 encodes a transcriptional regulatory protein that interacts with canonical signaling and lineage pathways. Mutations in mouse Zfp423 or its human ortholog ZNF423 are associated with a range of developmental abnormalities reminiscent of ciliopathies, including cerebellar vermis hypoplasia and other midline brain defects. Null mice have reduced viability in most strain backgrounds. Here we show complete lethality on a C57BL/6J background, dominant rescue in backcrosses to any of 13 partner strains, with strain-dependent survival frequencies, and evidence for a BALB/c-derived survival modifier locus on chromosome 5. Survival data indicate both perinatal and postnatal periods of lethality. Anatomical data from a hypomorphic gene trap allele observed on both C57BL/6J and BALB/c congenic backgrounds shows an aggregate effect of background on sensitivity to Zfp423 loss rather than a binary effect on viability.

genetics↗

Discovery of repurposing drug candidates for the treatment of diseases caused by pathogenic free-living amoebae

Diseases caused by pathogenic free-living amoebae include primary amoebic meningoencephalitis (Naegleria fowleri), granulomatous amoebic encephalitis (Acanthamoeba spp.), Acanthamoeba keratitis, and Balamuthia amoebic encephalitis (Balamuthia mandrillaris). Each of these are difficult to treat and have high morbidity and mortality rates due to lack of effective therapeutics. In pursuit of repurposing drugs for chemotherapies, we conducted a high throughput phenotypic screen of 12,000 compounds from the Calibr ReFRAME library. We discovered a total of 58 potent inhibitors (IC50 <1 M) against N. fowleri (n=19), A. castellanii (n=12), and B. mandrillaris (n=27) plus an additional 90 micromolar inhibitors. Of these, 113 inhibitors have never been reported to have activity against Naegleria, Acanthamoeba or Balamuthia. Rapid onset of action is important for new anti-amoeba drugs and we identified 19 compounds that inhibit N. fowleri in vitro within 24 hours (halofuginone, NVP-HSP990, fumagillin, bardoxolone, belaronib, and BPH-942, solithromycin, nitracrine, quisinostat, pabinostat, pracinostat, dacinostat, fimepinostat, sanguinarium, radicicol, acriflavine, REP3132, BC-3205 and PF-4287881). These compounds inhibit N. fowleri in vitro faster than any of the drugs currently used for chemotherapy. The results of these studies demonstrate the utility of phenotypic screens for discovery of new drugs for pathogenic free-living amoebae, including Acanthamoeba for the first time. Given that many of the repurposed drugs have known mechanisms of action, these compounds can be used to validate new targets for structure-based drug design. Author SummaryFree-living amoebae (FLA) are ubiquitous in soil and freshwater and most are non-pathogenic to people; however, three different pathogenic FLA have been found to cause severe, most often fatal diseases in humans. Due to poor detection and inadequate treatment options available for pathogenic FLA, the fatality rates are still > 90% for the diseases caused by Balamuthia mandrillaris, Naegleria fowleri, and Acanthamoeba spp. With hundreds of cases in the United States and many more cases reported worldwide, there is still an urgent clinical need for effective diagnosis and specific treatments discovered against these opportunistic parasites. Drug repurposing is a powerful approach for drug-discovery because it significantly improves the discovery time, reduces the amount of resources, and decreases costs required to advance lead candidate drugs of interest into the clinic. This is extremely helpful for neglected diseases including pathogenic FLA where there is a need for new active therapies with limited budgets. This report addresses the discovery of new active drugs with potential for repurposing, multiple new drug classes that inhibit pathogenic FLA, and numerous putative drug targets that can be used as tools for further investigation and structure-based drug design.

microbiology↗

A machine learning approach to optimizing cell-free DNA sequencing panels: with an application to prostate cancer

BackgroundCell-free DNAs (cfDNA) use as a biomarker in cancer is challenging due to genetic heterogeneity of malignancies and rarity of tumor-derived molecules. Here we describe and demonstrate a novel machine-learning guided panel design strategy for improving the detection of tumor variants in cfDNA. Using this approach, we first generated a model to classify and score candidate variants for inclusion on a prostate cancer targeted sequencing panel. We then used this panel to screen tumor variants from prostate cancer patients with localized disease in both in silico and hybrid capture settings. MethodsWhole Genome Sequence (WGS) data from 550 prostate tumors was analyzed to build a targeted sequencing panel of single point and small (<200bp) indel mutations, which was subsequently screened in silico against prostate tumor sequences from 5 patients to assess performance against commonly used alternative panel designs. The panels ability to detect tumor-derived cfDNA variants was then assessed using prospectively collected cfDNA and tumor foci from a test set 18 prostate cancer patients with localized disease undergoing radical proctectomy. ResultsThe panel generated from this approach identified as top candidates mutations in known driver genes (e.g. HRAS) and prostate cancer related transcription factor binding sites (e.g. MYC, AR). It outperformed two commonly used designs in detecting somatic mutations found in the cfDNA of 5 prostate cancer patients when analyzed in an in silico setting. Additionally, hybrid capture and 2,500X sequencing of cfDNA molecules using the panel resulted in detection of tumor variants in all 18 patients of a test set, where 15 of the 18 patients had detected variants found in multiple foci. ConclusionMachine learning-prioritized targeted sequencing panels may prove useful for broad and sensitive variant detection in the cfDNA of heterogeneous diseases. This strategy has implications for disease detection and monitoring when applied to the cfDNA isolated from prostate cancer patients.

cancer biology↗

More filtering on SNP calling does not remove evidence of inter-nucleus recombination in dikaryotic arbuscular mycorrhizal fungi

We respond to a recent reanalysis of single nucleus sequence data from Chen et al. 2018 eLife, which indicated that evidence of inter-nuclear recombination in dikaryotic arbuscular mycorrhizal fungi decreases when heterozygous, duplicated sites being supported by less than 5 reads, are removed from the dataset. Here, we show that applying a more stringent methodology for filtering SNP calls that focuses exclusively on single copy and homozygous regions with at least 5 reads supporting a given SNP, still recovers several hundreds putative inter-nucleus recombination events within the same dataset. We also provide evidence for retaining SNPs supported by less than 5 reads for genotyping individual nuclei using the same dataset.

genomics↗

High-throughput screening of the ReFRAME library identifies potential drug repurposing candidates for Trypanosoma cruzi

Chagas disease, caused by the kinetoplastid parasite Trypanosoma cruzi, affects between 6 and 7 million people worldwide, with an estimated 300,000 to 1 million of these cases in the United States. In the chronic phase of infection, T. cruzi can cause severe gastrointestinal and cardiac disease, which can be fatal. Currently, only benznidazole is clinically-approved by the FDA for pediatric use to treat this infection in the USA. Toxicity associated with this compound has driven the search for new anti-Chagas agents. Drug repurposing is a particularly attractive strategy for neglected diseases, as pharmacological parameters and toxicity are already known for these compounds, reducing costs and saving time in the drug development pipeline. Here, we screened ~ 12,000 compounds from the ReFRAME library, a collection of drugs or compounds with confirmed clinical safety, against T. cruzi. We identified 7 compounds of interest with potent in vitro activity against the parasite with a therapeutic index of 10 or greater, including the previously-unreported activity of the antiherpetic compound 348U87. These results provide the framework for further development of new T. cruzi leads that can potentially move quickly to the clinic.

microbiology↗

Characterization of GRK5 as a novel regulator of rhabdomyosarcoma tumor cell growth and self-renewal

Rhabdomyosarcoma (RMS) is the most common soft-tissue pediatric sarcoma. Treatment options remain limited, presenting an urgent need for novel therapeutic targets. Using a high-throughput siRNA screen against the human kinome, we identified GRK5, a G-protein receptor kinase, as a novel regulator of RMS tumor cell growth and self-renewal. Through functional assays in vitro and in vivo, we show that GRK5 regulates cell cycling in a kinase-independent manner to promote RMS tumor cell growth. GRK5 interacts with NFAT to facilitate autoregulation of NFAT1 expression in a kinase independent manner, and loss of NFAT1 phenocopies GRK5 loss-of-function effects on cell cycle arrest. Self-renewal of RMS, required for recapitulation of tumor heterogeneity, is significantly reduced with loss of GRK5 due to increased cell death. Treatment of human RMS xenografts in mice with CCG-215022, a GRK5-selective inhibitor, reduces tumor growth of RMS. GRK5 represents a novel therapeutic target for the treatment of RMS. Statement of SignificanceGRK5 promotes growth and self-renewal of RMS, thereby representing a novel therapeutic target for improving survival outcomes of RMS patients. GRK5 regulates RMS tumor cell growth in a kinase-independent manner through direct interaction with NFAT1. This finding promises novel drug design, targeting non-kinase domains of GRK5.

cancer biology↗

HDAC6 promotes self-renewal and migration/invasion of rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a devastating pediatric sarcoma. The survival outcomes remain poor for patients with relapsed or metastatic disease. Effective targeted therapy is lacking due to our limited knowledge of the underlying cellular and molecular mechanisms leading to disease progression. In this study, we used functional assays in vitro and in vivo (zebrafish and xenograft mouse models) to demonstrate the crucial role of HDAC6, a cytoplasmic histone deacetylase, in driving RMS tumor growth, self-renewal and migration/invasion. Treatment with the HDAC6-selective inhibitor, Tubastatin A, recapitulates the HDAC6 loss-of-function phenotypes. HDAC6 regulates cytoskeletal dynamics to promote tumor cell migration and invasion. RAC1, a Rho family GTPase, is an essential mediator of HDAC6 function, and is necessary and sufficient for RMS cell migration and invasion. High expression of RAC1 correlates with poor clinical prognosis in RMS patients. Targeting the HDAC6-RAC1 axis represents a promising therapeutic option for improving survival outcomes of RMS patients.

cancer biology↗

Bayesian modelling of high-throughput sequencing assays with malacoda

NGS studies have uncovered an ever-growing catalog of human variation while leaving an enormous gap between observed variation and experimental characterization of variant function. High-throughput screens powered by NGS have greatly increased the rate of variant functionalization, but the development of comprehensive statistical methods to analyze screen data has lagged behind. In the massively parallel reporter assay (MPRA), short barcodes are counted by sequencing DNA libraries transfected into cells and output RNA in order to simultaneously measure the shifts in transcription induced by thousands of genetic variants. These counts present many statistical challenges, including over-dispersion, depth dependence, and uncertain DNA concentrations. So far, the statistical methods used have been rudimentary, employing transformations on count level data and disregarding experimental and technical structure while failing to quantify uncertainty in the statistical model.\n\nWe have developed an extensive framework for the analysis of NGS functionalization screens available as an R package called malacoda (available from github.com/andrewGhazi/malacoda). Our software implements a probabilistic, fully Bayesian model of screen data. The model uses the negative binomial distribution with gamma priors to model sequencing counts while accounting for effects from input library preparation and sequencing depth. The method leverages the high-throughput nature of the assay to estimate the priors empirically. External annotations such as ENCODE data or DeepSea predictions can also be incorporated to obtain more informative priors - a transformative capability for data integration. The package also includes quality control and utility functions, including automated barcode counting and visualization methods.\n\nTo validate our method, we analyzed several datasets datasets using malacoda and alternative MPRA analysis methods. These data include experiments from the literature, simulated assays, and primary MPRA data. We also used luciferase assays to experimentally validate the strongest hits from our primary data, as well as variants for which the various methods disagree and variants detectable only with the aid of external annotations.\n\nAuthor SummaryGenetic sequencing technology has progressed rapidly in the past two decades. Huge genomic characterization studies have resulted in a massive quantity of background information across the entire genome, including catalogs of observed human variation, gene regulation features, and computational predictions of genomic function. Meanwhile, new types of experiments use the same sequencing technology to simultaneously test the impact of thousands of mutations on gene regulation. While the design of experiments has become increasingly complex, the data analysis methods deployed have remained overly simplistic, often relying on summary measures that discard information. Here we present a statistical framework called for the analysis of massively parallel genomic experiments designed to incorporate prior information in an unbiased way. We validate our method by comparing our method to alternatives on simulated and real datasets, by using different types of assays that provide a similar type of information, and by closely inspecting an example experimental result that only our method detected. We also present the methods accompanying software package which provides and end-to-end pipeline that provides a simple interface for data preparation, analysis, and visualization.

bioinformatics↗

Automated Lifespan Determination Across Caenorhabditis Strains and Species Reveals Assay-Specific Effects of Chemical Interventions

The goal of the Caenorhabditis Intervention Testing Program is to identify robust and reproducible pro-longevity interventions that are efficacious across genetically diverse cohorts in the Caenorhabditis genus. The project design features multiple experimental replicates collected by three different laboratories. Our initial effort employed fully manual survival assays. With an interest in increasing throughput, we explored automation with flatbed scanner-based Automated Lifespan Machines (ALMs). We used ALMs to measure survivorship of 22 Caenorhabditis strains spanning three species. Additionally, we tested five chemicals that we previously found extended lifespan in manual assays. Overall, we found similar sources of variation among trials for the ALM and our previous manual assays, verifying reproducibility of outcome. Survival assessment was generally consistent between the manual and the ALM assays, although we did observe radically contrasting results for certain compound interventions. We found that particular lifespan outcome differences could be attributed to protocol elements such as enhanced light exposure of specific compounds in the ALM, underscoring that differences in technical details can influence outcomes and therefore interpretation. Overall, we demonstrate that the ALMs effectively reproduce a large, conventionally scored dataset from a diverse test set, independently validating ALMs as a robust and reproducible approach towards aging-intervention screening.

physiology↗

Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR/Cas9 screening

Many gene fusions have been reported in tumours and for most their role remains unknown. As fusions can be used clinically for diagnostic and prognostic purposes, and are targets for treatment, it is crucial to assess their functional implications in cancer. To investigate the role of fusions in tumor cell fitness, we developed a systematic analysis utilising RNA-sequencing data from 1,011 human cancer cell lines to functionally link 8,354 gene fusion events with genomic data, sensitivity to >350 anti-cancer drugs and CRISPR-Cas9 loss-of-fitness information. Established clinically-relevant fusions were readily identified. Overall, functional fusions were rare, including those involving cancer driver genes, suggesting that many fusions are dispensable for tumor cell fitness. Novel therapeutically actionable fusions involving RAF1, BRD4 and ROS1 were verified in new histologies. In addition, recurrent YAP1-MAML2 fusions were identified as activators of Hippo-pathway signaling in multiple cancer types, supporting therapeutic targeting of Hippo signalling. Our approach discriminates functional fusions, identifying new drivers of carcinogenesis and fusions that could have important clinical implications. SignificanceWe identify fusions as new potential candidates for drug repurposing and drivers of carcinogenesis. These results support histology agnostic marker-driven precision cancer medicine. Most fusions are not functional with implications for interpreting cancer fusions reported from clinical sequencing studies.

cancer biology↗

Identification of functional variants for platelet CD36 expression by Massively Parallel Reporter Assay.

CD36 is a platelet membrane glycoprotein whose engagement with oxidized low-density lipoprotein (oxLDL) results in platelet activation. The CD36 gene has been associated with platelet count, platelet volume, as well as lipid levels and CVD risk by genome-wide association studies. Platelet CD36 expression levels have been shown to be associated with both the platelet oxLDL response and an elevated risk of thrombo-embolism. Several genomic variants have been identified as associated with platelet CD36 levels, however none have been conclusively demonstrated to be causative. We screened 81 expression quantitative trait loci (eQTL) single nucleotide polymorphisms (SNPs) associated with platelet CD36 expression by a Massively Parallel Reporter Assay (MPRA) and analyzed the results with a novel Bayesian statistical method. Ten eQTLs located in a 35kb region upstream of the CD36 transcriptional start site demonstrated significant transcription shifts between their minor and major allele in the MPRA assay. Of these, rs2366739 and rs1194196, separated by only 20bp, were confirmed by luciferase assay to alter transcriptional regulation. In addition, electromobility shift assays demonstrated differential DNA:protein complex formation between the two alleles of this locus. Furthermore, deletion of the genomic locus by CRISPR/Cas9 in K562 cells results in upregulation of CD36 transcription. These data indicate that we have identified a variant that regulates expression of CD36, which in turn affects platelet function. To assess the clinical relevance of our findings we used the PhenoScanner tool, which aggregates large scale GWAS findings; the results reinforce the clinical relevance of our variants and the utility of the MPRA assay. The study demonstrates a generalizable paradigm for functional testing of genetic variants to inform mechanistic studies, support patient management and develop precision therapies. Author SummaryPlatelets are anucleate cells that are best known as regulators of vascular hemostasis and thrombosis but also play important roles in cancer, angiogenesis, and inflammation. CD36 is a platelet surface marker that can activate platelet in response to oxidized low density lipoprotein (oxLDL). CD36 has been associated with numerous cardiovascular traits in human including blood lipid levels, platelet count, and cardiovascular disease prevalence in human genetic studies. Human variability in platelet CD36 levels are associated with the platelet response to oxLDL. However, the genetic mechanisms responsible for the variability of CD36 levels are unknown. We examined 81 genetic variants associated with CD36 levels for functionality using a high-throughput assay. Of the ten variants that were identified in that assay, one doublet, rs2366739 and rs1194196, were confirmed using additional molecular and cellular assays. Deletion of the genomic region containing rs2366739 and rs1194196 resulted in overexpression of CD36 in a cell culture system. This finding indicates a control locus which can serve as a potential target in modulating CD36 expression and altering platelet function in cardiovascular disease.

genomics↗

10Kin1day: A bottom-up neuroimaging initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

neuroscience↗