15 research outputs found

    Exploring the Role of Plasma Lipids and Statins Interventions on Multiple Sclerosis Risk and Severity: A Mendelian Randomization Study

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    BACKGROUND: There has been considerable interest in statins due to their pleiotropic effects beyond their lipid-lowering properties. Many of these pleiotropic effects are predominantly ascribed to Rho small guanosine triphosphatases (Rho GTPases) proteins. We aimed to genetically investigate the role of lipids and statin interventions on multiple sclerosis (MS) risk and severity. METHOD: We employed two-sample Mendelian randomization (MR) to investigate: (1) the causal role of genetically mimic both cholesterol-dependent (via low-density lipoprotein cholesterol (LDL-C) and cholesterol biosynthesis pathway) and cholesterol-independent (via Rho GTPases) effects of statins on MS risk and MS severity, (2) the causal link between lipids (high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG)) levels and MS risk and severity; and (3) the reverse causation between lipid fractions and MS risk. We used summary statistics from the Global Lipids Genetics Consortium (GLGC), eQTLGen Consortium and the International MS Genetics Consortium (IMSGC) for lipids, expression quantitative trait loci and MS, respectively (GLGC: n = 188,577; eQTLGen: n = 31,684; IMSGC (MS risk): n = 41,505; IMSGC (MS severity): n =7,069). RESULTS: The results of MR using the inverse variance weighted method show that genetically predicted RAC2, a member of cholesterol-independent pathway, (OR 0.86 (95% CI 0.78 to 0.95), p-value 3.80E-03) is implicated causally in reducing MS risk. We found no evidence for the causal role of LDL-C and the member of cholesterol biosynthesis pathway on MS risk. MR results also show that lifelong higher HDL-C (OR 1.14 (95% CI 1.04 to1.26), p-value 7.94E-03) increase MS risk but TG was not. Furthermore, we found no evidence for the causal role of lipids and genetically mimicked statins on MS severity. There is no evidence of reverse causation between MS risk and lipids. CONCLUSION: Evidence from this study suggests that RAC2 is a genetic modifier of MS risk. Since RAC2 has been reported to mediate some of the pleiotropic effects of statins, we suggest that statins may reduce MS risk via a cholesterol-independent pathway (i.e., RAC2-related mechanism(s)). MR analyses also support a causal effect of HDL-C on MS risk

    Genetic evidence for serum amyloid P component as a drug target in neurodegenerative disorders

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    The mechanisms responsible for neuronal death causing cognitive loss in Alzheimer's disease (AD) and many other dementias are not known. Serum amyloid P component (SAP) is a constitutive plasma protein, which is cytotoxic for cerebral neurones and also promotes formation and persistence of cerebral Aβ amyloid and neurofibrillary tangles. Circulating SAP, which is produced exclusively by the liver, is normally almost completely excluded from the brain. Conditions increasing brain exposure to SAP increase dementia risk, consistent with a causative role in neurodegeneration. Furthermore, neocortex content of SAP is strongly and independently associated with dementia at death. Here, seeking genomic evidence for a causal link of SAP with neurodegeneration, we meta-analysed three genome-wide association studies of 44 288 participants, then conducted cis-Mendelian randomization assessment of associations with neurodegenerative diseases. Higher genetically instrumented plasma SAP concentrations were associated with AD (odds ratio 1.07, 95% confidence interval (CI) 1.02; 1.11, p = 1.8 × 10-3), Lewy body dementia (odds ratio 1.37, 95%CI 1.19; 1.59, p = 1.5 × 10-5) and plasma tau concentration (0.06 log2(ng l-1) 95%CI 0.03; 0.08, p = 4.55 × 10-6). These genetic findings are consistent with neuropathogenicity of SAP. Depletion of SAP from the blood and the brain, by the safe, well tolerated, experimental drug miridesap may thus be neuroprotective

    Improving the odds of drug development success through human genomics: modelling study.

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    Lack of efficacy in the intended disease indication is the major cause of clinical phase drug development failure. Explanations could include the poor external validity of pre-clinical (cell, tissue, and animal) models of human disease and the high false discovery rate (FDR) in preclinical science. FDR is related to the proportion of true relationships available for discovery (γ), and the type 1 (false-positive) and type 2 (false negative) error rates of the experiments designed to uncover them. We estimated the FDR in preclinical science, its effect on drug development success rates, and improvements expected from use of human genomics rather than preclinical studies as the primary source of evidence for drug target identification. Calculations were based on a sample space defined by all human diseases - the 'disease-ome' - represented as columns; and all protein coding genes - 'the protein-coding genome'- represented as rows, producing a matrix of unique gene- (or protein-) disease pairings. We parameterised the space based on 10,000 diseases, 20,000 protein-coding genes, 100 causal genes per disease and 4000 genes encoding druggable targets, examining the effect of varying the parameters and a range of underlying assumptions, on the inferences drawn. We estimated γ, defined mathematical relationships between preclinical FDR and drug development success rates, and estimated improvements in success rates based on human genomics (rather than orthodox preclinical studies). Around one in every 200 protein-disease pairings was estimated to be causal (γ = 0.005) giving an FDR in preclinical research of 92.6%, which likely makes a major contribution to the reported drug development failure rate of 96%. Observed success rate was only slightly greater than expected for a random pick from the sample space. Values for γ back-calculated from reported preclinical and clinical drug development success rates were also close to the a priori estimates. Substituting genome wide (or druggable genome wide) association studies for preclinical studies as the major information source for drug target identification was estimated to reverse the probability of late stage failure because of the more stringent type 1 error rate employed and the ability to interrogate every potential druggable target in the same experiment. Genetic studies conducted at much larger scale, with greater resolution of disease end-points, e.g. by connecting genomics and electronic health record data within healthcare systems has the potential to produce radical improvement in drug development success rate

    Druggable proteins influencing cardiac structure and function: Implications for heart failure therapies and cancer cardiotoxicity

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    Dysfunction of either the right or left ventricle can lead to heart failure (HF) and subsequent morbidity and mortality. We performed a genome-wide association study (GWAS) of 16 cardiac magnetic resonance (CMR) imaging measurements of biventricular function and structure. Cis-Mendelian randomization (MR) was used to identify plasma proteins associating with CMR traits as well as with any of the following cardiac outcomes: HF, non-ischemic cardiomyopathy, dilated cardiomyopathy (DCM), atrial fibrillation, or coronary heart disease. In total, 33 plasma proteins were prioritized, including repurposing candidates for DCM and/or HF: IL18R (providing indirect evidence for IL18), I17RA, GPC5, LAMC2, PA2GA, CD33, and SLAF7. In addition, 13 of the 25 druggable proteins (52%; 95% confidence interval, 0.31 to 0.72) could be mapped to compounds with known oncological indications or side effects. These findings provide leads to facilitate drug development for cardiac disease and suggest that cardiotoxicities of several cancer treatments might represent mechanism-based adverse effects

    Druggable proteins influencing cardiac structure and function: Implications for heart failure therapies and cancer cardiotoxicity

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    Dysfunction of either the right or left ventricle can lead to heart failure (HF) and subsequent morbidity and mortality. We performed a genome-wide association study (GWAS) of 16 cardiac magnetic resonance (CMR) imaging measurements of biventricular function and structure. Cis-Mendelian randomization (MR) was used to identify plasma proteins associating with CMR traits as well as with any of the following cardiac outcomes: HF, non-ischemic cardiomyopathy, dilated cardiomyopathy (DCM), atrial fibrillation, or coronary heart disease. In total, 33 plasma proteins were prioritized, including repurposing candidates for DCM and/or HF: IL18R (providing indirect evidence for IL18), I17RA, GPC5, LAMC2, PA2GA, CD33, and SLAF7. In addition, 13 of the 25 druggable proteins (52%; 95% confidence interval, 0.31 to 0.72) could be mapped to compounds with known oncological indications or side effects. These findings provide leads to facilitate drug development for cardiac disease and suggest that cardiotoxicities of several cancer treatments might represent mechanism-based adverse effects

    Unexpected Inheritance of a Balanced Homologous translocation t(22q;22q) from father to a phenotypically normal daughter

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    Rearrangements between homologous chromosomes are extremely rare and manifest mainly as monosomic or trisomic offsprings. There are remarkably few reports of balanced homologous chromosomal translocation t (22q; 22q) and only two cases of transmission of this balanced homohologous rearrangement from mother to normal daughter are reported. Robersonian translocation carriers in non-homologous chromosomes have the ability to have an unaffected child. However, it is not possible to have an unaffected child in cases with Robersonian translocations in homologous chromosomes. Carriers of homologous chromosome 22 translocations with maternal uniparental disomy do not have any impact on their phenotype. We are presenting a family with a history of multiple first trimester miscarriages and an unexpected inheritance of balanced homologous translocation of chromosome 22 with paternal uniparental disomy. There are no data available regarding the impact of paternal UPD 22 on the phenotype. We claim this to be the first report explaining that paternal UPD 22 does not impact the phenotype

    Comparing the effects of CETP in East Asian and European ancestries: a Mendelian randomization study

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    Abstract CETP inhibitors are a class of lipid-lowering drugs in development for treatment of coronary heart disease (CHD). Genetic studies in East Asian ancestry have interpreted the lack of CETP signal with low-density lipoprotein cholesterol (LDL-C) and lack of drug target Mendelian randomization (MR) effect on CHD as evidence that CETP inhibitors might not be effective in East Asian participants. Capitalizing on recent increases in sample size of East Asian genetic studies, we conducted a drug target MR analysis, scaled to a standard deviation increase in high-density lipoprotein cholesterol. Despite finding evidence for possible neutral effects of lower CETP levels on LDL-C, systolic blood pressure and pulse pressure in East Asians (interaction p-values < 1.6 × 10−3), effects on cardiovascular outcomes were similarly protective in both ancestry groups. In conclusion, on-target inhibition of CETP is anticipated to decrease cardiovascular disease in individuals of both European and East Asian ancestries

    Genetic drug target validation using Mendelian randomisation

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    Mendelian randomisation (MR) analysis of drug targets has potential to aid drug development. Here, the authors introduce a mathematical framework to elucidate this specific application of MR
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