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52 results for “Mendelian Randomization”
Parathyroid hormone and bone mineral density: a Mendelian randomization study
<p><b>Purpose:</b> Accumulating evidence implicates parathyroid hormone (PTH) in the development of osteoporosis. However, the causal effect of PTH on bone mineral density (BMD) remains unclear. Thus, this study aimed at exploring the association between the concentrations of serum PTH and BMD.</p> <p><b>Methods:</b> The<b> </b>instrumental variables for PTH were selected from a large-scale genome-wide association study (GWAS) [n = 29,155]. Outcomes included BMD of forearm (FA) [n = 8143], femoral neck (FN) [n = 33,297], lumbar spine (LS) [n = 32,735], heel (HL) [n = 394,929] and risk of fractures in these bones (n = 361,194). Furthermore, the BMD of five different age groups; 15 or less [n = 11,807], 15-30 [4180], 30-45 [10,062], 45-60 [18,805] and 60 or more [22,504] were extracted from a GWAS meta-analysis study. The analyses were performed using the two-sample Mendelian randomization (MR) method.</p> <p><b>Results: </b>MR analysis revealed that the level of serum PTH were inversely associated with BMD of FA (95% CI: -0.763 to -0.016), FN (95% CI: -0.669 to -0.304) and LS (95% CI: -0.667 to -0.243). A causal relationship between serum PTH levels and BMD was observed in individuals aged 30-45 (95% CI: -0.888 to -0.166), 45-60 (95% CI: -0.758 to -0.232) and over 60 years (95% CI: -0.649 to -0.163).</p> <p><b>Main conclusions: </b>This study demonstrated that the concentrations of serum PTH is inversely associated with BMD of several bones. Further analysis revealed a site and age-specific correlations between serum PTH levels and BMD, which implies that the levels of serum PTH contribute to the development of osteoporosis.</p>
Data from: Relative effects of LDL-C on ischaemic stroke & coronary disease: a Mendelian randomization study
Objective: To examine the causal relevance of lifelong differences in LDL-C for ischaemic stroke (IS) relative to that for coronary heart disease (CHD) using a Mendelian randomization approach. Methods: We undertook a two-sample Mendelian randomization, based on summary data, to estimate the causal relevance of LDL-C for risk of IS and CHD. Information from 62 independent genetic variants with genome-wide significant effects on LDL-C levels was used to estimate the causal effects of LDL-C for IS and IS subtypes (based on 12,389 IS cases from METASTROKE) and for CHD (based on 60,801 cases from CARDIoGRAMplusC4D). We then assessed the effects of LDL-C on IS and CHD for heterogeneity. Results: A 1 mmol/L higher genetically-determined LDL-C was associated with a 50% higher risk of CHD (OR: 1.49, 95%CI: 1.32-1.68, p=1.1x10-8). By contrast, the causal effect of LDL-C was much weaker for IS (OR: 1.12, 95%CI: 0.96-1.30, p=0.14; p for heterogeneity=2.6x10-3) and, in particular, for cardioembolic stroke (OR: 1.06, 95%CI: 0.84-1.33, p=0.64; p for heterogeneity=8.6x10-3) when compared with that for CHD. Conclusions: In contrast with the consistent effects of LDL-C lowering therapies on IS and CHD, genetic variants that confer lifelong LDL-C differences show a weaker effect on IS than on CHD. The relevance of aetiologically distinct IS subtypes may contribute to the differences observed.
Data from: Childhood adiposity and type 1 diabetes: a Mendelian randomization study
BACKGROUND: The incidence of type 1 diabetes (T1D) is increasing globally. One hypothesis is that increasing childhood obesity rates may explain part of this increase, but, as T1D is rare, intervention studies are challenging to perform. The aim of this study was to assess this hypothesis with a Mendelian randomization approach that uses genetic variants as instrumental variables to test for causal associations. METHODS AND FINDINGS: We created a genetic instrument of 23 single nucleotide polymorphisms (SNPs) associated with childhood adiposity in children aged 2-10 years. Summary-level association results for these 23 SNPs with childhood-onset (<17 years) T1D were extracted from a meta-analysis of genome-wide association study with 5,913 T1D cases and 8,828 reference samples. Using inverse-variance weighted Mendelian randomization analysis, we found support for an effect of childhood adiposity on T1D risk (odds ratio 1.32, 95% CI 1.06-1.64 per standard deviation score in body mass index [SDS-BMI]). A sensitivity analysis provided evidence of horizontal pleiotropy bias (p = 0.04) diluting the estimates towards the null. We therefore applied Egger regression and multivariable Mendelian randomization methods to control for this type of bias and found evidence in support of a role of childhood adiposity in T1D (odds ratio in Egger regression, 2.76, 95% CI 1.40-5.44). Limitations of our study include that underlying genes and their mechanisms for most of the genetic variants included in the score are not known. Mendelian randomization requires large sample sizes, and power was limited to provide precise estimates. This research has been conducted using data from the Early Growth Genetics (EGG) Consortium, the Genetic Investigation of Anthropometric Traits (GIANT) Consortium, the Tobacco and Genetics (TAG) Consortium, and the Social Science Genetic Association Consortium (SSGAC), as well as meta-analysis results from a T1D genome-wide association study. CONCLUSIONS: This study provides genetic support for a link between childhood adiposity and T1D risk. Together with evidence from observational studies, our findings further emphasize the importance of measures to reduce the global epidemic of childhood obesity and encourage mechanistic studies.
Causality of 486 human blood metabolites on gastric cancer: a two-sample Mendelian randomization study
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Mental disease and risk of autoimmune disease: a Mendelian randomization study
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The causal links between gut microbiota and diabetic nephropathy: A Mendelian randomization study. Supplementary material
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Integration of Single-Cell Analysis and Mendelian Randomization Reveals NET1 as a Potential Key Player in Lung Cancer Pathogenesis
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Supplementary Data forExploring Potential Druggable Gene Targets for Hypertrophic Cardiomyopathy through Mendelian Randomization
<p><em>该数据集包含探索肥厚型心肌病可成药基因靶点的手稿的补充材料</em>。</p>
raw data - Causal relationship of immune cells and primary open-angle glaucoma: A Mendelian randomization study
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Data from: Diabetes mellitus, glycemic traits, and cerebrovascular disease: A Mendelian randomization study
<p><span><span><span><span><span><span><span><span><span><span><span><b>Objective: </b>We employed Mendelian randomization (MR) to explore the effects of genetic predisposition to type 2 diabetes (T2D), hyperglycemia, insulin resistance, and β-cell dysfunction on risk of stroke subtypes and related cerebrovascular phenotypes.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><a name="_Hlk49339275"><b>Methods: </b></a>We selected instruments for genetic predisposition to T2D (74,124 cases, 824,006 controls), HbA1c levels (n=421,923), fasting glucose levels (n=133,010), insulin resistance (n=108,557), and β-cell dysfunction (n=16,378) based on published genome-wide association studies. Applying two-sample MR, we examined associations with ischemic stroke (60,341 cases, 454,450 controls), intracerebral hemorrhage (1,545 cases, 1,481 controls), and ischemic stroke subtypes (large artery, cardioembolic, small vessel stroke), as well as with related phenotypes (carotid atherosclerosis, imaging markers of cerebral white matter integrity, and brain atrophy). </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Results: </b>Genetic predisposition to T2D and higher HbA1c levels were associated with higher risk of any ischemic stroke, large artery stroke, and small vessel stroke. Similar associations were also noted for carotid atherosclerotic plaque, fractional anisotropy, a white matter disease marker, and markers of brain atrophy. We further found associations of genetic predisposition to insulin resistance with large artery and small vessel stroke, whereas predisposition to β-cell dysfunction was associated with small vessel stroke, intracerebral hemorrhage, lower grey matter volume, and total brain volume.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Conclusions: </b>This study supports causal effects of T2D and hyperglycemia on large artery and small vessel stroke. </span></span></span></span></span></span></span></span></span></span></span><a name="_Hlk52240657">We show associations of genetically predicted insulin resistance and β-cell dysfunction with large artery and small vessel stroke that might have implications for anti-diabetic treatments targeting these mechanisms.</a></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Classification of Evidence:</b> This study provides Class II evidence that genetic predisposition to T2D and higher HbA1c levels are associated with a higher risk of large artery and small vessel ischemic stroke.</span></span></span></span></span></span></span></span></span></span></span></p>
Food Liking and Risk of Sepsis: A Two-Sample Mendelian Randomization Study_Supplementary Materials
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Fetal/maternal-determined birth weight and adulthood type 2 diabetes and its subtypes: a Mendelian randomization study
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Effects of blood cell traits on cardiovascular morpho-functional phenotypes: Evidence from Mendelian randomization analysis
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Unraveling the Impact of Nutrients and Dietary Patterns on Periodontitis: A Mendelian Randomization Study
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Proteome-wide Mendelian randomization study identifies potential therapeutic targets for Coronary atherosclerosis
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Insight into modifiable risk factors for tuberculosis : a Mendelian randomization study(supplementary materials)
<p>Detailed results of the above 5 statistical methods.</p>
Systematic comparison of Mendelian randomization studies and randomized controlled trials using electronic databases
<p><strong>Supplementary Dataset 1. </strong>Select ClinicalTrials.Gov data fields for the RCT studies identified as the<br> <em>main </em>dataset.<br> <strong>Supplementary Dataset 2.</strong> Select ClinicalTrials.Gov data fields for the RCT studies identified as the<br> <em>literature </em>dataset.<br> <strong>Supplementary Dataset 3.</strong> Comparison of frequency of RCT general features between the <em>Main</em><br> dataset and background of all RCTs available in ClinicalTrials.Gov.</p> <p><strong>Supplementary Dataset 4. </strong>PubMed and SemMedDB data for published MR and RCT studies.<br> <strong>Supplementary Dataset 5. </strong>Case series of MR and RCT studies with matching exposures<br> (interventions) and outcomes (conditions).</p>
Study of the Causal Link Between Rheumatoid Arthritis and Periodontitis Using Mendelian Randomization
ClinicalTrials.gov study NCT06603207. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Parathyroid hormone and bone mineral density: a Mendelian randomization study
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Data from: Risky behaviors and Parkinson’s disease: a Mendelian randomization study
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.