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19 results for “Mendelian disease”
Affected cell types for hundreds of Mendelian diseases revealed by analysis of human and mouse single-cell data
<p>Hereditary diseases manifest clinically in certain tissues, however their affected cell types typically remain elusive. Single-cell expression studies showed that overexpression of disease-associated genes may point to the affected cell types. Here, we developed a method that infers disease-affected cell types from the preferential expression of disease-associated genes in cell types (PrEDiCT). We applied PrEDiCT to single-cell expression data of six human tissues, to infer the cell types affected in 1,459 hereditary diseases. Overall, we identified 114 cell types affected by 1,140 diseases. We corroborated our findings by literature text-mining and recapitulation in mouse corresponding tissues. Based on these findings, we explored features of disease-affected cell types and cell classes, highlighted cell types affected by mitochondrial diseases and heritable cancers, and identified diseases that perturb intercellular communication. This study expands our understanding of disease mechanisms and cellular vulnerability.</p>
Investigating the causal association between immune cell phenotypes and allergic diseases and non-allergic asthma using conventional Two-sample and Bayesian weighted Mendelian randomization
<p>Investigating the causal association between immune cell phenotypes and allergic diseases and non-allergic asthma using conventional Two-sample and Bayesian weighted Mendelian randomization</p>
Systematic creation and phenotyping of Mendelian disease models in C. elegans: towards large-scale drug repurposing
<p>Data collected for the eLife OpenAccess paper: Systematic creation and phenotyping of Mendelian disease models in <em>C. elegans</em>: towards large-scale drug repurposing. (doi: 10.7554/eLife.92491.1)</p> <p>Contains: extracted features, calculated stats, normalised z-scores and timerseries data of all the disease model mutants generated. In addition, there is a static .html file that allows for mousing over the clustermaps to easily view differences in strains compared to the N2 wild-type. Dataset also contains, metadata and feature summary/file name information of FDA-library drug screen and the confirmation screen of the hit from this (i.e., all data collected in published in the associated paper). </p>
Affected cell types for hundreds of Mendelian diseases revealed by analysis of human and mouse single-cell data
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Data from: Sleep, major depressive disorder and Alzheimer's disease: a Mendelian randomisation study
<div class="WordSection1"> <span><span>Objective</span></span> <p><span>To explore the causal relationships between sleep, major depressive disorder (MDD), and Alzheimer's disease (AD).</span></p> <span><span>Methods</span></span> <p><span>We conducted bi-directional two-sample Mendelian randomisation analyses. Genetic associations were obtained from the largest genome-wide association studies currently available in UK Biobank (N=446,118), the Psychiatric Genomics Consortium (N=18,759), and the International Genomics of Alzheimer's Project (N=63,926). We used the inverse variance weighted Mendelian randomisation method to estimate the causal effects, and the weighted median and MR-Egger for sensitivity analyses to test for pleiotropic effects. </span></p> <span><span>Results</span></span> <p><span>We found that higher risk of AD was significantly associated with being a "morning person" (odds ratio (OR)=1.01, P=0.001), shorter sleep duration (self-reported: β=-0.006, P=1.9×10<sup>-4</sup>; accelerometer-based: β=-0.015, P=6.9×10<sup>-5</sup>), less likely to report long sleep (β=-0.003, P=7.3×10<sup>-7</sup>), earlier timing of the least active 5 hours (β=-0.024, P=1.7×10<sup>-13</sup>), and a smaller number of sleep episodes (β=-0.025, P=5.7×10<sup>-14</sup>) after adjusting for multiple comparisons. We also found that higher risk of AD was associated with lower risk of insomnia (OR=0.99, P=7×10<sup>-13</sup>). However, we did not find evidence that these abnormal sleep patterns were causally related to AD or a significant causal relationship between MDD and risk of AD. </span></p> <span><span>Conclusion</span></span> <p><span>We found that AD may causally influence sleep patterns. However, we did not find evidence supporting a causal role of disturbed sleep patterns in AD or evidence for a causal relationship between MDD and AD risk.</span></p> </div> <p> </p>
The simulation dataset of GRIPT: a novel case-control analysis method for Mendelian disease gene discovery
<p>The simulation dataset of GRIPT: a novel case-control analysis method for Mendelian disease gene discovery</p> <p>To uncompress the data:</p> <p>tar -xvf Simulation_data.tar.gz</p> <p>The meaning of the datasets:</p> <p>sim_X_Y.tar.gz means the simulation is generated with the maximum population frequency cutoff of X and the sample size of Y.</p> <p>sim_X_Y.tar.gz is generated based on the average allele frequency in population.</p> <p>sim_X_Y_AMR.tar.gz is generated based on the allele frequency in Latino population.</p> <p>sim_X_Y_500_Z.tar.gz is mixed of Latino population with a proportion of (500-Z)/500, and African population with a proportion of Z/500.</p> <p>The allele frequency is based on the ExAC database (Lek et al Nature 2016)</p> <p>Within each folder, there are case or control folders. The case folder contains the simulation spiked in the HGMD mutation of the given gene (i.e. RPE65 or TINF2) in the given percentage of individuals (e.g. 0.5%, 1%, 2%, 3%). The control folder contains the simulation without HGMD mutation spiked in.</p>
Data for: Genetic prevalence and clinical relevance of canine Mendelian disease variants in over one million dogs
<p><span>Hundreds of genetic variants implicated in Mendelian disease have been characterized in dogs and commercial screening is being offered for most of them worldwide. There is typically limited information available regarding the broader population frequency of variants and uncertainty regarding their functional and clinical impact in ancestry backgrounds beyond the discovery breed. Genetic panel screening of disease variants, commercially offered directly to the consumer or via a veterinary clinician, provides an opportunity to establish large-scale cohorts with phenotype data available to address open questions related to variant prevalence and relevance. We screened the largest canine cohort examined in a single study to date (1,054,293 representative dogs from our existing cohort of 3.5 million; a total of 811,628 mixed breed dogs and 242,665 purebreds from more than 150 countries) to examine the prevalence and distribution of a total of 250 genetic disease-associated variants in the general population. Electronic medical records from veterinary clinics were available for 43.5% of the genotyped dogs, enabling the clinical impact of variants to be investigated. We provide detailed frequencies for all tested variants across breeds and find that 57% of dogs carry at least one copy of a studied Mendelian disease-associated variant. Focusing on a subset of variants, we provide evidence of full penetrance for 10 variants, and at minimum plausible evidence for clinical significance of 22 variants, on diverse breed backgrounds. Specifically, we report that inherited hypocatalasia is a notable oral health condition, confirm that factor VII deficiency presents as subclinical bleeding propensity and verify two genetic causes of reduced leg length. We further assess genome-wide heterozygosity levels in over 100 breeds and show that a reduction in genome-wide heterozygosity is associated with an increased Mendelian disease load. The accumulated knowledge represents a resource to guide discussions on genetic test relevance by breed.</span></p>
Genetics of Mendelian Forms of Young Onset Alzheimer Disease
ClinicalTrials.gov study NCT01622894. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Sleep, major depressive disorder and Alzheimer’s disease: a Mendelian randomisation study
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Data for: Genetic prevalence and clinical relevance of canine Mendelian disease variants in over one million dogs
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Data from: Risky behaviors and Parkinson's disease: a Mendelian randomization study
Objective: To examine causal associations between risky behavior phenotypes on Parkinson's disease using a Mendelian randomization approach. Methods: We used two-sample Mendelian randomization to generate unconfounded estimates using summary statistics from two independent, large meta-analyses of genome-wide association studies on risk taking behaviors (n=370,771-939,908) and Parkinson's disease (cases: n=9581, controls: n = 33,245). We used inverse variance weighted as the main method for judging causality. Results: Our results support a strong protective association between the tendency to smoke and Parkinson's disease (OR=0.714 per log odds of ever smoking; 95% CI=0.568-0.897; p-value=0.0041; Cochran Q test; p-value=0.238; I2 index=6.3%). Furthermore, we observed risk association trends between automobile speed propensity as well as the number of sexual partners and Parkinson's disease after removal of overlapping loci with other risky traits (OR=1.986 for each standard deviation increase in normalized automobile speed propensity; 95% CI=1.215-3.243; p-value=0.0066, OR=1.635 for each standard deviation increase in number of sexual partners; 95% CI=1.165-2.293; p-value=0.0049). Conclusion: These findings provide support for a causal relationship between general risk tolerance and Parkinson's disease and may provide new insights in the pathogenic mechanisms leading to the development of Parkinson's disease.
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.
Mental disease and risk of autoimmune disease: 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>
Data from: Risky behaviors and Parkinson’s disease: a Mendelian randomization study
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Data from: Relative effects of LDL-C on ischaemic stroke & coronary disease: a Mendelian randomization study
Open the record for dataset details and reuse information.
Data from: Diabetes mellitus, glycemic traits, and cerebrovascular disease: A Mendelian randomization study
Open the record for dataset details and reuse information.
Functional and Transcriptomic Characterization of iPSC-derived Macrophages and their Application in Modeling Mendelian Disease
GEO Series GSE55536. Homo sapiens. 33 samples. Type: Expression profiling by high throughput sequencing.
Genetics of Mendelian Diseases in Qatar
ClinicalTrials.gov study NCT02021734. IPD Sharing: NO. Countries: 1. Publications: 0.
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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.