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metabrain eqtl data  (Metabrain Research)

 
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    Metabrain Research metabrain eqtl data
    a , b Colocalization of GWAS of clinical diagnosis ( a ) and Aβ levels ( b ) <t>with</t> <t>ROSMAP,</t> MetaBrain, and GTEx eQTLs. Colocalizations with a posterior probability above 0.5 are shown. c Heatmap of gene prioritization of loci reaching suggestive significance from single-variant association analysis. The heatmap includes genes nearest to lead-SNPs (red), <t>eQTL</t> colocalization (green), eQTL signals associated with lead-SNPs (yellow), peak-to-gene connections identified through scATAC (blue), and evidence from prior publications (purple). d Heatmap of DEGs derived from a previous study (Mathys et al.) according to the final cognitive consensus diagnosis across brain cell subtypes. Significance levels are indicated as * p < 0.05, ** p < 0.01, and *** p < 0.001. e Regional p lots of the clinical diagnosis GWAS and GTEx cortex eQTLs for APCDD1 within a 500 kb window of the lead variant (rs28372356). f APCDD1 and VAPA expression across different cell types in response to pseudo-progression of SEA-AD. Each line represents the locally weighted mean expression (LOWESS) of the supertypes with each subclass. Source data are provided as a Source Data file. Aβ, amyloid beta; ROSMAP, Religious Orders Study/Memory and Aging Project; GTEx, genotype-tissue expression; AFR, African; OPC, oligodendrocyte precursor cell; eQTL, expression quantitative trait loci; DEG, differential expressed gene; Astro, astrocyte; Exc, excitatory neuron; Inh, inhibitory neuron; CAMs, cell adhesion molecules; Micro, microglia; Oligo, oligodendrocyte; End, endothelial cells; Fib, fibroblasts; Per, pericytes; SMC, smooth muscle cell; VLMC, vascular and leptomeningeal cells; Micro-PVM, microglia and perivascular macrophages; GWAS, genome-wide association analysis; scATAC, single-cell chromatin accessibility; SEA-AD, Seattle Alzheimer’s Disease Brain Cell Atlas.
    Metabrain Eqtl Data, supplied by Metabrain Research, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    metabrain eqtl data - by Bioz Stars, 2026-09
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    1) Product Images from "Whole-genome sequencing analyses suggest novel genetic factors associated with Alzheimer’s disease and a cumulative effects model for risk liability"

    Article Title: Whole-genome sequencing analyses suggest novel genetic factors associated with Alzheimer’s disease and a cumulative effects model for risk liability

    Journal: Nature Communications

    doi: 10.1038/s41467-025-59949-y

    a , b Colocalization of GWAS of clinical diagnosis ( a ) and Aβ levels ( b ) with ROSMAP, MetaBrain, and GTEx eQTLs. Colocalizations with a posterior probability above 0.5 are shown. c Heatmap of gene prioritization of loci reaching suggestive significance from single-variant association analysis. The heatmap includes genes nearest to lead-SNPs (red), eQTL colocalization (green), eQTL signals associated with lead-SNPs (yellow), peak-to-gene connections identified through scATAC (blue), and evidence from prior publications (purple). d Heatmap of DEGs derived from a previous study (Mathys et al.) according to the final cognitive consensus diagnosis across brain cell subtypes. Significance levels are indicated as * p < 0.05, ** p < 0.01, and *** p < 0.001. e Regional p lots of the clinical diagnosis GWAS and GTEx cortex eQTLs for APCDD1 within a 500 kb window of the lead variant (rs28372356). f APCDD1 and VAPA expression across different cell types in response to pseudo-progression of SEA-AD. Each line represents the locally weighted mean expression (LOWESS) of the supertypes with each subclass. Source data are provided as a Source Data file. Aβ, amyloid beta; ROSMAP, Religious Orders Study/Memory and Aging Project; GTEx, genotype-tissue expression; AFR, African; OPC, oligodendrocyte precursor cell; eQTL, expression quantitative trait loci; DEG, differential expressed gene; Astro, astrocyte; Exc, excitatory neuron; Inh, inhibitory neuron; CAMs, cell adhesion molecules; Micro, microglia; Oligo, oligodendrocyte; End, endothelial cells; Fib, fibroblasts; Per, pericytes; SMC, smooth muscle cell; VLMC, vascular and leptomeningeal cells; Micro-PVM, microglia and perivascular macrophages; GWAS, genome-wide association analysis; scATAC, single-cell chromatin accessibility; SEA-AD, Seattle Alzheimer’s Disease Brain Cell Atlas.
    Figure Legend Snippet: a , b Colocalization of GWAS of clinical diagnosis ( a ) and Aβ levels ( b ) with ROSMAP, MetaBrain, and GTEx eQTLs. Colocalizations with a posterior probability above 0.5 are shown. c Heatmap of gene prioritization of loci reaching suggestive significance from single-variant association analysis. The heatmap includes genes nearest to lead-SNPs (red), eQTL colocalization (green), eQTL signals associated with lead-SNPs (yellow), peak-to-gene connections identified through scATAC (blue), and evidence from prior publications (purple). d Heatmap of DEGs derived from a previous study (Mathys et al.) according to the final cognitive consensus diagnosis across brain cell subtypes. Significance levels are indicated as * p < 0.05, ** p < 0.01, and *** p < 0.001. e Regional p lots of the clinical diagnosis GWAS and GTEx cortex eQTLs for APCDD1 within a 500 kb window of the lead variant (rs28372356). f APCDD1 and VAPA expression across different cell types in response to pseudo-progression of SEA-AD. Each line represents the locally weighted mean expression (LOWESS) of the supertypes with each subclass. Source data are provided as a Source Data file. Aβ, amyloid beta; ROSMAP, Religious Orders Study/Memory and Aging Project; GTEx, genotype-tissue expression; AFR, African; OPC, oligodendrocyte precursor cell; eQTL, expression quantitative trait loci; DEG, differential expressed gene; Astro, astrocyte; Exc, excitatory neuron; Inh, inhibitory neuron; CAMs, cell adhesion molecules; Micro, microglia; Oligo, oligodendrocyte; End, endothelial cells; Fib, fibroblasts; Per, pericytes; SMC, smooth muscle cell; VLMC, vascular and leptomeningeal cells; Micro-PVM, microglia and perivascular macrophages; GWAS, genome-wide association analysis; scATAC, single-cell chromatin accessibility; SEA-AD, Seattle Alzheimer’s Disease Brain Cell Atlas.

    Techniques Used: Biomarker Discovery, Variant Assay, Derivative Assay, Expressing, GWAS

    Related Articles

    Transformation Assay:

    Article Title: Local genetic covariance analysis with lipid traits identifies novel loci for early-onset Alzheimer's Disease.
    Article Snippet: .. P-values were extracted and transformed – using -log10(P) – from the results of the MetaBrain eQTL data, the gene-based analysis, and the ROSMAP methylation data for each gene. ..

    Methylation:

    Article Title: Local genetic covariance analysis with lipid traits identifies novel loci for early-onset Alzheimer's Disease.
    Article Snippet: .. P-values were extracted and transformed – using -log10(P) – from the results of the MetaBrain eQTL data, the gene-based analysis, and the ROSMAP methylation data for each gene. ..

    other:

    Article Title: Multi-ancestry genome-wide association meta-analysis of Parkinson’s disease
    Article Snippet: Multi-ancestry brain eQTL data from Zeng et al. are available at https://hoffmg01.hpc.mssm.edu/brema/ . eQTL/mQTL/caQTL data used for SMR outside of MetaBrain and eQTLGen are available at https://yanglab.westlake.edu.cn/software/smr/#DataResource .

    Blocking Assay:

    Article Title: Local genetic covariance analysis with lipid traits identifies novel loci for early-onset Alzheimer’s Disease
    Article Snippet: .. Locus zoom plots of these regions were inspected visually and any gene within LD of the EOAD top SNP in each region (any part of the gene can be within the LD block) was investigated further and given a composite score based on: 1) results from gene-based analysis; 2) AD risk scores from AGORA ( https://agora.adknowledgeportal.org/about ) hosting high-dimensional human transcriptomic, proteomic, and metabolomic evidence for gene association with AD; 3) MetaBrain eQTL data; 4) eQTL colocalization analyses; 5) ROSMAP brain DNA methylation data (see below); and 6) single cell RNA sequencing data from both humans and zebrafish. ..

    DNA Methylation Assay:

    Article Title: Local genetic covariance analysis with lipid traits identifies novel loci for early-onset Alzheimer’s Disease
    Article Snippet: .. Locus zoom plots of these regions were inspected visually and any gene within LD of the EOAD top SNP in each region (any part of the gene can be within the LD block) was investigated further and given a composite score based on: 1) results from gene-based analysis; 2) AD risk scores from AGORA ( https://agora.adknowledgeportal.org/about ) hosting high-dimensional human transcriptomic, proteomic, and metabolomic evidence for gene association with AD; 3) MetaBrain eQTL data; 4) eQTL colocalization analyses; 5) ROSMAP brain DNA methylation data (see below); and 6) single cell RNA sequencing data from both humans and zebrafish. ..

    RNA Sequencing:

    Article Title: Local genetic covariance analysis with lipid traits identifies novel loci for early-onset Alzheimer’s Disease
    Article Snippet: .. Locus zoom plots of these regions were inspected visually and any gene within LD of the EOAD top SNP in each region (any part of the gene can be within the LD block) was investigated further and given a composite score based on: 1) results from gene-based analysis; 2) AD risk scores from AGORA ( https://agora.adknowledgeportal.org/about ) hosting high-dimensional human transcriptomic, proteomic, and metabolomic evidence for gene association with AD; 3) MetaBrain eQTL data; 4) eQTL colocalization analyses; 5) ROSMAP brain DNA methylation data (see below); and 6) single cell RNA sequencing data from both humans and zebrafish. ..

    Expressing:

    Article Title: Whole-genome sequencing analyses suggest novel genetic factors associated with Alzheimer’s disease and a cumulative effects model for risk liability
    Article Snippet: .. We employed three different eQTL databases: genotype-tissue expression (GTEx) eQTL data, cell type-specific eQTL data from the Religious Orders Study/Memory and Aging Project (ROSMAP), and MetaBrain eQTL data. .. In the clinical diagnosis GWAS, the rs429358 locus exhibited colocalization with four genes ( ZNF227 , TRAPPC6A , FOSB , and APOE ), and the rs28372356 locus was found to colocalize with APCDD1 (Fig. and Supplementary Data S ).



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    a , b Colocalization of GWAS of clinical diagnosis ( a ) and Aβ levels ( b ) <t>with</t> <t>ROSMAP,</t> MetaBrain, and GTEx eQTLs. Colocalizations with a posterior probability above 0.5 are shown. c Heatmap of gene prioritization of loci reaching suggestive significance from single-variant association analysis. The heatmap includes genes nearest to lead-SNPs (red), <t>eQTL</t> colocalization (green), eQTL signals associated with lead-SNPs (yellow), peak-to-gene connections identified through scATAC (blue), and evidence from prior publications (purple). d Heatmap of DEGs derived from a previous study (Mathys et al.) according to the final cognitive consensus diagnosis across brain cell subtypes. Significance levels are indicated as * p < 0.05, ** p < 0.01, and *** p < 0.001. e Regional p lots of the clinical diagnosis GWAS and GTEx cortex eQTLs for APCDD1 within a 500 kb window of the lead variant (rs28372356). f APCDD1 and VAPA expression across different cell types in response to pseudo-progression of SEA-AD. Each line represents the locally weighted mean expression (LOWESS) of the supertypes with each subclass. Source data are provided as a Source Data file. Aβ, amyloid beta; ROSMAP, Religious Orders Study/Memory and Aging Project; GTEx, genotype-tissue expression; AFR, African; OPC, oligodendrocyte precursor cell; eQTL, expression quantitative trait loci; DEG, differential expressed gene; Astro, astrocyte; Exc, excitatory neuron; Inh, inhibitory neuron; CAMs, cell adhesion molecules; Micro, microglia; Oligo, oligodendrocyte; End, endothelial cells; Fib, fibroblasts; Per, pericytes; SMC, smooth muscle cell; VLMC, vascular and leptomeningeal cells; Micro-PVM, microglia and perivascular macrophages; GWAS, genome-wide association analysis; scATAC, single-cell chromatin accessibility; SEA-AD, Seattle Alzheimer’s Disease Brain Cell Atlas.
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    a , b Colocalization of GWAS of clinical diagnosis ( a ) and Aβ levels ( b ) with ROSMAP, MetaBrain, and GTEx eQTLs. Colocalizations with a posterior probability above 0.5 are shown. c Heatmap of gene prioritization of loci reaching suggestive significance from single-variant association analysis. The heatmap includes genes nearest to lead-SNPs (red), eQTL colocalization (green), eQTL signals associated with lead-SNPs (yellow), peak-to-gene connections identified through scATAC (blue), and evidence from prior publications (purple). d Heatmap of DEGs derived from a previous study (Mathys et al.) according to the final cognitive consensus diagnosis across brain cell subtypes. Significance levels are indicated as * p < 0.05, ** p < 0.01, and *** p < 0.001. e Regional p lots of the clinical diagnosis GWAS and GTEx cortex eQTLs for APCDD1 within a 500 kb window of the lead variant (rs28372356). f APCDD1 and VAPA expression across different cell types in response to pseudo-progression of SEA-AD. Each line represents the locally weighted mean expression (LOWESS) of the supertypes with each subclass. Source data are provided as a Source Data file. Aβ, amyloid beta; ROSMAP, Religious Orders Study/Memory and Aging Project; GTEx, genotype-tissue expression; AFR, African; OPC, oligodendrocyte precursor cell; eQTL, expression quantitative trait loci; DEG, differential expressed gene; Astro, astrocyte; Exc, excitatory neuron; Inh, inhibitory neuron; CAMs, cell adhesion molecules; Micro, microglia; Oligo, oligodendrocyte; End, endothelial cells; Fib, fibroblasts; Per, pericytes; SMC, smooth muscle cell; VLMC, vascular and leptomeningeal cells; Micro-PVM, microglia and perivascular macrophages; GWAS, genome-wide association analysis; scATAC, single-cell chromatin accessibility; SEA-AD, Seattle Alzheimer’s Disease Brain Cell Atlas.

    Journal: Nature Communications

    Article Title: Whole-genome sequencing analyses suggest novel genetic factors associated with Alzheimer’s disease and a cumulative effects model for risk liability

    doi: 10.1038/s41467-025-59949-y

    Figure Lengend Snippet: a , b Colocalization of GWAS of clinical diagnosis ( a ) and Aβ levels ( b ) with ROSMAP, MetaBrain, and GTEx eQTLs. Colocalizations with a posterior probability above 0.5 are shown. c Heatmap of gene prioritization of loci reaching suggestive significance from single-variant association analysis. The heatmap includes genes nearest to lead-SNPs (red), eQTL colocalization (green), eQTL signals associated with lead-SNPs (yellow), peak-to-gene connections identified through scATAC (blue), and evidence from prior publications (purple). d Heatmap of DEGs derived from a previous study (Mathys et al.) according to the final cognitive consensus diagnosis across brain cell subtypes. Significance levels are indicated as * p < 0.05, ** p < 0.01, and *** p < 0.001. e Regional p lots of the clinical diagnosis GWAS and GTEx cortex eQTLs for APCDD1 within a 500 kb window of the lead variant (rs28372356). f APCDD1 and VAPA expression across different cell types in response to pseudo-progression of SEA-AD. Each line represents the locally weighted mean expression (LOWESS) of the supertypes with each subclass. Source data are provided as a Source Data file. Aβ, amyloid beta; ROSMAP, Religious Orders Study/Memory and Aging Project; GTEx, genotype-tissue expression; AFR, African; OPC, oligodendrocyte precursor cell; eQTL, expression quantitative trait loci; DEG, differential expressed gene; Astro, astrocyte; Exc, excitatory neuron; Inh, inhibitory neuron; CAMs, cell adhesion molecules; Micro, microglia; Oligo, oligodendrocyte; End, endothelial cells; Fib, fibroblasts; Per, pericytes; SMC, smooth muscle cell; VLMC, vascular and leptomeningeal cells; Micro-PVM, microglia and perivascular macrophages; GWAS, genome-wide association analysis; scATAC, single-cell chromatin accessibility; SEA-AD, Seattle Alzheimer’s Disease Brain Cell Atlas.

    Article Snippet: We employed three different eQTL databases: genotype-tissue expression (GTEx) eQTL data, cell type-specific eQTL data from the Religious Orders Study/Memory and Aging Project (ROSMAP), and MetaBrain eQTL data.

    Techniques: Biomarker Discovery, Variant Assay, Derivative Assay, Expressing, GWAS