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5,946 results for “diabetes type 2”
Multi-Omic Integrated networks connect DNA methylation and miRNA with skeletal muscle plasticity to chronic exercise in type 2 diabetic obesity
GEO Series GSE58250. synthetic construct; Homo sapiens. 102 samples. Type: Non-coding RNA profiling by array; Expression profiling by array; Methylation profiling by array.
Differential promoter methylation of macrophage genes correlates with impaired vascular growth in ischemic muscles of hyperlipidemic and type 2 diabetic mice
GEO Series GSE65803. Mus musculus. 21 samples. Type: Methylation profiling by high throughput sequencing.
Circulating Exosomal miR-20b-5p is Elevated in Type 2 Diabetes and Could Impair Insulin Action in Human Skeletal Muscle.
GEO Series GSE102295. Homo sapiens. 6 samples. Type: Expression profiling by array.
Sodium ferrous citrate and 5-aminolevulinic acid improve type 2 diabetes by maintaining muscle and mitochondrial health
GEO Series GSE201092. Mus musculus. 6 samples. Type: Expression profiling by array.
Expression data from peripheral blood mononuclear cells（PBMCs) in newly diagnosed type 2 diabetes
GEO Series GSE168437. Homo sapiens. 4 samples. Type: Expression profiling by array; Non-coding RNA profiling by array.
Gene expression profiles of beta-cell enriched tissue obtained by Laser Capture Microdissection from subjects with type 2 diabetes
GEO Series GSE20966. Homo sapiens. 20 samples. Type: Expression profiling by array.
Disrupted Circadian Oscillations in Type 2 Diabetes are Linked to Altered Rhythmic Mitochondrial Metabolism in Skeletal Muscle [Affymetrix]
GEO Series GSE182120. Homo sapiens. 49 samples. Type: Expression profiling by high throughput sequencing.
Single-cell Transcriptomic Atlas of Gingival Mucosa in Type 2 Diabetes
GEO Series GSE188217. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
DNA methylation data throughout human muscle cell differentiation in individuals with type 2 diabetes and controls
GEO Series GSE166787. Homo sapiens. 56 samples. Type: Methylation profiling by genome tiling array.
Disrupted Circadian Oscillations in Type 2 Diabetes are Linked to Altered Rhythmic Mitochondrial Metabolism in Skeletal Muscle
GEO Series GSE182121. Homo sapiens. 235 samples. Type: Expression profiling by high throughput sequencing; Expression profiling by array.
Adipocyte Precursor Cells from First Degree Relatives of type 2 diabetic patients feature changes of hsa-mir-23a-5p, -193a-5p, and -193b-5p and Insulin-Like Growth Factor 2 expression [smallRNA-seq]
GEO Series GSE162133. Homo sapiens. 4 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Summary level-data accompanying "A functional locus at 8q21.13 associated to FABP4 levels and causally links coronary artery disease and type 2 diabetes"
<p><strong>Introduction</strong></p> <p>These are the <em>Summary Level-data</em> as presented in:</p> <p>"A functional locus at 8q21.13 associated to FABP4 levels and causally links coronary artery disease and type 2 diabetes". <em>Unpublished</em>. (tentative title)</p> <p>If you use these data please cite this DOI or the (pre)print when available. When you have any questions or comments regarding this study or these files, please contact me via:</p> <p><strong>Sander W. van der Laan, PhD</strong> | <em>Central Diagnostics Laboratory, Division Laboratory, Pharmacy and Biomedical genetics, Circulatory Health Program, University Medical Center Utrecht, Utrecht University</em> | s.w.vanderlaan-2 [at] umcutrecht [dot] nl or s.w.vanderlaan [at] gmail [dot] com | @swvanderlaan</p> <p> </p> <p><strong>Files and description</strong></p> <p>There are three files available:</p> <ol> <li>meta.GWAS.FABP4.1Gp1.EUR.MODEL1.* - Gzipped file containing all the (unfiltered) meta-analysis results for model 1 (FABP4 ~ SNP + age + sex + PC1-10 + study specific covariates). <ul> <li>Discovery dataset ends with: "summaryQC.ELISAonly.txt.gz"</li> <li>Replication dataset ends with: "summaryQC.OLINKonly.txt.gz"</li> <li>Combined dataset ends with: "summaryQC.txt.gz"</li> </ul> </li> <li>meta.GWAS.FABP4.1Gp1.EUR.MODEL2.* - Gzipped file containing all the (unfiltered) meta-analysis results for model 2 (FABP4 ~ SNP + age + sex + PC1-10 + study specific covariates + BMI). <ul> <li>Discovery dataset ends with: "summaryQC.ELISAonly.txt.gz"</li> <li>Replication dataset ends with: "summaryQC.OLINKonly.txt.gz"</li> <li>Combined dataset ends with: "summaryQC.txt.gz"</li> </ul> </li> <li>meta.GWAS.FABP4.1Gp1.EUR.MODEL3.* - Gzipped file containing all the (unfiltered) meta-analysis results for model 3 (FABP4 ~ SNP + age + sex + PC1-10 + study specific covariates + BMI + eGFR). <ul> <li>Discovery dataset ends with: "summaryQC.ELISAonly.txt.gz"</li> <li>Replication dataset ends with: "summaryQC.OLINKonly.txt.gz"</li> <li>Combined dataset ends with: "summaryQC.txt.gz"</li> </ul> </li> </ol> <p>All these files have the same lay-out and are gzipped. The reference used for meta-analysis of GWAS was 1000G phase 1, version 3 (so called 'ALL.wgs.integrated_phase1_v3.20101123.snps_indels_sv.sites'-panel) using data from the EUR populations. For a more detailed explanation of these columns and the reason to include them, please refer to <a href="https://doi.org/10.1093/hmg/ddn288">De Bakker <em>et al.</em> Hum Mol Genet 2008</a>. </p> <ul> <li><em>VARIANTID</em> - variantID as represented in 1000G phase 1, version 3.</li> <li><em>CHR</em> - chromosome numbers [1-22 and X, Y, MT].</li> <li><em>POS</em> - base pair position.</li> <li><em>MINOR</em> - minor allele as present in 1000G.</li> <li><em>MAJOR</em> - major allele as present in 1000G.</li> <li><em>MAF</em> - minor allele frequency as present in 1000G.</li> <li><em>CODEDALLELE</em> - coded allele, <em>i.e.</em> the effect allele, as represented (and harmonized) across cohorts. Note that this is not necessarily the minor allele!</li> <li><em>OTHERALLELE</em> - the other allele, <em>i.e.</em> the non-effect allele.</li> <li><em>CAF</em> - coded allele frequency, <em>i.e.</em> the effect allele frequency. Note that this is not necessarily the minor allele frequency!</li> <li><em>N_EFF</em> - the effective sample size corrected for the imputation quality.</li> <li><em>Z_SQRTN</em> - Z-score of the effective sample-size-weighted meta-analysis.</li> <li><em>P_SQRTN</em> - P-value of the effective sample-size-weighted meta-analysis.</li> <li><em>BETA_FIXED</em> - beta from the fixed-effects model.</li> <li><em>SE_FIXED</em> - standard error from the fixed-effects model.</li> <li><em>Z_FIXED</em> - z-score from the fixed-effects model.</li> <li><em>P_FIXED</em> - P-value from the fixed-effects model.</li> <li><em>BETA_LOWER_FIXED</em> - 95% lower confidence interval of the beta from the fixed-effects model.</li> <li><em>BETA_UPPER_FIXED</em> - 95% upper confidence interval of the beta from the fixed-effects model.</li> <li><em>BETA_GC</em> - beta after correcting the fixed-effects beta for genomic inflation.</li> <li><em>SE_GC</em> - standard error after correcting the fixed-effects SE for genomic inflation.</li> <li><em>Z_GC</em> - Z-score after correcting the fixed-effects Z-score for genomic inflation.</li> <li><em>P_GC</em> - P-value after correcting the fixed-effects p-value for genomic inflation.</li> <li><em>BETA_RANDOM</em> - beta from the random-effects model.</li> <li><em>SE_RANDOM</em> - standard error from the random-effects model.</li> <li><em>Z_RANDOM</em> - Z-score from the random-effects model.</li> <li><em>P_RANDOM</em> - P-value from the random-effects model.</li> <li><em>BETA_LOWER_RANDOM</em> - 95% lower confidence interval of the beta from the random-effects model.</li> <li><em>BETA_UPPER_RANDOM</em> - 95% upper confidence interval of the beta from the random-effects model.</li> <li><em>COCHRANS_Q</em> - Cochran's Q as a measure of heterogeneity between studies (<a href="https://wiki.joannabriggs.org/pages/viewpage.action?pageId=9273407">see this wiki</a>).</li> <li><em>DF</em> - degrees of freedom, equals the number of studies included for the respective variant (<em>N</em>) minus 1, <em>i.e.</em> <em>DF = N-1</em>.</li> <li><em>P_COCHRANS_Q</em> - P-value of Cochran's heterogeneity test.</li> <li><em>I_SQUARED</em> - <em>I<sup>2</sup></em> as a measure of heterogeneity between studies (<a href="https://wiki.joannabriggs.org/display/MANUAL/3.3.10.2+Quantification+of+the+statistical+heterogeneity%3A+I+squared">see this wiki</a>).</li> <li><em>TAU_SQUARED</em> - <em>Tau<sup>2</sup></em> as a measure of true heterogeneity between studies (<a href="https://wiki.joannabriggs.org/display/MANUAL/3.3.10.3+Tau-squared+for+random+effects+model+meta-analysis">see this wiki</a>).</li> <li><em>DIRECTIONS</em> - the sign of beta in each contributing cohort, annotated as “.” if the variant is missing from a particular cohort.</li> <li><em>GENES_250KB</em> - list of all genes as mapped using GENCODE v19 (GRCh37, hg19, Feb2009) with 250kb.</li> <li><em>NEAREST_GENE</em> - the gene closest to the respective variant.</li> <li><em>NEAREST_GENE_ENSEMBLID</em> - the ENSEMBLID of the nearest gene.</li> <li><em>NEAREST_GENE_STRAND</em> - strand on which the nearest gene is present.</li> <li><em>VARIANT_FUNCTION</em> - variant function as taken from dbSNP v150.</li> <li><em>CAVEAT</em> - potential issue as reported by <a href="https://github.com/swvanderlaan/MetaGWASToolKit">MetaGWASToolKit</a>, <em>e.g.</em> if the variant is an A/T or C/G SNP with allele frequency between 0.35 and 0.65 (indicating strandedness ambiguity).</li> <li><em>QC</em> - utility column, can be used to filter out all the variants with <em>e.g.</em> 'CAF' < 0.001, 'DF' <= 2, 'N_EFF' < 5000 and 'CAVEAT' having an issue depending on the dataset used (discovery, replication, or combined).</li> </ul> <p> </p>
Patient journeys in type 2 diabetes treatments as part of the findings from Co-design Activity 1
<p>This is an enlargeable figure to elaborate on Figure 47 of Chininthorn's Ph.D. thesis.</p>
FIGURE 1. a–e in A genome-wide association search for type 2 diabetes genes in African Americans.
FIGURE 1. a–e. Hemielimaea adeviara sp. nov., Liu, Song and Yuan. a. Stridulatory area of male left tegmen; b. Stridulatory area of male right tegmen; c. Male stridulaotry file on underside of left tegmen, whole view; d. Central quarter part of stridulatory file on underside of left tegmen; e. Apical area of male subgenital plate; f. Male abdominal apex in dorsal view; g. Male abdominal apex in lateral view; h. Male phallic sclerite in dorsal view.
Neuroendocrine Brake for Type 2 Diabetes Mellitus
ClinicalTrials.gov study NCT00450710. IPD Sharing: Not stated. Countries: 1. Publications: 0.
BMS-646256 in Obese and Overweight Type 2 Diabetics
ClinicalTrials.gov study NCT00541567. IPD Sharing: Not stated. Countries: 0. Publications: 0.
The Effect of Continuous Glucose Monitoring in Individuals With Newly Diagnosed Type 2 Diabetes
ClinicalTrials.gov study NCT06471699. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Effects of First-Line Oral Hypoglycemics in Bone Markers of Treatment Naïve Saudi Adults With Type 2 Diabetes
ClinicalTrials.gov study NCT06439758. IPD Sharing: NO. Countries: 0. Publications: 0.
Evaluation of Efficacy and Safety of Combination Therapy of Henagliflozin Proline, Retagliptin and Metformin in New Diagnosed Type 2 Diabetes Patients
ClinicalTrials.gov study NCT06417489. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Exercise and Diet in Type 2 Diabetic Women
ClinicalTrials.gov study NCT00763074. IPD Sharing: Not stated. Countries: 0. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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OpenNeuro
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