Expression data from human liver with or without type 2 diabetes
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PROVIDER: S-DIXA-D-1066 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:The liver may regulate glucose homeostasis by modulating the sensitivity/resistance of peripheral tissues to insulin, by way of the production of secreted proteins, termed hepatokines. To identify hepatic secretory proteins involved in insulin resistance, we performed liver biopsies in humans with or without type 2 diabetes and conducted a comprehensive analysis of gene expression profiles.
2010-07-31 | GSE23343 | GEO
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Project description:The liver may regulate glucose homeostasis by modulating the sensitivity/resistance of peripheral tissues to insulin, by way of the production of secreted proteins, termed hepatokines. To identify hepatic secretory proteins involved in insulin resistance, we performed liver biopsies in humans with or without type 2 diabetes and conducted a comprehensive analysis of gene expression profiles. Samples for analysis were obtained from ten patients with type 2 diabetes and 7 subjects with normal glucose tolerance, who were admitted to Kanazawa University Hospital. Hepatic tissues were obtained with percutaneous needle liver biopsy, and immediately frozen in liquid nitrogen and stored at −80°C until use. This dataset is part of the TransQST collection.
2010-07-31 | E-GEOD-23343 | biostudies-arrayexpress
Project description:Hepatic lipid accumulation is an important complication of obesity linked to risk for type 2 diabetes. To identify novel transcriptional changes in human liver which could contribute to hepatic lipid accumulation and associated insulin resistance and type 2 diabetes (DM2), we evaluated gene expression and gene set enrichment in surgical liver biopsies from 13 obese (9 with DM2) and 5 control subjects, obtained in the fasting state at the time of elective abdominal surgery for obesity or cholecystectomy. RNA was isolated for cRNA preparation and hybridized to Affymetrix U133A microarrays.
2009-06-01 | GSE15653 | GEO
Project description:The association between the amount and sources of fructose intake with insulin sensitivity and liver fat needs further elucidation. This study aimed at examining whether habitual intake of sucrose plus non-sucrose bound as well as of non-sucrose bound fructose (total fructose, fruit-derived, juice-derived, sugar sweetened beverages (SSB)-derived fructose) is cross-sectionally associated with insulin sensitivity and fatty liver index (FLI). Fructose intake was estimated using the EPIC food frequency questionnaire from 161 participants with type 2 diabetes (T2D) in the ongoing German Diabetes Study (GDS) (age 53 ± 9 years; HbA1c 6.4 ± 0.9%) and 62 individuals without diabetes (CON) (47 ± 14 years; 5.3 ± 0.3%). Peripheral (M-value) and hepatic insulin resistance were assessed by hyperinsulinemic-euglycemic clamps with stable isotope dilution. FLI was calculated based on body mass index, waist circumference, triglyceride and gamma glutamyl transferase concentrations. Multivariable linear regression analyses were performed. A doubling of SSB-derived sucrose plus non-sucrose bound as well as of non-sucrose bound fructose intake was independently associated with a reduction of the M-value by -2.6% (-4.9; -0.2) and -2.7% (-5.2; -0.1) among T2D, respectively, with an increase in the odds of fatty liver by 16% and 17%, respectively among T2D (all p < 0.05). Doubling fruit-derived sucrose plus non-sucrose bound fructose intake independently related to a reduction in the odds of fatty liver by 13% (p = 0.033) among T2D. Moderate SSB-derived fructose intake may detrimentally affect peripheral insulin sensitivity, whereas fruit-derived fructose intake appeared beneficial for liver fat content.
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Project description:Although the early mechanisms responsible for diabetic kidney disease remain unclear, it is widely believed that chronic hyperglycemia disrupts the proteolytic milieu in the diabetic kidney and may contribute to early kidney injury. We thus performed mechanistic peptidomics in type 1 diabetes before the onset of microalbuminuria. In the discovery cohort of 30 participants, we identified 6550 peptides from 753 proteins. After removing false hits and potential contaminants, there were 6323 quantified peptides: 5708 peptides can be found in youths with type 1 diabetes, 5011 in healthy controls, and 4396 common to both groups. After applying a cut-off of 100%, there were 162 peptides found in each and every urine sample. From this subset, fifteen peptides were differentially excreted between youths with type 1 diabetes and their non-diabetic peers (P < 0.05, t-test); five remained significant after Benjamini-Hochberg adjustment (Q < 0.05). Excretion rates of six peptides were validated in a second cohort of thirty participants using parallel reaction monitoring (separate PRIDE file). Interestingly, these peptides originated from a small region near the C-terminus of uromodulin, a kidney-specific protein. In silico analyses of cleavage sites implicated several metallo and serine proteases involved in wound healing. Two of the uromodulin peptides activated NFκB in a TLR4-dependent manner in cultured kidney tubular cells and also promoted neutrophil migration in vitro. In summary, the differential excretion of uromodulin peptides may shed light onto early inflammatory processes in the diabetic kidney.
2020-01-20 | PXD012210 | Pride
Project description:Diabetic kidney disease is the leading cause of end-stage renal disease worldwide. Our understanding of the early kidney response to chronic hyperglycemia remains incomplete. In this study, we aimed to uncover the early, dysregulated pathways in the diabetic kidney before the onset of microalbuminuria by analysing the urinary proteomes of otherwise healthy youths with and without type 1 diabetes. Our study population included two cohorts for the discovery (N = 30) and validation (N = 30) of differentially excreted proteins. Of the 2451 proteins identified, 576 were quantified in all samples from the discovery cohort, and 34 comprised the urinary signature for early type 1 diabetes after Benjamini-Hochberg adjustment (Q < 0.05). The top pathways associated with this signature included lysosome, glycosaminoglycan degradation, and innate immune system (Q < 0.01). Notably, all enzymes involved in keratan sulfate degradation were significantly elevated in urines from youths with type 1 diabetes (fold change > 1.6). Increased urinary excretion of monocyte differentiation antigen CD14, hexosaminidase A, and lumican was also observed in the validation cohort (P < 0.05). Our findings draw attention to novel pathways such as keratan sulfate degradation in the early kidney response to hyperglycemia.
2020-06-01 | PXD017213 | Pride
Project description:Genome-wide association studies (GWAS) have demonstrated the ability to identify the strongest causal common variants in complex human diseases. However, to date, the massive data generated from GWAS have not been maximally explored to identify true associations that fail to meet the stringent level of association required to achieve genome-wide significance. Genetics of gene expression (GGE) studies have shown promise towards identifying DNA variations associated with disease and providing a path to functionally characterize findings from GWAS. Here, we present the first empiric study to systematically characterize the set of single nucleotide polymorphisms associated with expression (eSNPs) in liver, subcutaneous fat, and omental fat tissues, demonstrating these eSNPs are significantly more enriched for SNPs that associate with type 2 diabetes (T2D) in three large-scale GWAS than a matched set of randomly selected SNPs. This enrichment for T2D association increases as we restrict to eSNPs that correspond to genes comprising gene networks constructed from adipose gene expression data isolated from a mouse population segregating a T2D phenotype. Finally, by restricting to eSNPs corresponding to genes comprising an adipose subnetwork strongly predicted as causal for T2D, we dramatically increased the enrichment for SNPs associated with T2D and were able to identify a functionally related set of diabetes susceptibility genes. We identified and validated malic enzyme 1 (Me1) as a key regulator of this T2D subnetwork in mouse and provided support for the association of this gene to T2D in humans. This integration of eSNPs and networks provides a novel approach to identify disease susceptibility networks rather than the single SNPs or genes traditionally identified through GWAS, thereby extracting additional value from the wealth of data currently being generated by GWAS.
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Project description:The human Major Histocompatibility Complex (MHC) is a highly polymorphic genomic region occupying approximately 4 Mb on chromosome 6p21.3. The relationship between human MHC and type 1 diabetes (T1D) has been previously investigated. To fine map the disease locus in this region, we carried out both linkage and association analyses using the Type 1 Diabetes Genetics Consortium data.Two-point linkage analysis was performed with a set of microsatellite markers assuming a fully recessive inheritance model, where we found clustering of high LOD (logarithm of the odds) scores across the MHC region. To narrow down the linkage region, we performed association analyses using both microsatellite and two sets of single nucleotide polymorphism (SNP) markers. We focused on the nuclear families containing a discordant sib-pair (an affected and unaffected sib). For the microsatellite markers, we computed the average repeat length for each individual and carried out a paired t-test.Microsatellite marker D6S2884 showed the highest association in a sharp peak with a p value of 3.15E-24. We confirmed this finding when using also SNP markers performing a McNemar's test for association. The SNPs that showed the most significant evidence of association mapped to almost the same location as the microsatellite markers.Besides the main goal of fine mapping of T1D genes, our results also illustrated the differences and the advantage of using both linkage and association analyses. After the identification of a wide peak with linkage analysis, we were able to dramatically narrow down the region by performing association analysis.
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Project description:Expression data from Human liver biopsy
| PRJNA690119 | ENA