186 research outputs found
Periodontitis as a risk factor for systemic disease: Are microparticles the missing link?
Periodontitis is an oral inflammatory disease affecting the teeth supportive tissue. Its bacterial infectious etiology is well established. Periodontitis has been associated with increased prevalence of systemic diseases such as cardiovascular diseases, diabetes, rheumatoid arthritis, preeclampsia, preterm birth and inflammatory bowel disease. The rational of considering periodontitis as risk factor for systemic disease is the passage of inflammatory cytokines and/or bacteria in the bloodstream, thus affecting distant organs.
Membrane microparticles are released by multiple cells in inflammatory environment. Recent data suggested the role of these microparticles in the pathogenic process of many systemic diseases, that can be also associated to periodontitis. We hypothesized that periodontitis could be a chronic reservoir of microparticles, hence elucidating partially the interaction with systemic diseases initiation or progression
Positional Cloning of a Type 2 Diabetes Quantitative Trait Locus; Tomosyn-2, a Negative Regulator of Insulin Secretion
We previously mapped a type 2 diabetes (T2D) locus on chromosome 16 (Chr 16) in an F2 intercross from the BTBR T (+) tf (BTBR) Lepob/ob and C57BL/6 (B6) Lepob/ob mouse strains. Introgression of BTBR Chr 16 into B6 mice resulted in a consomic mouse with reduced fasting plasma insulin and elevated glucose levels. We derived a panel of sub-congenic mice and narrowed the diabetes susceptibility locus to a 1.6 Mb region. Introgression of this 1.6 Mb fragment of the BTBR Chr 16 into lean B6 mice (B6.16BT36–38) replicated the phenotypes of the consomic mice. Pancreatic islets from the B6.16BT36–38 mice were defective in the second phase of the insulin secretion, suggesting that the 1.6 Mb region encodes a regulator of insulin secretion. Within this region, syntaxin-binding protein 5-like (Stxbp5l) or tomosyn-2 was the only gene with an expression difference and a non-synonymous coding single nucleotide polymorphism (SNP) between the B6 and BTBR alleles. Overexpression of the b-tomosyn-2 isoform in the pancreatic β-cell line, INS1 (832/13), resulted in an inhibition of insulin secretion in response to 3 mM 8-bromo cAMP at 7 mM glucose. In vitro binding experiments showed that tomosyn-2 binds recombinant syntaxin-1A and syntaxin-4, key proteins that are involved in insulin secretion via formation of the SNARE complex. The B6 form of tomosyn-2 is more susceptible to proteasomal degradation than the BTBR form, establishing a functional role for the coding SNP in tomosyn-2. We conclude that tomosyn-2 is the major gene responsible for the T2D Chr 16 quantitative trait locus (QTL) we mapped in our mouse cross. Our findings suggest that tomosyn-2 is a key negative regulator of insulin secretion
The diabetes gene Zfp69 modulates hepatic insulin sensitivity in mice
AIMS/HYPOTHESIS: Zfp69 was previously identified by positional cloning as a candidate gene for obesity-associated diabetes. C57BL/6J and New Zealand obese (NZO) mice carry a loss-of-function mutation due to the integration of a retrotransposon. On the NZO background, the Zfp69 locus caused severe hyperglycaemia and loss of beta cells. To provide direct evidence for a causal role of Zfp69, we investigated the effects of its overexpression on both a lean [B6-Tg(Zfp69)] and an obese [NZO/B6-Tg(Zfp69)] background. METHODS: Zfp69 transgenic mice were generated by integrating the cDNA into the ROSA locus of the C57BL/6 genome and characterised. RESULTS: B6-Tg(Zfp69) mice were normoglycaemic, developed hyperinsulinaemia, and exhibited increased expression of G6pc and Pck1 and slightly reduced phospho-Akt levels in the liver. During OGTTs, glucose clearance was normal but insulin levels were significantly higher in the B6-Tg(Zfp69) than in control mice. The liver fat content and plasma triacylglycerol levels were significantly increased in B6-Tg(Zfp69) and NZO/B6-Tg(Zfp69) mice on a high-fat diet compared with controls. Liver transcriptome analysis of B6-Tg(Zfp69) mice revealed a downregulation of genes involved in glucose and lipid metabolism. Specifically, expression of Nampt, Lpin2, Map2k6, Gys2, Bnip3, Fitm2, Slc2a2, Ppargc1α and Insr was significantly decreased in the liver of B6-Tg(Zfp69) mice compared with wild-type animals. However, overexpression of Zfp69 did not induce overt diabetes with hyperglycaemia and beta cell loss. CONCLUSIONS/INTERPRETATION: Zfp69 mediates hyperlipidaemia, liver fat accumulation and mild insulin resistance. However, it does not induce type 2 diabetes, suggesting that the diabetogenic effect of the Zfp69 locus requires synergy with other as yet unidentified genes
Evaluation of four novel genetic variants affecting hemoglobin A1c levels in a population-based type 2 diabetes cohort (the HUNT2 study)
<p>Abstract</p> <p>Background</p> <p>Chronic hyperglycemia confers increased risk for long-term diabetes-associated complications and repeated hemoglobin A1c (HbA1c) measures are a widely used marker for glycemic control in diabetes treatment and follow-up. A recent genome-wide association study revealed four genetic loci, which were associated with HbA1c levels in adults with type 1 diabetes. We aimed to evaluate the effect of these loci on glycemic control in type 2 diabetes.</p> <p>Methods</p> <p>We genotyped 1,486 subjects with type 2 diabetes from a Norwegian population-based cohort (HUNT2) for single-nucleotide polymorphisms (SNPs) located near the <it>BNC2</it>, <it>SORCS1</it>, <it>GSC </it>and <it>WDR72 </it>loci. Through regression models, we examined their effects on HbA1c and non-fasting glucose levels individually and in a combined genetic score model.</p> <p>Results</p> <p>No significant associations with HbA1c or glucose levels were found for the <it>SORCS1</it>, <it>BNC2</it>, <it>GSC </it>or <it>WDR72 </it>variants (all <it>P</it>-values > 0.05). Although the observed effects were non-significant and of much smaller magnitude than previously reported in type 1 diabetes, the <it>SORCS1 </it>risk variant showed a direction consistent with increased HbA1c and glucose levels, with an observed effect of 0.11% (<it>P </it>= 0.13) and 0.13 mmol/l (<it>P </it>= 0.43) increase per risk allele for HbA1c and glucose, respectively. In contrast, the <it>WDR72 </it>risk variant showed a borderline association with reduced HbA1c levels (<it>β </it>= -0.21, <it>P </it>= 0.06), and direction consistent with decreased glucose levels (<it>β </it>= -0.29, <it>P </it>= 0.29). The allele count model gave no evidence for a relationship between increasing number of risk alleles and increasing HbA1c levels (<it>β </it>= 0.04, <it>P </it>= 0.38).</p> <p>Conclusions</p> <p>The four recently reported SNPs affecting glycemic control in type 1 diabetes had no apparent effect on HbA1c in type 2 diabetes individually or by using a combined genetic score model. However, for the <it>SORCS1 </it>SNP, our findings do not rule out a possible relationship with HbA1c levels. Hence, further studies in other populations are needed to elucidate whether these novel sequence variants, especially rs1358030 near the <it>SORCS1 </it>locus, affect glycemic control in type 2 diabetes.</p
The effect of ABCA1 gene polymorphisms on ischaemic stroke risk and relationship with lipid profile
<p>Abstract</p> <p>Background</p> <p>Ischaemic stroke is a common disorder with genetic and environmental components contributing to overall risk. Atherothromboembolic abnormalities, which play a crucial role in the pathogenesis of ischaemic stroke, are often the end result of dysregulation of lipid metabolism. The ATP Binding Cassette Transporter (<it>ABCA1</it>) is a key gene involved in lipid metabolism. It encodes the cholesterol regulatory efflux protein which mediates the transfer of cellular phospholipids and cholesterol to acceptor apolipoproteins such as apolipoprotein A-I (ApoA-I). Common polymorphisms in this gene affect High Density Lipoprotein Cholesterol (HDL-C) and Apolipoprotein A-I levels and so influence the risk of atherosclerosis. This study has assessed the distribution of <it>ABCA1 </it>polymorphisms and haplotype arrangements in patients with ischaemic stroke and compared them to an appropriate control group. It also examined the relationship of these polymorphisms with serum lipid profiles in cases and controls.</p> <p>Methods</p> <p>We studied four common polymorphisms in <it>ABCA1 </it>gene: G/A-L158L, G/A-R219K, G/A-G316G and G/A-R1587K in 400 Caucasian ischaemic stroke patients and 487 controls. Dynamic Allele Specific Hybridisation (DASH) was used as the genotyping assay.</p> <p>Results</p> <p>Genotype and allele frequencies of all polymorphisms were similar in cases and controls, except for a modest difference in the <it>ABCA1 </it>R219K allele frequency (P-value = 0.05). Using the PHASE2 program, haplotype frequencies for the four loci (158, 219, 316, and 1587) were estimated in cases and controls. There was no significant difference in overall haplotypes arrangement in patients group compared to controls (p = 0.27). 2211 and 1211 haplotypes (1 = common allele, 2 = rare allele) were more frequent in cases (p = 0.05). Adjusted ORs indicated 40% and 46% excess risk of stroke for these haplotypes respectively. However, none of the adjusted ORs were statistically significant. Individuals who had R219K "22" genotype had a higher LDL level (p = 0.001).</p> <p>Conclusion</p> <p>Our study does not support a major role for the <it>ABCA1 </it>gene as a risk factor for ischaemic stroke. Some haplotypes may confer a minor amount of increased risk or protection. Polymorphisms in this gene may influence serum lipid profile.</p
Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers
Environmental variation predicts patterns of genomic variation in an African tropical forest frog
Central African rainforests are predicted to be disproportionately affected by future climate change. How species will cope with these changes is unclear, but rapid environmental changes will likely impose strong selection pressures. Here we examined environmental drivers of genomic variation in the central African puddle frog (Phrynobatrachus auritus) to identify areas of elevated environmentally-associated turnover. We also compared current and future climate models to pinpoint areas of high genomic vulnerability where allele frequencies will have to shift the most in order to keep pace with future climate change. Neither physical landscape barriers nor the effects of past Pleistocene refugia influenced genomic differentiation. Alternatively, geographic distance and seasonal aspects of precipitation are the most important drivers of SNP allele frequency variation. Patterns of genomic differentiation coincided with key ecological gradients across the forest-savanna ecotone, montane areas, and a coastal to interior rainfall gradient. Areas of greatest vulnerability were found in the lower Sanaga basin, the southeastern region of Cameroon, and southwest Gabon. In contrast with past conservation efforts that have focused on hotspots of species richness or endemism, our findings highlight the importance of maintaining environmentally heterogeneous landscapes to preserve genomic variation and ongoing evolutionary processes in the face of climate change
Specific loss of adipocyte CD248 improves metabolic health via reduced white adipose tissue hypoxia, fibrosis and inflammation
Background: A positive energy balance promotes white adipose tissue (WAT) expansion which is characterized by activation of a repertoire of events including hypoxia, inflammation and extracellular matrix remodelling. The transmembrane glycoprotein CD248 has been implicated in all these processes in different malignant and inflammatory diseases but its potential impact in WAT and metabolic disease has not been explored.Methods: The role of CD248 in adipocyte function and glucose metabolism was evaluated by omits analyses in human WAT, gene knockdowns in human in vitro differentiated adipocytes and by adipocyte-specific and inducible Cd248 gene knockout studies in mice.Findings: CD248 is upregulated in white but not brown adipose tissue of obese and insulin-resistant individuals. Gene ontology analyses showed that CD248 expression associated positively with pro-inflammatory/pro-fibrotic pathways. By combining data from several human cohorts with gene knockdown experiments in human adipocytes, our results indicate that CD248 acts as a microenvironmental sensor which mediates part of the adipose tissue response to hypoxia and is specifically perturbed in white adipocytes in the obese state. Adipocytespecific and inducible Cd248 knockouts in mice, both before and after diet-induced obesity and insulin resistance/glucose intolerance, resulted in increased microvascular density as well as attenuated hypoxia, inflammation and fibrosis without affecting fat cell volume. This was accompanied by significant improvements in insulin sensitivity and glucose tolerance.Interpretation: CD248 exerts detrimental effects on WAT phenotype and systemic glucose homeostasis which may be reversed by suppression of adipocyte CD248. Therefore, CD248 may constitute a target to treat obesity-associated co-morbidities. (C) 2019 The Authors. Published by Elsevier B.V.</p
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