Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.
Project description:Aims/hypothesisMetabolomic profiling in populations with impaired glucose tolerance has revealed that branched chain and aromatic amino acids (BCAAs) are predictive of type 2 diabetes. Because gestational diabetes mellitus (GDM) shares pathophysiological similarities with type 2 diabetes, the metabolite profile predictive of type 2 diabetes could potentially identify women who will develop GDM.MethodsWe conducted a nested case-control study of 18- to 40-year-old women who participated in the Massachusetts General Hospital Obstetrical Maternal Study between 1998 and 2007. Participants were enrolled during their first trimester of a singleton pregnancy and fasting serum samples were collected. The women were followed throughout pregnancy and identified as having GDM or normal glucose tolerance (NGT) in the third trimester. Women with GDM (n = 96) were matched to women with NGT (n = 96) by age, BMI, gravidity and parity. Liquid chromatography-mass spectrometry was used to measure the levels of 91 metabolites.ResultsData analyses revealed the following characteristics (mean ± SD): age 32.8 ± 4.4 years, BMI 28.3 ± 5.6 kg/m(2), gravidity 2 ± 1 and parity 1 ± 1. Six metabolites (anthranilic acid, alanine, glutamate, creatinine, allantoin and serine) were identified as having significantly different levels between the two groups in conditional logistic regression analyses (p < 0.05). The levels of the BCAAs did not differ significantly between GDM and NGT.Conclusions/interpretationMetabolic markers identified as being predictive of type 2 diabetes may not have the same predictive power for GDM. However, further study in a racially/ethnically diverse population-based cohort is necessary.
Project description:Diabetes related cognitive dysfunction (DACD), one of the chronic complications of diabetes, seriously affect the quality of life in patients and increase family burden. Although the initial stage of DACD can lead to metabolic alterations or potential pathological changes, DACD is difficult to diagnose accurately. Moreover, the details of the molecular mechanism of DACD remain somewhat elusive. To understand the pathophysiological changes that underpin the development and progression of DACD, we carried out a global analysis of metabolic alterations in response to DACD. The metabolic alterations associated with DACD were first investigated in humans, using plasma metabonomics based on high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis. The related pathway of each metabolite of interest was searched in database online. The network diagrams were established KEGGSOAP software package. Receiver operating characteristic (ROC) analysis was used to evaluate diagnostic accuracy of metabolites. This is the first report of reliable biomarkers of DACD, which were identified using an integrated strategy. The identified biomarkers give new insights into the pathophysiological changes and molecular mechanisms of DACD. The disorders of sphingolipids metabolism, bile acids metabolism, and uric acid metabolism pathway were found in T2DM and DACD. On the other hand, differentially expressed plasma metabolites offer unique metabolic signatures for T2DM and DACD patients. These are potential biomarkers for disease monitoring and personalized medication complementary to the existing clinical modalities.
Project description:BackgroundIncidence rates of cardiovascular disease (CVD) are increasing, partly driven by the diabetes epidemic. Novel prediction tools and modifiable treatment targets are needed to enhance risk assessment and management. Plasma metabolite associations with subclinical atherosclerosis were investigated in the Diabetes Heart Study (DHS), a cohort enriched for type 2 diabetes (T2D).MethodsThe analysis included 700 DHS participants, 438 African Americans (AAs), and 262 European Americans (EAs), in whom coronary artery calcium (CAC) was assessed using ECG-gated computed tomography. Plasma metabolomics using liquid chromatography-mass spectrometry identified 853 known metabolites. An ancestry-specific marginal model incorporating generalized estimating equations examined associations between metabolites and CAC (log-transformed (CAC + 1) as outcome measure). Models were adjusted for age, sex, BMI, diabetes duration, date of plasma collection, time between plasma collection and CT exam, low-density lipoprotein cholesterol (LDL-C), and statin use.ResultsAt an FDR-corrected p-value < 0.05, 33 metabolites were associated with CAC in AAs and 36 in EAs. The androgenic steroids, fatty acid, phosphatidylcholine, and bile acid metabolism subpathways were associated with CAC in AAs, whereas fatty acid, lysoplasmalogen, and branched-chain amino acid (BCAA) subpathways were associated with CAC in EAs.ConclusionsStrikingly different metabolic signatures were associated with subclinical coronary atherosclerosis in AA and EA DHS participants.
Project description:In order to determine whether dis-regulation of a genetic pathway could explain the increased apoptosis of parp-2-/- double positive thymocytes, the gene expression profiles in double positive thymocytes derived from wild-type and parp-2-/- mice were analysed using Affymetrix oligonucleotide chips (mouse genome 430 2.0).
Project description:Cancer-associated fibroblasts (CAFs) have been recognized as important contributors to cancer development and progression. However, opposing evidence has been published whether CAFs, in addition to epigenetic, also undergo somatic genetic alterations and whether these changes contribute to carcinogenesis and tumour progression. We combined multiparameter DNA flow cytometry, flow-sorting and 6K SNP-arrays to study DNA aneuploidy, % S-phase, loss of heterozygosity (LOH) and copy number alterations (CNAs) to study somatic genetic alterations in cervical cancer-associated stromal cell fractions (n = 58) from formalin-fixed, paraffin-embedded (FFPE) samples. Tissue sections were examined for the presence of CAFs. Microsatellite analysis was used to study LOH. By flow cytometry we found no proof for DNA aneuploidy in the vimentin-positive stromal cell fractions of any samples (CV G0G1 population 3.7% +/- 1.2; S-phase 1.4% +/- 1.8). The genotype concordance between the stromal cells and the paired normal endometrium samples was > 99.9%. No evidence for CNAs or LOH was found in the stromal cell fractions. In contrast, high frequencies of DNA content abnormalities (43/57), a significant higher S-phase (14.6% +/- 8.5)(p = 0.0001) and substantial numbers of CNAs and LOH were identified in the keratin-positive epithelial cell fractions (CV G0G1 population 4.1% +/- 1.0). Smooth muscle actin and vimentin immunohistochemistry verified the presence of CAFs in all cases tested. LOH hot-spots on chromosomes 3p, 4p and 6p were confirmed by microsatellite analysis but the stromal cell fractions showed retention of heterozygosity only. From our study we conclude that stromal cell fractions from cervical carcinomas are DNA diploid, have a genotype undistinguishable from patient-matched normal tissue and are genetically stable. Stromal genetic changes do not seem to play a role during cervical carcinogenesis and progression. In addition, the stromal cell fraction of cervical carcinomas can be used as reference allowing large retrospective studies of archival FFPE tissues for which no normal reference tissue is available. Paired experiment, Endometrial (non-tumor) cells vs stromal cells from cervical tumors. Biological replicates: 58 patients. From 5 tumors also the tumor fraction was profiled.
Project description:Recurrent non-medullary thyroid carcinoma (NMTC) is a rare disease. We initially characterized 27 recurrent NMTC: 13 papillary thyroid cancers (PTC), 10 oncocytic follicular carcinomas (FTC-OV), and 4 non-oncocytic follicular carcinomas (FTC). A validation cohort composed of benign and malignant (both recurrent and non-recurrent) thyroid tumours was subsequently analysed (n = 20). Methods Data from genome-wide SNP arrays and flow cytometry were combined to determine the chromosomal dosage (allelic state) in these tumours, including mutation analysis of components of PIK3CA/AKT and MAPK pathways. Results All FTC-OVs showed a very distinct pattern of genomic alterations. Ten out of 10 FTC-OV cases showed near-haploidisation with or without subsequent genome endoreduplication. Near-haploidisation was seen in 5/10 as extensive chromosome-wide monosomy (allelic state [A]) with near-haploid DNA indices and retention of especially chromosome 7 (seen as a heterozygous allelic state [AB]). In the remaining 5/10 chromosomal allelic states AA with near diploid DNA indices were seen with allelic state AABB of chromosome 7, suggesting endoreduplication after preceding haploidisation. The latter was supported by the presence of both near-haploid and endoreduplicated tumour fractions in some of the cases. Results were confirmed using FISH analysis. Relatively to FTC-OV limited numbers of genomic alterations were identified in other types of recurrent NMTC studied, except for chromosome 22q which showed alterations in 6 of 13 PTCs. Only two HRAS, but no mutations of EGFR or BRAF were found in FTC-OV. The validation cohort showed two additional tumours with the distinct pattern of genomic alterations (both with oncocytic features and recurrent). Conclusions We demonstrate that recurrent FTC-OV is frequently characterised by genome-wide DNA haploidisation, heterozygous retention of chromosome 7, and endoreduplication of a near-haploid genome. Whether normal gene dosage on especially chromosome 7 (containing EGFR, BRAF, cMET) is crucial for FTC-OV tumour survival is an important topic for future research. 28 thyroid tumors from 27 patients were profiled by SNP array. Comparisons between different types were made.
Project description:Gestational diabetes mellitus (GDM) is a pregnancy-related metabolic disorder associated with short-term and long-term adverse health outcomes, but its pathogenesis has not been clearly elucidated. Investigations of the dynamic changes in metabolomic markers in different trimesters may reveal the underlying pathophysiology of GDM progression. Therefore, in the present study, we analysed the metabolic profiles of 75 women with GDM and 75 women with normal glucose tolerance throughout the three trimesters. We found that the variation trends of 38 metabolites were significantly changed during GDM development. Specifically, longitudinal analyses revealed that cysteine (Cys) levels significantly decreased over the course of GDM progression. Further study showed that Cys alleviated GDM in female mice at gestational day 14.5, possibly by inhibiting phosphoenolpyruvate carboxykinase to suppress hepatic gluconeogenesis. Taken together, these findings suggest that the Cys metabolism pathway might play a crucial role in GDM and Cys supplementation represents a potential new treatment strategy for GDM patients.
Project description:Asthma is a complex syndrome associated with episodic decompensations provoked by aeroaller-gen exposures. The underlying pathophysiological states driving exacerbations are latent in the resting state and do not adequately inform biomarker-driven therapy. A better understanding of the pathophysiological pathways driving allergic exacerbations is needed. We hypothesized that disease-associated pathways could be identified in humans by unbiased metabolomics of bron-choalveolar fluid (BALF) during the peak inflammatory response provoked by a bronchial aller-gen challenge. We analyzed BALF metabolites in samples from 12 volunteers who underwent segmental bronchial antigen provocation (SBP-Ag). Metabolites were quantified using liquid chromatography-tandem mass spectrometry (LC–MS/MS) followed by pathway analysis and cor-relation with airway inflammation. SBP-Ag induced statistically significant changes in 549 fea-tures that mapped to 72 uniquely identified metabolites. From these features, two distinct induci-ble metabolic phenotypes were identified by the principal component analysis, partitioning around medoids (PAM) and k-means clustering. Ten index metabolites were identified that in-formed the presence of asthma-relevant pathways, including unsaturated fatty acid produc-tion/metabolism, mitochondrial beta oxidation of unsaturated fatty acid, and bile acid metabolism. Pathways were validated using proteomics in eosinophils. A segmental bronchial allergen chal-lenge induces distinct metabolic responses in humans, providing insight into pathogenic and pro-tective endotypes in allergic asthma.