Identification of putative biomarkers for leptomeningeal invasion in B-cell non-Hodgkin lymphoma by NMR metabolomics

Introduction

B-cell non-Hodgkin lymphoma (B-NHL) is the most common hematological malignancy and different genetic alterations are frequently detected in transformed B lymphocytes. Within this heterogeneous disease, certain aggressive subgroups have an increased risk of central nervous system (CNS) involvement at diagnosis and/or relapse, resulting in parenchymal or leptomeningeal infiltration (LI) in 5–15% of cases. The current sensitivity limitations of cerebrospinal fluid (CSF) cytology and contrast-enhanced MRI for CNS involvement, mainly at early stages, motivates the search for alternative diagnostic methods.

Objectives

Here we aim at using untargeted ¹H-NMR metabolomics to identify putative biomarkers for LI in B-NHL patients.

Methods

CSF and peripheral blood samples were obtained from B-NHL patients with a positive (n?=?7, LI group) or negative LI diagnostic (n?=?13, control group). For seven patients, CSF samples were collected during the course of intrathecal chemotherapy, making it possible to assess the patient´s response to treatment. ¹H-NMR spectra were acquired and statistical multivariate and univariate analysis were performed to identify significant alterations.

Results

Significant metabolite differences were found between LI and control groups in CSF, but not in serum. A predictive PLS-DA cross-validated model identified significant pool changes in glycine, alanine, pyruvate, acetylcarnitine, carnitine, and phenylalanine. Additionally, increments in protein signals were detected in the LI group. Significantly, the PLS-DA model predicted correctly all samples obtained from the group of patients in remission during LI treatment.

Conclusions

The results show that the CSF NMR-metabolomics approach is a promising complementary method in clinical diagnosis and treatment follow-up of LI in B-NHL patients.

     

Identification of new biomarkers of bronchopulmonary dysplasia using metabolomics

Metabolomics - Methanol utilization by bacteria is important for various industrial processes. Methylotrophic bacteria are taxonomically diverse and some species promote plant growth and induce...     

Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study)

Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically diagnosed as abnormally high urinary albumin excretion rate (AER). We hypothesize that subtle changes in the urine metabolome precede the clinically significant rise in AER. To test this, 52 type 1 diabetic patients were recruited by the FinnDiane study that had normal AER (normoalbuminuric). After an average of 5.5?years of follow-up half of the subjects (26) progressed from normal AER to microalbuminuria or DKD (macroalbuminuria), the other half remained normoalbuminuric. The objective of this study is to discover urinary biomarkers that differentiate the progressive form of albuminuria from non-progressive form of albuminuria in humans. Metabolite profiles of baseline 24?h urine samples were obtained by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) to detect potential early indicators of pathological changes. Multivariate logistic regression modeling of the metabolomics data resulted in a profile of metabolites that separated those patients that progressed from normoalbuminuric AER to microalbuminuric AER from those patients that maintained normoalbuminuric AER with an accuracy of 75% and a precision of 73%. As this data and samples are from an actual patient population and as such, gathered within a less controlled environment it is striking to see that within this profile a number of metabolites (identified as early indicators) have been associated with DKD already in literature, but also that new candidate biomarkers were found. The discriminating metabolites included acyl-carnitines, acyl-glycines and metabolites related to tryptophan metabolism. We found candidate biomarkers that were univariately significant different. This study demonstrates the potential of multivariate data analysis and metabolomics in the field of diabetic complications, and suggests several metabolic pathways relevant for further biological studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0291-6) contains supplementary material, which is available to authorized users.     

Association between DNA strand breakage and oxidative, inflammatory and endothelial biomarkers in type 2 diabetes

Evidence has been presented recently that type 2 diabetes patients have an increased level of DNA damage. This DNA damage could be associated with oxidative, inflammatory, and endothelial biomarkers and could represent a possible indication of injury in the endothelium and induction of inflammation in type 2 diabetes. To confirm this possible association, DNA strand breakage was evaluated by use of the comet assay and its association with oxidative, inflammatory, and endothelial biomarkers in type 2 diabetes patients. A case-control study (30 healthy controls and 32 subjects with type 2 diabetes) was performed to evaluate the association between DNA damage and NOx (nitrate/nitrite), interleukin-6 (IL-6), urinary albumin, fasting glucose, and glycated hemoglobin (HbA(1c)) levels. Type 2 diabetes patients presented higher DNA damage than control subjects, higher levels of IL-6 and urinary albumin, and lower NOx. Significant correlations between DNA damage and NOx (r=-0.303, p=0.016), IL-6 (r=0.845, p<0.001), urinary albumin (r=0.496, p<0.001), fasting glucose (r=0.449, p<0.001), and HbA(1c) (r=0.575, p<0.001) were reported. Our findings showed an increase of DNA damage in type 2 diabetes especially in those patients with poor glycemic control and associations among NOx, IL-6 and urinary albumin levels with DNA damage.     

Serum metabolomics profile of type 2 diabetes mellitus in a Brazilian rural population

Introduction

The development of common forms of diabetes comes from the interaction between environmental and genetic factors, and the consequences of poor glycemic control in these patients could result in several complications. Metabolomic studies for type 2 diabetes mellitus in serum/plasma have reported changes in numerous metabolites, which might be considered possible targets for future mechanistic research. However, the specific role of a particular metabolite as cause or consequence of diabetes derangements is difficult to establish.

Objectives

As type 2 diabetes is a disease that changes the metabolic profile in several levels, this work aimed to compare the metabolomic profiles of type 2 diabetes mellitus and non-diabetic participants. In addition, we exploited our family-based study design to bring a better understanding of the causal relationship of identified metabolites and diabetes.

Methods

In the current study, population based metabolomics was applied in 939 subjects from the Baependi Heart Study. Participants were separated into two groups: diabetic (77 individuals) and non-diabetic (862 individuals), and the metabolic profile was performed by GC/MS technique.

Results

We have identified differentially concentrated metabolites in serum of diabetic and non-diabetic individuals. We identified 72 metabolites up-regulated in type 2 diabetes mellitus compared to non-diabetics. It was possible to recapitulate the main pathways that the literature shows as changed in diabetes. Also, based on metabolomic profile, we separated pre-diabetic individuals (with glucose concentration between 100–125 mg/dL) from non-diabetics and diabetics. Finally, using heritability analysis, we were able to suggest metabolites in which altered levels may precede diabetic development.

Conclusion

Our data can be used to derive a better understanding of the causal relationship of the observed associations and help to prioritize diabetes-associated metabolites for further work.

     

Association of single-nucleotide polymorphisms in the suppressor of cytokine signaling 2 (SOCS2) gene with type 2 diabetes in the Japanese

Several previous linkage scans in type 2 diabetes (T2D) families indicated a putative susceptibility locus on chromosome 12q15-q22, while the underlying gene for T2D has not yet been identified. We performed a region-wide association analysis on 12q15-q22, using a dense set of >500 single-nucleotide polymorphisms (SNPs), in 1492 unrelated Japanese individuals enrolled in this study. We identified an association between T2D and a haplotype block spanning 13.6 kb of genomic DNA that includes the entire SOCS2 gene. Evolutionary-based haplotype analysis of haplotype-tagging SNPs followed by a "sliding window" haplotypic analysis indicated SNPs that mapped to the 5' region of the SOCS2gene to be associated with T2D with high statistical significance. The SOCS2 gene was expressed ubiquitously in human and murine tissues, including pancreatic beta-cell lines. Adenovirus-mediated expression of the SOCS2 gene in MIN6 cells or isolated rat islets significantly suppressed glucose-stimulated insulin secretion. Our data indicate that SOCS2 may play a role in susceptibility to T2D in the Japanese.     

Radiation metabolomics. 1. Identification of minimally invasive urine biomarkers for gamma-radiation exposure in mice

Gamma-radiation exposure has both short- and long-term adverse health effects. The threat of modern terrorism places human populations at risk for radiological exposures, yet current medical countermeasures to radiation exposure are limited. Here we describe metabolomics for gamma-radiation biodosimetry in a mouse model. Mice were gamma-irradiated at doses of 0, 3 and 8 Gy (2.57 Gy/min), and urine samples collected over the first 24 h after exposure were analyzed by ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-TOFMS). Multivariate data were analyzed by orthogonal partial least squares (OPLS). Both 3- and 8-Gy exposures yielded distinct urine metabolomic phenotypes. The top 22 ions for 3 and 8 Gy were analyzed further, including tandem mass spectrometric comparison with authentic standards, revealing that N-hexanoylglycine and beta-thymidine are urinary biomarkers of exposure to 3 and 8 Gy, 3-hydroxy-2-methylbenzoic acid 3-O-sulfate is elevated in urine of mice exposed to 3 but not 8 Gy, and taurine is elevated after 8 but not 3 Gy. Gene Expression Dynamics Inspector (GEDI) self-organizing maps showed clear dose-response relationships for subsets of the urine metabolome. This approach is useful for identifying mice exposed to gamma radiation and for developing metabolomic strategies for noninvasive radiation biodosimetry in humans.     

Genome-wide association study of copy number variations associated with pulmonary function measures in Korea Associated Resource (KARE) cohorts

Copy number variation (CNV) is an attractive emerging approach to study the association with various diseases. We performed a CNV-based genome-wide association study of pulmonary function measures (FEV(1), FVC, and FEV(1)/FVC) in KARE cohorts. Affymetrix Genome-wide Human SNP Array 5.0 was used to measure genome-wide variation and CNV segmentation was performed using Golden Helix SVS 7.0. Single and multivariate regressions were used for the association study using the R statistical package and the Dabatase for Annotation, Visualization and Integrated (DAVID v6.7b) tool for the functional annotation. We identified significantly associated 1260 CNVs with pulmonary function measures of FEV(1) and FVC. Functional gene classification and annotation analysis found 5 highly enriched clusters, the BPI/LBP/Plunc superfamily, myosin, serpin peptidase inhibitor, protein tyrosine phosphatase, and olfactory receptors. According to the functional annotation, gene-based CNVs are likely to be involved in the pathogenesis and inflammatory responsiveness of pulmonary diseases.     

抵抗素与肥胖和2型糖尿病

抵抗素(resistin)是近年来新发现的一个由脂肪组织特异表达分泌的细胞因子,其在前脂肪细胞分化过程中抑制脂肪生成.众多的研究显示抵抗素可诱导脂肪、肝脏及肌肉组织产生胰岛素抵抗,损伤机体的糖脂代谢功能.由于胰岛素抵抗在一些其他代谢性疾病及并发症如动脉粥样硬化及高血压发病机制中也发挥重要作用,提示抵抗素有可能介入了这些疾病的发病过程.本文简要介绍抵抗素的结构、分布及表达调控,并重点分析抵抗素在胰岛素抵抗中的作用.     

抵抗素与肥胖和2型糖尿病

抵抗素（resistin）是近年来新发现的一个由脂肪组织特异表达分泌的细胞因子,其在前脂肪细胞分化过程中抑制脂肪生成。众多的研究显示抵抗素可诱导脂肪、肝脏及肌肉组织产生胰岛素抵抗,损伤机体的糖脂代谢功能。由于胰岛素抵抗在一些其他代谢性疾病及并发症如动脉粥样硬化及高血压发病机制中也发挥重要作用,提示抵抗素有可能介入了这些疾病的发病过程。本文简要介绍抵抗素的结构、分布及表达调控,并重点分析抵抗素在胰岛素抵抗中的作用。     

Increased circulatory levels of lipopolysaccharide (LPS) and zonulin signify novel biomarkers of proinflammation in patients with type 2 diabetes

Emerging data indicate that gut-derived endotoxin (metabolic endotoxemia) may contribute to low-grade systemic inflammation in insulin-resistant states. Specific gut bacteria seem to serve as lipopolysaccharide (LPS) sources and several reports claim a role for increased intestinal permeability in the genesis of metabolic disorders. Therefore, we investigated the serum levels of LPS and zonulin (ZO-1, a marker of gut permeability) along with systemic levels of tumor necrosis factor-α (TNF-α) and Interleukin-6 (IL-6) in patients with type 2 diabetes mellitus (T2DM) compared to control subjects. Study subjects were recruited from the Chennai Urban Rural Epidemiology Study [CURES], Chennai, India. Study group (n = 45 each) comprised of a) subjects with normal glucose tolerance (NGT) and (b) patients with T2DM. LPS, ZO-1, TNF-α, and IL-6 levels were measured by ELISA. Serum levels of LPS [p < 0.05], LPS activity [p < 0.001], ZO-1 [p < 0.001], TNFα [p < 0.001], and IL-6 [p < 0.001] were significantly increased in patients with T2DM compared to control subjects. Pearson correlation analysis revealed that LPS activity was significantly and positively correlated with ZO-1, fasting plasma glucose, 2 h post glucose, HbA1c, serum triglycerides, TNF-α, IL-6, and negatively correlated with HDL cholesterol. Regression analysis showed that increased LPS levels were significantly associated with type 2 diabetes [odds ratio (OR) 13.43, 95 % CI 1.998–18.9; p = 0.003]. In Asian Indians who are considered highly insulin resistant, the circulatory LPS levels, LPS activity, and ZO-1 were significantly increased in patients with type 2 diabetes and showed positive correlation with inflammatory markers and poor glycemic/lipid control.     

Circulating sphingolipid biomarkers in models of type 1 diabetes

Alterations in lipid metabolism may contribute to diabetic complications. Sphingolipids are essential components of cell membranes and have essential roles in homeostasis and in the initiation and progression of disease. However, the role of sphingolipids in type 1 diabetes remains largely unexplored. Therefore, we sought to quantify sphingolipid metabolites by LC-MS/MS from two animal models of type 1 diabetes (streptozotocin-induced diabetic rats and Ins2(Akita) diabetic mice) to identify putative therapeutic targets and biomarkers. The results reveal that sphingosine-1-phosphate (So1P) is elevated in both diabetic models in comparison to respective control animals. In addition, diabetic animals demonstrated reductions in plasma levels of omega-9 24:1 (nervonic acid)-containing ceramide, sphingomyelin, and cerebrosides. Reduction of 24:1-esterfied sphingolipids was also observed in liver and heart. Nutritional stress via a high-fat diet also reduced 24:1 content in the plasma and liver of mice, exacerbating the decrease in some cases where diabetes was also present. Subcutaneous insulin corrected both circulating So1P and 24:1 levels in the murine diabetic model. Thus, changes in circulating sphingolipids, as evidenced by an increase in bioactive So1P and a reduction in cardio- and neuro-protective omega-9 esterified sphingolipids, may serve as biomarkers for type 1 diabetes and represent novel therapeutic targets.     

Association of SGK1 gene polymorphisms with type 2 diabetes

The serum and glucocorticoid inducible kinase SGK1 is genomically upregulated by glucocorticoids and in turn stimulates a variety of carriers and channels including the renal epithelial Na(+) channel ENaC and the intestinal Na(+) glucose transporter SGLT1. Twin studies disclosed an association of a specific SGK1 haplotype with moderately enhanced blood pressure in individuals who are carrying simultaneously a homozygous genotype for a variant in intron 6 [I6CC] and a homozygous or heterozygous genotype for the C allele of a polymorphism in exon 8 [E8CC/CT] of the SGK1 gene. A subsequent study confirmed the impact of this risk haplotype on blood pressure. SGK1 knockout mice are resistant to the insulin and high salt induced increase of blood pressure, glucocorticoid induced increase of electrogenic glucose transport, and glucocorticoid induced suppression of insulin release. The present study explored whether the I6CC/E8CC/CT haplotype impacts on the prevalence of type 2 diabetes. The prevalence of the I6CC genotype was 3.1% in a healthy German, 2.4 % in a healthy Romanian and 11.6 % in a healthy African population from Ghana (p=0.0006 versus prevalence in Caucasians). Comparison of genotype frequencies between type 2 diabetic patients and the respective control groups revealed significant differences for the intron 6 T>C variant. Carriers of at least one T allele were protected against type 2 diabetes (Romanians: p=0.023; OR 0.29; 95% CI 0.09-0.89; Germans: p=0.01; OR 0.37; 95% CI 0.17-0.81). The SGK1 risk haplotype (I6CC/E8CC/CT) was significantly (p=0.032; OR 4.31, 95% CI 1.19-15.58) more frequent in diabetic patients (7.2 %) than in healthy volunteers from Romania (1.8%). The observations support the view that SGK-1 may participate in the pathogenesis of metabolic syndrome.     

Genome-wide analysis of copy number variations reveals that aging processes influence body fat distribution in Korea Associated Resource (KARE) cohorts

Many anthropometric measures, including body mass index (BMI), waist-to-hip ratio (WHR), and subcutaneous fat thickness, are used as indicators of nutritional status, fertility and predictors of future health outcomes. While BMI is currently the best available estimate of body adiposity, WHR and skinfold thickness at various sites (biceps, triceps, suprailiac, and subscapular) are used as indices of body fat distribution. Copy number variation (CNV) is an attractive emerging approach to the study of associations with various diseases. In this study, we investigated the dosage effect of genes in the CNV genome widely associated with fat distribution phenotypes in large cohorts. We used the Affymetrix genome-wide human SNP Array 5.0 data of 8,842 healthy unrelated adults in KARE cohorts and identified CNVs associated with BMI and fat distribution-related traits including WHR and subcutaneous skinfold thickness at suprailiac (SUP) and subscapular (SUB) sites. CNV segmentation of each chromosome was performed using Golden Helix SVS 7.0, and single regression analysis was used to identify CNVs associated with each phenotype. We found one CNV for BMI, 287 for WHR, 2,157 for SUP, and 2,102 for SUB at the 5?% significance level after Holm–Bonferroni correction. Genes included in the CNV were used for the analysis of functional annotations using the Database for Annotation, Visualization and Integrated Discovery (DAVID v6.7b) tool. Functional gene classification analysis identified five significant gene clusters (metallothionein, ATP-binding proteins, ribosomal proteins, kinesin family members, and zinc finger proteins) for SUP, three (keratin-associated proteins, zinc finger proteins, keratins) for SUB, and one (protamines) for WHR. BMI was excluded from this analysis because the entire structure of no gene was identified in the CNV. Based on the analysis of genes enriched in the clusters, the fat distribution traits of KARE cohorts were related to the fat redistribution associated with the aging process. In addition to structural variation, dosage effect analysis of genes based on CNV is useful to gain an understanding of the comprehensive biological phenomena underlying particular phenotypes and/or diseases.     

The progress and potential of proteomic biomarkers for type 1 diabetes in children

Introduction: Although it is possible to identify the genetic risk for type 1 diabetes (T1D), it is not possible to predict who will develop the disease. New biomarkers are needed that would help understand the mechanisms of disease onset and when to administer targeted therapies and interventions.

Areas covered: An overview is presented of international study efforts towards understanding the cause of T1D, including the collection of several extensive temporal sample series that follow the development of T1D in at risk children. The results of the proteomics analysis of these materials are presented, which have included bodily fluids, such as serum or plasma and urine, as well as tissue samples from the pancreas.

Expert commentary: Promising recent reports have indicated detection of early proteomic changes in the serum of patients prior to diagnosis, potentially providing new measures for risk assessment. Similarly, there has been evidence that post-translational modification (PTM) may result in the recognition of islet cell proteins as autoantigens; modified proteins could thus be used as targets for immunomodulation to overcome the threat of the autoimmune response.