Molecular signatures for obesity and associated disorders identified through partial least square regression models

Sinha, Neeraj; Sharma, Sachin; Tripathi, Parul; Negi, Simarjeet; Tikoo, Kamiya; Kumar, Dhiraj; Rao, Kanury V. S.; Chatterjee, Samrat

doi:10.1186/s12918-014-0104-4

Cited by 5 publications

(7 citation statements)

References 26 publications

(29 reference statements)

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“…The rationale behind the selection of the panel of the tissues was derived from the relevant literature and is described in the supplementary information 5 6 13 14 15 . The details of experimental strategy were recently reported by our group and is briefly described in supplementary information 9 10 . To study crosstalk between different tissues, we developed a novel analytical approach.…”

Section: Resultsmentioning

confidence: 99%

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A Comprehensive Inter-Tissue Crosstalk Analysis Underlying Progression and Control of Obesity and Diabetes

Samdani¹,

Singhal²,

Sinha

et al. 2015

Sci Rep

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Obesity is a metabolic state associated with excess of positive energy balance. While adipose tissues are considered the major contributor for complications associated with obesity, they influence a variety of tissues and inflict significant metabolic and inflammatory alterations. Unfortunately, the communication network between different cell-types responsible for such systemic alterations has been largely unexplored. Here we study the inter-tissue crosstalk during progression and cure of obesity using multi-tissue gene expression data generated through microarray analysis. We used gene expression data sets from 10 different tissues from mice fed on high-fat-high-sugar diet (HFHSD) at various stages of disease development and applied a novel analysis algorithm to deduce the tissue crosstalk. We unravel a comprehensive network of inter-tissue crosstalk that emerges during progression of obesity leading to inflammation and insulin resistance. Many of the crosstalk involved interactions between well-known modulators of obesity and associated pathology like inflammation. We then used similar datasets from mice that in addition to HFHSD were also administered with a herbal concoction known to circumvent the effects of HFHSD in the diet induced model of obesity in mice. We propose, the analysis presented here could be applied to understand systemic details of several chronic diseases.

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Section: Resultsmentioning

confidence: 99%

“…Animals and diet, treatment with Kal-1, tissue isolation, RNA isolation and microarray experiments has been described our earlier report and are briefly explained in the suplementary informations 9 10 .…”

Section: Methodsmentioning

confidence: 99%

A Comprehensive Inter-Tissue Crosstalk Analysis Underlying Progression and Control of Obesity and Diabetes

Samdani¹,

Singhal²,

Sinha

et al. 2015

Sci Rep

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“…Although further work should improve the fluorescence ratio of positive assays over negative control targets by offering a more robust optical detection platform and enabling temperature control of the microarray surface until fluorescence acquisition, it is worth comparing these ratios to traditionally accepted ratios to differentiate between overexpression and underexpression of genes for in expression analysis microarray. A ratio of 1.5 or more typically 2 is considered sufficient to differentiate with certainty the level of expression of a gene in a reliable fashion 41, 42 . Ratios currently observed with our structured oligonucleotide technique are within ranges of accepted microarray differentiation ratios.…”

Section: Resultsmentioning

confidence: 99%

Structured oligonucleotides for target indexing to allow single-vessel PCR amplification and solid support microarray hybridization

Girard

Boissinot

Peytavi

et al. 2015

Analyst

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The combination of molecular diagnostic technologies is increasingly used to overcome limitations on sensitivity, specificity or multiplexing capabilities, and provide efficient lab-on-chip devices. Two such techniques, PCR amplification and microarray hybridization are used serially to take advantage of the high sensitivity and specificity of the former combined with high multiplexing capacities of the latter. These methods are usually performed in different buffers and reaction chambers. However, these elaborate methods have a high complexity cost related to reagent requirements, liquid storage and the number of reaction chambers to integrate into automated devices. Furthermore, microarray hybridizations have a sequence dependent efficiency not always predictable. In this work, we have developed the concept of a structured oligonucleotide probe which is activated by cleavage from polymerase exonuclease activity. This technology is called SCISSOHR for Structured Cleavage Induced Single-Stranded Oligonucleotide Hybridization Reaction. The SCISSOHR probes enable indexing the target sequence to a tag sequence. The SCISSOHR technology also allows the combination of nucleic acid amplification and microarray hybridization in a single vessel in presence of the PCR buffer only. The SCISSOHR technology uses an amplification probe that is irreversibly modified in presence of the target, releasing a single-stranded DNA tag for microarray hybridization. Each tag is composed of a 3-nucleotidesequence-dependent segment and a unique “target sequence-independent” 14-nucleotide segment allowing for optimal hybridization with minimal cross-hybridization. We evaluated the performance of five (5) PCR buffers to support microarray hybridization, compared to a conventional hybridization buffer. Finally, as a proof of concept, we developed a multiplexed assay for the amplification, detection, and identification of three (3) DNA targets. This new technology will facilitate the design of lab-on-chip microfluidic devices, while also reducing consumable costs. At term, it will allow the cost-effective automation of highly multiplexed assays for detection and identification of genetic targets.

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“…Cytokines that promote in ammation include interleukins (IL) IL-7 and IL-8, granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon-inducible protein-10 (IP-10), monocyte chemoattractant protein (MCP)-1, and tumor necrosis factor (TNF)-α among others [7][8][9]27]. Cytokines that reduce in ammation include IL-10 and IL-13 [32,33] while IL-6 has been implicated as pro-and anti-in ammatory mediator [34].…”

Section: Introductionmentioning

confidence: 99%

Predictors of HbA1c among adipocytokine biomarkers in African American men with varied glucose tolerance

Barengolts¹,

Akbar

Layden

et al. 2020

Preprint

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Background: Adipocytokines are important in type 2 diabetes (T2D). This study explored adipocytokine associations with acute and chronic hyperglycemia in African American Men (AAM). Methods: Fourteen adipocytokines were measured (multiplex assay) in blood samples from men with normal glucose tolerance (NGT) or T2D (drug-naïve MF(-) or using metformin MF(+)). Acute and chronic hyperglycemia were evaluated at 120-minute of OGTT and by HbA1c, respectively. Results: AAM with T2D (N=21) compared to NGT (N=20) were significantly older (59 vs. 54 years) and had higher body mass index (BMI 35 vs. 27 kg/m2) (p<0.01 for both). Fasting and 120-minute OGTT glucose and insulin were higher in T2D than NGT, however, differences did not reach statistical significance after adjusting for age and BMI. In the fasted state, TNF-a, IL-6, PAI-1 (p<0.01 for all) and IL-13, adiponectin, adipsin, lipocalin (p<0.05 for all) were lower in T2D compared to NGT. At 120-minute post-glucose load (acute hyperglycemia) TNF-a, IL-6, IL-13, IL-8, PAI-1, adiponectin, adipsin (p<0.01 for all) and lipocalin, resistin (p<0.05 for both) were lower in T2D than in NGT group. There were no statistical differences for the other adipocytokines including GM-CSF, IL-7, IL-10, IP-10, and MCP-1. Regression analysis (adjusted for age and BMI) showed that fasting IL-8, TNF-a, adiponectin, lipocalin, resistin, adipsin, and PAI-1 were all associated with HbA1c (p<0.05 for all). Further modeling revealed that after adjusting for age, BMI, glucose tolerance status and metformin use, only adipsin remained significantly associated with HbA1c (p=0.004). The model including adipsin, TNF-a, age, BMI, and group designation (i.e. NGT, MF(-), MF(+)) explained 86% of HbA1c variability. Conclusions: The study suggested that adipsin could be independently associated with HbA1c in AAM with varied glucose tolerance. Additional studies should corroborate these data and provide mechanistic insights for enabling adipsin-related discoveries of novel T2D treatment.

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Molecular signatures for obesity and associated disorders identified through partial least square regression models

Cited by 5 publications

References 26 publications

A Comprehensive Inter-Tissue Crosstalk Analysis Underlying Progression and Control of Obesity and Diabetes

A Comprehensive Inter-Tissue Crosstalk Analysis Underlying Progression and Control of Obesity and Diabetes

Structured oligonucleotides for target indexing to allow single-vessel PCR amplification and solid support microarray hybridization

Predictors of HbA1c among adipocytokine biomarkers in African American men with varied glucose tolerance

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