Proteins related to lipoprotein profile were identified using a pharmaco-proteomic approach as markers for growth response to growth hormone (GH) treatment in short prepubertal children

<p>Abstract</p> <p>Background</p> <p>The broad range in growth observed in response to growth hormone (GH) treatment is mainly caused by individual variations in both GH secretion and GH sensitivity. Individual GH responsiveness can be estimated using evidence-based models that predict the response to GH treatment; however, these models can be improved. High-throughput proteomics techniques can be used to identify proteins that may potentially be used as variables in such models in order to improve their predictive ability. Previously we have reported that proteomic analyses can identify biomarkers that discriminate between short prepubertal children with idiopathic short stature (ISS) who show good or poor growth in response to GH treatment. In this study we used a pharmaco-proteomic approach to identify novel factors that correlate with the growth response to GH treatment in prepubertal children who are short due to GH deficiency or ISS. The study included 128 short prepubertal children receiving GH treatment, of whom 39 were GH-deficient and 89 had ISS. Serum protein expression profiles at study start and after 1 year of GH treatment were analyzed using SELDI-TOF. Cross-validated regression and random permutation analyses were performed to identify significant correlations between protein expression patterns and the 2-year growth response to GH treatment.</p> <p>Results</p> <p>At start of treatment we identified a combination of seven protein peaks that correlated with the 2-year growth response in the GH-deficient group (R²= 0.73). After 1 year of treatment, a combination of four peaks in the GH-deficient group (R²= 0.64), eight peaks in the ISS group R²= 0.47) and eight peaks in the total study group correlated with the 2-year growth response R²= 0.38).</p> <p>The peaks identified corresponded to apolipoproteins A-I, A-II, C-I, C-III, transthyretin and serum amyloid A 4, which are all part of the high-density lipoprotein.</p> <p>Conclusion</p> <p>Using a proteomic approach we identified biomarkers related to the lipoprotein profile that could be used to predict growth response to GH treatment in prepubertal children who are short as a result of GH-deficiency or who have ISS.</p> <p>These results support our previous findings that apolipoproteins and transthyretin may have a role in GH sensitivity.</p

A proteomic approach identified growth hormone-dependent nutrition markers in children with idiopathic short stature

<p>Abstract</p> <p>Background</p> <p>The broad range in growth observed in short prepubertal children receiving the same growth hormone (GH) dose is due to individual variation in GH responsiveness. This study used a pharmaco-proteomic approach in order to identify novel biomarkers that discriminate between short non-GH-deficient (GHD) children who show a good or poor growth response to GH treatment.</p> <p>A group of 32 prepubertal children with idiopathic short stature (ISS) were included in the study. Children were classified on the basis of their first year growth velocity as either good (high responders, n = 13; range, 0.9–1.3 standard deviation score (SDS) or poor (low responders, n = 19; range, 0.3–0.5 SDS) responders to GH treatment (33 μg/kg daily).</p> <p>Serum protein expression profiles before, and after 1 year of GH treatment, were analyzed on a weak cationic exchange array (CM10) using surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS).</p> <p>Results</p> <p>Changes in the intensity of two protein peaks (13.788 kDa and 17.139 kD) during the study period allowed the correct classification of 82% of children as high and low responders, respectively. The 13.788 kD peak, transthyretin, decreased in the high-responder group and increased in the low-responder group during 1 year of GH treatment, whereas the 17.139 kDa peak, apolipoprotein A-II (Apo A-II) decreased in the high-responder group and remained unchanged in the low-responder group. These peaks were identified by the consistency of peak pattern in the spectra, serum depletion experiments using specific antibodies and mass spectrometry.</p> <p>Conclusion</p> <p>Our results suggest that transthyretin and apolipoprotein A-II may have a role in GH sensitivity and could be used as markers to predict which short prepubertal children with ISS will show a good or poor response to GH treatment.</p

The epidemiology of low- and high-energy distal radius fracture in middle-aged and elderly men and women in Southern Norway

Published version of an article in the journal: PLoS One. Also available from the publisher: http://dx.doi.org/10.1371/journal.pone.0043367BACKGROUND: Distal radius is one of the most frequent sites for fractures in the elderly population. Despite this, there is a paucity of epidemiological data for distal radius fracture, in particular, distinguishing between high- and low-energy fractures. Our aim was to study the epidemiology of high- and low-energy distal radius fracture in middle-aged and elderly men and women in Southern Norway, and search for associates with high- or low-energy distal radius fracture in this population. METHODOLOGY/PRINCIPAL FINDINGS: Patients with distal radius fractures aged >/=50 years were identified from all four hospitals in Southern Norway between 2004 and 2005. Age-adjusted and age-specific incidence rates for men and women were calculated, and potential associates with high- and low-energy distal radius fracture were explored both in univariate and multivariate analyses. A total of 799 individuals (118 men and 681 women) aged >/=50 years with low-energy and 84 (48 men and 36 women) with high-energy distal radius fracture were identified. The overall age-adjusted incidence rate per 10,000 person-years was 18.9 for men (low energy, 12.8 vs. high-energy, 6.1) and 75.1 for women (low energy, 71.1 vs. high energy, 4.0). In multivariate model, younger age, male gender, summer season, and living in a rural area were independently associated with an increased risk of high-energy fracture. CONCLUSION: An approximately fourfold higher age-adjusted incidence rate for distal radius fracture was found among women, when compared with men. However, the proportion of patients with high-energy distal radius fracture was approximately fivefold higher in men than in women. Our data suggest that younger age, male gender, summer seasons, and living in rural areas are independent risk factors for increased risk of high-energy distal radius fracture

Comparing Chemistry and Census-Based Estimates of Net Ecosystem Calcification on a Rim Reef in Bermuda

Coral reef net ecosystem calcification (NEC) has decreased for many Caribbean reefs over recent decades primarily due to changes in benthic community composition. Chemistry-based approaches to calculate NEC utilize the drawdown of seawater total alkalinity (TA) combined with residence time to calculate an instantaneous measurement of NEC. Census-based approaches combine annual growth rates with benthic cover and reef structural complexity to estimate NEC occurring over annual timescales. Here, NEC was calculated for Hog Reef in Bermuda using both chemistry and census-based NEC techniques to compare the mass-balance generated by the two methods and identify the dominant biocalcifiers at Hog Reef. Our findings indicate close agreement between the annual 2011 census-based NEC 2.35 ± 1.01 kg CaCO3•m−2•y−1 and chemistry-based NEC 2.23 ± 1.02 kg CaCO3•m−2•y−1 at Hog Reef. An additional record of Hog Reef TA data calculated from an autonomous CO2 mooring measuring pCO2 and modeled pHtotal every 3-h highlights the dynamic temporal variability in coral reef NEC. This ability for chemistry-based NEC techniques to capture higher frequency variability in coral reef NEC allows the mechanisms driving NEC variability to be explored and tested. Just four coral species, Diploria labyrinthiformis, Pseudodiploria strigosa, Millepora alcicornis, and Orbicella franksi, were identified by the census-based NEC as contributing to 94 ± 19% of the total calcium carbonate production at Hog Reef suggesting these species should be highlighted for conservation to preserve current calcium carbonate production rates at Hog Reef. As coral cover continues to decline globally, the agreement between these NEC estimates suggest that either method, but ideally both methods, may serve as a useful tool for coral reef managers and conservation scientists to monitor the maintenance of coral reef structure and ecosystem services

Computation of significance scores of unweighted Gene Set Enrichment Analyses

<p>Abstract</p> <p>Background</p> <p>Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for interpreting microarray gene expression data, but it can be applied to any sorted list of genes. Given the gene list and an arbitrary biological category, GSEA evaluates whether the genes of the considered category are randomly distributed or accumulated on top or bottom of the list. Usually, significance scores (p-values) of GSEA are computed by nonparametric permutation tests, a time consuming procedure that yields only estimates of the p-values.</p> <p>Results</p> <p>We present a novel dynamic programming algorithm for calculating exact significance values of unweighted Gene Set Enrichment Analyses. Our algorithm avoids typical problems of nonparametric permutation tests, as varying findings in different runs caused by the random sampling procedure. Another advantage of the presented dynamic programming algorithm is its runtime and memory efficiency. To test our algorithm, we applied it not only to simulated data sets, but additionally evaluated expression profiles of squamous cell lung cancer tissue and autologous unaffected tissue.</p

MicroRNAs targeting oncogenes are down-regulated in pancreatic malignant transformation from benign tumors

BACKGROUND MicroRNA (miRNA) expression profiles have been described in pancreatic ductal adenocarcinoma (PDAC), but these have not been compared with pre-malignant pancreatic tumors. We wished to compare the miRNA expression signatures in pancreatic benign cystic tumors (BCT) of low and high malignant potential with PDAC, in order to identify miRNAs deregulated during PDAC development. The mechanistic consequences of miRNA dysregulation were further evaluated. METHODS Tissue samples were obtained at a tertiary pancreatic unit from individuals with BCT and PDAC. MiRNA profiling was performed using a custom microarray and results were validated using RT-qPCR prior to evaluation of miRNA targets. RESULTS Widespread miRNA down-regulation was observed in PDAC compared to low malignant potential BCT. We show that amongst those miRNAs down-regulated, miR-16, miR-126 and let-7d regulate known PDAC oncogenes (targeting BCL2, CRK and KRAS respectively). Notably, miR-126 also directly targets the KRAS transcript at a "seedless" binding site within its 3'UTR. In clinical specimens, miR-126 was strongly down-regulated in PDAC tissues, with an associated elevation in KRAS and CRK proteins. Furthermore, miR-21, a known oncogenic miRNA in pancreatic and other cancers, was not elevated in PDAC compared to serous microcystic adenoma (SMCA), but in both groups it was up-regulated compared to normal pancreas, implicating early up-regulation during malignant change. CONCLUSIONS Expression profiling revealed 21 miRNAs down-regulated in PDAC compared to SMCA, the most benign lesion that rarely progresses to invasive carcinoma. It appears that miR-21 up-regulation is an early event in the transformation from normal pancreatic tissue. MiRNA expression has the potential to distinguish PDAC from normal pancreas and BCT. Mechanistically the down-regulation of miR-16, miR-126 and let-7d promotes PDAC transformation by post-transcriptional up-regulation of crucial PDAC oncogenes. We show that miR-126 is able to directly target KRAS; re-expression has the potential as a therapeutic strategy against PDAC and other KRAS-driven cancers

A novel algorithm for detecting differentially regulated paths based on gene set enrichment analysis

Motivation: Deregulated signaling cascades are known to play a crucial role in many pathogenic processes, among them are tumor initiation and progression. In the recent past, modern experimental techniques that allow for measuring the amount of mRNA transcripts of almost all known human genes in a tissue or even in a single cell have opened new avenues for studying the activity of the signaling cascades and for understanding the information flow in the networks

miRNAs in lung cancer - Studying complex fingerprints in patient's blood cells by microarray experiments

<p>Abstract</p> <p>Background</p> <p>Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls.</p> <p>Methods</p> <p>We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls.</p> <p>Results</p> <p>Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%].</p> <p>Conclusion</p> <p>Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.</p