Towards an Age-Phenome Knowledge-base

<p>Abstract</p> <p>Background</p> <p>Currently, data about age-phenotype associations are not systematically organized and cannot be studied methodically. Searching for scientific articles describing phenotypic changes reported as occurring at a given age is not possible for most ages.</p> <p>Results</p> <p>Here we present the Age-Phenome Knowledge-base (APK), in which knowledge about age-related phenotypic patterns and events can be modeled and stored for retrieval. The APK contains evidence connecting specific ages or age groups with phenotypes, such as disease and clinical traits. Using a simple text mining tool developed for this purpose, we extracted instances of age-phenotype associations from journal abstracts related to non-insulin-dependent Diabetes Mellitus. In addition, links between age and phenotype were extracted from clinical data obtained from the NHANES III survey. The knowledge stored in the APK is made available for the relevant research community in the form of 'Age-Cards', each card holds the collection of all the information stored in the APK about a particular age. These Age-Cards are presented in a wiki, allowing community review, amendment and contribution of additional information. In addition to the wiki interaction, complex searches can also be conducted which require the user to have some knowledge of database query construction.</p> <p>Conclusions</p> <p>The combination of a knowledge model based repository with community participation in the evolution and refinement of the knowledge-base makes the APK a useful and valuable environment for collecting and curating existing knowledge of the connections between age and phenotypes.</p

Direct visualization of lipid aggregates in native human bile by light- and cryo-transmission electron-microscopy

AbstractThe evolution of microstructures present in human gallbladder and hepatic bile was observed simultaneously by video-enhanced light microscopy (VELM) and transmission electron microscopy of vitrified specimens (cryo-TEM), as a function of time after withdrawal from patients. Fresh centrifuged gallbladder bile samples contained small (6 nm) spherical micelles in coexistence with vesicles (40 nm). Out of the seven bile samples investigated four contained, in addition, two types of elongated aggregates that have not been previously described. Uncentrifuged gallbladder bile also contained a mixture of ribbon- and plate-like crystals seen by VELM, but not by cryo-TEM. In aged (3–6-week-old) gallbladder bile samples VELM also revealed spiral and helical crystal structures. No such crystals were present in hepatic bile samples, although microcrystals, not observable by VELM were seen by cryo-TEM in addition to micelles and vesicles. The similarity of these observations to those observed in bile models lends strong support for the validity of the model systems. Furthermore, the presence of microcrystals in hepatic bile samples, apparently devoid of crystals by light microscopy, indicates that under certain conditions the common criterion of ‘nueleation time’ (NT), based on light microscopy, does not represent the real time of nucleation. In the human bile samples investigated in this study the dissociation between NT and the time of observation of microcrystals was seen in hepatic but not in gallbladder bile samples. Hence, crystal growth may be rate limiting only in dilute biles

BORIS/CTCFL promotes a switch from a proliferative towards an invasive phenotype in melanoma cells

Melanoma is among the most aggressive cancers due to its tendency to metastasize early. Phenotype switching between a proliferative and an invasive state has been suggested as a critical process for metastasis, though the mechanisms that regulate state transitions are complex and remain poorly understood. Brother of Regulator of Imprinted Sites (BORIS), also known as CCCTC binding factor-Like (CTCFL), is a transcriptional modulator that becomes aberrantly expressed in melanoma. Yet, the role of BORIS in melanoma remains elusive. Here, we show that BORIS is involved in melanoma phenotype switching. Genetic modification of BORIS expression in melanoma cells combined with whole-transcriptome analysis indicated that BORIS expression contributes to an invasion-associated transcriptome. In line with these findings, inducible BORIS overexpression in melanoma cells reduced proliferation and increased migration and invasion, demonstrating that the transcriptional switch is accompanied by a phenotypic switch. Mechanistically, we reveal that BORIS binds near the promoter of transforming growth factor-beta 1 (TFGB1), a well-recognized factor involved in the transition towards an invasive state, which coincided with increased expression of TGFB1. Overall, our study indicates a pro-invasive role for BORIS in melanoma via transcriptional reprogramming

Two Patterns of Adipokine and Other Biomarker Dynamics in a Long-Term Weight Loss Intervention

Objective: Long-term dietary intervention frequently induces a rapid weight decline followed by weight stabilization/regain. Here, we sought to identify adipokine biomarkers that may reflect continued beneficial effects of dieting despite partial weight regain. Research design and methods: We analyzed the dynamics of fasting serum levels of 12 traditional metabolic biomarkers and novel adipokines among 322 participants in the 2-year Dietary Intervention Randomized Controlled Trial (DIRECT) of low-fat, Mediterranean, or low-carbohydrate diets for weight loss. Results: We identified two distinct patterns: Pattern A includes biomarkers (insulin, triglycerides, leptin, chemerin, monocyte chemoattractant protein 1, and retinol-binding protein 4) whose dynamics tightly correspond to changes in body weight, with the trend during the weight loss phase (months 0–6) going in the opposite direction to that in the weight maintenance/regain phase (months 7–24) (P < 0.05 between phases, all biomarkers). Pattern B includes biomarkers (high molecular weight adiponectin, HDL cholesterol [HDL-C], high-sensitivity C-reactive protein [hsCRP], fetuin-A, progranulin, and vaspin) that displayed a continued, cumulative improvement (P < 0.05 compared with baseline, all biomarkers) throughout the intervention. These patterns were consistent across sex, diabetic groups, and diet groups, although the magnitude of change varied. Hierarchical analysis suggested similar clusters, revealing that the dynamic of leptin (pattern A) was most closely linked to weight change and that the dynamic of hsCRP best typified pattern B. Conclusions: hsCRP, HDL-C, adiponectin, fetuin-A, progranulin, and vaspin levels display a continued long-term improvement despite partial weight regain. This may likely reflect either a delayed effect of the initial weight loss or a continuous beneficial response to switching to healthier dietary patterns

Large bowel obstruction due to sesame seed bezoar: a case report

peer-reviewedWe report a case of a 79 year old man with a known benign anastomotic stricture presenting with large bowel obstruction. At laparotomy the obstruction was found to be caused by a large sesame seed bezoar. Seed bezoars are well known to cause impaction in the rectum but have never been previously reported to cause large bowel obstruction. We recommend that patients with known large bowel strictures should be advised not to eat seeds as this could ultimately lead to obstruction, ischaemia or perforationPUBLISHEDpeer-reviewe

Unsupervised Analysis of Classical Biomedical Markers: Robustness and Medical Relevance of Patient Clustering Using Bioinformatics Tools

Motivation: It has been proposed that clustering clinical markers, such as blood test results, can be used to stratify patients. However, the robustness of clusters formed with this approach to data pre-processing and clustering algorithm choices has not been evaluated, nor has clustering reproducibility. Here, we made use of the NHANES survey to compare clusters generated with various combinations of pre-processing and clustering algorithms, and tested their reproducibility in two separate samples. Method: Values of 44 biomarkers and 19 health/life style traits were extracted from the National Health and Nutrition Examination Survey (NHANES). The 1999–2002 survey was used for training, while data from the 2003–2006 survey was tested as a validation set. Twelve combinations of pre-processing and clustering algorithms were applied to the training set. The quality of the resulting clusters was evaluated both by considering their properties and by comparative enrichment analysis. Cluster assignments were projected to the validation set (using an artificial neural network) and enrichment in health/life style traits in the resulting clusters was compared to the clusters generated from the original training set. Results: The clusters obtained with different pre-processing and clustering combinations differed both in terms of cluster quality measures and in terms of reproducibility of enrichment with health/life style properties. Z-score normalization, for example, dramatically improved cluster quality and enrichments, as compared to unprocessed data, regardless of the clustering algorithm used. Clustering diabetes patients revealed a group of patients enriched with retinopathies. This coul

CHILD: a new tool for detecting low-abundance insertions and deletions in standard sequence traces

Several methods have been proposed for detecting insertion/deletions (indels) from chromatograms generated by Sanger sequencing. However, most such methods are unsuitable when the mutated and normal variants occur at unequal ratios, such as is expected to be the case in cancer, with organellar DNA or with alternatively spliced RNAs. In addition, the current methods do not provide robust estimates of the statistical confidence of their results, and the sensitivity of this approach has not been rigorously evaluated. Here, we present CHILD, a tool specifically designed for indel detection in mixtures where one variant is rare. CHILD makes use of standard sequence alignment statistics to evaluate the significance of the results. The sensitivity of CHILD was tested by sequencing controlled mixtures of deleted and undeleted plasmids at various ratios. Our results indicate that CHILD can identify deleted molecules present as just 5% of the mixture. Notably, the results were plasmid/primer-specific; for some primers and/or plasmids, the deleted molecule was only detected when it comprised 10% or more of the mixture. The false positive rate was estimated to be lower than 0.4%. CHILD was implemented as a user-oriented web site, providing a sensitive and experimentally validated method for the detection of rare indel-carrying molecules in common Sanger sequence reads

Serum Apolipoproteins C-I and C-III Are Reduced in Stomach Cancer Patients: Results from MALDI-Based Peptidome and Immuno-Based Clinical Assays

Finding new peptide biomarkers for stomach cancer in human sera that can be implemented into a clinically practicable prediction method for monitoring of stomach cancer. We studied the serum peptidome from two different biorepositories. We first employed a C8-reverse phase liquid chromatography approach for sample purification, followed by mass-spectrometry analysis. These were applied onto serum samples from cancer-free controls and stomach cancer patients at various clinical stages. We then created a bioinformatics analysis pipeline and identified peptide signature discriminating stomach adenocarcinoma patients from cancer-free controls. Matrix Assisted Laser Desorption/Ionization–Time of Flight (MALDI-TOF) results from 103 samples revealed 9 signature peptides; with prediction accuracy of 89% in the training set and 88% in the validation set. Three of the discriminating peptides discovered were fragments of Apolipoproteins C-I and C-III (apoC-I and C-III); we further quantified their serum levels, as well as CA19-9 and CRP, employing quantitative commercial-clinical assays in 142 samples. ApoC-I and apoC-III quantitative results correlated with the MS results. We then employed apoB-100-normalized apoC-I and apoC-III, CA19-9 and CRP levels to generate rules set for stomach cancer prediction. For training, we used sera from one repository, and for validation, we used sera from the second repository. Prediction accuracies of 88.4% and 74.4% were obtained in the training and validation sets, respectively. Serum levels of apoC-I and apoC-III combined with other clinical parameters can serve as a basis for the formulation of a diagnostic score for stomach cancer patients

Identification of six new susceptibility loci for invasive epithelial ovarian cancer.

Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 ] HEALTH ]F2 ]2009 ]223175). The CIMBA data management and data analysis were supported by Cancer Research.UK grants 12292/A11174 and C1287/A10118. The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME ]ON Post ]GWAS Initiative (U19 ]CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The cBio portal is developed and maintained by the Computational Biology Center at Memorial Sloan ] Kettering Cancer Center. SH is supported by an NHMRC Program Grant to GCT. Details of the funding of individual investigators and studies are provided in the Supplementary Note. This study made use of data generated by the Wellcome Trust Case Control consortium, funding for which was provided by the Wellcome Trust under award 076113. The results published here are, in part, based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancerhttp://dx.doi.org/10.1038/ng.3185This is the Author Accepted Manuscript of 'Identification of six new susceptibility loci for invasive epithelial ovarian cancer' which was published in Nature Genetics 47, 164–171 (2015) © Nature Publishing Group - content may only be used for academic research