Roberto Incitti

Identification of SPOCK2 as a susceptibility gene for bronchopulmonary dysplasia

RATIONALE Bronchopulmonary dysplasia is the most common chronic respiratory disease in premature infants. Genetic factors might contribute to bronchopulmonary dysplasia susceptibility. OBJECTIVES To identify genetic variants involved in bronchopulmonary dysplasia through a genome-wide association study. METHODS We prospectively evaluated 418 premature neonates (gestational age <28 wk), of whom 22% developed bronchopulmonary dysplasia. Two discovery series were created, using a DNA pooling strategy in neonates from white and African ancestry. Polymorphisms associated with the disease were confirmed in an independent replication population. Genes were then explored by fine mapping and associations were replicated in an external Finnish population of 213 neonates. Validated genes expression patterns were studied in rat lung, after air or hyperoxia exposure. MEASUREMENTS AND MAIN RESULTS SPOCK2 gene was identified by both discovery series. The most significant polymorphism (rs1245560; P = 1.66 × 10(-7)) was confirmed by individual genotyping, and in the replication population (P = 0.002). Fine mapping confirmed the association of rs1245560 with bronchopulmonary dysplasia in both white and African populations with adjusted odds ratios of 2.96 (95% confidence interval [CI], 1.37-6.40) and 4.87 (95% CI, 1.88-12.63), respectively. In white neonates, rs1049269 was also associated with the disease (odds ratio, 3.21; 95% CI, 1.51-6.82). These associations were replicated in the Finnish population. In newborn rat lungs, SPOCK2 mRNA levels markedly increased during the alveolar stage of lung development. After rat exposure to hyperoxia, SPOCK2 expression increased relative to air-exposed controls. CONCLUSIONS We identified SPOCK2 as a new possible candidate susceptibility gene for bronchopulmonary dysplasia. Its lung expression pattern points toward a potential role in alveolarization.

Aberrant methylation of NPY, PENK, and WIF1 as a promising marker for blood-based diagnosis of colorectal cancer

BackgroundDNA methylation is a well-known epigenetic mechanism involved in epigenetic gene regulation. Several genes were reported hypermethylated in CRC, althought no gene marker was proven to be individually of sufficient sensitivity or specificity in routine clinical practice. Here, we identified novel epigenetic markers and assessed their combined use for diagnostic accuracy.MethodsWe used methylation arrays on samples from several effluents to characterize methylation profiles in CRC samples and controls, as established by colonoscopy and pathology findings, and selected two differentially methylated candidate epigenetic genes (NPY, PENK). To this gene panel we added WIF, on the basis of being reported in literature as silenced by promoter hypermethylation in several cancers, including CRC. We measured their methylation degrees by quantitative multiplex-methylation specific PCR (QM-MSP) on 15 paired carcinomas and adjacent non-cancerous colorectal tissues and we subsequently performed a clinical validation on two different series of 266 serums, subdivided in 32 CRC, 26 polyps, 47 other cancers and 161 with normal colonoscopy. We assessed the results by receiver operating characteristic curve (ROC), using cumulative methylation index (CMI) as variable threshold.ResultsWe obtained CRC detection on tissues with both sensitivity and specificity of 100%. On serum CRC samples, we obtained sensitivity/specificity values of, e.g., 87%/80%, 78%/90% and 59%/95%, and negative predictive value/positive predictive value figures of 97%/47%, 95%/61% and 92%/70%. On serum samples from other cancers we obtained sensitivity/specificity of, e.g, 89%/25%, 43%/80% and 28%/91%.ConclusionsWe showed the potential of NPY, PENK, and WIF1 as combined epigenetic markers for CRC diagnosis, both in tissue and serum and tested their use as serum biomarkers in other cancers. We optimized a QM-MSP for simultaneously quantifying their methylation levels. Our assay can be an effective blood test for patients where CRC risk is present but difficult to assess (e.g. mild symptoms with no CRC family history) and who would therefore not necessarily choose to go for further examination. This panel of markers, if validated, can also be a cost effective screening tool for the detection of asymptomatic cancer patients for colonoscopy.

Profiling target genes of FGF18 in the postnatal mouse lung: possible relevance for alveolar development

Better understanding alveolarization mechanisms could help improve prevention and treatment of diseases characterized by reduced alveolar number. Although signaling through fibroblast growth factor (FGF) receptors is essential for alveolarization, involved ligands are unidentified. FGF18, the expression of which peaks coincidentally with alveolar septation, is likely to be involved. Herein, a mouse model with inducible, lung-targeted FGF18 transgene was used to advance the onset of FGF18 expression peak, and genome-wide expression changes were determined by comparison with littermate controls. Quantitative RT-PCR was used to confirm expression changes of selected up- and downregulated genes and to determine their expression profiles in the course of lung postnatal development. This allowed identifying so-far unknown target genes of the factor, among which a number are known to be involved in alveolarization. The major target was adrenomedullin, a promoter of lung angiogenesis and alveolar development, whose transcript was increased 6.9-fold. Other genes involved in angiogenesis presented marked expression increases, including Wnt2 and cullin2. Although it appeared to favor cell migration notably through enhanced expression of Snai1/2, FGF18 also induced various changes consistent with prevention of epithelial-mesenchymal transition. Together with antifibrotic effects driven by induction of E prostanoid receptor 2 and repression of numerous myofibroblast markers, this could prevent alveolar septation-driving mechanisms from becoming excessive and deleterious. Last, FGF18 up- or downregulated genes of extracellular matrix components and epithelial cell markers previously shown to be up- or downregulated during alveolarization. These findings therefore argue for an involvement of FGF18 in the control of various developmental events during the alveolar stage.

Combining Position Weight Matrices and Document-Term Matrix for Efficient Extraction of Associations of Methylated Genes and Diseases from Free Text

Background In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually. Methodology We developed a novel text mining methodology based on a new concept of position weight matrices (PWMs) for text representation and feature generation. We applied PWMs in conjunction with the document-term matrix to extract with high accuracy associations between methylated genes and diseases from free text. The performance results are based on large manually-classified data. Additionally, we developed a web-tool, DEMGD, which automates extraction of these associations from free text. DEMGD presents the extracted associations in summary tables and full reports in addition to evidence tagging of text with respect to genes, diseases and methylation words. The methodology we developed in this study can be applied to similar association extraction problems from free text. Conclusion The new methodology developed in this study allows for efficient identification of associations between concepts. Our method applied to methylated genes in different diseases is implemented as a Web-tool, DEMGD, which is freely available at http://www.cbrc.kaust.edu.sa/demgd/. The data is available for online browsing and download.

DDMGD: the database of text-mined associations between genes methylated in diseases from different species.

Gathering information about associations between methylated genes and diseases is important for diseases diagnosis and treatment decisions. Recent advancements in epigenetics research allow for large-scale discoveries of associations of genes methylated in diseases in different species. Searching manually for such information is not easy, as it is scattered across a large number of electronic publications and repositories. Therefore, we developed DDMGD database (http://www.cbrc.kaust.edu.sa/ddmgd/) to provide a comprehensive repository of information related to genes methylated in diseases that can be found through text mining. DDMGDs scope is not limited to a particular group of genes, diseases or species. Using the text mining system DEMGD we developed earlier and additional post-processing, we extracted associations of genes methylated in different diseases from PubMed Central articles and PubMed abstracts. The accuracy of extracted associations is 82% as estimated on 2500 hand-curated entries. DDMGD provides a user-friendly interface facilitating retrieval of these associations ranked according to confidence scores. Submission of new associations to DDMGD is provided. A comparison analysis of DDMGD with several other databases focused on genes methylated in diseases shows that DDMGD is comprehensive and includes most of the recent information on genes methylated in diseases.