Bayesian Methods for Network-Structured Genomics Data

Graphs and networks are common ways of depicting information. In biology, many different processes are represented by graphs, such as regulatory networks, metabolic pathways and protein-protein interaction networks. This information provides useful supplement to the standard numerical genomic data such as microarray gene expression data. Effectively utilizing such an information can lead to a better identification of biologically relevant genomic features in the context of our prior biological knowledge. In this paper, we present a Bayesian variable selection procedure for network-structured covariates for both Gaussian linear and probit models. The key of our approach is the introduction of a Markov random field prior for the indicator variables that describe which covariates should be included in the model and the use of the Wolff algorithm for Markov Chain Monte Carlo inference. We illustrate the proposed procedure with simulations and with an analysis of genomic data. Finally, we present some other areas of genomics research where novel Bayesian approaches may play important roles

Freedman's theorem for unitarily invariant states on the CCR algebra

The set of states on ${\rm CCR}(\ch)$, the CCR algebra of a separable Hilbert space $\ch$, is here looked at as a natural object to obtain a non-commutative version of Freedman's theorem for unitarily invariant stochastic processes. In this regard, we provide a complete description of the compact convex set of states of ${\rm CCR}(\ch)$ that are invariant under the action of all automorphisms induced in second quantization by unitaries of $\ch$. We prove that this set is a Bauer simplex, whose extreme states are either the canonical trace of the CCR algebra or Gaussian states with variance at least $1$.Comment: 22 page

Vertex Clustering in Random Graphs via Reversible Jump Markov Chain Monte Carlo

Networks are a natural and effective tool to study relational data, in which observations are collected on pairs of units. The units are represented by nodes and their relations by edges. In biology, for example, proteins and their interactions, and, in social science, people and inter-personal relations may be the nodes and the edges of the network. In this paper we address the question of clustering vertices in networks, as a way to uncover homogeneity patterns in data that enjoy a network representation. We use a mixture model for random graphs and propose a reversible jump Markov chain Monte Carlo algorithm to infer its parameters. Applications of the algorithm to one simulated data set and three real data sets, which describe friendships among members of a University karate club, social interactions of dolphins, and gap junctions in the C. Elegans, are given

Gas Chromatography–Mass Spectrometry (GC–MS) Metabolites Analysis in Endometriosis Patients: A Prospective Observational Translational Study

Background: Endometriosis affects women of reproductive age, and its pathogenesis is still unclear. Typically, it overlaps other similar medical and surgical conditions, determining a delay in early diagnosis. Metabolomics allows studying metabolic changes in different physiological or pathological states to discover new potential biomarkers. We used the gas chromatography–mass spectrometer (GC–MS) to explore metabolic alterations in endometriosis to better understand its pathophysiology and find new biomarkers. Methods: Twenty-two serum samples of patients with symptomatic endometriosis and ten without it were collected and subjected to GC–MS analysis. Multivariate and univariate statistical analyses were performed, followed by pathway analysis. Results: Partial least squares discriminant analysis was performed to determine the differences between the two groups (p = 0.003). Threonic acid, 3-hydroxybutyric acid, and proline increased significantly in endometriosis patients, while alanine and valine decreased. ROC curves were built to test the diagnostic power of metabolites. The pathway analysis identified the synthesis and degradation of ketone bodies and the biosynthesis of phenylalanine, tyrosine, and tryptophan as the most altered pathways. Conclusions: The metabolomic approach identifies metabolic alterations in women with endometriosis. These findings may improve our understanding of the pathophysiological mechanisms of disease and the discovery of new biomarkers

A treelet transform analysis to relate nutrient patterns to the risk of hormonal receptor-defined breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Objective: Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aimed at extracting nutrient patterns with respect to breast cancer (BC) aetiology. Design: Nutrient patterns were derived with treelet transform (TT) and related to BC risk. TT was applied to twenty-three log-transformed nutrient densities from dietary questionnaires. Hazard ratios (HR) and 95 % confidence intervals computed using Cox proportional hazards models quantified the association between quintiles of nutrient pattern scores and risk of overall BC, and by hormonal receptor and menopausal status. Principal component analysis was applied for comparison. Setting: The European Prospective Investigation into Cancer and Nutrition (EPIC). Subjects: Women (n 334 850) from the EPIC study. Results: The first TT component (TC1) highlighted a pattern rich in nutrients found in animal foods loading on cholesterol, protein, retinol, vitamins B12 and D, while the second TT component (TC2) reflected a diet rich in β-carotene, riboflavin, thiamin, vitamins C and B6, fibre, Fe, Ca, K, Mg, P and folate. While TC1 was not associated with BC risk, TC2 was inversely associated with BC risk overall (HRQ5 v. Q1=0·89, 95 % CI 0·83, 0·95, Ptrend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, Ptrend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, Ptrend<0·01). Conclusions: TT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC

Segmental transverse colectomy. Minimally invasive versus open approach: results from a multicenter collaborative study

none65noThe role of minimally invasive surgery in the treatment of transverse colon cancer is still controversial. The aim of this study is to investigate the advantages of a totally laparoscopic technique comparing open versus laparoscopic/robotic approach. Three hundred and eighty-eight patients with transverse colon cancer, treated with a segmental colon resection, were retrospectively analyzed. Demographic data, tumor stage, operative time, intraoperative complications, number of harvested lymph nodes and recovery outcomes were recorded. Recurrences and death were also evaluated during the follow-up. No differences were found between conventional and minimally invasive surgery, both for oncological long-term outcomes (recurrence rate p = 0.28; mortality p = 0.62) and postoperative complications (overall rate p = 0.43; anemia p = 0.78; nausea p = 0.68; infections p = 0.91; bleeding p = 0.62; anastomotic leak p = 0.55; ileus p = 0.75). Nevertheless, recovery outcomes showed statistically significant differences in favor of minimally invasive surgery in terms of time to first flatus (p = 0.001), tolerance to solid diet (p = 0.017), time to first mobilization (p = 0.001) and hospital stay (p = 0.004). Compared with laparoscopic approach, robotic surgery showed significantly better results for time to first flatus (p = 0.001), to first mobilization (p = 0.005) and tolerance to solid diet (p = 0.001). Finally, anastomosis evaluation confirmed the superiority of intracorporeal approach which showed significantly better results for time to first flatus (p = 0.001), to first mobilization (p = 0.003) and tolerance to solid diet (p = 0.001); moreover, we recorded a statistical difference in favor of intracorporeal approach for infection rate (p = 0.04), bleeding (p = 0.001) and anastomotic leak (p = 0.03). Minimally invasive approach is safe and effective as the conventional open surgery, with comparable oncological results but not negligible advantages in terms of recovery outcomes. Moreover, we demonstrated that robotic approach may be considered a valid option and an intracorporeal anastomosis should always be preferred.noneMilone, Marco; Degiuli, Maurizio; Velotti, Nunzio; Manigrasso, Michele; Vertaldi, Sara; D'Ugo, Domenico; De Palma, Giovanni Domenico; Dario Bruzzese, Giuseppe Servillo, Giuseppe De Simone, Katia Di Lauro, Silvia Sofia, Marco Ettore Allaix, Mario Morino, Rossella Reddavid, Carlo Alberto Ammirati, Stefano Scabini, Gabriele Anania, Cristina Bombardini, Andrea Barberis, Roberta Longhin, Andrea Belli, Francesco Bianco, Giampaolo Formisano, Giuseppe Giuliani, Paolo Pietro Bianchi, Davide Cavaliere, Leonardo Solaini, Claudio Coco, Gianluca Rizzo, Andrea Coratti, Raffaele De Luca, Michele Simone, Alberto Di Leo, Giovanni De Manzoni, Paola De Nardi, Ugo Elmore, Riccardo Rosati, Andrea Vignali, Paolo Delrio, Ugo Pace, Daniela Rega, Antonio Di Cataldo, Giovanni Li Destri, Annibale Donini, Luigina Graziosi, Andrea Fontana, Michela Mineccia, Sergio Gentilli, Manuela Monni, Mario Guerrieri, Monica Ortenzi, Francesca Pecchini, Micaela Piccoli, Italy. Corrado Pedrazzani, Giulia Turri, Sara Pollesel, Franco Roviello, Marco Rigamonti, Michele Zuolo, Mauro Santarelli, Federica Saraceno, Pierpaolo Sileri Giuseppe Sigismondo Sica, Luigi Siragusa Salvatore Pucciarelli, Matteo ZuinMilone, Marco; Degiuli, Maurizio; Velotti, Nunzio; Manigrasso, Michele; Vertaldi, Sara; D'Ugo, Domenico; De Palma, Giovanni Domenico; Dario Bruzzese, Giuseppe Servillo, Giuseppe De Simone, Katia Di Lauro, Silvia Sofia, Marco Ettore Allaix, Mario Morino, Rossella Reddavid, Carlo Alberto Ammirati, Stefano Scabini, Gabriele Anania, Cristina Bombardini, Andrea Barberis, Roberta Longhin, Andrea Belli, Francesco Bianco, Giampaolo Formisano, Giuseppe Giuliani, Paolo Pietro Bianchi, Davide Cavaliere, Leonardo Solaini, Claudio Coco, Gianluca Rizzo, Andrea Coratti, Raffaele De Luca, Michele Simone, Alberto Di Leo, Giovanni De Manzoni, Paola De Nardi, Ugo Elmore, Riccardo Rosati, Andrea Vignali, Paolo Delrio, Ugo Pace, Daniela Rega, Antonio Di Cataldo, Giovanni Li Destri, Annibale Donini, Luigina Graziosi, Andrea Fontana, Michela Mineccia, Sergio Gentilli, Manuela Monni, Mario Guerrieri, Monica Ortenzi, Francesca Pecchini, Micaela Piccoli, Italy. Corrado Pedrazzani, Giulia Turri, Sara Pollesel, Franco Roviello, Marco Rigamonti, Michele Zuolo, Mauro Santarelli, Federica Saraceno, Pierpaolo Sileri Giuseppe Sigismondo Sica, Luigi Siragusa Salvatore Pucciarelli, Matteo Zui

Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis. OBJECTIVE To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery. EXPOSURES Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections. MAIN OUTCOMES AND MEASURES The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable. RESULTS A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95%CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95%CI, 1.15-1.53; P &lt; .001), and stenotic lesions (OR, 1.15; 95%CI, 1.01-1.31; P = .03). CONCLUSIONS AND RELEVANCE This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients