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Aim We aimed to compare cardiovascular outcomes of patients with type 2 diabetes (T2D) who initiated GLP-1 receptor agonists (GLP-1RA) or basal insulin (BI) under routine care. Methods We accessed the administrative claims database of the Veneto Region (Italy) to identify new users of GLP-1RA or BI in 2014–2018. Propensity score matching (PSM) was implemented to obtain two cohorts of patients with superimposable characteristics. The primary endpoint was the 3-point major adverse cardiovascular events (3P-MACE). Secondary endpoints included 3P-MACE components, hospitalization for heart failure, revascularizations, and adverse events. Results From a background population of 5,242,201 citizens, 330,193 were identified as having diabetes. PSM produced two very well matched cohorts of 4063 patients each, who initiated GLP-1RA or BI after an average of 2.5 other diabetes drug classes. Patients were 63-year-old and only 15% had a baseline history of cardiovascular disease. During a median follow-up of 24 months in the intention-to-treat analysis, 3P-MACE occurred less frequently in the GLP-1RA cohort (HR versus BI 0.59; 95% CI 0.50–0.71; p Conclusions Patients with T2D who initiated a GLP-1RA experienced far better cardiovascular outcomes than did matched patients who initiated a BI in the same healthcare system. These finding supports prioritization of GLP-1RA as the first injectable regimen for the management of T2D.

Aims Glucagon like peptide-1 (GLP-1) receptor agonists (GLP-1RA) are effective to control type 2 diabetes (T2Ds) and can protect from adverse cardiovascular outcomes. GLP-1RA are based on the human GLP-1 or the exendin-4 sequence. We compared cardiovascular outcomes of patients with T2D who received human-based or exendin-based GLP-1RA in routine clinical practice. Methods and results We performed a retrospective study on the administrative database of T2D patients from the Veneto Region (North-East Italy). We identified patients who initiated a human-based or exendin-based GLP-1RA from 2011 to 2018. The primary outcome was occurrence of major adverse cardiovascular events (MACE). Secondary outcomes were individual MACE components, revascularization, hospitalization for heart failure, or for cardiovascular causes. From 330 193 patients with diabetes, 6620 were new users of GLP-1RA. After propensity score matching, we analysed 1098 patients in each group, who were on average 61 years old, 59.5% males, 13% with established cardiovascular disease, had an estimated diabetes duration of 8.4 years, and a baseline HbA1c of 7.9%. During a median follow-up of 18 months, patients treated with human-based GLP-1RA as compared to those treated with exendin-based GLP-1RA, showed lower rates of MACE [hazard ratio 0.61; 95% confidence interval (CI) 0.39–0.95], myocardial infarction (0.51; 95% CI 0.28–0.94), and hospitalization for cardiovascular causes (0.66; 95% CI 0.47–0.92). Conclusion We observed better cardiovascular outcomes among patients treated with human-based vs. exendin-based GLP-1RA under routine care. In the absence of comparative trials and in view of the limitations of retrospective studies, this finding provides a moderate level of evidence to guide clinical decision.

Because other coronaviruses enter the cells by binding to dipeptidyl-peptidase-4 (DPP-4), it has been speculated that DPP-4 inhibitors (DPP-4is) may exert an activity against severe acute respiratory syndrome coronavirus 2. In the absence of clinical trial results, we analysed epidemiological data to support or discard such a hypothesis. We retrieved information on exposure to DPP-4is among patients with type 2 diabetes (T2D) hospitalized for COVID-19 at an outbreak hospital in Italy. As a reference, we retrieved information on exposure to DPP-4is among matched patients with T2D in the same region. Of 403 hospitalized COVID-19 patients, 85 had T2D. The rate of exposure to DPP-4is was similar between T2D patients with COVID-19 (10.6%) and 14 857 matched patients in the region (8.8%), or 793 matched patients in the local outpatient clinic (15.4%), 8284 matched patients hospitalized for other reasons (8.5%), and when comparing 71 patients hospitalized for COVID-19 pneumonia (11.3%) with 351 matched patients with pneumonia of another aetiology (10.3%). T2D patients with COVID-19 who were on DPP-4is had a similar disease outcome as those who were not. In summary, we found no evidence that DPP-4is might affect hospitalization for COVID-19.

Background Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease progressively affecting upper and lower motor neurons in the brain and spinal cord. Mean life expectancy is three to five years, with paralysis of muscles, respiratory failure and loss of vital functions being the common causes of death. Clinical manifestations of ALS are heterogeneous due to the mix of anatomic regions involvement and the variability in disease course; consequently, diagnosis and prognosis at the level of individual patient is really challenging. Prediction of ALS progression and stratification of patients into meaningful subgroups have been long-standing interests to clinical practice, research and drug development. Methods We developed a Dynamic Bayesian Network (DBN) model on more than 4500 ALS patients included in the Pooled Resource Open-Access ALS Clinical Trials Database (PRO-ACT), in order to detect probabilistic relationships among clinical variables and identify risk factors related to survival and loss of vital functions. Furthermore, the DBN was used to simulate the temporal evolution of an ALS cohort predicting survival and the time to impairment of vital functions (communication, swallowing, gait and respiration). A first attempt to stratify patients by risk factors and simulate the progression of ALS subgroups was also implemented. Results The DBN model provided the prediction of ALS most probable trajectories over time in terms of important clinical outcomes, including survival and loss of autonomy in functional domains. Furthermore, it allowed the identification of biomarkers related to patients’ clinical status as well as vital functions, and unrevealed their probabilistic relationships. For instance, DBN found that bicarbonate and calcium levels influence survival time; moreover, the model evidenced dependencies over time among phosphorus level, movement impairment and creatinine. Finally, our model provided a tool to stratify patients into subgroups of different prognosis studying the effect of specific variables, or combinations of them, on either survival time or time to loss of autonomy in specific functional domains. Conclusions The analysis of the risk factors and the simulation allowed by our DBN model might enable better support for ALS prognosis as well as a deeper insight into disease manifestations, in a context of a personalized medicine approach. Electronic supplementary material The online version of this article (10.1186/s12859-019-2692-x) contains supplementary material, which is available to authorized users.

People with diabetes require lifelong access to healthcare services to delay the onset of complications. Their disease management processes generate great volumes of data across several domains, from clinical to administrative. Difficulties in accessing and processing these data hinder their secondary use in an institutional setting, even for highly desirable applications, such as the prediction of cardiovascular disease, the main driver of excess mortality in diabetes. Hence, in the present work, we propose a deep learning model for the prediction of major adverse cardiovascular events (MACE), developed and validated using the administrative claims of 214,676 diabetic patients of the Veneto region, in North East Italy. Specifically, we use a year of pharmacy and hospitalisation claims, together with basic patient's information, to predict the 4P-MACE composite endpoint, i.e., the first occurrence of death, heart failure, myocardial infarction, or stroke, with a variable prediction horizon of 1 to 5 years. Adapting to the time-to-event nature of this task, we cast our problem as a multi-outcome (4P-MACE and components), multi-label (1 to 5 years) classification task with a custom loss to account for the effect of censoring. Our model, purposefully specified to minimise data preparation costs, exhibits satisfactory performance in predicting 4P-MACE at all prediction horizons: AUROC from 0.812 (C.I.: 0.797 – 0.827) to 0.792 (C.I.: 0.781 – 0.802); C-index from 0.802 (C.I.: 0.788 – 0.816) to 0.770 (C.I.: 0.761 – 0.779). Components’ prediction performance is also adequate, ranging from death's 0.877 1-year AUROC to stroke's 0.689 5-year AUROC.

Aims We compared cardiovascular outcomes of patients with type 2 diabetes (T2D) receiving sodium glucose cotransporter-2 inhibitors (SGLT2i) or dipeptidyl peptidase-4 inhibitors (DPP4i) under routine care. Methods From an administrative claims database of >5.2M citizen, we identified patients with T2D who initiated SGLT2i or DPP4i from 2014 to 2018. Patients were matched by propensity scores. The primary outcome was the 3-point major adverse cardiovascular events (3P-MACE). Results After matching, we included 3216 patients/group, with mean age of 63 years, diabetes duration of 8.7 years, and 20% had cardiovascular disease. During a median follow-up of 18 months, the rate of 3P-MACE was lower among patients who initiated SGLT2i versus DPP4i (HR 0.74; 95 %C.I. 0.58–0.94). Initiators of SGLT2i also showed significantly lower rates of myocardial infarction (HR 0.75; 95 %C.I. 0.56–1.00), hospitalization for heart failure (HR 0.44; 95 %C.I. 0.25–0.95) or cardiovascular causes (HR 0.72; 95 %C.I. 0.60–0.87), and all-cause death (HR 0.49; 95 %C.I. 0.25–0.95). Renal failure was less common with SGLT2i than with DPP4i. Results were consistent to those obtained in a meta-analysis of 10 observational studies on ~1.5M patients. Conclusions Patients with T2D who initiated SGLT2i under routine care had better cardio-renal outcomes and lower all-cause mortality than similar patients who initiated DPP4i.

Newly differentiated pancreatic β cells lack proper insulin secretion profiles of mature functional β cells. The global gene expression differences between paired immature and mature β cells have been studied, but the dynamics of transcriptional events, correlating with temporal development of glucose-stimulated insulin secretion (GSIS), remain to be fully defined. This aspect is important to identify which genes and pathways are necessary for β-cell development or for maturation, as defective insulin secretion is linked with diseases such as diabetes. In this study, we assayed through RNA sequencing the global gene expression across six β-cell developmental stages in mice, spanning from β-cell progenitor to mature β cells. A computational pipeline then selected genes differentially expressed with respect to progenitors and clustered them into groups with distinct temporal patterns associated with biological functions and pathways. These patterns were finally correlated with experimental GSIS, calcium influx, and insulin granule formation data. Gene expression temporal profiling revealed the timing of important biological processes across β-cell maturation, such as the deregulation of β-cell developmental pathways and the activation of molecular machineries for vesicle biosynthesis and transport, signal transduction of transmembrane receptors, and glucose-induced Ca2+ influx, which were established over a week before β-cell maturation completes. In particular, β cells developed robust insulin secretion at high glucose several days after birth, coincident with the establishment of glucose-induced calcium influx. Yet the neonatal β cells displayed high basal insulin secretion, which decreased to the low levels found in mature β cells only a week later. Different genes associated with calcium-mediated processes, whose alterations are linked with insulin resistance and deregulation of glucose homeostasis, showed increased expression across β-cell stages, in accordance with the temporal acquisition of proper GSIS. Our temporal gene expression pattern analysis provided a comprehensive database of the underlying molecular components and biological mechanisms driving β-cell maturation at different temporal stages, which are fundamental for better control of the in vitro production of functional β cells from human embryonic stem/induced pluripotent cell for transplantation-based type 1 diabetes therapy.

People affected by diabetes are at a high risk of developing diabetic nephropathy, which, in turn, is the leading cause of end-stage chronic kidney disease worldwide. Predicting the onset of renal complications as early as possible, when kidney function is still intact, is of paramount importance for therapy selection due to existence of a class of antidiabetic agents (SGLT2 inhibitors) with known nephroprotective properties.

This work presents a tool based on a Dynamic Bayesian Network (DBN) model to simulate the progression to type 2 diabetes (T2D) onset in the ageing population. Including longitudinally collected features characterizing different aspects of the ageing process, we dynamically model the relationships among the variables and the outcome over time, obtaining a network that shows a direct joined effect of glycated hemoglobin and body mass index (BMI) on the T2D onset. Remarkably, DBNs present a broad interpretability regardless of their complexity. We also employ the model to assess the impact of modifiable risk factors on developing the disease, showing how an increased BMI leads to an augmented T2D risk.

Background Cardiovascular outcome trials in high-risk patients showed that some GLP-1 receptor agonists (GLP-1RA), but not dipeptidyl-peptidase-4 inhibitors (DPP-4i), can prevent cardiovascular events in type 2 diabetes (T2D). Since no trial has directly compared these two classes of drugs, we performed a comparative outcome analysis using real-world data. Methods From a database of ~ 5 million people from North-East Italy, we retrospectively identified initiators of GLP-1RA or DPP-4i from 2011 to 2018. We obtained two balanced cohorts by 1:1 propensity score matching. The primary outcome was the 3-point major adverse cardiovascular events (3P-MACE; a composite of death, myocardial infarction, or stroke). 3P-MACE components and hospitalization for heart failure were secondary outcomes. Results From 330,193 individuals with T2D, we extracted two matched cohorts of 2807 GLP-1RA and 2807 DPP-4i initiators, followed for a median of 18 months. On average, patients were 63 years old, 60% male; 15% had pre-existing cardiovascular disease. The rate of 3P-MACE was lower in patients treated with GLP-1RA compared to DPP4i (23.5 vs. 34.9 events per 1000 person-years; HR: 0.67; 95% C.I. 0.53–0.86; p = 0.002). Rates of myocardial infarction (HR 0.67; 95% C.I. 0.50–0.91; p = 0.011) and all-cause death (HR 0.58; 95% C.I. 0.35–0.96; p = 0.034) were lower among GLP-1RA initiators. The as-treated and intention-to-treat approaches yielded similar results. Conclusions Patients initiating a GLP-1RA in clinical practice had better cardiovascular outcomes than similar patients who initiated a DPP-4i. These data strongly confirm findings from cardiovascular outcome trials in a lower risk population.

Diabetes is a chronic disease characterised by high blood glucose levels, resulting in reduced life expectancy and requiring lifelong treatment. Because of their frequent necessity to seek healthcare services, diabetic patients generate huge volumes of administrative claims, detailing their healthcare encounters and prescription history. In the Veneto region (NE Italy), as in the rest of the country, these data are collected systematically and cover all eligible beneficiaries (~5 million in Veneto). Since cardiovascular complications are the main drivers of excess mortality in diabetes, forecasting their onset is desirable for patients’ care and policymaking. Hence, in the present work, we investigate the possibility of predicting 3-year cardiovascular outcomes following a 1-year baseline period of pharmacy data collection. We implement an approach based on recurrent neural networks that combines the chronologically-ordered sequence of prescriptions filled by a diabetic patient and basic biographical information (age, gender, estimated diabetes duration) to determine whether he or she will experience a 4P-MACE (4-point major adverse cardiovascular event; defined as death, myocardial infarction, stroke, or heart failure) endpoint. We develop our model with the data of 97,466 known diabetic patients identified using a validated claims-based algorithm. Independent performance tests on 4,873 subjects yield an area under the receiver-operating characteristic curve of 0.791 and a concordance index of 0.765 for the 4P-MACE primary outcome. We find death to be the easiest 4P-MACE component to predict (AUROC = 0.846), followed by heart failure (0.796), stroke (0.714), and, finally, myocardial infarction (0.708). Secondary, stratified experiments highlight independence of performance from gender, age, and number of prescriptions filled in a year with respect to the primary outcome. To the best of our knowledge, this is the first large-scale prediction model of cardiovascular complications in medication-treated diabetes solely based on sequences of filled prescriptions collected from administrative claims.

Background and aims Diabetes can often remain undiagnosed or unregistered in administrative databases long after its onset, even when laboratory test results meet diagnostic criteria. In the present work, we analyse healthcare data of the Veneto Region, North East Italy, with the aims of: (i) developing an algorithm for the identification of diabetes from administrative claims (4,236,007 citizens), (ii) assessing its reliability by comparing its performance with the gold standard clinical diagnosis from a clinical database (7525 patients), (iii) combining the algorithm and the laboratory data of the regional Health Information Exchange (rHIE) system (543,520 subjects) to identify undiagnosed diabetes, and (iv) providing a credible estimate of the true prevalence of diabetes in Veneto. Methods and results The proposed algorithm for the identification of diabetes was fed by administrative data related to drug dispensations, outpatient visits, and hospitalisations. Evaluated against a clinical database, the algorithm achieved 95.7% sensitivity, 87.9% specificity, and 97.6% precision. To identify possible cases of undiagnosed diabetes, we applied standard diagnostic criteria to the laboratory test results of the subjects who, according to the algorithm, had no diabetes-related claims. Using a simplified probabilistic model, we corrected our claims-based estimate of known diabetes (6.17% prevalence; 261,303 cases) to account for undiagnosed cases, yielding an estimated total prevalence of 7.50%. Conclusion We herein validated an algorithm for the diagnosis of diabetes using administrative claims against the clinical diagnosis. Together with rHIE laboratory data, this allowed to identify possibly undiagnosed diabetes and estimate the true prevalence of diabetes in Veneto.

We performed a comparative gene expression profiling (GEP) study on B-cells and plasma cells of Waldenström Macroglobulinemia (WM), IgM monoclonal gammopathies of undetermined significance (IgMMGUS), and normal individuals (CTRLs) to identify GEP changes as reliable predictors of progression of IgMMGUS to WM. We analyzed bone marrow B-cells and plasma cells from 36 WM patients, 13 IgMMGUS subjects, and 7 CTRLs by Affymetrix microarray, respectively (Table 1). GEP experiments were performed on the CD19+ and CD138+ cells using GeneChip-HGU133 Plus 2.0. Data were preprocessed and normalized by Robust Multi-Array Average and ComBat. Selection of the different expressed genes was performed separately for CD19+ and CD138+ cells, using Significance Analysis of Microarrays (SAM) on the 3 groups and a false discovery rate threshold of 5%, followed, for significance comparisons, by a pair-wise SAM test corrected for multiple testing. We focused on the comparison of the CD19+ cells of WM vs. IgMMGUS vs. CTRLs which highlighted 2038 unique genes whereas the same comparison of the CD138+ cells determined 29 unique genes (Trojani et.al. Cancers 2021). Among the 2038 DEGs, 115 genes were grouped in KEGG pathways involved in Wnt-signaling, BCR-signaling, calcium signaling, hematopoietic cell antigens, cell adhesion, adherens junctions, coagulation cascade, platelet activation, cytokine receptor, and signaling pathways responsible for cell cycle, apoptosis, and survival. Interestingly, most of the 115 DEGs in B-cells were different expressed in WM vs. IgMMGUS and CTRLs. Only 9/115 DEGs were significantly different expressed in WM vs. CTRLs and in IgMMGUS vs. CTRLs, but no significant expression changes were noted between WM and IgMMGUS (Table 2). To further inspect the similarities and the differences among WM and IgMMGUS, we computed the Euclidean pair-wise distance between subjects and, using this distance as weight, constructed a minimum spanning tree (MST) (Figure 1). Considerably, four probesets identified ADRB2 (transmembrane Beta adrenergic receptor) which was up regulated in WM and IgMMGUS compared to CTRLs. The over expression of ADRB2 was also demonstrated in Mantle Cell Lymphoma cell lines and in Diffuse large B-cell lymphoma (DLBCL) lymphocytes compared to normal B-cells (doi10.1016/j.cellsig.2017.08.002), and in most malignancies (doi10.1007/s11033-021-06250-y) . As far as we know, ADAM23 (ADAM Metallopeptidase Domain23) has not been found in WM, whereas we suggest its possible role in WM patients with Sjogren's syndrome (SS). ADAM23 plays a role in the peripheral neuropathy by controlling the activity of potassium channels in SS (doi10.1007/s10067-016-3499-z). Some authors found that sensory/motor neuropathies were associated with MGUS patients (doi10.1017/s0317167100011483). We strongly believe that the down regulation of ADAM23 in WM and IgMMGUS has a good chance to be associated with clinical neuropathy in WM and IgMMGUS. RASGRP3 (RAS Guanyl Releasing Protein3) and PIK3AP1 (Phosphoinositide 3 Kinase Adaptor Protein1) play crucial roles in BCR signaling pathway: PIK3AP1 activates the PI3K-Akt signaling while RASGRP3 stimulates MAPK signaling pathway. The deregulation of LEF1 (Lymphoid Enhancer Binding Factor1) and genes of Wnt-pathway were previously demonstrated in B-cell disorders and multiple myeloma (doi10.1007/s00277-017-3207-3, doi10.1016/j.pathol.2019.09.009). According to these studies, we showed the under expression of LEF1 in WM and IgMMGUS compared to CTRLs. We identified the down regulation of EZH2 (Enhancer Of Zeste2 Polycomb Repressive Complex2Subunit) in WM and IgMMGUS compared to CTRLs. EZH2 is involved in Follicular lymphoma and DLBCL (doi10.1080/2162402X.2017.1321184). CDHR3 (Cadherin Related Family Member3), CHEK1 (Checkpoint Kinase1), and HIST1H1B (Histone-H1.5) were over expressed in CTRLs compared to IgMMGUS and WM. In conclusion, the common gene-set in WM and IgMMGUS could suggest two-hit hypothesis. First, the gene-set could play a role in the risk of progression of IgMMGUS to WM. Until now, all the IgMMGUS subjects have not been transformed in WM or other NHL, but they have been monitored every 6 months, and their possible transformation to lymphoma could highlight new insights. The second hypothesis suggests their involvement in the biological processes of leukemogenesis in WM and IgMMGUS which will be further investigated. Figure 1 Figure 1. Disclosures Tedeschi: AbbVie: Honoraria, Speakers Bureau; AstraZeneca: Honoraria, Speakers Bureau; Beigene: Honoraria, Speakers Bureau; Janssen: Honoraria, Speakers Bureau.

BACKGROUND: Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder with heterogeneous biological and clinical features. The biomolecular mechanisms of CML response to tyrosine-kinase inhibitors are not fully defined. OBJECTIVE: We undertook a gene expression profiling (GEP) study of selected bone marrow (BM) CD34+/lin-cells of chronic-phase CML patients at diagnosis and after 12 months of TKI nilotinib to investigate molecular signatures characterizing both conditions. METHODS:We selected and counted BM CD34+/lin- cells of 30 CML patients at diagnosis and during 3, 6 and 12 months of first-line nilotinib treatment. GEP was performed between CD34+/lin- cells of patients at diagnosis and the same patients after 12 months of nilotinib. RESULTS: The number of BM CD34+/lin- cells dramatically decreased after 3, 6 and 12 months of nilotinib. GEP detected 264 statistically significant differentially expressed genes at diagnosis vs. 12 months of nilotinib. Functional enrichment analysis revealed groups of genes belonging to 14 pathways differentially active during nilotinib treatment. CONCLUSIONS: In conclusion, lipid, glucose and sphingolipid metabolism, insulin resistance, complement and coagulation, platelet activation, cytoscheleton, cell adhesion, transport, B cell differentiation, RAS-signaling pathway, proliferation, growth factors, and apoptosis were significantly deregulated between CML patients at diagnosis and after 12 months of nilotinib.

Background Complication screening is recommended for patients with type 2 diabetes (T2D), but the optimal screening intensity and schedules are unknown. In this study, we evaluated whether intensive versus standard complication screening affects long-term cardiovascular outcomes. Methods In this observational study, we included 368 T2D patients referred for intensive screening provided as a 1-day session of clinical–instrumental evaluation of diabetic complications, followed by dedicated counseling. From a total of 4906 patients, we selected control T2D patients who underwent standard complication screening at different visits, by 2:1 propensity score matching. The primary endpoint was the 4p-MACE, defined as cardiovascular mortality, or non-fatal myocardial infarction, stroke, or heart failure. The Cox proportional regression analyses was used to compare outcome occurrence in the two groups, adjusted for residual confounders. Results 357 patients from the intensive screening group (out of 368) were matched with 683 patients in the standard screening group. Clinical characteristics were well balanced between the two groups, except for a slightly higher prevalence of microangiopathy in the intensive group (56% vs 50%; standardized mean difference 0.11, p = 0.1). Median follow-up was 5.6 years. The adjusted incidence of 4p-MACE was significantly lower in the intensive versus standard screening group (HR 0.70; 95% CI 0.52–0.95; p = 0.02). All components of the primary endpoint had nominally lower rates in the intensive versus standard screening group, which was particularly significant for heart failure (HR 0.43; 95% CI 0.22–0.83; p = 0.01). Conclusion Among T2D patients attending a specialist outpatient clinic, intensive complication screening is followed by better long-term cardiovascular outcomes. No significant effect was noted for cardiovascular and all-cause mortality and the benefit was mainly driven by a reduced rate of hospitalization for heart failure.

Chronic myeloid leukemia (CML) is characterized by the constitutive tyrosine kinase activity of the oncoprotein BCR-ABL1 in myeloid progenitor cells that activates multiple signal transduction pathways leading to the leukemic phenotype. The tyrosine-kinase inhibitor (TKI) nilotinib inhibits the tyrosine kinase activity of BCR-ABL1 in CML patients. Despite the success of nilotinib treatment in patients with chronic-phase (CP) CML, a population of Philadelphia-positive (Ph+) quiescent stem cells escapes the drug activity and can lead to drug resistance. The molecular mechanism by which these quiescent cells remain insensitive is poorly understood. The aim of this study was to compare the gene expression profiling (GEP) of bone marrow (BM) CD34+/lin- cells from CP-CML patients at diagnosis and after 12 months of nilotinib treatment by microarray, in order to identify gene expression changes and the dysregulation of pathways due to nilotinib action. We selected BM CD34+/lin- cells from 78 CP-CML patients at diagnosis and after 12 months of first-line nilotinib therapy and microarray analysis was performed. GEP bioinformatic analyses identified 2,959 differently expressed probes and functional clustering determined some significantly enriched pathways between diagnosis and 12 months of nilotinib treatment. Among these pathways, we observed the under expression of 26 genes encoding proteins belonging to the cell cycle after 12 months of nilotinib treatment which led to the up-regulation of chromosome replication, cell proliferation, DNA replication, and DNA damage checkpoint at diagnosis. We demonstrated the under expression of the ATP-binding cassette (ABC) transporters ABCC4, ABCC5, and ABCD3 encoding proteins which pumped drugs out of the cells after 12 months of nilotinib. Moreover, GEP data demonstrated the deregulation of genes involved in the JAK-STAT signaling pathway. The down-regulation of JAK2, IL7, STAM, PIK3CA, PTPN11, RAF1, and SOS1 key genes after 12 months of nilotinib could demonstrate the up-regulation of cell cycle, proliferation and differentiation via MAPK and PI3K-AKT signaling pathways at diagnosis.

Diabetes is a chronic illness characterised by elevated blood glucose levels, driving excess mortality. Its prompt detection and accurate management are critical for delaying complications. Nevertheless, diabetes can remain undiagnosed for years from the onset. The identification of undiagnosed diabetes is a public health priority: in Italy, it is estimated that up to 30% of diabetes cases remain undetected, i.e., that ~1.8 million citizens may be unaware they need medical help. Sometimes, this happens even though these subjects undergo routine or emergency check-ups. Veneto, a region in North-East Italy with 4.9 million residents, implements a regional Health Information Exchange system (rHIE) to collect healthcare data, including laboratory reports, and integrate them with administrative claims. Their combination may be instrumental in finding otherwise undetected cases of diabetes. On the one hand, known diabetic patients should have disease management-generated claims; on the other, laboratory test results can be independently evaluated against diagnostic criteria. In the present work, we examined the anonymised claims and laboratory data, extracted from the rHIE, of 23,376 citizens of the Veneto region. We compared their exemptions, diabetes-related hospitalisation discharge codes, and antidiabetic drugs between 2012 and 2018 to the results of their fasting glucose, glycated haemoglobin, and oral glucose tolerance tests in 2017-2018. We identified 1,407 (6.02%) subjects who, according to administrative claims, appear to be free from diabetes, but met at least one laboratory diagnostic criterion. Such a discrepancy suggests that these people may be undiagnosed diabetic patients. To the best of our knowledge, this is the first proof of concept of an automatic system for the detection of undiagnosed diabetes in Italy. Its full integration in the rHIE and its consequent capillary application could potentially reveal thousands of hidden cases throughout Veneto.

IntroductionSodium glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) protect type 2 diabetic (T2D) patients from cardiovascular events, but no trial has directly compared their cardiovascular effects. We aimed to address this gap using real-world data.Research design and methodsWe performed a retrospective real-world study on a population of ~5 million inhabitants from North-East Italy. We identified T2D patients who received new prescription of SGLT2i or GLP-1RA from 2014 to 2018. SGLT2i and GLP-1RA initiators were matched 1:1 by propensity scores. The primary outcome was a composite of all-cause death, myocardial infarction, and stroke (three-point major adverse cardiovascular events (3P-MACE)). Secondary endpoints were each component of the primary endpoint, hospitalization for heart failure (HF), revascularization, hospitalization for cardiovascular causes, and adverse events.ResultsFrom a population of 330 193 diabetic patients, we followed 8596 SGLT2i and GLP-1RA matched initiators for a median of 13 months. Patients in both groups were on average 63 years old, 63% men, and 18% had pre-existing cardiovascular disease. T2D patients treated with SGLT2i versus GLP-1RA, experienced a lower rate of 3P-MACE (HR 0.68; 95% CI 0.61 to 0.99; p=0.043), myocardial infarction (HR 0.72; 95% CI 0.53 to 0.98; p=0.035), hospitalization for HF (HR 0.59; 95% CI 0.35 to 0.99; p=0.048), and hospitalization for cardiovascular causes (HR 0.82; 95% CI 0.69 to 0.99; p=0.037). Adverse events were not significantly different between the two groups.ConclusionsIn the absence of dedicated trials, this observational study suggests that SGLT2i may be more effective than GLP-1RA in improving cardiovascular outcomes of T2D.Trial registration numberNCT04184947.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in clinical presentation with an urgent need for better stratification tools for clinical development and care. In this study we used a crowdsourcing approach to address the problem of ALS patient stratification. The DREAM Prize4Life ALS Stratification Challenge was a crowdsourcing initiative using data from >10,000 patients from completed ALS clinical trials and 1479 patients from community-based patient registers. Challenge participants used machine learning and clustering techniques to predict ALS progression and survival. By developing new approaches, the best performing teams were able to predict disease outcomes better than currently available methods. At the same time, the integration of clustering components across methods led to the emergence of distinct consensus clusters, separating patients into four consistent groups, each with its unique predictors for classification. This analysis reveals for the first time the potential of a crowdsourcing approach to uncover covert patient sub-populations, and to accelerate disease understanding and therapeutic development.

Persistent infection by high-risk human papillomaviruses (HPVs) is associated with the development of cervical cancer and a subset of anogenital and head and neck squamous cell carcinomas. Abnormal expression of cellular microRNAs (miRNAs) plays an important role in the development of cancer, including HPV-related tumors. In this study, we demonstrated that miR-146a-5p was down-regulated by E6 and, less efficiently, by E7 of high-risk HPV16 in keratinocytes and the presence of low levels of this miRNA in cervical carcinoma cell lines and in high-risk HPV-positive cervical specimens. Down-regulation of miR-146a-5p was mediated at least in part by the transcription repressor c-MYC, through binding sites in the miR-146a promoter. Overexpression of miR-146a-5p significantly inhibited proliferation and migration of keratinocytes and cervical cancer cells. The histone demethylase KDM2B was validated as a new direct target of miR-146a-5p and two putative binding sites for miR-146a-5p were identified in its 3'UTR sequence. Western blot analysis and immunohistochemistry showed that KDM2B was overexpressed in HPV16 E6/E7-positive keratinocytes, in cervical cancer cell lines, and in a subset of invasive cervical carcinomas and HPV-positive laryngeal squamous cell carcinomas. In these tumors, KDM2B overexpression was associated with c-MYC copy number gain. In vitro, silencing of KDM2B inhibited proliferation of cervical cancer cells. In conclusion, this study identified a novel player, the hystone demethylase KDM2B, in HPV-mediated tumorigenesis. E6 and, less efficiently, E7 of high-risk HPV16 up-regulated KDM2B expression in human keratinocytes through a pathway involving overexpression of c-MYC, which in turn downregulated miR-146a-5p.

Background & Aims MicroRNAs (miRNAs) have been involved in hepatocarcinogenesis, but little is known on their role in the progression of chronic viral hepatitis. Aim of this study was to identify miRNA signatures associated with stages of disease progression in patients with chronic viral hepatitis. Methods MiRNA expression profile was investigated in liver biopsies from patients with chronic viral hepatitis and correlated with clinical, virological and histopathological features. Relevant miRNAs were further investigated. Results Most of the significant changes in miRNA expression were associated with liver fibrosis stages and included the significant up-regulation of a group of miRNAs that were demonstrated to target the master regulators of epithelial–mesenchymal transition ZEB1 and ZEB2 and involved in the preservation of epithelial cell differentiation, but also in cell proliferation and fibrogenesis. In agreement with miRNA data, immunostaining of liver biopsies showed that expression of the epithelial marker E-cadherin was maintained in severe fibrosis/cirrhosis while expression of ZEBs and other markers of epithelial–mesenchymal transition were low or absent. Severe liver fibrosis was also significantly associated with the down-regulation of miRNAs with antiproliferative and tumour suppressor activity. Similar changes in miRNA and target gene expression were demonstrated along with disease progression in a mouse model of carbon tetrachloride (CCl4)-induced liver fibrosis, suggesting that they might represent a general response to liver injury. Conclusion Chronic viral hepatitis progression is associated with the activation of miRNA pathways that promote cell proliferation and fibrogenesis, but preserve the differentiated hepatocyte phenotype.

ObjectiveType 2 diabetes arises from the interaction of physiological and lifestyle risk factors. Our objective was to develop a model for predicting the risk of T2D, which could use various amounts of background information.Research design and methodsWe trained a survival analysis model on 8483 people from three large Finnish and Spanish data sets, to predict the time until incident T2D. All studies included anthropometric data, fasting laboratory values, an oral glucose tolerance test (OGTT) and information on co-morbidities and lifestyle habits. The variables were grouped into three sets reflecting different degrees of information availability. Scenario 1 included background and anthropometric information; Scenario 2 added routine laboratory tests; Scenario 3 also added results from an OGTT. Predictive performance of these models was compared with FINDRISC and Framingham risk scores.ResultsThe three models predicted T2D risk with an average integrated area under the ROC curve equal to 0.83, 0.87 and 0.90, respectively, compared with 0.80 and 0.75 obtained using the FINDRISC and Framingham risk scores. The results were validated on two independent cohorts. Glucose values and particularly 2-h glucose during OGTT (2h-PG) had highest predictive value. Smoking, marital and professional status, waist circumference, blood pressure, age and gender were also predictive.ConclusionsOur models provide an estimation of patient’s risk over time and outweigh FINDRISC and Framingham traditional scores for prediction of T2D risk. Of note, the models developed in Scenarios 1 and 2, only exploited variables easily available at general patient visits.

Background. Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease primarily affecting upper and lower motor neurons in the brain and spinal cord. The heterogeneity in the course of ALS clinical progression and ultimately survival, coupled with the rarity of this disease, make predicting disease outcome at the level of the individual patient very challenging. Besides, stratification of ALS patients has been known for years as a question of great importance to clinical practice, research and drug development. Methods. In this work, we present a Dynamic Bayesian Network (DBN) model of ALS progression to detect probabilistic relationships among variables included in the Pooled Resource Open-Access ALS Clinical Trials Database (PRO-ACT), which provides records of over 10,700 patients from different clinical trials, and with over 2,869,973 longitudinally collected data measurements. Results. Our model unravels new dependencies among clinical variables in relation to ALS progression, such as the influence of basophil count and creatine kinase on patients’ clinical status and the respiratory functional state, respectively. Furthermore, it provided an indication of ALS temporal evolution, in terms of the most probable disease trajectories across time at the level of both patient population and individual patient. Conclusions. The risk factors identified by out DBN model could allow patients' stratification based on velocity of disease progression and a sensitivity analysis on this latter in response to changes in input variables, i.e. variables measured at diagnosis.

Diabetes is the leading cause of end stage renal disease. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2,843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (p=6x10-3 7 ). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associated variants. Whole exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (p=2.2×10-5) and the risk of type 2 diabetes (p=6.1x10-4 11 ) were associated with the risk of diabetic kidney disease. We also found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (p=1.1×10-4 13 ). Pathway analysis implicated ascorbate and aldarate metabolism (p=9×10-6), and pentose and glucuronate interconversions (p=3×10-6 14 ) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.

In this study, we investigated the transcriptome differences of selected bone marrow (BM) CD19+ and BM CD138+ cells of Waldenström's Macroglobulinemia (WM) patients vs. IgM Monoclonal Gammopathy of Undetermined Significance (IgMMGUS) subjects vs. healthy donors (CTLRs). We performed the gene expression profiling (GEP) considering all the different transcript isoforms of genes, coding and non-coding transcripts. Microarrays were performed on BM CD19+ cells (n=36) and BM CD138+ (n=32) in WM, BM CD19+ cells (n=10) and BM CD138+ (n=10) cells in IgMMGUS, BM CD19+ cells (n=7) and BM CD138+ (n=7) cells in healthy donors (CTRLs), respectively. Data were preprocessed and normalized using RMA and ComBat. We performed a functional annotation clustering and enrichment analysis on each pattern using DAVID 6.7 (https://david.ncifcrf.gov/). Selection of differentially expressed genes (DEg) was performed separately for CD19+ and CD138+ cells using Statistical Analysis for Microarrays (SAM) on 3 groups (WM, IgMMGUS and CTRLs). A false discovery rate threshold of 5% was used followed, for significance comparisons, by a pair-wise SAM test. We identified 3095 unique probe-sets corresponding to 2559 unique genes and 494 not annotated probe-sets from the comparison of WM vs. IgMMGUS vs. CRTLs in CD19+ cells. The comparison of WM, IgMMGUS and CRTLs in CD138+ cells demonstrated 38 unique probe-sets corresponding to 32 unique genes and 2 not annotated probe-sets. There were no genes in common between the CD19+ and the CD138+ DEg lists. To better characterize the genes selected as differentially expressed we considered, for all genes that resulted significantly DE in at least one of the below listed comparisons, the following patterns of differential expression: 1) WM>IgMGUS, IgMGUS>CTRLs, and WM>CTRLs; 2) WM We identified 265 unique genes in the CD19+ cells pattern 1 whereas the CD19+ cells pattern 2 contained 403 unique genes. Enrichment analyses showed that transmembrane, adhesion and flavo proteins were progressively significantly under expressed in the WM>IgMGUS>CTRL CD19+ pattern. IL2RA (CD25), ATP1B1 and ADRB2 (cGMP-PKG signaling pathway), GPER (activating PI3K signaling pathway) and IGHM were up regulated in WM. We found in the hematopoietic lineage that CD1D (positive in WM Natural Killer T cells), CD44 (marker in WM stromal cells), IL6 and IGHM were progressively under expressed in WM vs. IgMMGUS vs. CTRLs. CEACAM1 and ANG, both inducing new blood vessels formation, were progressively down regulated in WM vs. IgMMGUS vs. CTRLs. Notably, ANG was over expressed in WM vs. IgMMGUS vs. CTRLs with the fold change (FC) of 1.54, 2.13 and 3.27, respectively. The WM ADARB1 (alternative splicing) and LEF1 (transcription regulation) were progressively over expressed in WM vs. IgMMGUS vs. CTRLs with the following FC: -2.19, -2.16, -4.72 and -1.50, -2.58, -3.86, respectively. In addition, IL4R (plasma membrane protein) which has been demonstrated to be down regulated in WM B cells, was progressively up regulated in WM vs. IgMMGUS vs. CTRLs with the FC of -1.83, -2.18, and -3.99, respectively. GEP data determined few genes in the CD138+ cells patterns: no genes were differently expressed in the WM>IgMGUS>CTRL CD138+ pattern 1 whereas 26 genes emerged from the WM TJP1 (apoptosis) was progressively over expressed in WM vs. IgMMGUS vs. CTRLs with the FC -2.65, -2.33 and -6.18, respectively. In previous studies it has been demonstrated that the TJP1 lower expression induced resistance to proteasome inhibitors in myeloma. TUBB2B, SEPT10, TTLL,SYNM, PARD3, ARHGAP32, involved in the cytoskeleton, as well as PERP (TP53 apoptosis effector), ESPR1 (RNA splicing), and CADPS2 (protein transport) were progressively down regulated in CTRLs vs. IgMMGUS vs. WM. In conclusion, we demonstrated that transmembrane receptors, cell cycle, and cytoskeleton proteins in BM CD19+ cells as well as transmembrane/cell junctions molecules in BM CD138+ cells were differently and progressively deregulated in WM vs. IgMMGUS vs. CTRLs, respectively. Disclosures Tedeschi: Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; BeiGene: Honoraria; SUNESIS: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen spa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Consultancy. Montillo:AbbVie: Consultancy, Honoraria, Speakers Bureau; Versatem: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Speakers Bureau; Acerta: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau.

Dysregulation of host microRNA expression has been involved in the development and progression of human papillomavirus (HPV)-related tumors. Analysis of miR-146a expression in a series of 59 penile squamous cell carcinomas (PSCCs) showed that its levels were lower in high-risk HPV-positive than in HPV-negative PSCCs and inversely correlated with expression of epidermal growth factor receptor (EGFR), a known target for miR-146a. Analysis of genotype distribution for rs2910164, a common functional polymorphism of miR-146a, did not identify correlations with miR-146a levels and EGFR expression in PSCCs. In vitro experiments demonstrated that E6 of HPV type 16, but not low-risk HPV-6, down-regulated miR-146a in human foreskin keratinocytes and up-regulated EGFR. Ectopic expression of miR-146a decreased expression of EGFR and inhibited proliferation of keratinocytes and cervical carcinoma cells. EGFR is commonly overexpressed in penile cancer and in other squamous cell carcinomas. Molecular mechanisms leading to EGFR overexpression and activation are known for HPV-negative cancers and include amplification or mutations of the EGFR gene. The results of this study indicate that down-regulation of miR-146a may represent another mechanism of EGFR overexpression in PSCCs, which can be mediated by high-risk HPV E6 in HPV-related tumors.

Several studies demonstrated IGVH mutational status and ZAP70 expression as the most relevant prognostic markers in Chronic Lymphocytic Leukemia (CLL), suggesting the separation of two patient subgroups: with good mutated ZAP70 negative (MTZAP70(-) and poor unmutated ZAP70 positive (UMZAP70(+)) prognosis.We determined the gene expression of B cells in 112 CLL patients divided into three classes: class 1 with MTZAP70(-), class 2 with UMZAP70(+), and class 3 included both UMZAP70(-) and MTZAP70(+).We found LPL, AGPAT2, MBOAT1, CHPT1, AGPAT4, PLD1 genes encoding enzymes involved in lipid metabolism overexpressed in UMZAP70(+). In addition, this study identified ARSD, a gene belonging to the sphingolipid metabolism, as a new gene significantly overexpressed in UMZAP70(+) compared to MTZAP70(-). Western blots confirmed that ARSD protein levels were significantly different between the 3 classes of patients and normal controls. Statistical analysis identified a significant correlation between ARSD and IGVH; however, both ARSD protein level and IGVH were independently associated with the need for therapy of CLL patients.ARSD is a novel prognostic factor as the time to start therapy is shorter in patients with high levels of ARSD protein and sphingolipid metabolism could represent a new biological mechanism in CLL.

Waldenstrom macroglobulinemia (WM) (symptomatic and indolent) and immunoglobulin M (IgM) monoclonal gammopathy of undetermined significance (IgMMGUS) can be identified based on the bone marrow (BM) infiltration and the existence of symptoms. The purpose of this study was to investigate the biological and genetic characteristics of both disorders comparing the molecular signature of WM versus IgMMGUS using microarray analysis. We investigated BM CD19 + cells isolated from 21 WM patients and 10 IgMMGUS cases, and CD138 + BM cells isolated from all of the WM patients and 4 of the IgMMGUS cases. Gene expression profiling of WM versus IgMMGUS CD19 + cells highlighted 151 differently expressed genes and the comparison with CD138 + cells demonstrated 43 differently expressed genes in WM versus IgMMGUS. Regulation of transcription, Janus kinase/signal transducer and activator of transcription, PI3K/Akt/mammalian target of rapamycin, mitogen-activated protein kinase signaling pathways are the relevant gene ontology biological processes occurring in CD19 + cells, and immune response, cell activation, and signaling processes developing in CD138 + cells mainly distinguish WM and IgMMGUS.

Cardiovascular diseases (CVD) and diabetes still represent the main cause of mortality and morbidity in the industrialized world. Low birth weight (LBW), caused by intrauterine growth restriction (IUGR), was recently known to be associated with increased rates of CVD and non-insulin dependent diabetes in adult life (Barker's hypothesis). Well-established animal models have shown that environmentally induced IUGR (diet, diabetes, hormone exposure, hypoxia) increases the risk of a variety of diseases later in life with similar phenotypic outcomes in target organs. This suggests that a range of disruptions in fetal and postnatal growth may act through common pathways to regulate the developmental programming and produce a similar adult phenotype. The identification of all involved signaling cascades, underlying the physiopathology of these damages in IUGR fetuses, with their influence on adult health, is still far from satisfactory. The endothelium may be important for long-term remodeling and in the control of elastic properties of the arterial wall. Several clinical and experimental studies showed that IUGR fetuses, neonates, children and adolescents present signs of endothelial dysfunction, valuated by aorta intima media thickness, carotid intima media thickness and stiffness, central pulse wave velocity, brachial artery flow-mediated dilation, laser Doppler skin perfusion and by the measure of arterial blood pressure. In utero identification of high risk fetuses and long-term follow-up are necessary to assess the effects of interventions aimed at preventing pregnancy-induced hypertension, reducing maternal obesity, encouraging a healthy life style and preventing childhood obesity on adult blood pressure and cardiovascular disease in later life.

AIMS/HYPOTHESIS: Diabetic nephropathy is a major diabetic complication, and diabetes is the leading cause of end-stage renal disease (ESRD). Family studies suggest a hereditary component for diabetic nephropathy. However, only a few genes have been associated with diabetic nephropathy or ESRD in diabetic patients. Our aim was to detect novel genetic variants associated with diabetic nephropathy and ESRD.METHODS: We exploited a novel algorithm, 'Bag of Naive Bayes', whose marker selection strategy is complementary to that of conventional genome-wide association models based on univariate association tests. The analysis was performed on a genome-wide association study of 3,464 patients with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study and subsequently replicated with 4,263 type 1 diabetes patients from the Steno Diabetes Centre, the All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK collection (UK-Republic of Ireland) and the Genetics of Kidneys in Diabetes US Study (GoKinD US).RESULTS: Five genetic loci (WNT4/ZBTB40-rs12137135, RGMA/MCTP2-rs17709344, MAPRE1P2-rs1670754, SEMA6D/SLC24A5-rs12917114 and SIK1-rs2838302) were associated with ESRD in the FinnDiane study. An association between ESRD and rs17709344, tagging the previously identified rs12437854 and located between the RGMA and MCTP2 genes, was replicated in independent case-control cohorts. rs12917114 near SEMA6D was associated with ESRD in the replication cohorts under the genotypic model (p CONCLUSIONS/INTERPRETATION: This study supports the previously identified findings on the RGMA/MCTP2 region and suggests novel susceptibility loci for ESRD. This highlights the importance of applying complementary statistical methods to detect novel genetic variants in diabetic nephropathy and, in general, in complex diseases.

The metabolic syndrome (MS), a predisposing condition for cardiovascular disease, presents disturbances in hemodynamics; impedance cardiography (ICG) can assess these alterations. In subjects with MS, the morphology of the pulses present in the ICG time series is more irregular/complex than in normal subjects. Therefore, the aim of the present study was to quantitatively assess the complexity of ICG times series in 53 patients, with or without MS, through a nonlinear analysis algorithm, the approximate entropy, a method employed in recent years for the study of several biological signals, which provides a scalar index, ApEn. We correlated ApEn computed from ICG times series data during fasting and postprandial phase with the presence of alterations in the parameters defining MS [Adult Treatment Panel (ATP) III (Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C; National Heart, Lung, and Blood Institute; American Heart Association. Circulation 109: 433–438, 2004) and the International Diabetes Federation (IDF) definition]. Results show that ApEn was significantly higher in subjects with MS compared with those without (1.81 ± 0.09 vs. 1.65 ± 0.13; means ± SD; P = 0.0013, with ATP III definition; 1.82 ± 0.09 vs. 1.67 ± 0.12; P = 0.00006, with the IDF definition). We also demonstrated that ApEn increase parallels the number of components of MS. ApEn was then correlated to each MS component: mean ApEn values of subjects belonging to the first and fourth quartiles of the distribution of MS parameters were statistically different for all parameters but HDL cholesterol. No difference was observed between ApEn values evaluated in fasting and postprandial states. In conclusion, we identified that MS is characterized by an increased complexity of ICG signals: this may have a prognostic relevance in subjects with this condition.

Abstract 3447 Several studies have focused on the identification of biological markers that influence the clinical heterogeneity of Chronic lymphocytic leukemia (CLL). Until now IGVH and ZAP-70 are the most relevant prognostic markers in CLL suggesting the separation of two patient subgroups: with good MTZAP-70− (mutated and ZAP-70 negative) and poor UMZAP-70+ (unmutated and ZAP-70 positive) prognosis. Gene expression profiling in CLL has been demonstrated to be useful for the development of new biomarkers as prognostic factors able to predict the clinical course, the response and resistance to therapy. The aim of this study has focused on the identification of different molecular signatures capable of revealing new potential molecular predictors for prognostic assessment or genetic risk and intriguing biological pathways. We have determined gene expression profiling of B cells in 112 CLL patients divided into three classes: the first with MT and ZAP-70−, the second with UM and ZAP-70+, and the third included both UM ZAP-70− and MT ZAP-70+ using Affymetrix HG-U133 Plus 2.0. Among the set of 65 genes identified by microarray analysis we have found: AGPAT2, APP, ARSD, CHPT1, CRY1, DCLK2, LPL, MBOAT1, P2RX1, RIMKLB, ZAP-70, ZNF66 whose expressions were higher in second class (UMZAP-70+) while ADAM29, EGR3, FGL2, FUT8, NRIP1, TGFBR3, YPEL1 showed higher expression levels in first class (MTZAP-70−). Both analysis of differential expression and cluster analysis revealed that CLL patients were better partitioned in two rather than in three classes, based on their expression profiles. We have also noted that the expression signature differentiating between MTZAP-70− and UMZAP-70+ B cells from CLL patients showed that gene coding for enzymes which regulate lipid metabolism (sphingolipid/glycerolipid/glycerophospholipid) ARSD, LPL, MBOAT1, CHPT1, AGPAT4, AGPAT2, PLD1 were overexpressed in UMZAP-70+ compared to MTZAP-70−. In particular we focused on ARSD as a new gene in CLL whose expression was consistently higher in UMZAP-70+ compared to MTZAP-70− CLL B cells. Western blotting experiments showed that the expression level of ARSD protein was 1.8 times higher in UMZAP-70+ compared to MTZAP-70− B cells (p-value=0.0002), whereas ARSD protein levels in B cells from healthy donors (CTRL) were 2.03 (p-value=0.0006) and 3.73 (p-value=0.001) times lower compared to MTZAP-70− and UMZAP-70+, respectively. The marked increase in ARSD expression in UMZAP-70+ compared to MTZAP-70− and CTRLs was statistically significant as shown in Figure 1. At present our attention has been focused on ARSD role in predicting the entry in therapy. By means of a ROC analysis carried out with the Youden's method to determine the cut-off value we have found it at 99, so that we have pragmatically set it at 100. Even if the patient number is limited the difference in treatment-free survivorship between the two groups (above and below 100) was statistically significant (p = 0.0205) and the cut-off value used as prognostic index showed 66.7% sensitivity and positive predictive value and 75.0% specificity and negative predictive value. Differences in treatment-free survival are showed in figure 2.Figure 2Treatment-free survivalFigure 2. Treatment-free survival In conclusion 65 genes were differentially expressed in MTZAP-70− vs UMZAP-70+ CLL patients; among the 65 genes 7 were involved in lipid metabolism, in particular ARSD being identified in sphingolipid pathway. Western blotting experiments detected significantly higher ARSD levels in UMZAP-70+ compared to MTZAP-70− and CTRLs B cells. Future studies will assess the role of ARSD as a prognostic factor in clinical trials combined with IGVH and ZAP-70 as well as the sphingolipid metabolism as a putative new biological mechanism in CLL. Disclosures: No relevant conflicts of interest to declare.

Neisseria meningitidis is a human-specific pathogen known for its capability to cause sepsis and meningitis. Here we report the availability of 2 draft genome sequences obtained from patients infected during the same epidemic outbreak. Both bacterial isolates belong to serogroup C, but their genome sequences show local and remarkable differences compared with each other or with the reference genome of strain FAM18.

Background In diabetes chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation through the activation of the MAP kinases, which in turn regulate cellular proliferation. However, it is not known whether insulin itself could increase the transcription of specific genes for cellular proliferation in the endothelium. Hence, the characterization of transcriptional modifications in endothelium is an important step for a better understanding of the mechanism of insulin action and the relationship between endothelial cell dysfunction and insulin resistance. Methodology and principal findings The transcriptional response of endothelial cells in the 440 minutes following insulin stimulation was monitored using microarrays and compared to a control condition. About 1700 genes were selected as differentially expressed based on their treated minus control profile, thus allowing the detection of even small but systematic changes in gene expression. Genes were clustered in 7 groups according to their time expression profile and classified into 15 functional categories that can support the biological effects of insulin, based on Gene Ontology enrichment analysis. In terms of endothelial function, the most prominent processes affected were NADH dehydrogenase activity, N-terminal myristoylation domain binding, nitric-oxide synthase regulator activity and growth factor binding. Pathway-based enrichment analysis revealed “Electron Transport Chain” significantly enriched. Results were validated on genes belonging to “Electron Transport Chain” pathway, using quantitative RT-PCR. Conclusions As far as we know, this is the first systematic study in the literature monitoring transcriptional response to insulin in endothelial cells, in a time series microarray experiment. Since chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation, some of the genes identified in the present work are potential novel candidates in diabetes complications related to endothelial dysfunction.

Abstract 4388 Introduction Chronic lymphocytic leukemia (CLL) is a heterogeneous disease; ZAP-70 protein expression and IgVH mutational status have shown to be strong associated and to offer important prognostic information. Aim Our aim was to determine gene expression profiles of 46 CLL patients divided into three classes: group one (n=26) with mutated IgVH and ZAP-70-, group two (n=12) with unmutated IgVH and ZAP-70+, and group three (n=8) included CLL patients with unmutated IgVH and ZAP-70-, or mutated IgVH and ZAP-70+ respectively. Afterwards, in a second phase of the study, 16 other patients were investigated. Finally, the purpose was to define prognostic biomarkers and the biological pathways related to CLL. Patients and Methods We determined gene expression profiles using Affymetrix HG U133 Plus 2.0 in CD19+ leukemic cells. Differentially expressed genes were detected using ANOVA and t-test adapted for microarray data analysis and corrected for multiple testing using false discovery rate p-values. Subjects were clustered in groups with similar expression signature using cluster analysis (K-means, Euclidean distance). Results Statistical analysis revealed 154 differentially expressed probe-sets in the first (mutated IgVH and ZAP-70-) vs the second (unmutated IgVH and ZAP-70+) group, corresponding to 88 genes annotated in public databases. Interestingly, six genes were associated to the following biological pathways: MAPKsignaling (heat shock 70kD protein 8 HSPA8), B cell receptor signaling (ZAP-70, CKLF-like MARVEL transmembrane domain containing 3 CMTM3, dual adaptor of phosphotyrosine and 3-phosphoinositides DAPP1), Matrix Metalloproteinasis (transcription factor 20, TCF20), Apoptosis (X-linked inhibitor of apoptosis XIAP) and T cell receptor signaling (ZAP-70). In particular, ZAP-70, HSPA8, CMTM3 were significatively underexpressed while XIAP, TCF20 and DAPP1 were overexpressed in the first group of patients in comparison to the second group, respectively. Based on the expression of the 88 genes identified in the comparison between the first and the second group of patients, the 8 patients of the third class were divided in two clusters: 5 subjects were more similar to the first class, while 3 subjects appeared to be more similar to the second one. In particular, cluster analysis revealed that the 46 patients were better partitioned in two rather than in three classes, based on their expression profiles. 16 additional subjects were independently analyzed in a second phase of the project. Based only on the expression of the 88 genes previously identified, all of them were correctly classified in group one and group two. Further analysis was carried on the total of 62 subjects (n=46+16), dividing them in group A (n=17), showing deletion of 17p13 region and group B (n=45) without the deletion. Statistical analysis showed no correlation between groups A and B with respect to the previously defined group one, two and three. Moreover, no genes were identified as significantly differentially expressed in group A vs B. Conclusions In conclusion, our preliminary data revealed different gene expression signatures in B-cell chronic lymphocytic leukemia prognostic subgroups of patients, defined by IgVH mutational status and ZAP-70 expression. The functional pathways related to: MAPK signaling, B cell receptor signaling, apoptosis and T cell receptor signaling may ultimately influence CLL biology. Gene expression profiling studies are in progress on larger series of CLL patients in order to assess the association of the molecular signature, based on the identified genes and their pathways, with respect to prognostic information. No different gene expression signatures appeared considering CLL patients divided in two groups differing from the presence or the absence of deletion of 17p13 region respectively Disclosures: No relevant conflicts of interest to declare.

In order to better understand the relations between different risk factors in the predisposition to type 2 diabetes, we present a Bayesian Network analysis of a large dataset, composed of three European population studies. Our results show, together with a key role of metabolic syndrome and of glucose after 2 hours of an Oral Glucose Tolerance Test, the importance of education, measured as the number of years of study, in the predisposition to type 2 diabetes.