George Vavougios

Phenotypes of comorbidity in OSAS patients: combining categorical principal component analysis with cluster analysis

Phenotyping obstructive sleep apnea syndromes comorbidity has been attempted for the first time only recently. The aim of our study was to determine phenotypes of comorbidity in obstructive sleep apnea syndrome patients employing a data‐driven approach. Data from 1472 consecutive patient records were recovered from our hospitals database. Categorical principal component analysis and two‐step clustering were employed to detect distinct clusters in the data. Univariate comparisons between clusters included one‐way analysis of variance with Bonferroni correction and chi‐square tests. Predictors of pairwise cluster membership were determined via a binary logistic regression model. The analyses revealed six distinct clusters: A, ‘healthy, reporting sleeping related symptoms’; B, ‘mild obstructive sleep apnea syndrome without significant comorbidities’; C1: ‘moderate obstructive sleep apnea syndrome, obesity, without significant comorbidities’; C2: ‘moderate obstructive sleep apnea syndrome with severe comorbidity, obesity and the exclusive inclusion of stroke’; D1: ‘severe obstructive sleep apnea syndrome and obesity without comorbidity and a 33.8% prevalence of hypertension’; and D2: ‘severe obstructive sleep apnea syndrome with severe comorbidities, along with the highest Epworth Sleepiness Scale score and highest body mass index’. Clusters differed significantly in apnea–hypopnea index, oxygen desaturation index; arousal index; age, body mass index, minimum oxygen saturation and daytime oxygen saturation (one‐way analysis of variance P < 0.0001). Binary logistic regression indicated that older age, greater body mass index, lower daytime oxygen saturation and hypertension were associated independently with an increased risk of belonging in a comorbid cluster. Six distinct phenotypes of obstructive sleep apnea syndrome and its comorbidities were identified. Mapping the heterogeneity of the obstructive sleep apnea syndrome may help the early identification of at‐risk groups. Finally, determining predictors of comorbidity for the moderate and severe strata of these phenotypes implies a need to take these factors into account when considering obstructive sleep apnea syndrome treatment options.

Pleural effusion levels of DJ-1 are increased in elderly lung cancer patients with malignant pleural effusions

Objectives: DJ-1 is a multifunctional protein implicated in redox dependent cell fate decisions. The aim of our study was to determine the pleural fluid (PF) levels of DJ-1 in malignant pleural effusions (MPEs) secondary to lung cancer. Additionally, we opted to assess potential correlations of DJ-1 PF levels with the PF levels of superoxide dismutase-1 (SOD1) and 8-isoprostane that are known antioxidant enzymes and have been previously reported in MPEs. Methods: Forty lung cancer patients with cytological proof of MPE were enrolled in this study. The PF levels of DJ-1, SOD1, and 8-isoprostane were measured by means of enzyme-linked immunosorbent assay. Results: The median PF levels of DJ-1 were 826 ng/mL (interquartile range, IQR: 482–1010 ng/mL). DJ-1 PF levels significantly correlated with PF Cu/Zn-SOD1 and PF 8-isoprostane levels (Spearmans rho, r; r = −0.476, P = 0.002 and r = −0.264, P = 0.033, respectively), PF lactate dehydrogenase (r = −0.497, P = 0.001) and total PF cell counts (r = −0.325, P = 0.041). Finally, in patients aged over 65 the PF DJ-1 levels were significantly higher than patients aged less than 65 (875 ng/mL vs. 607 ng/mL, respectively, P = 0.037). Discussion: To our knowledge, this is the first report to determine DJ-1s levels in MPEs due to lung cancer. The negative correlations between DJ-1, SOD1, and 8-isorpostane warrant further investigation regarding the altered redox regulation associated with MPEs.

Novel candidate genes of the PARK7 interactome as mediators of apoptosis and acetylation in multiple sclerosis: An in silico analysis

BACKGROUND currently only 4 studies have explored the potential role of PARK7s dysregulation in MS pathophysiology Currently, no study has evaluated the potential role of the PARK7 interactome in MS. OBJECTIVE The aim of our study was to assess the differential expression of PARK7 mRNA in peripheral blood mononuclears (PBMCs) donated from MS versus healthy patients using data mining techniques. METHODS The PARK7 interactome data from the GDS3920 profile were scrutinized for differentially expressed genes (DEGs); Gene Enrichment Analysis (GEA) was used to detect significantly enriched biological functions. RESULTS 27 differentially expressed genes in the MS dataset were detected; 12 of these (NDUFA4, UBA2, TDP2, NPM1, NDUFS3, SUMO1, PIAS2, KIAA0101, RBBP4, NONO, RBBP7 AND HSPA4) are reported for the first time in MS. Stepwise Linear Discriminant Function Analysis constructed a predictive model (Wilks λ = 0.176, χ2 = 45.204, p = 1.5275e-10) with 2 variables (TIDP2, RBBP4) that achieved 96.6% accuracy when discriminating between patients and controls. Gene Enrichment Analysis revealed that induction and regulation of programmed / intrinsic cell death represented the most salient Gene Ontology annotations. Cross-validation on systemic lupus erythematosus and ischemic stroke datasets revealed that these functions are unique to the MS dataset. CONCLUSIONS Based on our results, novel potential target genes are revealed; these differentially expressed genes regulate epigenetic and apoptotic pathways that may further elucidate underlying mechanisms of autorreactivity in MS.

THE PUTATIVE INTERPLAY BETWEEN DJ-1 / NRF2 AND DIMETHYL FUMARATE: A POTENTIALLY IMPORTANT PHARMACOLOGICAL TARGET

Recent research has outlined that Dimethyl Fumarate (DMF) functions as a gene regulator via multiple pathways, critical among which is the NRF2 cytoprotective cascade. PARK7/DJ-1 is a multifunctional protein that acts as a redox sensor and effector of multiple cytoprotective pathways, including NRF2. Specifically, it prevents the association of NRF2 with its inhibitor KEAP1, allowing NRF2 to enter the nucleus and mediate cytoprotective and antioxidant cascades. It is our hypothesis that while the NRF2-KEAP1 inhibitory complex is reported the main pharmacological target for DMFs NRF dependent functions, no study to date has explored the effects of DMF on DJ-1s expression, and vice-versa, the possibility of a regulatory inadequacy in the upstream, oxidant-responsive DJ-1 activator of the NRF2 cascade.

Identification of a prospective early motor progression cluster of Parkinson's disease: Data from the PPMI study

AIM The aim of our study is to phenotype PD motor progression, and to detect whether serum, cerebrospinal fluid (CSF), neuroimaging biomarkers and neuropsychological measures characterize PD motor progression phenotypes. METHODS We defined motor progression as a difference of at least one point in the Hoehn & Yahr (H&Y) scale between the baseline (Visit 0, V0), 12 months (Visit 04, V04) and 36 months (Visit 08, V08) milestones of the Progression Markers Initiative (PPMI) study. H&Y progression events were recorded at each milestone in order to be used as cluster analysis variables, in order to produce progression phenotypes. Subsequently, cross-cluster comparisons prior to and following (pairwise) propensity score matching were performed in order to assess phenotype - defining characteristics. RESULTS Four progression clusters where identified: SPPD: Secondarily Progressive PD, H&Y progression between V04 and V08; EPPD: Early Progressive PD. H&Y progression between V0 and V04; NPPD: Non Progressive PD, no H&Y progression; MIPD: Minimally Improving PD, i.e. Minimal H&Y improvement H&Y progression between V04 and V08;. Independent Samples Mann Whitney U tests determined CSF aSyn (p = 0.006, adj p-value = 0.036. I) and Semantic Animal fluency T-score (SFT, p = 0.003, adjusted p-value = 0.016.) as statistically significant cross-cluster characteristics. Following Propensity Score Matching, SFT, Hopkins Verbal Learning Test (Retention/Recall), Serum IGF1, CSF aSyn, DaT-SPECT binding ratios (SBRs) and the Benton Judgement of Line Orientation Test (BJLOT) were determined as statistically significant predictors of cluster differentiation (p < 0.05). DISCUSSION SFT, Serum IGF1, CSF aSyn and DaT-SPECT-derived, basal ganglia Striatal Binding Ratios warrant further investigation as possible motor progression biomarkers.