The Role of Polymorphisms at the Interleukin-1, Interleukin-4, GATA-3 and Cyclooxygenase-2 Genes in Non-Surgical Periodontal Therapy

Periodontitis is a multifactorial disease. The aim of this explorative study was to investigate the role of Interleukin-(IL)-1, IL-4, GATA-3 and Cyclooxygenase-(COX)-2 polymorphisms after non-surgical periodontal therapy with adjunctive systemic antibiotics (amoxicillin/metronidazole) and subsequent maintenance in a Caucasian population. Analyses were performed using blood samples from periodontitis patients of a multi-center trial (ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00707369","term_id":"NCT00707369"}}NCT00707369=ABPARO-study). Polymorphisms were analyzed using quantitative real-time PCR. Clinical attachment levels (CAL), percentage of sites showing further attachment loss (PSAL) ≥1.3 mm, bleeding on probing (BOP) and plaque score were assessed. Exploratory statistical analysis was performed. A total of 209 samples were genotyped. Patients carrying heterozygous genotypes and single-nucleotide-polymorphisms (SNP) on the GATA-3-IVS4 +1468 gene locus showed less CAL loss than patients carrying wild type. Heterozygous genotypes and SNPs on the IL-1A-889, IL-1B +3954, IL-4-34, IL-4-590, GATA-3-IVS4 +1468 and COX-2-1195 gene loci did not influence CAL. In multivariate analysis, CAL was lower in patients carrying GATA-3 heterozygous genotypes and SNPs than those carrying wild-types. For the first time, effects of different genotypes were analyzed in periodontitis progression after periodontal therapy and during supportive treatment using systemic antibiotics demonstrating a slight association of GATA-3 gene locus with CAL. This result suggests that GATA-3 genotypes are a contributory but non-essential risk factor for periodontal disease progression.     

GANAB and N-Glycans Substrates Are Relevant in Human Physiology,Polycystic Pathology and Multiple Sclerosis: A Review

Glycans are one of the four fundamental macromolecular components of living matter, and they are highly regulated in the cell. Their functions are metabolic, structural and modulatory. In particular, ER resident N-glycans participate with the Glc₃Man₉GlcNAc₂ highly conserved sequence, in protein folding process, where the physiological balance between glycosylation/deglycosylation on the innermost glucose residue takes place, according GANAB/UGGT concentration ratio. However, under abnormal conditions, the cell adapts to the glucose availability by adopting an aerobic or anaerobic regimen of glycolysis, or to external stimuli through internal or external recognition patterns, so it responds to pathogenic noxa with unfolded protein response (UPR). UPR can affect Multiple Sclerosis (MS) and several neurological and metabolic diseases via the BiP stress sensor, resulting in ATF6, PERK and IRE1 activation. Furthermore, the abnormal GANAB expression has been observed in MS, systemic lupus erythematous, male germinal epithelium and predisposed highly replicating cells of the kidney tubules and bile ducts. The latter is the case of Polycystic Liver Disease (PCLD) and Polycystic Kidney Disease (PCKD), where genetically induced GANAB loss affects polycystin-1 (PC1) and polycystin-2 (PC2), resulting in altered protein quality control and cyst formation phenomenon. Our topics resume the role of glycans in cell physiology, highlighting the N-glycans one, as a substrate of GANAB, which is an emerging key molecule in MS and other human pathologies.     

Arabinoxylan and Pectin Metabolism in Crohn’s Disease Microbiota: An In Silico Study

Inflammatory bowel disease is a chronic disorder including ulcerative colitis and Crohn’s disease (CD). Gut dysbiosis is often associated with CD, and metagenomics allows a better understanding of the microbial communities involved. The objective of this study was to reconstruct in silico carbohydrate metabolic capabilities from metagenome-assembled genomes (MAGs) obtained from healthy and CD individuals. This computational method was developed as a mean to aid rationally designed prebiotic interventions to rebalance CD dysbiosis, with a focus on metabolism of emergent prebiotics derived from arabinoxylan and pectin. Up to 1196 and 1577 MAGs were recovered from CD and healthy people, respectively. MAGs of Akkermansia muciniphila, Barnesiella viscericola DSM 18177 and Paraprevotella xylaniphila YIT 11841 showed a wide range of unique and specific enzymes acting on arabinoxylan and pectin. These glycosidases were also found in MAGs recovered from CD patients. Interestingly, these arabinoxylan and pectin degraders are predicted to exhibit metabolic interactions with other gut microbes reduced in CD. Thus, administration of arabinoxylan and pectin may ameliorate dysbiosis in CD by promoting species with key metabolic functions, capable of cross-feeding other beneficial species. These computational methods may be of special interest for the rational design of prebiotic ingredients targeting at CD.     

Loxin Reduced the Inflammatory Response in the Liver and the Aortic Fatty Streak Formation in Mice Fed with a High-Fat Diet

Oxidized low-density lipoprotein (ox-LDL) is the most harmful form of cholesterol associated with vascular atherosclerosis and hepatic injury, mainly due to inflammatory cell infiltration and subsequent severe tissue injury. Lox-1 is the central ox-LDL receptor expressed in endothelial and immune cells, its activation regulating inflammatory cytokines and chemotactic factor secretion. Recently, a Lox-1 truncated protein isoform lacking the ox-LDL binding domain named LOXIN has been described. We have previously shown that LOXIN overexpression blocked Lox-1-mediated ox-LDL internalization in human endothelial progenitor cells in vitro. However, the functional role of LOXIN in targeting inflammation or tissue injury in vivo remains unknown. In this study, we investigate whether LOXIN modulated the expression of Lox-1 and reduced the inflammatory response in a high-fat-diet mice model. Results indicate that human LOXIN blocks Lox-1 mediated uptake of ox-LDL in H4-II-E-C3 cells. Furthermore, in vivo experiments showed that overexpression of LOXIN reduced both fatty streak lesions in the aorta and inflammation and fibrosis in the liver. These findings were associated with the down-regulation of Lox-1 in endothelial cells. Then, LOXIN prevents hepatic and aortic tissue damage in vivo associated with reduced Lox-1 expression in endothelial cells. We encourage future research to understand better the underlying molecular mechanisms and potential therapeutic use of LOXIN.     

Technical Validation and Clinical Implications of Ultrasensitive PCR Approaches for EGFR-Thr790Met Mutation Detection in Pretreatment FFPE Samples and in Liquid Biopsies from Non-Small Cell Lung Cancer Patients

In pretreatment tumor samples of EGFR-mutated non-small cell lung cancer (NSCLC) patients, EGFR-Thr790Met mutation has been detected in a variable prevalence by different ultrasensitive assays with controversial prognostic value. Furthermore, its detection in liquid biopsy (LB) samples remains challenging, being hampered by the shortage of circulating tumor DNA (ctDNA). Here, we describe the technical validation and clinical implications of a real-time PCR with peptide nucleic acid (PNA-Clamp) and digital droplet PCR (ddPCR) for EGFR-Thr790Met detection in diagnosis FFPE samples and in LB. Limit of blank (LOB) and limit of detection (LOD) were established by analyzing negative and low variant allele frequency (VAF) FFPE and LB specimens. In a cohort of 78 FFPE samples, both techniques showed an overall agreement (OA) of 94.20%. EGFR-Thr790Met was detected in 26.47% of cases and was associated with better progression-free survival (PFS) (16.83 ± 7.76 vs. 11.47 ± 1.83 months; p = 0.047). In LB, ddPCR was implemented in routine diagnostics under UNE-EN ISO 15189:2013 accreditation, increasing the detection rate of 32.43% by conventional methods up to 45.95%. During follow-up, ddPCR detected EGFR-Thr790Met up to 7 months before radiological progression. Extensively validated ultrasensitive assays might decipher the utility of pretreatment EGFR-Thr790Met and improve its detection rate in LB studies, even anticipating radiological progression.     

Improving the Management of Endometrial Cancer Patients through the Use of Liquid Biopsy Analyses: A Case Report

Endometrial cancer (EC) is the 4th most common neoplasm of the female genital tract, with 15–20% of patients being of high risk of recurrence which leads to a significant decrease in patient survival. Current therapeutic options for patients with EC are poor, being the combined therapy of carboplatin and paclitaxel the standard of care, with limited efficacy. Therefore, new therapeutic options and better monitoring tools are needed to improve the management of the disease. In the current case report, we showcase the value of liquid biopsy analyses in a microsatellite instability EC patient with initially good prognosis that however underwent rapid progression disease within 6 months post-surgery; through the study of plasma cfDNA/ctDNA dynamics to assess the tumour evolution during treatment, as well as the study of the uterine aspirate as a valuable sample that captures the intra-tumour heterogeneity that allows a comprehensive genomic profiling of the disease to identify potential therapeutic options. Furthermore, preclinical models were generated at the time of tumour progression to assess the efficacy of the identified targeted therapies.     

Anatomical Laser Microdissection of the Ileum Reveals mtDNA Depletion Recovery in A Mitochondrial Neuro-Gastrointestinal Encephalomyopathy (MNGIE) Patient Receiving Liver Transplant

mitochondrial neuro-gastrointestinal encephalomyopathy (MNGIE) is a rare genetic disorder characterized by thymidine phosphorylase (TP) enzyme defect. The absence of TP activity induces the imbalance of mitochondrial nucleotide pool, leading to impaired mitochondrial DNA (mtDNA) replication and depletion. Since mtDNA is required to ensure oxidative phosphorylation, metabolically active tissues may not achieve sufficient energy production. The only effective life-saving approach in MNGIE has been the permanent replacement of TP via allogeneic hematopoietic stem cell or liver transplantation. However, the follow-up of transplanted patients showed that gut tissue changes do not revert and fatal complications, such as massive gastrointestinal bleeding, can occur. The purpose of this study was to clarify whether the reintroduction of TP after transplant can recover mtDNA copy number in a normal range. Using laser capture microdissection and droplet-digital-PCR, we assessed the mtDNA copy number in each layer of full-thickness ileal samples of a naive MNGIE cohort vs. controls and in a patient pre- and post-TP replacement. The treatment led to a significant recovery of gut tissue mtDNA amount, thus showing its efficacy. Our results indicate that a timely TP replacement is needed to maximize therapeutic success before irreversible degenerative tissue changes occur in MNGIE.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.