Paraoxonase 1 L55M, Q192R and paraoxonase 2 S311C alleles in atherothrombosis

Increased oxidative stress is known to play a role in the pathogenesis of atherosclerosis, and polymorphisms in genes encoding for enzymes involved in modulation of oxidant stress, such as paraoxonases (PONs), provide a potentially powerful approach to study the risk of disease susceptibility. Aim of our study is to investigate the possible association among PONs polymorphisms, clinical and metabolic factors, and atherothrombotic events in an Italian population. We evaluated in 105 subjects, with or without atherosclerotic risk factors, the presence of PON1 L55M, PON1 Q192R, and PON2 S311C genetic variants, as well as lipid profile, the concentration of aminothiols (blood reduced glutathione, plasma total glutathione, homocysteine, cysteine, cysteinyl glycine), and malondialdehyde as markers of lipid peroxidation

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background

<p>Abstract</p> <p>Background</p> <p>Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis</p> <p>Results</p> <p>Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg.</p> <p>Conclusion</p> <p>This study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.</p

Collagen XIX Alpha 1 improves prognosis in amyotrophic lateral sclerosis

The identification of more reliable diagnostic or prognostic biomarkers in age-related neurodegenerative diseases, such as Amyotrophic Lateral Sclerosis (ALS), is urgently needed. The objective in this study was to identify more reliable prognostic biomarkers of ALS mirroring neurodegeneration that could be of help in clinical trials. A total of 268 participants from three cohorts were included in this study. The muscle and blood cohorts were analyzed in two cross-sectional studies, while the serial blood cohort was analyzed in a longitudinal study at 6-monthly intervals. Fifteen target genes and fourteen proteins involved in muscle physiology and differentiation, metabolic processes and neuromuscular junction dismantlement were studied in the three cohorts. In the muscle biopsy cohort, the risk for a higher mortality in an ALS patient that showed high Collagen type XIX, alpha 1 (COL19A1) protein levels and a fast progression of the disease was 70.5% (P < 0.05), while in the blood cohort, this risk was 20% (P < 0.01). In the serial blood cohort, the linear mixed model analysis showed a significant association between increasing COL19A1 gene levels along disease progression and a faster progression during the follow-up period of 24 months (P < 0.05). Additionally, higher COL19A1 levels and a faster progression increased 17.9% the mortality risk (P < 0.01). We provide new evidence that COL19A1 can be considered a prognostic biomarker that could help the selection of homogeneous groups of patients for upcoming clinical trial and may be pointed out as a promising therapeutic target in ALS

Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) as a model of small vessel disease: update on clinical, diagnostic, and management aspects.

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common and best known monogenic small vessel disease. Here, we review the clinical, neuroimaging, neuropathological, genetic, and therapeutic aspects based on the most relevant articles published between 1994 and 2016 and on the personal experience of the authors, all directly involved in CADASIL research and care. We conclude with some suggestions that may help in the clinical practice and management of these patients

Analysis of shared common genetic risk between amyotrophic lateral sclerosis and epilepsy

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe

Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.Peer reviewe

Ruolo biologico della lattoferrina nella mielopoiesi e in tumori della mammella

Dottorato di ricerca in biologia umana (basi cellulari e basi molecolari). 6. ciclo. A.a. 1994-95Consiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7, Rome; Biblioteca Nazionale Centrale - P.za Cavalleggeri, 1, Florence / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

A Novel Mathematical Approach to Define the Genes/SNPs Conferring Risk or Protection in Sporadic Amyotrophic Lateral Sclerosis Based on Auto Contractive Map Neural Networks and Graph Theory

Background. Complex diseases like amyotrophic lateral sclerosis (ALS) implicate phenotypic and genetic heterogeneity. Therefore, multiple genetic traits may show differential association with the disease. The Auto Contractive Map (AutoCM), belonging to the Artificial Neural Network (ANN) architecture, “spatializes” the correlation among variables by constructing a suitable embedding space where a visually transparent and cognitively natural notion such as “closeness” among variables reflects accurately their associations. Results. In this pilot case-control study single nucleotide polymorphism (SNP) in several genes has been evaluated with a novel data mining approach based on an AutoCM. We have divided the ALS dataset into two dataset: Cases and Control dataset; we have applied to each one, independently, the AutoCM algorithm. Six genetic variants were identified which differently contributed to the complexity of the system: three of the above genes/SNPs represent protective factors, APOA4, NOS3, and LPL, since their contribution to the whole complexity resulted to be as high as 0.17. On the other hand ADRB3, LIPC, and MMP3, whose hub relevancies contribution resulted to be as high as 0.13, seem to represent susceptibility factors. Conclusion. The biological information available on these six polymorphisms is consistent with possible pathogenetic pathways related to ALS

Update on Barrett’s Oesophagus

Barrett’s oesophagus (BO) is a precancerous lesion associated with the development of oesophageal adenocarcinoma (OAC). Although different types of metaplasia have been described in BO, only the presence of intestinal metaplasia with goblet cells seems to be indispensable for an accurate diagnosis. Surveillance in BO is still controversial and, to date, the endoscopic screening is recommended only for patients who have at least one risk factor for OAC in addition to chronic gastroesophageal reflux disease (GERD), including being 50 years of age, male gender, Caucasian ethnicity, hiatal hernia, increased body mass index, intra-abdominal distribution of fat, nocturnal reflux symptoms, and tobacco use. Moreover, genetic factors play an important and critical role in the development of BO. In particular, genes related to inflammation, DNA repair, and xenobiotic metabolism have been investigated. To date, relatively little is known about the mechanisms that confer susceptibility to BO carcinogenesis even though several risk factors, genetic and acquired, have been identified. Since BO is a complex disease we support the use of advanced intelligent systems to integrate all the variables involved in this complex pathology and in its progression to cancer. In this review we summarise some of the most interesting controversial topics about the diagnosis, pathogenesis, management, and treatment of BO