Putative functional genes in idiopathic dilated cardiomyopathy

Moisture content monitoring in withering leaves during black tea processing based on electronic eye and near infrared spectroscopy

Monitoring the moisture content of withering leaves in black tea manufacturing remains a difficult task because the external and internal information of withering leaves cannot be simultaneously obtained. In this study, the spectral data and the color/texture information of withering leaves were obtained using near infrared spectroscopy (NIRS) and electronic eye (E-eye), respectively, and then fused to predict the moisture content. Subsequently, the low- and middle-level fusion strategy combined with support vector regression (SVR) was applied to detect the moisture level of withering leaves. In the middle-level fusion strategy, the principal component analysis (PCA) and random frog (RF) were employed to compress the variables and select effective information, respectively. The middle-level-RF (cutoff line = 0.8) displayed the best performance because this model used fewer variables and still achieved a satisfactory result, with 0.9883 and 5.5596 for the correlation coefficient of the prediction set (R_p) and relative percent deviation (RPD), respectively. Hence, our study demonstrated that the proposed data fusion strategy could accurately predict the moisture content during the withering process.

Association between chronic periodontitis and the risk of Alzheimer's disease: combination of text mining and GEO dataset

BACKGROUND

Although chronic periodontitis has previously been reported to be linked with Alzheimer's disease (AD), the pathogenesis between the two is unclear. The purpose of this study is to analyze and screen the relevant and promising molecular markers between chronic periodontitis and Alzheimer's disease (AD).

METHODS

In this paper, we analyzed three AD expression datasets and extracted differentially expressed genes (DEGs), then intersected them with chronic periodontitis genes obtained from text mining, and finally obtained integrated DEGs. We followed that by enriching the matching the matching cell signal cascade through DAVID analysis. Moreover, the MCODE of Cytoscape software was employed to uncover the protein-protein interaction (PPI) network and the matching hub gene. Finally, we verified our data using a different independent AD cohort.

RESULTS

The chronic periodontitis gene set acquired from text abstracting was intersected with the previously obtained three AD groups, and 12 common genes were obtained. Functional enrichment assessment uncovered 12 cross-genes, which were mainly linked to cell morphogenesis involved in neuron differentiation, leading edge membrane, and receptor ligand activity. After PPI network creation, the ten hub genes linked to AD were retrieved, consisting of SPP1, THY1, CD44, ITGB1, HSPB3, CREB1, SST, UCHL1, CCL5 and BMP7. Finally, the function terms in the new independent dataset were used to verify the previous dataset, and we found 22 GO terms and one pathway, "ECM-receptor interaction pathways", in the overlapping functional terms.

CONCLUSIONS

The establishment of the above-mentioned candidate key genes, as well as the enriched signaling cascades, provides promising molecular markers for chronic periodontitis-related AD, which may help the diagnosis and treatment of AD patients in the future.

Understanding the genetics of adult-onset dilated cardiomyopathy: what a clinician needs to know

There is increasing understanding of the genetic basis to dilated cardiomyopathy and in this review, we offer a practical primer for the practising clinician. We aim to help all clinicians involved in the care of patients with dilated cardiomyopathy to understand the clinical relevance of the genetic basis of dilated cardiomyopathy, introduce key genetic concepts, explain which patients and families may benefit from genetic testing, which genetic tests are commonly performed, how to interpret genetic results, and the clinical applications of results. We conclude by reviewing areas for future research in this dynamic field.

Individualized interactomes for network-based precision medicine in hypertrophic cardiomyopathy with implications for other clinical pathophenotypes

Progress in precision medicine is limited by insufficient knowledge of transcriptomic or proteomic features in involved tissues that define pathobiological differences between patients. Here, myectomy tissue from patients with obstructive hypertrophic cardiomyopathy and heart failure is analyzed using RNA-Seq, and the results are used to develop individualized protein-protein interaction networks. From this approach, hypertrophic cardiomyopathy is distinguished from dilated cardiomyopathy based on the protein-protein interaction network pattern. Within the hypertrophic cardiomyopathy cohort, the patient-specific networks are variable in complexity, and enriched for 30 endophenotypes. The cardiac Janus kinase 2-Signal Transducer and Activator of Transcription 3-collagen 4A2 (JAK2-STAT3-COL4A2) expression profile informed by the networks was able to discriminate two hypertrophic cardiomyopathy patients with extreme fibrosis phenotypes. Patient-specific network features also associate with other important hypertrophic cardiomyopathy clinical phenotypes. These proof-of-concept findings introduce personalized protein-protein interaction networks (reticulotypes) for characterizing patient-specific pathobiology, thereby offering a direct strategy for advancing precision medicine.

New Insights on Genetic Diagnostics in Cardiomyopathy and Arrhythmia Patients Gained by Stepwise Exome Data Analysis

Inherited cardiomyopathies are characterized by clinical and genetic heterogeneity that challenge genetic diagnostics. In this study, we examined the diagnostic benefit of exome data compared to targeted gene panel analyses, and we propose new candidate genes. We performed exome sequencing in a cohort of 61 consecutive patients with a diagnosis of cardiomyopathy or primary arrhythmia, and we analyzed the data following a stepwise approach. Overall, in 64% of patients, a variant of interest (VOI) was detected. The detection rate in the main sub-cohort consisting of patients with dilated cardiomyopathy (DCM) was much higher than previously reported (25/36; 69%). The majority of VOIs were found in disease-specific panels, while a further analysis of an extended panel and exome data led to an additional diagnostic yield of 13% and 5%, respectively. Exome data analysis also detected variants in candidate genes whose functional profile suggested a probable pathogenetic role, the strongest candidate being a truncating variant in STK38. In conclusion, although the diagnostic yield of gene panels is acceptable for routine diagnostics, the genetic heterogeneity of cardiomyopathies and the presence of still-unknown causes favor exome sequencing, which enables the detection of interesting phenotype–genotype correlations, as well as the identification of novel candidate genes.

Clinical characterisation of a novel SCN5A variant associated with progressive malignant arrhythmia and dilated cardiomyopathy

INTRODUCTION

The SCN5A gene is implicated in many arrhythmogenic and cardiomyopathic processes. We identified a novel SCN5A variant in a family with significant segregation in individuals affected with progressive sinus and atrioventricular nodal disease, atrial arrhythmia, dilated cardiomyopathy, and early sudden cardiac arrest.

METHODS

A patient pedigree was created following the clinical evaluation of three affected individuals, two monozygotic twins and a paternal half-brother, which lead to the evaluation of a paternal half-sister (four siblings with the same father and three mothers) all of whom experienced varying degrees of atrial arrhythmias, conduction disease, and dilated cardiomyopathy in addition to a paternal history of unexplained death in his 50s with similar autopsy findings. The index male underwent sequencing of 58 genes associated with cardiomyopathies. Sanger sequencing was used to provide data for bases with insufficient coverage and for bases in some known regions of genomic segmental duplications. All clinically significant and novel variants were confirmed by independent Sanger sequencing.

RESULTS

All relatives tested were shown to have the same SCN5A variant of unknown significance (p. Asp197His) and the monozygotic twins shared a co-occurring NEXN (p. Glu575*). Segregation analysis demonstrates likely pathogenic trait for the SCN5A variant with an additional possible role for the NEXN variant in combination.

CONCLUSIONS

There is compelling clinical evidence suggesting that the SCN5A variant p. Asp197His may be re-classified as likely pathogenic based on the segregation analysis of our family of interest. Molecular mechanism studies are pending.