Differential Biological Effects of Dietary Lipids and Irradiation on the Aorta, Aortic Valve, and the Mitral Valve

peer reviewedAimsDietary cholesterol and palmitic acid are risk factors for cardiovascular diseases (CVDs) affecting the arteries and the heart valves. The ionizing radiation that is frequently used as an anticancer treatment promotes CVD. The specific pathophysiology of these distinct disease manifestations is poorly understood. We, therefore, studied the biological effects of these dietary lipids and their cardiac irradiation on the arteries and the heart valves in the rabbit models of CVD.Methods and ResultsCholesterol-enriched diet led to the thickening of the aortic wall and the aortic valve leaflets, immune cell infiltration in the aorta, mitral and aortic valves, as well as aortic valve calcification. Numerous cells expressing α-smooth muscle actin were detected in both the mitral and aortic valves. Lard-enriched diet induced massive aorta and aortic valve calcification, with no detectable immune cell infiltration. The addition of cardiac irradiation to the cholesterol diet yielded more calcification and more immune cell infiltrates in the atheroma and the aortic valve than cholesterol alone. RNA sequencing (RNAseq) analyses of aorta and heart valves revealed that a cholesterol-enriched diet mainly triggered inflammation-related biological processes in the aorta, aortic and mitral valves, which was further enhanced by cardiac irradiation. Lard-enriched diet rather affected calcification- and muscle-related processes in the aorta and aortic valve, respectively. Neutrophil count and systemic levels of platelet factor 4 and ent-8-iso-15(S)-PGF2α were identified as early biomarkers of cholesterol-induced tissue alterations, while cardiac irradiation resulted in elevated levels of circulating nucleosomes.ConclusionDietary cholesterol, palmitic acid, and cardiac irradiation combined with a cholesterol-rich diet led to the development of distinct vascular and valvular lesions and changes in the circulating biomarkers. Hence, our study highlights unprecedented specificities related to common risk factors that underlie CVD

A persistent neutrophil-associated immune signature characterizes post-COVID-19 pulmonary sequelae

Interstitial lung disease and associated fibrosis occur in a proportion of individuals who have recovered from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection through unknown mechanisms. We studied individuals with severe coronavirus disease 2019 (COVID-19) after recovery from acute illness. Individuals with evidence of interstitial lung changes at 3 to 6 months after recovery had an up-regulated neutrophil-associated immune signature including increased chemokines, proteases, and markers of neutrophil extracellular traps that were detectable in the blood. Similar pathways were enriched in the upper airway with a concomitant increase in antiviral type I interferon signaling. Interaction analysis of the peripheral phosphoproteome identified enriched kinases critical for neutrophil inflammatory pathways. Evaluation of these individuals at 12 months after recovery indicated that a subset of the individuals had not yet achieved full normalization of radiological and functional changes. These data provide insight into mechanisms driving development of pulmonary sequelae during and after COVID-19 and provide a rational basis for development of targeted approaches to prevent long-term complications

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock