In Silico Analysis of Differential Gene Expression in Three Common Rat Models of Diastolic Dysfunction

Collagen VIII in vascular diseases

Collagens have dual functions in the extracellular matrix (ECM), acting as both structural components and signaling molecules in matricellular communication. Although collagen molecules share a common triple helix motif, the supramolecular organization helps classify them into nearly 30 different types of collagens. Collagen type VIII is a non-fibrillar, short-chain, network-forming collagen that is expressed throughout the vasculature. Collagen VIII expression is aberrant in cardiovascular, lung, and renal disease, as well as in several different types of cancer. It plays active roles in angiogenesis, vessel injury repair, maintenance of arterial compliance, atherosclerotic plaque formation and stability modulation, fibrosis, and ECM remodeling. This review presents an overview of the characteristics of collagen VIII in vascular-related disorders, from clinical significance to laboratory studies, with a major focus on highlighting the signaling properties of collagen VIII in the vascular ECM. The expression patterns of collagen VIII in human diseases and experimental animal models highlight the protein's important yet underexplored functions. A deeper understanding of its mechanisms and downstream signaling pathways may pave the way for translational and tissue engineering applications of collagen VIII.

A new gene tree algorithm employing DNA sequences of bovine genome using discrete Fourier transformation

Within the realms of human thoughts on nature, Fourier analysis is considered as one of the greatest ideas currently put forwarded. The Fourier transform shows that any periodic function can be rewritten as the sum of sinusoidal functions. Having a Fourier transform view on real-world problems like the DNA sequence of genes, would make things intuitively simple to understand in comparison with their initial formal domain view. In this study we used discrete Fourier transform (DFT) on DNA sequences of a set of genes in the bovine genome known to govern milk production, in order to develop a new gene clustering algorithm. The implementation of this algorithm is very user-friendly and requires only simple routine mathematical operations. By transforming the configuration of gene sequences into frequency domain, we sought to elucidate important features and reveal hidden gene properties. This is biologically appealing since no information is lost via this transformation and we are therefore not reducing the number of degrees of freedom. The results from different clustering methods were integrated using evidence accumulation algorithms to provide in insilico validation of our results. We propose using candidate gene sequences accompanied by other genes of biologically unknown function. These will then be assigned some degree of relevant annotation by using our proposed algorithm. Current knowledge in biological gene clustering investigation is also lacking, and so DFT-based methods will help shine a light on use of these algorithms for biological insight.

Genomic, Proteomic, and Metabolic Comparisons of Small Animal Models of Heart Failure With Preserved Ejection Fraction: A Tale of Mice, Rats, and Cats

Heart failure with preserved ejection fraction (HFpEF) remains a medical anomaly that baffles researchers and physicians alike. The overall phenotypical changes of diastolic function and left ventricular hypertrophy observed in HFpEF are definable; however, the metabolic and molecular alterations that ultimately produce these changes are not well established. Comorbidities such as obesity, hypertension, and diabetes, as well as general aging, play crucial roles in its development and progression. Various animal models have recently been developed to better understand the pathophysiological and metabolic developments in HFpEF and to illuminate novel avenues for pharmacotherapy. These models include multi‐hit rodents and feline aortic constriction animals. Recently, genomic, proteomic, and metabolomic approaches have been used to define altered signaling pathways in the heart associated with HFpEF, including those involved in inflammation, cGMP‐related, Ca²⁺ handling, mitochondrial respiration, and the unfolded protein response in endoplasmic reticulum stress. This article aims to present an overview of what has been learnt by these studies, focusing mainly on the findings in common while highlighting unresolved issues. The knowledge gained from these research models will not simply be of benefit for treating HFpEF but will undoubtedly provide new insights into the mechanisms by which the heart deals with external stresses and how the processes involved can fail.

Targeting the Metabolic-Inflammatory Circuit in Heart Failure With Preserved Ejection Fraction

PURPOSE OF REVIEW

Heart failure with preserved ejection fraction (HFpEF) is a leading cause of morbidity and mortality. The current mechanistic paradigm supports a comorbidity-driven systemic proinflammatory state that evokes microvascular and myocardial dysfunction. Crucially, diabetes and obesity are frequently prevalent in HFpEF patients; as such, we review the involvement of a metabolic-inflammatory circuit in disease pathogenesis.

RECENT FINDINGS

Experimental models of diastolic dysfunction and genuine models of HFpEF have facilitated discovery of underlying drivers of HFpEF, where metabolic derangement and systemic inflammation appear to be central components of disease pathophysiology. Despite a shared phenotype among these models, molecular signatures differ depending on type and combination of comorbidities present. Inflammation, oxidative stress, hypertension, and metabolic derangements have been positioned as therapeutic targets to suppress the metabolic-inflammatory circuit in HFpEF. However, the stratification of unique patient phenogroups within the collective HFpEF subgroup argues for specific interventions for distinct phenogroups.

Cardiac Microvascular Endothelial Cells in Pressure Overload-Induced Heart Disease

BACKGROUND

Chronic pressure overload predisposes to heart failure, but the pathogenic role of microvascular endothelial cells (MiVEC) remains unknown. We characterized transcriptional, metabolic, and functional adaptation of cardiac MiVEC to pressure overload in mice and patients with aortic stenosis (AS).

METHODS

In Tie2-Gfp mice subjected to transverse aortic constriction or sham surgery, we performed RNA sequencing of isolated cardiac Gfp⁺-MiVEC and validated the signature in freshly isolated MiVEC from left ventricle outflow tract and right atrium of patients with AS. We next compared their angiogenic and metabolic profiles and finally correlated molecular and pathological signatures with clinical phenotypes of 42 patients with AS (50% women).

RESULTS

In mice, transverse aortic constriction induced progressive systolic dysfunction, fibrosis, and reduced microvascular density. After 10 weeks, 25 genes predominantly involved in matrix-regulation were >2-fold upregulated in isolated MiVEC. Increased transcript levels of Cartilage Intermediate Layer Protein (Cilp), Thrombospondin-4, Adamtsl-2, and Collagen1a1 were confirmed by quantitative reverse transcription polymerase chain reaction and recapitulated in left ventricle outflow tract-derived MiVEC of AS (P<0.05 versus right atrium-MiVEC). Fatty acid oxidation increased >2-fold in left ventricle outflow tract-MiVEC, proline content by 130% (median, IQR, 58%-474%; P=0.008) and procollagen secretion by 85% (mean [95% CI, 16%-154%]; P<0.05 versus right atrium-MiVEC for all). The altered transcriptome in left ventricle outflow tract-MiVEC was associated with impaired 2-dimensional-vascular network formation and 3-dimensional-spheroid sprouting (P<0.05 versus right atrium-MiVEC), profibrotic ultrastructural changes, and impaired diastolic left ventricle function, capillary density and functional status, especially in female AS.

CONCLUSIONS

Pressure overload induces major transcriptional and metabolic adaptations in cardiac MiVEC resulting in excess interstitial fibrosis and impaired angiogenesis. Molecular rewiring of MiVEC is worse in women, compromises functional status, and identifies novel targets for intervention.

tRNA-Derived Small RNAs and Their Potential Roles in Cardiac Hypertrophy

Transfer RNAs (tRNAs) are abundantly expressed, small non-coding RNAs that have long been recognized as essential components of the protein translation machinery. The tRNA-derived small RNAs (tsRNAs), including tRNA halves (tiRNAs), and tRNA fragments (tRFs), were unexpectedly discovered and have been implicated in a variety of important biological functions such as cell proliferation, cell differentiation, and apoptosis. Mechanistically, tsRNAs regulate mRNA destabilization and translation, as well as retro-element reverse transcriptional and post-transcriptional processes. Emerging evidence has shown that tsRNAs are expressed in the heart, and their expression can be induced by pathological stress, such as hypertrophy. Interestingly, cardiac pathophysiological conditions, such as oxidative stress, aging, and metabolic disorders can be viewed as inducers of tsRNA biogenesis, which further highlights the potential involvement of tsRNAs in these conditions. There is increasing enthusiasm for investigating the molecular and biological functions of tsRNAs in the heart and their role in cardiovascular disease. It is anticipated that this new class of small non-coding RNAs will offer new perspectives in understanding disease mechanisms and may provide new therapeutic targets to treat cardiovascular disease.