Cardiac MRI in Young Adults with Sedentary Lifestyle-Related Risks

Western society is characterized by a sedentary lifestyle combined with an unhealthy diet resulting in growing populations with overweight, high blood pressure and type 2 diabetes. In older populations, it was demonstrated that these risk factors trigger cardiac adaptation. If cardiac adaptation already occurs at younger age, these changes could potentially overlap with findings on cardiac MRI that are suggestive of cardiomyopathy, complicating diagnosis and treatment. In a prospectively recruited study cohort of 311 young adults (18-45 years old, 49% male), the impact of the aforementioned risk factors on cardiac MRI outcomes was investigated. It was shown that overweight, high blood pressure and type 2 diabetes cause alterations in wall mass, cardiac volumes and tissue characteristics. Therefore, reference values of cardiac outcomes have been reported for young risk populations to more reliably assess future MRI scans. Also, it was demonstrated that the body metric being used for indexation of body size has a significant impact. Furthermore, changes in ejection fraction were not found, whereas subtle wall motion abnormalities were present. With literature, the applicability of the tissue characteristics T2 (edema) and T2*-mapping (iron) was assessed for the differentiation of cardiac diseases, risk factors and healthy individuals. Further, it was demonstrated that aortic dimensions can be measured accurately with native imaging, thereby reducing potential health risks in especially risk populations. Lastly, a short-axis cardiac MRI contour-tracing protocol was validated which can be used to accurately assess morphology and function, and also to manually adjust automated tracings in a standardized fashion

Postmortem diagnosis of acute myocardial infarction in patients with acute respiratory failure - demographics, etiologic and pulmonary histologic analysis

OBJECTIVES: Acute respiratory failure is present in 5% of patients with acute myocardial infarction and is responsible for 20% to 30% of the fatal post-acute myocardial infarction. The role of inflammation associated with pulmonary edema as a cause of acute respiratory failure post-acute myocardial infarction remains to be determined. We aimed to describe the demographics, etiologic data and histological pulmonary findings obtained through autopsies of patients who died during the period from 1990 to 2008 due to acute respiratory failure with no diagnosis of acute myocardial infarction during life. METHODS: This study considers 4,223 autopsies of patients who died of acute respiratory failure that was not preceded by any particular diagnosis while they were alive. The diagnosis of acute myocardial infarction was given in 218 (4.63%) patients. The age, sex and major associated diseases were recorded for each patient. Pulmonary histopathology was categorized as follows: diffuse alveolar damage, pulmonary edema, alveolar hemorrhage and lymphoplasmacytic interstitial pneumonia. The odds ratio of acute myocardial infarction associated with specific histopathology was determined by logistic regression. RESULTS: In total, 147 men were included in the study. The mean age at the time of death was 64 years. Pulmonary histopathology revealed pulmonary edema as well as the presence of diffuse alveolar damage in 72.9% of patients. Bacterial bronchopneumonia was present in 11.9% of patients, systemic arterial hypertension in 10.1% and dilated cardiomyopathy in 6.9%. A multivariate analysis demonstrated a significant positive association between acute myocardial infarction with diffuse alveolar damage and pulmonary edema. CONCLUSIONS: For the first time, we demonstrated that in autopsies of patients with acute respiratory failure as the cause of death, 5% were diagnosed with acute myocardial infarction. Pulmonary histology revealed a significant inflammatory response, which has not previously been reported

A de novo germline mutation in MYH7 causes a progressive dominant myopathy in pigs

BACKGROUND: About 9% of the offspring of a clinically healthy Piétrain boar named ‘Campus’ showed a progressive postural tremor called Campus syndrome (CPS). Extensive backcross experiments suggested a dominant mode of inheritance, and the founder boar was believed to be a gonadal mosaic. A genome-scan mapped the disease-causing mutation to an 8 cM region of porcine chromosome 7 containing the MHY7 gene. Human distal myopathy type 1 (MPD1), a disease partially resembling CPS in pigs, has been associated with mutations in the MYH7 gene. RESULTS: The porcine MYH7 gene structure was predicted based on porcine reference genome sequence, porcine mRNA, and in comparison to the human ortholog. The gene structure was highly conserved with the exception of the first exon. Mutation analysis of a contiguous genomic interval of more than 22 kb spanning the complete MYH7 gene revealed an in-frame insertion within exon 30 of MYH7 (c.4320_4321insCCCGCC) which was perfectly associated with the disease phenotype and confirmed the dominant inheritance. The mutation is predicted to insert two amino acids (p.Ala1440_Ala1441insProAla) in a very highly conserved region of the myosin tail. The boar ‘Campus’ was shown to be a germline and somatic mosaic as assessed by the presence of the mutant allele in seven different organs. CONCLUSION: This study illustrates the usefulness of recently established genomic resources in pigs. We have identified a spontaneous mutation in MYH7 as the causative mutation for CPS. This paper describes the first case of a disorder caused by a naturally occurring mutation in the MYH7 gene of a non-human mammalian species. Our study confirms the previous classification as a primary myopathy and provides a defined large animal model for human MPD1. We provide evidence that the CPS mutation occurred during the early development of the boar ‘Campus’. Therefore, this study provides an example of germline mosaicism with an asymptomatic founder

Impact of atrial programmed electrical stimulation techniques on unipolar electrogram morphology

Introduction: Intra-atrial conduction abnormalities are associated with the development of atrial fibrillation (AF) and cause morphological changes of the unipolar atrial electrogram (U-AEGM). This study examined the impact of

Varied Responses to a High m.3243A>G Mutation Load and Respiratory Chain Dysfunction in Patient-Derived Cardiomyocytes

The m.3243A>G mutation in mitochondrial tRNA-Leu(UUR) is one of the most common pathogenic mitochondrial DNA mutations in humans. The clinical manifestations are highly heterogenous and the causes for the drastic clinical variability are unknown. Approximately one third of patients suffer from cardiac disease, which often increases mortality. Why only some patients develop cardiomyopathy is unknown. Here, we studied the molecular effects of a high m.3243A>G mutation load on cardiomyocyte functionality, using cells derived from induced pluripotent stem cells (iPSC-CM) of two different m.3243A>G patients, only one of them suffering from severe cardiomyopathy. While high mutation load impaired mitochondrial respiration in both patients’ iPSC-CMs, the downstream consequences varied. mtDNA mutant cells from a patient with no clinical heart disease showed increased glucose metabolism and retained cellular ATP levels, whereas cells from the cardiac disease patient showed reduced ATP levels. In this patient, the mutations also affected intracellular calcium signaling, while this was not true in the other patient’s cells. Our results reflect the clinical variability in mitochondrial disease patients and show that iPSC-CMs retain tissue specific features seen in patients

Recent Trends in Computational Research on Diseases

Recent advances in information technology have brought forth a paradigm shift in science, especially in the biology and medical fields. Statistical methodologies based on high-performance computing and big data analysis are now indispensable for the qualitative and quantitative understanding of experimental results. In fact, the last few decades have witnessed drastic improvements in high-throughput experiments in health science, for example, mass spectrometry, DNA microarray, next generation sequencing, etc. Those methods have been providing massive data involving four major branches of omics (genomics, transcriptomics, proteomics, and metabolomics). Information about amino acid sequences, protein structures, and molecular structures are fundamental data for the prediction of bioactivity of chemical compounds when screening drugs. On the other hand, cell imaging, clinical imaging, and personal healthcare devices are also providing important data concerning the human body and disease. In parallel, various methods of mathematical modelling such as machine learning have developed rapidly. All of these types of data can be utilized in computational approaches to understand disease mechanisms, diagnosis, prognosis, drug discovery, drug repositioning, disease biomarkers, driver mutations, copy number variations, disease pathways, and much more. In this Special Issue, we have published 8 excellent papers dedicated to a variety of computational problems in the biomedical field from the genomic level to the whole-person physiological level

Varied Responses to a High m.3243A>G Mutation Load and Respiratory Chain Dysfunction in Patient-Derived Cardiomyocytes

The m.3243A>G mutation in mitochondrial tRNA-Leu(UUR) is one of the most common pathogenic mitochondrial DNA mutations in humans. The clinical manifestations are highly heterogenous and the causes for the drastic clinical variability are unknown. Approximately one third of patients suffer from cardiac disease, which often increases mortality. Why only some patients develop cardiomyopathy is unknown. Here, we studied the molecular effects of a high m.3243A>G mutation load on cardiomyocyte functionality, using cells derived from induced pluripotent stem cells (iPSC-CM) of two different m.3243A>G patients, only one of them suffering from severe cardiomyopathy. While high mutation load impaired mitochondrial respiration in both patients’ iPSC-CMs, the downstream consequences varied. mtDNA mutant cells from a patient with no clinical heart disease showed increased glucose metabolism and retained cellular ATP levels, whereas cells from the cardiac disease patient showed reduced ATP levels. In this patient, the mutations also affected intracellular calcium signaling, while this was not true in the other patient’s cells. Our results reflect the clinical variability in mitochondrial disease patients and show that iPSC-CMs retain tissue specific features seen in patients