Next-generation sequencing (NGS) is getting routinely used in the diagnosis of hereditary diseases, such as human cardiomyopathies. Hence, it is of utter importance to secure high quality sequencing data, enabling the identification of disease-relevant mutations or the conclusion of neg-ative test results. During the process of sample preparation, each protocol for target enrichment library preparation has its own requirements for quality control (QC); however, there is little evi-dence on the actual impact of these guidelines on resulting data quality. In this study, we analyzed the impact of QC during the diverse library preparation steps of Agilent SureSelect XT target enrichment and Illumina sequencing. We quantified the parameters for a cohort of around 600 sam-ples, which include starting amount of DNA, amount of sheared DNA, smallest and largest frag-ment size of the starting DNA; amount of DNA after the pre-PCR, and smallest and largest fragment size of the resulting DNA;as well as the amount of the final library, the corresponding smallest and largest fragment size, and the number of detected variants. Intriguingly, there is a high tolerance for variations in all QC steps, meaning that within the boundaries proposed in the current study, a considerable variance at each step of QC can be well tolerated without compromising NGS quality.

The search for a parameter representing left ventricular relaxation from non-invasive and invasive diagnostic tools has been extensive, since heart failure (HF) with preserved ejection fraction (HF-pEF) is a global health problem. We explore here the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Fifty eight patients with idiopathic dilated cardiomyopathy have undergone thorough clinical evaluation, including cardiac magnetic resonance imaging (MRI), heart catheterization, echocardiography, and cardiac biomarker assessment. A previously-introduced framework for creating multi-scale patient-specific cardiac models has been applied on all these patients. Novel parameters, such as global stiffness factor and maximum left ventricular active stress, representing cardiac active and passive tissue properties have been computed for all patients. Invasive pressure measurements from heart catheterization were then used to evaluate ventricular relaxation using the time constant of isovolumic relaxation Tau (s). Parameters from heart catheterization and the multi-scale model have been evaluated and compared to patient clinical presentation. The model parameter global stiffness factor, representing diastolic passive tissue properties, is correlated signif-icantly across the patient population with s. This study shows that multi-modal cardiac models can successfully capture diastolic (dys) function, a prerequisite for future clinical trials on HF-pEF.