Phenotype and Clinical Outcomes of Titin Cardiomyopathy.

BACKGROUND: Improved understanding of dilated cardiomyopathy (DCM) due to titin truncation (TTNtv) may help guide patient stratification. OBJECTIVES: The purpose of this study was to establish relationships among TTNtv genotype, cardiac phenotype, and outcomes in DCM. METHODS: In this prospective, observational cohort study, DCM patients underwent clinical evaluation, late gadolinium enhancement cardiovascular magnetic resonance, TTN sequencing, and adjudicated follow-up blinded to genotype for the primary composite endpoint of cardiovascular death, and major arrhythmic and major heart failure events. RESULTS: Of 716 subjects recruited (mean age 53.5 ± 14.3 years; 469 men [65.5%]; 577 [80.6%] New York Heart Association function class I/II), 83 (11.6%) had TTNtv. Patients with TTNtv were younger at enrollment (49.0 years vs. 54.1 years; p = 0.002) and had lower indexed left ventricular mass (5.1 g/m2 reduction; padjusted = 0.03) compared with patients without TTNtv. There was no difference in biventricular ejection fraction between TTNtv+/- groups. Overall, 78 of 604 patients (12.9%) met the primary endpoint (median follow-up 3.9 years; interquartile range: 2.0 to 5.8 years), including 9 of 71 patients with TTNtv (12.7%) and 69 of 533 (12.9%) without. There was no difference in the composite primary outcome of cardiovascular death, heart failure, or arrhythmic events, for patients with or without TTNtv (hazard ratio adjusted for primary endpoint: 0.92 [95% confidence interval: 0.45 to 1.87]; p = 0.82). CONCLUSIONS: In this large, prospective, genotype-phenotype study of ambulatory DCM patients, we show that prognostic factors for all-cause DCM also predict outcome in TTNtv DCM, and that TTNtv DCM does not appear to be associated with worse medium-term prognosis

Adenosine-stress cardiac magnetic resonance imaging in suspected coronary artery disease: a net cost analysis and reimbursement implications

The health and economic implications of new imaging technologies are increasingly relevant policy issues. Cardiac magnetic resonance imaging (CMR) is currently not or not sufficiently reimbursed in a number of countries including Germany, presumably because of a limited evidence base. It is unknown, however, whether it can be effectively used to facilitate medical decision-making and reduce costs by serving as a gatekeeper to invasive coronary angiography. We investigated whether the application of CMR in patients suspected of having coronary artery disease (CAD) reduces costs by averting referrals to cardiac catheterization. We used propensity score methods to match 218 patients from a CMR registry to a previously studied cohort in which CMR was demonstrated to reliably identify patients who were low-risk for major cardiac events. Covariates over which patients were matched included comorbidity profiles, demographics, CAD-related symptoms, and CAD risk as measured by Morise scores. We determined the proportion of patients for whom cardiac catheterization was deferred based upon CMR findings. We then calculated the economic effects of practice pattern changes using data on cardiac catheterization and CMR costs. CMR reduced the utilization of cardiac catheterization by 62.4%. Based on estimated catheterization costs of € 619, the utilization of CMR as a gatekeeper reduced per-patient costs by a mean of € 90. Savings were realized until CMR costs exceeded € 386. Cost savings were greatest for patients at low-risk for CAD, as measured by baseline Morise scores, but were present for all Morise subgroups with the exception of patients at the highest risk of CAD. CMR significantly reduces the utilization of cardiac catheterization in patients suspected of having CAD. Per-patient savings range from € 323 in patients at lowest risk of CAD to € 58 in patients at high-risk but not in the highest risk stratum. Because a negative CMR evaluation has high negative predictive value, its application as a gatekeeper to cardiac catheterization should be further explored as a treatment option

Intra-observer and interobserver variability of biventricular function, volumes and mass in patients with congenital heart disease measured by CMR imaging

Cardiovascular magnetic resonance (CMR) imaging provides highly accurate measurements of biventricular volumes and mass and is frequently used in the follow-up of patients with acquired and congenital heart disease (CHD). Data on reproducibility are limited in patients with CHD, while measurements should be reproducible, since CMR imaging has a main contribution to decision making and timing of (re)interventions. The aim of this study was to assess intra-observer and interobserver variability of biventricular function, volumes and mass in a heterogeneous group of patients with CHD using CMR imaging. Thirty-five patients with CHD (7–62 years) were included in this study. A short axis set was acquired using a steady-state free precession pulse sequence. Intra-observer and interobserver variability was assessed for left ventricular (LV) and right ventricular (RV) volumes, function and mass by calculating the coefficient of variability. Intra-observer variability was between 2.9 and 6.8% and interobserver variability was between 3.9 and 10.2%. Overall, variations were smallest for biventricular end-diastolic volume and highest for biventricular end-systolic volume. Intra-observer and interobserver variability of biventricular parameters assessed by CMR imaging is good for a heterogeneous group of patients with CHD. CMR imaging is an accurate and reproducible method and should allow adequate assessment of changes in ventricular size and global ventricular function

The role of dobutamine stress cardiovascular magnetic resonance in the clinical management of patients with suspected and known coronary artery disease

BACKGROUND: Recent studies have demonstrated the consistently high diagnostic and prognostic value of dobutamine stress cardiovascular magnetic resonance (DCMR). The value of DCMR for clinical decision making still needs to be defined. Hence, the purpose of this study was to assess the utility of DCMR regarding clinical management of patients with suspected and known coronary artery disease (CAD) in a routine setting. METHODS AND RESULTS: We prospectively performed a standard DCMR examination in 1532 consecutive patients with suspected and known CAD. Patients were stratified according to the results of DCMR: DCMR-positive patients were recommended to undergo invasive coronary angiography and DCMR-negative patients received optimal medical treatment. Of 609 (40%) DCMR-positive patients coronary angiography was performed in 478 (78%) within 90 days. In 409 of these patients significant coronary stenoses ≥ 50% were present (positive predictive value 86%). Of 923 (60%) DCMR-negative patients 833 (90%) received optimal medical therapy. During a mean follow-up period of 2.1 ± 0.8 years (median: 2.1 years, interquartile range 1.5 to 2.7 years) 8 DCMR-negative patients (0.96%) sustained a cardiac event.In 131 DCMR-positive patients who did not undergo invasive angiography, 20 patients (15%) suffered cardiac events. In 90 DCMR-negative patients (10%) invasive angiography was performed within 2 years (range 0.01 to 2.0 years) with 56 patients having coronary stenoses ≥ 50%. CONCLUSION: In a routine setting DCMR proved a useful arbiter for clinical decision making and exhibited high utility for stratification and clinical management of patients with suspected and known CAD

All Our Babies Cohort Study: recruitment of a cohort to predict women at risk of preterm birth through the examination of gene expression profiles and the environment

<p>Abstract</p> <p>Background</p> <p>Preterm birth is the leading cause of perinatal morbidity and mortality. Risk factors for preterm birth include a personal or familial history of preterm delivery, ethnicity and low socioeconomic status yet the ability to predict preterm delivery before the onset of preterm labour evades clinical practice. Evidence suggests that genetics may play a role in the multi-factorial pathophysiology of preterm birth. The All Our Babies Study is an on-going community based longitudinal cohort study that was designed to establish a cohort of women to investigate how a women's genetics and environment contribute to the pathophysiology of preterm birth. Specifically this study will examine the predictive potential of maternal leukocytes for predicting preterm birth in non-labouring women through the examination of gene expression profiles and gene-environment interactions.</p> <p>Methods/Design</p> <p>Collaborations have been established between clinical lab services, the provincial health service provider and researchers to create an interdisciplinary study design for the All Our Babies Study. A birth cohort of 2000 women has been established to address this research question. Women provide informed consent for blood sample collection, linkage to medical records and complete questionnaires related to prenatal health, service utilization, social support, emotional and physical health, demographics, and breast and infant feeding. Maternal blood samples are collected in PAXgene™ RNA tubes between 18-22 and 28-32 weeks gestation for transcriptomic analyses.</p> <p>Discussion</p> <p>The All Our Babies Study is an example of how investment in clinical-academic-community partnerships can improve research efficiency and accelerate the recruitment and data collection phases of a study. Establishing these partnerships during the study design phase and maintaining these relationships through the duration of the study provides the unique opportunity to investigate the multi-causal factors of preterm birth. The overall All Our Babies Study results can potentially lead to healthier pregnancies, mothers, infants and children.</p

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Comprehensive molecular characterization of the hippo signaling pathway in cancer

Hippo signaling has been recognized as a key tumor suppressor pathway. Here, we perform a comprehensive molecular characterization of 19 Hippo core genes in 9,125 tumor samples across 33 cancer types using multidimensional “omic” data from The Cancer Genome Atlas. We identify somatic drivers among Hippo genes and the related microRNA (miRNA) regulators, and using functional genomic approaches, we experimentally characterize YAP and TAZ mutation effects and miR-590 and miR-200a regulation for TAZ. Hippo pathway activity is best characterized by a YAP/TAZ transcriptional target signature of 22 genes, which shows robust prognostic power across cancer types. Our elastic-net integrated modeling further reveals cancer-type-specific pathway regulators and associated cancer drivers. Our results highlight the importance of Hippo signaling in squamous cell cancers, characterized by frequent amplification of YAP/TAZ, high expression heterogeneity, and significant prognostic patterns. This study represents a systems-biology approach to characterizing key cancer signaling pathways in the post-genomic era