Hypertrophic Cardiomyopathy with Left Ventricular Systolic Dysfunction: Insights from the SHaRe Registry

Background: The term "end stage" has been used to describe hypertrophic cardiomyopathy (HCM) with left ventricular systolic dysfunction (LVSD), defined as occurring when left ventricular ejection fraction is <50%. The prognosis of HCM-LVSD has reportedly been poor, but because of its relative rarity, the natural history remains incompletely characterized. Methods: Data from 11 high-volume HCM specialty centers making up the international SHaRe Registry (Sarcomeric Human Cardiomyopathy Registry) were used to describe the natural history of patients with HCM-LVSD. Cox proportional hazards models were used to identify predictors of prognosis and incident development. Results: From a cohort of 6793 patients with HCM, 553 (8%) met the criteria for HCM-LVSD. Overall, 75% of patients with HCM-LVSD experienced clinically relevant events, and 35% met the composite outcome (all-cause death [n=128], cardiac transplantation [n=55], or left ventricular assist device implantation [n=9]). After recognition of HCM-LVSD, the median time to composite outcome was 8.4 years. However, there was substantial individual variation in natural history. Significant predictors of the composite outcome included the presence of multiple pathogenic/likely pathogenic sarcomeric variants (hazard ratio [HR], 5.6 [95% CI, 2.3-13.5]), atrial fibrillation (HR, 2.6 [95% CI, 1.7-3.5]), and left ventricular ejection fraction <35% (HR, 2.0 [95% CI, 1.3-2.8]). The incidence of new HCM-LVSD was ≈7.5% over 15 years. Significant predictors of developing incident HCM-LVSD included greater left ventricular cavity size (HR, 1.1 [95% CI, 1.0-1.3] and wall thickness (HR, 1.3 [95% CI, 1.1-1.4]), left ventricular ejection fraction of 50% to 60% (HR, 1.8 [95% CI, 1.2, 2.8]-2.8 [95% CI, 1.8-4.2]) at baseline evaluation, the presence of late gadolinium enhancement on cardiac magnetic resonance imaging (HR, 2.3 [95% CI, 1.0-4.9]), and the presence of a pathogenic/likely pathogenic sarcomeric variant, particularly in thin filament genes (HR, 1.5 [95% CI, 1.0-2.1] and 2.5 [95% CI, 1.2-5.1], respectively). Conclusions: HCM-LVSD affects ≈8% of patients with HCM. Although the natural history of HCM-LVSD was variable, 75% of patients experienced adverse events, including 35% experiencing a death equivalent an estimated median time of 8.4 years after developing systolic dysfunction. In addition to clinical features, genetic substrate appears to play a role in both prognosis (multiple sarcomeric variants) and the risk for incident development of HCM-LVSD (thin filament variants)

Macrophyte abundance in Waquoit Bay : effects of land-derived nitrogen loads on seasonal and multi-year biomass patterns

Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Estuaries and Coasts 31 (2008): 532-541, doi:10.1007/s12237-008-9039-6.Anthropogenic inputs of nutrients to coastal waters have rapidly restructured coastal ecosystems. To examine the response of macrophyte communities to land-derived nitrogen loading, we measured macrophyte biomass monthly for six years in three estuaries subject to different nitrogen loads owing to different land uses on the watersheds. The set of estuaries sampled had nitrogen loads over the broad range of 12 to 601 kg N ha-1 y-1. Macrophyte biomass increased as nitrogen loads increased, but the response of individual taxa varied. Specifically, biomass of Cladophora vagabunda and Gracilaria tikvahiae increased significantly as nitrogen loads increased. The biomass of other macroalgal taxa tended to decrease with increasing load, and the relative proportion of these taxa to total macrophyte biomass also decreased. The seagrass, Zostera marina, disappeared from the higher loaded estuaries, but remained abundant in the estuary with the lowest load. Seasonal changes in macroalgal standing stock were also affected by nitrogen load, with larger fluctuations in biomass across the year and higher minimum biomass of macroalgae in the higher loaded estuaries. There were no significant changes in macrophyte biomass over the six years of this study, but there was a slight trend of increasing macroalgal biomass in the latter years. Macroalgal biomass was not related to irradiance or temperature, but Z. marina biomass was highest during the summer months when light and temperatures peak. Irradiance might, however, be a secondary limiting factor controlling macroalgal biomass in the higher loaded estuaries by restricting the depth of the macroalgal canopy. The relationship between the bloom-forming macroalgal species, C. vagabunda and G. tikvahiae, and nitrogen loads suggested a strong connection between development on watersheds and macroalgal blooms and loss of seagrasses. The influence of watershed land uses largely overwhelmed seasonal and inter-annual differences in standing stock of macrophytes in these temperate estuaries.This research was supported by the National Oceanic and Atmospheric Administration (NOAA), Cooperative Institute for Coastal and Estuarine Environmental Technologies (CICEET-UNH#99-304, NOAA NA87OR512), NOAA National Estuarine Research Reserve Graduate Research Fellowship NERRS GRF, #NA77OR0228), and an Environmental Protection Agency (EPA) STAR Fellowship for Graduate Environmental Study (U-915335-01-0) awarded to J. Hauxwell. S. Fox was supported by a NOAA NERRS GRF (#NA03NOS4200132) and an EPA STAR Graduate Research Fellowship. We also thank the Quebec-Labrador Foundation Atlantic Center for the Environment's Sounds Conservancy Program and the Boston University Ablon/Bay Committee for their awarding research funds

Track D Social Science, Human Rights and Political Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

Genotype and Lifetime Burden of Disease in Hypertrophic Cardiomyopathy: Insights from the Sarcomeric Human Cardiomyopathy Registry (SHaRe)

Background: A better understanding of the factors that contribute to heterogeneous outcomes and lifetime disease burden in hypertrophic cardiomyopathy (HCM) is critically needed to improve patient management and outcomes. The Sarcomeric Human Cardiomyopathy Registry (SHaRe) was established to provide the scale of data required to address these issues, aggregating longitudinal datasets curated by eight international HCM specialty centers.Methods: Data on 4591 HCM patients (2763 genotyped), followed for a mean of 5.4±6.9 years (24,791 patient-years; median [interquartile range] 2.9 [0.3-7.9] years) were analyzed regarding cardiac a

Distribution of biomass dynamics in relation to tree size in forests across the world

•Tree size shapes forest carbon dynamics and determines how trees interact with their environment, including a changing climate. Here, we conduct the first global analysis of among-site differences in how aboveground biomass stocks and fluxes are distributed with tree size. •We analyzed repeat tree censuses from 25 large-scale (4–52 ha) forest plots spanning a broad climatic range over five continents to characterize how aboveground biomass, woody productivity, and woody mortality vary with tree diameter. We examined how the median, dispersion, and skewness of these size-related distributions vary with mean annual temperature and precipitation. •In warmer forests, aboveground biomass, woody productivity, and woody mortality were more broadly distributed with respect to tree size. In warmer and wetter forests, aboveground biomass and woody productivity were more right skewed, with a long tail towards large trees. Small trees (1–10 cm diameter) contributed more to productivity and mortality than to biomass, highlighting the importance of including these trees in analyses of forest dynamics. •Our findings provide an improved characterization of climate-driven forest differences in the size structure of aboveground biomass and dynamics of that biomass, as well as refined benchmarks for capturing climate influences in vegetation demographic models

GWAS Meta-Analysis of Suicide Attempt:Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values &lt;5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.</p

GWAS Meta-Analysis of Suicide Attempt:Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values &lt;5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.</p