Induction of Ankrd1 in dilated cardiomyopathy correlates with the heart failure progression

Progression of idiopathic dilated cardiomyopathy (IDCM) is marked with extensive left ventricular remodeling whose clinical manifestations and molecular basis are poorly understood. We aimed to evaluate the clinical potential of titin ligands in monitoring progression of cardiac remodeling associated with end-stage IDCM. Expression patterns of 8 mechanoptotic machinery-associated titin ligands (ANKRD1, ANKRD2, TRIM63, TRIM55, NBR1, MLP, FHL2, and TCAP) were quantitated in endomyocardial biopsies from 25 patients with advanced IDCM. When comparing NYHA disease stages, elevated ANKRD1 expression levels marked transition from NYHA < IV to NYHA IV. ANKRD1 expression levels closely correlated with systolic strain depression and short E wave deceleration time, as determined by echocardiography. On molecular level, myocardial ANKRD1 and serum adiponectin correlated with low BAX/BCL-2 ratios, indicative of antiapoptotic tissue propensity observed during the worsening of heart failure. ANKRD1 is a potential marker for cardiac remodeling and disease progression in IDCM. ANKRD1 expression correlated with reduced cardiac contractility and compliance. The association of ANKRD1 with antiapoptotic response suggests its role as myocyte survival factor during late stage heart disease, warranting further studies on ANKRD1 during end-stage heart failure

Fitting the integrated Spectral Energy Distributions of Galaxies

Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time, attempting to keep up with the vastly increased volume and quality of available data. We review here the field of SED fitting, describing the modelling of ultraviolet to infrared galaxy SEDs, the creation of multiwavelength data sets, and the methods used to fit model SEDs to observed galaxy data sets. We touch upon the achievements and challenges in the major ingredients of SED fitting, with a special emphasis on describing the interplay between the quality of the available data, the quality of the available models, and the best fitting technique to use in order to obtain a realistic measurement as well as realistic uncertainties. We conclude that SED fitting can be used effectively to derive a range of physical properties of galaxies, such as redshift, stellar masses, star formation rates, dust masses, and metallicities, with care taken not to over-interpret the available data. Yet there still exist many issues such as estimating the age of the oldest stars in a galaxy, finer details ofdust properties and dust-star geometry, and the influences of poorly understood, luminous stellar types and phases. The challenge for the coming years will be to improve both the models and the observational data sets to resolve these uncertainties. The present review will be made available on an interactive, moderated web page (sedfitting.org), where the community can access and change the text. The intention is to expand the text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics & Space Scienc

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function

Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

The value of subtropical grass pastures for use as foggage on the eastern Transvaal Highveld.

The utilization of frosted herbage of Pennisetum clandestinum, Paspalum notatum, Digitaria eriantha, Cynodon sp. and Chloris gayana by Merino wethers during the winter confirmed the potential of this practice as an alternative winter feeding strategy under Highveld conditions. P. clandestinum and P. notatum provided good quality foggage with average daily gains of 60-80 g sheep -1 being recorded. D. eriantha also provided good quality foggage when stem production was minimized. C. gayana gave good livestock performance, but did not persist under Highveld conditions. Although Cynodon sp. proved to be a relatively poor foggage species, it provided for the maintenance of livemass. Longer rest periods in the growing season increased the available pasture, grazing capacity and livestock production ha -1, but increased the probability of poorer livestock performance. This is probably linked with a lower protein content and a higher proportion of stem material in herbage rested for a longer period.Language: EnglishKeywords: average daily gain; chloris gayana; cynodon; Cynodon species; digitaria eriantha; eastern transvaal; feeding strategy; foggage; Grass pastures; grasses; grazing capacity; herbage; livestock; Livestock performance; merino; Paspalum notatum; pasture; pastures; pennisetum clandestinum; production; south africa; subtropical grasses; transvaal highveld; utilizatio

The complete mouse nebulin gene sequence and the identification of cardiac nebulin

Nebulin is a giant (Mr 750-850kDa), modular sarcomeric protein proposed to regulate the assembly, and to specify the precise lengths of actin (thin) filaments in vertebrate skeletal muscles. Nebulin's potential role as a molecular template is based on its structural and biochemical properties. Its central ∼700kDa portion associates with actin along the entire length of the thin filament, its N-terminal region extends to thin filament pointed ends, and ∼80kDa of its C-terminal region integrates within the Z-line lattice. Here, we determined the exon/intron organization of the entire mouse nebulin gene, which contains 165 exons in a 202kb segment. We identified 16 novel exons, 15 of which encode nebulin-repeat motifs (12 from its central region and 3 from its Z-line region). One novel exon shares high sequence homology to the 20 residue repeats of the tight-junction protein, ZO-1. RT-PCR analyses revealed that all 16 novel exons are expressed in mouse skeletal muscle. Surprisingly, we also amplified mRNA transcripts from mouse and human heart cDNA using primers designed along the entire length of nebulin. The expression of cardiac-specific nebulin transcripts was confirmed by in situ hybridization in fetal rat cardiomyocytes and in embryonic Xenopus laevis (frog) heart. On the protein level, antibodies specific for skeletal muscle nebulin's N and C-terminal regions stained isolated rat cardiac myofibrils at the pointed and barbed ends of thin filaments, respectively. These data indicate a conserved molecular layout of the nebulin filament systems in both cardiac and skeletal myofibrils. We propose that thin filament length regulation in cardiac and skeletal muscles may share conserved nebulin-based mechanisms, and that nebulin isoform diversity may contribute to thin filament length differences in cardiac and skeletal muscle