Insulin resistance increases the occurrence of new cardiovascular events in patients with manifest arterial disease without known diabetes. The SMART study

<p>Abstract</p> <p>Background</p> <p>Insulin resistance is accompanied by a cluster of metabolic changes, often referred to as metabolic syndrome. Metabolic syndrome is associated with an increased cardiovascular risk in patients with manifest arterial disease. We investigated whether insulin resistance is associated with an increased risk for cardiovascular events in patients with manifest arterial disease without known diabetes and whether this can be explained by the components of the metabolic syndrome or by inflammation.</p> <p>Methods</p> <p>Prospective cohort study in 2611 patients with manifest arterial disease without known diabetes. Homeostasis model of insulin resistance (HOMA-IR) was used to quantify insulin resistance. The relation of HOMA-IR with cardiovascular events (vascular death, myocardial infarction or stroke) and all cause mortality was assessed with Cox regression analysis. In additional models adjustments were performed for the single components constituting the metabolic syndrome and for inflammation.</p> <p>Results</p> <p>HOMA-IR increases with the number of metabolic syndrome components (mean HOMA-IR ± SD in groups with 0, 1, 2, 3, 4 and 5 metabolic syndrome components: 1.4 ± 0.7; 1.8 ± 1.2; 2.4 ± 1.5; 3.1 ± 1.8; 4.0 ± 2.6; and 5.6 ± 3.6 respectively). High HOMA-IR was independently associated with an increased risk of cardiovascular events (tertile 2 vs. 1 HR 1.92; 95%CI 1.20-3.08) (tertile 3 vs.1 HR 1.78; 95%CI 1.10-2.89) and with all cause mortality (tertile 2 vs. 1 HR 1.80; 95%CI 1.04-3.10) (tertile 3 vs.1 HR 1.56; 95%CI 0.88-2.75). These relations were not influenced by the individual components of metabolic syndrome or by inflammation.</p> <p>Conclusions</p> <p>In patients with manifest arterial disease without known diabetes, insulin resistance increases with the number of metabolic syndrome components, and elevated insulin resistance increases the risk of new cardiovascular events.</p

Estimating treatment effects for individual patients based on the results of randomised clinical trials

Objectives To predict treatment effects for individual patients based on data from randomised trials, taking rosuvastatin treatment in the primary prevention of cardiovascular disease as an example, and to evaluate the net benefit of making treatment decisions for individual patients based on a predicted absolute treatment effect

Aldosterone, atherosclerosis and vascular events in patients with stable coronary artery disease

AbstractBackground and aimsPlasma aldosterone has been associated with all-cause and cardiovascular mortality in high-risk cardiovascular populations, including patients with heart failure, myocardial infarction and high-risk coronary artery disease (CAD) patients. In the present study, we evaluated the association of plasma aldosterone levels with vascular events in a large prospective cohort of stable CAD patients recruited in an outpatient setting. Moreover, we investigated the relationship between aldosterone and atherosclerotic burden.Methods and resultsBaseline plasma aldosterone levels were measured in 2699 subjects with CAD (mean age 60±10years, 82% male). During a median follow-up of 4.7years, 308 (11%) patients died, of which 203 were from a vascular cause. Vascular endpoints of myocardial infarction, ischemic stroke or vascular death occurred in 355 (13%) patients. Multivariable Cox regression analysis was performed, adjusting for multiple confounders. Aldosterone (median 96pg/mL, interquartile range 70–138pg/mL, normal range 58–362pg/mL) was independently associated with major vascular events (hazard ratio (HR) 1.56, 95% confidence interval (CI) 1.13–2.15) and vascular mortality (HR 1.95, 95% CI 1.27–3.00). By multivariable regression analysis, aldosterone was also associated with the presence of atherosclerosis in additional vascular territories (cerebrovascular disease and/or peripheral artery disease) (p=0.026).ConclusionsIn patients with stable coronary artery disease, plasma aldosterone is independently associated with the risk of major vascular events and vascular mortality and with atherosclerotic burden

Saponin-based adjuvants induce cross-presentation in dendritic cells by intracellular lipid body formation

Saponin-based adjuvants (SBAs) are being used in animal and human (cancer) vaccines, as they induce protective cellular immunity. Their adjuvant potency is a factor of inflammasome activation and enhanced antigen cross-presentation by dendritic cells (DCs), but how antigen cross-presentation is induced is not clear. Here we show that SBAs uniquely induce intracellular lipid bodies (LBs) in the CD11b+ DC subset in vitro and in vivo. Using genetic and pharmacological interference in models for vaccination and in situ tumour ablation, we demonstrate that LB induction is causally related to the saponin- dependent increase in cross-presentation and T-cell activation. These findings link adjuvant activity to LB formation, aid the application of SBAs as a cancer vaccine component, and will stimulate development of new adjuvants enhancing T-cell-mediated immunity

A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders