Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) -- estimation of adverse event risks

The SAVVY project aims to improve the analyses of adverse event (AE) data in clinical trials through the use of survival techniques appropriately dealing with varying follow-up times and competing events (CEs). Although statistical methodologies have advanced, in AE analyses often the incidence proportion, the incidence density, or a non-parametric Kaplan-Meier estimator (KME) are used, which either ignore censoring or CEs. In an empirical study including randomized clinical trials from several sponsor organisations, these potential sources of bias are investigated. The main aim is to compare the estimators that are typically used in AE analysis to the Aalen-Johansen estimator (AJE) as the gold-standard. Here, one-sample findings are reported, while a companion paper considers consequences when comparing treatment groups. Estimators are compared with descriptive statistics, graphical displays and with a random effects meta-analysis. The influence of different factors on the size of the bias is investigated in a meta-regression. Comparisons are conducted at the maximum follow-up time and at earlier evaluation time points. CEs definition does not only include death before AE but also end of follow-up for AEs due to events possibly related to the disease course or the treatment. Ten sponsor organisations provided 17 trials including 186 types of AEs. The one minus KME was on average about 1.2-fold larger than the AJE. Leading forces influencing bias were the amount of censoring and of CEs. As a consequence, the average bias using the incidence proportion was less than 5%. Assuming constant hazards using incidence densities was hardly an issue provided that CEs were accounted for. There is a need to improve the guidelines of reporting risks of AEs so that the KME and the incidence proportion are replaced by the AJE with an appropriate definition of CEs

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) -- comparison of adverse event risks in randomized controlled trials

Analyses of adverse events (AEs) are an important aspect of the evaluation of experimental therapies. The SAVVY (Survival analysis for AdVerse events with Varying follow-up times) project aims to improve the analyses of AE data in clinical trials through the use of survival techniques appropriately dealing with varying follow-up times, censoring, and competing events (CE). In an empirical study including seventeen randomized clinical trials the effect of varying follow-up times, censoring, and competing events on comparisons of two treatment arms with respect to AE risks is investigated. The comparisons of relative risks (RR) of standard probability-based estimators to the gold-standard Aalen-Johansen estimator or hazard-based estimators to an estimated hazard ratio (HR) from Cox regression are done descriptively, with graphical displays, and using a random effects meta-analysis on AE level. The influence of different factors on the size of the bias is investigated in a meta-regression. We find that for both, avoiding bias and categorization of evidence with respect to treatment effect on AE risk into categories, the choice of the estimator is key and more important than features of the underlying data such as percentage of censoring, CEs, amount of follow-up, or value of the gold-standard RR. There is an urgent need to improve the guidelines of reporting AEs so that incidence proportions are finally replaced by the Aalen-Johansen estimator - rather than by Kaplan-Meier - with appropriate definition of CEs. For RRs based on hazards, the HR based on Cox regression has better properties than the ratio of incidence densities

Hypoxia Inducible Factor-2Alpha and Prolinhydroxylase 2 Polymorphisms in Patients with Acute Respiratory Distress Syndrome (ARDS)

Hypoxia-inducible-factor-2 alpha (HIF-2 alpha) and HIF-2 degrading prolyl-hydroxylases (PHD) are key regulators of adaptive hypoxic responses i.e., in acute respiratory distress syndrome (ARDS). Specifically, functionally active genetic variants of HIF-2 alpha (single nucleotide polymorphism (SNP) [ch2:46441523(hg18)]) and PHD2 (C/T;SNP rs516651 and T/C;SNP rs480902) are associated with improved adaptation to hypoxia i.e., in high-altitude residents. However, little is known about these SNPs' prevalence in Caucasians and impact on ARDS-outcome. Thus, we tested the hypotheses that in Caucasian ARDS patients SNPs in HIF-2 alpha or PHD2 genes are (1) common, and (2) independent risk factors for 30-day mortality. After ethics-committee approval, 272 ARDS patients were prospectively included, genotyped for PHD2 (Taqman SNP Genotyping Assay) and HIF-2 alpha-polymorphism (restriction digest + agarose-gel visualization), and genotype dependent 30-day mortality was analyzed using Kaplan-Meier-plots and multivariate Cox-regression analyses. Frequencies were 99.62% for homozygous HIF-2 alpha CC-carriers (CG: 0.38%;GG: 0%), 2.3% for homozygous PHD2 SNP rs516651 TT-carriers (CT: 18.9%;CC: 78.8%), and 3.7% for homozygous PHD2 SNP rs480902 TT-carriers (CT: 43.9%;CC: 52.4%). PHD2 rs516651 TT-genotype in ARDS was independently associated with a 3.34 times greater mortality risk (OR 3.34, CI 1.09-10.22;p = 0.034) within 30-days, whereas the other SNPs had no significant impact (p = ns). The homozygous HIF-2 alpha GG-genotype was not present in our Caucasian ARDS cohort;however PHD2 SNPs exist in Caucasians, and PHD2 rs516651 TT-genotype was associated with an increased 30-day mortality suggesting a relevance for adaptive responses in ARDS

Epigenetic Silencing of the Circadian Clock Gene CRY1 is Associated with an Indolent Clinical Course in Chronic Lymphocytic Leukemia

Disruption of circadian rhythm is believed to play a critical role in cancer development. Cryptochrome 1 (CRY1) is a core component of the mammalian circadian clock and we have previously shown its deregulated expression in a subgroup of patients with chronic lymphocytic leukemia (CLL). Using real-time RT-PCR in a cohort of 76 CLL patients and 35 normal blood donors we now demonstrate that differential CRY1 mRNA expression in high-risk (HR) CD38+/immunoglobulin variable heavy chain gene (IgVH) unmutated patients as compared to low-risk (LR) CD38−/IgVH mutated patients can be attributed to down-modulation of CRY1 in LR CLL cases. Analysis of the DNA methylation profile of the CRY1 promoter in a subgroup of 57 patients revealed that CRY1 expression in LR CLL cells is silenced by aberrant promoter CpG island hypermethylation. The methylation pattern of the CRY1 promoter proved to have high prognostic impact in CLL where aberrant promoter methylation predicted a favourable outcome. CRY1 mRNA transcript levels did not change over time in the majority of patients where sequential samples were available for analysis. We also compared the CRY1 expression in CLL with other lymphoid malignancies and observed epigenetic silencing of CRY1 in a patient with B cell acute lymphoblastic leukemia (B-ALL)

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease

Genome-wide association analysis of chronic lymphocytic leukaemia, Hodgkin lymphoma and multiple myeloma identifies pleiotropic risk loci

B-cell malignancies (BCM) originate from the same cell of origin, but at different maturation stages and have distinct clinical phenotypes. Although genetic risk variants for individual BCMs have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. We explored genome-wide association studies of chronic lymphocytic leukaemia (CLL, N = 1,842), Hodgkin lymphoma (HL, N = 1,465) and multiple myeloma (MM, N = 3,790). We identified a novel pleiotropic risk locus at 3q22.2 (NCK1, rs11715604, P = 1.60 × 10−9) with opposing effects between CLL (P = 1.97 × 10−8) and HL (P = 3.31 × 10−3). Eight established non-HLA risk loci showed pleiotropic associations. Within the HLA region, Ser37 + Phe37 in HLA-DRB1 (P = 1.84 × 10−12) was associated with increased CLL and HL risk (P = 4.68 × 10−12), and reduced MM risk (P = 1.12 × 10−2), and Gly70 in HLA-DQB1 (P = 3.15 × 10−10) showed opposing effects between CLL (P = 3.52 × 10−3) and HL (P = 3.41 × 10−9). By integrating eQTL, Hi-C and ChIP-seq data, we show that the pleiotropic risk loci are enriched for B-cell regulatory elements, as well as an over-representation of binding of key B-cell transcription factors. These data identify shared biological pathways influencing the development of CLL, HL and MM. The identification of these risk loci furthers our understanding of the aetiological basis of BCMs

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57