Kathleen F. Kerr

Genetic Associations with Valvular Calcification and Aortic Stenosis

BACKGROUND Limited information is available regarding genetic contributions to valvular calcification, which is an important precursor of clinical valve disease. METHODS We determined genomewide associations with the presence of aortic-valve calcification (among 6942 participants) and mitral annular calcification (among 3795 participants), as detected by computed tomographic (CT) scanning; the study population for this analysis included persons of white European ancestry from three cohorts participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (discovery population). Findings were replicated in independent cohorts of persons with either CT-detected valvular calcification or clinical aortic stenosis. RESULTS One SNP in the lipoprotein(a) (LPA) locus (rs10455872) reached genomewide significance for the presence of aortic-valve calcification (odds ratio per allele, 2.05; P=9.0×10(-10)), a finding that was replicated in additional white European, African-American, and Hispanic-American cohorts (P<0.05 for all comparisons). Genetically determined Lp(a) levels, as predicted by LPA genotype, were also associated with aortic-valve calcification, supporting a causal role for Lp(a). In prospective analyses, LPA genotype was associated with incident aortic stenosis (hazard ratio per allele, 1.68; 95% confidence interval [CI], 1.32 to 2.15) and aortic-valve replacement (hazard ratio, 1.54; 95% CI, 1.05 to 2.27) in a large Swedish cohort; the association with incident aortic stenosis was also replicated in an independent Danish cohort. Two SNPs (rs17659543 and rs13415097) near the proinflammatory gene IL1F9 achieved genomewide significance for mitral annular calcification (P=1.5×10(-8) and P=1.8×10(-8), respectively), but the findings were not replicated consistently. CONCLUSIONS Genetic variation in the LPA locus, mediated by Lp(a) levels, is associated with aortic-valve calcification across multiple ethnic groups and with incident clinical aortic stenosis. (Funded by the National Heart, Lung, and Blood Institute and others.).

The External RNA Controls Consortium: a progress report

Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.

Net Reclassification Indices for Evaluating Risk Prediction Instruments: A Critical Review

Net reclassification indices have recently become popular statistics for measuring the prediction increment of new biomarkers. We review the various types of net reclassification indices and their correct interpretations. We evaluate the advantages and disadvantages of quantifying the prediction increment with these indices. For predefined risk categories, we relate net reclassification indices to existing measures of the prediction increment. We also consider statistical methodology for constructing confidence intervals for net reclassification indices and evaluate the merits of hypothesis testing based on such indices. We recommend that investigators using net reclassification indices should report them separately for events (cases) and nonevents (controls). When there are two risk categories, the components of net reclassification indices are the same as the changes in the true- and false-positive rates. We advocate the use of true- and false-positive rates and suggest it is more useful for investigators to retain the existing, descriptive terms. When there are three or more risk categories, we recommend against net reclassification indices because they do not adequately account for clinically important differences in shifts among risk categories. The category-free net reclassification index is a new descriptive device designed to avoid predefined risk categories. However, it experiences many of the same problems as other measures such as the area under the receiver operating characteristic curve. In addition, the category-free index can mislead investigators by overstating the incremental value of a biomarker, even in independent validation data. When investigators want to test a null hypothesis of no prediction increment, the well-established tests for coefficients in the regression model are superior to the net reclassification index. If investigators want to use net reclassification indices, confidence intervals should be calculated using bootstrap methods rather than published variance formulas. The preferred single-number summary of the prediction increment is the improvement in net benefit.

European Ancestry as a Risk Factor for Atrial Fibrillation in African Americans

Background— Despite a higher burden of standard atrial fibrillation (AF) risk factors, African Americans have a lower risk of AF than whites. It is unknown whether the higher risk is due to genetic or environmental factors. Because African Americans have varying degrees of European ancestry, we sought to test the hypothesis that European ancestry is an independent risk factor for AF. Methods and Results— We studied whites (n=4543) and African Americans (n=822) in the Cardiovascular Health Study (CHS) and whites (n=10 902) and African Americans (n=3517) in the Atherosclerosis Risk in Communities (ARIC) Study (n=3517). Percent European ancestry in African Americans was estimated with 1747 ancestry informative markers from the Illumina custom ITMAT-Broad-CARe array. Among African Americans without baseline AF, 120 of 804 CHS participants and 181 of 3517 ARIC participants developed incident AF. A meta-analysis from the 2 studies revealed that every 10% increase in European ancestry increased the risk of AF by 13% (hazard ratio, 1.13; 95% confidence interval, 1.03 to 1.23; P=0.007). After adjustment for potential confounders, European ancestry remained a predictor of incident AF in each cohort alone, with a combined estimated hazard ratio for each 10% increase in European ancestry of 1.17 (95% confidence interval, 1.07 to 1.29; P=0.001). A second analysis using 3192 ancestry informative markers from a genome-wide Affymetrix 6.0 array in ARIC African Americans yielded similar results. Conclusions— European ancestry predicted risk of incident AF. Our study suggests that investigating genetic variants contributing to differential AF risk in individuals of African versus European ancestry will be informative.

Testing for improvement in prediction model performance

Authors have proposed new methodology in recent years for evaluating the improvement in prediction performance gained by adding a new predictor, Y, to a risk model containing a set of baseline predictors, X, for a binary outcome D. We prove theoretically that null hypotheses concerning no improvement in performance are equivalent to the simple null hypothesis that Y is not a risk factor when controlling for X, H0 : P(D = 1 | X,Y ) = P(D = 1 | X). Therefore, testing for improvement in prediction performance is redundant if Y has already been shown to be a risk factor. We also investigate properties of tests through simulation studies, focusing on the change in the area under the ROC curve (AUC). An unexpected finding is that standard testing procedures that do not adjust for variability in estimated regression coefficients are extremely conservative. This may explain why the AUC is widely considered insensitive to improvements in prediction performance and suggests that the problem of insensitivity has to do with use of invalid procedures for inference rather than with the measure itself. To avoid redundant testing and use of potentially problematic methods for inference, we recommend that hypothesis testing for no improvement be limited to evaluation of Y as a risk factor, for which methods are well developed and widely available. Analyses of measures of prediction performance should focus on estimation rather than on testing for no improvement in performance.

The plant signal salicylic acid shuts down expression of the vir regulon and activates quormone-quenching genes in Agrobacterium

Agrobacterium tumefaciens is capable of transferring and integrating an oncogenic T-DNA (transferred DNA) from its tumor-inducing (Ti) plasmid into dicotyledonous plants. This transfer requires that the virulence genes (vir regulon) be induced by plant signals such as acetosyringone in an acidic environment. Salicylic acid (SA) is a key signal molecule in regulating plant defense against pathogens. However, how SA influences Agrobacterium and its interactions with plants is poorly understood. Here we show that SA can directly shut down the expression of the vir regulon. SA specifically inhibited the expression of the Agrobacterium virA/G two-component regulatory system that tightly controls the expression of the vir regulon including the repABC operon on the Ti plasmid. We provide evidence suggesting that SA attenuates the function of the VirA kinase domain. Independent of its effect on the vir regulon, SA up-regulated the attKLM operon, which functions in degrading the bacterial quormone N-acylhomoserine lactone. Plants defective in SA accumulation were more susceptible to Agrobacterium infection, whereas plants overproducing SA were relatively recalcitrant to tumor formation. Our results illustrate that SA, besides its well known function in regulating plant defense, can also interfere directly with several aspects of the Agrobacterium infection process.

Evaluating the Incremental Value of New Biomarkers With Integrated Discrimination Improvement

The integrated discrimination improvement (IDI) index is a popular tool for evaluating the capacity of a marker to predict a binary outcome of interest. Recent reports have proposed that the IDI is more sensitive than other metrics for identifying useful predictive markers. In this article, the authors use simulated data sets and theoretical analysis to investigate the statistical properties of the IDI. The authors consider the common situation in which a risk model is fitted to a data set with and without the new, candidate predictor(s). Results demonstrate that the published method of estimating the standard error of an IDI estimate tends to underestimate the error. The z test proposed in the literature for IDI-based testing of a new biomarker is not valid, because the null distribution of the test statistic is not standard normal, even in large samples. If a test for the incremental value of a marker is desired, the authors recommend the test based on the model. For investigators who find the IDI to be a useful measure, bootstrap methods may offer a reasonable option for inference when evaluating new predictors, as long as the added predictive capacity is large.

Genome-wide association studies of the PR interval in African Americans

The PR interval on the electrocardiogram reflects atrial and atrioventricular nodal conduction time. The PR interval is heritable, provides important information about arrhythmia risk, and has been suggested to differ among human races. Genome-wide association (GWA) studies have identified common genetic determinants of the PR interval in individuals of European and Asian ancestry, but there is a general paucity of GWA studies in individuals of African ancestry. We performed GWA studies in African American individuals from four cohorts (n = 6,247) to identify genetic variants associated with PR interval duration. Genotyping was performed using the Affymetrix 6.0 microarray. Imputation was performed for 2.8 million single nucleotide polymorphisms (SNPs) using combined YRI and CEU HapMap phase II panels. We observed a strong signal (rs3922844) within the gene encoding the cardiac sodium channel (SCN5A) with genome-wide significant association (p<2.5×10−8) in two of the four cohorts and in the meta-analysis. The signal explained 2% of PR interval variability in African Americans (beta  = 5.1 msec per minor allele, 95% CI  = 4.1–6.1, p = 3×10−23). This SNP was also associated with PR interval (beta = 2.4 msec per minor allele, 95% CI = 1.8–3.0, p = 3×10−16) in individuals of European ancestry (n = 14,042), but with a smaller effect size (p for heterogeneity <0.001) and variability explained (0.5%). Further meta-analysis of the four cohorts identified genome-wide significant associations with SNPs in SCN10A (rs6798015), MEIS1 (rs10865355), and TBX5 (rs7312625) that were highly correlated with SNPs identified in European and Asian GWA studies. African ancestry was associated with increased PR duration (13.3 msec, p = 0.009) in one but not the other three cohorts. Our findings demonstrate the relevance of common variants to African Americans at four loci previously associated with PR interval in European and Asian samples and identify an association signal at one of these loci that is more strongly associated with PR interval in African Americans than in Europeans.

Association of Low-Density Lipoprotein Cholesterol–Related Genetic Variants With Aortic Valve Calcium and Incident Aortic Stenosis

IMPORTANCE Plasma low-density lipoprotein cholesterol (LDL-C) has been associated with aortic stenosis in observational studies; however, randomized trials with cholesterol-lowering therapies in individuals with established valve disease have failed to demonstrate reduced disease progression. OBJECTIVE To evaluate whether genetic data are consistent with an association between LDL-C, high-density lipoprotein cholesterol (HDL-C), or triglycerides (TG) and aortic valve disease. DESIGN, SETTING, AND PARTICIPANTS Using a Mendelian randomization study design, we evaluated whether weighted genetic risk scores (GRSs), a measure of the genetic predisposition to elevations in plasma lipids, constructed using single-nucleotide polymorphisms identified in genome-wide association studies for plasma lipids, were associated with aortic valve disease. We included community-based cohorts participating in the CHARGE consortium (n = 6942), including the Framingham Heart Study (cohort inception to last follow-up: 1971-2013; n = 1295), Multi-Ethnic Study of Atherosclerosis (2000-2012; n = 2527), Age Gene/Environment Study-Reykjavik (2000-2012; n = 3120), and the Malmö Diet and Cancer Study (MDCS, 1991-2010; n = 28,461). MAIN OUTCOMES AND MEASURES Aortic valve calcium quantified by computed tomography in CHARGE and incident aortic stenosis in the MDCS. RESULTS The prevalence of aortic valve calcium across the 3 CHARGE cohorts was 32% (n = 2245). In the MDCS, over a median follow-up time of 16.1 years, aortic stenosis developed in 17 per 1000 participants (n = 473) and aortic valve replacement for aortic stenosis occurred in 7 per 1000 (n = 205). Plasma LDL-C, but not HDL-C or TG, was significantly associated with incident aortic stenosis (hazard ratio [HR] per mmol/L, 1.28; 95% CI, 1.04-1.57; P = .02; aortic stenosis incidence: 1.3% and 2.4% in lowest and highest LDL-C quartiles, respectively). The LDL-C GRS, but not HDL-C or TG GRS, was significantly associated with presence of aortic valve calcium in CHARGE (odds ratio [OR] per GRS increment, 1.38; 95% CI, 1.09-1.74; P = .007) and with incident aortic stenosis in MDCS (HR per GRS increment, 2.78; 95% CI, 1.22-6.37; P = .02; aortic stenosis incidence: 1.9% and 2.6% in lowest and highest GRS quartiles, respectively). In sensitivity analyses excluding variants weakly associated with HDL-C or TG, the LDL-C GRS remained associated with aortic valve calcium (P = .03) and aortic stenosis (P = .009). In instrumental variable analysis, LDL-C was associated with an increase in the risk of incident aortic stenosis (HR per mmol/L, 1.51; 95% CI, 1.07-2.14; P = .02). CONCLUSIONS AND RELEVANCE Genetic predisposition to elevated LDL-C was associated with presence of aortic valve calcium and incidence of aortic stenosis, providing evidence supportive of a causal association between LDL-C and aortic valve disease. Whether earlier intervention to reduce LDL-C could prevent aortic valve disease merits further investigation.

Comparative transcriptome analysis of Agrobacterium tumefaciens in response to plant signal salicylic acid, indole‐3‐acetic acid and γ‐amino butyric acid reveals signalling cross‐talk and Agrobacterium–plant co‐evolution

Agrobacterium has evolved sophisticated strategies to perceive and transduce plant‐derived cues. Recent studies have found that numerous plant signals, including salicylic acid (SA), indole‐3‐acetic acid (IAA) and γ‐amino butyric acid (GABA), profoundly affect Agrobacterium–plant interactions. Here we determine and compare the transcriptome profiles of Agrobacterium in response to these three plant signals. Collectively, the transcription of 103, 115 and 95 genes was significantly altered by SA, IAA and GABA respectively. Both distinct cellular responses and overlapping signalling pathways were elicited by these three plant signals. Interestingly, these three plant compounds function additively to shut off the Agrobacterium virulence programme and activate the quorum‐quenching machinery. Moreover, the repression of the virulence programme by SA and IAA and the inactivation of quorum‐sensing signals by SA and GABA are regulated through independent pathways. Our data indicate that these plant signals, while cross‐talk in plant signalling networks, also act as cross‐kingdom signals and play redundant roles in tailoring Agrobacterium regulatory pathways, resulting in intensive signalling cross‐talk in Agrobacterium. Our results support the notion that Agrobacterium has evolved the ability to hijack plant signals for its own benefit. The complex signalling interplay between Agrobacterium and its plant hosts reflects an exquisite co‐evolutionary balance.