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.

Background

The genetic background of atrial fibrillation (AF) in whites and African Americans is largely unknown. Genes in cardiovascular pathways have not been systematically investigated.

Methods and Results

We examined a panel of approximately 50,000 common single nucleotide polymorphisms (SNPs) in 2,095 cardiovascular candidate genes and AF in three cohorts with participants of European (n=18,524; 2,260 cases) or African American descent (n=3,662; 263 cases) in the National Heart Lung and Blood Institute's Candidate Gene Association Resource. Results in whites were followed up in the German Competence Network for AF (n=906, 468 cases). The top result was assessed in relation to incident ischemic stroke in the Cohorts for Heart and Aging Research in Genomic Epidemiology Stroke Consortium (n= 19,602 whites, 1544 incident strokes). SNP rs4845625 in the IL6R gene was associated with AF (relative risk (RR) C allele, 0.90; 95% confidence interval (CI), 0.85–0.95; P=0.0005) in whites, but did not reach statistical significance in African Americans (RR, 0.86; 95% CI, 0.72–1.03; P=0.09). The results were comparable in the German AF Network replication, (RR, 0.71; 95% CI, 0.57–0.89; P=0.003). No association between rs4845625 and stroke was observed in whites. The known chromosome 4 locus near PITX2 in whites also was associated with AF in African Americans (rs4611994, hazard ratio, 1.40; 95% CI, 1.16–1.69; P=0.0005).

Conclusions

In a community-based cohort meta-analysis, we identified genetic association in IL6R with AF in whites. Additionally, we demonstrated that the chromosome 4 locus known from recent genome-wide association studies in whites is associated with AF in African Americans.

Background

Burn demographics, prevention and care have changed considerably since the 1970s. The objectives were to 1) identify new and confirm previously described changes, 2) make comparisons to the American Burn Association National Burn Repository, 3) determine when the administration of fluids in excess of the Baxter formula began and to identify potential causes, and 4) model mortality over time, during a 36-year period (1974–2009) at the Harborview Burn Center in Seattle, WA, USA.

Methods and Findings

14,266 consecutive admissions were analyzed in five-year periods and many parameters compared to the National Burn Repository. Fluid resuscitation was compared in five-year periods from 1974 to 2009. Mortality was modeled with the rBaux model. Many changes are highlighted at the end of the manuscript including 1) the large increase in numbers of total and short-stay admissions, 2) the decline in numbers of large burn injuries, 3) that unadjusted case fatality declined to the mid-1980s but has changed little during the past two decades, 4) that race/ethnicity and payer status disparity exists, and 5) that the trajectory to death changed with fewer deaths occurring after seven days post-injury. Administration of fluids in excess of the Baxter formula during resuscitation of uncomplicated injuries was evident at least by the early 1990s and has continued to the present; the cause is likely multifactorial but pre-hospital fluids, prophylactic tracheal intubation and opioids may be involved.

Conclusions

1) The dramatic changes include the rise in short-stay admissions; as a result, the model of burn care practiced since the 1970s is still required but is no longer sufficient. 2) Fluid administration in excess of the Baxter formula with uncomplicated injuries began at least two decades ago. 3) Unadjusted case fatality declined to ∼6% in the mid-1980s and changed little since then. The rBaux mortality model is quite accurate.

Using ∼60,000 SNPs selected for minimal linkage disequilibrium, we perform population structure analysis of 1,374 unrelated Hispanic individuals from the Multi-Ethnic Study of Atherosclerosis (MESA), with self-identification corresponding to Central America (n = 93), Cuba (n = 50), the Dominican Republic (n = 203), Mexico (n = 708), Puerto Rico (n = 192), and South America (n = 111). By projection of principal components (PCs) of ancestry to samples from the HapMap phase III and the Human Genome Diversity Panel (HGDP), we show the first two PCs quantify the Caucasian, African, and Native American origins, while the third and fourth PCs bring out an axis that aligns with known South-to-North geographic location of HGDP Native American samples and further separates MESA Mexican versus Central/South American samples along the same axis. Using k-means clustering computed from the first four PCs, we define four subgroups of the MESA Hispanic cohort that show close agreement with self-identification, labeling the clusters as primarily Dominican/Cuban, Mexican, Central/South American, and Puerto Rican. To demonstrate our recommendations for genetic analysis in the MESA Hispanic cohort, we present pooled and stratified association analysis of triglycerides for selected SNPs in the LPL and TRIB1 gene regions, previously reported in GWAS of triglycerides in Caucasians but as yet unconfirmed in Hispanic populations. We report statistically significant evidence for genetic association in both genes, and we further demonstrate the importance of considering population substructure and genetic heterogeneity in genetic association studies performed in the United States Hispanic population.

Author Summary

Using genotype data from about 60,000 distinct genetic markers, we examined population structure in 1,374 unrelated Hispanic individuals from the Multi-Ethnic Study of Atherosclerosis (MESA), with self-identification corresponding to Central America (n = 93), Cuba (n = 50), the Dominican Republic (n = 203), Mexico (n = 708), Puerto Rico (n = 192), and South America (n = 111). By comparing genetic ancestry of MESA Hispanic participants to reference samples representing worldwide diversity, we show major differences in ancestry of MESA Hispanics reflecting their Caucasian, African, and Native American origins, with finer differences corresponding to North-South geographic origins that separate MESA Mexican versus Central/South American samples. Based on our analysis, we define four subgroups of the MESA Hispanic cohort that show close agreement with the following self-identified regions of origin: Dominican/Cuban, Mexican, Central/South American, and Puerto Rican. We examine association of triglycerides with selected genetic markers, and we further demonstrate the importance of considering differences in genetic ancestry (or factors associated with genetic ancestry) when performing genetic studies of the United States Hispanic population.

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 if the higher riskis due to genetic or environmental factors. As 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=4,543) and African Americans (n=822) in the Cardiovascular Health Study (CHS) and whites (n=10,902) and Africa Americans (n=3,517) in the Atherosclerosis Risk in Communities (ARIC) Study (n=3,517). Percent European ancestry in African Americans was estimated using 1,747 ancestry informative markers (AIMs) from the Illumina custom ITMAT-Broad-CARe (IBC) array. Among African Americans without baseline AF, 120 of 804 CHS participants and 181 of 3,517 ARIC participants developed incident AF. A meta-analysis from the two studies revealed that every 10% increase in European ancestry increased the risk of AF by 13% (HR 1.13, 95% CI 1.03–1.23, p=0.007). After adjusting 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% CI 1.07–1.29, p=0.001). A second analysis using 3,192 AIMs from a genome wide Affymetrix 6.0 array in ARIC African Americans yielded similar results.

Conclusion

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.

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.

Author Summary

We performed genome-wide association studies in African American participants from four population-based cohorts to identify genetic variation that correlates with variation in PR interval duration, an electrocardiographic measure of conduction through the atria and atrioventricular node. We observed a strong signal within the gene encoding the cardiac sodium channel, SCN5A, with genome-wide significant association (p<2.5×10−8) in two cohorts and in a meta-analysis of four cohorts with African Americans. We replicated this association in two additional cohorts of African Americans and in Europeans (p = 3×10−16). The signal explains 2% of PR duration variability in African Americans and 0.5% in Europeans. In further meta-analysis, we observed genome-wide significant associations for single nucleotide polymorphisms in SCN10A, MEIS1, TBX5, corresponding to signals observed in people of European and Asian descent. We found an association of genetic ancestry and PR interval in one but not the other three cohorts. Our findings provide the first demonstration of the relevance of these loci to individuals of African ancestry and identify an association signal from SCN5A that is more strongly associated with PR interval in African Americans.

Motivation: Permutation testing is very popular for analyzing microarray data to identify differentially expressed (DE) genes; estimating false discovery rates (FDRs) is a very popular way to address the inherent multiple testing problem. However, combining these approaches may be problematic when sample sizes are unequal.

Results: With unbalanced data, permutation tests may not be suitable because they do not test the hypothesis of interest. In addition, permutation tests can be biased. Using biased P-values to estimate the FDR can produce unacceptable bias in those estimates. Results also show that the approach of pooling permutation null distributions across genes can produce invalid P-values, since even non-DE genes can have different permutation null distributions. We encourage researchers to use statistics that have been shown to reliably discriminate DE genes, but caution that associated P-values may be either invalid, or a less-effective metric for discriminating DE genes.

Contact: katiek@u.washington.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Background

As part of its broad and ambitious mission, the MicroArray Quality Control (MAQC) project reported the results of experiments using External RNA Controls (ERCs) on five microarray platforms. For most platforms, several different methods of data processing were considered. However, there was no similar consideration of different methods for processing the data from the Agilent two-color platform. While this omission is understandable given the scale of the project, it can create the false impression that there is consensus about the best way to process Agilent two-color data. It is also important to consider whether ERCs are representative of all the probes on a microarray.

Results

A comparison of different methods of processing Agilent two-color data shows substantial differences among methods for low-intensity genes. The sensitivity and specificity for detecting differentially expressed genes varies substantially for different methods. Analysis also reveals that the ERCs in the MAQC data only span the upper half of the intensity range, and therefore cannot be representative of all genes on the microarray.

Conclusion

Although ERCs demonstrate good agreement between observed and expected log-ratios on the Agilent two-color platform, such an analysis is incomplete. Simple loess normalization outperformed data processing with Agilent's Feature Extraction software for accurate identification of differentially expressed genes. Results from studies using ERCs should not be over-generalized when ERCs are not representative of all probes on a microarray.

Background

There are currently many different methods for processing and summarizing probe-level data from Affymetrix oligonucleotide arrays. It is of great interest to validate these methods and identify those that are most effective. There is no single best way to do this validation, and a variety of approaches is needed. Moreover, gene expression data are collected to answer a variety of scientific questions, and the same method may not be best for all questions. Only a handful of validation studies have been done so far, most of which rely on spike-in datasets and focus on the question of detecting differential expression. Here we seek methods that excel at estimating relative expression. We evaluate methods by identifying those that give the strongest linear association between expression measurements by array and the "gold-standard" assay.

Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) is generally considered the "gold-standard" assay for measuring gene expression by biologists and is often used to confirm findings from microarray data. Here we use qRT-PCR measurements to validate methods for the components of processing oligo array data: background adjustment, normalization, mismatch adjustment, and probeset summary. An advantage of our approach over spike-in studies is that methods are validated on a real dataset that was collected to address a scientific question.

Results

We initially identify three of six popular methods that consistently produced the best agreement between oligo array and RT-PCR data for medium- and high-intensity genes. The three methods are generally known as MAS5, gcRMA, and the dChip mismatch mode. For medium- and high-intensity genes, we identified use of data from mismatch probes (as in MAS5 and dChip mismatch) and a sequence-based method of background adjustment (as in gcRMA) as the most important factors in methods' performances. However, we found poor reliability for methods using mismatch probes for low-intensity genes, which is in agreement with previous studies.

Conclusion

We advocate use of sequence-based background adjustment in lieu of mismatch adjustment to achieve the best results across the intensity spectrum. No method of normalization or probeset summary showed any consistent advantages.

There are many options in handling microarray data that can affect study conclusions, sometimes drastically. Working with a two-color platform, this study uses ten spike-in microarray experiments to evaluate the relative effectiveness of some of these options for the experimental goal of detecting differential expression. We consider two data transformations, background subtraction and intensity normalization, as well as six different statistics for detecting differentially expressed genes. Findings support the use of an intensity-based normalization procedure and also indicate that local background subtraction can be detrimental for effectively detecting differential expression. We also verify that robust statistics outperform t-statistics in identifying differentially expressed genes when there are few replicates. Finally, we find that choice of image analysis software can also substantially influence experimental conclusions.

Background

Hypertrophic scar was first described over 100 years ago; PubMed has more than 1,000 references on the topic. Nevertheless prevention and treatment remains poor, because 1) there has been no validated animal model; 2) human scar tissue, which is impossible to obtain in a controlled manner, has been the only source for study; 3) tissues typically have been homogenized, mixing cell populations; and 4) gene-by-gene studies are incomplete.

Methodology/Principal Findings

We have assembled a system that overcomes these barriers and permits the study of genome-wide gene expression in microanatomical locations, in shallow and deep partial-thickness wounds, and pigmented and non-pigmented skin, using the Duroc(pigmented fibroproliferative)/Yorkshire(non-pigmented non-fibroproliferative) porcine model. We used this system to obtain the differential transcriptome at 1, 2, 3, 12 and 20 weeks post wounding. It is not clear when fibroproliferation begins, but it is fully developed in humans and the Duroc breed at 20 weeks. Therefore we obtained the derivative functional genomics unique to 20 weeks post wounding. We also obtained long-term, forty-six week follow-up with the model.

Conclusions/Significance

1) The scars are still thick at forty-six weeks post wounding further validating the model. 2) The differential transcriptome provides new insights into the fibroproliferative process as several genes thought fundamental to fibroproliferation are absent and others differentially expressed are newly implicated. 3) The findings in the derivative functional genomics support old concepts, which further validates the model, and suggests new avenues for reductionist exploration. In the future, these findings will be searched for directed networks likely involved in cutaneous fibroproliferation. These clues may lead to a better understanding of the systems biology of cutaneous fibroproliferation, and ultimately prevention and treatment of hypertrophic scarring.