Jan A. Kors

Cohort Profile: The Study of Health in Pomerania

Henry Volzke, y Dietrich Alte,1y Carsten Oliver Schmidt, Dorte Radke, Roberto Lorbeer, Nele Friedrich, Nicole Aumann, Katharina Lau, Michael Piontek, Gabriele Born, Christoph Havemann, Till Ittermann, Sabine Schipf, Robin Haring, Sebastian E Baumeister, Henri Wallaschofski, Matthias Nauck, Stephanie Frick, Andreas Arnold, Michael Junger, Julia Mayerle, Matthias Kraft, Markus M Lerch, Marcus Dorr, Thorsten Reffelmann, Klaus Empen, Stephan B Felix, Anne Obst, Beate Koch, Sven Glaser, Ralf Ewert, Ingo Fietze, Thomas Penzel, Martina Doren, Wolfgang Rathmann, Johannes Haerting, Mario Hannemann, Jurgen Ropcke, Ulf Schminke, Clemens Jurgens, Frank Tost, Rainer Rettig, Jan A Kors, Saskia Ungerer, Katrin Hegenscheid, Jens-Peter Kuhn, Julia Kuhn, Norbert Hosten, Ralf Puls, Jorg Henke, Oliver Gloger, Alexander Teumer, Georg Homuth, Uwe Volker, Christian Schwahn, Birte Holtfreter, Ines Polzer, Thomas Kohlmann, Hans J Grabe, Dieter Rosskopf, Heyo K Kroemer, Thomas Kocher, Reiner Biffar,17,y Ulrich John20y and Wolfgang Hoffmann1y

Spatial QRS-T angle predicts cardiac death in a general population

AIMS The aim of this study was to assess the prognostic importance of the spatial QRS-T angle for fatal and non-fatal cardiac events. METHODS AND RESULTS Electrocardiograms (ECGs) were recorded in 6134 men and women aged 55 years and over from the prospective population-based Rotterdam Study. Spatial QRS-T angles were categorized as normal, borderline or abnormal. Using Coxs proportional hazards model, abnormal angles showed increased hazard ratios of cardiac death (age-and sex-adjusted hazard ratio 5.2 (95% CI 4.0-6.8)), non-fatal cardiac events (2.2 (1.5-3.1)), sudden death (5.6 (3.7-8.5)) and total mortality (2.3 (2.0-2.7)). None of the classical cardiovascular and ECG predictors provided larger hazard ratios. After adjustment for these predictors, the association of abnormal spatial QRS-T angles with all fatal study endpoints remained strong, but the association with non-fatal cardiac events disappeared. Computation of Akaikes information criterion showed that the angle contributed significantly to the prediction of all fatal endpoints by classical cardiovascular and ECG predictors. CONCLUSION The spatial QRS-T angle is a strong and independent predictor of cardiac mortality in the elderly. It is stronger than any of the classical cardiovascular risk factors and ECG risk indicators and provides additional value to them in predicting fatal cardiac events.

Data mining on electronic health record databases for signal detection in pharmacovigilance: which events to monitor?

Data mining on electronic health records (EHRs) has emerged as a promising complementary method for post‐marketing drug safety surveillance. The EU‐ADR project, funded by the European Commission, is developing techniques that allow mining of EHRs for adverse drug events across different countries in Europe. Since mining on all possible events was considered to unduly increase the number of spurious signals, we wanted to create a ranked list of high‐priority events.

Common NOS1AP Variants Are Associated With a Prolonged QTc Interval in the Rotterdam Study

Background— QT prolongation is an important risk factor for sudden cardiac death. About 35% of QT-interval variation is heritable. In a recent genome-wide association study, a common variant (rs10494366) in the nitric oxide synthase 1 adaptor protein (NOS1AP) gene was found to be associated with QT-interval variation. We tested for association of 2 NOS1AP variants with QT duration and sudden cardiac death. Methods and Results— The Rotterdam Study is a population-based, prospective cohort study of individuals ≥55 years of age. The NOS1AP variants rs10494366 T>G and rs10918594 C>G were genotyped in 6571 individuals. Heart rate–corrected QT interval (QTc) was determined with ECG analysis software on up to 3 digital ECGs per individual (total, 11108 ECGs from 5374 individuals). The association with QTc duration was estimated with repeated-measures analyses, and the association with sudden cardiac death was estimated by Cox proportional-hazards analyses. The rs10494366 G allele (36% frequency) was associated with a 3.8-ms (95% confidence interval, 3.0 to 4.6; P=7.8×10−20) increase in QTc interval duration for each additional allele copy, and the rs10918594 G allele (31% frequency) was associated with a 3.6-ms (95% confidence interval, 2.7 to 4.4; P=6.9×10−17) increase per additional allele copy. None of the inferred NOS1AP haplotypes showed a stronger effect than the individual single-nucleotide polymorphisms. There were 233 sudden cardiac deaths over 11.9 median years of follow-up. No significant association was observed with sudden cardiac death risk. Conclusions— Common variants in NOS1AP are strongly associated with QT-interval duration in an elderly population. Larger sample sizes are needed to confirm or exclude an effect on sudden cardiac death risk.

Local depolarization abnormalities are the dominant pathophysiologic mechanism for type 1 electrocardiogram in brugada syndrome a study of electrocardiograms, vectorcardiograms, and body surface potential maps during ajmaline provocation.

OBJECTIVES We sought to obtain new insights into the pathophysiologic basis of Brugada syndrome (BrS) by studying changes in various electrocardiographic depolarization and/or repolarization variables that occurred with the development of the signature type 1 BrS electrocardiogram (ECG) during ajmaline provocation testing. BACKGROUND BrS is associated with sudden cardiac death. Its pathophysiologic basis, although unresolved, is believed to reside in abnormal cardiac depolarization or abnormal repolarization. METHODS Ajmaline provocation was performed in 269 patients suspected of having BrS with simultaneous recording of ECGs, vectorcardiograms, and 62-lead body surface potential maps. RESULTS A type 1 ECG was elicited in 91 patients (BrS patients), 162 patients had a negative test result (controls), and 16 patients had an abnormal test result. Depolarization abnormalities were more prominent in BrS patients and were mapped to the right ventricle (RV) by longer right precordial filtered QRS complex durations (142 +/- 23 ms vs. 125 +/- 14 ms, p < 0.01) and right terminal conduction delay (60 +/- 11 ms vs. 53 +/- 9 ms, p < 0.01). Repolarization abnormalities remained concordant with depolarization abnormalities as indicated by steady low nondipolar content (12 +/- 8% vs. 8 +/- 4%, p = NS), lower spatial QRS-T integrals (33 +/- 12 mV.ms vs. 40 +/- 16 mV.ms, p < 0.05), similar spatial QRS-T angles (92 +/- 39 degrees vs. 87 +/- 31 degrees , p = NS), similar T(peak)-T(end) interval (143 +/- 36 ms vs. 138 +/- 25 ms, p = NS), and similar T(peak)-T(end) dispersion (47 +/- 37 ms vs. 45 +/- 27 ms, p = NS). CONCLUSIONS The type 1 BrS ECG is characterized predominantly by localized depolarization abnormalities, notably (terminal) conduction delay in the RV, as assessed with complementary noninvasive electrocardiographic techniques. We could not define a separate role for repolarization abnormalities but suggest that the typical signs of repolarization derangements seen on the ECG are secondary to these depolarization abnormalities.

A dictionary to identify small molecules and drugs in free text

MOTIVATION From the scientific community, a lot of effort has been spent on the correct identification of gene and protein names in text, while less effort has been spent on the correct identification of chemical names. Dictionary-based term identification has the power to recognize the diverse representation of chemical information in the literature and map the chemicals to their database identifiers. RESULTS We developed a dictionary for the identification of small molecules and drugs in text, combining information from UMLS, MeSH, ChEBI, DrugBank, KEGG, HMDB and ChemIDplus. Rule-based term filtering, manual check of highly frequent terms and disambiguation rules were applied. We tested the combined dictionary and the dictionaries derived from the individual resources on an annotated corpus, and conclude the following: (i) each of the different processing steps increase precision with a minor loss of recall; (ii) the overall performance of the combined dictionary is acceptable (precision 0.67, recall 0.40 (0.80 for trivial names); (iii) the combined dictionary performed better than the dictionary in the chemical recognizer OSCAR3; (iv) the performance of a dictionary based on ChemIDplus alone is comparable to the performance of the combined dictionary. AVAILABILITY The combined dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web site http://www.biosemantics.org/chemlist.

The CHEMDNER corpus of chemicals and drugs and its annotation principles

The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotated text corpus is desirable. Furthermore, large corpora permit the robust evaluation and comparison of different approaches that detect chemicals in documents. We present the CHEMDNER corpus, a collection of 10,000 PubMed abstracts that contain a total of 84,355 chemical entity mentions labeled manually by expert chemistry literature curators, following annotation guidelines specifically defined for this task. The abstracts of the CHEMDNER corpus were selected to be representative for all major chemical disciplines. Each of the chemical entity mentions was manually labeled according to its structure-associated chemical entity mention (SACEM) class: abbreviation, family, formula, identifier, multiple, systematic and trivial. The difficulty and consistency of tagging chemicals in text was measured using an agreement study between annotators, obtaining a percentage agreement of 91. For a subset of the CHEMDNER corpus (the test set of 3,000 abstracts) we provide not only the Gold Standard manual annotations, but also mentions automatically detected by the 26 teams that participated in the BioCreative IV CHEMDNER chemical mention recognition task. In addition, we release the CHEMDNER silver standard corpus of automatically extracted mentions from 17,000 randomly selected PubMed abstracts. A version of the CHEMDNER corpus in the BioC format has been generated as well. We propose a standard for required minimum information about entity annotations for the construction of domain specific corpora on chemical and drug entities. The CHEMDNER corpus and annotation guidelines are available at: http://www.biocreative.org/resources/biocreative-iv/chemdner-corpus/

Distribution of information in biomedical abstracts and full-text publications

MOTIVATION Full-text documents potentially hold more information than their abstracts, but require more resources for processing. We investigated the added value of full text over abstracts in terms of information content and occurrences of gene symbol--gene name combinations that can resolve gene-symbol ambiguity. RESULTS We analyzed a set of 3902 biomedical full-text articles. Different keyword measures indicate that information density is highest in abstracts, but that the information coverage in full texts is much greater than in abstracts. Analysis of five different standard sections of articles shows that the highest information coverage is located in the results section. Still, 30-40% of the information mentioned in each section is unique to that section. Only 30% of the gene symbols in the abstract are accompanied by their corresponding names, and a further 8% of the gene names are found in the full text. In the full text, only 18% of the gene symbols are accompanied by their gene names.

Genome-wide association analysis identifies multiple loci related to resting heart rate

Higher resting heart rate is associated with increased cardiovascular disease and mortality risk. Though heritable factors play a substantial role in population variation, little is known about specific genetic determinants. This knowledge can impact clinical care by identifying novel factors that influence pathologic heart rate states, modulate heart rate through cardiac structure and function or by improving our understanding of the physiology of heart rate regulation. To identify common genetic variants associated with heart rate, we performed a meta-analysis of 15 genome-wide association studies (GWAS), including 38,991 subjects of European ancestry, estimating the association between age-, sex- and body mass-adjusted RR interval (inverse heart rate) and approximately 2.5 million markers. Results with P < 5 × 10(-8) were considered genome-wide significant. We constructed regression models with multiple markers to assess whether results at less stringent thresholds were likely to be truly associated with RR interval. We identified six novel associations with resting heart rate at six loci: 6q22 near GJA1; 14q12 near MYH7; 12p12 near SOX5, c12orf67, BCAT1, LRMP and CASC1; 6q22 near SLC35F1, PLN and c6orf204; 7q22 near SLC12A9 and UfSp1; and 11q12 near FADS1. Associations at 6q22 400 kb away from GJA1, at 14q12 MYH6 and at 1q32 near CD34 identified in previously published GWAS were confirmed. In aggregate, these variants explain approximately 0.7% of RR interval variance. A multivariant regression model including 20 variants with P < 10(-5) increased the explained variance to 1.6%, suggesting that some loci falling short of genome-wide significance are likely truly associated. Future research is warranted to elucidate underlying mechanisms that may impact clinical care.

The meaning of the Tp-Te interval and its diagnostic value

BACKGROUND The interval between T peak (Tp) and T end (Te) has been proposed as a measure of transmural dispersion of repolarization, but experimental and clinical studies to validate Tp-Te have given conflicting results. We have investigated the meaning of Tp-Te and its diagnostic potential. METHODS We used a digital model of the left ventricular wall to simulate the effect of varying action potential durations on the timing of Tp and Te. Furthermore, we used the vectorcardiogram to explain the relationships between Tp locations in the precordial electrocardiogram leads. RESULTS Prolongation or ischemic shortening of action potentials in our model did not result in substantial Tp shifts. The phase relationships revealed by the vectorcardiogram showed that Tp-Te in the precordial leads is a derivative of T loop morphology. CONCLUSION Tp-Te is the resultant of the global distribution of the repolarization process and is a surrogate diagnostic parameter.