Jan A Kors

Publications of Jan A Kors

• The EU-ADR corpus: Annotated drugs, diseases, targets, and their relationships.

  Authors: Erik M van Mulligen, Annie Fourrier-Reglat, David Gurwitz, Mariam Molokhia, Ainhoa Nieto, Gianluca Trifiro, Jan A Kors, Laura I Furlong

  Journal of biomedical informatics. 04/2012;

  Corpora with specific entities and relationships annotated are essential to train and evaluate text-mining systems that are developed to extract specific structured information from a large corpus.Corpora with specific entities and relationships annotated are essential to train and evaluate text-mining systems that are developed to extract specific structured information from a large corpus. In this paper we describe an approach where a named-entity recognition system produces a first annotation and annotators revise this annotation using a web-based interface. The agreement figures achieved show that the inter-annotator agreement is much better than the agreement with the system provided annotations. The corpus has been annotated for drugs, disorders, genes and their inter-relationships. For each of the drug-disorder, drug-target, and target-disorder relations three experts have annotated a set of 100 abstracts. These annotated relationships will be used to train and evaluate text-mining software to capture these relationships in texts.

• Using an ensemble system to improve concept extraction from clinical records.

  Authors: Ning Kang, Zubair Afzal, Bharat Singh, Erik M van Mulligen, Jan A Kors

  Journal of biomedical informatics. 01/2012;

  Recognition of medical concepts is a basic step in information extraction from clinical records. We wished to improve on the performance of a variety of concept recognition systems by combining theirRecognition of medical concepts is a basic step in information extraction from clinical records. We wished to improve on the performance of a variety of concept recognition systems by combining their individual results. We selected two dictionary-based systems and five statistical-based systems that were trained to annotate medical problems, tests, and treatments in clinical records. Manually annotated clinical records for training and testing were made available through the 2010 i2b2/VA (Informatics for Integrating Biology and the Bedside) challenge. Results of individual systems were combined by a simple voting scheme. The statistical systems were trained on a set of 349 records. Performance (precision, recall, F-score) was assessed on a test set of 477 records, using varying voting thresholds. The combined annotation system achieved a best F-score of 82.2% (recall 81.2%, precision 83.3%) on the test set, a score that ranks third among 22 participants in the i2b2/VA concept annotation task. The ensemble system had better precision and recall than any of the individual systems, yielding an F-score that is 4.6% point higher than the best single system. Changing the voting threshold offered a simple way to obtain a system with high precision (and moderate recall) or one with high recall (and moderate precision). The ensemble-based approach is straightforward and allows the balancing of precision versus recall of the combined system. The ensemble system is freely available and can easily be extended, integrated in other systems, and retrained.

• Training text chunkers on a silver standard corpus: can silver replace gold?

  Authors: Ning Kang, Erik M van Mulligen, Jan A Kors

  BMC bioinformatics. 01/2012; 13:17.

  ABSTRACT: To train chunkers in recognizing noun phrases and verb phrases in biomedical text, an annotated corpus is required. The creation of gold standard corpora (GSCs), however, is expensive andABSTRACT: To train chunkers in recognizing noun phrases and verb phrases in biomedical text, an annotated corpus is required. The creation of gold standard corpora (GSCs), however, is expensive and time-consuming. GSCs therefore tend to be small and to focus on specific subdomains, which limits their usefulness. We investigated the use of a silver standard corpus (SSC) that is automatically generated by combining the outputs of multiple chunking systems. We explored two use scenarios: one in which chunkers are trained on an SSC in a new domain for which a GSC is not available, and one in which chunkers are trained on an available, although small GSC but supplemented with an SSC. We have tested the two scenarios using three chunkers, Lingpipe, OpenNLP, and Yamcha, and two different corpora, GENIA and PennBioIE. For the first scenario, we showed that the systems trained for noun-phrase recognition on the SSC in one domain performed 2.7-3.1 percentage points better in terms of F-score than the systems trained on the GSC in another domain, and only 0.2-0.8 percentage points less than when they were trained on a GSC in the same domain as the SSC. When the outputs of the chunkers were combined, the combined system showed little improvement when using the SSC. For the second scenario, the systems trained on a GSC supplemented with an SSC performed considerably better than systems that were trained on the GSC alone, especially when the GSC was small. For example, training the chunkers on a GSC consisting of only 10 abstracts but supplemented with an SSC yielded similar performance as training them on a GSC of 100-250 abstracts. The combined system even performed better than any of the individual chunkers trained on a GSC of 500 abstracts. We conclude that an SSC can be a viable alternative for or a supplement to a GSC when training chunkers in a biomedical domain. A combined system only shows improvement if the SSC is used to supplement a GSC. Whether the approach is applicable to other systems in a natural-language processing pipeline has to be further investigated.

• A Concept Annotation System for Clinical Records

  Authors: Ning Kang, Rogier Barendse, Zubair Afzal, Bharat Singh, Martijn J Schuemie, Erik M van Mulligen, Jan A Kors

  12/2010;

  Unstructured information comprises a valuable source of data in clinical records. For text mining in clinical records, concept extraction is the first step in finding assertions and relationships.Unstructured information comprises a valuable source of data in clinical records. For text mining in clinical records, concept extraction is the first step in finding assertions and relationships. This study presents a system developed for the annotation of medical concepts, including medical problems, tests, and treatments, mentioned in clinical records. The system combines six publicly available named entity recognition system into one framework, and uses a simple voting scheme that allows to tune precision and recall of the system to specific needs. The system provides both a web service interface and a UIMA interface which can be easily used by other systems. The system was tested in the fourth i2b2 challenge and achieved an F-score of 82.1% for the concept exact match task, a score which is among the top-ranking systems. To our knowledge, this is the first publicly available clinical record concept annotation system. Comment: in Adrian Paschke, Albert Burger, Andrea Splendiani, M. Scott Marshall, Paolo Romano: Proceedings of the 3rd International Workshop on Semantic Web Applications and Tools for the Life Sciences, Berlin,Germany, December 8-10, 2010

• Comparing and combining chunkers of biomedical text.

  Authors: Ning Kang, Erik M van Mulligen, Jan A Kors

  Journal of biomedical informatics. 11/2010; 44(2):354-60.

  Text chunking is an essential pre-processing step in information extraction systems. No comparative studies of chunking systems, including sentence splitting, tokenization and part-of-speech tagging,Text chunking is an essential pre-processing step in information extraction systems. No comparative studies of chunking systems, including sentence splitting, tokenization and part-of-speech tagging, are available for the biomedical domain. We compared the usability (ease of integration, speed, trainability) and performance of six state-of-the-art chunkers for the biomedical domain, and combined the chunker results in order to improve chunking performance. We investigated six frequently used chunkers: GATE chunker, Genia Tagger, Lingpipe, MetaMap, OpenNLP, and Yamcha. All chunkers were integrated into the Unstructured Information Management Architecture framework. The GENIA Treebank corpus was used for training and testing. Performance was assessed for noun-phrase and verb-phrase chunking. For both noun-phrase chunking and verb-phrase chunking, OpenNLP performed best (F-scores 89.7% and 95.7%, respectively), but differences with Genia Tagger and Yamcha were small. With respect to usability, Lingpipe and OpenNLP scored best. When combining the results of the chunkers by a simple voting scheme, the F-score of the combined system improved by 3.1 percentage point for noun phrases and 0.6 percentage point for verb phrases as compared to the best single chunker. Changing the voting threshold offered a simple way to obtain a system with high precision (and moderate recall) or high recall (and moderate precision). This study is the first to compare the performance of the whole chunking pipeline, and to combine different existing chunking systems. Several chunkers showed good performance, but OpenNLP scored best both in performance and usability. The combination of chunker results by a simple voting scheme can further improve performance and allows for different precision-recall settings.

• Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction.

  Authors: Nona Sotoodehnia, Aaron Isaacs, Paul I W de Bakker, Marcus Dörr, Christopher Newton-Cheh, Ilja M Nolte, Pim van der Harst, Martina Müller, Mark Eijgelsheim, Alvaro Alonso [......] Thomas J Wang, Vilmundur Gudnason, Cornelia M van Duijn, Stephan B Felix, Glenn I Fishman, Yalda Jamshidi, Bruno H Ch Stricker, Nilesh J Samani, Stefan Kääb, Dan E Arking

  Nature genetics. 11/2010; 42(12):1068-76.

  The QRS interval, from the beginning of the Q wave to the end of the S wave on an electrocardiogram, reflects ventricular depolarization and conduction time and is a risk factor for mortality, suddenThe QRS interval, from the beginning of the Q wave to the end of the S wave on an electrocardiogram, reflects ventricular depolarization and conduction time and is a risk factor for mortality, sudden death and heart failure. We performed a genome-wide association meta-analysis in 40,407 individuals of European descent from 14 studies, with further genotyping in 7,170 additional Europeans, and we identified 22 loci associated with QRS duration (P < 5 × 10(-8)). These loci map in or near genes in pathways with established roles in ventricular conduction such as sodium channels, transcription factors and calcium-handling proteins, but also point to previously unidentified biologic processes, such as kinase inhibitors and genes related to tumorigenesis. We demonstrate that SCN10A, a candidate gene at the most significantly associated locus in this study, is expressed in the mouse ventricular conduction system, and treatment with a selective SCN10A blocker prolongs QRS duration. These findings extend our current knowledge of ventricular depolarization and conduction.

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

  Authors: Mark Eijgelsheim, Christopher Newton-Cheh, Nona Sotoodehnia, Paul I W de Bakker, Martina Müller, Alanna C Morrison, Albert V Smith, Aaron Isaacs, Serena Sanna, Marcus Dörr [......] Peter P Pramstaller, Cornelia M van Duijn, Edward G Lakatta, Stephan B Felix, Vilmundur Gudnason, Arne Pfeufer, Susan R Heckbert, Bruno H Ch Stricker, Eric Boerwinkle, Christopher J O'Donnell

  Human molecular genetics. 10/2010; 19(19):3885-94.

  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 aboutHigher 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.

• Unrecognised myocardial infarction and long-term risk of heart failure in the elderly: the Rotterdam Study.

  Authors: Maarten J G Leening, Suzette E Elias-Smale, Janine F Felix, Jan A Kors, Jaap W Deckers, Albert Hofman, Bruno H Ch Stricker, Jacqueline C M Witteman

  Heart (British Cardiac Society). 09/2010; 96(18):1458-62.

  To examine the association between unrecognised myocardial infarction (MI) as detected by electrocardiography and the long-term risk of heart failure. The Rotterdam Study is a prospectiveTo examine the association between unrecognised myocardial infarction (MI) as detected by electrocardiography and the long-term risk of heart failure. The Rotterdam Study is a prospective population-based cohort study of the general population of a suburb of the city of Rotterdam, The Netherlands. At baseline 2581 men and 3724 women aged > or =55 years were classified on the basis of electrocardiography, interview and clinical data into those with recognised MI, those with ECG-based unrecognised MI and those without MI. The participants were followed-up for incident heart failure, death or end of the study period on 12 October 2006. During a median follow-up time of 13.2 years, 823 cases of heart failure occurred, of which 403 in men. Independently of cardiovascular risk factors, recognised and unrecognised MIs yielded HRs of developing heart failure in men of 2.6 (95% CI 2.0 to 3.3) and 2.1 (95% CI 1.5 to 2.9), respectively. In women, recognised MI was associated with heart failure (HR=2.8; 95% CI 1.9 to 4.1), whereas unrecognised MI was not significantly related to the risk of heart failure (HR=1.1; 95% CI 0.7 to 1.7). Unrecognised MI detected by electrocardiography yields a long-term risk of heart failure equivalent to recognised MI in men, but is not significantly related to heart failure in women. In the light of the high incidence of both unrecognised MI and heart failure in the elderly, it may be worthwhile for both doctors and patients to improve responsiveness to typical and atypical symptoms of MI.

• The spatial QRS-T angle in the Frank vectorcardiogram: accuracy of estimates derived from the 12-lead electrocardiogram.

  Authors: Charlotte A Schreurs, Annemijn M Algra, Sum-Che Man, Suzanne C Cannegieter, Ernst E van der Wall, Martin J Schalij, Jan A Kors, Cees A Swenne

  Journal of electrocardiology. 04/2010; 43(4):294-301.

  The spatial QRS-T angle (SA), a predictor of sudden cardiac death, is a vectorcardiographic variable. Gold standard vertorcardiograms (VCGs) are recorded by using the Frank electrode positions.The spatial QRS-T angle (SA), a predictor of sudden cardiac death, is a vectorcardiographic variable. Gold standard vertorcardiograms (VCGs) are recorded by using the Frank electrode positions. However, with the commonly available 12-lead ECG, VCGs must be synthesized by matrix multiplication (inverse Dower matrix/Kors matrix). Alternatively, Rautaharju proposed a method to calculate SA directly from the 12-lead ECG. Neither spatial angles computed by using the inverse Dower matrix (SA-D) nor by using the Kors matrix (SA-K) or by using Rautaharju's method (SA-R) have been validated with regard to the spatial angles as directly measured in the Frank VCG (SA-F). Our present study aimed to perform this essential validation. We analyzed SAs in 1220 simultaneously recorded 12-lead ECGs and VCGs, in all data, in SA-F-based tertiles, and after stratification according to pathology or sex. Linear regression of SA-K, SA-D, and SA-R on SA-F yielded offsets of 0.01 degree, 20.3 degrees, and 28.3 degrees and slopes of 0.96, 0.86, and 0.79, respectively. The bias of SA-K with respect to SA-F (mean +/- SD, -3.2 degrees +/- 13.9 degrees) was significantly (P < .001) smaller than the bias of both SA-D and SA-R with respect to SA-F (8.0 degrees +/- 18.6 degrees and 9.8 degrees +/- 24.6 degrees, respectively); tertile analysis showed a much more homogeneous behavior of the bias in SA-K than of both the bias in SA-D and in SA-R. In pathologic ECGs, there was no significant bias in SA-K; bias in men and women did not differ. SA-K resembled SA-F best. In general, when there is no specific reason either to synthesize VCGs with the inverse Dower matrix or to calculate the spatial QRS-T angle with Rautaharju's method, it seems prudent to use the Kors matrix.

• Cohort profile: the study of health in Pomerania.

  Authors: Henry Völzke, Dietrich Alte, Carsten Oliver Schmidt, Dörte Radke, Roberto Lorbeer, Nele Friedrich, Nicole Aumann, Katharina Lau, Michael Piontek, Gabriele Born [......] Birte Holtfreter, Ines Polzer, Thomas Kohlmann, Hans J Grabe, Dieter Rosskopf, Heyo K Kroemer, Thomas Kocher, Reiner Biffar, Ulrich John, Wolfgang Hoffmann

  International journal of epidemiology. 02/2010; 40(2):294-307.

• 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.

  Authors: Pieter G Postema, Pascal F H M van Dessel, Jan A Kors, Andre C Linnenbank, Gerard van Herpen, Henk J Ritsema van Eck, Nan van Geloven, Jacques M T de Bakker, Arthur A M Wilde, Hanno L Tan

  Journal of the American College of Cardiology. 02/2010; 55(8):789-97.

  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 thatWe 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. BrS is associated with sudden cardiac death. Its pathophysiologic basis, although unresolved, is believed to reside in abnormal cardiac depolarization or abnormal repolarization. Ajmaline provocation was performed in 269 patients suspected of having BrS with simultaneous recording of ECGs, vectorcardiograms, and 62-lead body surface potential maps. 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). 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.

• Genome-wide association study of PR interval.

  Authors: Arne Pfeufer, Charlotte van Noord, Kristin D Marciante, Dan E Arking, Martin G Larson, Albert Vernon Smith, Kirill V Tarasov, Martina Müller, Nona Sotoodehnia, Moritz F Sinner [......] Thomas Meitinger, Daniel Levy, Vilmundur Gudnason, Patrick T Ellinor, Serena Sanna, Stefan Kääb, Jacqueline C M Witteman, Alvaro Alonso, Emelia J Benjamin, Susan R Heckbert

  Nature genetics. 02/2010; 42(2):153-9.

  The electrocardiographic PR interval (or PQ interval) reflects atrial and atrioventricular nodal conduction, disturbances of which increase risk of atrial fibrillation. We report a meta-analysis ofThe electrocardiographic PR interval (or PQ interval) reflects atrial and atrioventricular nodal conduction, disturbances of which increase risk of atrial fibrillation. We report a meta-analysis of genome-wide association studies for PR interval from seven population-based European studies in the CHARGE Consortium: AGES, ARIC, CHS, FHS, KORA, Rotterdam Study, and SardiNIA (N = 28,517). We identified nine loci associated with PR interval at P < 5 x 10(-8). At the 3p22.2 locus, we observed two independent associations in voltage-gated sodium channel genes, SCN10A and SCN5A. Six of the loci were near cardiac developmental genes, including CAV1-CAV2, NKX2-5 (CSX1), SOX5, WNT11, MEIS1, and TBX5-TBX3, providing pathophysiologically interesting candidate genes. Five of the loci, SCN5A, SCN10A, NKX2-5, CAV1-CAV2, and SOX5, were also associated with atrial fibrillation (N = 5,741 cases, P < 0.0056). This suggests a role for common variation in ion channel and developmental genes in atrial and atrioventricular conduction as well as in susceptibility to atrial fibrillation.

• Finding a short and accurate decision rule in disjunctive normal form by exhaustive search.

  Authors: Peter R. Rijnbeek, Jan A. Kors

  Machine Learning. 01/2010; 80:33-62.

• Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining.

  Authors: Kristina M Hettne, Antony J Williams, Erik M van Mulligen, Jos Kleinjans, Valery Tkachenko, Jan A Kors

  Journal of cheminformatics. 01/2010; 2(1):4.

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• Association of health behaviour with heart rate variability: a population-based study.

  Authors: Alexander Kluttig, Barbara Schumann, Cees A Swenne, Jan A Kors, Oliver Kuss, Hendrik Schmidt, Karl Werdan, Johannes Haerting, Karin H Greiser

  BMC cardiovascular disorders. 01/2010; 10:58.

  Reduced heart rate variability (HRV), a non-invasive marker of autonomic dysfunction, and an unhealthy lifestyle are associated with an increased morbidity and mortality of cardiovascular diseasesReduced heart rate variability (HRV), a non-invasive marker of autonomic dysfunction, and an unhealthy lifestyle are associated with an increased morbidity and mortality of cardiovascular diseases (CVD). The autonomic dysfunction is a potential mediator of the association of behavioural risk factors with adverse health outcomes. We studied the association of HRV with behavioural risk factors in an elderly population. This analysis was based on the cross-sectional data of 1671 participants (age range, 45-83 years) of the prospective, population-based Cardiovascular Disease, Living and Ageing in Halle (CARLA) Study. Physical activity, smoking habits, alcohol consumption and dietary patterns were assessed in standardized interviews. Time and frequency domain measures of HRV were computed from 5-min segments of highly standardized 20-min electrocardiograms. Their association with behavioural risk factors was determined by linear and non-parametric regression modelling. There were only weak and inconsistent associations of higher physical activity, moderate consumption of alcohol, and non-smoking with higher time and frequency domain HRV in both sexes, and no association with dietary pattern. Results changed only marginally by excluding subjects with CVD, diabetes mellitus and use of cardioactive medication. We hypothesized that HRV is associated with behavioural factors and therefore might be a mediator of the effect of behavioural risk factors on CVD, but this hypothesis was not confirmed by our results. These findings support the interpretation that there may be no true causal association of behavioural factors with HRV.

• Rewriting and suppressing UMLS terms for improved biomedical term identification.

  Authors: Kristina M Hettne, Erik M van Mulligen, Martijn J Schuemie, Bob Ja Schijvenaars, Jan A Kors

  Journal of biomedical semantics. 01/2010; 1(1):5.

  ABSTRACT: Identification of terms is essential for biomedical text mining.. We concentrate here on the use of vocabularies for term identification, specifically the Unified Medical Language SystemABSTRACT: Identification of terms is essential for biomedical text mining.. We concentrate here on the use of vocabularies for term identification, specifically the Unified Medical Language System (UMLS). To make the UMLS more suitable for biomedical text mining we implemented and evaluated nine term rewrite and eight term suppression rules. The rules rely on UMLS properties that have been identified in previous work by others, together with an additional set of new properties discovered by our group during our work with the UMLS. Our work complements the earlier work in that we measure the impact on the number of terms identified by the different rules on a MEDLINE corpus. The number of uniquely identified terms and their frequency in MEDLINE were computed before and after applying the rules. The 50 most frequently found terms together with a sample of 100 randomly selected terms were evaluated for every rule. Five of the nine rewrite rules were found to generate additional synonyms and spelling variants that correctly corresponded to the meaning of the original terms and seven out of the eight suppression rules were found to suppress only undesired terms. Using the five rewrite rules that passed our evaluation, we were able to identify 1,117,772 new occurrences of 14,784 rewritten terms in MEDLINE. Without the rewriting, we recognized 651,268 terms belonging to 397,414 concepts; with rewriting, we recognized 666,053 terms belonging to 410,823 concepts, which is an increase of 2.8% in the number of terms and an increase of 3.4% in the number of concepts recognized. Using the seven suppression rules, a total of 257,118 undesired terms were suppressed in the UMLS, notably decreasing its size. 7,397 terms were suppressed in the corpus. We recommend applying the five rewrite rules and seven suppression rules that passed our evaluation when the UMLS is to be used for biomedical term identification in MEDLINE. A software tool to apply these rules to the UMLS is freely available at http://biosemantics.org/casper.

• GeneE: Gene and protein query expansion with disambiguation.

  Authors: Martijn J Schuemie, Ning Kang, Maarten L Hekkelman, Jan A Kors

  Bioinformatics (Oxford, England). 10/2009;

  SUMMARY: When referring to genes, authors often use synonyms instead of the official gene symbols. In order to accurately retrieve as many relevant documents as possible, we have developed GeneE, aSUMMARY: When referring to genes, authors often use synonyms instead of the official gene symbols. In order to accurately retrieve as many relevant documents as possible, we have developed GeneE, a web application that expands a gene query to include all known synonyms, and adds disambiguation information for ambiguous terms, before forwarding the query to either PubMed, Google, or Jane. The query expansion algorithm is also available as a web service. AVAILABILITY: http://biosemantics.org/geneE CONTACT: m.schuemie@erasmusmc.nl.

• A Dictionary to Identify Small Molecules and Drugs in Free Text.

  Authors: Kristina M Hettne, Rob H Stierum, Martijn J Schuemie, Peter JM Hendriksen, Bob Ja Schijvenaars, Erik M van Mulligen, Jos Kleinjans, Jan A Kors

  Bioinformatics (Oxford, England). 09/2009;

  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 correctMOTIVATION: 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: (1) each of the different processing steps increase precision with a minor loss of recall; (2) the overall performance of the combined dictionary is acceptable (precision 0.67, recall 0.40 (0.80 for trivial names); (3) the combined dictionary performed better than the dictionary in the chemical recognizer OSCAR3; (4) 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 at http://www.biosemantics.org/chemlist. CONTACT: k.hettne@erasmusmc.nl.

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

  Authors: Gianluca Trifirò, Antoine Pariente, Preciosa M Coloma, Jan A Kors, Giovanni Polimeni, Ghada Miremont-Salamé, Maria Antonietta Catania, Francesco Salvo, Anaelle David, Nicholas Moore, Achille Patrizio Caputi, Miriam Sturkenboom, Mariam Molokhia, Julia Hippisley-Cox, Carlos Diaz Acedo, Johan van der Lei, Annie Fourrier-Reglat

  Pharmacoepidemiology and drug safety. 09/2009;

  PURPOSE: 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 EuropeanPURPOSE: 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. METHODS: Scientific literature, medical textbooks, and websites of regulatory agencies were reviewed to create a preliminary list of events that are deemed important in pharmacovigilance. Two teams of pharmacovigilance experts independently rated each event on five criteria: 'trigger for drug withdrawal', 'trigger for black box warning', 'leading to emergency department visit or hospital admission', 'probability of event to be drug-related', and 'likelihood of death'. In case of disagreement, a consensus score was obtained. Ordinal scales between 0 and 3 were used for rating the criteria, and an overall score was computed to rank the events. RESULTS: An initial list comprising 23 adverse events was identified. After rating all the events and calculation of overall scores, a ranked list was established. The top-ranking events were: cutaneous bullous eruptions, acute renal failure, anaphylactic shock, acute myocardial infarction, and rhabdomyolysis. CONCLUSIONS: A ranked list of 23 adverse drug events judged as important in pharmacovigilance was created to permit focused data mining. The list will need to be updated periodically as knowledge on drug safety evolves and new issues in drug safety arise. Copyright (c) 2009 John Wiley & Sons, Ltd.

• Common variants at ten loci influence QT interval duration in the QTGEN Study.

  Authors: Christopher Newton-Cheh, Mark Eijgelsheim, Kenneth M Rice, Paul I W de Bakker, Xiaoyan Yin, Karol Estrada, Joshua C Bis, Kristin Marciante, Fernando Rivadeneira, Peter A Noseworthy [......] Jan A Kors, Jacqueline C M Witteman, Albert Hofman, Susan R Heckbert, Christopher J O'Donnell, André G Uitterlinden, Bruce M Psaty, Thomas Lumley, Martin G Larson, Bruno H Ch Stricker

  Nature genetics. 05/2009; 41(4):399-406.

  QT interval duration, reflecting myocardial repolarization on the electrocardiogram, is a heritable risk factor for sudden cardiac death and drug-induced arrhythmias. We conducted a meta-analysis ofQT interval duration, reflecting myocardial repolarization on the electrocardiogram, is a heritable risk factor for sudden cardiac death and drug-induced arrhythmias. We conducted a meta-analysis of three genome-wide association studies in 13,685 individuals of European ancestry from the Framingham Heart Study, the Rotterdam Study and the Cardiovascular Health Study, as part of the QTGEN consortium. We observed associations at P < 5 x 10(-8) with variants in NOS1AP, KCNQ1, KCNE1, KCNH2 and SCN5A, known to be involved in myocardial repolarization and mendelian long-QT syndromes. Associations were found at five newly identified loci, including 16q21 near NDRG4 and GINS3, 6q22 near PLN, 1p36 near RNF207, 16p13 near LITAF and 17q12 near LIG3 and RFFL. Collectively, the 14 independent variants at these 10 loci explain 5.4-6.5% of the variation in QT interval. These results, together with an accompanying paper, offer insights into myocardial repolarization and suggest candidate genes that could predispose to sudden cardiac death and drug-induced arrhythmias.