Michael Krawczak

Christian-Albrechts-Universität zu Kiel, Kiel, Schleswig-Holstein, Germany

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Publications (388)2296.51 Total impact

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    ABSTRACT: Gene-environment interactions (G × E) have attracted considerable research interest in the past owing to their scientific and public health implications, but powerful statistical methods are required to successfully track down G × E, particularly at a genome-wide level. Previously, a case-only (CO) design has been proposed as a means to identify G × E with greater efficiency than traditional case-control or cohort studies. However, as with genotype-phenotype association studies themselves, hidden population stratification (PS) can impact the validity of G × E studies using a CO design. Since this problem has been subject to little research to date, we used comprehensive simulation to systematically assess the type I error rate, power and effect size bias of CO studies of G × E in the presence of PS. Three types of PS were considered, namely genetic-only (PSG), environment-only (PSE), and joint genetic and environmental stratification (PSGE). Our results reveal that the type I error rate of an unadjusted Wald test, appropriate for the CO design, would be close to its nominal level (0.05 in our study) as long as PS involves only one interaction partner (i.e., either PSG or PSE). In contrast, if the study population is stratified with respect to both G and E (i.e., if there is PSGE), then the type I error rate is seriously inflated and estimates of the underlying G × E interaction are biased. Comparison of CO to a family-based case-parents design confirmed that the latter is more robust against PSGE, as expected. However, case-parent trios may be particularly unsuitable for G × E studies in view of the fact that they require genotype data from parents and that many diseases with an environmental component are likely to be of late onset. An alternative approach to adjusting for PS is principal component analysis (PCA), which has been widely used for this very purpose in past genome-wide association studies (GWAS). However, resolving genetic PS properly by PCA requires genetic data at the population level, the availability of which would conflict with the basic idea of the CO design. Therefore, we explored three modified Wald test statistics, inspired by the genomic control (GC) approach to GWAS, as an alternative means to allow for PSGE. The modified statistics were benchmarked against a stratified Wald test assuming known population affiliation, which should provide maximum power under PS. Our results confirm that GC is capable of successfully and efficiently correcting the PS-induced inflation of the type I error rate in CO studies of G × E.
    No preview · Article · Aug 2015 · Human Genetics
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    ABSTRACT: Human pigmentation traits are of great interest to many research areas, from ancient DNA analysis to forensic science. We developed a gene-based predictive model for pigmentation phenotypes in a realistic target population for forensic case work from Northern Germany and compared our model with those brought forth by previous studies of genetically more heterogeneous populations. In doing so, we aimed at answering the following research questions: (1) do existing models allow good prediction of high-quality phenotypes in a genetically similar albeit more homogeneous population? (2) Would a model specifically set up for the more homogeneous population perform notably better than existing models? (3) Can the number of markers included in existing models be reduced without compromising their predictive capability in the more homogenous population? We investigated the association between eye, hair and skin colour and 12 candidate single-nucleotide polymorphisms (SNPs) from six genes. Our study comprised two samples of 300 and 100 individuals from Northern Germany. SNP rs12913832 in HERC2 was found to be strongly associated with blue eye colour (odds ratio=40.0, P<1.2 × 10(-4)) and to yield moderate predictive power (AUC: 77%; sensitivity: 90%, specificity: 63%, both at a 0.5 threshold for blue eye colour probability). SNP associations with hair and skin colour were weaker and genotypes less predictive. A comparison with two recently published sets of markers to predict eye and hair colour revealed that the consideration of additional SNPs with weak-to-moderate effect increased the predictive power for eye colour, but not for hair colour.European Journal of Human Genetics advance online publication, 19 August 2015; doi:10.1038/ejhg.2015.167.
    No preview · Article · Aug 2015 · European journal of human genetics: EJHG
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    ABSTRACT: The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.
    Full-text · Article · Jul 2015 · PLoS ONE
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    ABSTRACT: Guided by the practice of classical epidemiology, research into the genetic basis of complex disease has usually taken for granted the dictum that causative mutations are invariably over-represented among clinically affected as compared to unaffected individuals. However, we show that this supposition is not true and that a mutation contributing to the etiology of a complex disease can, under certain circumstances, be depleted among patients. Populations with defined disease prevalence were repeatedly simulated under a Wright-Fisher model, assuming various types of population history and genotype-phenotype relationship. For each simulation, the resulting mutation-specific population frequencies and odds ratios (ORs) were evaluated. In addition, the relationship between mutation frequency and OR was studied using real data from the NIH GWAS catalogue of reported phenotype associations of single-nucleotide polymorphisms (SNPs). While rare diseases (prevalence <1%) were found to be consistently caused by rare mutations with ORs>1, up to 20% of mutations causing a pandemic disease (prevalence 10-20%) had ORs<1, and their population frequency ranged from 0% to 100%. Moreover, simulation-based ORs exhibited a wide distribution, irrespective of mutation frequency. In conclusion, a substantial proportion of mutations causing common complex diseases may appear 'protective' in genetic epidemiological studies and hence would normally tend to be excluded, albeit erroneously, from further study. This apparently paradoxical result is explicable in terms of mutual confounding of the respective genotype-phenotype relationships due to a negative correlation between causal mutations induced by their common gene genealogy. As would be predicted by our findings, a significant negative correlation became apparent in published genome-wide association studies between the OR of genetic variants associated with a particular disease and the prevalence of that disease.
    No preview · Article · Jul 2015 · PLoS ONE
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    ABSTRACT: Genetic studies not only contribute substantially to our current understanding of the natural variation in behavior and health in many species, they also provide the basis of numerous in vivo models of human traits. Despite the many challenges posed by the high level of biological and social complexity, a long lifespan and difficult access in the field, genetic studies of primates are particularly rewarding because of the close evolutionary relatedness of these species to humans. The free-ranging rhesus macaque (Macaca mulatta) population on Cayo Santiago (CS), Puerto Rico, provides a unique resource in this respect because several of the abovementioned caveats are of either minor importance there, or lacking altogether, thereby allowing long-term genetic research in a primate population under constant surveillance since 1956. This review summarizes more than 40 years of genetic research carried out on CS, from early blood group typing and the genetic characterization of skeletal material via population-wide paternity testing with DNA fingerprints and short tandem repeats (STRs) to the analysis of the highly polymorphic DQB1 locus within the major histocompatibility complex (MHC). The results of the paternity studies also facilitated subsequent studies of male dominance and other factors influencing male reproductive success, of male reproductive skew, paternal kin bias, and mechanisms of paternal kin recognition. More recently, the CS macaques have been the subjects of functional genetic and gene expression analyses and have played an important role in behavioral and quantitative genetic studies. In addition, the CS colony has been used as a natural model for human adult-onset macular degeneration, glaucoma, and circadian rhythm disorder. Our review finishes off with a discussion of potential future directions of research on CS, including the transition from STRs to single nucleotide polymorphism (SNP) typing and whole genome sequencing. Am. J. Primatol.
    No preview · Article · Jun 2015 · American Journal of Primatology
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    ABSTRACT: Age-related macular degeneration (AMD) is the leading cause of blindness among white caucasians over the age of 50 years with a prevalence rate expected to increase markedly with an anticipated increase in the life span of the world population. To further expand our knowledge of the genetic architecture of the disease, we pursued a candidate gene approach assessing 25 genes and a total of 109 variants. Of these, synonymous single nucleotide polymorphism (SNP) rs17810398 located in death-associated protein-like 1 (DAPL1) was found to be associated with AMD in a joint analysis of 3,229 cases and 2,835 controls from five studies [combined PADJ = 1.15 × 10−6, OR 1.332 (1.187–1.496)]. This association was characterized by a highly significant sex difference (Pdiff = 0.0032) in that it was clearly confined to females with genome-wide significance [PADJ = 2.62 × 10−8, OR 1.541 (1.324–1.796); males: PADJ = 0.382, OR 1.084 (0.905–1.298)]. By targeted resequencing of risk and non-risk associated haplotypes in the DAPL1 locus, we identified additional potentially functional risk variants, namely a common 897-bp deletion and a SNP predicted to affect a putative binding site of an exonic splicing enhancer. We show that the risk haplotype correlates with a reduced retinal transcript level of two, less frequent, non-canonical DAPL1 isoforms. DAPL1 plays a role in epithelial differentiation and may be involved in apoptotic processes thereby suggesting a possible novel pathway in AMD pathogenesis. Electronic supplementary material The online version of this article (doi:10.1007/s12017-015-8342-1) contains supplementary material, which is available to authorized users.
    No preview · Article · Feb 2015 · NeuroMolecular Medicine
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    Amke Caliebe · Arne Jochens · Sascha Willuweit · Lutz Roewer · Michael Krawczak
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    ABSTRACT: Match probability calculation is deemed much more intricate for lineage genetic markers, including Y-chromosomal short tandem repeats (Y-STRs), than for autosomal markers. This is because, owing to the lack of recombination, strong interdependence between markers is likely, which implies that haplotype frequency estimates cannot simply be obtained through the multiplication of allele frequency estimates. As yet, however, the practical relevance of this problem has not been studied in much detail using real data. In fact, such scrutiny appears well warranted because the high mutation rates of Y-STRs and the possibility of backward mutation should have worked against the statistical association of Y-STRs. We examined haplotype data of 21 markers included in the PowerPlex(®)Y23 set (PPY23, Promega Corporation, Madison, WI) originating from six different populations (four European and two Asian). Assessing the conditional entropies of the markers, given different subsets of markers from the same panel, we demonstrate that the PowerPlex(®)Y23 set cannot be decomposed into smaller marker subsets that would be (conditionally) independent. Nevertheless, in all six populations, >94% of the joint entropy of the 21 markers is explained by the seven most rapidly mutating markers. Although this result might render a reduction in marker number a sensible option for practical casework, the partial haplotypes would still be almost as diverse as the full haplotypes. Therefore, match probability calculation remains difficult and calls for the improvement of currently available methods of haplotype frequency estimation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
    Full-text · Article · Oct 2014 · Forensic Science International: Genetics
  • Pankaj Yadav · Sandra Freitag-Wolf · Wolfgang Lieb · Michael Krawczak
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    ABSTRACT: Gene-environment (G × E) interactions have been invoked to account, at least in part, for the gap between the known heritability of common human diseases and the phenotypic variation hitherto explained by genetic variants. Noteworthy in this context, a case-only (CO) design has been proposed in the past as a means to detect G × E interactions possibly more efficiently than by using classical case-control and cohort designs. So far, however, most CO studies have followed a candidate (or single) gene approach, and the genome-wide utility of the CO design is still more or less unknown. In particular, the way in which linkage disequilibrium (LD) impacts upon the chance to detect G × E interaction through the analysis of proxy markers has not been studied in much detail before. Therefore, we systematically assessed the power to indirectly detect a given G × E interaction through exploiting LD in a CO design. Our simulations revealed a strong relationship between LD and detection power that was subsequently validated in a real colorectal cancer data set.
    No preview · Article · Oct 2014 · Human Genetics
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    ABSTRACT: In a worldwide collaborative effort, 19,630 Y-chromosomes were sampled from 129 different populations in 51 countries. These chromosomes were typed for 23 short-tandem repeat (STR) loci (DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS385ab, DYS437, DYS438, DYS439, DYS448, DYS456, DYS458, DYS635, GATAH4, DYS481, DYS533, DYS549, DYS570, DYS576, DYS643) and using the PowerPlex Y23 System (PPY23, Promega Corporation, Madison, WI). Locus-specific allelic spectra of these markers were determined and a consistently high level of allelic diversity was observed. A considerable number of null, duplicate and off-ladder alleles were revealed. Standard single-locus and haplotype-based parameters were calculated and compared between subsets of Y-STR markers established for forensic casework. The PPY23 marker set provides substantially stronger discriminatory power than other available kits but at the same time reveals the same general patterns of population structure as other marker sets. A strong correlation was observed between the number of Y-STRs included in a marker set and some of the forensic parameters under study. Interestingly a weak but consistent trend towards smaller genetic distances resulting from larger numbers of markers became apparent.
    Full-text · Article · Sep 2014 · Forensic Science International: Genetics
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    Björn Stade · Dominik Seelow · Ingo Thomsen · Michael Krawczak · Andre Franke
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    ABSTRACT: BACKGROUND: Next Generation Sequencing (NGS) of whole exomes or genomes is increasingly being used in human genetic research and diagnostics. Sharing NGS data with third parties can help physicians and researchers to identify causative or predisposing mutations for a specific sample of interest more efficiently. In many cases, however, the exchange of such data may collide with data privacy regulations. GrabBlur is a newly developed tool to aggregate and share NGS-derived single nucleotide variant (SNV) data in a public database, keeping individual samples unidentifiable. In contrast to other currently existing SNV databases, GrabBlur includes phenotypic information and contact details of the submitter of a given database entry. By means of GrabBlur human geneticists can securely and easily share SNV data from resequencing projects. GrabBlur can ease the interpretation of SNV data by offering basic annotations, genotype frequencies and in particular phenotypic information - given that this information was shared - for the SNV of interest.
    Full-text · Article · May 2014 · BMC Genomics
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    [Show abstract] [Hide abstract]
    ABSTRACT: In a worldwide collaborative effort, 19,630 Y-chromosomes were sampled from 129 different populations in 51 countries. These chromosomes were typed for 23 short-tandem repeat (STR) loci (DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS385ab, DYS437, DYS438, DYS439, DYS448, DYS456, DYS458, DYS635, GATAH4, DYS481, DYS533, DYS549, DYS570, DYS576, DYS643) and using the PowerPlex Y23 System (PPY23, Promega Corporation, Madison, WI). Locus-specific allelic spectra of these markers were determined and a consistently high level of allelic diversity was observed. A considerable number of null, duplicate and off-ladder alleles were revealed. Standard single-locus and haplotype-based parameters were calculated and compared between subsets of Y-STR markers established for forensic casework. The PPY23 marker set provides substantially stronger discriminatory power than other available kits but at the same time reveals the same general patterns of population structure as other marker sets. A strong correlation was observed between the number of Y-STRs included in a marker set and some of the forensic parameters under study. Interestingly a weak but consistent trend towards smaller genetic distances resulting from larger numbers of markers became apparent.
    Full-text · Article · Apr 2014 · Forensic Science International: Genetics
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    ABSTRACT: Next Generation Sequencing (NGS) erlaubt die Untersuchung des kompletten Exoms oder Genoms eines Patienten mit vertretbarem zeitlichem und finanziellem Aufwand. Dieser diagnostische Quantensprung hat neben rechtlichen, ethischen und ökonomischen Aspekten auch vielfältige Auswirkungen auf die Patientenversorgung. Die weitgehende Einführung des NGS in die Routinediagnostik steht momentan jedoch noch vor vielen Hürden. Insbesondere ist zu erwarten, dass mittels NGS eine Vielzahl seltener Varianten bei einem Patienten entdeckt wird, die nach derzeitigem Wissensstand klinisch nicht hinreichend klar interpretierbar sind. Als einen ersten Schritt zur Lösung dieses Problems wird das Konzept einer Datenbank vorgestellt, die systematisch genotypische und phänotypische Informationen aus dem Versorgungskontext in Deutschland integrieren soll. Die so entstehende Ressource wäre nicht nur von großem wissenschaftlichem Interesse. Sie böte vordringlich den klinisch tätigen Humangenetikern die notwendige Evidenzbasis für eine zuverlässige Bewertung ihrer patientenbezogenen Sequenzierungsdaten.
    Full-text · Article · Mar 2014 · Medizinische Genetik
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    ABSTRACT: Genome-wide association studies (GWAS) have revealed genetic determinants of iron metabolism, but correlation of these with clinical phenotypes is pending. Homozygosity for HFE C282Y is the predominant genetic risk factor for hereditary hemochromatosis (HH) and may cause liver cirrhosis. However, this genotype has a low penetrance. Thus, detection of yet unknown genetic markers that identify patients at risk of developing severe liver disease is necessary for better prevention. Genetic loci associated with iron metabolism (TF, TMPRSS6, PCSK7, TFR2 and Chr2p14) in recent GWAS and liver fibrosis (PNPLA3) in recent meta-analysis were analyzed for association with either liver cirrhosis or advanced fibrosis in 148 German HFE C282Y homozygotes. Replication of associations was sought in additional 499 Austrian/Swiss and 112 HFE C282Y homozygotes from Sweden. Only variant rs236918 in the PCSK7 gene (proprotein convertase subtilisin/kexin type 7) was associated with cirrhosis or advanced fibrosis (P = 1.02 × 10−5) in the German cohort with genotypic odds ratios of 3.56 (95% CI 1.29–9.77) for CG heterozygotes and 5.38 (95% CI 2.39–12.10) for C allele carriers. Association between rs236918 and cirrhosis was confirmed in Austrian/Swiss HFE C282Y homozygotes (P = 0.014; ORallelic = 1.82 (95% CI 1.12–2.95) but not in Swedish patients. Post hoc combined analyses of German/Swiss/Austrian patients with available liver histology (N = 244, P = 0.00014, ORallelic = 2.84) and of males only (N = 431, P = 2.17 × 10−5, ORallelic = 2.54) were consistent with the premier finding. Association between rs236918 and cirrhosis was not confirmed in alcoholic cirrhotics, suggesting specificity of this genetic risk factor for HH. PCSK7 variant rs236918 is a risk factor for cirrhosis in HH patients homozygous for the HFE C282Y mutation.
    Full-text · Article · Feb 2014 · Human Molecular Genetics

  • No preview · Article · Jan 2014
  • Carolin Knecht · Michael Krawczak
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    ABSTRACT: Databases of disease-associated or disease-causing mutations allow the study, not only of the molecular mechanisms underlying the primary lesions at the DNA level, but also of the functional consequences of mutation at the phenotypic level. The Human Gene Mutation Database (HGMD) and the bioinformatics analyses of its content provide an illustrative example of this indirect approach to molecular genetic epidemiology. In fact, the Bayesian type of reasoning underlying previous scientific analyses of HGMD data is also reflected in current software tools used to predict the likely disease relevance of a newly detected genetic variant. After a brief resume of the past scientific utility of HGMD, we, therefore, shortly review three representative and commonly used examples of these tools, namely SIFT, PolyPhen-2 and NNSplice.
    No preview · Article · Nov 2013 · Human Genetics
  • A. Pfeufer · M. Krawczak

    No preview · Article · Oct 2013
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    ABSTRACT: Colorectal cancer (CRC) is one of the most common cancer worldwide. However, a large number of genetic risk factors involved in CRC have not been understood. Copy number variations (CNVs) might partly contribute to the 'missing heritability' of CRC. An increased overall burden of CNV has been identified in several complex diseases, whereas the association between the overall CNV burden and CRC risk is largely unknown. We performed a genome-wide investigation of CNVs on genomic DNA from 384 familial CRC cases and 1,285 healthy controls by the Affymetrix 6.0 array. An increase of overall CNV burden was observed in familial CRC patients compared to healthy controls, especially for CNVs larger than 50 kb (case/control ratio = 1.66, P = 0.025). In addition, we discovered for the first time a novel structural variation at 12p12.3 and determined the breakpoints by strategic PCR and sequencing. This 12p12.3 structural variation was found in four of 2,862 CRC cases, but not in 6,243 healthy controls (P = 0.0098). RERGL gene (RERG/RAS-like), the only gene influenced by the 12p12.3 structural variation, sharing most of the conserved regions with its close family member RERG tumor suppressor gene (RAS-like, estrogen-regulated, growth inhibitor), might be a novel CRC related gene. In conclusion, this is the first study to reveal the contribution of the overall burden of CNVs to familial CRC risk, and identified a novel rare structural variation at 12p12.3 containing RERGL gene to be associated with CRC.
    Full-text · Article · Oct 2013 · Carcinogenesis
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    ABSTRACT: To date, liver biopsy is the only means of reliable diagnosis for fatty liver disease (FLD). Owing to the inevitable biopsy-associated health risks, however, the development of valid noninvasive diagnostic tools for FLD is well warranted. We evaluated a particular metabolic profile with regard to its ability to diagnose FLD and compared its performance to that of established phenotypes, conventional biomarkers and disease-associated genotypes. The study population comprised 115 patients with ultrasound-diagnosed FLD and 115 sex- and age-matched controls for whom the serum concentration was measured of 138 different metabolites, including acylcarnitines, amino acids, biogenic amines, hexose, phosphatidylcholines (PCs), lyso-PCs and sphingomyelins. Established phenotypes, biomarkers, disease-associated genotypes and metabolite data were included in diagnostic models for FLD using logistic regression and partial least-squares discriminant analysis. The discriminative power of the ensuing models was compared with respect to area under curve (AUC), integrated discrimination improvement (IDI) and by way of cross-validation (CV). Use of metabolic markers for predicting FLD showed the best performance among all considered types of markers, yielding an AUC of 0.8993. Additional information on phenotypes, conventional biomarkers or genotypes did not significantly improve this performance. Phospholipids and branched-chain amino acids were most informative for predicting FLD. We show that the inclusion of metabolite data may substantially increase the power to diagnose FLD over that of models based solely upon phenotypes and conventional biomarkers.
    Full-text · Article · Oct 2013 · PLoS ONE
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    Michael Krawczak · Jürgen Goebel

    Preview · Article · Sep 2013 · Deutsche Zeitschrift für die Gesamte Gerichtliche Medizin
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    ABSTRACT: Human longevity is a multifactorial phenotype influenced by both genetic and environmental factors. Despite its heritability of 25-32 %, the genetic background of longevity is as yet largely unexplained. Apart from APOE status, variation in the FOXO3A gene is the only confirmed genetic contributor to survival into old age. On the other hand, FOXO3A activity is known to be downregulated in various cancers, and the gene was recently identified as a novel deletion hotspot in human lung adenocarcinoma. In view of the strong association between smoking and lung cancer, we set out to explore whether smoking modifies the known association between FOXO3A variation and longevity. To this end, we conducted a case-control study in two different populations, drawing upon extensive collections of old-aged individuals and younger controls available to us (1,613 German centenarians/nonagenarians and 1,104 controls; 1,088 Danish nonagenarians and 736 controls). In the German sample, 21 single nucleotide polymorphisms (SNPs) from the FOXO3A gene region were genotyped, whereas 15 FOXO3A SNPs were analyzed in the Danish sample. Eight SNPs were typed in both populations. Logistic regression analysis revealed that adjustment for smoking does not systematically alter the association between FOXO3A variation and longevity in neither population. Our analysis therefore suggests that the said association is not largely due to the confounding effects of lung cancer.
    No preview · Article · Sep 2013 · Age

Publication Stats

20k Citations
2,296.51 Total Impact Points


  • 2002-2015
    • Christian-Albrechts-Universität zu Kiel
      • • UKSH Institut für Medizinische Informatik und Statistik
      • • Institute of Clinical Molecular Biology
      Kiel, Schleswig-Holstein, Germany
    • National Human Genome Research Institute
      베서스다, Maryland, United States
  • 2006-2014
    • University Medical Center Schleswig-Holstein
      • Department of Pediatrics
      Kiel, Schleswig-Holstein, Germany
  • 2013
    • National Research Centre for the Working Environment
      København, Capital Region, Denmark
  • 2012
    • University of Tartu
      • Estonian Genome Center
      Dorpat, Tartu, Estonia
  • 2004-2012
    • Universitätsklinikum Schleswig - Holstein
      • Institut für Medizinische Informatik und Statistik (Kiel)
      Kiel, Schleswig-Holstein, Germany
  • 1997-2003
    • University of Wales
      • College of Medicine
      Cardiff, Wales, United Kingdom
  • 2000
    • Hospital Universitario Ramón y Cajal
      Madrid, Madrid, Spain
  • 1990-1999
    • Thrombosis Research Institute
      Londinium, England, United Kingdom
  • 1991-1998
    • Hannover Medical School
      • Institute for Human Genetics
      Hanover, Lower Saxony, Germany
  • 1996
    • Cardiff University
      • Institute of Medical Genetics
      Cardiff, WLS, United Kingdom
  • 1993
    • Humboldt-Universität zu Berlin
      • Department of Biology
      Berlín, Berlin, Germany
  • 1986-1991
    • Charles University in Prague
      • Ústav klinické biochemie a patobiochemie (2. LF)
      Praha, Hlavni mesto Praha, Czech Republic
  • 1985-1991
    • Georg-August-Universität Göttingen
      Göttingen, Lower Saxony, Germany
  • 1989-1990
    • Universitätsmedizin Göttingen
      • Department of Human Genetics
      Göttingen, Lower Saxony, Germany