Markus Brugger, Manuel Lutz, Martina Müller-Nurasyid, Peter Lichtner, Emily P Slater, Elvira Matthäi, Detlef K Bartsch, Konstantin Strauch
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Similarly, an association analysis based on haplotypes instead of single markers can increase mapping power when the association pattern is complex.</p><p><strong>Methods: </strong>In this paper, we present an extension to the GENEHUNTER-MODSCORE software package that enables a JLA analysis based on haplotypes and uses information from arbitrary pedigree types and unrelated individuals. Our new JLA method is an extension of the MOD score approach for linkage analysis, which allows the estimation of trait-model and linkage disequilibrium (LD) parameters, i.e., penetrance, disease-allele frequency, and haplotype frequencies. LD is modeled between alleles at a single diallelic disease locus and up to three diallelic test markers. Linkage information is contributed by additional multi-allelic flanking markers. We investigated the statistical properties of our JLA implementation using extensive simulations, and we compared our approach to another commonly used single-marker JLA test. To demonstrate the applicability of our new method in practice, we analyzed pedigree data from the German National Case Collection for Familial Pancreatic Cancer (FaPaCa).</p><p><strong>Results: </strong>Based on the simulated data, we demonstrated the validity of our JLA-MOD score analysis implementation and identified scenarios in which haplotype-based tests outperformed the single-marker test. The estimated trait-model and LD parameters were in good accordance with the simulated values. Our method outperformed another commonly used JLA single-marker test when the LD pattern was complex. The exploratory analysis of the FaPaCa families led to the identification of a promising genetic region on chromosome 22q13.33, which can serve as a starting point for future mutation analysis and molecular research in pancreatic cancer.</p><p><strong>Conclusion: </strong>Our newly proposed JLA-MOD score method proves to be a valuable gene mapping and characterization tool, especially when either linkage or association information alone provide insufficient power to identify the disease-causing genetic variants.</p>","PeriodicalId":13226,"journal":{"name":"Human Heredity","volume":" ","pages":"8-31"},"PeriodicalIF":1.1000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Joint Linkage and Association Analysis Using GENEHUNTER-MODSCORE with an Application to Familial Pancreatic Cancer.\",\"authors\":\"Markus Brugger, Manuel Lutz, Martina Müller-Nurasyid, Peter Lichtner, Emily P Slater, Elvira Matthäi, Detlef K Bartsch, Konstantin Strauch\",\"doi\":\"10.1159/000535840\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Joint linkage and association (JLA) analysis combines two disease gene mapping strategies: linkage information contained in families and association information contained in populations. 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引用次数: 0
摘要
简介联合连锁与关联(JLA)分析结合了两种疾病基因图谱绘制策略:包含在家系中的连锁信息和包含在人群中的关联信息。这种联合关联分析可以提高测绘能力,尤其是当关联和关联的证据都处于中低水平时。同样,当关联模式复杂时,基于单倍型而非单一标记的关联分析也能提高测绘能力:本文介绍了对 GENEHUNTER-MODSCORE 软件包的扩展,该软件包可基于单倍型进行 JLA 分析,并使用来自任意血统类型和非相关个体的信息。我们的新 JLA 方法是 MOD 评分法在联系分析方面的扩展,可以估算性状模型和联系不平衡(LD)参数,即穿透性、疾病等位基因频率和单倍型频率。LD 是在一个单倍性疾病基因座的等位基因和多达三个双倍性测试标记之间建立的模型。额外的多等位基因侧翼标记提供了连锁信息。我们通过大量模拟研究了我们的 JLA 实现的统计特性,并将我们的方法与另一种常用的单标记 JLA 检验进行了比较。为了证明我们的新方法在实践中的适用性,我们分析了德国家族性胰腺癌(FaPaCa)国家病例收集的血统数据:基于模拟数据,我们证明了我们的 JLA MOD 评分分析实施方案的有效性,并确定了基于单倍型的检验优于单标记检验的情况。估计的性状模型和 LD 参数与模拟值十分吻合。当 LD 模式复杂时,我们的方法优于另一种常用的 JLA 单标记检验。通过对FaPaCa家系的探索性分析,我们在22q13.33染色体上发现了一个有希望的遗传区域,该区域可作为未来胰腺癌突变分析和分子研究的起点:结论:我们新提出的 JLA MOD 评分方法被证明是一种有价值的基因图谱绘制和特征描述工具,尤其是在单靠关联或关联信息不足以识别致病基因变异的情况下。
Joint Linkage and Association Analysis Using GENEHUNTER-MODSCORE with an Application to Familial Pancreatic Cancer.
Introduction: Joint linkage and association (JLA) analysis combines two disease gene mapping strategies: linkage information contained in families and association information contained in populations. Such a JLA analysis can increase mapping power, especially when the evidence for both linkage and association is low to moderate. Similarly, an association analysis based on haplotypes instead of single markers can increase mapping power when the association pattern is complex.
Methods: In this paper, we present an extension to the GENEHUNTER-MODSCORE software package that enables a JLA analysis based on haplotypes and uses information from arbitrary pedigree types and unrelated individuals. Our new JLA method is an extension of the MOD score approach for linkage analysis, which allows the estimation of trait-model and linkage disequilibrium (LD) parameters, i.e., penetrance, disease-allele frequency, and haplotype frequencies. LD is modeled between alleles at a single diallelic disease locus and up to three diallelic test markers. Linkage information is contributed by additional multi-allelic flanking markers. We investigated the statistical properties of our JLA implementation using extensive simulations, and we compared our approach to another commonly used single-marker JLA test. To demonstrate the applicability of our new method in practice, we analyzed pedigree data from the German National Case Collection for Familial Pancreatic Cancer (FaPaCa).
Results: Based on the simulated data, we demonstrated the validity of our JLA-MOD score analysis implementation and identified scenarios in which haplotype-based tests outperformed the single-marker test. The estimated trait-model and LD parameters were in good accordance with the simulated values. Our method outperformed another commonly used JLA single-marker test when the LD pattern was complex. The exploratory analysis of the FaPaCa families led to the identification of a promising genetic region on chromosome 22q13.33, which can serve as a starting point for future mutation analysis and molecular research in pancreatic cancer.
Conclusion: Our newly proposed JLA-MOD score method proves to be a valuable gene mapping and characterization tool, especially when either linkage or association information alone provide insufficient power to identify the disease-causing genetic variants.
期刊介绍:
Gathering original research reports and short communications from all over the world, ''Human Heredity'' is devoted to methodological and applied research on the genetics of human populations, association and linkage analysis, genetic mechanisms of disease, and new methods for statistical genetics, for example, analysis of rare variants and results from next generation sequencing. The value of this information to many branches of medicine is shown by the number of citations the journal receives in fields ranging from immunology and hematology to epidemiology and public health planning, and the fact that at least 50% of all ''Human Heredity'' papers are still cited more than 8 years after publication (according to ISI Journal Citation Reports). Special issues on methodological topics (such as ‘Consanguinity and Genomics’ in 2014; ‘Analyzing Rare Variants in Complex Diseases’ in 2012) or reviews of advances in particular fields (‘Genetic Diversity in European Populations: Evolutionary Evidence and Medical Implications’ in 2014; ‘Genes and the Environment in Obesity’ in 2013) are published every year. Renowned experts in the field are invited to contribute to these special issues.