Departments of aEpidemiology bBiostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama cDepartment of Experimental and Clinical Pharmacology, College of Pharmacy dDepartment of Medicine and Pathology, Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota eJean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Medford, Massachusetts fDivision of Statistical Genomics, Genome Sciences Center, Washington University School of Medicine, Seattle, Washington gDepartment of Internal Medicine, Division of Cardiovascular Genetics, School of Medicine, University of Utah, Salt Lake City, Utah, USA hDepartment of Epidemiology, Atherothrombosis and Imaging, Centro Nacional de Investigaciones Cardiovasculares (CNIC) and Instituto Madrileño de Estudios Avanzados (IMDEA) Alimentacion, Madrid, Spain.
Pharmacogenet Genomics. 2015 Oct;25(10):511-4. doi: 10.1097/FPC.0000000000000162.
Cost-effective identification of novel pharmacogenetic variants remains a pressing need in the field. Using data from the Genetics of Lipid Lowering Drugs and Diet Network, we identified genomic regions of relevance to fenofibrate response in a sample of 173 families. Our approach included a multipoint linkage scan, followed by selection of the families showing evidence of linkage. We identified a strong signal for changes in LDL-cholesterol (LDL-C) on chromosome 7 (peak logarithm of odds score = 4.76) in the full sample (n = 821). The signal for LDL-C response remained even after adjusting for baseline LDL-C. Restricting analyses only to the families contributing to the linkage signal for LDL-C (N = 19), we observed a peak logarithm of odds score of 5.17 for chromosome 7. Two genes under this peak (ABCB4 and CD36) were of biological interest. These results suggest that linked family analyses might be a useful approach to gene discovery in the presence of a complex (e.g. multigenic) phenotype.
在该领域,经济有效地鉴定新的药物遗传学变异仍然是一个紧迫的需求。利用降脂药物和饮食网络遗传学研究的数据,我们在一个包含 173 个家族的样本中鉴定了与非诺贝特反应相关的基因组区域。我们的方法包括多点连锁扫描,然后选择有连锁证据的家族。我们在全样本(n = 821)中发现了一个位于 7 号染色体上的 LDL-胆固醇(LDL-C)变化的强烈信号(最大对数值优势得分=4.76)。即使在调整了 LDL-C 基线后,LDL-C 反应的信号仍然存在。将分析仅限于对 LDL-C 连锁信号有贡献的家族(n = 19),我们观察到 7 号染色体的最大对数值优势得分峰值为 5.17。该峰下的两个基因(ABCB4 和 CD36)具有生物学意义。这些结果表明,在存在复杂(例如多基因)表型的情况下,连锁家族分析可能是一种有用的基因发现方法。