Knight Stacey, Abo Ryan P, Abel Haley J, Neklason Deborah W, Tuohy Therese M, Burt Randall W, Thomas Alun, Camp Nicola J
Division of Genetic Epidemiology, University of Utah School of Medicine, Salt Lake City, UT 84108, USA.
Ann Hum Genet. 2012 Nov;76(6):500-9. doi: 10.1111/j.1469-1809.2012.00728.x. Epub 2012 Sep 19.
Shared genomic segment (SGS) analysis uses dense single nucleotide polymorphism genotyping in high-risk (HR) pedigrees to identify regions of sharing between cases. Here, we illustrate the power of SGS to identify dominant rare risk variants. Using simulated pedigrees, we consider 12 disease models based on disease prevalence, minor allele frequency and penetrance to represent disease loci that explain 0.2-99.8% of total disease risk. Pedigrees were required to contain ≥ 15 meioses between all cases and to be HR based on significant excess of disease (P < 0.001 or P < 0.00001). Across these scenarios, the power for a single pedigree ranged widely. Nonetheless, fewer than 10 pedigrees were sufficient for excellent power in the majority of models. Power increased with the risk attributable to the disease locus, penetrance and the excess of disease in the pedigree. Sharing allowing for one sporadic case was uniformly more powerful than sharing using all cases. Furthermore, an SGS analysis using a large attenuated familial adenomatous polyposis pedigree identified a 1.96 Mb region containing the known causal APC gene with genome-wide significance. SGS is a powerful method for detecting rare variants and a valuable complement to genome-wide association studies and linkage analysis.
共享基因组片段(SGS)分析利用高危(HR)家系中的密集单核苷酸多态性基因分型来识别病例之间的共享区域。在此,我们展示了SGS识别显性罕见风险变异的能力。使用模拟家系,我们基于疾病患病率、次要等位基因频率和外显率考虑了12种疾病模型,以代表解释0.2 - 99.8%总疾病风险的疾病位点。要求家系在所有病例之间包含≥15次减数分裂,并且基于疾病的显著过量(P < 0.001或P < 0.00001)为高危家系。在这些情况下,单个家系的效能差异很大。尽管如此,在大多数模型中,少于10个家系就足以获得出色的效能。效能随着疾病位点的可归因风险、外显率以及家系中疾病的过量而增加。允许一个散发病例的共享始终比使用所有病例的共享更有效。此外,使用一个大型的家族性腺瘤性息肉病衰减家系进行的SGS分析确定了一个1.96 Mb的区域,其中包含具有全基因组显著性的已知致病基因APC。SGS是检测罕见变异的有力方法,也是全基因组关联研究和连锁分析的有价值补充。