A genome-wide assessment of the role of untagged copy number variants in type 1 diabetes.
A genome-wide assessment of the role of untagged copy number variants in type 1 diabetes.
复制标题
全基因组对1型糖尿病中未标记拷贝数变异的作用的评估。
DOI：
10.1371/journal.pgen.1004367
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发表时间：
2014
期刊：
影响因子：
4.5
通讯作者：
Rich SS
中科院分区：
文献类型：
--
作者：
Zanda M;Onengut-Gumuscu S;Walker N;Shtir C;Gallo D;Wallace C;Smyth D;Todd JA;Hurles ME;Plagnol V;Rich SS
1型糖尿病（T1 D）的全基因组关联研究（GWAS）已成功鉴定出40多个独立的T1 D相关标记单核苷酸多态性（SNP）。然而，由于拷贝数变异（CNVs）基因分型检测的技术限制，CNVs的作用的评估已被限制在这些与标签SNP高度连锁不平衡的子集。未标记的CNV，通常是多等位基因的，并且难以使用现有的检测方法进行基因分型，对T1 D的遗传性的贡献仍然是一个悬而未决的问题。为了研究这个问题，我们设计了一个定制的比较遗传杂交阵列（aCGH），专门设计用于检测从各种来源中鉴定的未标记的CNV基因座。为了克服这类CNVs病例对照设计的技术限制，我们对1型糖尿病遗传学联盟（T1 DGC）家族资源（代表3，903例从父母到受影响后代的传播）进行了基因分型，并使用了不需要获得离散基因型的关联检验策略。我们的设计针对4，309个CNV，其中3，410个通过了严格的质量控制过滤器。作为阳性对照，通过直接分型5′可变数目串联重复序列（VNTR）基因座，扫描证实了INS基因座的已知T1 D关联。我们的研究结果澄清了这样一个事实，即疾病的关联是无法区分的两个主要的多态性等位基因类的INS VNTR，I类和III类。我们还鉴定了新的技术伪像，其导致分别在染色体14q11.2、7 q34和14q32.33上的体细胞重排位点、T细胞受体、TCRA/TCRD和TCRB以及免疫球蛋白重链、IGH位点的虚假关联。然而，我们的数据没有发现新的T1 D基因座。我们的研究结果不支持未标记的CNVs在T1 D遗传性中的主要作用。对于许多复杂的性状，特别是1型糖尿病（T1 D），全基因组关联研究（GWAS）设计已经成功地检测了大量导致疾病风险的基因座。然而，在T1 D以及几乎所有其他性状的情况下，这些基因座的总和并不能完全解释从家族研究中估计的遗传力。这一观察结果提出了存在其他变体但尚未发现的可能性，因为它们尚未被GWAS设计有效地靶向。在这里，我们专注于一类特定的大的缺失/重复称为拷贝数变异（CNVs），更准确地说，这些位点的子集，突变迅速，这是高度多态性。这种高水平多态性的结果是，这些变异通常没有被以前的GWAS研究捕获。我们使用基于家族的设计，该设计经过优化以捕获这些以前未经测试的变体。然后，我们进行全基因组扫描，以评估它们对T1 D的贡献。我们的扫描在技术上是成功的，但没有发现新的关联。这表明GWAS策略几乎没有遗漏，T1 D的剩余遗传性很可能是由大量变异驱动的，这些变异要么罕见，要么常见，但对疾病风险的个体贡献很小。
Genome-wide association studies (GWAS) for type 1 diabetes (T1D) have successfully identified more than 40 independent T1D associated tagging single nucleotide polymorphisms (SNPs). However, owing to technical limitations of copy number variants (CNVs) genotyping assays, the assessment of the role of CNVs has been limited to the subset of these in high linkage disequilibrium with tag SNPs. The contribution of untagged CNVs, often multi-allelic and difficult to genotype using existing assays, to the heritability of T1D remains an open question. To investigate this issue, we designed a custom comparative genetic hybridization array (aCGH) specifically designed to assay untagged CNV loci identified from a variety of sources. To overcome the technical limitations of the case control design for this class of CNVs, we genotyped the Type 1 Diabetes Genetics Consortium (T1DGC) family resource (representing 3,903 transmissions from parents to affected offspring) and used an association testing strategy that does not necessitate obtaining discrete genotypes. Our design targeted 4,309 CNVs, of which 3,410 passed stringent quality control filters. As a positive control, the scan confirmed the known T1D association at the INS locus by direct typing of the 5′ variable number of tandem repeat (VNTR) locus. Our results clarify the fact that the disease association is indistinguishable from the two main polymorphic allele classes of the INS VNTR, class I-and class III. We also identified novel technical artifacts resulting into spurious associations at the somatically rearranging loci, T cell receptor, TCRA/TCRD and TCRB, and Immunoglobulin heavy chain, IGH, loci on chromosomes 14q11.2, 7q34 and 14q32.33, respectively. However, our data did not identify novel T1D loci. Our results do not support a major role of untagged CNVs in T1D heritability. For many complex traits, and in particular type 1 diabetes (T1D), the genome-wide association study (GWAS) design has been successful at detecting a large number of loci that contribute disease risk. However, in the case of T1D as well as almost all other traits, the sum of these loci does not fully explain the heritability estimated from familial studies. This observation raises the possibility that additional variants exist but have not yet been found because they have not effectively been targeted by the GWAS design. Here, we focus on a specific class of large deletions/duplications called copy number variants (CNVs), and more precisely to the subset of these loci that mutate rapidly, which are highly polymorphic. A consequence of this high level of polymorphism is that these variants have typically not been captured by previous GWAS studies. We use a family based design that is optimized to capture these previously untested variants. We then perform a genome-wide scan to assess their contribution to T1D. Our scan was technically successful but did not identify novel associations. This suggests that little was missed by the GWAS strategy, and that the remaining heritability of T1D is most likely driven by a large number of variants, either rare of common, but with a small individual contribution to disease risk.
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