Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital and The Ohio State University, Columbus, OH, 43205, USA,
J Neurodev Disord. 2011 Jun;3(2):113-23. doi: 10.1007/s11689-011-9072-9. Epub 2011 Jan 19.
The Autism Genome Project has assembled two large datasets originally designed for linkage analysis and genome-wide association analysis, respectively: 1,069 multiplex families genotyped on the Affymetrix 10 K platform, and 1,129 autism trios genotyped on the Illumina 1 M platform. We set out to exploit this unique pair of resources by analyzing the combined data with a novel statistical method, based on the PPL statistical framework, simultaneously searching for linkage and association to loci involved in autism spectrum disorders (ASD). Our analysis also allowed for potential differences in genetic architecture for ASD in the presence or absence of lower IQ, an important clinical indicator of ASD subtypes. We found strong evidence of multiple linked loci; however, association evidence implicating specific genes was low even under the linkage peaks. Distinct loci were found in the lower IQ families, and these families showed stronger and more numerous linkage peaks, while the normal IQ group yielded the strongest association evidence. It appears that presence/absence of lower IQ (LIQ) demarcates more genetically homogeneous subgroups of ASD patients, with not just different sets of loci acting in the two groups, but possibly distinct genetic architecture between them, such that the LIQ group involves more major gene effects (amenable to linkage mapping), while the normal IQ group potentially involves more common alleles with lower penetrances. The possibility of distinct genetic architecture across subtypes of ASD has implications for further research and perhaps for research approaches to other complex disorders as well.
孤独症基因组计划(Autism Genome Project)收集了两套最初分别用于连锁分析和全基因组关联分析的大型数据集:1069 个经 Affymetrix 10K 平台基因分型的多病例家系,以及 1129 个经 Illumina 1M 平台基因分型的孤独症三联体。我们旨在利用这一对独特的资源,通过分析基于 PPL 统计框架的联合数据,同时搜索与孤独症谱系障碍(ASD)相关的连锁和关联基因座,来开发这种新的统计方法。我们的分析还允许在存在或不存在低智商的情况下,对 ASD 的遗传结构进行潜在差异的研究,低智商是 ASD 亚型的一个重要临床指标。我们发现了多个连锁基因座的有力证据;然而,即使在连锁峰下,与特定基因相关联的证据也很低。在低智商家族中发现了不同的基因座,这些家族表现出更强、更多的连锁峰,而正常智商组则产生了最强的关联证据。似乎有无低智商(LIQ)可以区分 ASD 患者的遗传同质性亚组,两组不仅有不同的基因座在起作用,而且它们之间可能存在不同的遗传结构,使得 LIQ 组涉及更多的主要基因效应(可通过连锁作图来研究),而正常智商组可能涉及更多低外显率的常见等位基因。ASD 亚型之间可能存在不同的遗传结构,这对进一步的研究,甚至对其他复杂疾病的研究方法都有影响。