Department of Psychiatry, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen Medical Center, Reinier Postlaan 10, Nijmegen, The Netherlands.
Eur Child Adolesc Psychiatry. 2010 Mar;19(3):281-95. doi: 10.1007/s00787-010-0092-x. Epub 2010 Feb 11.
Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are both highly heritable neurodevelopmental disorders. Evidence indicates both disorders co-occur with a high frequency, in 20-50% of children with ADHD meeting criteria for ASD and in 30-80% of ASD children meeting criteria for ADHD. This review will provide an overview on all available studies [family based, twin, candidate gene, linkage, and genome wide association (GWA) studies] shedding light on the role of shared genetic underpinnings of ADHD and ASD. It is concluded that family and twin studies do provide support for the hypothesis that ADHD and ASD originate from partly similar familial/genetic factors. Only a few candidate gene studies, linkage studies and GWA studies have specifically addressed this co-occurrence, pinpointing to some promising pleiotropic genes, loci and single nucleotide polymorphisms (SNPs), but the research field is in urgent need for better designed and powered studies to tackle this complex issue. We propose that future studies examining shared familial etiological factors for ADHD and ASD use a family-based design in which the same phenotypic (ADHD and ASD), candidate endophenotypic, and environmental measurements are obtained from all family members. Multivariate multi-level models are probably best suited for the statistical analysis.
注意缺陷多动障碍(ADHD)和自闭症谱系障碍(ASD)都是高度遗传性的神经发育障碍。有证据表明,这两种疾病的发病率都很高,20-50%的 ADHD 儿童符合 ASD 标准,30-80%的 ASD 儿童符合 ADHD 标准。这篇综述将概述所有可用的研究[基于家庭、双胞胎、候选基因、连锁和全基因组关联(GWA)研究],揭示 ADHD 和 ASD 共同的遗传基础的作用。研究结论表明,家庭和双胞胎研究确实支持 ADHD 和 ASD 源自部分相似的家族/遗传因素的假说。只有少数候选基因研究、连锁研究和 GWA 研究专门针对这种共病性,指出了一些有希望的多效基因、基因座和单核苷酸多态性(SNP),但该研究领域迫切需要更好设计和更有力的研究来解决这一复杂问题。我们建议未来研究 ADHD 和 ASD 的共同家族病因时,使用基于家庭的设计,从所有家庭成员中获得相同的表型(ADHD 和 ASD)、候选内表型和环境测量。多变量多层次模型可能最适合用于统计分析。