Evaluation of familial phenotype deviation to measure the impact of de novo mutations in autism.

IF 10.4 1区 生物学 Q1 GENETICS & HEREDITY
Soo-Whee Kim, Hyeji Lee, Da Yea Song, Gang-Hee Lee, Jae Hyun Han, Jee Won Lee, Hee Jung Byun, Ji Hyun Son, Ye Rim Kim, Yoojeong Lee, Eunjoon Kim, Donna M Werling, So Hyun Kim, Stephan J Sanders, Hee Jeong Yoo, Joon-Yong An
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引用次数: 0

Abstract

Background: The phenotypic outcomes of de novo variants (DNVs) in autism spectrum disorder (ASD) exhibit wide variability. To date, no study has comprehensively estimated DNV effects accounting for familial phenotypic background.

Methods: To evaluate DNV effects in a family-relative context, we defined within-family standardized deviations (WFSD) by subtracting phenotype scores of unaffected family members and standardizing the result. We applied this approach to 78,685 individuals from 21,735 families from ASD cohorts of diverse ancestries. We compared the distribution, associations with disruptive DNVs, and gene discovery results between WFSD and raw phenotype scores. We further performed outlier analysis based on WFSDs per gene to detect genes with high variability between families.

Results: We observed that ASD probands with disruptive DNVs exhibited greater behavioral symptoms and lower adaptive functioning relative to their within-family unaffected members. Compared to raw phenotype scores, WFSD provided clearer associations with DNVs and enabled greater yield in DNV-enriched gene discovery, including 18 novel ASD-associated genes. Outlier analysis identified 11 genes with high intrafamilial variability in phenotypic effects, influenced by mutation sites within functional domains or exons.

Conclusions: Familial DNV analysis provides accurate effect estimates, a reliable basis for predicting clinical outcomes, and precise support while minimizing confounding from family background. This approach improves the identification of ASD-associated genes with true phenotypic effects by reducing variability, as well as genes with genuine phenotypic heterogeneity across families driven by mutation site. These findings enhance our understanding of ASD phenotype variability and inform potential targets for intervention.

评估家族表型偏差以衡量自闭症新生突变的影响。
背景:自闭症谱系障碍(ASD)中新生变异(dnv)的表型结果表现出广泛的变异性。到目前为止,还没有研究全面估计DNV对家族表型背景的影响。方法:为了评估DNV在家庭相关背景下的影响,我们通过减去未受影响的家庭成员的表型评分并标准化结果来定义家庭内标准化偏差(WFSD)。我们将这种方法应用于来自不同祖先的21,735个ASD队列家庭的78,685名个体。我们比较了WFSD和原始表型评分之间的分布、与破坏性dnv的关联以及基因发现结果。我们进一步根据每个基因的WFSDs进行离群分析,以检测家族间高变异性的基因。结果:我们观察到,与未受影响的家庭成员相比,具有破坏性dnv的ASD先证者表现出更大的行为症状和更低的适应功能。与原始表型评分相比,WFSD提供了与dnv更清晰的关联,并使dnv富集基因的发现产量更高,包括18个新的asd相关基因。异常值分析发现,受功能域或外显子内突变位点的影响,11个基因在表型效应上具有较高的家族内变异性。结论:家族性DNV分析提供了准确的效果估计,预测临床结果的可靠基础,并提供了精确的支持,同时最大限度地减少了家庭背景的混淆。该方法通过减少变异,提高了对具有真正表型效应的asd相关基因的鉴定,以及由突变位点驱动的具有真正表型异质性的家族基因的鉴定。这些发现增强了我们对ASD表型变异性的理解,并为干预的潜在目标提供了信息。
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来源期刊
Genome Medicine
Genome Medicine GENETICS & HEREDITY-
CiteScore
20.80
自引率
0.80%
发文量
128
审稿时长
6-12 weeks
期刊介绍: Genome Medicine is an open access journal that publishes outstanding research applying genetics, genomics, and multi-omics to understand, diagnose, and treat disease. Bridging basic science and clinical research, it covers areas such as cancer genomics, immuno-oncology, immunogenomics, infectious disease, microbiome, neurogenomics, systems medicine, clinical genomics, gene therapies, precision medicine, and clinical trials. The journal publishes original research, methods, software, and reviews to serve authors and promote broad interest and importance in the field.
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