Heritability Estimation of Cognitive Phenotypes in the ABCD Study® Using Mixed Models,Behavior Genetics

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Heritability Estimation of Cognitive Phenotypes in the ABCD Study® Using Mixed Models
Behavior Genetics ( IF 2.6 ) Pub Date : 2023-04-07 , DOI: 10.1007/s10519-023-10141-2
Diana M Smith _{1,

2,

3} , Robert Loughnan ₄ , Naomi P Friedman ₅ , Pravesh Parekh ₆ , Oleksandr Frei _{6,

7} , Wesley K Thompson ₈ , Ole A Andreassen ₆ , Michael Neale ₉ , Terry L Jernigan _{2,

10,

11,

12} , Anders M Dale _{3,

10,

11,

12,

13}

Affiliation

Neurosciences Graduate Program, University of California San Diego, La Jolla, CA, USA.
Center for Human Development, University of California, San Diego, La Jolla, CA, USA.
Center for Multimodal Imaging and Genetics, San Diego School of Medicine, University of California, La Jolla, CA, USA.
Population Neuroscience and Genetics Lab, University of California, San Diego, La Jolla, CA, USA.
Institute for Behavioral Genetics, Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA.
NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway.
Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK, USA.
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA.
Department of Radiology, University of California, San Diego School of Medicine, La Jolla, CA, USA.
Department of Psychiatry, University of California, San Diego School of Medicine, La Jolla, CA, USA.
Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla, CA, USA.

Twin and family studies have historically aimed to partition phenotypic variance into components corresponding to additive genetic effects (A), common environment (C), and unique environment (E). Here we present the ACE Model and several extensions in the Adolescent Brain Cognitive Development℠ Study (ABCD Study^®), employed using the new Fast Efficient Mixed Effects Analysis (FEMA) package. In the twin sub-sample (n = 924; 462 twin pairs), heritability estimates were similar to those reported by prior studies for height (twin heritability = 0.86) and cognition (twin heritability between 0.00 and 0.61), respectively. Incorporating SNP-derived genetic relatedness and using the full ABCD Study^® sample (n = 9,742) led to narrower confidence intervals for all parameter estimates. By leveraging the sparse clustering method used by FEMA to handle genetic relatedness only for participants within families, we were able to take advantage of the diverse distribution of genetic relatedness within the ABCD Study^® sample.

中文翻译：

使用混合模型的 ABCD Study® 中认知表型的遗传力估计

双胞胎和家庭研究历来旨在将表型方差划分为与加性遗传效应 ( A )、共同环境 ( C ) 和独特环境 ( E ) 相对应的组成部分。^{在这里，我们介绍了青少年大脑认知发展℠研究 (ABCD Study ®} )中的 ACE 模型和几个扩展，这些扩展使用了新的快速高效混合效应分析 (FEMA) 包。在双胞胎子样本（n = 924；462对双胞胎）中，身高（双胞胎遗传力= 0.86）和认知（双胞胎遗传力在0.00和0.61之间）的遗传力估计值分别与先前研究报告的相似。结合 SNP 衍生的遗传相关性并使用完整的 ABCD Study ^®样本 ( n = 9,742) 可以缩小所有参数估计值的置信区间。通过利用 FEMA 使用的稀疏聚类方法仅处理家庭内参与者的遗传相关性，我们能够利用 ABCD Study ^®样本中遗传相关性的多样化分布。

更新日期：2023-04-08

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