The Genetic Specificity of Cognitive Tests After Controlling for General Cognitive Ability.

IF 2.2 4区 医学 Q2 BEHAVIORAL SCIENCES
Behavior Genetics Pub Date : 2025-03-01 Epub Date: 2025-02-18 DOI:10.1007/s10519-025-10213-5
Francesca Procopio, Engin Keser, Jacob Knyspel, Margherita Malanchini, Kaili Rimfeld, Robert Plomin
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引用次数: 0

Abstract

Diverse tests of cognitive abilities correlate about 0.30 phenotypically and about 0.60 genetically. Their phenotypic overlap defines general cognitive ability (g), driven largely by genetic overlap. Consequently, much of our understanding of the genetic landscape of specific cognitive tests likely reflects g rather than the tests themselves. Removing this g-associated genetic variance will sharpen research on cognitive tests. Here, we use Genomic Structural Equation Modelling (Genomic SEM) to remove shared genetic variance among 12 diverse cognitive tests that capture verbal and nonverbal cognitive domains. We applied Genomic SEM to summary statistics from the largest genome-wide association studies of verbal tests (GenLang Consortium, five tests) and largely nonverbal tests (UK Biobank, seven tests) to chart the genetic landscape of the 12 tests independent of g as compared to uncorrected cognitive tests. We found that SNP heritabilities were nearly as high for the tests corrected for g as uncorrected: the average SNP heritability was 0.16 (SE = 0.02) for the uncorrected tests and 0.13 (SE = 0.02) for the tests corrected for g. Despite this, the genetic landscape of the cognitive tests transformed after controlling for genomic g. The matrix of positive genetic correlations for the cognitive tests (average 0.45) disappeared after g-correction, and some strong negative correlations emerged; for instance, Memory and Word (-0.72), Fluid and Symbol (-0.72), and Tower and Spelling (-0.79). The summary statistics for these g-corrected cognitive tests can be used by researchers to create polygenic scores that focus on the specificity of the tests.

控制一般认知能力后认知测试的遗传特异性。
不同的认知能力测试在表型上的相关性约为0.30,在遗传上的相关性约为0.60。它们的表型重叠决定了一般的认知能力(g),主要由基因重叠驱动。因此,我们对特定认知测试的基因景观的理解很可能反映了g而不是测试本身。消除这种与g相关的基因变异将使认知测试的研究更加敏锐。在这里,我们使用基因组结构方程模型(基因组SEM)来去除12种不同的认知测试中共享的遗传变异,这些测试捕获了语言和非语言认知领域。我们应用基因组扫描技术总结了语言测试(GenLang Consortium, 5项测试)和非语言测试(UK Biobank, 7项测试)的最大全基因组关联研究的统计数据,以绘制独立于g的12项测试与未校正的认知测试的遗传图谱。我们发现,校正g的测试与未校正的测试的SNP遗传率几乎一样高:未校正测试的平均SNP遗传率为0.16 (SE = 0.02),校正g的测试的平均SNP遗传率为0.13 (SE = 0.02)。尽管如此,在控制基因组g后,认知测试的遗传格局发生了变化。校正g后,认知测试的正遗传相关矩阵(平均0.45)消失了,出现了一些强烈的负相关;例如,《记忆与词汇》(-0.72)、《流体与符号》(-0.72)以及《塔与拼写》(-0.79)。研究人员可以使用这些g校正认知测试的汇总统计数据来创建专注于测试特异性的多基因评分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Behavior Genetics
Behavior Genetics 生物-行为科学
CiteScore
4.90
自引率
7.70%
发文量
30
审稿时长
6-12 weeks
期刊介绍: Behavior Genetics - the leading journal concerned with the genetic analysis of complex traits - is published in cooperation with the Behavior Genetics Association. This timely journal disseminates the most current original research on the inheritance and evolution of behavioral characteristics in man and other species. Contributions from eminent international researchers focus on both the application of various genetic perspectives to the study of behavioral characteristics and the influence of behavioral differences on the genetic structure of populations.
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