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. 2014;24(1):31-8.
doi: 10.2188/jea.je20130070. Epub 2013 Nov 30.

Common genetic factors influence hand strength, processing speed, and working memory

Soshiro Ogata  1 , Kenji Kato, Chika Honda, Kazuo Hayakawa
Affiliations

Common genetic factors influence hand strength, processing speed, and working memory

Soshiro Ogata et al. J Epidemiol. 2014.

Abstract
in English, Japanese

Background: It is important to detect cognitive decline at an early stage, especially before onset of mild cognitive impairment and dementia. Processing speed and working memory are aspects of cognitive function that are associated with cognitive decline. Hand strength is an inexpensive, easily measurable indicator of cognitive decline. However, associations between hand strength, processing speed, and working memory have not been studied. In addition, the genetic and environmental structure of the association between hand strength and cognitive decline is unclear. We investigated phenotypic associations between hand strength, processing speed, and working memory and examined the genetic and environmental structure of the associations between phenotypes.

Methods: Hand strength, processing speed (digit symbol performance), and working memory (digit span performance) were examined in monozygotic and dizygotic twin pairs. Generalized estimating equations were used to identify phenotypic associations, and structural equation modeling was used to investigate the genetic and environmental structure of the association.

Results: Generalized estimating equations showed that hand strength was phenotypically associated with digit symbol performance but not with digit span performance. Structural equation modeling showed that common genetic factors influenced hand strength and digit symbol and digit span performance.

Conclusions: There was a phenotypic association between hand strength and processing speed. In addition, some genetic factors were common to hand strength, processing speed, and working memory.

背景: 初期段階、特に軽度認知症および認知症発症前での認知機能低下を発見することは重要である。認知機能の処理速度とワーキングメモリーは認知機能低下に影響すると報告されている。また握力は簡易に測定でき安価な認知機能低下の指標になると報告されている。しかしながら握力と処理速度とワーキングメモリーの関連は不明である。また握力と認知機能の関連における遺伝環境構造は不明である。そのため本研究の目的は、握力と処理速度及びワーキングメモリーに関連があるか検討すること、加えてこれら変数間の関連における遺伝環境構造を検討することとする。

方法: 一卵性双生児ペアと二卵性双生児ペアの握力、処理速度(符号問題で測定)、及びワーキングメモリー(数唱で測定) を測定した。一般化推定方程式を用いて握力と処理速度及びワーキングメモリーの関連を分析した。構造方程式モデリングを用いて、これら変数間の関連における遺伝環境構造を検討した。

結果: 一般化推定方程式の結果、握力は符号問題と関連はあったが数唱とは関連がなかった。構造方程式モデリングの結果、握力と符号問題及び数唱に共通する遺伝要因が示された。

結論: 本研究により握力は処理速度と関連があることが示され、握力は初期段階の認知機能低下発見の指標となると示唆された。握力と処理速度及びワーキングメモリーに共通する遺伝要因が発見された。

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Figures

Figure 1.
Figure 1.. Full ACE Cholesky model. Rectangles represent observed variables, ellipses represent latent variables, and arrows indicate a directional effect. Abbreviations: A, additive genetic; C, shared environment; E, nonshared environment.
Figure 2.
Figure 2.. Standardized path coefficients for hand strength, digit symbol performance, and digit span performance in the full ACE Cholesky model. Rectangles represent observed variables, ellipses represent latent variables, and arrows indicate a directional effect. Abbreviations: A, additive genetic; C, shared environment; E, nonshared environment.
Figure 3.
Figure 3.. Standardized path coefficients and 95% CIs for hand strength, digit symbol performance, and digit span performance in the best-fitting model. Rectangles represent observed variables, ellipses represent latent variables, and arrows indicate a directional effect. Abbreviations: A, additive genetic; C, shared environment; E, nonshared environment.
See this image and copyright information in PMC

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