高次元遺伝子環境相互作用分析

Mengyun Wu¹, Yingmeng Li¹, Shuangge Ma²

¹School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China.

Annual review of statistics and its application

|August 29, 2025

まとめ

遺伝子と環境の相互作用は複雑な病気には極めて重要ですこのレビューは,これらの遺伝子環境相互作用を分析するための統計的方法を取り上げ,疾患発達の研究を支援します.

科学分野:

遺伝学
環境健康
バイオ統計学

背景:

複雑な疾患は遺伝的および環境的要因から生じ,遺伝子-環境 (G-E) の相互作用が重要な役割を果たします.
現在のG-E相互作用分析では,病気に関連した遺伝的および環境的要因の監視された枠組みがしばしば使用されます.
G-E相互作用分析の方法論的進歩をレビューするには,統計的視点が必要である.

研究の目的:

遺伝子と環境の相互作用分析のための統計的方法論の選択的なレビューを提供すること.
G-E相互作用の研究で使用される主要な枠組みとテクニックを分類し,議論する.
これらの方法を様々な研究シナリオで適用するための考慮事項を強調する.

主な方法:

仮説テスト,変数選択,次元縮小技術のレビュー.
テストベースの,推定ベースの,予測ベースの分析フレームワークの議論.
線形/非線形,固定/ランダム,限界/共同,そしてベイジアン/周波数分析の探索.

主要な成果:

テストベースの,推定ベースの,予測ベースの3つの主要な統計的フレームワークを特定しました.
線形/非線形およびベイジアン/周波数主義的な方法を含む様々な分析アプローチを詳細に説明しました.
統計的特性,計算的側面,およびG-Eインタラクションメソッドの実用的なアプリケーションを強調した.

結論:

遺伝子と環境の相互作用を分析するための方法論的な多様性は存在し,異なる研究目標に対応しています.
このレビューは,G-E相互作用の分析のための統計学的手法の適切な適用を容易にする.
統計的なGE相互作用分析における将来の研究方向が概説されている.

キーワード:

寸法縮小遺伝子と環境の相互作用仮説テスト限界分析と共同分析変数の選択

さらに関連する動画

06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.4K

08:09

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease

Published on: January 7, 2014

7.6K

関連する概念動画

01:20

Gene-Environment Interactions

433

Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...

433

02:27

Background and Environment Affect Phenotype

6.7K

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...

6.7K

01:06

Heritability

303

Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic"...

303

01:23

Behavioral Genetics and Its Designs

505

Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...

505

01:09

Epistasis Analysis

5.2K

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

5.2K

01:17

Two-Way ANOVA

2.8K

The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...