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Related Concept Videos

Gene-Environment Interactions01:20

Gene-Environment Interactions

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...
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

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...
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

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...
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism

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Related Experiment Video

Updated: Jun 18, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

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

Published on: September 17, 2019

Leveraging longitudinal data to boost statistical power for gene-environment interaction analysis.

He Xu1, Yuzhuo Ma1, Yufei Liu1

  • 1Department of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing, China.

Nature Computational Science
|June 16, 2026
PubMed
Summary

We developed SAGELD, a new method for analyzing gene-environment interactions in longitudinal studies. This approach enhances genetic discovery and precision medicine by utilizing longitudinal data more effectively than previous methods.

Related Experiment Videos

Last Updated: Jun 18, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

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

Published on: September 17, 2019

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical genomics

Background:

  • Gene-environment interaction (G×E) analyses are vital for genetic discovery, heritability, and precision medicine.
  • Current G×E methods primarily use cross-sectional data, limiting the use of valuable longitudinal data.
  • There is a need for efficient G×E methods that can leverage longitudinal data in large-scale studies.

Purpose of the Study:

  • To introduce SAGELD, a scalable and accurate genome-wide G×E method designed for longitudinal traits.
  • To enable G×E analyses in large datasets while controlling for sample relatedness.
  • To demonstrate the advantages of using longitudinal data for G×E studies.

Main Methods:

  • SAGELD employs matrix projection for test statistics construction.
  • The SPAGRM framework is utilized for efficient control of sample relatedness.
  • The method was validated through simulations and UK Biobank data analysis.

Main Results:

  • SAGELD achieves significant speedups (10- to 10,000-fold) compared to existing methods.
  • The method demonstrates greater statistical power than cross-sectional G×E analyses.
  • Identified 74 loci for genetic × age interactions and 5 loci for genetic × adiposity interactions using UK Biobank data.

Conclusions:

  • SAGELD offers a scalable and powerful approach for genome-wide G×E analyses with longitudinal data.
  • Leveraging longitudinal data in G×E analyses significantly enhances genetic discovery.
  • The findings support the utility of SAGELD for advancing precision medicine through comprehensive genetic insights.