Genotype environment interaction

GENOTYPE ENVIRONMENT
INTERACTION
Sania Saher

What is genotype environment interaction?
ENVIRONMENT
GENOTYPE 2
GENOTYPE 1
PHENOTYPE
When two different genotypes respond to environmental
variation in different way..

CONTENTS
History
Phenotype is the function of Genotype and Environment
Epidemiological Models of GxE
Methods of analysis
Traditional genetic designs
Molecular analyses
Can we model G×E interaction in statistics?
Other Examples
Significance of GxE
Conclusion
References
3

HISTORY
• The first instance of debate occurred between Ronald Fisher
and Lancelot Hogben.
• A similar argument faced multiple scientists in the 1970s.
• Arthur Jensen defended that interaction was purely a statistical
phenomenon.
• Kenneth J. Rothman supported the use of a statistical
definition for interaction.
• Kupper and Hogan believed the definition and existence of
interaction was dependent on the model being used.
• Moffitt and Caspi's studies on 5-HTTLPR and stress and its
influence on depression.
4

CONTENTS
History
Methods of analysis
Molecular analyses
Other Examples
Significance of GxE
Conclusion
References
5

Phenotype is the function of Genotype and
Environment
• Genotype- genetic makeup of an individual.
• Phenotype- the expression of the genes.
• Environmental variation- change in environment. It can be
physical, chemical, biological, behavior patterns or life events.
• P=G+E
6

The ability of one genotype to produce more than one phenotype
when exposed to different environments.
7

CONTENTS
History
Methods of analysis
Molecular analyses
Other Examples
Significance of GxE
Conclusion
References
8

Epidemiological models of GxE
9

• Model A-describes a genotype that increases the level of
expression of a risk factor but does not cause the disease
itself.
Example: Phenylketonuria (PKU).
10

• Model B- has a direct effect on disease susceptibility which is
amplified by the genetic susceptibility.
Example: Xeroderma pigmentosum.
11

• Model C- where the genetic susceptibility directly effects
disease while the risk factor amplifies this effect.
Example: Porphyria variegata.
12

• Model D- differs as neither factor in this situation can effect
disease risk, however, when both genetic susceptibility and
risk factor are present the risk is increased.
Example: G6PD deficiency gene.
13

• Model E- depicts a scenario where the environmental risk
factor and genetic susceptibility can individually both
influence disease risk.
Example: α-1-antitrypsin deficiency.
14

CONTENTS
History
Methods of analysis
Molecular analyses
Other Examples
Significance of GxE
Conclusion
References
15

Methods of analyses of GXE
• Twin studies- monozygotic and dizygotic twins are compared.
16

Adoptive Studies
• Children living apart from their biological parents are studied.
• Biological parents vs. adoptive parents.
17

Molecular Analyses
• Interaction with single genes- this method used to detect
gene environment interactions by studying the effect of a
single gene variation with respect to particular environment.
• Example: Single nucleotide polymorphism.
18

Molecular Analyses
• Interaction with multiple genes- polygenic approach can be
used to analyze GxE interaction.
19

CONTENTS
History
Methods of analysis
Molecular analyses
Other Examples
Significance of GxE
Conclusion
References
20

Significance
• Disease can be prevented by reducing exposure to
environmental risks.
• An individual’s response to a drug can result from various
gene by environment interactions.
• Study of gene–environment interaction is important for
improving accuracy and precision in the assessment of both
genetic and environmental influences.
• An understanding of gene–environment interaction also has
important implications for public health.
• It aids in predicting disease rates and provides a basis for
well-informed recommendations for disease prevention.
• In Evolution play important role.
21

CONTENTS
History
Methods of analysis
Molecular analyses
Other Examples
Significance of GxE
Conclusion
References
23

• Although the biological definition of G×E interaction is
straightforward, its implementation into statistics is far less
clear.
• Two models are commonly used;
1. Additive model- Effect modification of the risk difference
corresponds with additive interaction.
when r11 − r01 ≠ r10 − r00.
2. Multiplicative model- Effect modification on the risk ratio
or odds ratio corresponds with multiplicative interaction.
when r11/r01 ≠ r10/r00.
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CONTENTS
History
Methods of analysis
Molecular analyses
Other Examples
Significance of GxE
Conclusion
References
25

Some other Examples
In plants:
• A plant’s structure reflects interactions with the environment.
• Some desert plants have reduced their leaves.
• Basmati Rice.
26

In Animals
• Climate change effect animal’s morphology.
• Arctic fox in winter and summer.
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In Humans
28
Gene symbol Variants (s) Environmental
exposure
Outcome and nature of
interaction
MC1R Variant for fair skin
Sunlight or ultraviolet
light B
Risk of skin cancer is
higher in people with
fair skin color that are
exposed to higher
amounts of sunlight.
CCR5 Delta 32 deletion HIV
Carriers of the receptor
deletion have lower
rates of HIV infection
and disease progression.
PPARG2 Pro12Ala Dietary fat intake
Stronger relation
between dietary fat
intake and obesity in
carriers of the Pro12Ala
allele.
ADRB2 Arg16Gly Asthma drugs
Arg16Gly homozygotes
have a greater response
in airway.

CONTENTS
History
Methods of analysis
Molecular analyses
Other Examples
Significance of GxE
Conclusion
References
29

Conclusion
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• Expression of genes is modified by environment.
• Gene-environment interactions are useful for understanding
some diseases.

References
• https://en.wikipedia.org/wiki/Genotype.
• Khoury, MJ.; Beaty, TH.; Cohen, BH. Fundamentals of genetic epidemiology.
Oxford Univ. Press; New York: 1993.
• 2. Rothman, KJ. Modern epidemiology. Little, Brown; Boston: 1986. Interactions
between causes; p. 311-26.
• “Genotype definition - Medical Dictionary definitions” . medterms.com.
• Allaby, Michael, ed. (2009). A dictionary of zoology (3rd ed.). Oxford: Oxford
University Press. ISBN 9780199233410 .
• SoftGenetics Application Note - GeneMarker® Software for Trisomy Analysis
(PDF). SoftGenetics. November 2006. Archived from the original.
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