Genetic epidemiology of complex traits:
This presentation is the property of its rightful owner.
Sponsored Links
1 / 28

Genetic epidemiology of complex traits: issues and methods PowerPoint PPT Presentation


  • 104 Views
  • Uploaded on
  • Presentation posted in: General

Genetic epidemiology of complex traits: issues and methods. M.W.Zuurman, Werkbespreking Medische Biologie 28 november 2005. Breedte strategie. The presentation. Background Issues Methods. What do we want anyway?. We want to cure disease!. We want to explain disease!.

Download Presentation

Genetic epidemiology of complex traits: issues and methods

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Genetic epidemiology of complex traits issues and methods

Genetic epidemiology of complex traits:

issues and methods

M.W.Zuurman, Werkbespreking Medische Biologie

28 november 2005

Breedtestrategie


Genetic epidemiology of complex traits issues and methods

The presentation

  • Background

  • Issues

  • Methods


Genetic epidemiology of complex traits issues and methods

What do we want anyway?

We want to cure disease!

We want to explain disease!

We want to counteract disease!


Genetic epidemiology of complex traits issues and methods

Let’s explain disease

Breedtestrategie: Let’s explain Cardiovascular and Renal disease

What is disease?


Genetic epidemiology of complex traits issues and methods

What is disease?

Disease is a condition in the organism that impairs normal function of the organism


Genetic epidemiology of complex traits issues and methods

Normal:

  • Conforming with or constituting a norm or standard or level or type or social norm

  • In accordance with scientific laws

  • Being approximately average or within certain limits

  • Convention: something regarded as a normative example

  • A statistical measure of usually observed structures, typical, or representative type

Subjectivity of ‘normal’ vs ‘diseased’:

A disease is any abnormal condition of the body or mind that causes discomfort,

dysfunction, or distress to the person affected or those in contact with the person.(Wikipedia)

Disease:

Disease is a condition in the organism that impairs normal function of the organism


Genetic epidemiology of complex traits issues and methods

Medical/Research practice:

Disease (Platonic)

+

+

+

Symptoms (Phenotypes!)

Causes:

Nurture/Nature

+

-

-

Intervention


Genetic epidemiology of complex traits issues and methods

Organisms are born with a set of genes in a certain environment

Disease

Genotype

Environment

Nature versus Nurture

Mulcaster (1581): “that treasure bestowed on them by nature, to be bettered in them by nurture”

Genetic versus environmental influence

In reality, you can’t have one without the other:


Genetic epidemiology of complex traits issues and methods

Summary (1)

When seeking to explain disease:

  • Define disease clearly

  • What is normal and why?

    • It will determine the extend of ‘abnormal’

  • Define phenotypes clearly

    • Make them quantifiable with sufficient

      Specificity :

      the probability to detect a negative result

      (e.g. ‘healthy’ or ‘control’)

      and

      Sensitivity

      the probability to detect a positive result

      (e.g. ‘diseased’ or ‘case’)


Genetic epidemiology of complex traits issues and methods

Main issue

Genetic epidemiology of complex traits

Research Question:

What is the genetic basis of complex traits (=disease/disease phenotypes)?


Genetic epidemiology of complex traits issues and methods

Genetic variation

Locus (e.g. QTL)

Gene (e.g. expression arrays)

Single Nucleotide Polymorphisms (SNP) (genotyping):

~AATGCCGA~~AATACCGA~

~TTACGGCT~~TTATGGCT~

Divided in wild type and mutated alleles

Has the genotype form of AA AB BB

Can be functional

Can be a neighbor of a functional variation (haplotype)

Can be none of those


Genetic epidemiology of complex traits issues and methods

Complex Traits

  • Mendelian traits: a single gene  phenotype

  • - e.g. eye colour, curly hair etc.

  • - also called dichotomous traits

    • - irrespective of environment in most cases

  • Continuously variable trait:polygenic and/or pleiotropic

  • polygenic : multiple genes affect a single trait

  • pleiotropic : one gene affects multiple traits

  • Note: pure polygenic/pleiotropic (without environmental

  • influences) hardly exist

  • Complex Trait: polygenic- and pleiotropic gene-environment interaction

  • Examples: stature, atherosclerosis, blood pressure regulation, and many

  • many more.


Genetic epidemiology of complex traits issues and methods

Context effect of genetic variance in complex traits

2 SNPs (4 alleles, 9 possible combinations)

1,00

1,27

1,30

1,34

1,24

250

200

Count

150

100

50

2,00

1,33

1,39

1,33

1,32

3,00

1,40

1,39

1,40

1,41

250

200

Count

150

100

50

1,00

2,00

3,00

HDL


Genetic epidemiology of complex traits issues and methods

Power drainage

One SNP

Two SNPs

Three SNPs


Genetic epidemiology of complex traits issues and methods

Methods (1)

  • We need methods to:

  • Preserve power

  • Reduce noise

  • Lift shadows of stronger determinants


Genetic epidemiology of complex traits issues and methods

FGClustor

Hypothesis driven Exploration via FGClustor

Conceptual thinking:

Given any outcome parameter measured in a population

one is able to detect differences in frequency of a combination

of geno- or phenotypes along the range of the parameter when

compared to the prevalence of that combination in the whole population.


Genetic epidemiology of complex traits issues and methods

FGClustor

FGClustor principle

y

f1a

a

f2a

f3a

f4a

f1b

b

f2b

f3b

f4b

f1c

f2c

f3c

f4c

c

d

f1d

f2d

f3d

f4d

HDL-c

f1e

e

f2e

f3e

f4e

Frequency of combination n

Frequency of combination 1

Frequency of combination 2

Frequency of combination 3

f

f1f

f2f

f3f

f4f

g

f1g

f2g

f3g

f4g

h

f1h

f2h

f3h

f4h

0

0

combinations

combinations


Genetic epidemiology of complex traits issues and methods

FGClustor


Genetic epidemiology of complex traits issues and methods

FGClustor


Genetic epidemiology of complex traits issues and methods

FGClustor

FGClustor and strong confounders

Phenotype: Systolic blood pressureComplex Trait: Quartiles Cholesterol + Gender

Chi-square Test

M1

M2

M3

M4

F2

F3

F4

F1


Genetic epidemiology of complex traits issues and methods

FGClustor

FGClustor and SNPs

Phenotype : HDL-cholesterolComplex Trait: SNP1 + SNP2

Chi-square Test

ABCC

ABDD

AACC


Genetic epidemiology of complex traits issues and methods

FGClustor

Summary

Pro:

  • FGClustor used in hypothesis driven approach can shed light on relationships of covariates of interest

  • FGClustor can visualize context-based main effects of parameters of interest

  • “Standard” statistical methods are needed in conjunction with FGClustor output to confirm context-based main effects

    Con:

  • FGClustor is not statistically powerful


Genetic epidemiology of complex traits issues and methods

MDR

Multifactor Dimensionality Reduction

  • What is MDR?

  • Nonparametric and genetic model-free

  • Alternative to logistic regression

  • Detecting nonlinear interactions among discrete genetic

  • and environmental attributes.

  • The MDR method combines

  • attribute selection,

  • attribute construction,

  • classification,

  • cross-validation and

  • visualization

  • http://www.epistasis.org/mdr.html

Moore (Expert Review of Molecular Diagnostics, 4:795-803, 2004)


Genetic epidemiology of complex traits issues and methods

MDR

Worked example: SBP (dichotomous by median)

Covariates: Sex and Quartiles of Total cholesterol


Genetic epidemiology of complex traits issues and methods

MDR

MDR

Worked example: SBP (dichotomous by median)

Covariates: Sex and Quartiles of Total cholesterol

Best Model output:


Genetic epidemiology of complex traits issues and methods

MDR

MDR

Worked example: HDL-c (dichotomous by <= 1 mmol/L)

Covariates: SNP1 SNP2

Best Model output:

AACC

ABCC

ABDD


Genetic epidemiology of complex traits issues and methods

MDR

Summary

Pro:

  • Includes cross-validation in the same population

  • Can be used as dataminer, not necessarily hypothesis driven

  • Statistically powerful to uncover also weak (genotype) effects

    Con:

  • Can be used as dataminer, not necessarily hypothesis driven

  • Limited by categorical data only


Genetic epidemiology of complex traits issues and methods

Discussion

  • Standard methods in genetic epidemiology only show very strong association in case of direct or extremely close relationship between gene and outcome parameter of interest.

  • Complex traits are build of individual contributors (genetic variants, environmental parameters) that each in itself have a weak main effect on the trait.

  • Noise and strong confounders limit detection of the weaker contributors in complex traits by standard statistics

  • Main effects of the individual contributors can be visualized using novel tools (e.g. FGClustor, MDR) in a context dependent approach at the background of solid hypothesis


  • Login