Multifactorial traits Flashcards

1
Q

How do we know if a genetic component is non-Mendelian?

A

Twin studies (concordance rate)

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2
Q

Common multifactorial diseases involve

A

many DNA changes, each with a predisposing effect

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3
Q

A gene variant is

A

a single nucleotide polymorphism (SNP) that is associated with an increased risk of developing disease

it is present more frequently in those with the phenotype

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4
Q

Polymorphism

A

the presence of genetic variation within a population, upon which natural selection can operate

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5
Q

single nucleotide polymorphism

A

single base change
most common genomic variation
a substitution of a single nucleotide that occurs at a specific position in the genome, where each variation is present to some appreciable degree within a population
can predispose to conditions

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6
Q

The additive model is

A

a linear effect whereby if you have two copies of the disease allele, your risk is doubled
(think of graph)
GG

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7
Q

examples of common multifactorial quantitative traits

A

BMI, height, BP, CRP, LDL, fasting glucose

quantitative traits have more frequent gene variants that are specifically associated with higher/lower levels of the trait

Additive model applies, though environment ultimately controls (e.g. obesity)

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8
Q

The heritability of multifactorial diseases and continuous traits is due to

A

a large number of variants (more variants = more polygenicity)

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9
Q

GWAS

A

genome wide association studies

Hypothesis Free Approach - no prior knowledge

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10
Q

Types of GWAS

A

SNP-chip microarrays

whole genome sequencing (millions of SNPs)

hybrid alternatives (imputation)

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11
Q

SNP-chips

A

500-1m SNPs
high-density oligo arrays containing up to several million probes of smaller length, which allow for the genotyping of hundreds of thousands of selected SNPs across all chromosomes in a single reaction
cheap but limited to variation known about

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12
Q

whole genome sequencing

A

Whole genome sequencing is ostensibly the process of determining the complete DNA sequence of an organism’s genome at a single time. This entails sequencing all of an organism’s chromosomal DNA as well as DNA contained in the mitochondria

capturs more variation than SNP microarrays including variation which might not be catalogued BUT expensive

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13
Q

Hybrid alternatives

A

Imputation: refers to the statistical inference of unobserved genotypes.

cheap but based on statistical modelling - assay preferred for very rare variation

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14
Q

the point of GWAS is to develop

A

personalised medicine

DNA variant > molecular biology > physiology > disease

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15
Q

Predicting disease with genetic variants

A

ROC is the receiver operating characteristic
The ROC curve, is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied

The ROC curve is created by plotting the true positive rate (TPR) against the false positive rate (FPR) at various threshold settings

area under the curve (AUC) is the measure of accuracy: AUC=50 no better than flipping coin

AUC=0.8 clinically useful

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16
Q

Autoimmune diseases are heavily influence by

A

HLA
human leukocyte antigen
on chromosome 6
e.g type 1 diabetes exception to ROC curve

17
Q

Linkage disequilibrium

A

the occurrence in members of a population of combinations of linked genes in non-random proportions.

18
Q

Linkage disequilibrium creates

A

correlation among genetic variants

19
Q

Missing heritability is

A

the fact that GWAS has identified 1000s of genetic associations for disease risk and quantitative traits

but most of the observed effects are small: 1.1x increase in type 2 diabetes for every risk increasing allele

20
Q

Reasons for missing heritability (4)

A

larger sample sizes (resolution?)

rare/structural variants not tested

genetic interactions (epistasis, environment)

over-estimation of heritability

21
Q

In contrast to Mendelian diseases which are largely caused by protein coding changes, complex traits are mainly driven by

A

non coding variants that affect gene regulation

22
Q

Pleiotropy and epistasis

A

Pleiotropy:
a single gene at a give locus affects many phenotypes
e.g. albinism affects hair, eye and skin pigment

Epistasis:
2 or more alleles at one locus affect the expression of genes at a different locus