Genetics of common disease Flashcards

1
Q

Can linkage analysis only be used to track the inheritance of rare genetic variants that cause disease? Why or why not?

A
  • No Linkage analysis can alos be used to track inheritance of common genetic variants that cause disease
  • This is because genetic variants that cause common disease also segregate with variants which are tightly linked to their region of the chromosome.
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2
Q

What are the differences between common disease and mendelian disease in terms of their causes and their inheritance?

A
  • Common diseases are caused mutations in multiple genes while mendelian disease is caused by a mutation in one gene
  • Common diseases are also influenced by multiple environmental factors while mendelian disease isn’t affceted by environmental factors
  • Inheritance patterns of common diseases are not clear unlike in Mendelian disease
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3
Q

What does the common disease common variant hypothesis state?

A
  • It states that common diseases are likely to be influenced by genetic variation that is also common in the population.
  • Also states that common variants that cause common diseases must have a small genetic effect on the phenotype, otherwise a larger proportion of the population would have these common diseases.
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4
Q

What does the fact that common disease is caused by common variants mean for the penetrance of those variants?

A

It means that the penetrance (effect size) for any single common variant must be smaller than that of any single rare variant.

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5
Q

What is heritability?

A
  • A measure of how well differences in people’s genes (genotype) account for differences in their traits (phenotype).
  • Heritability is assigned a score between 0 and 1
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6
Q

What does a heritability score of one mean?

A

A heritability score of one indicates that all of the variability in a trait comes from genetic differences, with no contribution from environmental factors.

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7
Q

What heritability score is generally considered high enough for a particular trait to be worth studying? Why is this?

A
  • heritability score above 0.4
  • This is because there’s enough variation in that trait to be detected
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8
Q

Why are twin studies used to calculate heritability scores?

A

Because twins have similar environments so theroretically any differences between the twins that you see in a trait will be due to differences within their genes.

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9
Q

Explain how to carry out a twin study?

A
  • Measure the concordance of a treat in both monozygotic twins and then measure the concordance of that same trait in both zygotic twins
  • You then plot these concordance measurements onto a graph
  • A Heritability score, the difference between the concordance of monozygotic twins and dizygotic twins, can then be calculated from the study
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10
Q

In a twin study what does a trait having a high concordance mean?

A

It means that a trait is more similar between the individual twins that are studied

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11
Q

In a twin study, if there’s a large difference between the concordance of a trait between monozygotic and dizygotic twins what does this mean?

A
  • The bigger the difference in concordance between dizygotic twins compared to monozygotic twins, the more that trait is determined by differences in genetics
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12
Q

Why does a large difference in concordance of a trait between monozygotic and dizygotic twins mean that there are differences in the genes associated with that trait between the 2 types of twins?

A
  • This is because monozygotic twins share 100% of their genetics with each other while dizygotic twins only share 50% of their genetics with each other
  • Also, both the monozygotic and dizygotic twins will have been exposed to very similar environmental factors
  • This means that the only real reason for the difference in concordance of that trait is due to the difference in the amount of genetics that are shared between the 2 types of twins
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13
Q

What is the most common type of genetic variation within the human genome?

A

Single nucleotide polymorphisms/single nucleotide variants

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14
Q

What is a Genome-wide association study?

A

Study of common variants across the genomes of a number of individuals, both with and without a common trait (e.g. a disease) to see which common variants are associated with a particular trait

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15
Q

Apart from performing whole genome sequencing, what other technique can be used to perform a genome wide association study?

A

Genome wide SNP microarrays

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16
Q

How is SNP microarray data analysed inititially?

A
  • The SNP microarry allows for the genotype of every SNP on the array to be identified
  • This then allows for data to be produced which groups the genotype for every SNP into 3 distinct genotypes, homozgous for one SNP allele; homozygous for the other SNP allele or heterozygous, for every single person that’s sequenced
17
Q

Once microarry data is used to place individuals into 3 distinct genotypes based on the alleles they possess for each SNP, how is the data analysed further?

A

SNP microarray data is then converted into a binary code

18
Q

Below is an example of the binary code that SNP microarray data is converted into, what does each number mean?

A
  • 0 means that a person doesn’t carry any copies of the rare allele at that position.
  • 1 means that a person carries one copy of the rare allele
  • 2 means that a person has 2 copies of the rare allele
19
Q

For SNP microarray data is there any significance to the way the particular alleles for a SNP are presented?

A

The most common allele for any position where a SNP occurs is stated first while the less common allele is stated afterwards

20
Q

Why is SNP microarray data able to identify the genotype for every single SNP within a person’s genome despite the fact that not every single SNP is assayed?

A
  • Because we know that particular SNPs are inherited together so if a particular SNP is identified on the SNP microarray then you are able to say that a person’s genome also contains SNPs associated with the one found on the array
  • This is known as SNP-SNP association, or linkage disequilibrium (LD)
21
Q

Define linkage disequilibrium

A

The difference between the observed frequency of a particular combination of alleles at two loci and the frequency expected for random association (e.g. homologous recombination).

22
Q

How is the lnkage disequilibrium between two SNPS affected by the physical distance of those SNPs on a chromosome?

A

Linkage disequilibrium between two SNPs decreases with physical distance on a chromosome as the further apart they are they more likely those SNPs will be seperated/inherited separately as a result of a recombination event between them.

23
Q

Apart from physical distance between 2 SNPs what else can affect the linkage disequilibrium between 2 SNPs?

A
  • Region of genome in which the SNPs are located
  • E.g. recombination hotspots - where a large amount of recombination occurs
24
Q

Where are most SNPs/SNVs located within the genome? Why is this?

A
  • Most SNPs/SNVs are located within non-coding regions of the genome
  • The reason for this is because there is a higher selection pressure within the exome (coding region) compared to the non-coding regions and the reason why that is is to make sure that harmful mutations aren’t incorporated into the exome as to not affect protein function.
25
Q

Why is there a higher selection pressure on variants/mutations within the coding regions compared to the non-coding regions of the genome?

A

To make sure that harmful mutations aren’t incorporated into the exome as to not affect protein function

26
Q

Since most SNPs/SNVs are found in non-coding regions what does this mean for the way they can affect the expression of a particular gene?

A

It means that although most SNPs can’t affect whether a particular gene is expressed or not they can affect how much a particular gene is expressed.

27
Q

How can GWAS data be analysed?

A
  • Once you Identify the genotypes of a SNP associated with a particular trait for all the individuals being studied, you convert each genotype into an allele dosage (encoding each genotype).
  • You then plot a graph of the measurement of the observed trait against the allele dosage (genotype).
28
Q

When analysing GWAS data a graph of the genotype for a particular SNP against the measurement of an observed trait can be produced. What can this graph be used to calculate?

A
  • Can be used to calculate the effect size for that variant/allele - This tells you the effect of having the less common allele has on a particular trait per copy of the less common allele for a particular SNP
  • Can also be used to calculate the P-value for that SNP - indicates the significance of the association between a trait and a SNP
29
Q

What is a manhattan plot?

A

It’s a graph used to present GWAS results by plotting the -log10(p-value) for every SNP against the position in the genome to see if a particular SNP is significantly associated with a particular trait.

30
Q

What is the Bonferroni correction?

A
  • Used to produce a threshold significance value in a GWAS study that indicates that a SNP must be associated with the trait if its P value is above the threshold
  • If the number of tests (SNPs genotyped) is n, we set the threshold to be 0.05/n
31
Q

If you identify a SNP that is significantly associated with disease, what are the three possibilities for why that result was produced?

A
  • There is a causal relationship between SNP and disease
  • The marker is in linkage disequilibrium with a causal locus (linked to SNP that causes the disease)
  • False positive
32
Q

What method could you use verify the results of a GWAS study?

A

Repeat the study with the same/larger population size compared to the first study and see if the result was replicated.