Genetics of common disease

Question 1

Describe mendelian diseases

Answer 1

• Mainly due to 1 gene and one mutation
  
  • e.g CF deltaF508 - a three-base deletion, which removes a phenylalanine codon.
• Inheritance pattern is clear (recessive loss of function, autosomal dominant, X-linked)
• Minimal influence from environment

Question 2

Describe common diseases

Answer 2

• Are MULTIFACTORIAL
  
  • Multiple genes affect the disease trait
  • There is a strong influence of the environment
  • The effect of every single gene may be neglibile
    
    • Multiple common alleles influence susceptibillity

Question 3

What is heritability?

Answer 3

Measure of how well differences in peoples genes account for differences in their traits

Question 4

What does a heritability close to 1 indicate?

Answer 4

Almost all variability in a trait comes from genetic differences, with very little contribution from environment factors

e.g Cystic Fibrosis has a heritability of 1

Question 5

How do we calculate heritability?

Answer 5

Using twin studies

• Monozygotic twins have 100% DNA
• Dizygotic twins have 50% DNA
  
  • Both share the same environment therefore any differences would be due to disease/trait

Question 6

How do you interpret twin studies?

Answer 6

When looking at a trait e.g height measure height in both sets and assess their concordance

• The higher the concordance = more similar they are going to be

The more the trait is determined by a genetic contribution, the greater the difference in concordance because monozygotic twins share 100% DNA, dizygotic twins share 50% DNA (essentially more genes involved = greater difference)

Once our heritabillity study has been carried out we identify the genes which contribute to that trait

Question 7

What is concordance?

Answer 7

It’s how similar phenotype is

Question 8

How can we find out which genes contribute to a trait/disease?

Answer 8

Through genetic association

• GWAS (genome wide association study)

Question 9

How is a GWAS study carried out?

Answer 9

• Method for identifying gene variants (SNPs) involved in complex diseases by scored for hundreds or thousands of individuals who have the disease and controls (who do not)
• A typical GWAS collects data to find out the common variants in a number of individuals, bot with and without a common trait (e.g. a disease), across the genome, using genome wide SNP arrays.

Question 10

How does a SNP microarray work?

Answer 10

1. DNA sample prepared and fragmented
2. DNA tagged/ labelled with fluorescent probe
3. Mix DNA with slide, which contains oligonucleotides which match the region of the genome around each variant being tested
4. If DNA sample contains a variant, then it will bind to specific matching oligonucleotides and fluoresce
5. Signal is produced and detected

Question 11

Encoding SNP chip data for analysis

Answer 11

After we have our data from the SNP chip we will convert it in a computer to get a code.

This works out what the genotypes of individuals are and converts them into a binary code that computer programmes deal with

Question 12

Explain how we use SNP chips and avoid measuring all the genetic polymorphisms

Answer 12

• Rather than directly measuring genotypes at all genetic polymorphisms, we rely on the associations between SNPs we do assay and SNPs we don’t assay
• SNP-SNP association, or LINKAGE DISEQUILIBRIUM is the fundamental ability to sample a whole genome with few SNPs

Question 13

What is linkage disequilibrium?

Answer 13

Non random association of alleles at two or more loci in a general population

Linkage disequilibrium between 2 SNPs decreases with physical distance as you are more likely to have recombination between them

If LD is strong (chance of variants in that region inherited together is higher), fewer SNPs are needed to capture variation in that region, therefore cheaper and easier way to analyse

Question 14

What analysis is carried out to indicate how likely a variant is to be associated with a trait?

Answer 14

Statistical analysis (p- value indicates the significance of the association)

• Lower P-value = more significant

all of the p-values for all of the SNPs on the chip are then plotted on a Manhatten Plot

high peaks = high significance between a gene region and trait

Question 15

What are the three possibilities if a SNP is associated with disease?

Answer 15

• There is a causal relationship between SNP and disease
• The marker is in linkage disequilibrium with a causal locus
• False posotive

Question 16

What is the short term goal of GWAS?

Answer 16

• Short-term Goal: Identify genetic regions that explain differences in phenotype among individuals in a study population.
  
  • Qualitative: disease status, presence/absence of congenital defect
  • Quantitative: blood glucose levels, % body fat, heart rate
• If association found, then further study can follow to:
  
  • Determine the causal variants
  • Understand mechanism of action and disease etiology in individuals
  • Characterise relevance and/or impact in more general population

Question 17

What is the long term goal in GWAS?

Answer 17

To inform process of identifying and delivering better prevention and treatment strategies

Question 18

How do you interpret statistical results?

Explain the bonferroni correction

Answer 18

• If we set the p-value threshold for each test to be 0.05, by chance we will “find” about 5% of the SNPs to be associated with the disease.
• Bonferroni correction - if the number of tests (SNPs genotyped) is n, we set the threshold to be 0.05/n.