12. Tools for complex traits Flashcards

1
Q

Explain what are complex traits

A

Complex traits - traits controlled by multiple genes and the environment
Can have:
- binary phenotype - disease / no disease
- continuous phenotype - height

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2
Q

What are the causes a phenotype?

A

P = G + E

Trait phenoype is a result of interaction betweent he genetic and environmental determinants for the trait

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3
Q

What is the genetic architecture of a trait?

A

Trait genetic architecture - the network of number and action of causal variants for a trait

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4
Q

Are all traits P=G+E at 50/50?

A

No, different phenotypes have different divisions between G adn E -ex:
- Huntington’s - 100% G
- Drug addiction - 50/50% G and E
- Malaria - complicated interaction can’t be easily decided

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5
Q

What are the genetic markers used for finding trait genes in genomes?

A

Single nucleotide polymorphisms (SNPs) in genomes - nucleotide variation at the posiition - easy to detect / analyse

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6
Q

How are SNPs passed on parentally?

A

For all loci two alleles on two homologous chromosomes - at an SNP can be homozygous / heterozygous

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7
Q

Explain what types of loci are there in terms of their alleles

A

Loci for a specific population can be:
- monomorphic - one allele at the locus in the population
- polymorphic - 2+ alleles segregating at the locus

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8
Q

What could be the sequence options for a polymorphic marker?

A

A polymorphic marker couls be AA, AB, BB - ex: a marker which is polymorphic for G and T -> GG, GT, TT (?? why no TG - maybe because considering only one strain?)

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9
Q

What could be the types of traits?

A

Types of traits:
- recessive / dominant
- autosomal / sex-linked

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10
Q

What are the trait aspects investigated if the trait is considered to be a Mendelian trait?

A
  • observed pattern of inheritance
  • recessive / dominant
  • autosomal / sex-linked
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11
Q

What is the inheritance pattern of autosomal recessive, autosomal dominant, and sex-linked recessive genes?

A
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12
Q

Define what is heritability

A

Heritability - proportion of phenotypic variation that can be attributed to differences in genetic factors

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13
Q

How is heritability estimated?

A

Heritability is traditionally estimated from relatives: phenotypic similarity - known relationships -> known level of heritability - how much of phenotypic similarity explained by genetic similarity

A range 0-1:
- if 0 - completely environmentally determined phenotype
- if 1 - completely genetically determined phenotype

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14
Q

What can be used to measure if theoretical heritability estimates are correct?

A

Genomics - SNPs markers can be used to measure true heritability for specific traits

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15
Q

Both parent-offspring and full-sib heritability estimates are 0.5, for which pair markers are expected to vary more?

A

Between full-sibs will vary more than parent-offspring because the child will definitely share all their alleles with their parents but not necessarily with the siblings if they inherited different alleles

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16
Q

How are markers chosen in case-control association studies?

A

Markers must be chosen in case -control association studies - too expensive / time-consuming to look at all genome - use haplotype blocks instead of single markers - see their LD / diversity within the block in disease vs healthy group

Usually looked at haplotype blocks - tagging SNPs - SNP panels chosen - identify genes around a causal variant

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17
Q

How can genomic data be used to predict relationships?

A

Genomics can be used to predict relationships - based on SNP similarity scores
- no longer need pedigrees
- need to account for other phenotypic causes - ex: age, sex

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18
Q

Summary 1

A
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19
Q

What is a case-control association study?

A

Case-control association study - don’t know which genes/variants involved - see what segregates with the disease - need observable markers - SNPs:
- diseased
- healthy

If there is difference in allele frequencies between groups - locus has sufficiently large effect on the disease

Ex: disease caused by recessive mutant D allele - H allele healthy -n found alle freq disequilibrium in diseased group

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20
Q

How are markers in case-control association studies chosen?

A

Markers must be chosen in case -control association studies - too expensive / time-consuming to look at all genome - use haplotype blocks instead of single markers - see their LD in disease vs healthy group

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21
Q

What is linkage disequlibrium?

A

Linkage disequilibrium (LD) - occurrence of conbinations of alleles at two loci more often than expected - non-random association of alleles at two or more loci

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22
Q

What are tagging SNPs?

A

Tagging SNPs - a subset that explains majority of variation

Distributed through the genome - represent haplotype blocks

23
Q

What are SNP panels?

A

SNP panels (chips) - pre-determined SNP variants - 700,000 in human genome - selected as tagging SNPs

24
Q

Why are surrounding genes informative when identifying a disease-causing allele?

A

When mutation occurs - variant segregates with neighbouring genes - over generations the haplotype piece decreases in size but surrounding genes likely to stay - low haplotype diversity around the causal variant

25
Q

What are important aspects of samples in case control association studies which could influence the results?

A

Important to precisely choose diseased - healthy controls with similar backgrounds to decrease background variation as much as pssible - ex: age, sex, geographic location, ethnicity - otherwise additional variation will be introduced which will be detected but not contributing to disease

26
Q

How is the significance of identified association assessed?

A

Statistical analysis - test for independence - logistic regression allows other explanatory variables to be fitted - choose best candidate

Disease status - complex - hard to find single causal allele - biuld models of risk

27
Q

Explain what is GWAS

A

Genome-wide association studies (GWAS) - an approach to compare genomes from different people to find genetic markers associated with a particular phenotype / disease

28
Q

How is the effect of an allele on the disease represented in GWAS?

A

Known B to be disease-causing

29
Q

What are the important aspects to consider when performing GWAS?

A
  • Stringent signifincance thresholds to prevent false positives - identifying association when there’s none
  • Carefully choosing controls
30
Q

How are GWAS loci results presented?

A

Manhattan plot - the higher the peak of a particular locus - the higher significance (association with the phenotype) - low are non-significant loci for this trait

31
Q

Summary 2

A
32
Q

What are the limitations of GWAS?

A

GWAS limitations:
- identified SNPs not causal - only in LD with the causal - because LD regions contain many genes
- associated SNPs are non-coding regions - in introns - could be regulatory or in LD with coding SNP at a distance
- identified variants are usually associated with risk rather than causation - disease complex genetic architecture - many genes with small effects

33
Q

What are polygenic traits?

A

Polygenic traits - phenotypes influenced by several genes

Contribution of each chromosome to the disease - depends on the length - the longer the more genes can accommodate

34
Q

What greatly influences the significance of GWAS results?

A

Sample size - the more involved - the more significant are the results - stronger associations found - higher support for polygenic traits

35
Q

Is GWAS sufficient on its own to infer prediction for disease?

A

No - after identifying loci / genes in GWAS - see their function, build models of function - in what pathways / mechanisms they act to see if it could be causing the disease

36
Q

Give an example disease which was uncovered using GWAS and subsequent functional studies

A

Urate level regulation - gout - urate accummulation - theories:
- level regulation (poor excretion): export into urine or re-uptake into blood -> GWAS found LD in 8 transporters
- excess synthesis: no association found in GWAS => regulation has greater role than synthesis

37
Q

Summary 3

A
38
Q

Give an example of a recent application of GWAS for personalised medicine

A

Some people experience severe covid - genetic determination of the phenotype - loci involved suggest drug targets

For GWAS sequenced severe covid patients + controls before covid exposure from UK Biobank - identified 4 regions in LD => identified genes investigated - involved in viral defense + mediators of inlammatory organ damage + low expression of IFNAR2, high expression of TYK2, CCR2 - drug with the same target already developed => baricitinib for arthritis downregulates TYK2 => reduces severe covid mortaloity by 20%

39
Q

Explain what is precision / personalised medicine

A

Precision / personalised medicine - used genetic information in combination with lifestyle and environment to offer the best treatment approach

Genome-guided treatment - pharmacogenomics

P = G + E

40
Q

What is essential in effective precision medicine?

A

Effective genetic diagnostic tests and risk prediction from results

41
Q

What kind of genetic diagnostic tests are used in personalised medicine?

A

Genetic diagnostic tests:
- single gene disorders - ex cystic fibrosis - single autosomal recessive CFTR gene BUT there are 2000 variants of mutation in CFTR that cause - test for 20 most common - because there is so many disease variants - degree of severty varies between patients
- complex disorders

42
Q

What kind of tests can be performed to forsee disease

A
  • Test parents if carriers
  • Prenatal testing
  • Test newborn
43
Q

Explain genome sequencing benefit in dealing with breast cancer

A

High heritability of BRCA1 and BRCA2 - with specific variants women have 50-80% chance of breast cancer - likelihood increases with age

Environment influences too but general population chance of breast cancer 12%

-> routine screening thorugh mammograms for patients with genetic BRCA1, BRCA1 profiles

44
Q

When genome sequenced what is used to determine the risk of a patient for particular disease?

A

Polygenic risk score - sums the effects of alleles in the specific patient - predicts genetic components for phenotype - need to: estimate SNP effect + choose SNPs to be included

45
Q

How are SNPs from GWAS chosen to be included in polygenic scores?

A

Only SNPs with significant peaks are included into polygenic scores - stingent threshold of significance - can set own p value level for signifcance to include more/less SNPs

46
Q

What is the risk of choosing too many SNPs for calculating a polygenic risk score?

A

Additional SNPs included in polygenic risk scores could create noise - best threshold depends on genetic architecture of the specific disease for which the polygenic score is counted

47
Q

How do the polygenic risks scores of breast cancer change with age?

A
48
Q

What are the particular tumour markers?

A
49
Q

What are the important aspects of genome-guided treatment

A
50
Q

How is cystic fibrosis treated after considering the genomics behind each patient?

A

Personalised drug chosen for the specific carried mutation - not a general approach

51
Q

How are cancers treated after considering the genomics behind each patient?

A

Specific targeted therapies for genetically caused cancers

52
Q

Explain how genetics influences warfarin dosing

A

Warfarin - anticoagulant - used to slow down blood clotting - two genes known to be involved with sensitivity to warfarin:
- CYP2C9 - enzyme responsible for warfarin metabolism
- VKORC1 - warfarin drug target

53
Q

Summary 4

A