4. Genetics and disease 3 - polygenic disorders and somatic disease Flashcards
what are polygenic disorders?
- many genes or gene variants are involved
- inheritance is unclear due to the number of genes involved
- environmental risk factors
- genetic risk factors which usually lead to early onset
what are polygenic disorders also known as?
complex or multifactorial disorders
how are multiple genes involved in polygenic disorders?
- Epistasis
- Genetic heterogeneity
what is Epistasis?
the interaction between genes that are not alleles.
the expression of 1 gene or gene variant is dependant on the expression of another
what is genetic heterogeneity?
when multiple genes or genetic factors contribute to the phenotype
what kind of disease burden do polygenic disorders have?
a very high disease burden
How are polygenic disorders studied?
across a population - the larger the better
make a liability model
what is a liability model?
liability = the contributing factors to a disease
across the population it will show a normal distribution with a threshold above which disease develops
genetic factors can shift the curve increasing the risk of developing disease
what is heritability?
the proportion of disease risk that is attributed to genetic factors
how can we study heritability?
- twin studies to study phenotypic variations over time in different environments = environmental factors
- family studies to study siblings that genetically similar but not identical = genetic factors
- adoption studies which study siblings split and raised in different environments = environmental factors
Problems with genetic analysis: poor genotype/phenotype correlation
- genetic heterogeneity
- several susceptibility genes
- different susceptibility genes in different population
- variable penetrance - not all susceptible individuals are affected
- phenocopy
what is phenocopy?
when the disease is due to just environmental factors not any genetic factors
what are the methods of identifying genes in polygenic disorders?
- candidate genes = best guess
- linkage analysis = non parametric methods are more successful
- Association studies = genome wide association studies
what are genome-wide association studies (GWAS)?
- much more successful but you need a large cohort to get statistical significance
- SNPs
- screen the cohort
- HapMap
- thousand genomes project
what results do you get from a genome wide association study?
- case cohort = people with the disease
- control cohort = people without the disease
- sequencing the genome and see what SNPs are in the population and see if certain ones are elevated in the case cohort
- produce a manhattan plot with spikes at point with more common SNPs
how do you interpret a GWAS?
- the highest point is the lead SNP which is the most statistically significant SNP in the population but it is not always the causative SNP
- fine-mapping
- linkage disequilibrium
what is fine mapping?
- using linkage disequilibrium
- makes a heat map to find location on the genome which is likely to have inherited as a haplotype
- areas with high linkage disequilibrium have fewer haplotypes associated with them
- look at areas of interest with candidate genes
- test the hypothesis
- targets for treatments once identified
what is a haplotype?
a physical grouping of genomic variants or polymporphisms that tend to be inherited together
GWAS and autism spectrum disorder
- SNP on chr5 p arm between 2 genes
- lots of common varients that have small effects
- rarer variants that tend to have larger effects
- most have a combo of SNPs
- suggests a genetically predisposed susceptibility
what is a quantitative trait?
a continuous, measurable phenotype that’s due to genetic and/or environmental influences
eg weight/height
NOTE
a disease can be a quantitative trait but not all quantitative traits are diseases
what are quantitative trait loci (QTL)?
- the loci where the alleles affect this variation
- QTL mapping studies association between alleles and a continuous trait
- these loci effect things like transcription, post-transcription and post-translation regulation
EXAMPLE
Achondroplasia where a single gene loci has a big impact on a quantitative trait
what does GWASs study?
Association between alleles and binary traits
Expression QTLs
effect expression of protein coding genes and non coding RNAs
A single SNP can have a large effect on protein expression
QTLs: effect on transcription regulation
gene varients effect epigenetic regulation:
1. variants in CpG island can change the point of methylation
2. variants in histones cause complications like remodelling of chromatin
3. variants in regulation elements can change binding of enhancers and promoters
QTLs: effects on post-transcriptional regulation
- variants can change the alternative RNA splicing
- variants can cause differential RNA editing
- variants can cause alternative polyadenylation and effect the regulation of RNA
QTLs: effects on post translational regulation
- varients can cause disorder of protein structure
- variants can cause altered protein expression
- variants can cause altered post translational modifications
QTLs: effects on the metabolic regulation and microbiome interaction
- variants can cause different levels of metabolites
- variants can cause altered microbial composition
Example of polygenic disorders: schizophrenia
- a sever long term mental health condition
- 81% heritable but alleles associated with schizophrenia have very low penetrance
- problems with linkage analysis due to phenocopy and low penetrance
- GWAS show association 6p - HLA region and copy variations at 1q, 15q, 22q
Example of polygenic disorders: Type 1 diabetes
- Insulin-dependant, early onset, autoimmune disease
- non-parametric allele sharing to identify genetic risk factors - inherit common chromosomal regions
- animal models - meh
- GWAS - >40 gene loci, HLA 6p cluster associated with autoimmunity
- epistasis and genetic heterogeneity is a problem
Example of polygenic disorders: type 2 diabetes
- Insulin-independent, late onset, mainly dietary cause (high fat/sugar)
- most methods to identify genes unsuccessful
- GWAS - ~30 loci found, HLA not important and no major predisposing loci
Example of polygenic disorders: CVD - lipid metabolism
- familial hypercholesterolaemia
- autosomal dominant
- high serum cholesterol
- mutation in Low density lipoprotein receptor gene - cholesterol backed up into the circulation and taken up into macrophages = foam cells
- GWAS - 30 loci associated with circulating lipid levels
Example of polygenic disorders: CVD - hypertension
- easy to treat with medication
- angiotensin causes blood vessel constriction and familial hypertension link to angiotensin gene
- angiotensin converting enzyme activates angiotensin but polymorphisms link to risk of heart attacks
- GWAS - 14 susceptibility loci identified
Example of polygenic disorders: coronary artery disease and myocardial infarction
GWAS identified 12 susceptibility loci
Example of polygenic disorders: Alzheimer’s disease (senile dementia)
- clear genetic predisposition
- 2nd biggest killer in the uk in 2021
- neurofibrillary tangles and amyloid deposits build up and kill of neural cells
Example of polygenic disorders: Alzheimer’s disease genes
NOTE: most studied Alzheimer’s is early onset but most cases are last onset
- amyloid precursor protein on Chr21
- presenilin 1 (Chr14) & presenilin 2 (Chr1) - mutations in early onset
- Apolipoprotein E (Chr19) - lipoprotein transport
- early and late forms
- alleles E2 and E3 are protective
- allele E4 increased risk - GWAS studies identified other loci
- most Alzheimer’s cases are late onset with no genetic origin
- epistasis and genetic heterogeneity present
Example of polygenic disorders: Alzheimer’s disease mechanism
- amyloid precursor protein
- ß-secretase (possible drug target)
- Fragments
- Aß peptide
- plaques and apolipoproteins
==== Neuronal death
Somatic defects: Cancer
- 5% caused by germline mutations like BRCA1/2
- 95% caused by sporadic somatic mutations - the risk increases as you age
- oncogenes and tumour suppressor genes are driver mutations that push towards cancer phenotypes
- loss or gain of function mutations
- need multiple genetic changes for most cancers
Somatic defects: cancer model of carcinogenesis
- carcinogens cause the mutations -> cancer
- mutations present in the cell are activated by carcinogens
Somatic defects: genetic mosaics
- more then 1 genetic population of cells from the same genetic origin
- after zygote formation 1 cell undergoes mutation and any of its daughter cells carry the mutation. All other cells are fine.
- caused by non-disjunction in embryogenesis
- mosaic distribution of otherwise lethal mutations like trisomies
Somatic defects: Genetic chimeras
- more then 1 genetic population of cells from different genetic origins
- can occur if 2 embryos merge in embryogenesis = 2 sets of germline cells
- exchange of blood stem cells in utero between non-identical twins
- bone marrow transplants will cause a chimera
