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genetic disorders 3 - Coggle Diagram

- - - - alleles identified to be associated with this condition are of low penetrance
        
        therefore having the genes doesn't mean you will definitely develop the disease
    - - low penetrance
      - phenocopy
  - - - GWAS
      - non-parametric allele sharing
      - the HLA gene cluster 6p21 proves important in disease
      - what makes it difficult
        
        genetic heterogeneity and epistasis
        
        disease onset also usually dependent on an environmental factor too
  - - - high levels of LDL (cholesterol) in blood due to mutations in LDL receptor
    - - high blood pressure
      - associated with angiotensin pathway
  - - - neuronal cell death
      - neurofibrillary tangles
      - amyloid protein deposits
        
        it is plaques of apolipoprotein (and stuff) that cause cell death
    - - most cases are late onset with no known genetic origin
- - - - classical
        
        exposure to chemical drives mutation... expansion... cancer
      - alternative
        
        pre-existing driver mutation... carcinogen exposure... expansion... cancer
  - - - expression of phenotype is therefore variable depending on frequency of condition throughout body
  - - - e.g. germline cells can be genetically different to blood
    - - can occur through the fusing of two embryos in uterus
      - another way is through a bone marrow transplant:
        
        as now obviously the blood cells will be genetically different
- - - - polygenic disorders
        
        many genes involved
        
        epistasis
        
        expression of one gene may depend on a separate gene
        
        interaction between genes that aren't alleles
        
        genetic heterogeneity
        
        multiple genes contribute to one phenotype
- - - - several genes contribute to the phenotype
      - variable penetrance
    - - unhealthy lifestyle leads to disease in absence of genetic factors (purely environmental)
  - - - look at genetic disorders 1
    - - large sample size of people used to observe genetic patterns in mutations and phenotypes (i think)
        
        version of this is... GWAS (Genome Wide Association Studies)
        
        uses observation of SNPs, and common SNPs associated with phenotypes
        
        why does observation of SNPs actually work in indicating related genes to the phenotype?
        
        linkage disequilibrium
        
        non-random association of alleles
        
        1 more item...
        
        interpreting GWAS results
        
        a graph will be created, which is every gene liderally ever (X), and frequency (Y, i think)
        
        then you identify the peak with abnormal SNPs going on... and zoom in real close on this peak
        
        a threshold value (horizontal line) is added to the graph, where all peaks above it are significant and worth investigating
        
        1 more item...
      - candidate gene = scientists chosen gene to observe (i think)