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Lect 3: Models of CD (1) Planning stage: Gathering basic knowledge (G1:…
Lect 3: Models of CD
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Genome wide studies -> GWAS or GWLS dep on families available
- Human Genome Mapping Project + SNPmap +Hapmap -> extensive study
- Impute missing date from from databases easily -> extending data
- Sufficient fully genotyped samples with complete haplotypes in database
- E.g. Impute missing genotypes based on expected linkage pattern -> exploits linkage diseqm
- Imputations -> PLINK software
- Greater the no of WGS -> greater the quality of imputed data -
- Success of method dep on degree of linkage diseqbm between tagged SNPs on target haplotypes
- x req hypothesis initially -> flexible; hypothesis generating
- Hence hypothesis free GWAS -> data -> identifies regions arnd genes that contribute to biological systems -> impt in understanding disease pathology
Each strategy -> sub-strategy - info to det plan reqd -> genome wide or selective approach
- if selective -> whole genome or single candidate gene looked ar
- dep on knowledge of previous & current studies & disease pathology
Studying extended haplotypes - lengthy DBA sections where multiple alleles inherited in specific grps
- Linkage diseqm (alleles of 2 or more genes found tgt more often than normal although equally segregated)
- Several impt genes all related to same pathway -> e.g. MHC contains key genes for T cell immunity -> widespread polymorph -> precise susceptibility allele -> difficult to identify
- But data set large -> x issue
- Combining haplotype data with GWAS data using imputation to assign HLA haplotypes -> interesting results in autoimmune liver disease primary biliary cirrhosis
Field of statistics vital - Sample size (stats confidence), case & control selection, sampling errors, publication bias
a) Prevalence & Incidence
- Incidence = no. of new cases/time
- Prevalence = total no. of cases of disease at time X (new & pre-existing cases)
- Diff reflect environmental factors
b) Family, twin, adoption studies -> check signs of heritabilityi) Family Studies - Informative but families in complex disease rare & x conform to Mendelian patterns
- Incidence of traits
- Inheritance pattern
- Geography vital -> consider migration
- Beware heritability -> when talking about genes
ii) Twin Studiesa) MZ twins (identical)
b) DiZ (non-identical)
c) Identify genetic variation levels
- higher concordance in MZ vs DZ -> sig genetic component
c) Linkage analysis -> map susceptibility loci -> families and several affected individuals
d) Association analysis -> narrow down region -> x several affected individuals do this
e) Identify DNA seq variants conferring susceptibility
f) Define biochemical action
Studying selected chromosomal region - 2nd phase process & undertaken if prior studies identified regions of interest
- Tagged SNPs indicate association with specific gene but more likely across an area
- High resolution analysis using tagged SNPs -> identify association peaks in/arnd genes
- However commercial SNP chip unavailable/costly to apply GWAS to single chromosome
Investigating pathways
- Systems biology -> focuses on study of pathway interaction
- With prior data -> able to study CD
- E.g. Identification of NOD2 (CARD15) link to pathways associated with immune tolerance to commensal gut bacteria -> Crohn's disease -> value of styuding processes instead of individual genes in CD
Candidate gene approach - single gene - Hypothesis driven -> so limited to observing associations at specified loci
- loci selected -> hv some fun_al r/s bet gene pdt & disease
- limitations:
- lack understanding of human biology & disease pathology
- Narrow view -> miss other associations
- But if prior studies solid -> high resolution genotyping of gene to identify polymorph associated with disease susceptibility relevant
- Early pathogenesis of diseases poor -> late onset of disease -> poor hypothesis -> gene candidate selection poor -> gene studies rarely successful
- Pathology changes but genome same -> so genome wide then observe pathways, haplotypes & candidate genes
- Biological defects known: target specific gene or genes in biochemical pathway
- If unknown biological defect or characterised with uncertainty
o Whole genome scanning –> microsatellite/SNPs
o Multiple candidates -> multiple pathways
Positional approach to select candidate
- Single gene (selected candidate)
- Chromosomal region (e.g. MHC)
- Whole chromosome & GWAS
Functional approach to select candidates -> hypothesis driven
- Candidate region/gene -> MHC on chromosome 6p21.3 -> genetic association with disease -> high as impt with immunity
- Pathway (HSCR)
- Both -> Complementary -> CARD15 (protein)/NOD2(gene) in Crohn’s Disease