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Describe non-parametric linkage analysis. Why is this method advantageous for studying complex diseases, compared to parametric methods?. Judith Pagan. Essay Plan. Briefly describe:- parametric linkage analysis Co-segregation of genetic loci in pedigrees
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Describe non-parametric linkage analysis. Why is this method advantageous for studying complex diseases, compared to parametric methods? Judith Pagan
Essay Plan • Briefly describe:- • parametric linkage analysis • Co-segregation of genetic loci in pedigrees • Model of disease expression must be specified • Non-parametric linkage analysis • Complex disease • No disease model required • alleles or chromosomal segments that are shared by affected individuals • Shared segment analysis • Excess sharing in disease region • Hypothesis that a marker is not near a disease susceptibility gene • Allele sharing • IBD and IBS • Affected sib pairs • Linkage suggested if above the 1:2:1 ratio • Advantages • No assumptions required • Easier to collect affected sib-pairs • Parametric linkage analysis on ‘near mendelian’ families can give spurious results
Parametric linkage analysis • Analysis of co-segregation of genetic loci in pedigrees • Loci that are further apart • Recombination event will break up segregation • Main quantity of interest is the recombination fraction (θ) • Probability of recombination between two loci at meiosis • Used to calculate LOD score • Model of disease expression must be specified • Frequency of disease allele, mode of inheritance and penetrance
What is non-parametric linkage analysis? • Linkage analysis that does not require specification of a disease model • Used for complex diseases • No clear mode of inheritance • Several genes (and environmental factors) may contribute to disease risk • Looks for alleles or chromosomal segments that are shared by affected individuals
Shared segment analysis • Affected individuals will show excess sharing of haplotypes in the region of a disease causing gene • Irrespective of mode of inheritance • Principle is based on the null hypothesis that a marker is not near a disease susceptibility gene • Various methods test whether sharing at a locus is greater than expected under the null hypothesis
IBD IBS Allele sharing • Two alleles are identical-by-descent (IBD) if inherited from a common ancestor • Identical-by-state (IBS) if the same allele regardless of ancestral origin • Parents unavailable • Common alleles present or parents homozygous • If the marker is near a disease susceptibility gene • Increase in alleles shared IBD among affecteds relative to null expectation
Sibling pairs • Simplest approach is to study sibling pairs where both are affected • IBD sharing is determined by 4 meioses • Mendel’s law of equal segregation • 4 scenarios equally likely • Share zero, one or two alleles with probability ¼, ½ or ¼ respectively
Sibling pairs • Affected sib pairs (ASP) are typed for markers • Multilocus testing increases power • Linkage is suggested if chromosomal regions are showing above random 1:2:1 ratio • Testing for difference convert to something similar to a LOD score (threshold of 3.6 for IBD testing and 4.0 for IBS testing).
Sibling pairs • IBD sharing must be distinguished from alleles shared that are IBS • Shared segment analysis can be conducted using IBS or IBD data provided appropriate analysis is used • IBD analysis is more powerful but requires samples from more relatives (parental genotypes known) • Rare alleles usually implies IBD
Other groups • Shared segment analysis can be used within families • Affected sib pairs (ASP) • Affected pedigree member analysis • Modified statistical analysis • Statistical analysis packages • Genehunter, Allegro
Advantages compared to parametric linkage analysis • Performed without making any assumptions about the disease • No disease model required • Much easier to collect affected sib-pairs than extended families • Simplicity and robustness of ASP mapping • Sib pairs are well matched for age and environment • Main tool used for detecting genes involved in complex diseases
Parametric linkage analysis on ‘near mendelian’ families • Complex disease is heterogeneous • mendelian conditions included that are indistinguishable from the non-mendelian majority • Balance can be tipped by mendelian segregation of one of the many susceptibility factors • families where determinants of the disease are present in most people tested • Give spurious result • chance aggregation of affected people • e.g. early work on schizophrenia gave a lod score of 6
References • Strachan and Read (chapter 15) • Genetic linkage studies. Teare & Barrett The Lancet 2005 366, 1036-1044. • Allele-sharing among affected relatives: non-parametric methods for identifying genes. Shih & Whittemore Statisitical Methods in Medical Research 2001 10, 27-55.