How old is this mutation? - a study of three Ashkenazi Jewish founder mutations.
BACKGROUND
Several founder mutations leading to increased risk of cancer among Ashkenazi Jewish individuals have been identified, and some estimates of the age of the mutations have been published. A variety of different methods have been used previously to estimate the age of the mutations. Here three datasets containing genotype information near known founder mutations are reanalyzed in order to compare three approaches for estimating the age of a mutation. The methods are: (a) the single marker method used by Risch et al., (1995); (b) the intra-allelic coalescent model known as DMLE, and (c) the Goldgar method proposed in Neuhausen et al. (1996), and modified slightly by our group. The three mutations analyzed were MSH2*1906 G->C, APC*I1307K, and BRCA2*6174delT.


RESULTS
All methods depend on accurate estimates of inter-marker recombination rates. The modified Goldgar method allows for marker mutation as well as recombination, but requires prior estimates of the possible haplotypes carrying the mutation for each individual. It does not incorporate population growth rates. The DMLE method simultaneously estimates the haplotypes with the mutation age, and builds in the population growth rate. The single marker estimates, however, are more sensitive to the recombination rates and are unstable. Mutation age estimates based on DMLE are 16.8 generations for MSH2 (95% credible interval (13, 23)), 106 generations for I1037K (86-129), and 90 generations for 6174delT (71-114).


CONCLUSIONS
For recent founder mutations where marker mutations are unlikely to have occurred, both DMLE and the Goldgar method can give good results. Caution is necessary for older mutations, especially if the effective population size may have remained small for a long period of time.
Greenwood
Celia M T
CM
Genetics and Genome Biology, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada.
Sun
Shuying
S
Veenstra
Justin
J
Hamel
Nancy
N
Niell
Bethany
B
Gruber
Stephen
S
Foulkes
William D
WD
D018703:Founder Effect; D005787:Gene Frequency; D017491:Genes, APC; D019398:Genes, BRCA1; D020022:Genetic Predisposition to Disease; D006801:Humans; D007585:Jews / Q000235:genetics*; D015233:Models, Statistical; D051718:MutS Homolog 2 Protein / Q000235:genetics; D009154:Mutation; D013995:Time
C497172:MSH2 protein, human; D051718:MutS Homolog 2 Protein
Am J Hum Genet. 2005 Mar;76(3):449-62
15700229
Ann Hum Genet. 2008 May;72(Pt 3):310-8
18215206
Am J Hum Genet. 1998 Jun;62(6):1381-8
9585613
Genome Biol. 2009;10(1):R7
19161619
Am J Hum Genet. 2001 Jul;69(1):159-78
11410841
Nat Genet. 1995 Feb;9(2):152-9
7719342
Am J Hum Genet. 2002 Dec;71(6):1395-412
12454801
Genet Epidemiol. 2006 Jan;30(1):48-61
16206141
Am J Hum Genet. 1998 Feb;62(2):459-73
9463316
Annu Rev Genomics Hum Genet. 2000;1:225-49
11701630
Am J Hum Genet. 2001 Apr;68(4):978-89
11254454
Am J Hum Genet. 1999 Dec;65(6):1800-2
10577940
Nat Rev Genet. 2001 Nov;2(11):891-8
11715044
Genet Test. 2001 Summer;5(2):141-6
11551102
Fam Cancer. 2004;3(3-4):249-57
15516849
Am J Hum Genet. 2003 Dec;73(6):1250-60
14624392
Bioinformatics. 2002 Jun;18(6):894-5
12075030
Am J Hum Genet. 1996 Sep;59(3):633-43
8751865
Cancer Res. 2008 Apr 1;68(7):2145-53
18381419
Am J Hum Genet. 2003 Apr;72(4):812-22
12612865
Hum Genet. 1990 Apr;84(5):449-54
1969843
J Med Genet. 2005 Oct;42(10):766-8
16199548
Am J Hum Genet. 2003 Nov;73(5):1162-9
14574645
Am J Hum Genet. 1996 Feb;58(2):271-80
8571953