Genome scan in familial late-onset Alzheimer's disease: a locus on chromosome 6 contributes to age-at-onset.

Alzheimer's disease (AD) is a common, genetically complex, fatal neurodegenerative disorder of late life. Although several genes are known to play a role in early-onset AD, identification of the genetic basis of late onset AD (LOAD) has been challenging, with only the APOE gene known to have a high contribution to both AD risk and age-at-onset. Here, we present the first genome-scan analysis of the complete, well-characterized University of Washington LOAD sample of 119 pedigrees, using age-at-onset as the trait of interest. The analysis approach used allows for a multilocus trait model while at the same time accommodating age censoring, effects of APOE as a known genetic covariate, and full pedigree and marker information. The results provide strong evidence for linkage of loci contributing to age-at-onset to genomic regions on chromosome 6q16.3, and to 19q13.42 in the region of the APOE locus. There was evidence for interaction between APOE and the locus on chromosome 6q and suggestive evidence for linkage to chromosomes 11p13, 15q12-14, and 19p13.12. These results provide the first independent confirmation of an AD age-at-onset locus on chromosome 6 and suggest that further efforts towards identifying the underlying causal locus or loci are warranted.

Estimation and visualization of identity-by-descent within pedigrees simplifies interpretation of complex trait analysis.

Linkage analysis identifies markers that appear to be co-inherited with a trait within pedigrees. The inheritance of a chromosomal segment may be probabilistically reconstructed, with missing data complicating inference. Inheritance patterns are further obscured in the analysis of complex traits, where variants in one or more genes may contribute to phenotypic variation within a pedigree. In this case, determining which relatives share a trait variant is not simple. We describe how to represent these patterns of inheritance for marker loci. We summarize how to sample patterns of inheritance consistent with genotypic and pedigree data using gl_auto, available in MORGAN v3.0. We describe identification of classes of equivalent inheritance patterns with the program IBDgraph. We finally provide an example of how these programs may be used to simplify interpretation of linkage analysis of complex traits in general pedigrees. We borrow information across loci in a parametric linkage analysis of a large pedigree. We explore the contribution of each equivalence class to a linkage signal, illustrate estimated patterns of identity-by-descent sharing, and identify a haplotype tagging the chromosomal segment driving the linkage signal. Haplotype carriers are more likely to share the linked trait variant, and can be prioritized for subsequent DNA sequencing.

Genome scan of age-at-onset in the NIMH Alzheimer disease sample uncovers multiple loci, along with evidence of both genetic and sample heterogeneity.

Alzheimer's disease (AD) is a common neurodegenerative disorder of late life with a complex genetic basis. Although several genes are known to play a role in rare early onset AD, only the APOE gene is known to have a high contribution to risk of the common late-onset form of the disease (LOAD, onset >60 years). APOE genotypes vary in their AD risk as well as age-at-onset distributions, and it is likely that other loci will similarly affect AD age-at-onset. Here we present the first analysis of age-at-onset in the NIMH LOAD sample that allows for both a multilocus trait model and genetic heterogeneity among the contributing sites, while at the same time accommodating age censoring, effects of known genetic covariates, and full pedigree and marker information. The results provide evidence for genomic regions not previously implicated in this data set, including regions on chromosomes 7q, 15, and 19p. They also affirm evidence for loci on chromosomes 1q, 6p, 9q, 11, and, of course, the APOE locus on 19q, all of which have been reported previously in the same sample. The analyses failed to find evidence for linkage to chromosome 10 with inclusion of unaffected subjects and extended pedigrees. Several regions implicated in these analyses in the NIMH sample have been previously reported in genome scans of other AD samples. These results, therefore, provide independent confirmation of AD loci in family-based samples on chromosomes 1q, 7q, 19p, and suggest that further efforts towards identifying the underlying causal loci are warranted.

Evidence for three loci modifying age-at-onset of Alzheimer's disease in early-onset PSEN2 families.

Families with early-onset Alzheimer's disease (AD) sharing a single PSEN2 mutation exhibit a wide range of age-at-onset, suggesting that modifier loci segregate within these families. While APOE is known to be an age-at-onset modifier, it does not explain all of this variation. We performed a genome scan within nine such families for loci influencing age-at-onset, while simultaneously controlling for variation in the primary PSEN2 mutation (N141I) and APOE. We found significant evidence of linkage between age-at-onset and chromosome 1q23.3 (P < 0.001) when analysis included all families, and to chromosomes 1q23.3 (P < 0.001), 17p13.2 (P = 0.0002), 7q33 (P = 0.017), and 11p14.2 (P = 0.017) in a single large pedigree. Simultaneous analysis of these four chromosomes maintained strong evidence of linkage to chromosomes 1q23.3 and 17p13.2 when all families were analyzed, and to chromosomes 1q23.3, 7q33, and 17p13.2 within the same single pedigree. Inclusion of major gene covariates proved essential to detect these linkage signals, as all linkage signals dissipated when PSEN2 and APOE were excluded from the model. The four chromosomal regions with evidence of linkage all coincide with previous linkage signals, associated SNPs, and/or candidate genes identified in independent AD study populations. This study establishes several candidate regions for further analysis and is consistent with an oligogenic model of AD risk and age-at-onset. More generally, this study also demonstrates the value of searching for modifier loci in existing datasets previously used to identify primary causal variants for complex disease traits.

Contrasting identity-by-descent estimators, association studies, and linkage analyses using the Framingham Heart Study data.

We explored the utility of population- and pedigree-based analyses using the Framingham Heart Study genome-wide 50 k single-nucleotide polymorphism marker data provided for Genetic Analysis Workshop 16. Our aims were: 1) to compare identity-by-descent sharing estimates from variable amounts of data; 2) to apply each of these estimates to a case-control association study designed to control for relatedness among samples; and 3) to contrast these results to those obtained using model-based and model-free linkage analysis methods.

Combining information from linkage and association methods.

Group 12 evaluated approaches to incorporate outside information or otherwise optimize traditional linkage and association analyses. The abundance of available data allowed exploration of identity-by-descent (IBD) estimation, score statistics, formal combination of linkage and association testing, significance estimation, and replication. We observed that IBD estimation can be optimized with a subset of marker data while estimation of inheritance vectors can provide both IBD estimates and a measure of their uncertainty. Score statistics incorporating covariates or combining association and linkage information performed at least as well as standard approaches while requiring less computation time. The formal combination of linkage and association methods may be fruitful, although the nature of the simulated data limited our conclusions. Estimation of significance may be improved through simulation, correction for cryptic relatedness, and the inclusion of prior information. Replication using real data provided consistent results, though the same was not true of simulated data replicates. Overall, we found that increasing the amount of available data limits analyses due to computational constraints and motivates the need to improve methods for the identification of complex-trait genes.

Estimating the age of retrotransposon subfamilies using maximum likelihood.

We present a maximum likelihood model to estimate the age of retrotransposon subfamilies. This method is designed around a master gene model which assumes a constant retrotransposition rate. The statistical properties of this model and an ad hoc estimation procedure are compared using two simulated data sets. We also test whether each estimation procedure is robust to violation of the master gene model. According to our results, both estimation procedures are accurate under the master gene model. While both methods tend to overestimate ages under the intermediate model, the maximum likelihood estimate is significantly less inflated than the ad hoc estimate. We estimate the ages of two subfamilies of human-specific LINE-I insertions using both estimation procedures. By calculating confidence intervals around the maximum likelihood estimate, our model can both provide an estimate of retrotransposon subfamily age and describe the range of subfamily ages consistent with the data.

Culture creates genetic structure in the Caucasus: autosomal, mitochondrial, and Y-chromosomal variation in Daghestan.

BACKGROUND: Near the junction of three major continents, the Caucasus region has been an important thoroughfare for human migration. While the Caucasus Mountains have diverted human traffic to the few lowland regions that provide a gateway from north to south between the Caspian and Black Seas, highland populations have been isolated by their remote geographic location and their practice of patrilocal endogamy. We investigate how these cultural and historical differences between highland and lowland populations have affected patterns of genetic diversity. We test 1) whether the highland practice of patrilocal endogamy has generated sex-specific population relationships, and 2) whether the history of migration and military conquest associated with the lowland populations has left Central Asian genes in the Caucasus, by comparing genetic diversity and pairwise population relationships between Daghestani populations and reference populations throughout Europe and Asia for autosomal, mitochondrial, and Y-chromosomal markers. RESULTS: We found that the highland Daghestani populations had contrasting histories for the mitochondrial DNA and Y-chromosome data sets. Y-chromosomal haplogroup diversity was reduced among highland Daghestani populations when compared to other populations and to highland Daghestani mitochondrial DNA haplogroup diversity. Lowland Daghestani populations showed Turkish and Central Asian affinities for both mitochondrial and Y-chromosomal data sets. Autosomal population histories are strongly correlated to the pattern observed for the mitochondrial DNA data set, while the correlation between the mitochondrial DNA and Y-chromosome distance matrices was weak and not significant. CONCLUSION: The reduced Y-chromosomal diversity exhibited by highland Daghestani populations is consistent with genetic drift caused by patrilocal endogamy. Mitochondrial and Y-chromosomal phylogeographic comparisons indicate a common Near Eastern origin of highland populations. Lowland Daghestani populations show varying influence from Near Eastern and Central Asian populations.