The value of molecular haplotypes in a family-based linkage study

Abstract

Novel methods that could improve the power of conventional methods of gene discovery for complex diseases should be investigated. In a simulation study, we aimed to investigate the value of molecular haplotypes in the context of a family-based linkage study. The term "haplotype" (or "haploid genotype") refers to syntenic alleles inherited on a single chromosome, and we use the term "molecular haplotype" to refer to haplotypes that have been determined directly by use of a molecular technique such as long-range allele-specific polymerase chain reaction. In our study, we simulated genotype and phenotype data and then compared the powers of analyzing these data under the assumptions that various levels of information from molecular haplotypes were available. (This information was available because of the simulation procedure.) Several conclusions can be drawn. First, as expected, when genetic homogeneity is expected or when marker data are complete, it is not efficient to generate molecular haplotyping information. However, with levels of heterogeneity and missing data patterns typical of complex diseases, we observed a 23%-77% relative increase in the power to detect linkage in the presence of heterogeneity with heterogeneity LOD scores >3.0 when all individuals are molecularly haplotyped (compared with the power when only standard genotypes are used). Furthermore, our simulations indicate that most of the increase in power can be achieved by molecularly haplotyping a single individual in each family, thereby making molecular haplotyping a valuable strategy for increasing the power of gene mapping studies of complex diseases. Maximization of power, given an existing family set, can be particularly important for late-onset, often-fatal diseases such as cancer, for which informative families are difficult to collect.

Figure 1.

Pedigree structure used in simulation analyses. Each pedigree was required to have three affected individuals for ascertainment. Which three individuals were affected was somewhat limited, to minimize the inclusion of families uninformative for linkage analysis.

Figure 2.

Examples of pedigrees excluded from simulations. Families were not included if the three affected members were all founders (A), a parent-parent-offspring trio (B), a trio of parent, offspring, and a founder who is not a grandparent (C), a founder-founder-spouse trio (D), or a trio of individuals 7, 12, and either 5 or 6 (E) (individual numbering as in fig. 1).

Figure 3.

Examples of specific pedigrees included in simulation analyses

Figure 4.

Outline of nine STR FM analyses for all three levels of genetic heterogeneity (H0, H1, and H2). (Results are shown in tables 1–3). For each level of genetic heterogeneity (A), we considered three levels of molecular haplotyping information (P0, P1, and P2) (B), and, for each level of molecular haplotyping information, we considered three levels of missing data (M0, M1, and M2) (C).

Figure 5.

Outline of additional STR FM analyses (H2 only). For the H2 level of heterogeneity only (A), we considered two additional levels of molecular haplotyping information (B), each with molecular haplotyping information available for a single individual. For each of these two levels of molecular haplotyping information, we considered three levels of missing data (M0, M1, and M2) (C). Results are shown in table 4.

Figure 6.

Outline of additional STR GWS analyses (H2 only). For the H2 level of heterogeneity only, we also analyzed four STR markers at GWS density (markers 10 cM apart). Results are shown in table 5.

Figure 7.

Outline of additional SNP GWS analyses (H2 only). For the H2 level of heterogeneity only, we also analyzed four SNP markers at GWS density (markers 1 cM apart). Results are shown in table 6.