Effect of heterogeneity and assumed mode of inheritance on lod scores.

Heterogeneity is a major factor in many common, complex diseases and can confound linkage analysis. Using computer-simulated heterogeneous data we tested what effect unlinked families have on a linkage analysis when heterogeneity is not taken into account. We created 60 data sets of 40 nuclear families each with different proportions of linked and unlinked families and with different modes of inheritance. The ascertainment probability was 0.05, the disease had a penetrance of 0.6, and the recombination fraction for the linked families was zero. For the analysis we used a variety of assumed modes of inheritance and penetrances. Under these conditions we looked at the effect of the unlinked families on the lod score, the evaluation of the mode of inheritance, and the estimate of penetrance and of the recombination fraction in the linked families. 1. When the analysis was done under the correct mode of inheritance for the linked families, we found that the mode of inheritance of the unlinked families had minimal influence on the highest maximum lod score (MMLS) (i.e., we maximized the maximum lod score with respect to penetrance). Adding sporadic families decreased the MMLS less than adding recessive or dominant unlinked families. 2. The mixtures of dominant linked families with unlinked families always led to a higher MMLS when analyzed under the correct (dominant) mode of inheritance than when analyzed under the incorrect mode of inheritance. In the mixtures with recessive linked families, assuming the correct mode of inheritance generally led to a higher MMLS, but we observed broad variation.(ABSTRACT TRUNCATED AT 250 WORDS)

Durner M ，Greenberg DA 《american journal of medical genetics》

Inferring mode of inheritance by comparison of lod scores.

One usually must assume a mode of inheritance when using lod scores for linkage analysis. In this study, we asked the question, "If one assumed mode of inheritance in a linkage analysis gives a higher lod score than another, does that indicate that the mode of inheritance that led to the higher lod score is more 'correct' than the other?" We simulated data under a variety of penetrances, assuming either dominant or recessive inheritance. We then analyzed those simulated data under the correct mode of inheritance, assuming a range of penetrance values, and under the incorrect model, also assuming a range of penetrance values. We found that, if there was enough information for a maximum lod score of at least 3.0, assuming the correct penetrance value or mode of inheritance in the analysis led to a higher lod score than assuming the incorrect penetrance or the incorrect mode of inheritance. These results cannot yet be generalized outside of the specific modes of inheritance and penetrance combinations that we have modeled. Also, penetrance was modeled as "random." The effect of "reduced penetrance" caused by other genetic factors has not yet been tested. We also tested the effect of non-standard ascertainment on drawing conclusions about mode of inheritance from linkage data. Even when families were ascertained only if the family was multiplex (i.e., more than one affected sib), assuming the correct mode of inheritance gave a higher lod score than assuming the incorrect mode of inheritance. This method has the promise of both simplifying and expanding the application of linkage analysis.(ABSTRACT TRUNCATED AT 250 WORDS)

Greenberg DA 《american journal of medical genetics》

Linkage analysis assuming a single-locus mode of inheritance for traits determined by two loci: inferring mode of inheritance and estimating penetrance.

What happens to the results of linkage analysis when one assumes that a disease results from a single genetic locus with reduced penetrance when the actual cause is two epistatically interacting loci? We wanted to (1) determine whether assuming the correct mode of inheritance at the linked locus leads to a higher lod score than assuming the incorrect mode of inheritance irrespective of penetrance assumptions and (2) determine whether it is possible to estimate the apparent penetrance due to the second, unlinked locus from the linkage data. Linkage data were simulated under three different two-locus models. Different "penetrances" were simulated by using different disease allele frequencies at the unlinked locus. Data were then analyzed assuming a single locus with reduced penetrance. The maximum lod score was maximized with respect to penetrance (LVP curves). We found that if there were enough data, assuming the correct (i.e., generating) mode of inheritance at the linked locus always led to a higher lod score than assuming the incorrect mode of inheritance no matter what the penetrance assumption. In contrast to the case where reduced penetrance is due to random factors, the estimate of the apparent penetrance (the "penetrance" due to the second locus) was biased, thus making any estimation of the gene frequency at the second locus doubtful. The ability to detect linkage was apparently not affected when the effects of the second locus were treated as random reduced penetrance. The results suggest that analyzing the data under the assumption of a single-locus model with reduced penetrance rather than a two-locus model will not substantially decrease the ability to establish linkage nor will it affect determining the mode of inheritance at the linked locus from the linkage data.

Greenberg DA 《GENETIC EPIDEMIOLOGY》

Determining trait locus position from multipoint analysis: accuracy and power of three different statistics.

Previous work using two-point linkage analysis showed that performing a lod score (LOD) analysis twice, once assuming dominant and once assuming recessive inheritance, and then taking the larger of the two values (designated MMLS) usually has more power to detect linkage than any other method tested. Using computer simulation for a variety of complex inheritance models, we demonstrated power for the MMLS comparable with analysis assuming the true model. However, reports in the literature suggested that the MMLS approach might fail to detect linkage using multipoint analysis due to genetic model misspecification. Here, we tested the robustness of the MMLS approach under multipoint analysis. We simulated data under complex inheritance models, including heterogeneity, epistatic, and additive models. We examined the expected maximum LOD, LOD assuming heterogeneity (HLOD), and nonparametric linkage statistics and the corresponding estimated position in a chromosomal interval of 10 markers with 10% recombination between markers. The mean estimates of position were generally good for all three statistics except when heterogeneity existed, where the LOD and the NPL did not perform as well as the HLOD. The MMLS approach was as robust using multipoint as using two-point linkage analysis. LOD and/or the HLOD generally had more power to detect linkage than NPL across a variety of generating models, even after correcting for the multiple tests. For finding linkage to one locus of several contributing to disease expression, assuming the dominant and recessive models with reduced penetrance is a good approximation of the mode of inheritance at that locus.

Greenberg DA ，Abreu PC 《GENETIC EPIDEMIOLOGY》

The impact of population admixture on traditional linkage analysis.

Families of admixed ancestry are routinely excluded from traditional (Log of the Odds [LOD] score) linkage analysis or are analyzed as being derived from a homogeneous population using the proband's ethnicity. Using traditional linkage analysis with these families can cause complications due to the mixing of different disease rates and allele frequencies that occurs. The presence of admixture violates the key assumptions of Hardy-Weinberg Equilibrium (HWE) and Linkage Equilibrium (LE) invoked in the current methods of linkage analysis. If one or more of these assumptions are violated, incorrect inference for linkage could result. Through simulation, we investigated the effect of admixture of two populations on the LOD score under various conditions, using prostate cancer as our underlying disease model. Four-generation homogeneous and admixed families were simulated with 27 markers and two linked, bi-allelic disease loci. Two different types of admixture were tested: admixture within a family unit and a mixture of homogeneous families within a data set. All mixing was done at the founder level in three different proportions: 30/70, 50/50 and 70/30. We observed that the LOD scores under both models of admixture were closest to the homogeneous family scores of the population having the highest mixing proportion. Random sampling of families or ascertainment of families with disease affection status did not affect this observation, nor did the mode of inheritance (dominant/recessive) or sample size. Thus, the presence of families of mixed population ancestry impacts linkage analysis in terms of the LOD score and the estimate of the recombination fraction.

Barnholtz-Sloan JS ，de Andrade M ，Chakraborty R 《ETHNICITY & DISEASE》