Multipoint linkage-disequilibrium-mapping approach based on the case-parent trio design

In the present study we propose a multipoint approach, for the mapping of genes, that is based on the case-parent trio design. We first derive an expression for the expected preferential-allele-transmission statistics for transmission, from either parent to an affected child, for an arbitrary location within a chromosomal region demarcated by several genetic markers. No assumption about genetic mechanism is needed in this derivation, beyond the assumption that no more than one disease gene lies in the region framed by the markers. When one builds on this representation, the way in which one may maximize the genetic information from multiple markers becomes obvious. This proposed method differs from the popular transmission/disequilibrium test (TDT) approach for fine mapping, in the following ways: First, in contrast with the TDT approach, all markers contribute information, regardless of whether the parents are heterozygous at any one marker, and incomplete trio data can be utilized in our approach. Second, rather than performing the TDT at each marker separately, we propose a single test statistic that follows a chi(2) distribution with 1 df, under the null hypothesis of no linkage or linkage disequilibrium to the region. Third, in the presence of linkage evidence, we offer a means to estimate the location of the disease locus along with its sampling uncertainty. We illustrate the proposed method with data from a family study of asthma, conducted in Barbados.     

A genomic screen of autism: evidence for a multilocus etiology.

We have conducted a genome screen of autism, by linkage analysis in an initial set of 90 multiplex sibships, with parents, containing 97 independent affected sib pairs (ASPs), with follow-up in 49 additional multiplex sibships, containing 50 ASPs. In total, 519 markers were genotyped, including 362 for the initial screen, and an additional 157 were genotyped in the follow-up. As a control, we also included in the analysis unaffected sibs, which provided 51 discordant sib pairs (DSPs) for the initial screen and 29 for the follow-up. In the initial phase of the work, we observed increased identity by descent (IBD) in the ASPs (sharing of 51.6%) compared with the DSPs (sharing of 50.8%). The excess sharing in the ASPs could not be attributed to the effect of a small number of loci but, rather, was due to the modest increase in the entire distribution of IBD. These results are most compatible with a model specifying a large number of loci (perhaps >/=15) and are less compatible with models specifying 相似文献   

A unified sampling approach for multipoint analysis of qualitative and quantitative traits in sib pairs

Recent advances in molecular biology have enhanced the opportunity to conduct multipoint mapping for complex diseases. Concurrently, one sees a growing interest in the use of quantitative traits in linkage studies. Here, we present a multipoint sib-pair approach to locate the map position (tau) of a trait locus that controls the observed phenotype (qualitative or quantitative), along with a measure of statistical uncertainty. This method builds on a parametric representation for the expected identical-by-descent statistic at an arbitrary locus, conditional on an event reflecting the sampling scheme, such as affected sib pairs, for qualitative traits, or extreme discordant (ED) sib pairs, for quantitative traits. Our results suggest that the variance about tau&d4;, the estimator of tau, can be reduced by as much as 60%-70% by reducing the length of intervals between markers by one half. For quantitative traits, we examine the precision gain (measured by the variance reduction in tau&d4;) by genotyping extremely concordant (EC) sib pairs and including them along with ED sib pairs in the statistical analysis. The precision gain depends heavily on the residual correlation of the quantitative trait for sib pairs but considerably less on the allele frequency and exact genetic mechanism. Since complex traits involve multiple loci and, hence, the residual correlation cannot be ignored, our finding strongly suggests that one should incorporate EC sib pairs along with ED sib pairs, in both design and analysis. Finally, we empirically establish a simple linear relationship between the magnitude of precision gain and the ratio of the number of ED pairs to the number of EC pairs. This relationship allows investigators to address issues of cost effectiveness that are due to the need for phenotyping and genotyping subjects.     

Consanguinity and the sib-pair method: an approach using identity by descent between and within individuals.

To test for linkage between a trait and a marker, one can consider identical marker alleles in related individuals, for instance, sibs. For recessive diseases, it has been shown that some information may be gained from the identity by descent (IBD) of the two alleles of an affected inbred individual at the marker locus. The aim of this paper is to extend the sib-pair method of linkage analysis to the situation of sib pairs sampled from consanguineous populations. This extension takes maximum advantage of the information provided by both the IBD pattern between sibs and allelic identity within each sib of the pair. This is possible through the use of the condensed identity coefficients. Here, we propose a new test of linkage based on a chi2. We compare the performance of this test with that of the classical chi2 test based on the distribution of sib pairs sharing 0, 1, or 2 alleles IBD. For sib pairs from first-cousin matings, the proposed test can better detect the role of a disease-susceptibility (DS) locus. Its power is shown to be greater than that of the classical test, especially for models where the DS allele may be common and incompletely penetrant; that is to say for situations that may be encountered in multifactorial diseases. A study of the impact of inbreeding on the expected proportions of sib pairs sharing 0, 1, or 2 alleles IBD is also performed here. Ignoring inbreeding, when in fact inbreeding exists, increases the rate of type I errors in tests of linkage.     

High-resolution linkage mapping for susceptibility genes in human polygenic disease: Insulin-dependent diabetes mellitus and chromosome 11q

Insulin-dependent diabetes mellitus (IDDM) has a complex pattern of genetic inheritance. In addition to genes mapping to the major histocompatibility complex (MHC), several lines of evidence point to the existence of other genetic susceptibility factors. Recent studies of the nonobese diabetic mouse (NOD) model of IDDM have suggested the presence, on mouse chromosome 9, of a susceptibility gene linked to the locus encoding the T-cell antigen, Thy-1. A region on human chromosome 11q is syntenic to this region on mouse chromosome 9. We have used a set of polymorphic DNA markers from chromosome 11q to investigate this region for linkage to a susceptibility gene in 81 multiplex diabetic pedigrees. The data were investigated by maximization of lod scores over genetic models and by multiple-locus affected-sib-pair analysis. We were able to exclude the presence of a susceptibility gene (location scores less than -2) throughout greater than 90% of the chromosome 11q homology region, under the assumption that the susceptibility factor would cause greater than 50% of affected sib pairs to share two alleles identical by descent. Theoretical estimates of the power to map susceptibility genes with a high-resolution map of linked markers in a candidate region were made, using HLA as a model locus. This result illustrates the feasibility that IDDM linkage studies using mapped sets of polymorphic DNA markers have, both for other areas of the genome in IDDM and for other polygenic diseases. The analytic approaches introduced here will be useful for affected-sib-pair studies of other complex phenotypes.     

A genomewide screen for autism: strong evidence for linkage to chromosomes 2q, 7q, and 16p

Autism is characterized by impairments in reciprocal communication and social interaction and by repetitive and stereotyped patterns of activities and interests. Evidence for a strong underlying genetic predisposition comes from twin and family studies, although susceptibility genes have not yet been identified. A whole-genome screen for linkage, using 83 sib pairs with autism, has been completed, and 119 markers have been genotyped in 13 candidate regions in a further 69 sib pairs. The addition of new families and markers provides further support for previous reports of linkages on chromosomes 7q and 16p. Two new regions of linkage have also been identified on chromosomes 2q and 17q. The most significant finding was a multipoint maximum LOD score (MLS) of 3.74 at marker D2S2188 on chromosome 2; this MLS increased to 4.80 when only sib pairs fulfilling strict diagnostic criteria were included. The susceptibility region on chromosome 7 was the next most significant, generating a multipoint MLS of 3.20 at marker D7S477. Chromosome 16 generated a multipoint MLS of 2.93 at D16S3102, whereas chromosome 17 generated a multipoint MLS of 2.34 at HTTINT2. With the addition of new families, there was no increased allele sharing at a number of other loci originally showing some evidence of linkage. These results support the continuing collection of multiplex sib-pair families to identify autism-susceptibility genes.     

Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM).

A population association has consistently been observed between insulin-dependent diabetes mellitus (IDDM) and the "class 1" alleles of the region of tandem-repeat DNA (5'' flanking polymorphism [5''FP]) adjacent to the insulin gene on chromosome 11p. This finding suggests that the insulin gene region contains a gene or genes contributing to IDDM susceptibility. However, several studies that have sought to show linkage with IDDM by testing for cosegregation in affected sib pairs have failed to find evidence for linkage. As means for identifying genes for complex diseases, both the association and the affected-sib-pairs approaches have limitations. It is well known that population association between a disease and a genetic marker can arise as an artifact of population structure, even in the absence of linkage. On the other hand, linkage studies with modest numbers of affected sib pairs may fail to detect linkage, especially if there is linkage heterogeneity. We consider an alternative method to test for linkage with a genetic marker when population association has been found. Using data from families with at least one affected child, we evaluate the transmission of the associated marker allele from a heterozygous parent to an affected offspring. This approach has been used by several investigators, but the statistical properties of the method as a test for linkage have not been investigated. In the present paper we describe the statistical basis for this "transmission test for linkage disequilibrium" (transmission/disequilibrium test [TDT]). We then show the relationship of this test to tests of cosegregation that are based on the proportion of haplotypes or genes identical by descent in affected sibs. The TDT provides strong evidence for linkage between the 5''FP and susceptibility to IDDM. The conclusions from this analysis apply in general to the study of disease associations, where genetic markers are usually closely linked to candidate genes. When a disease is found to be associated with such a marker, the TDT may detect linkage even when haplotype-sharing tests do not.     

Fine mapping of the chromosome 12 late-onset Alzheimer disease locus: potential genetic and phenotypic heterogeneity

Apolipoprotein E (APOE) is the only confirmed susceptibility gene for late-onset Alzheimer disease (AD). In a recent genomic screen of 54 families with late-onset AD, we detected significant evidence for a second late-onset AD locus located on chromosome 12 between D12S373 and D12S390. Linkage to this region was strongest in 27 large families with at least one affected individual without an APOE-4 allele, suggesting that APOE and the chromosome 12 locus might have independent effects. We have since genotyped several additional markers across the region, to refine the linkage results. In analyzing these additional data, we have addressed the issue of heterogeneity in the data set by weighting results by clinical and neuropathologic features, sibship size, and APOE genotype. When considering all possible affected sib pairs (ASPs) per nuclear family, we obtained a peak maximum LOD score between D12S1057 and D12S1042. The magnitude and location of the maximum LOD score changed when different weighting schemes were used to control for the number of ASPs contributed by each nuclear family. Using the affected-relative-pair method implemented in GENEHUNTER-PLUS, we obtained a maximum LOD score between D12S398 and D12S1632, 25 cM from the original maximum LOD score. These results indicate that family size influences the location estimate for the chromosome 12 AD gene. The results of conditional linkage analysis by use of GENEHUNTER-PLUS indicated that evidence for linkage to chromosome 12 was stronger in families with affected individuals lacking an APOE-4 allele; much of this evidence came from families with affected individuals with neuropathologic diagnosis of dementia with Lewy bodies (DLB). Taken together, these results indicate that the chromosome 12 locus acts independently of APOE to increase the risk of late-onset familial AD and that it may be associated with the DLB variant of AD.     

A unified Haseman-Elston method for testing linkage with quantitative traits

The Haseman and Elston (H-E) method uses a simple linear regression to model the squared trait difference of sib pairs with the shared allele identical by descent (IBD) at marker locus for linkage testing. Under this setting, the squared mean-corrected trait sum is also linearly related to the IBD sharing. However, the resulting slope estimate for either model is not efficient. In this report, we propose a simple linkage test that optimally uses information from the estimates of both models. We also demonstrate that the new test is more powerful than both the traditional one and the recently revisited H-E methods.     

Evidence for Linkage of Bipolar Disorder to Chromosome 18 with a Parent-of-Origin Effect

A susceptibility gene on chromosome 18 and a parent-of-origin effect have been suggested for bipolar affective disorder (BPAD). We have studied 28 nuclear families selected for apparent unilineal transmission of the BPAD phenotype, by using 31 polymorphic markers spanning chromosome 18. Evidence for linkage was tested with affected-sib-pair and LOD score methods under two definitions of the affected phenotype. The affected-sib-pair analyses indicated excess allele sharing for markers on 18p within the region reported previously. The greatest sharing was at D18S37: 64% in bipolar and recurrent unipolar (RUP) sib pairs (P = .0006). In addition, excess sharing of the paternally, but not maternally, transmitted alleles was observed at three markers on 18q: at D18S41, 51 bipolar and RUP sib pairs were concordant for paternally transmitted alleles, and 21 pairs were discordant (P = .0004). The evidence for linkage to loci on both 18p and 18q was strongest in the 11 paternal pedigrees, i.e., those in which the father or one of the father's sibs is affected. In these pedigrees, the greatest allele sharing (81%; P = .00002) and the highest LOD score (3.51; θ = 0.0) were observed at D18S41. Our results provide further support for linkage of BPAD to chromosome 18 and the first molecular evidence for a parent-of-origin effect operating in this disorder. The number of loci involved, and their precise location, require further study.     

Robust multipoint simultaneous identical-by-descent mapping for two linked loci

A challenging issue in genetic mapping of complex human diseases is localizing disease susceptibility genes when the genetic effects are small to moderate. There are greater complexities when multiple loci are linked to a chromosomal region. Liang et al. [Hum Hered 2001;51:64-78] proposed a robust multipoint method that can simultaneously estimate both the position of a trait locus and its effect on disease status by using affected sib pairs (ASPs). Based on the framework of generalized estimating equations (GEEs), the estimate and standard error of the position of a trait locus are robust to different genetic models. To utilize other relative pairs collected in pedigree data, Schaid et al. [Am J Hum Genet 2005;76:128-138] extended Liang's method to various types of affected relative pairs (ARPs) by two approaches: unconstrained and constrained methods. However, the above methods are limited to situations in which only one trait locus exists on the chromosome of interest. The mean functions are no longer correctly specified when there are multiple causative loci linked to a chromosomal region. To overcome this, Biernacka et al. [Genet Epidemiol 2005;28:33-47] considered the multipoint methods for ASPs to allow for two linked disease genes. We further generalize the approach to cover other types of ARPs. To reflect realistic situations for complex human diseases, we set modest sizes of genetic effects in our simulation. Our results suggest that several hundred independent pedigrees are needed, and markers with high information, to provide reliable estimates of trait locus positions and their confidence intervals. Bootstrap resampling can correct the downward bias of the robust variance for location estimates. These methods are applied to a prostate cancer linkage study on chromosome 20 and compared with the results for the one-locus model [Am J Hum Genet 2005;76:128-138]. We have implemented the multipoint IBD mapping for one and two linked loci in our software GEEARP, which allows analyses for five general types of ARPs.     

Ignoring linkage disequilibrium among tightly linked markers induces false-positive evidence of linkage for affected sib pair analysis

Most multipoint linkage programs assume linkage equilibrium among the markers being studied. The assumption is appropriate for the study of sparsely spaced markers with intermarker distances exceeding a few centimorgans, because linkage equilibrium is expected over these intervals for almost all populations. However, with recent advancements in high-throughput genotyping technology, much denser markers are available, and linkage disequilibrium (LD) may exist among the markers. Applying linkage analyses that assume linkage equilibrium to dense markers may lead to bias. Here, we demonstrated that, when some or all of the parental genotypes are missing, assuming linkage equilibrium among tightly linked markers where strong LD exists can cause apparent oversharing of multipoint identity by descent (IBD) between sib pairs and false-positive evidence for multipoint model-free linkage analysis of affected sib pair data. LD can also mimic linkage between a disease locus and multiple tightly linked markers, thus causing false-positive evidence of linkage using parametric models, particularly when heterogeneity LOD score approaches are applied. Bias can be eliminated by inclusion of parental genotype data and can be reduced when additional unaffected siblings are included in the analysis.     

Efficiency robust tests for mapping quantitative trait loci using extremely discordant sib pairs

In 1972, Haseman and Elston proposed a pioneering regression method for mapping quantitative trait loci using randomly selected sib pairs. Recently, the statistical power of their method was shown to be increased when extremely discordant sib pairs are ascertained. While the precise genetic model may not be known, prior information that constrains IBD probabilities is often available. We investigate properties of tests that are robust against model uncertainty and show that the power gain from further constraining IBD probabilities is marginal. The additional linkage information contained in the trait values can be incorporated by combining the Haseman-Elston regression method and a robust allele sharing test.     

Replication study supports evidence for linkage to 9p24 in obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is a severe psychiatric illness that is characterized by intrusive and senseless thoughts and impulses (obsessions) and by repetitive behaviors (compulsions). Family, twin, and segregation studies support the presence of both genetic and environmental susceptibility factors, and the only published genome scan for OCD identified a candidate region on 9p24 at marker D9S288 that met criteria for suggestive significance (Hanna et al. 2002). In an attempt to replicate this finding, we genotyped 50 pedigrees with OCD, using microsatellite markers spanning the 9p24 candidate region, and analyzed the data, using parametric and nonparametric linkage analyses under both a narrow phenotype model (DSM-IV OCD definite; 41 affected sib pairs) and a broad phenotype model (DSM-IV OCD definite and probable; 50 affected sib pairs). Similar to what was described by Hanna et al. (2002), our strongest findings came with the dominant parameters and the narrow phenotype model: the parametric signal peaked at marker D9S1792 with an HLOD of 2.26 ( alpha =0.59), and the nonparametric linkage signal (NPL) peaked at marker D9S1813 with an NPL of 2.52 (P=.006). These findings are striking in that D9S1813 and D9S1792 lie within 0.5 cM (<350 kb) of the original 9p24 linkage signal at D9S288; furthermore, pedigree-based association analyses also implicated the 9p24 candidate region by identifying two markers (D9S288 and GATA62F03) with modest evidence (P=.046 and .02, respectively) for association.     

Assessing whether an allele can account in part for a linkage signal: the Genotype-IBD Sharing Test (GIST)

To fine map genes, investigators often test for disease-marker association in chromosomal regions with evidence for linkage. Given a marker allele tentatively associated with disease, one would ask if this allele, or one in linkage disequilibrium (LD) with it, could account in part for the observed linkage signal. This question can be addressed by determining if families selected on the basis of the presence of the tentatively associated allele show stronger evidence of linkage as measured by increased allele sharing identical by descent (IBD) by affected family members. However, common selection strategies can be biased for or against linkage in the marker region, even given no disease-marker association. We define unbiased selection schemes and extend the definition to allow weighted selection on the basis of all genotyped family members. For affected-sibship data, we describe three genotype-based weight variables, corresponding to dominant, recessive, and additive models. We then introduce a test for association of a family weight variable with excess IBD sharing. This test allows us to determine if the linkage signal in a region can be attributed in part to the presence of a marker allele, either because of direct involvement in disease etiology or because of LD with a predisposing genetic variant. For samples of 500 affected sib pairs, the tests are powerful in detection of genotype-IBD sharing association, even for disease models with sib relative risk as low as lambda S=1.1, or when evidence for linkage is absent because of sampling variation. This makes our method a new tool for detecting linkage as well as association, especially in regions harboring a candidate gene. We have implemented these methods in the software package GIST (Genotype-IBD Sharing Test).     

Association of the GABRD gene and childhood‐onset mood disorders

The chromosome 1p36 region was previously indicated as a locus for susceptibility to recurrent major depressive disorder based on a linkage study in a sample of 497 sib pairs. We investigated the gamma‐aminobutyric acid A (GABA_A) δ receptor subunit gene, GABRD, as a susceptibility gene to childhood‐onset mood disorders (COMD) because of substantial evidence implicating GABAergic dysfunction in mood disorders and the position of this gene near the 1p36 linkage region. Using a sample consisting of 645 Hungarian families with a child/adolescent proband diagnosed with a mood disorder with the onset of the first episode before age 15, we found some evidence for the association of two polymorphisms located within the gene, rs2376805 and rs2376803, as well as significant evidence for biased transmission of the haplotypes of these two markers (global χ² test for haplotypes = 12.746, 3 df, P = 0.0052). Furthermore, significant evidence of association was only observed in male subjects (n = 438) when the results were analyzed by sex (χ² = 9.000 1 df, P = 0.003 for rs2376805). This was in contrast with the previous linkage findings, as LOD scores exceeding 3 were only in female–female pairs in that study. These findings point to the GABRD gene as a susceptibility gene for COMD; however, this gene may not explain the previous linkage finding.     

Nonparametric trend statistic incorporating dispersion differences in sib pair linkage for quantitative traits

The Haseman-Elston (HE) regression method and its extensions are widely used in genetic studies for detecting linkage to quantitative trait loci (QTL) using sib pairs. The principle underlying the simple HE regression method is that the similarity in phenotypes between two siblings increases as they share an increasing number of alleles identical by descent (IBD) from their parents at a particular marker locus. In such a procedure, similarity was identified with the locations, that is, means of groups of sib pairs sharing 0, 1, and 2 alleles IBD. A more powerful, rank-based nonparametric test to detect increasing similarity in sib pairs is presented by combining univariate trend statistics not only of locations, but also of dispersions of the squared phenotypic differences of two siblings for three groups. This trend test does not rely on distributional assumptions, and is applicable to the skewed or leptokurtic phenotypic distributions, in addition to normal or near normal phenotypic distributions. The performances of nonparametric trend statistics, including nonparametric regression slope, are compared with the HE regression methods as genetic linkage strategies.     

Nonparametric simulation-based statistics for detecting linkage in general pedigrees.

We present here four nonparametric statistics for linkage analysis that test whether pairs of affected relatives share marker alleles more often than expected. These statistics are based on simulating the null distribution of a given statistic conditional on the unaffecteds' marker genotypes. Each statistic uses a different measure of marker sharing: the SimAPM statistic uses the simulation-based affected-pedigree-member measure based on identity-by-state (IBS) sharing. The SimKIN (kinship) measure is 1.0 for identity-by-descent (IBD) sharing, 0.0 for no IBD status sharing, and the kinship coefficient when the IBD status is ambiguous. The simulation-based IBD (SimIBD) statistic uses a recursive algorithm to determine the probability of two affecteds sharing a specific allele IBD. The SimISO statistic is identical to SimIBD, except that it also measures marker similarity between unaffected pairs. We evaluated our statistics on data simulated under different two-locus disease models, comparing our results to those obtained with several other nonparametric statistics. Use of IBD information produces dramatic increases in power over the SimAPM method, which uses only IBS information. The power of our best statistic in most cases meets or exceeds the power of the other nonparametric statistics. Furthermore, our statistics perform comparisons between all affected relative pairs within general pedigrees and are not restricted to sib pairs or nuclear families.     

Multipoint linkage analysis of the pseudoautosomal regions, using affected sibling pairs

Affected sibling pairs are often the design of choice in linkage-analysis studies with the goal of identifying the genes that increase susceptibility to complex diseases. Methods for multipoint analysis based on sibling amount of sharing that is identical by descent are widely available, for both autosomal and X-linked markers. Such methods have the advantage of making few assumptions about the mode of inheritance of the disease. However, with this approach, data from the pseudoautosomal regions on the X chromosome pose special challenges. Same-sex sibling pairs will share, in that region of the genome, more genetic material identical by descent, with and without the presence of a disease-susceptibility gene. This increased sharing will be more pronounced for markers closely linked to the sex-specific region. For the same reason, opposite-sex sibling pairs will share fewer alleles identical by descent. Failure to take this inequality in sharing into account may result in a false declaration of linkage if the study sample contains an excess of sex-concordant pairs, or a linkage may be missed when an excess of sex-discordant pairs is present. We propose a method to take into account this expected increase/decrease in sharing when markers in the pseudoautosomal region are analyzed. For quantitative traits, we demonstrate, using the Haseman-Elston method, (1) the same inflation in type I error, in the absence of an appropriate correction, and (2) the inadequacy of permutation tests to estimate levels of significance when all phenotypic values are permuted, irrespective of gender. The proposed method is illustrated with a genome screen on 350 sibling pairs affected with type I diabetes.     

Gene-environment interaction and affected sib pair linkage analysis

OBJECTIVES: Gene-environment (GxE) interaction influences risk for many complex disease traits. However, genome screens using affected sib pair linkage techniques are typically conducted without regard for GxE interaction. We propose a simple extension of the commonly used mean test and evaluate its power for several forms of GxE interaction. METHODS: We compute expected IBD sharing by sibling exposure profile, that is by whether two sibs are exposed (EE), unexposed (UU), or are discordant for exposure (EU). We describe a simple extension of the mean test, the "mean-interaction" test that utilizes heterogeneity in IBD sharing across EE, EU, and UU sib pairs in a test for linkage. RESULTS: The mean-interaction test provides greater power than the mean test for detecting linkage in the presence of moderate or strong GxE interaction, typically when the interaction relative risk (R(ge)) exceeds 3 or is less than 1/3. In the presence of strong interaction (R(ge) = 10), the required number of affected sib pairs to achieve 80% power for detecting linkage is approximately 30% higher when the environmental factor is ignored in the mean test, than when it is utilized in the mean-interaction test. CONCLUSION: Linkage methods that incorporate environmental data and allow for interaction can lead to increased power for localizing a disease gene involved in a GxE interaction.