Inferential testing for linkage with GENEHUNTER-MODSCORE: The impact of the pedigree structure on the null distribution of multipoint MOD scores

Joint Linkage and Association Analysis Using GENEHUNTER-MODSCORE with an Application to Familial Pancreatic Cancer

INTRODUCTION

Joint linkage and association (JLA) analysis combines two disease gene mapping strategies: linkage information contained in families and association information contained in populations. Such a JLA analysis can increase mapping power, especially when the evidence for both linkage and association is low to moderate. Similarly, an association analysis based on haplotypes instead of single markers can increase mapping power when the association pattern is complex.

METHODS

In this paper, we present an extension to the GENEHUNTER-MODSCORE software package that enables a JLA analysis based on haplotypes and uses information from arbitrary pedigree types and unrelated individuals. Our new JLA method is an extension of the MOD score approach for linkage analysis, which allows the estimation of trait-model and linkage disequilibrium (LD) parameters, i.e., penetrance, disease-allele frequency, and haplotype frequencies. LD is modeled between alleles at a single diallelic disease locus and up to three diallelic test markers. Linkage information is contributed by additional multi-allelic flanking markers. We investigated the statistical properties of our JLA implementation using extensive simulations, and we compared our approach to another commonly used single-marker JLA test. To demonstrate the applicability of our new method in practice, we analyzed pedigree data from the German National Case Collection for Familial Pancreatic Cancer (FaPaCa).

RESULTS

Based on the simulated data, we demonstrated the validity of our JLA-MOD score analysis implementation and identified scenarios in which haplotype-based tests outperformed the single-marker test. The estimated trait-model and LD parameters were in good accordance with the simulated values. Our method outperformed another commonly used JLA single-marker test when the LD pattern was complex. The exploratory analysis of the FaPaCa families led to the identification of a promising genetic region on chromosome 22q13.33, which can serve as a starting point for future mutation analysis and molecular research in pancreatic cancer.

CONCLUSION

Our newly proposed JLA-MOD score method proves to be a valuable gene mapping and characterization tool, especially when either linkage or association information alone provide insufficient power to identify the disease-causing genetic variants.

Properties and Evaluation of the MOBIT - a novel Linkage-based Test Statistic and Quantification Method for Imprinting

Genomic imprinting is a parent-of-origin effect apparent in an appreciable number of human diseases. We have proposed the new imprinting test statistic MOBIT, which is based on MOD score analysis. We were interested in the properties of the MOBIT concerning its distribution under three hypotheses: (1) H0,a: no linkage, no imprinting; (2) H0,b: linkage, no imprinting; (3) H1: linkage and imprinting. More specifically, we assessed the confounding between imprinting and sex-specific recombination frequencies, which presents a major difficulty in linkage-based testing for imprinting, and evaluated the power of the test. To this end, we have performed a linkage simulation study of affected sib-pairs and a three-generation pedigree with two trait models, many two- and multipoint marker scenarios, three genetic map ratios, two sample sizes, and five imprinting degrees. We also investigated the ability of the MOBIT to quantify the degree of imprinting and applied the MOBIT using a real data example on house dust mite allergy. We further proposed and evaluated two approaches to obtain empiric p values for the MOBIT. Our results showed that twopoint analyses assuming a sex-averaged marker map led to an inflated type I error due to confounding, especially for a larger marker-trait locus distance. When the correct sex-specific marker map was assumed, twopoint analyses have a reduced power to detect imprinting, compared to sex-averaged analyses with an appropriate correction for the inflation of the test statistic. However, confounding was not an issue in multipoint analysis unless the map ratio was extreme and marker spacing was sparse. With multipoint analysis, power as well as the ability to quantify the imprinting degree were almost equally high when a sex-averaged or the correct sex-specific map was used in the analysis. We recommend to obtain empiric p values for the MOBIT using genotype simulations based on the best-fitting nonimprinting model of the real dataset analysis. In addition, an implementation of a method based on the permutation of parental sexes is also available. In summary, we propose to perform multipoint analyses using densely spaced markers to efficiently discover new imprinted loci and to reliably quantify the degree of imprinting.

Estimation of Trait-Model Parameters in a MOD Score Linkage Analysis

Background/Aims

Theoretically, the trait-model parameters (disease allele frequency and penetrance function) can be estimated without bias in a MOD score linkage analysis. We aimed to practically evaluate the MOD score approach regarding its ability to provide unbiased trait-model parameters for various pedigree-type and trait-model scenarios. We further investigated the ability of the MOD score approach to detect imprinting using affected sib pairs (ASPs) and affected half-sib pairs (AHSPs) when all parental genotypes are missing.

Methods

Simulated pedigree data were analyzed using the GENEHUNTER-MODSCORE software package. Parameter estimation performance in terms of bias and variability was evaluated with regard to trait-model type and pedigree complexity.

Results

Generally, parameters were estimated with lower bias and variability with increasing pedigree complexity, especially for recessive and overdominant models. However, dominant and additive models could hardly be distinguished even when using 3-generation pedigrees. Imprinting could clearly be detected for mixtures of mainly ASPs and only few AHSPs with the common parent of the imprinted sex, even though no parental genotypes were available.

Conclusion

Our results provide guidance to researchers regarding the possibility to estimate trait-model parameters by a MOD score analysis, including the degree of imprinting, with certain types of pedigrees.

Evidence for linkage of migraine in Rolandic epilepsy to known 1q23 FHM2 and novel 17q22 genetic loci

Migraine headaches are a common comorbidity in Rolandic epilepsy (RE) and familial aggregation of migraine in RE families suggests a genetic basis not mediated by seizures. We performed a genome-wide linkage analysis of the migraine phenotype in 38 families with RE to localize potential genetic contribution, with a follow-up in an additional 21 families at linked loci. We used two-point and multipoint LOD (logarithm of the odds) score methods for linkage, maximized over genetic models. We found evidence of linkage to migraine at chromosome 17q12-22 [multipoint HLOD (heterogeneity LOD) 4.40, recessive, 99% penetrance], replicated in the second dataset (HLOD 2.61), and suggestive evidence at 1q23.1-23.2, centering over the FHM2 locus (two-point LOD 3.00 and MP HLOD 2.52). Sanger sequencing in 14 migraine-affected individuals found no coding mutations in the FHM2 gene ATP1A2. There was no evidence of pleiotropy for migraine and either reading or speech disorder, or the electroencephalographic endophenotype of RE when the affected definition was redefined as those with migraine or the comorbid phenotype, and pedigrees were reanalyzed for linkage. In summary, we report a novel migraine susceptibility locus at 17q12-22, and a second locus that may contribute to migraine in the general population at 1q23.1-23.2. Comorbid migraine in RE appears genetically influenced, but we did not obtain evidence that the identified susceptibility loci are consistent with pleiotropic effects on other comorbidities in RE. Loci identified here should be fine-mapped in individuals from RE families with migraine, and prioritized for analysis in other types of epilepsy-associated migraine.

Genome-wide linkage analysis of congenital heart defects using MOD score analysis identifies two novel loci

Background

Congenital heart defects (CHD) is the most common cause of death from a congenital structure abnormality in newborns and is often associated with fetal loss. There are many types of CHD. Human genetic studies have identified genes that are responsible for the inheritance of a particular type of CHD and for some types of CHD previously thought to be sporadic. However, occasionally different members of the same family might have anatomically distinct defects — for instance, one member with atrial septal defect, one with tetralogy of Fallot, and one with ventricular septal defect. Our objective is to identify susceptibility loci for CHD in families affected by distinct defects. The occurrence of these apparently discordant clinical phenotypes within one family might hint at a genetic framework common to most types of CHD.

Results

We performed a genome-wide linkage analysis using MOD score analysis in families with diverse CHD. Significant linkage was obtained in two regions, at chromosome 15 (15q26.3, P_empirical = 0.0004) and at chromosome 18 (18q21.2, P_empirical = 0.0005).

Conclusions

In these two novel regions four candidate genes are located: SELS, SNRPA1, and PCSK6 on 15q26.3, and TCF4 on 18q21.2. The new loci reported here have not previously been described in connection with CHD. Although further studies in other cohorts are needed to confirm these findings, the results presented here together with recent insight into how the heart normally develops will improve the understanding of CHD.

Motor sequencing deficit as an endophenotype of speech sound disorder: a genome-wide linkage analysis in a multigenerational family

OBJECTIVES

The aim of this pilot study was to investigate a measure of motor sequencing deficit as a potential endophenotype of speech sound disorder (SSD) in a multigenerational family with evidence of familial SSD.

METHODS

In a multigenerational family with evidence of a familial motor-based SSD, affectation status and a measure of motor sequencing during oral motor testing were obtained. To further investigate the role of motor sequencing as an endophenotype for genetic studies, parametric and nonparametric linkage analyses were carried out using a genome-wide panel of 404 microsatellites.

RESULTS

In seven of the 10 family members with available data, SSD affectation status and motor sequencing status coincided. Linkage analysis revealed four regions of interest, 6p21, 7q32, 7q36, and 8q24, primarily identified with the measure of motor sequencing ability. The 6p21 region overlaps with a locus implicated in rapid alternating naming in a recent genome-wide dyslexia linkage study. The 7q32 locus contains a locus implicated in dyslexia. The 7q36 locus borders on a gene known to affect the component traits of language impairment.

CONCLUSION

The results are consistent with a motor-based endophenotype of SSD that would be informative for genetic studies. The linkage results in this first genome-wide study in a multigenerational family with SSD warrant follow-up in additional families and with fine mapping or next-generation approaches to gene identification.

MLEP: an R package for exploring the maximum likelihood estimates of penetrance parameters

Background

Linkage analysis is a useful tool for detecting genetic variants that regulate a trait of interest, especially genes associated with a given disease. Although penetrance parameters play an important role in determining gene location, they are assigned arbitrary values according to the researcher’s intuition or as estimated by the maximum likelihood principle. Several methods exist by which to evaluate the maximum likelihood estimates of penetrance, although not all of these are supported by software packages and some are biased by marker genotype information, even when disease development is due solely to the genotype of a single allele.

Findings

Programs for exploring the maximum likelihood estimates of penetrance parameters were developed using the R statistical programming language supplemented by external C functions. The software returns a vector of polynomial coefficients of penetrance parameters, representing the likelihood of pedigree data. From the likelihood polynomial supplied by the proposed method, the likelihood value and its gradient can be precisely computed. To reduce the effect of the supplied dataset on the likelihood function, feasible parameter constraints can be introduced into maximum likelihood estimates, thus enabling flexible exploration of the penetrance estimates. An auxiliary program generates a perspective plot allowing visual validation of the model’s convergence. The functions are collectively available as the MLEP R package.

Conclusions

Linkage analysis using penetrance parameters estimated by the MLEP package enables feasible localization of a disease locus. This is shown through a simulation study and by demonstrating how the package is used to explore maximum likelihood estimates. Although the input dataset tends to bias the likelihood estimates, the method yields accurate results superior to the analysis using intuitive penetrance values for disease with low allele frequencies. MLEP is part of the Comprehensive R Archive Network and is freely available at http://cran.r-project.org/web/packages/MLEP/index.html.

Parameter estimation and quantitative parametric linkage analysis with GENEHUNTER-QMOD

OBJECTIVE

We present a parametric method for linkage analysis of quantitative phenotypes. The method provides a test for linkage as well as an estimate of different phenotype parameters. We have implemented our new method in the program GENEHUNTER-QMOD and evaluated its properties by performing simulations.

METHODS

The phenotype is modeled as a normally distributed variable, with a separate distribution for each genotype. Parameter estimates are obtained by maximizing the LOD score over the normal distribution parameters with a gradient-based optimization called PGRAD method.

RESULTS

The PGRAD method has lower power to detect linkage than the variance components analysis (VCA) in case of a normal distribution and small pedigrees. However, it outperforms the VCA and Haseman-Elston regression for extended pedigrees, nonrandomly ascertained data and non-normally distributed phenotypes. Here, the higher power even goes along with conservativeness, while the VCA has an inflated type I error. Parameter estimation tends to underestimate residual variances but performs better for expectation values of the phenotype distributions.

CONCLUSION

With GENEHUNTER-QMOD, a powerful new tool is provided to explicitly model quantitative phenotypes in the context of linkage analysis. It is freely available at http://www.helmholtz-muenchen.de/genepi/downloads.

A comparison of different linkage statistics in small to moderate sized pedigrees with complex diseases

Background

In the last years GWA studies have successfully identified common SNPs associated with complex diseases. However, most of the variants found this way account for only a small portion of the trait variance. This fact leads researchers to focus on rare-variant mapping with large scale sequencing, which can be facilitated by using linkage information. The question arises why linkage analysis often fails to identify genes when analyzing complex diseases. Using simulations we have investigated the power of parametric and nonparametric linkage statistics (KC-LOD, NPL, LOD and MOD scores), to detect the effect of genes responsible for complex diseases using different pedigree structures.

Results

As expected, a small number of pedigrees with less than three affected individuals has low power to map disease genes with modest effect. Interestingly, the power decreases when unaffected individuals are included in the analysis, irrespective of the true mode of inheritance. Furthermore, we found that the best performing statistic depends not only on the type of pedigrees but also on the true mode of inheritance.

Conclusions

When applied in a sensible way linkage is an appropriate and robust technique to map genes for complex disease. Unlike association analysis, linkage analysis is not hampered by allelic heterogeneity. So, why does linkage analysis often fail with complex diseases? Evidently, when using an insufficient number of small pedigrees, one might miss a true genetic linkage when actually a real effect exists. Furthermore, we show that the test statistic has an important effect on the power to detect linkage as well. Therefore, a linkage analysis might fail if an inadequate test statistic is employed. We provide recommendations regarding the most favorable test statistics, in terms of power, for a given mode of inheritance and type of pedigrees under study, in order to reduce the probability to miss a true linkage.

A new susceptibility locus for bipolar affective disorder in PAR1 on Xp22.3/Yp11.3

We present the findings of a linkage study of bipolar affective disorder (BPAD) that involve the pseudoautosomal region 1 of the human sex chromosomes. We analyzed a substantial subset of pedigrees (89 families of German and Spanish origin; 661 participants; 298 affected individuals) from the large collection of BPAD-affected families with which a genomewide linkage analysis was previously performed and where the pseudoautosomal regions were poorly covered. Nonparametric linkage (Z(lr)) scores were calculated. The highest Z(lr) scores were obtained on Xp22.3/Yp11.3 in the Spanish subsample (DXS1071; Z(lr) = 3.54, P(empirical) = 0.0009 for the broad definition of affection sttuts; Z(lr) = 2.63, P(empirical) = 0.0129 for the medium definition of affection status; Z(lr) = 2.12, P(empirical) = 0.0429 for the narrow definition of affection status). Empirical P-values are adjusted using the Bonferroni correction to account for the testing of three affection status definitions. This region has not drawn much attention in previous linkage studies of BPAD. On the basis of these results, Xp22.3/Yp11.3 should now be considered a candidate region for BPAD.