BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation.

BACKGROUND: X chromosome inactivation (XCI) is an epigenetic phenomenon that one of two X chromosomes in females is transcriptionally silenced during early embryonic development. Skewed XCI has been reported to be associated with some X-linked diseases. There have been several methods measuring the degree of the skewness of XCI. However, these methods may still have several limitations. RESULTS: We propose a Bayesian method to obtain the point estimate and the credible interval of the degree of XCI skewing by incorporating its prior information of being between 0 and 2. We consider a normal prior and a uniform prior for it (respectively denoted by BN and BU). We also propose a penalized point estimate based on the penalized Fieller's method and derive the corresponding confidence interval. Simulation results demonstrate that the BN and BU methods can solve the problems of extreme point estimates, noninformative intervals, empty sets and discontinuous intervals. The BN method generally outperforms other methods with the lowest mean squared error in the point estimation, and well controls the coverage probability with the smallest median and the least variation of the interval width in the interval estimation. We apply all the methods to the Graves' disease data and the Minnesota Center for Twin and Family Research data, and find that SNP rs3827440 in the Graves' disease data may undergo skewed XCI towards the allele C. CONCLUSIONS: We recommend the BN method for measuring the degree of the skewness of XCI in practice. The R package BEXCIS is publicly available at https://github.com/Wen-YiYu/BEXCIS .

Robust association tests for quantitative traits on the X chromosome.

The genome-wide association study is an elementary tool to assess the genetic contribution to complex human traits. However, such association tests are mainly proposed for autosomes, and less attention has been given to methods for identifying loci on the X chromosome due to their distinct biological features. In addition, the existing association tests for quantitative traits on the X chromosome either fail to incorporate the information of males or only detect variance heterogeneity. Therefore, we propose four novel methods, which are denoted as QXcat, QZmax, QMVXcat and QMVZmax. When using these methods, it is assumed that the risk alleles for females and males are the same and that the locus being studied satisfies the generalized genetic model for females. The first two methods are based on comparing the means of the trait value across different genotypes, while the latter two methods test for the difference of both means and variances. All four methods effectively incorporate the information of X chromosome inactivation. Simulation studies demonstrate that the proposed methods control the type I error rates well. Under the simulated scenarios, the proposed methods are generally more powerful than the existing methods. We also apply our proposed methods to data from the Minnesota Center for Twin and Family Research and find 10 single nucleotide polymorphisms that are statistically significantly associated with at least two traits at the significance level of 1 × 10-3.

Uptake and correlates of chlamydia and gonorrhea testing among female sex workers in Southern China: a cross-sectional study.

BACKGROUND: Female sex workers (FSW) are highly susceptible to chlamydia and gonorrhea infection. However, there is limited literature examining their testing uptake to date. This study aimed to assess the uptake and determinants of chlamydia and gonorrhea testing among FSW in Southern China. METHODS: A cross-sectional study with convenience sampling was performed in five cities in Southern China. Data on socio-demographic characteristics, sexual behaviors, chlamydia and gonorrhea testing, and the utilization of health care services from participants were collected through face-to-face interviews. Univariate and multivariable logistic regressions were used to determine factors associated with chlamydia and gonorrhea testing, respectively. RESULTS: Overall, 1207 FSWs were recruited, with the mean age of 30.7 ± 6.8 years and an average number of clients of 7.0 (4.0-10.0) per week. 65.4% participants constantly used condoms with clients during the past month. Only 7.5 and 10.4% had been tested for chlamydia and gonorrhea in the last year, respectively. Multivariable analysis indicated that FSW who worked at low tiers (adjusted Odds Ratio (aOR) = 2.36, 95%CI:1.23-10.14), had more clients in the last month (aOR = 1.03, 95%CI:1.01-1.05), used condoms consistently (aOR = 1.79, 95%CI:1.12-2.86), had STD symptoms (aOR = 4.09,95%CI:2.62-6.40), had been tested for HIV (aOR = 5.16, 95%CI:3.21-8.30) or syphilis (aOR = 6.90, 95%CI:4.21-11.22) in the last year were more likely to have chlamydia testing. In addition, FSW who had more clients in the past month (aOR = 1.02,95%CI:1.00-1.04), had STD symptoms (aOR = 3.33, 95%CI:2.03-5.46), had been tested for HIV (aOR = 3.94, 95%CI:2.34-6.65) and syphilis (aOR = 3.27, 95%CI:1.96-5.46) in the last year were more likely to have gonorrhea testing. CONCLUSIONS: The testing rates of chlamydia and gonorrhea are low among Chinese FSW. Integrating chlamydia and gonorrhea testing into HIV testing promotion programs may help bridge the gap among FSW.

A robust test for X-chromosome genetic association accounting for X-chromosome inactivation and imprinting.

The X chromosome is known to play an important role in many sex-specific diseases. However, only a few single-nucleotide polymorphisms on the X chromosome have been found to be associated with diseases. Compared to the autosomes, conducting association tests on the X chromosome is more intractable due to the difference in the number of X chromosomes between females and males. On the other hand, X-chromosome inactivation takes place in female mammals, which is a phenomenon in which the expression of one copy of two X chromosomes in females is silenced in order to achieve the same gene expression level as that in males. In addition, imprinting effects may be related to certain diseases. Currently, there are some existing approaches taking X-chromosome inactivation into account when testing for associations on the X chromosome. However, none of them allows for imprinting effects. Therefore, in this paper, we propose a robust test, ZXCII, which accounts for both X-chromosome inactivation and imprinting effects without requiring specifying the genetic models in advance. Simulation studies are conducted in order to investigate the validity and performance of ZXCII under various scenarios of different parameter values. The simulation results show that ZXCII controls the type I error rate well when there is no association. Furthermore, with regards to power, ZXCII is robust in all of the situations considered and generally outperforms most of the existing methods in the presence of imprinting effects, especially under complete imprinting effects.

A statistical measure for the skewness of X chromosome inactivation based on case-control design.

BACKGROUND: Skewed X chromosome inactivation (XCI), which is a non-random process, is frequently observed in both healthy and affected females. Furthermore, skewed XCI has been reported to be related to many X-linked diseases. However, no statistical method is available in the literature to measure the degree of the skewness of XCI for case-control design. Therefore, it is necessary to develop methods for such a task. RESULTS: In this article, we first proposed a statistical measure for the degree of XCI skewing by using a case-control design, which is a ratio of two logistic regression coefficients after a simple reparameterization. Based on the point estimate of the ratio, we further developed three types of confidence intervals (the likelihood ratio, Fieller's and delta methods) to evaluate its variation. Simulation results demonstrated that the likelihood ratio method and the Fieller's method have more accurate coverage probability and more balanced tail errors than the delta method. We also applied these proposed methods to analyze the Graves' disease data for their practical use and found that rs3827440 probably undergoes a skewed XCI pattern with 68.7% of cells in heterozygous females having the risk allele T active, while the other 31.3% of cells keeping the normal allele C active. CONCLUSIONS: For practical application, we suggest using the Fieller's method in large samples due to the non-iterative computation procedure and using the LR method otherwise for its robustness despite its slightly heavy computational burden.

Two Powerful Tests for Parent-of-Origin Effects at Quantitative Trait Loci on the X Chromosome.

Parent-of-origin effects, which describe an occurrence where the expression of a gene depends on its parental origin, are an important phenomenon in epigenetics. Statistical methods for detecting parent-of-origin effects on autosomes have been investigated for 20 years, but the development of statistical methods for detecting parent-of-origin effects on the X chromosome is relatively new. In the literature, a class of Q-XPAT-type tests are the only tests for the parent-of-origin effects for quantitative traits on the X chromosome. In this paper, we propose two simple and powerful classes of tests to detect parent-of-origin effects for quantitative trait values on the X chromosome. The proposed tests can accommodate complete and incomplete nuclear families with any number of daughters. The simulation study shows that our proposed tests produce empirical type I error rates that are close to their respective nominal levels, as well as powers that are larger than those of the Q-XPAT-type tests. The proposed tests are applied to a real data set on Turner's syndrome, and the proposed tests give a more significant finding than the Q-C-XPAT test.

A powerful parent-of-origin effects test for qualitative traits on X chromosome in general pedigrees.

BACKGROUND: Genomic imprinting is one of the well-known epigenetic factors causing the association between traits and genes, and has generally been examined by detecting parent-of-origin effects of alleles. A lot of methods have been proposed to test for parent-of-origin effects on autosomes based on nuclear families and general pedigrees. Although these parent-of-origin effects tests on autosomes have been available for more than 15 years, there has been no statistical test developed to test for parent-of-origin effects on X chromosome, until the parental-asymmetry test on X chromosome (XPAT) and its extensions were recently proposed. However, these methods on X chromosome are only applicable to nuclear families and thus are not suitable for general pedigrees. RESULTS: In this article, we propose the pedigree parental-asymmetry test on X chromosome (XPPAT) statistic to test for parent-of-origin effects in the presence of association, which can accommodate general pedigrees. When there are missing genotypes in some pedigrees, we further develop the Monte Carlo pedigree parental-asymmetry test on X chromosome (XMCPPAT) to test for parent-of-origin effects, by inferring the missing genotypes given the observed genotypes based on a Monte Carlo estimation. An extensive simulation study has been carried out to investigate the type I error rates and the powers of the proposed tests. Our simulation results show that the proposed methods control the size well under the null hypothesis of no parent-of-origin effects. Moreover, XMCPPAT substantially outperforms the existing tests and has a much higher power than XPPAT which only uses complete nuclear families (with both parents) from pedigrees. We also apply the proposed methods to analyze rheumatoid arthritis data for their practical use. CONCLUSIONS: The proposed XPPAT and XMCPPAT test statistics are valid and powerful in detecting parent-of-origin effects on X chromosome for qualitative traits based on general pedigrees and thus are recommended.

A statistical measure for the skewness of X chromosome inactivation based on family trios.

BACKGROUND: X chromosome inactivation (XCI) is an important gene regulation mechanism in females to equalize the expression levels of X chromosome between two sexes. Generally, one of two X chromosomes in females is randomly chosen to be inactivated. Nonrandom XCI (XCI skewing) is also observed in females, which has been reported to play an important role in many X-linked diseases. However, there is no statistical measure available for the degree of the XCI skewing based on family data in population genetics. RESULTS: In this article, we propose a statistical approach to measure the degree of the XCI skewing based on family trios, which is represented by a ratio of two genotypic relative risks in females. The point estimate of the ratio is obtained from the maximum likelihood estimates of two genotypic relative risks. When parental genotypes are missing in some family trios, the expectation-conditional-maximization algorithm is adopted to obtain the corresponding maximum likelihood estimates. Further, the confidence interval of the ratio is derived based on the likelihood ratio test. Simulation results show that the likelihood-based confidence interval has an accurate coverage probability under the situations considered. Also, we apply our proposed method to the rheumatoid arthritis data from USA for its practical use, and find out that a locus, rs2238907, may undergo the XCI skewing against the at-risk allele. But this needs to be further confirmed by molecular genetics. CONCLUSIONS: The proposed statistical measure for the skewness of XCI is applicable to complete family trio data or family trio data with some paternal genotypes missing. The likelihood-based confidence interval has an accurate coverage probability under the situations considered. Therefore, our proposed statistical measure is generally recommended in practice for discovering the potential loci which undergo the XCI skewing.

Detection of Imprinting Effects for Quantitative Traits on X Chromosome Using Nuclear Families with Multiple Daughters.

Genomic imprinting is an epigenetic phenomenon in which the expression of an allele copy depends on its parental origin. This mechanism has been found to play an important role in many complex diseases. Statistical tests for imprinting effects have been developed for more than 15 years, but they are only suitable for autosomes. It was not until recently that the parental-asymmetry test on the X chromosome (XPAT) was proposed to test for imprinting effects. However, this test can only be used for qualitative traits. Therefore, in this article, we propose a class of PAT-type tests to test for imprinting for quantitative traits on the X chromosome in the presence of association, namely, Q-XPAT(c), Q-1-XPAT(c) and Q-C-XPAT(c), where c is a constant. These methods can accommodate complete and incomplete nuclear families with an arbitrary number of daughters. Extensive simulation studies demonstrate that the proposed tests control the size well under the null hypothesis of no imprinting effects and are powerful under various family structures. Moreover, by setting the inbreeding coefficient in females to be nonzero and using the assortative mating pattern in simulations, the proposed tests are shown to be valid under Hardy-Weinberg disequilibrium.

Generalized disequilibrium test for association in qualitative traits incorporating imprinting effects based on extended pedigrees.

BACKGROUND: For dichotomous traits, the generalized disequilibrium test with the moment estimate of the variance (GDT-ME) is a powerful family-based association method. Genomic imprinting is an important epigenetic phenomenon and currently, there has been increasing interest of incorporating imprinting to improve the test power of association analysis. However, GDT-ME does not take imprinting effects into account, and it has not been investigated whether it can be used for association analysis when the effects indeed exist. RESULTS: In this article, based on a novel decomposition of the genotype score according to the paternal or maternal source of the allele, we propose the generalized disequilibrium test with imprinting (GDTI) for complete pedigrees without any missing genotypes. Then, we extend GDTI and GDT-ME to accommodate incomplete pedigrees with some pedigrees having missing genotypes, by using a Monte Carlo (MC) sampling and estimation scheme to infer missing genotypes given available genotypes in each pedigree, denoted by MCGDTI and MCGDT-ME, respectively. The proposed GDTI and MCGDTI methods evaluate the differences of the paternal as well as maternal allele scores for all discordant relative pairs in a pedigree, including beyond first-degree relative pairs. Advantages of the proposed GDTI and MCGDTI test statistics over existing methods are demonstrated by simulation studies under various simulation settings and by application to the rheumatoid arthritis dataset. Simulation results show that the proposed tests control the size well under the null hypothesis of no association, and outperform the existing methods under various imprinting effect models. The existing GDT-ME and the proposed MCGDT-ME can be used to test for association even when imprinting effects exist. For the application to the rheumatoid arthritis data, compared to the existing methods, MCGDTI identifies more loci statistically significantly associated with the disease. CONCLUSIONS: Under complete and incomplete imprinting effect models, our proposed GDTI and MCGDTI methods, by considering the information on imprinting effects and all discordant relative pairs within each pedigree, outperform all the existing test statistics and MCGDTI can recapture much of the missing information. Therefore, MCGDTI is recommended in practice.

A powerful association test for qualitative traits incorporating imprinting effects using general pedigree data.

For qualitative traits and diallelic marker loci, the pedigree disequilibrium test (PDT) based on general pedigrees and its extension (Monte Carlo PDT (MCPDT)) for dealing with missing genotypes are simple and powerful tests for association. There is an increasing interest of incorporating imprinting into association analysis. However, PDT and MCPDT do not take account of the information on imprinting effects in the analysis, which may reduce their test powers when the effects are present. On the other hand, the transmission disequilibrium test with imprinting (TDTI*) combines imprinting into the mapping of association variants. However, TDTI* only accommodates two-generation nuclear families and thus is not suitable for extended pedigrees. In this article, we first extend PDT to incorporate imprinting and propose PDTI for complete pedigrees (no missing genotypes). To fully utilize pedigrees with missing genotypes, we further develop the Monte Carlo PDTI (MCPDTI) statistic based on Monte Carlo sampling and estimation. Both PDTI and MCPDTI are derived in a two-stage framework. Simulation study shows that PDTI and MCPDTI control the size well under the null hypothesis of no association and are more powerful than PDT and TDTI* (based on a sample of nuclear families randomly selecting from pedigrees) when imprinting effects exist.

Powerful tests for association on quantitative trait loci incorporating imprinting effects.

Genomic imprinting is an important epigenetic factor in complex traits study, and there has recently been considerable interest in association study for quantitative traits by incorporating imprinting. However, these methods need the assumptions of Hardy-Weinberg equilibrium or only use information from families with one child. In this paper, by taking imprinting into account and making no assumption about the distribution of the quantitative traits, we propose two novel classes of Q-C-TDTI(c) and Q-C-MAX(c) family-based association tests for quantitative traits. The tests flexibly accommodate family data with missing parental genotype and with multiple siblings. Q-C-TDTI(c) is derived from a two-stage analysis, where in the first stage Q-C-PAT(c) is applied to test for imprinting effects and in the second stage we select the most appropriate statistic among three transmission disequilibrium tests for association according to the finding from Q-C-PAT(c). Another proposed Q-C-MAX(c) approach takes the maximum of the three statistics. Compared with the existing alternative methods, the simulation results demonstrate that the two proposed tests are robust to population stratification and have better performance for testing association under various scenarios. Further, the powerful and versatile Q-C-TDTI(c) test is applied to analyze Framingham Heart Study data.

X chromosome-wide association study of quantitative biomarkers from the Alzheimer's Disease Neuroimaging Initiative study.

Introduction: Alzheimer's disease (AD) is a complex neurodegenerative disease with high heritability. Compared to autosomes, a higher proportion of disorder-associated genes on X chromosome are expressed in the brain. However, only a few studies focused on the identification of the susceptibility loci for AD on X chromosome. Methods: Using the data from the Alzheimer's Disease Neuroimaging Initiative Study, we conducted an X chromosome-wide association study between 16 AD quantitative biomarkers and 19,692 single nucleotide polymorphisms (SNPs) based on both the cross-sectional and longitudinal studies. Results: We identified 15 SNPs statistically significantly associated with different quantitative biomarkers of the AD. For the cross-sectional study, six SNPs (rs5927116, rs4596772, rs5929538, rs2213488, rs5920524, and rs5945306) are located in or near to six genes DMD, TBX22, LOC101928437, TENM1, SPANXN1, and ZFP92, which have been reported to be associated with schizophrenia or neuropsychiatric diseases in literature. For the longitudinal study, four SNPs (rs4829868, rs5931111, rs6540385, and rs763320) are included in or near to two genes RAC1P4 and AFF2, which have been demonstrated to be associated with brain development or intellectual disability in literature, while the functional annotations of other five novel SNPs (rs12157031, rs428303, rs5953487, rs10284107, and rs5955016) have not been found. Discussion: 15 SNPs were found statistically significantly associated with the quantitative biomarkers of the AD. Follow-up study in molecular genetics is needed to verify whether they are indeed related to AD. The findings in this article expand our understanding of the role of the X chromosome in exploring disease susceptibility, introduce new insights into the molecular genetics behind the AD, and may provide a mechanistic clue to further AD-related studies.

An Efficient Bayesian Method for Estimating the Degree of the Skewness of X Chromosome Inactivation Based on the Mixture of General Pedigrees and Unrelated Females.

Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases. Several methods have been proposed to estimate the degree of XCI-S (denoted as γ) for quantitative and qualitative traits based on unrelated females. However, there is no method available for estimating γ based on general pedigrees. Therefore, in this paper, we propose a Bayesian method to obtain the point estimate and the credible interval of γ based on the mixture of general pedigrees and unrelated females (called mixed data for brevity), which is also suitable for only general pedigrees. We consider the truncated normal prior and the uniform prior for γ. Further, we apply the eigenvalue decomposition and Cholesky decomposition to our proposed methods to accelerate the computation speed. We conduct extensive simulation studies to compare the performances of our proposed methods and two existing Bayesian methods which are only applicable to unrelated females. The simulation results show that the incorporation of general pedigrees can improve the efficiency of the point estimation and the precision and the accuracy of the interval estimation of γ. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use.

A powerful approach for association analysis incorporating imprinting effects.

MOTIVATION: For a diallelic marker locus, the transmission disequilibrium test (TDT) is a simple and powerful design for genetic studies. The TDT was originally proposed for use in families with both parents available (complete nuclear families) and has further been extended to 1-TDT for use in families with only one of the parents available (incomplete nuclear families). Currently, the increasing interest of the influence of parental imprinting on heritability indicates the importance of incorporating imprinting effects into the mapping of association variants. RESULTS: In this article, we extend the TDT-type statistics to incorporate imprinting effects and develop a series of new test statistics in a general two-stage framework for association studies. Our test statistics enjoy the nature of family-based designs that need no assumption of Hardy-Weinberg equilibrium. Also, the proposed methods accommodate complete and incomplete nuclear families with one or more affected children. In the simulation study, we verify the validity of the proposed test statistics under various scenarios, and compare the powers of the proposed statistics with some existing test statistics. It is shown that our methods greatly improve the power for detecting association in the presence of imprinting effects. We further demonstrate the advantage of our methods by the application of the proposed test statistics to a rheumatoid arthritis dataset. CONTACT: wingfung@hku.hk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A powerful parent-of-origin effects test for qualitative traits incorporating control children in nuclear families.

Genomic imprinting is an important epigenetic phenomenon in studying complex traits and has generally been examined by detecting parent-of-origin effects of alleles. The parental-asymmetry test (PAT) based on nuclear families with both parents and its extensions to deal with missing parental genotypes is simple and powerful for such a task. However, these methods only use case (affected) children in nuclear families and thus do not make full use of information on control (unaffected) children, if available, in these families. In this article, we propose a novel parent-of-origin effects test C-PATu (the combined test of PATu and 1-PATu) by using both the control and case children in nuclear families with one or both parents. C-PATu is essentially a weighted framework, in which the test based on all the control children and their parents and that based on all the case children and their parents are weighted according to the population disease prevalence. Simulation results demonstrate that the proposed tests control the size well under no parent-of-origin effects and using additional information from control children improves the power of the tests under the imprinting alternative. Application of C-PATu to a Framingham Heart Study data set further shows the feasibility in practical application of the test.

Detection of Parent-of-Origin Effects for the Variants Associated With Behavioral Disinhibition in the MCTFR Data.

Behavioral disinhibition is one of the important characteristics of many mental diseases. It has been reported in literature that serious behavioral disinhibition will affect people's health and greatly reduce people's quality of life. Meanwhile, behavioral disinhibition can easily lead to illegal drug abuse and violent crimes, etc., which will bring great harm to the society. At present, large-scale genome-wide association analysis has identified many loci associated with behavioral disinhibition. However, these studies have not incorporated the parent-of-origin effects (POE) into analysis, which may ignore or underestimate the genetic effects of loci on behavioral disinhibition. Therefore, in this article, we analyzed the five phenotypes related to behavioral disinhibition in the Minnesota Center for Twin and Family Research data (nicotine, alcohol consumption, alcohol dependence, illicit drugs, and non-substance use related behavioral disinhibition), to further explore the POE of variants on behavioral disinhibition. We applied a linear mixed model to test for the POE at a genome-wide scale on five transformed phenotypes, and found nine SNPs with statistically significant POE at the significance level of 5 × 10-8. Among them, SNPs rs4141854, rs9394515, and rs4711553 have been reported to be associated with two neurological disorders (restless legs syndrome and Tourette's syndrome) which are related to behavioral disinhibition; SNPs rs12960235 and rs715351 have been found to be associated with head and neck squamous cell carcinoma, skin cancer and type I diabetes, while both SNPs have not been identified to be related to behavioral disinhibition in literature; SNPs rs704833, rs6837925, rs1863548, and rs11067062 are novel loci identified in this article, and their function annotations have not been reported in literature. Follow-up study in molecular genetics is needed to verify whether they are surely related to behavioral disinhibition.

Gene-Based Methods for Estimating the Degree of the Skewness of X Chromosome Inactivation.

Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases, and currently several methods have been proposed to estimate the degree of the XCI-S (denoted as γ) for a single locus. However, no method has been available to estimate γ for genes. Therefore, in this paper, we first propose the point estimate and the penalized point estimate of γ for genes, and then derive its confidence intervals based on the Fieller's and penalized Fieller's methods, respectively. Further, we consider the constraint condition of γ∈[0, 2] and propose the Bayesian methods to obtain the point estimates and the credible intervals of γ, where a truncated normal prior and a uniform prior are respectively used (denoted as GBN and GBU). The simulation results show that the Bayesian methods can avoid the extreme point estimates (0 or 2), the empty sets, the noninformative intervals ([0, 2]) and the discontinuous intervals to occur. GBN performs best in both the point estimation and the interval estimation. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use. In summary, in practical applications, we recommend using GBN to estimate γ of genes.

Detection of parent-of-origin effects using general pedigree data.

Genomic imprinting is an important epigenetic factor in complex traits study, which has generally been examined by testing for parent-of-origin effects of alleles. For a diallelic marker locus, the parental-asymmetry test (PAT) based on case-parents trios and its extensions to incomplete nuclear families (1-PAT and C-PAT) are simple and powerful for detecting parent-of-origin effects. However, these methods are suitable only for nuclear families and thus are not amenable to general pedigree data. Use of data from extended pedigrees, if available, may lead to more powerful methods than randomly selecting one two-generation nuclear family from each pedigree. In this study, we extend PAT to accommodate general pedigree data by proposing the pedigree PAT (PPAT) statistic, which uses all informative family trios from pedigrees. To fully utilize pedigrees with some missing genotypes, we further develop the Monte Carlo (MC) PPAT (MCPPAT) statistic based on MC sampling and estimation. Extensive simulations were carried out to evaluate the performance of the proposed methods. Under the assumption that the pedigrees and their associated affection patterns are randomly drawn from a population of pedigrees with at least one affected offspring, we demonstrated that MCPPAT is a valid test for parent-of-origin effects in the presence of association. Further, MCPPAT is much more powerful compared to PAT for trios or even PPAT for all informative family trios from the same pedigrees if there is missing data. Application of the proposed methods to a rheumatoid arthritis dataset further demonstrates the advantage of MCPPAT.

Detection of parent-of-origin effects for quantitative traits in complete and incomplete nuclear families with multiple children.

For a diallelic genetic marker locus, tests like the parental-asymmetry test (PAT) are simple and powerful for detecting parent-of-origin effects. However, these approaches are applicable only to qualitative traits and thus are currently not suitable for quantitative traits. In this paper, the authors propose a novel class of PAT-type parent-of-origin effects tests for quantitative traits in families with both parents and an arbitrary number of children, which is denoted by Q-PAT(c) for some constant c. The authors further develop Q-1-PAT(c) for detection of parent-of-origin effects when information is available on only 1 parent in each family. The authors suggest the Q-C-PAT(c) test for combining families with data on both parental genotypes and families with data on only 1 parental genotype. Simulation studies show that the proposed tests control the empirical type I error rates well under the null hypothesis of no parent-of-origin effects. Power comparison also demonstrates that the proposed methods are more powerful than the existing likelihood ratio test. Although normality is commonly assumed in methods for studying quantitative traits, the tests proposed in this paper do not make any assumption about the distribution of the quantitative trait.