Power calculations for likelihood ratio tests for offspring genotype risks, maternal effects, and parent-of-origin (POO) effects in the presence of missing parental genotypes when unaffected siblings are available

Estimating indirect parental genetic effects on offspring phenotypes using virtual parental genotypes derived from sibling and half sibling pairs

Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to their children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset conditions, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating “virtual” mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We apply our approach to 19066 sibling pairs from the UK Biobank and show that a polygenic score consisting of imputed parental educational attainment SNP dosages is strongly related to offspring educational attainment even after correcting for offspring genotype at the same loci. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring.

Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to children. Estimating indirect parental genetic effects on offspring outcomes at the genotype level has been challenging because it requires large-scale, individual level genotypes from both parents and their offspring, and there is a paucity of cohorts around the world with this information. Here we present a new approach to estimate indirect parental genetic effects without the requirement of physically genotyped parents. Our method creates virtual parental genotypes based on the genotypes of offspring pairs, and then uses these virtual genotypes in downstream genetic association analyses. We developed a software package “IMPISH” that allows users to impute virtual parental genotypes in their own genome-wide datasets and then use these in downstream genome-wide association analyses, as well a series of power calculators to estimate the power to detect indirect parental genetic effects on offspring phenotypes. We apply our method to educational attainment data from the UK Biobank and show that indirect parental genetic effects are related to offspring educational attainment even after correcting for offspring genotype at the same loci.

Learning about the X from our parents

The X chromosome is generally understudied in association studies, in part because the analyst has had limited methodological options. For nuclear-family-based association studies, most current methods extend the transmission disequilibrium test (TDT) to the X chromosome. We present a new method to study association in case-parent triads: the parent-informed likelihood ratio test for the X chromosome (PIX-LRT). Our method enables estimation of relative risks and takes advantage of parental genotype information and the sex of the affected offspring to increase statistical power to detect an effect. Under a parental exchangeability assumption for the X, if case-parent triads are complete, the parents of affected offspring provide an independent replication sample for estimates based on transmission distortion to their affected offspring. For each offspring sex we combine the parent-level and the offspring-level information to form a likelihood ratio test statistic; we then combine the two to form a combined test statistic. Our method can estimate relative risks under different modes of inheritance or a more general co-dominant model. In triads with missing parental genotypes, the method accounts for missingness with the Expectation-Maximization algorithm. We calculate non-centrality parameters to assess the power gain and robustness of our method compared to alternative methods. We apply PIX-LRT to publically available data from an international consortium of genotyped families affected by the birth defect oral cleft and find a strong, internally-replicated signal for a SNP marker related to cleft lip with or without cleft palate.

Review of statistical methodologies for the detection of parent-of-origin effects in family trio genome-wide association data with binary disease traits

The detection of parent-of-origin effects aims to identify whether the functionality of alleles, and in turn associated phenotypic traits, depends on the parental origin of the alleles. Different parent-of-origin effects have been identified through a variety of mechanisms and a number of statistical methodologies for their detection have been proposed, in particular for genome-wide association studies (GWAS). GWAS have had limited success in explaining the heritability of many complex disorders and traits, but successful identification of parent-of-origin effects using trio (mother, father and offspring) GWAS may help shed light on this missing heritability. However, it is important to choose the most appropriate parent-of-origin test or methodology, given knowledge of the phenotype, amount of available data and the type of parent-of-origin effect(s) being considered. This review brings together the parent-of-origin detection methodologies available, comparing them in terms of power and type I error for a number of different simulated data scenarios, and finally offering guidance as to the most appropriate choice for the different scenarios.

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 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 imprinting and heterogeneous maternal effects on high blood pressure using Framingham Heart Study data

Both imprinting and maternal effects could lead to parent-of-origin patterns in complex traits of human disorders. Statistical methods that differentiate these two effects and identify them simultaneously by using family-based data from retrospective studies are available. The usual data structures include case-parents triads and nuclear families with multiple affected siblings. We develop a likelihood-based method to detect imprinting and maternal effects simultaneously using data from prospective studies. The proposed method utilizes both affected and unaffected siblings in nuclear families by modeling familial genotypes and offspring's disease status jointly. Maternal effect is usually modeled as a fixed effect under the assumption that maternal variant allele(s) has (have) identical effect on any offspring. However, recent studies report that different people may carry different amounts of substances encoded by the mother's variant allele(s) (called maternal microchimerism), which could result in heterogeneity of maternal effects. The proposed method incorporates the heterogeneity of maternal effects by adding a random component to the logit of the penetrance. Our method was applied to the Framingham Heart Study data in two steps to detect single-nucleotide polymorphisms (SNPs) that may be associated with high blood pressure. In the first step, SNPs that affect susceptibility of high blood pressure through minor allele, genomic imprinting, or maternal effects were identified by using the proposed model without the random effect component. In the second step, we fitted the mixed effect model to the identified SNPs that have significant maternal effect to detect heterogeneity of the maternal effects.

Finding genes underlying human disease

With the surge in genome-wide association studies (GWAS), many have asked the question 'Are linkage studies dead?' In this article, we survey the approaches used in mapping human disease genes, reviewing the analysis strategies that preceded and laid the groundwork for GWAS. We note that earlier approaches are still useful and the development of new methodology is warranted.

Detection of parent-of-origin effects in complete and incomplete nuclear families with multiple affected children using multiple tightly linked markers

For a diallelic marker locus, the parental-asymmetry test (PAT) based on case-parents trios and its extensions to accommodate incomplete unclear families (1-PAT and C-PAT) are simple and powerful approaches to test for parent-of-origin effects. However, haplotype analysis is generally regarded as advantageous over single-marker analysis in genetic study of common complex diseases. This is mainly due to the fact that complex diseases are often associated with multiple markers. As such, HAP-PAT was constructed to test for parent-of-origin effects in the framework of haplotype analysis. However, its applicability is limited due to the need for complete parental information. In this paper, for nuclear families with only one parent and multiple affected children, we develop HAP-1-PAT to test for parent-of-origin effects using multiple tightly linked markers. We further propose HAP-C-PAT to combine data from families with both parents and those with only one parent. We carry out a simulation study to evaluate the validity and power of the test statistics in various settings, including incomplete family rates, marker/disease-locus linkage disequilibrium patterns, and population models. We perform analysis for all possible combinations of the markers being considered. A permutation-based Monte Carlo procedure is devised to determine the significance of the tests; the corrected global p values taking into account of multiple testing are used for inferences. The results show that HAP-1-PAT and HAP-C-PAT would work well even under the population stratification demographic model and assortative mating demographic model. Furthermore, for the disease models considered, there are significant gains in power from haplotype analysis compared to single-marker analysis, and from combined analysis using HAP-C-PAT compared to analysis using HAP-PAT for the complete family data only.

Investigating parent of origin effects in studies of type 2 diabetes and obesity

The role of parent-of-origin effects (POE) in the etiology of complex diseases such as type 2 diabetes (T2DM) and obesity is currently of intense interest, but still largely unclear. POE are transmittable genetic effects whereby the expression of the phenotype in the offspring depends upon whether the transmission originated from the mother or father. In mammals, POE can be caused by genetic imprinting, intrauterine effects, or maternally inherited mitochondrial genes. In this paper, we describe the different mechanisms underlying POE, characterize known examples of POE in rare forms of diabetes, and review the evidence from linkage and association studies for POE in T2DM and obesity. Finally, we summarize some of the new and established statistical and experimental approaches commonly used to detect POE. Through this paper, we hope emphasizes the potentially significant importance of POE in the etiology of T2DM and obesity.

Detection of parent-of-origin effects based on complete and incomplete nuclear families with multiple affected children

Parent-of-origin effects are important in studying genetic traits. More than 1% of all mammalian genes are believed to show parent-of-origin effects. Some statistical methods may be ineffective or fail to detect linkage or association for a gene with parent-of-origin effects. Based on case-parents trios, the parental-asymmetry test (PAT) is simple and powerful in detecting parent-of-origin effects. However, it is common in practice to collect nuclear families with both parents as well as nuclear families with only one parent. In this paper, when only one parent is available for each family with an arbitrary number of affected children, we firstly develop a new test statistic 1-PAT to test for parent-of-origin effects in the presence of association between an allele at the marker locus under study and a disease gene. Then we extend the PAT to accommodate complete nuclear families each with one or more affected children. Combining families with both parents and families with only one parent, the C-PAT is proposed to detect parent-of-origin effects. The validity of the test statistics is verified by simulation in various scenarios of parameter values. A power study shows that using the additional information from incomplete nuclear families in the analysis greatly improves the power of the tests, compared to that based on only complete nuclear families. Also, utilizing all affected children in each family, the proposed tests have a higher power than when only one affected child from each family is selected. Additional power comparison also demonstrates that the C-PAT is more powerful than a number of other tests for detecting parent-of-origin effects.

Genomic imprinting in the development and evolution of psychotic spectrum conditions

I review and evaluate genetic and genomic evidence salient to the hypothesis that the development and evolution of psychotic spectrum conditions have been mediated in part by alterations of imprinted genes expressed in the brain. Evidence from the genetics and genomics of schizophrenia, bipolar disorder, major depression, Prader-Willi syndrome, Klinefelter syndrome, and other neurogenetic conditions support the hypothesis that the etiologies of psychotic spectrum conditions commonly involve genetic and epigenetic imbalances in the effects of imprinted genes, with a bias towards increased relative effects from imprinted genes with maternal expression or other genes favouring maternal interests. By contrast, autistic spectrum conditions, including Kanner autism, Asperger syndrome, Rett syndrome, Turner syndrome, Angelman syndrome, and Beckwith-Wiedemann syndrome, commonly engender increased relative effects from paternally expressed imprinted genes, or reduced effects from genes favouring maternal interests. Imprinted-gene effects on the etiologies of autistic and psychotic spectrum conditions parallel the diametric effects of imprinted genes in placental and foetal development, in that psychotic spectrum conditions tend to be associated with undergrowth and relatively-slow brain development, whereas some autistic spectrum conditions involve brain and body overgrowth, especially in foetal development and early childhood. An important role for imprinted genes in the etiologies of psychotic and autistic spectrum conditions is consistent with neurodevelopmental models of these disorders, and with predictions from the conflict theory of genomic imprinting.

The evolutionary social brain: From genes to psychiatric conditions

The commentaries on our target article, “Psychosis and Autism as Diametrical Disorders of the Social Brain,” reflect the multidisciplinary yet highly fragmented state of current studies of human social cognition. Progress in our understanding of the human social brain must come from studies that integrate across diverse analytic levels, using conceptual frameworks grounded in evolutionary biology.

Folate and one-carbon metabolism gene polymorphisms and their associations with oral facial clefts

Folate metabolism plays a critical role in embryonic development. Prenatal folate supplementation reduces the risk of neural tube defects and probably oral facial clefts. Previous studies of related metabolic genes have associated polymorphisms in cystathionine-beta-synthase (CBS) and 5,10-methylenetetrahydrofolate reductase (MTHFR) with cleft risk. We explored associations between genes related to one-carbon metabolism and clefts in a Norwegian population-based study that included 362 families with cleft lip with or without cleft palate (CL/P) and 191 families with cleft palate only (CPO). We previously showed a 39% reduction in risk of CL/P with folic acid supplementation in this population. In the present study we genotyped 12 polymorphisms in nine genes related to one-carbon metabolism and looked for associations of clefting risk with fetal polymorphisms, maternal polymorphisms, as well as parent-of-origin effects, using combined likelihood-ratio tests (LRT). We also stratified by maternal periconceptional intake of folic acid (>400 microg) to explore gene-exposure interactions. We found a reduced risk of CL/P with mothers who carried the CBS C699T variant (rs234706); relative risk was 0.94 with one copy of the T allele (95% CI 0.63-1.4) and 0.50 (95% CI 0.26-0.96) with two copies (P = 0.008). We found no evidence of interaction of this variant with folate status. We saw no evidence of risk from the MTHFR C677T variant (rs1801133) either overall or after stratifying by maternal folate intake. No associations were found between any of the polymorphisms and CPO. Genetic variations in the nine metabolic genes examined here do not confer a substantial degree of risk for clefts.