Investigation of maternal effects, maternal-fetal interactions and parent-of-origin effects (imprinting), using mothers and their offspring

Efficient inference of parent-of-origin effect using case-control mother-child genotype data

Parent-of-origin effect plays an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parent-of-origin effect and is often convenient to collect in practice. Most existing methods for assessing parent-of-origin effect do not incorporate any covariates, which may be required to control for confounding factors. We propose to model the parent-of-origin effect through a logistic regression model, with predictors including maternal and child genotypes, parental origins, and covariates. The parental origins may not be fully inferred from genotypes of a target genetic marker, so we propose to use genotypes of markers tightly linked to the target marker to increase inference efficiency. A robust statistical inference procedure is developed based on a modified profile log-likelihood in a retrospective way. A computationally feasible expectation-maximization algorithm is devised to estimate all unknown parameters involved in the modified profile log-likelihood. This algorithm differs from the conventional expectation-maximization algorithm in the sense that it is based on a modified instead of the original profile log-likelihood function. The convergence of the algorithm is established under some mild regularity conditions. This expectation-maximization algorithm also allows convenient handling of missing child genotypes. Large sample properties, including weak consistency, asymptotic normality, and asymptotic efficiency, are established for the proposed estimator under some mild regularity conditions. Finite sample properties are evaluated through extensive simulation studies and the application to a real dataset.

Statistical methods to detect mother-father genetic interaction effects on risk of infertility: A genome-wide approach

Infertility is a heterogeneous phenotype, and for many couples, the causes of fertility problems remain unknown. One understudied hypothesis is that allelic interactions between the genotypes of the two parents may influence the risk of infertility. Our aim was, therefore, to investigate how allelic interactions can be modeled using parental genotype data linked to 15,789 pregnancies selected from the Norwegian Mother, Father, and Child Cohort Study. The newborns in 1304 of these pregnancies were conceived using assisted reproductive technologies (ART), and the remainder were conceived naturally. Treating the use of ART as a proxy for infertility, different parameterizations were implemented in a genome-wide screen for interaction effects between maternal and paternal alleles at the same locus. Some of the models were more similar in the way they were parameterized, and some produced similar results when implemented on a genome-wide scale. The results showed near-significant interaction effects in genes relevant to the phenotype under study, such as Dynein axonemal heavy chain 17 (DNAH17) with a recognized role in male infertility. More generally, the interaction models presented here are readily adaptable to the study of other phenotypes in which maternal and paternal allelic interactions are likely to be involved.

POIROT: a powerful test for parent-of-origin effects in unrelated samples leveraging multiple phenotypes

MOTIVATION

There is widespread interest in identifying genetic variants that exhibit parent-of-origin effects (POEs) wherein the effect of an allele on phenotype expression depends on its parental origin. POEs can arise from different phenomena including genomic imprinting and have been documented for many complex traits. Traditional tests for POEs require family data to determine parental origins of transmitted alleles. As most genome-wide association studies (GWAS) sample unrelated individuals (where allelic parental origin is unknown), the study of POEs in such datasets requires sophisticated statistical methods that exploit genetic patterns we anticipate observing when POEs exist. We propose a method to improve discovery of POE variants in large-scale GWAS samples that leverages potential pleiotropy among multiple correlated traits often collected in such studies. Our method compares the phenotypic covariance matrix of heterozygotes to homozygotes based on a Robust Omnibus Test. We refer to our method as the Parent of Origin Inference using Robust Omnibus Test (POIROT) of multiple quantitative traits.

RESULTS

Through simulation studies, we compared POIROT to a competing univariate variance-based method which considers separate analysis of each phenotype. We observed POIROT to be well-calibrated with improved power to detect POEs compared to univariate methods. POIROT is robust to non-normality of phenotypes and can adjust for population stratification and other confounders. Finally, we applied POIROT to GWAS data from the UK Biobank using BMI and two cholesterol phenotypes. We identified 338 genome-wide significant loci for follow-up investigation.

AVAILABILITY AND IMPLEMENTATION

The code for this method is available at https://github.com/staylorhead/POIROT-POE.

A family-based study of genetic and epigenetic effects across multiple neurocognitive, motor, social-cognitive and social-behavioral functions

Many psychiatric and neurodevelopmental disorders are known to be heritable, but studies trying to elucidate the genetic architecture of such traits often lag behind studies of somatic traits and diseases. The reasons as to why relatively few genome-wide significant associations have been reported for such traits have to do with the sample sizes needed for the detection of small effects, the difficulty in defining and characterizing the phenotypes, partially due to overlaps in affected underlying domains (which is especially true for cognitive phenotypes), and the complex genetic architectures of the phenotypes, which are not wholly captured in traditional case-control GWAS designs. We aimed to tackle the last two issues by performing GWASs of eight quantitative neurocognitive, motor, social-cognitive and social-behavioral traits, which may be considered endophenotypes for a variety of psychiatric and neurodevelopmental conditions, and for which we employed models capturing both general genetic association and parent-of-origin effects, in a family-based sample comprising 402 children and their parents (mostly family trios). We identified 48 genome-wide significant associations across several traits, of which 3 also survived our strict study-wide quality criteria. We additionally performed a functional annotation of implicated genes, as most of the 48 associations were with variants within protein-coding genes. In total, our study highlighted associations with five genes (TGM3, CACNB4, ANKS1B, CSMD1 and SYNE1) associated with measures of working memory, processing speed and social behavior. Our results thus identify novel associations, including previously unreported parent-of-origin associations with relevant genes, and our top results illustrate new potential gene → endophenotype → disorder pathways.

Maternal-fetal genetic interactions, imprinting, and risk of placental abruption

RESULTS

Abruption cases were more likely to experience preeclampsia, have shorter gestational age, and deliver infants with lower birthweight compared with controls. Models with MFGI effects provided improved fit than models with only maternal and fetal genotype main effects for SNP rs12530904 (p-value = 1.2e-04) in calcium/calmodulin-dependent protein kinase [CaM kinase] II beta (CAMK2B), and, SNP rs73136795 (p-value = 1.9e-04) in peroxisome proliferator-activated receptor-gamma (PPARG), both MB genes. We identified 320 SNPs in 45 maternally-imprinted genes (including potassium voltage-gated channel subfamily Q member 1 [KCNQ1], neurotrimin [NTM], and, ATPase phospholipid transporting 10 A [ATP10A]) associated with abruption. Top hits included rs2012323 (p-value = 1.6E-16) and rs12221520 (p-value1.3e-13) in KCNQ1, rs8036892 (p-value = 9.3E-17) and rs188497582 in ATP10A, rs12589854 (p-value = 2.9E-11) and rs80203467 (p-value = 4.6e-11) in maternally expressed 8, small nucleolar RNA host (MEG8), and rs138281088 in solute carrier family 22 member 2 (SLC22A2) (p-value = 6.8e-9).

CONCLUSIONS

We identified novel PA-related maternal-fetal MB gene interactions and imprinting effects that highlight the role of the fetus in PA risk development. Findings can inform mechanistic investigations to understand the pathogenesis of PA.

Benchmarking statistical methods for analyzing parent-child dyads in genetic association studies

Genetic association studies of child health outcomes often employ family-based study designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide marker data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multiethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.

Pleiotropy between language impairment and broader behavioral disorders-an investigation of both common and rare genetic variants

BACKGROUND

Language plays a major role in human behavior. For this reason, neurodevelopmental and psychiatric disorders in which linguistic ability is impaired could have a big impact on the individual's social interaction and general wellbeing. Such disorders tend to have a strong genetic component, but most past studies examined mostly the linguistic overlaps across these disorders; investigations into their genetic overlaps are limited. The aim of this study was to assess the potential genetic overlap between language impairment and broader behavioral disorders employing methods capturing both common and rare genetic variants.

METHODS

We employ polygenic risk scores (PRS) trained on specific language impairment (SLI) to evaluate genetic overlap across several disorders in a large case-cohort sample comprising ~13,000 autism spectrum disorder (ASD) cases, including cases of childhood autism and Asperger's syndrome, ~15,000 attention deficit/hyperactivity disorder (ADHD) cases, ~3000 schizophrenia cases, and ~21,000 population controls. We also examine rare variants in SLI/language-related genes in a subset of the sample that was exome-sequenced using the SKAT-O method.

RESULTS

We find that there is little evidence for genetic overlap between SLI and ADHD, schizophrenia, and ASD, the latter being in line with results of linguistic analyses in past studies. However, we observe a small, significant genetic overlap between SLI and childhood autism specifically, which we do not observe for SLI and Asperger's syndrome. Moreover, we observe that childhood autism cases have significantly higher SLI-trained PRS compared to Asperger's syndrome cases; these results correspond well to the linguistic profiles of both disorders. Our rare variant analyses provide suggestive evidence of association for specific genes with ASD, childhood autism, and schizophrenia.

CONCLUSIONS

Our study provides, for the first time, to our knowledge, genetic evidence for ASD subtypes based on risk variants for language impairment.

Covariate adjusted inference of parent-of-origin effects using case-control mother-child paired multilocus genotype data

It is of great interest to identify parent-of-origin effects (POEs) since POEs play an important role in many human heritable disorders and human early life growth and development. POE is sometimes referred to as imprinting effect in the literature. Compared with the standard logistic regression analyses, retrospective likelihood-based statistical methods are more powerful in identifying POEs when data are collected from related individuals retrospectively. However, none of existing retrospective-based methods can appropriately incorporate covariates that should be adjusted for if they are confounding factors. In this paper, a novel semiparametric statistical method, M-HAP, is developed to detect POEs by fully exploring available information from multilocus genotypes of case-control mother-child pairs and covariates. Some large sample properties are established for M-HAP. Finite sample properties of M-HAP are illustrated by extensive simulation studies and real data applications to the Jerusalem Perinatal Study and the Danish National Birth Cohort study, which confirm the desired superiority of M-HAP over some existing methods. M-HAP has been implemented in the updated R package CCMO.

Genome-Wide Association Studies of Conotruncal Heart Defects with Normally Related Great Vessels in the United States

Conotruncal defects with normally related great vessels (CTD-NRGVs) occur in both patients with and without 22q11.2 deletion syndrome (22q11.2DS), but it is unclear to what extent the genetically complex etiologies of these heart defects may overlap across these two groups, potentially involving variation within and/or outside of the 22q11.2 region. To explore this potential overlap, we conducted genome-wide SNP-level, gene-level, and gene set analyses using common variants, separately in each of five cohorts, including two with 22q11.2DS (N = 1472 total cases) and three without 22q11.2DS (N = 935 total cases). Results from the SNP-level analyses were combined in meta-analyses, and summary statistics from these analyses were also used in gene and gene set analyses. Across all these analyses, no association was significant after correction for multiple comparisons. However, several SNPs, genes, and gene sets with suggestive evidence of association were identified. For common inherited variants, we did not identify strong evidence for shared genomic mechanisms for CTD-NRGVs across individuals with and without 22q11.2 deletions. Nevertheless, several of our top gene-level and gene set results have been linked to cardiogenesis and may represent candidates for future work.

Common Variation in Cytoskeletal Genes is Associated with Conotruncal Heart Defects

There is strong evidence for a genetic contribution to non-syndromic congenital heart defects (CHDs). However, exome- and genome-wide studies conducted at the variant and gene-level have identified few genome-wide significant CHD-related genes. Gene-set analyses are a useful complement to such studies and candidate gene-set analyses of rare variants have provided insight into the genetics of CHDs. However, similar analyses have not been conducted using data on common genetic variants. Consequently, we conducted common variant analyses of 15 CHD candidate gene-sets, using data from two common types of CHDs: conotruncal heart defects (1431 cases) and left ventricular outflow tract defects (509 cases). After Bonferroni correction for evaluation of multiple gene-sets, the cytoskeletal gene-set was significantly associated with conotruncal heart defects (β_S = 0.09; 95% confidence interval (CI) 0.03–0.15). This association was stronger when analyses were restricted to the sub-set of cytoskeletal genes that have been observed to harbor rare damaging genotypes in at least two CHD cases (β_S = 0.32, 95% CI 0.08–0.56). These findings add to the evidence linking cytoskeletal genes to CHDs and suggest that, for cytoskeletal genes, common variation may contribute to the risk of CHDs.

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.

Case-Parent Trio Studies in Cleft Lip and Palate

Cleft lip with or without cleft palate (CL/P) is one of the most common congenital malformations in humans involving various genetic and environmental risk factors. The prevalence of CL/P varies according to geographical location, ethnicity, race, gender, and socioeconomic status, affecting approximately 1 in 800 live births worldwide. Genetic studies aim to understand the mechanisms contributory to a phenotype by measuring the association between genetic variants and also between genetic variants and phenotype population. Genome-wide association studies are standard tools used to discover genetic loci related to a trait of interest. Genetic association studies are generally divided into two main design types: population-based studies and family-based studies. The epidemiological population-based studies comprise unrelated individuals that directly compare the frequency of genetic variants between (usually independent) cases and controls. The alternative to population-based studies (case-control designs) includes various family-based study designs that comprise related individuals. An example of such a study is a case-parent trio design study, which is commonly employed in genetics to identify the variants underlying complex human disease where transmission of alleles from parents to offspring is studied. This article describes the fundamentals of case-parent trio study, trio design and its significances, statistical methods, and limitations of the trio studies.

Maternal effects shape the alternative splicing of parental alleles in reciprocal cross hybrids of Megalobrama amblycephala × Culter alburnus

Background

Maternal effects contribute to adaptive significance for shaping various phenotypes of many traits. Potential implications of maternal effects are the cause of expression diversity, but these effects on mRNA expression and alternative splicing (AS) have not been fully elucidated in hybrid animals.

Results

Two reciprocal cross hybrids following hybridization of Megalobrama amblycephala (blunt snout bream, BSB) and Culter alburnus (topmouth culter, TC) were used as a model to investigate maternal effects. By comparing the expression of BSB- and TC- homoeologous genes between the two reciprocal cross hybrids, we identified 49–348 differentially expressed BSB-homoeologous genes and 54–354 differentially expressed TC-homoeologous genes. 2402, 2959, and 3418 AS events between the two reciprocal cross hybrids were detected in Illumina data of muscle, liver, and gonad, respectively. Moreover, 21,577 (TC-homoeologs) and 30,007 (BSB-homoeologs) AS events were found in the 20,131 homoeologous gene pairs of TBF₃ based on PacBio data, while 30,561 (TC-homoeologs) and 30,305 (BSB-homoeologs) AS events were found in BTF₃. These results further improve AS prediction at the homoeolog level. The various AS patterns in bmpr2a belonging to the bone morphogenetic protein family were selected as AS models to investigate the expression diversity and its potential effects to body shape traits.

Conclusions

The distribution of differentially expressed genes and AS in BSB- and TC-subgenomes exhibited various changes between the two reciprocal cross hybrids, suggesting that maternal effects were the cause of expression diversity. These findings provide a novel insight into mRNA expression changes and AS under maternal effects in lower vertebrates.

Design efficiency in genetic association studies

Selecting the best design for genetic association studies requires careful deliberation; different study designs can be used to scan for different genetic effects, and each design has its own set of strengths and limitations. A variety of family and unrelated control configurations are amenable to genetic association analyses, including the case-control design, case-parent triads, and case-parent triads in combination with unrelated controls or control-parent triads. Ultimately, the goal is to choose the design that achieves the highest statistical power using the lowest cost. For given parameter values and genotyped individuals, designs can be compared directly by computing the power. However, a more informative and general design comparison can be achieved by studying the relative efficiency, defined as the ratio of variances of two different parameter estimators, corresponding to two separate designs. Using log-linear modeling, we derive the relative efficiency from the asymptotic variance of the parameter estimators and relate it to the concept of Pitman efficiency. The relative efficiency takes into account the fact that different designs impose different costs relative to the number of genotyped individuals. We show that while optimal efficiency for analyses of regular autosomal effects is achieved using the standard case-control design, the case-parent triad design without unrelated controls is efficient when searching for parent-of-origin effects. Due to the potential loss of efficiency, maternal genes should generally not be adjusted for in an initial genome-wide association study scan of offspring genes but instead checked post hoc. The relative efficiency calculations are implemented in our R package Haplin.

Incorporating information from markers in LD with test locus for detecting imprinting and maternal effects

Numerous statistical methods have been developed to explore genomic imprinting and maternal effects by identifying parent-of-origin patterns in complex human diseases. However, because most of these methods only use available locus-specific genotype data, it is sometimes impossible for them to infer the distribution of parental origin of a variant allele, especially when some genotypes are missing. In this article, we propose a two-step approach, LIMEhap, to improve upon a recent partial likelihood inference method. In the first step, the distribution of the missing genotypes is inferred through the construction of haplotypes by using information from nearby loci. In the second step, a partial likelihood method is applied to the inferred data. To substantiate the validity of the proposed procedures, we simulated data in a genomic region of gene GPX1. The results show that, by borrowing genetic information from nearby loci, the power of the proposed method can be close to that with complete genotype data at the locus of interest. Since the inference on the genotype distribution is made under the assumption of Hardy-Weinberg Equilibrium (HWE), we further studied the robustness of LIMEhap to violation of HWE. Finally, we demonstrate the utility of LIMEhap by applying it to an autism dataset.

Exome sequencing of family trios from the National Birth Defects Prevention Study: Tapping into a rich resource of genetic and environmental data

BACKGROUND

The National Birth Defects Prevention Study (NBDPS) is a multisite, population-based, case-control study of genetic and nongenetic risk factors for major structural birth defects. Eligible women had a pregnancy affected by a birth defect or a liveborn child without a birth defect between 1997 and 2011. They were invited to complete a telephone interview to collect pregnancy exposure data and were mailed buccal cell collection kits to collect specimens from themselves, their child (if living), and their child's father. Over 23,000 families representing more than 30 major structural birth defects provided DNA specimens.

METHODS

To evaluate their utility for exome sequencing (ES), specimens from 20 children with colonic atresia were studied. Evaluations were conducted on specimens collected using cytobrushes stored and transported in open versus closed packaging, on native genomic DNA (gDNA) versus whole genome amplified (WGA) products and on a library preparation protocol adapted to low amounts of DNA.

RESULTS

The DNA extracted from brushes in open packaging yielded higher quality sequence data than DNA from brushes in closed packaging. Quality metrics of sequenced gDNA were consistently higher than metrics from corresponding WGA products and were consistently high when using a low input protocol.

CONCLUSIONS

This proof-of-principle study established conditions under which ES can be applied to NBDPS specimens. Successful sequencing of exomes from well-characterized NBDPS families indicated that this unique collection can be used to investigate the roles of genetic variation and gene-environment interaction effects in birth defect etiologies, providing a valuable resource for birth defect researchers.

Investigation of Maternal Effects, Maternal-Fetal Interactions, and Parent-of-Origin Effects (Imprinting) for Candidate Genes Positioned on Chromosome 18q21, in Probands with Schizophrenia and their First-Degree Relatives

OBJECTIVE

A popular design for the investigation of such effects, including effects of parent-of-origin (imprinting), maternal genotype, and maternal-fetal genotype interactions, is to collect deoxyribonucleic acid (DNA) from affected offspring and their mothers and to compare with an appropriate control sample. We investigate the effects of estimation of maternal, imprinting and interaction effects using multimodal modeling using parents and their offspring with schizophrenia in Korean population.

METHODS

We have recruited 27 probands (with schizophrenia) with their parents and siblings whenever possible. We analyzed 20 SNPs of 7 neuronal genes in chromosome 18. We used EMIM analysis program for the estimation of maternal, imprinting and interaction effects using multimodal modeling.

RESULTS

Of analyzed 20 single nucleotide polymorphisms (SNPs), significant SNP (rs 2276186) was suggested in EMIM analysis for child genetics effects (p=0.0225438044) and child genetic effects allowing for maternal genetic effects (p=0.0209453210) with very stringent multiple comparison Bonferroni correction.

CONCLUSION

Our results are the pilot study for epigenetic study in mental disorder and help to understanding and use of EMIM statistical genetics analysis program with many limitations including small pedigree numbers.

The association of elevated maternal genetic risk scores for hypertension, type 2 diabetes and obesity and having a child with a congenital heart defect

Background

Maternal hypertension, type 2 diabetes (T2D) and obesity are associated with an increased risk of having offspring with conotruncal heart defects (CTDs). Prior studies have identified sets of single nucleotide polymorphisms (SNPs) that are associated with risk for each of these three adult phenotypes. We hypothesized that these same SNPs are associated with maternal risk of CTDs in offspring.

Methods and results

We evaluated the parents of children with a CTD ascertained from the Children’s Hospital of Philadelphia (n = 466) and by the Pediatric Cardiac Genomic Consortium (n = 255). We used a family-based design to assess the association between CTDs and the maternal genotype for individual hypertension, T2D, and obesity-related SNPs and found no association between CTDs and the maternal genotype for any individual SNP. In addition, we calculated genetic risk scores (GRS) for hypertension, T2D, and obesity using previously published GRS formulas. When comparing the GRS of mothers to fathers, there were no statistically significant differences in the mean for the combined GRS or the GRS for each individual condition. However, when we categorized the mothers and fathers of cases with CTDs as having high (>95^th percentile) or low (≤95^th percentile) scores, compared to fathers, mothers had almost two times the odds of having a high GRS for hypertension (OR 1.7, 95% CI 1.0, 2.8) and T2D (OR 1.8, 95% CI 1.1, 3.1).

Conclusions

Our results support a link between maternal genetic risk for hypertension/T2D and CTDs in their offspring. These associations might be independent of maternal phenotype at conception.

Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls

Background

Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or sample size is an important first step in the planning of any scientific study, there is currently a lack of software for genetic power calculations in family-based study designs. Here, we address this shortcoming through new implementations of power calculations in the R package Haplin, which is a flexible and robust software for genetic epidemiological analyses. Power calculations in Haplin can be performed analytically using the asymptotic variance-covariance structure of the parameter estimator, or else by a straightforward simulation approach. Haplin performs power calculations for child, parent-of-origin and maternal effects, as well as for gene-environment interactions. The power can be calculated for both single SNPs and haplotypes, either autosomal or X-linked. Moreover, Haplin enables power calculations for different child-parent configurations, including (but not limited to) case-parent triads, case-mother dyads, and case-parent triads in combination with unrelated control-parent triads.

Results

We compared the asymptotic power approximations to the power of analysis attained with Haplin. For external validation, the results were further compared to the power of analysis attained by the EMIM software using data simulations from Haplin. Consistency observed between Haplin and EMIM across various genetic scenarios confirms the computational accuracy of the inference methods used in both programs. The results also demonstrate that power calculations in Haplin are applicable to genetic association studies using either log-linear or multinomial modeling approaches.

Conclusions

Haplin provides a robust and reliable framework for power calculations in genetic association analyses for a wide range of genetic effects and etiologic scenarios, based on genotype data from a variety of child-parent configurations.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2727-3) contains supplementary material, which is available to authorized users.

Parent-of-origin effects on quantitative phenotypes in a large Hutterite pedigree

The impact of the parental origin of associated alleles in GWAS has been largely ignored. Yet sequence variants could affect traits differently depending on whether they are inherited from the mother or the father, as in imprinted regions, where identical inherited DNA sequences can have different effects based on the parental origin. To explore parent-of-origin effects (POEs), we studied 21 quantitative phenotypes in a large Hutterite pedigree to identify variants with single parent (maternal-only or paternal-only) effects, and then variants with opposite parental effects. Here we show that POEs, which can be opposite in direction, are relatively common in humans, have potentially important clinical effects, and will be missed in traditional GWAS. We identified POEs with 11 phenotypes, most of which are risk factors for cardiovascular disease. Many of the loci identified are characteristic of imprinted regions and are associated with the expression of nearby genes.

Genome-wide association study of maternal genetic effects and parent-of-origin effects on food allergy

Previous genetic studies of food allergy (FA) have mainly focused on inherited genotypic effects. The role of parental genotypic effects remains largely unexplored. Leveraging existing genome-wide association study (GWAS) data generated from the Chicago Food Allergy Study, we examined maternal genotypic and parent-of-origin (PO) effects using multinomial likelihood ratio tests in 588 complete and incomplete Caucasian FA trios. We identified 1 single nucleotide polymorphism with significant (P < 5×10) maternal effect on any FA (rs4235235), which is located in a noncoding RNA (LOC101927947) with unknown function. We also identified 3 suggestive (P < 5×10) loci with maternal genetic effects: 1 for any FA (rs976078, in a gene desert region on 13q31.1) and 2 for egg allergy (rs1343795 and rs4572450, in the ZNF652 gene, where genetic variants have been associated with atopic dermatitis). Three suggestive loci with PO effect were observed: 1 for peanut allergy (rs4896888 in the ADGB gene) and 2 for any FA in boys only (rs1036504 and rs2917750 in the IQCE gene). Findings from this family-based GWAS of FA provided some preliminary evidence on maternal genotypic or PO effects on FA. Additional family-based studies are needed to confirm our findings and gain new insight into maternal and paternal genetic contribution to FA.

Genome-Wide Association Studies and Meta-Analyses for Congenital Heart Defects

BACKGROUND

Maternal and inherited (ie, case) genetic factors likely contribute to the pathogenesis of congenital heart defects, but it is unclear whether individual common variants confer a large risk.

METHODS AND RESULTS

To evaluate the relationship between individual common maternal/inherited genotypes and risk for heart defects, we conducted genome-wide association studies in 5 cohorts. Three cohorts were recruited at the Children's Hospital of Philadelphia: 670 conotruncal heart defect (CTD) case-parent trios, 317 left ventricular obstructive tract defect (LVOTD) case-parent trios, and 406 CTD cases (n=406) and 2976 pediatric controls. Two cohorts were recruited through the Pediatric Cardiac Genomics Consortium: 355 CTD trios and 192 LVOTD trios. We also conducted meta-analyses using the genome-wide association study results from the CTD cohorts, the LVOTD cohorts, and from the combined CTD and LVOTD cohorts. In the individual genome-wide association studies, several genome-wide significant associations (P≤5×10^-8) were observed. In our meta-analyses, 1 genome-wide significant association was detected: the case genotype for rs72820264, an intragenetic single-nucleotide polymorphism associated with LVOTDs (P=2.1×10^-8).

CONCLUSIONS

We identified 1 novel candidate region associated with LVOTDs and report on several additional regions with suggestive evidence for association with CTD and LVOTD. These studies were constrained by the relatively small samples sizes and thus have limited power to detect small to moderate associations. Approaches that minimize the multiple testing burden (eg, gene or pathway based) may, therefore, be required to uncover common variants contributing to the risk of these relatively rare conditions.

Family-based exome-wide association study of childhood acute lymphoblastic leukemia among Hispanics confirms role of ARID5B in susceptibility

We conducted an exome-wide association study of childhood acute lymphoblastic leukemia (ALL) among Hispanics to confirm and identify novel variants associated with disease risk in this population. We used a case-parent trio study design; unlike more commonly used case-control studies, this study design is ideal for avoiding issues with population stratification bias among this at-risk ethnic group. Using 710 individuals from 323 Guatemalan and US Hispanic families, two inherited SNPs in ARID5B reached genome-wide level significance: rs10821936, RR = 2.31, 95% CI = 1.70–3.14, p = 1.7×10⁻⁸ and rs7089424, RR = 2.22, 95% CI = 1.64–3.01, p = 5.2×10⁻⁸. Similar results were observed when restricting our analyses to those with the B-ALL subtype: ARID5B rs10821936 RR = 2.22, 95% CI = 1.63–3.02, p = 9.63×10⁻⁸ and ARID5B rs7089424 RR = 2.13, 95% CI = 1.57–2.88, p = 2.81×10⁻⁷. Notably, effect sizes observed for rs7089424 and rs10821936 in our study were >20% higher than those reported among non-Hispanic white populations in previous genetic association studies. Our results confirmed the role of ARID5B in childhood ALL susceptibility among Hispanics; however, our assessment did not reveal any strong novel inherited genetic risks for acute lymphoblastic leukemia among this ethnic group.

The Gene Variants of Maternal/Fetal Renin-Angiotensin System in Preeclampsia: A Hybrid Case-Parent/Mother-Control Study

Preeclampsia (PE) is a common pregnancy-related complication, and polymorphisms in angiotensinogen (AGT), angiotensin-converting enzyme (ACE), and angiotensin II type 1 receptor (AT1R) are believed to contribute to PE development. We implemented a hybrid study to investigate the influence of maternal and fetal ACE I/D, ACE G2350A, AGT M235T, AGT T174M, and AT1R A1166C polymorphisms on PE in Han Chinese women. Polymorphisms were genotyped in 1,488 subjects (256 patients experiencing PE, along with their fetuses and partners, and 360 normotensive controls with their fetuses). Transmission disequilibrium tests revealed that ACE I/D (P = 0.041), ACE G2350A (P = 0.035), and AT1R A1166C (P = 0.018) were associated with maternal PE. The log-linear analyses revealed that mothers whose offspring carried the MM genotype of AGT M235T had a higher risk of PE (OR = 1.54, P = 0.010), whereas mothers whose offspring carried the II genotype of ACE I/D or the GG genotype of ACE G2350A had a reduced risk (OR = 0.58, P = 0.039; OR = 0.47, P = 0.045, respectively). Our findings demonstrate that fetal ACE I/D, ACE G2350A, AGT M235T, and AT1R A1166C polymorphisms may play significant roles in PE development among pregnant Han Chinese women.

Analysis of case-parent trios for imprinting effect using a loglinear model with adjustment for sex-of-parent-specific transmission ratio distortion

Transmission ratio distortion (TRD) is a phenomenon where parental transmission of disease allele to the child does not follow the Mendelian inheritance ratio. TRD occurs in a sex-of-parent-specific or non-sex-of-parent-specific manner. An offset computed from the transmission probability of the minor allele in control-trios can be added to the loglinear model to adjust for TRD. Adjusting the model removes the inflation in the genotype relative risk (RR) estimate and Type 1 error introduced by non-sex-of-parent-specific TRD. We now propose to further extend this model to estimate an imprinting parameter. Some evidence suggests that more than 1% of all mammalian genes are imprinted. In the presence of imprinting, for example, the offspring inheriting an over-transmitted disease allele from the parent with a higher expression level in a neighboring gene is over-represented in the sample. TRD mechanisms such as meiotic drive and gametic competition occur in a sex-of-parent-specific manner. Therefore, sex-of-parent-specific TRD (ST) leads to over-representation of maternal or paternal alleles in the affected child. As a result, ST may bias the imprinting effect when present in the sample. We propose a sex-of-parent-specific transmission offset in adjusting the loglinear model to account for ST. This extended model restores the correct RR estimates for child and imprinting effects, adjusts for inflation in Type 1 error, and improves performance on sensitivity and specificity compared to the original model without ST offset. We conclude that to correctly interpret the association signal of an imprinting effect, adjustment for ST is necessary to ensure valid conclusions.

Variants in the fetal genome near FLT1 are associated with risk of preeclampsia

Preeclampsia, which affects approximately 5% of pregnancies, is a leading cause of maternal and perinatal death. The causes of preeclampsia remain unclear, but there is evidence for inherited susceptibility. Genome-wide association studies (GWAS) have not identified maternal sequence variants of genome-wide significance that replicate in independent data sets. We report the first GWAS of offspring from preeclamptic pregnancies and discovery of the first genome-wide significant susceptibility locus (rs4769613; P = 5.4 × 10^-11) in 4,380 cases and 310,238 controls. This locus is near the FLT1 gene encoding Fms-like tyrosine kinase 1, providing biological support, as a placental isoform of this protein (sFlt-1) is implicated in the pathology of preeclampsia. The association was strongest in offspring from pregnancies in which preeclampsia developed during late gestation and offspring birth weights exceeded the tenth centile. An additional nearby variant, rs12050029, associated with preeclampsia independently of rs4769613. The newly discovered locus may enhance understanding of the pathophysiology of preeclampsia and its subtypes.

Human Birth Weight and Reproductive Immunology: Testing for Interactions between Maternal and Offspring KIR and HLA-C Genes

BACKGROUND/AIMS

Maternal and offspring cell contact at the site of placentation presents a plausible setting for maternal-fetal genotype (MFG) interactions affecting fetal growth. We test hypotheses regarding killer cell immunoglobulin-like receptor (KIR) and HLA-C MFG effects on human birth weight by extending the quantitative MFG (QMFG) test.

METHODS

Until recently, association testing for MFG interactions had limited applications. To improve the ability to test for these interactions, we developed the extended QMFG test, a linear mixed-effect model that can use multi-locus genotype data from families.

RESULTS

We demonstrate the extended QMFG test's statistical properties. We also show that if an offspring-only model is fit when MFG effects exist, associations can be missed or misattributed. Furthermore, imprecisely modeling the effects of both KIR and HLA-C could result in a failure to replicate if these loci's allele frequencies differ among populations. To further illustrate the extended QMFG test's advantages, we apply the extended QMFG test to a UK cohort study and the Norwegian Mother and Child Cohort (MoBa) study.

CONCLUSION

We find a significant KIR-HLA-C interaction effect on birth weight. More generally, the QMFG test can detect genetic associations that may be missed by standard genome-wide association studies for quantitative traits.

A genome-wide investigation into parent-of-origin effects in autism spectrum disorder identifies previously associated genes including SHANK3

Autism spectrum disorder (ASD) is known to be a heritable neurodevelopmental disorder affecting more than 1% of the population but in the majority of ASD cases, the genetic cause has not been identified. Parent-of-origin effects have been highlighted as an important mechanism in the pathology of neurodevelopmental disorders such as Prader-Willi and Angelman syndrome, with individuals with these syndromes often exhibiting ASD symptoms. Consequently, systematic investigation of these effects in ASD is clearly an important line of investigation in elucidating the underlying genetic mechanisms. Using estimation of maternal, imprinting and interaction effects using multinomial modelling (EMIM), we simultaneously investigated imprinting, maternal genetic effects and associations in the Autism Genome Project and Simons Simplex Consortium genome-wide association data sets. To avoid using the overly stringent genome-wide association study significance level, we used a Bayesian threshold that takes into account the sample size, allele frequency and any available prior knowledge. Between the two data sets, we identified a total of 18 imprinting effects and 68 maternal genetic effects that met this Bayesian threshold criteria, but none met the threshold in both data sets. We identified imprinting and maternal genetic effects for regions that have previously shown evidence for parent-of-origin effects in ASD. Together with these findings, we have identified maternal genetic effects not previously identified in ASD at a locus in SHANK3 on chromosome 22 and a locus in WBSCR17 on chromosome 7 (associated with Williams syndrome). Both genes have previously been associated with ASD.

Family-based exome-wide assessment of maternal genetic effects on susceptibility to childhood B-cell acute lymphoblastic leukemia in hispanics

BACKGROUND

Children of Hispanic ancestry have a higher incidence of acute lymphoblastic leukemia (ALL) compared with other ethnic groups, but to the authors' knowledge, the genetic basis for these racial disparities remain incompletely understood. Genome-wide association studies of childhood ALL to date have focused on inherited genetic effects; however, maternal genetic effects (the role of the maternal genotype on phenotype development in the offspring) also may play a role in ALL susceptibility.

METHODS

The authors conducted a family-based exome-wide association study of maternal genetic effects among Hispanics with childhood B-cell ALL using the Illumina Infinium HumanExome BeadChip. A discovery cohort of 312 Guatemalan and Hispanic American families and an independent replication cohort of 152 Hispanic American families were used.

RESULTS

Three maternal single-nucleotide polymorphisms (SNPs) approached the study threshold for significance after correction for multiple testing (P<1.0 × 10^-6 ): MTL5 rs12365708 (testis expressed metallothionein-like protein [tesmin]) (relative risk [RR], 2.62; 95% confidence interval [95% CI], 1.61-4.27 [P = 1.8 × 10^-5 ]); ALKBH1 rs6494 (AlkB homolog 1, histone H2A dioxygenase) (RR, 3.77; 95% CI, 1.84-7.74 [P = 3.7 × 10^-5 ]); and NEUROG3 rs4536103 (neurogenin 3) (RR, 1.75; 95% CI, 1.30-2.37 [P = 1.2 × 10^-4 ]). Although effect sizes were similar, these SNPs were not nominally significant in the replication cohort in the current study. In a meta-analysis comprised of the discovery cohort and the replication cohort, these SNPs were still not found to be statistically significant after correction for multiple comparisons (rs12365708: pooled RR, 2.27 [95% CI, 1.48-3.50], P = 1.99 × 10^-4 ; rs6494: pooled RR, 2.31 [95% CI, 1.38-3.85], P = .001; and rs4536103: pooled RR, 1.67 [95% CI, 1.29-2.16] P = 9.23 × 10^-5 ).

CONCLUSIONS

In what to the authors' knowledge is the first family-based based exome-wide association study to investigate maternal genotype effects associated with childhood ALL, the results did not implicate a strong role of maternal genotype on disease risk among Hispanics; however, 3 maternal SNPs were identified that may play a modest role in susceptibility. Cancer 2016;122:3697-704. © 2016 American Cancer Society.

Interaction between MTHFR 677C>T and periconceptional folic acid supplementation in the risk of Hypospadias

BACKGROUND

Hypospadias is a congenital malformation with both environmental factors and genetic predisposition involved in the pathogenesis. The role of maternal periconceptional folic acid supplement use in the development of hypospadias is unclear. As folate levels may also be influenced by the C677T polymorphism in the methylenetetrahydrofolate reductase (MTHFR) gene, we hypothesize that a gene-environment interaction between this polymorphism and folic acid use is involved in the etiology of hypospadias.

METHODS

We conducted a case-control study among 855 hypospadias cases and 713 population-based controls from the AGORA data- and biobank. Folic acid supplement use was derived from maternal questionnaires and infant and maternal DNA was used to determine the MTHFR C677T polymorphism using Taqman assays. We performed separate analyses for different hypospadias phenotypes (anterior/middle/posterior).

RESULTS

Hypospadias was neither associated with folic acid use or the MTHFR C677T polymorphism, nor with their interaction. However, we did find an association with middle hypospadias when no supplements were used (odds ratio = 1.6; 95% confidence interval, 1.1-2.4), especially in infants carrying the CT/TT genotype (odds ratio = 2.5; 95% confidence interval, 1.4-4.7). In addition, more infants with these genotypes seemed to have posterior hypospadias, regardless of folic acid use.

CONCLUSION

Our study does not suggest a major role for folic acid supplements or the MTHFR C677T polymorphism in the etiology of hypospadias in general, but not using folic acid and/or carrying the MTHFR C677T polymorphism may be associated with middle and posterior hypospadias. Therefore, we stress the importance of studying gene-environment interactions preferably in stratified analyses for different hypospadias phenotypes.

Expanding the toolbox of ADHD genetics. How can we make sense of parent of origin effects in ADHD and related behavioral phenotypes?

Genome-wide association (GWA) studies have shown that many different genetic variants cumulatively contribute to the risk of psychiatric disorders. It has also been demonstrated that various parent-of-origin effects (POE) may differentially influence the risk of these disorders. Together, these observations have provided important new possibilities to uncover the genetic underpinnings of such complex phenotypes. As POE so far have received little attention in neuropsychiatric disorders, there is still much progress to be made. Here, we mainly focus on the new and emerging role of POE in attention-deficit hyperactivity disorder (ADHD). We review the current evidence that POE play an imperative role in vulnerability to ADHD and related disorders. We also discuss how POE can be assessed using statistical genetics tools, expanding the resources of modern psychiatric genetics. We propose that better comprehension and inspection of POE may offer new insight into the molecular basis of ADHD and related phenotypes, as well as the potential for preventive and therapeutic interventions.

Increased Power for Detection of Parent-of-Origin Effects via the Use of Haplotype Estimation

Parent-of-origin (or imprinting) effects relate to the situation in which traits are influenced by the allele inherited from only one parent and the allele from the other parent has little or no effect. Given SNP genotype data from case-parent trios, the parent of origin of each allele in the offspring can often be deduced unambiguously; however, this is not true when all three individuals are heterozygous. Most existing methods for investigating parent-of-origin effects operate on a SNP-by-SNP basis and either perform some sort of averaging over the possible parental transmissions or else discard ambiguous trios. If the correct parent of origin at a SNP could be determined, this would provide extra information and increase the power for detecting the effects of imprinting. We propose making use of the surrounding SNP information, via haplotype estimation, to improve estimation of parent of origin at a test SNP for case-parent trios, case-mother duos, and case-father duos. This extra information is then used in a multinomial modeling approach for estimating parent-of-origin effects at the test SNP. We show through computer simulations that our approach has increased power over previous approaches, particularly when the data consist only of duos. We apply our method to two real datasets and find a decrease in significance of p values in genomic regions previously thought to possibly harbor imprinting effects, thus weakening the evidence that such effects actually exist in these regions, although some regions retain evidence of significant effects.

Detecting gene-environment interactions in human birth defects: Study designs and statistical methods

BACKGROUND

The National Birth Defects Prevention Study (NBDPS) contains a wealth of information on affected and unaffected family triads, and thus provides numerous opportunities to study gene-environment interactions (G×E) in the etiology of birth defect outcomes. Depending on the research objective, several analytic options exist to estimate G×E effects that use varying combinations of individuals drawn from available triads.

METHODS

In this study, we discuss important considerations in the collection of genetic data and environmental exposures.

RESULTS

We will also present several population- and family-based approaches that can be applied to data from the NBDPS including case-control, case-only, family-based trio, and maternal versus fetal effects. For each, we describe the data requirements, applicable statistical methods, advantages, and disadvantages.

CONCLUSION

A range of approaches can be used to evaluate potentially important G×E effects in the NBDPS. Investigators should be aware of the limitations inherent to each approach when choosing a study design and interpreting results.

Maternal filaggrin mutations increase the risk of atopic dermatitis in children: an effect independent of mutation inheritance

Epidemiological studies suggest that allergy risk is preferentially transmitted through mothers. This can be due to genomic imprinting, where the phenotype effect of an allele depends on its parental origin, or due to maternal effects reflecting the maternal genome's influence on the child during prenatal development. Loss-of-function mutations in the filaggrin gene (FLG) cause skin barrier deficiency and strongly predispose to atopic dermatitis (AD). We investigated the 4 most prevalent European FLG mutations (c.2282del4, p.R501X, p.R2447X, and p.S3247X) in two samples including 759 and 450 AD families. We used the multinomial and maximum-likelihood approach implemented in the PREMIM/EMIM tool to model parent-of-origin effects. Beyond the known role of FLG inheritance in AD (R1_{meta-analysis} = 2.4, P = 1.0 x 10⁻³⁶), we observed a strong maternal FLG genotype effect that was consistent in both independent family sets and for all 4 mutations analysed. Overall, children of FLG-carrier mothers had a 1.5-fold increased AD risk (S1 = 1.50, P_{meta-analysis} = 8.4 x 10⁻⁸). Our data point to two independent and additive effects of FLG mutations: i) carrying a mutation and ii) having a mutation carrier mother. The maternal genotype effect was independent of mutation inheritance and can be seen as a non-genetic transmission of a genetic effect. The FLG maternal effect was observed only when mothers had allergic sensitization (elevated allergen-specific IgE antibody plasma levels), suggesting that FLG mutation-induced systemic immune responses in the mother may influence AD risk in the child. Notably, the maternal effect reported here was stronger than most common genetic risk factors for AD recently identified through genome-wide association studies (GWAS). Our study highlights the power of family-based studies in the identification of new etiological mechanisms and reveals, for the first time, a direct influence of the maternal genotype on the offspring’s susceptibility to a common human disease.

Most human diseases are caused by a combination of multiple environmental and genetic influences. The widely used case/control approach aims to identify disease risk genes by comparing the genetic constitution of affected and healthy individuals. Although successful, this approach ignores additional mechanisms influencing disease risk. Here, we studied mutations in the filaggrin gene (FLG), which are strong risk factors for atopic dermatitis (AD) and allergies, in a large number of families with AD. We found that FLG mutations in the mother, not the father, increased the AD risk of the children, even if the child did not inherit the mutation. Thus, our study revealed, for the first time, a direct influence of a maternal mutation on the child’s risk for a common disease. The maternal FLG effect was only found when the mothers were allergic, and was absent in families of non-allergic mothers. This finding suggests that FLG-induced changes in the maternal immune response shape the child’s immune system during pregnancy and increase the child’s risk for AD. Our study indicates that maternal FLG mutations act as strong environmental risk factors for the child and highlights the potential of family-based studies in uncovering novel disease mechanisms in medical genetics.

Placental genome and maternal-placental genetic interactions: a genome-wide and candidate gene association study of placental abruption

While available evidence supports the role of genetics in the pathogenesis of placental abruption (PA), PA-related placental genome variations and maternal-placental genetic interactions have not been investigated. Maternal blood and placental samples collected from participants in the Peruvian Abruptio Placentae Epidemiology study were genotyped using Illumina's Cardio-Metabochip platform. We examined 118,782 genome-wide SNPs and 333 SNPs in 32 candidate genes from mitochondrial biogenesis and oxidative phosphorylation pathways in placental DNA from 280 PA cases and 244 controls. We assessed maternal-placental interactions in the candidate gene SNPS and two imprinted regions (IGF2/H19 and C19MC). Univariate and penalized logistic regression models were fit to estimate odds ratios. We examined the combined effect of multiple SNPs on PA risk using weighted genetic risk scores (WGRS) with repeated ten-fold cross-validations. A multinomial model was used to investigate maternal-placental genetic interactions. In placental genome-wide and candidate gene analyses, no SNP was significant after false discovery rate correction. The top genome-wide association study (GWAS) hits were rs544201, rs1484464 (CTNNA2), rs4149570 (TNFRSF1A) and rs13055470 (ZNRF3) (p-values: 1.11e-05 to 3.54e-05). The top 200 SNPs of the GWAS overrepresented genes involved in cell cycle, growth and proliferation. The top candidate gene hits were rs16949118 (COX10) and rs7609948 (THRB) (p-values: 6.00e-03 and 8.19e-03). Participants in the highest quartile of WGRS based on cross-validations using SNPs selected from the GWAS and candidate gene analyses had a 8.40-fold (95% CI: 5.8-12.56) and a 4.46-fold (95% CI: 2.94-6.72) higher odds of PA compared to participants in the lowest quartile. We found maternal-placental genetic interactions on PA risk for two SNPs in PPARG (chr3:12313450 and chr3:12412978) and maternal imprinting effects for multiple SNPs in the C19MC and IGF2/H19 regions. Variations in the placental genome and interactions between maternal-placental genetic variations may contribute to PA risk. Larger studies may help advance our understanding of PA pathogenesis.

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.

Genome-Wide Studies of Specific Language Impairment

Specific language impairment (SLI) is a multifactorial neurodevelopmental disorder which occurs unexpectedly and without an obvious cause. Over a decade of research suggests that SLI is highly heritable. Several genes and loci have already been implicated in SLI through linkage and targeted association methods. Recently, genome-wide association studies (GWAS) of SLI and language traits in the general population have been reported and, consequently, new candidate genes have been identified. This review aims to summarise the literature concerning genome-wide studies of SLI. In addition, this review highlights the methodologies that have been used to research the genetics of SLI to date, and also considers the current, and future, contributions that GWAS can offer.

Nonparametric method for detecting imprinting effect using all members of general pedigrees with missing data

Imprinting effects can lead to parent-of-origin patterns in complex human diseases. For a diallelic marker locus, Pedigree Parental-Asymmetry Test (PPAT) and its extension MCPPAT using pedigrees allowing for missing genotypes are simple and powerful for detecting imprinting effects. However, these approaches only take affected offspring into consideration, thus not making full use of the data available. In this paper, we propose Monte Carlo Pedigree Parental-Asymmetry Test using both affected and unaffected (MCPPATu) offsprings, which allows for missing genotypes through Monte Carlo sampling. Simulation studies demonstrate that MCPPATu controls the empirical type I error rate well under the null hypotheses of no parent-of-origin effects. It is also demonstrated that the use of additional information from unaffected offspring and partially observed genotypes in the analysis can greatly improve the statistical power. Indeed, for common diseases, MCPPATu is much more powerful than MCPPAT when all genotypes are observed and the power improvement is even greater when there is missing data. For rarer diseases, there are still substantial power gains with the inclusion of unaffected offspring, although the gains are less impressive compared with those for more common diseases.

Entropy-based selection for maternal-fetal genotype incompatibility with application to preterm prelabor rupture of membranes

Background

Maternal-fetal genotype incompatibility (MFGI) is increasingly reported to influence human diseases, especially pregnancy-related complications. In practice, it is challenging to identify the ideal incompatibility model for analysis, since the true MFGI mechanism is generally unknown. The underlying MFGI mechanism for different genetic variants can vary, and to use a single incompatibility model for all circumstances would cause power loss in testing MFGI.

Results

In this article, we propose a practical 2-step procedure that incorporates a model selection strategy based on an entropy measurement to select the most appropriate MFGI model represented by data and test the significance of the MFGI effect using the chosen model within the generalized linear regression framework.

Conclusions

Our simulation studies show that the proposed two-step procedure controls the type I error rate and increase the testing power under various scenarios. In a real data application, our analysis reveals genes having an MFGI effect, which may not be detected with a non-model selection counterpart.

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.

No major role for periconceptional folic acid use and its interaction with the MTHFR C677T polymorphism in the etiology of congenital anorectal malformations

BACKGROUND

Both genetic and nongenetic factors are suggested to be involved in the etiology of congenital anorectal malformations (ARM). Maternal periconceptional use of folic acid supplements were inconsistently suggested to play a role in the prevention of ARM. Therefore, we investigated independent associations and interactions of maternal periconceptional folic acid supplement use and the infant and maternal MTHFR (methylenetetrahydrofolate reductase) C677T polymorphisms with the risk of ARM and subgroups of ARM.

METHODS

A case-control study was conducted among 371 nonsyndromic ARM cases and 714 population-based controls born between 1990 and 2012 using maternal questionnaires and DNA samples from mother and child. Cases were treated for ARM at departments of Pediatric Surgery of the Radboud university medical center, Sophia Children's Hospital-Erasmus MC Rotterdam, and the University Medical Center Groningen in The Netherlands and hospitals throughout Germany.

RESULTS

No association with folic acid use was present (odds ratio = 1.1; 95% confidence interval: 0.8-1.4) for ARM as a group. Infant and maternal MTHFR C677T polymorphisms were weakly associated with isolated ARM in particular. Lack of folic acid supplement use in combination with infants or mothers carrying the MTHFR C677T polymorphism did not seem to increase the risk of ARM or subgroups of ARM. The relative excess risks due to interaction did not clearly indicate interaction on an additive scale either.

CONCLUSION

This first study investigating interactions between periconceptional folic acid supplement use and infant and maternal MTHFR C677T polymorphisms in the etiology of ARM did not provide evidence for a role of this gene-environment interaction.

Investigation of maternal genotype effects in autism by genome-wide association

Like most psychiatric disorders, autism spectrum disorders have both a genetic and an environmental component. While previous studies have clearly demonstrated the contribution of in utero (prenatal) environment on autism risk, most of them focused on transient environmental factors. Based on a recent sibling study, we hypothesized that environmental factors could also come from the maternal genome, which would result in persistent effects across siblings. In this study, the possibility of maternal genotype effects was examined by looking for common variants (single-nucleotide polymorphisms or SNPs) in the maternal genome associated with increased risk of autism in children. A case/control genome-wide association study was performed using mothers of probands as cases, and either fathers of probands or normal females as controls. Autism Genetic Resource Exchange and Illumina Genotype Control Database were used as our discovery cohort (n = 1616). The same analysis was then replicated on Simon Simplex Collection and Study of Addiction: Genetics and Environment datasets (n = 2732). We did not identify any SNP that reached genome-wide significance (P < 10(-8) ), and thus a common variant of large effect is unlikely. However, there was evidence for the possibility of a large number of alleles of effective size marginally below our power to detect.

Genome-wide association analyses of child genotype effects and parent-of-origin effects in specific language impairment

Specific language impairment (SLI) is a neurodevelopmental disorder that affects linguistic abilities when development is otherwise normal. We report the results of a genome-wide association study of SLI which included parent-of-origin effects and child genotype effects and used 278 families of language-impaired children. The child genotype effects analysis did not identify significant associations. We found genome-wide significant paternal parent-of-origin effects on chromosome 14q12 (P = 3.74 × 10⁻⁸) and suggestive maternal parent-of-origin effects on chromosome 5p13 (P = 1.16 × 10⁻⁷). A subsequent targeted association of six single-nucleotide-polymorphisms (SNPs) on chromosome 5 in 313 language-impaired individuals and their mothers from the ALSPAC cohort replicated the maternal effects, albeit in the opposite direction (P = 0.001); as fathers’ genotypes were not available in the ALSPAC study, the replication analysis did not include paternal parent-of-origin effects. The paternally-associated SNP on chromosome 14 yields a non-synonymous coding change within the NOP9 gene. This gene encodes an RNA-binding protein that has been reported to be significantly dysregulated in individuals with schizophrenia. The region of maternal association on chromosome 5 falls between the PTGER4 and DAB2 genes, in a region previously implicated in autism and ADHD. The top SNP in this association locus is a potential expression QTL of ARHGEF19 (also called WGEF) on chromosome 1. Members of this protein family have been implicated in intellectual disability. In summary, this study implicates parent-of-origin effects in language impairment, and adds an interesting new dimension to the emerging picture of shared genetic etiology across various neurodevelopmental disorders.

Detecting maternal-fetal genotype interactions associated with conotruncal heart defects: a haplotype-based analysis with penalized logistic regression

Nonsyndromic congenital heart defects (CHDs) develop during embryogenesis as a result of a complex interplay between environmental exposures, genetics, and epigenetic causes. Genetic factors associated with CHDs may be attributed to either independent effects of maternal or fetal genes, or the intergenerational interactions between maternal and fetal genes. Detecting gene-by-gene interactions underlying complex diseases is a major challenge in genetic research. Detecting maternal-fetal genotype (MFG) interactions and differentiating them from the maternal/fetal main effects has presented additional statistical challenges due to correlations between maternal and fetal genomes. Traditionally, genetic variants are tested separately for maternal/fetal main effects and MFG interactions on a single-locus basis. We conducted a haplotype-based analysis with a penalized logistic regression framework to dissect the genetic effect associated with the development of nonsyndromic conotruncal heart defects (CTD). Our method allows simultaneous model selection and effect estimation, providing a unified framework to differentiate maternal/fetal main effect from the MFG interaction effect. In addition, the method is able to test multiple highly linked SNPs simultaneously with a configuration of haplotypes, which reduces the data dimensionality and the burden of multiple testing. By analyzing a dataset from the National Birth Defects Prevention Study (NBDPS), we identified seven genes (GSTA1, SOD2, MTRR, AHCYL2, GCLC, GSTM3, and RFC1) associated with the development of CTDs. Our findings suggest that MFG interactions between haplotypes in three of seven genes, GCLC, GSTM3, and RFC1, are associated with nonsyndromic conotruncal heart defects.

A genome-wide survey of transgenerational genetic effects in autism

Effects of parental genotype or parent-offspring genetic interaction are well established in model organisms for a variety of traits. However, these transgenerational genetic models are rarely studied in humans. We have utilized an autism case-control study with 735 mother-child pairs to perform genome-wide screening for maternal genetic effects and maternal-offspring genetic interaction. We used simple models of single locus parent-child interaction and identified suggestive results (P<10⁻⁴) that cannot be explained by main effects, but no genome-wide significant signals. Some of these maternal and maternal-child associations were in or adjacent to autism candidate genes including: PCDH9, FOXP1, GABRB3, NRXN1, RELN, MACROD2, FHIT, RORA, CNTN4, CNTNAP2, FAM135B, LAMA1, NFIA, NLGN4X, RAPGEF4, and SDK1. We attempted validation of potential autism association under maternal-specific models using maternal-paternal comparison in family-based GWAS datasets. Our results suggest that further study of parental genetic effects and parent-child interaction in autism is warranted.

A unified framework integrating parent-of-origin effects for association study

Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting is related to several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we generalize the natural and orthogonal interactions (NOIA) framework to allow for estimation of both main allelic effects and POEs. We develop a statistical (Stat-POE) model that has the orthogonal estimates of parameters including the POEs. We conducted simulation studies for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Efficient simulation of epistatic interactions in case-parent trios

Statistical approaches to evaluate interactions between single nucleotide polymorphisms (SNPs) and SNP-environment interactions are of great importance in genetic association studies, as susceptibility to complex disease might be related to the interaction of multiple SNPs and/or environmental factors. With these methods under active development, algorithms to simulate genomic data sets are needed to ensure proper type I error control of newly proposed methods and to compare power with existing methods. In this paper we propose an efficient method for a haplotype-based simulation of case-parent trios when the disease risk is thought to depend on possibly higher-order epistatic interactions or gene-environment interactions with binary exposures.