PREMIM and EMIM: tools for estimation of maternal, imprinting and interaction effects using multinomial modelling

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.

Genetic variation near GRB10 associated with bone growth and osteosarcoma risk in canine and human populations

BACKGROUND

Canine and human osteosarcoma are similar in clinical presentation and tumor genomics. Giant breed dogs experience elevated osteosarcoma incidence, and taller stature remains a consistent risk factor for human osteosarcoma. Whether evolutionarily conserved genes contribute to both human and canine osteosarcoma predisposition merits evaluation.

METHODS

A multi-center sample of childhood osteosarcoma patients and controls underwent genome-wide genotyping and imputation. Ancestry-adjusted SNP associations were calculated within each dataset using logistic regression, then meta-analyzed across the three datasets, totaling 1091 patients and 3026 controls. Ten regions previously associated with canine osteosarcoma risk were mapped to the human genome, spanning ∼6 Mb. We prioritized association testing of 5985 human SNPs mapping to candidate osteosarcoma risk regions detected in Irish wolfhounds, the largest dog breed studied. Secondary analyses explored 6289 additional human SNPs mapping to candidate osteosarcoma risk regions identified in Rottweilers and greyhounds.

RESULTS

Fourteen SNPs were associated with human osteosarcoma risk after adjustment for multiple comparisons, all within a 42 kb region of human Chromosome 7p12.1. The lead variant was rs17454681 (OR=1.25, 95 %CI: 1.12-1.39; P=4.1×10-5), and independent risk variants were not observed in conditional analyses. While the associated region spanned 2.1 Mb and contained eight genes in Irish wolfhounds, associations were localized to a 50-fold smaller region of the human genome and strongly implicate GRB10 (growth factor receptor-bound protein 10) in canine and human osteosarcoma predisposition. PheWAS analysis in UK Biobank data identified noteworthy associations of the rs17454681 risk allele with varied measures of height and pubertal timing.

CONCLUSIONS

Our comparative oncology analysis identified a novel human osteosarcoma risk allele near GRB10, a growth inhibitor that suppresses activated receptor tyrosine kinases including IGF1R, PDGFRB, and EGFR. Epidemiologists may benefit from leveraging cross-species comparisons to identify haplotypes in highly susceptible but genetically homogenous populations of domesticated animals, then fine-mapping these associations in diverse human populations.

A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects

The risk of congenital heart defects (CHDs) may be influenced by maternal genes, fetal genes, and their interactions. Existing methods commonly test the effects of maternal and fetal variants one-at-a-time and may have reduced statistical power to detect genetic variants with low minor allele frequencies. In this article, we propose a gene-based association test of interactions for maternal-fetal genotypes (GATI-MFG) using a case-mother and control-mother design. GATI-MFG can integrate the effects of multiple variants within a gene or genomic region and evaluate the joint effect of maternal and fetal genotypes while allowing for their interactions. In simulation studies, GATI-MFG had improved statistical power over alternative methods, such as the single-variant test and functional data analysis (FDA) under various disease scenarios. We further applied GATI-MFG to a two-phase genome-wide association study of CHDs for the testing of both common variants and rare variants using 947 CHD case mother-infant pairs and 1306 control mother-infant pairs from the National Birth Defects Prevention Study (NBDPS). After Bonferroni adjustment for 23,035 genes, two genes on chromosome 17, TMEM107 (p = 1.64e-06) and CTC1 (p = 2.0e-06), were identified for significant association with CHD in common variants analysis. Gene TMEM107 regulates ciliogenesis and ciliary protein composition and was found to be associated with heterotaxy. Gene CTC1 plays an essential role in protecting telomeres from degradation, which was suggested to be associated with cardiogenesis. Overall, GATI-MFG outperformed the single-variant test and FDA in the simulations, and the results of application to NBDPS samples are consistent with existing literature supporting the association of TMEM107 and CTC1 with CHDs.

Methods and Software to Analyze Gene-Environment Interactions under a Case-Mother-Control-Mother Design with Partially Missing Child Genotype

INTRODUCTION

The case-mother-control-mother design allows to study fetal and maternal genetic factors together with environmental exposures on early life outcomes. Mendelian constraints and conditional independence between child genotype and environmental factors enabled semiparametric likelihood methods to estimate logistic models with greater efficiency than standard logistic regression. Difficulties in child genotype collection require methods handling missing child genotype.

METHODS

We review a stratified retrospective likelihood and two semiparametric likelihood approaches: a prospective one and a modified retrospective one, the latter either modeling the maternal genotype as a function of covariates or leaving their joint distribution unspecified (robust version). We also review software implementing these modeling alternatives, compare their statistical properties in a simulation study, and illustrate their application, focusing on gene-environment interactions and partially missing child genotype.

RESULTS

The robust retrospective likelihood provides generally unbiased estimates, with standard errors only slightly larger than when modeling maternal genotype based on exposure. The prospective likelihood encounters maximization problems. In the application to the association of small-for-gestational-age babies with CYP2E1 and drinking water disinfection by-products, the retrospective likelihood allowed a full array of covariates, while the prospective likelihood was limited to few covariates.

CONCLUSION

We recommend the robust version of the modified retrospective likelihood.

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.

Congenital Zika Syndrome Is Associated With Interferon Alfa Receptor 1

Host factors that influence Congenital Zika Syndrome (CZS) outcome remain elusive. Interferons have been reported as the main antiviral factor in Zika and other flavivirus infections. Here, we accessed samples from 153 pregnant women (77 without and 76 with CZS) and 143 newborns (77 without and 66 with CZS) exposed to ZIKV conducted a case-control study to verify whether interferon alfa receptor 1 (IFNAR1) and interferon lambda 2 and 4 (IFNL2/4) single nucleotide polymorphisms (SNPs) contribute to CZS outcome, and characterized placenta gene expression profile at term. Newborns carrying CG/CC genotypes of rs2257167 in IFNAR1 presented higher risk of developing CZS (OR=3.41; IC=1.35-8.60; Pcorrected=0.032). No association between IFNL SNPs and CZS was observed. Placenta from CZS cases displayed lower levels of IFNL2 and ISG15 along with higher IFIT5. The rs2257167 CG/CC placentas also demonstrated high levels of IFIT5 and inflammation-related genes. We found CZS to be related with exacerbated type I IFN and insufficient type III IFN in placenta at term, forming an unbalanced response modulated by the IFNAR1 rs2257167 genotype. Despite of the low sample size se findings shed light on the host-pathogen interaction focusing on the genetically regulated type I/type III IFN axis that could lead to better management of Zika and other TORCH (Toxoplasma, Others, Rubella, Cytomegalovirus, Herpes) congenital infections.

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.

Paternal genetic variants and risk of obstructive heart defects: A parent-of-origin approach

Previous research on risk factors for obstructive heart defects (OHDs) focused on maternal and infant genetic variants, prenatal environmental exposures, and their potential interaction effects. Less is known about the role of paternal genetic variants or environmental exposures and risk of OHDs. We examined parent-of-origin effects in transmission of alleles in the folate, homocysteine, or transsulfuration pathway genes on OHD occurrence in offspring. We used data on 569 families of liveborn infants with OHDs born between October 1997 and August 2008 from the National Birth Defects Prevention Study to conduct a family-based case-only study. Maternal, paternal, and infant DNA were genotyped using an Illumina Golden Gate custom single nucleotide polymorphism (SNP) panel. Relative risks (RR), 95% confidence interval (CI), and likelihood ratio tests from log-linear models were used to estimate the parent-of-origin effect of 877 SNPs in 60 candidate genes in the folate, homocysteine, and transsulfuration pathways on the risk of OHDs. Bonferroni correction was applied for multiple testing. We identified 3 SNPs in the transsulfuration pathway and 1 SNP in the folate pathway that were statistically significant after Bonferroni correction. Among infants who inherited paternally-derived copies of the G allele for rs6812588 in the RFC1 gene, the G allele for rs1762430 in the MGMT gene, and the A allele for rs9296695 and rs4712023 in the GSTA3 gene, RRs for OHD were 0.11 (95% CI: 0.04, 0.29, P = 9.16x10-7), 0.30 (95% CI: 0.17, 0.53, P = 9.80x10-6), 0.34 (95% CI: 0.20, 0.57, P = 2.28x10-5), and 0.34 (95% CI: 0.20, 0.58, P = 3.77x10-5), respectively, compared to infants who inherited maternally-derived copies of the same alleles. We observed statistically significant decreased risk of OHDs among infants who inherited paternal gene variants involved in folate and transsulfuration pathways.

Genetic predisposition to hypertension is associated with preeclampsia in European and Central Asian women

Preeclampsia is a serious complication of pregnancy, affecting both maternal and fetal health. In genome-wide association meta-analysis of European and Central Asian mothers, we identify sequence variants that associate with preeclampsia in the maternal genome at ZNF831/20q13 and FTO/16q12. These are previously established variants for blood pressure (BP) and the FTO variant has also been associated with body mass index (BMI). Further analysis of BP variants establishes that variants at MECOM/3q26, FGF5/4q21 and SH2B3/12q24 also associate with preeclampsia through the maternal genome. We further show that a polygenic risk score for hypertension associates with preeclampsia. However, comparison with gestational hypertension indicates that additional factors modify the risk of preeclampsia.

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.

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.

Language deficits in specific language impairment, attention deficit/hyperactivity disorder, and autism spectrum disorder: An analysis of polygenic risk

Language is one of the cognitive domains often impaired across many neurodevelopmental disorders. While for some disorders the linguistic deficit is the primary impairment (e.g., specific language impairment, SLI), for others it may accompany broader behavioral problems (e.g., autism). The precise nature of this phenotypic overlap has been the subject of debate. Moreover, several studies have found genetic overlaps across neurodevelopmental disorders. This raises the question of whether these genetic overlaps may correlate with phenotypic overlaps and, if so, in what manner. Here, we apply a genome‐wide approach to the study of the linguistic deficit in SLI, autism spectrum disorder (ASD), and attention deficit/hyperactivity disorder (ADHD). Using a discovery genome‐wide association study of SLI, we generate polygenic risk scores (PRS) in an independent sample which includes children with language impairment, SLI, ASD or ADHD and age‐matched controls and perform regression analyses across groups. The SLI‐trained PRS significantly predicted risk in the SLI case–control group (adjusted R² = 6.24%; P = 0.024) but not in the ASD or ADHD case‐control groups (adjusted R² = 0.0004%, 0.01%; P = 0.984, 0.889, respectively) nor for height, used as a negative control (R² = 0.2%; P = 0.452). Additionally, there was a significant difference in the normalized PRS between children with SLI and children with ASD (common language effect size = 0.66; P = 0.044). Our study suggests no additive common‐variant genetic overlap between SLI and ASD and ADHD. This is discussed in the context of phenotypic studies of SLI and related disorders. Autism Res 2020, 13: 369–381. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc.

Lay Summary

Language deficits are characteristic of specific language impairment (SLI), but may also be found in other neurodevelopmental disorders, such as autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). Many studies examined the overlaps and differences across the language deficits in these disorders, but few studies have examined the genetic aspect thereof. In this study, we use a genome‐wide approach to evaluate whether common genetic variants increasing risk of SLI may also be associated with ASD and ADHD in the same manner. Our results suggest that this is not the case, and we discuss this finding in the context of theories concerning the etiologies of these disorders.

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.

The TFAP2A-IRF6-GRHL3 genetic pathway is conserved in neurulation

Mutations in IRF6, TFAP2A and GRHL3 cause orofacial clefting syndromes in humans. However, Tfap2a and Grhl3 are also required for neurulation in mice. Here, we found that homeostasis of Irf6 is also required for development of the neural tube and associated structures. Over-expression of Irf6 caused exencephaly, a rostral neural tube defect, through suppression of Tfap2a and Grhl3 expression. Conversely, loss of Irf6 function caused a curly tail and coincided with a reduction of Tfap2a and Grhl3 expression in tail tissues. To test whether Irf6 function in neurulation was conserved, we sequenced samples obtained from human cases of spina bifida and anencephaly. We found two likely disease-causing variants in two samples from patients with spina bifida. Overall, these data suggest that the Tfap2a-Irf6-Grhl3 genetic pathway is shared by two embryologically distinct morphogenetic events that previously were considered independent during mammalian development. In addition, these data suggest new candidates to delineate the genetic architecture of neural tube defects and new therapeutic targets to prevent this common birth defect.

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.

LRP2 gene variants and their haplotypes strongly influence the risk of developing neural tube defects in the fetus: a family-triad study from South India

Neural tube defects (NTDs) are the leading cause of infant deaths worldwide. Lipoprotein related receptor 2 (LRP2) has been shown to play a crucial role in neural tube development in mouse models. However, the role of LRP2 gene in the development of human NTDs is not yet known. In view of this, family-based triad approach has been followed considering 924 subjects comprising 124 NTD case-parent trios and 184 control-parent trios diagnosed at Institute of Genetics and Hospital for Genetic Diseases, Hyderabad. Blood and tissue samples were genotyped for rs3755166 (-G759A) and rs2544390 (C835T) variants of LRP2 gene for their association with NTDs. Assessment of maternal-paternal genotype incompatibility risk for NTD revealed 3.77-folds risk with a combination of maternal GA and paternal GG genotypes (GAxGG = GA,p < 0.001), while CT genotypes of both the parents showed 4.19-folds risk for NTDs (CTxCT = CT,p = 0.009). Haplotype analysis revealed significant risk of maternal A-T (OR = 4.48,p < 0.001) and paternal G-T haplotypes (OR = 5.22,p < 0.001) for NTD development. Further, linkage analysis for parent-of-origin effects (POE) also revealed significant transmission of maternal 'A' allele (OR = 2.33,p = 0.028) and paternal 'T' allele (OR = 6.00,p = 0.016) to NTDs. Analysis of serum folate and active-B12 levels revealed significant association with LRP2 gene variants in the causation of NTDs. In conclusion, the present family-based triad study provides the first report on association of LRP2 gene variants with human NTDs.

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.

A parent-of-origin analysis of paternal genetic variants and increased risk of conotruncal heart defects

The association between conotruncal heart defects (CTHDs) and maternal genetic and environmental exposures is well studied. However, little is known about paternal genetic or environmental exposures and risk of CTHDs. We assessed the effect of paternal genetic variants in the folate, homocysteine, and transsulfuration pathways on risk of CTHDs in offspring. We utilized National Birth Defects Prevention Study data to conduct a family-based case only study using 616 live-born infants with CTHDs, born October 1997-August 2008. Maternal, paternal and infant DNA was genotyped using an Illumina® Golden Gate custom single nucleotide polymorphism (SNP) panel. Relative risks (RR) and 95% confidence intervals (CI) from log-linear models determined parent of origin effects for 921 SNPs in 60 candidate genes involved in the folate, homocysteine, and transsulfuration pathways on risk of CTHDs. The risk of CTHD among children who inherited a paternally derived copy of the A allele on GLRX (rs17085159) or the T allele of GLRX (rs12109442) was 0.23 (95%CI: 0.12, 0.42; p = 1.09 × 10^-6 ) and 0.27 (95%CI: 0.14, 0.50; p = 2.06 × 10^-5 ) times the risk among children who inherited a maternal copy of the same allele. The paternally inherited copy of the GSR (rs7818511) A allele had a 0.31 (95%CI: 0.18, 0.53; p = 9.94 × 10^-6 ] risk of CTHD compared to children with the maternal copy of the same allele. The risk of CTHD is less influenced by variants in paternal genes involved in the folate, homocysteine, or transsulfuration pathways than variants in maternal genes in those pathways.

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.

Novel Gene and Network Associations Found for Acute Lymphoblastic Leukemia Using Case-Control and Family-Based Studies in Multiethnic Populations

Background: Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, suggesting that germline variants influence ALL risk. Although multiple genome-wide association (GWA) studies have identified variants predisposing children to ALL, it remains unclear whether genetic heterogeneity affects ALL susceptibility and how interactions within and among genes containing ALL-associated variants influence ALL risk.Methods: Here, we jointly analyzed two published datasets of case-control GWA summary statistics along with germline data from ALL case-parent trios. We used the gene-level association method PEGASUS to identify genes with multiple variants associated with ALL. We then used PEGASUS gene scores as input to the network analysis algorithm HotNet2 to characterize the genomic architecture of ALL.Results: Using PEGASUS, we confirmed associations previously observed at genes such as ARID5B, IKZF1, CDKN2A/2B, and PIP4K2A, and we identified novel candidate gene associations. Using HotNet2, we uncovered significant gene subnetworks that may underlie inherited ALL risk: a subnetwork involved in B-cell differentiation containing the ALL-associated gene CEBPE, and a subnetwork of homeobox genes, including MEIS1Conclusions: Gene and network analysis uncovered loci associated with ALL that are missed by GWA studies, such as MEIS1 Furthermore, ALL-associated loci do not appear to interact directly with each other to influence ALL risk, and instead appear to influence leukemogenesis through multiple, complex pathways.Impact: We present a new pipeline for post hoc analysis of association studies that yields new insight into the etiology of ALL and can be applied in future studies to shed light on the genomic underpinnings of cancer. Cancer Epidemiol Biomarkers Prev; 26(10); 1531-9. ©2017 AACR.

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.

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.

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.

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.

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 model for family-based case-control studies of genetic imprinting and epistasis

Genetic imprinting, or called the parent-of-origin effect, has been recognized to play an important role in the formation and pathogenesis of human diseases. Although the epigenetic mechanisms that establish genetic imprinting have been a focus of many genetic studies, our knowledge about the number of imprinting genes and their chromosomal locations and interactions with other genes is still scarce, limiting precise inference of the genetic architecture of complex diseases. In this article, we present a statistical model for testing and estimating the effects of genetic imprinting on complex diseases using a commonly used case-control design with family structure. For each subject sampled from a case and control population, we not only genotype its own single nucleotide polymorphisms (SNPs) but also collect its parents' genotypes. By tracing the transmission pattern of SNP alleles from parental to offspring generation, the model allows the characterization of genetic imprinting effects based on Pearson tests of a 2 × 2 contingency table. The model is expanded to test the interactions between imprinting effects and additive, dominant and epistatic effects in a complex web of genetic interactions. Statistical properties of the model are investigated, and its practical usefulness is validated by a real data analysis. The model will provide a useful tool for genome-wide association studies aimed to elucidate the picture of genetic control over complex human diseases.