Detecting Gene-Environment Interaction for Maternal Exposures Using Case-Parent Trios Ascertained Through a Case With Non-Syndromic Orofacial Cleft

Maternal and Parent-of-Origin Gene-Environment Effects on the Etiology of Orofacial Clefting

Background/Objectives: We investigated maternal and parent-of-origin (PoO) gene-environment interaction effects on the risk of nonsyndromic orofacial clefts for two maternal environmental factors: periconceptional smoking and folic acid supplementation. Methods: Genome-wide single nucleotide polymorphisms (SNPs) genotypes and TopMed-imputed genotypes were obtained for case-parent triads from the EUROCRAN and ITALCLEFT studies. Candidate regions were selected around target SNPs from a previous genome-wide association study, resulting in 12 (726 SNPs) and 11 regions (730 SNPs) for maternal and PoO effects, respectively. Log-linear models were used to analyze 404 case-parent triads and 40 case-parent dyads. p-values were combined across regions. Results: None of the interactions reached statistical significance after correction for the number of regions tested. Nominally significant (pooled p-values < 0.05) interactions pointed to regions in or close to genes LRRC7 (maternal gene-folate interaction), NCKAP5 (PoO-smoking interaction), and IFT43 and GPATCH2L (PoO-folate interaction). Conclusions: Our results suggested that the genetic effects in or around these genes were heightened under periconceptional exposure to tobacco or no folic acid supplementation. The involvement of these genes in orofacial cleft development, in conjunction with environmental exposures, should be further studied.

Gene-by-environment interactions involving maternal exposures with orofacial cleft risk in Filipinos

Maternal exposures are known to influence the risk of isolated cleft lip with or without cleft palate (CL/P) - a common and highly heritable birth defect with a multifactorial etiology. To identify new CL/P risk loci, we conducted a genome-wide gene-environment interaction (GEI) analysis of CL/P on a sample of 540 cases and 260 controls recruited from the Philippines, incorporating the interaction effects of genetic variants with maternal smoking and vitamin use. As GEI analyses are typically low in power and the results can be difficult to interpret, we used multiple testing frameworks to evaluate potential GEI effects: 1 degree-of-freedom (1df) GxE test, the 3df joint test, and the two-step EDGE approach. While we did not detect any genome-wide significant interactions, we detected 12 suggestive GEI with smoking and 25 suggestive GEI with vitamin use between all testing frameworks. Several of these loci showed biological plausibility. Notable interactions with smoking include loci near FEZF1 , TWIST2, and NET1. While FEZF1 is involved in early neuronal development, TWIST2 and NET1 regulate epithelial-mesenchymal transition which is required for proper lip and palate fusion. Interactions with vitamins encompass CECR2 - a chromatin remodeling protein required for neural tube closure-and FURIN, a critical protease during early embryogenesis that activates various growth factor and extracellular-matrix protein. The activity of both proteins is influenced by folic acid. Our findings highlight the critical role of maternal exposures in identifying genes associated with structural birth defects such as CL/P and provide new paths to explore for CL/P genetics.

Gene-environment interactions in human health

Gene-environment interactions (G × E), the interplay of genetic variation with environmental factors, have a pivotal impact on human complex traits and diseases. Statistically, G × E can be assessed by determining the deviation from expectation of predictive models based solely on the phenotypic effects of genetics or environmental exposures. Despite the unprecedented, widespread and diverse use of G × E analytical frameworks, heterogeneity in their application and reporting hinders their applicability in public health. In this Review, we discuss study design considerations as well as G × E analytical frameworks to assess polygenic liability dependent on the environment, to identify specific genetic variants exhibiting G × E, and to characterize environmental context for these dynamics. We conclude with recommendations to address the most common challenges and pitfalls in the conceptualization, methodology and reporting of G × E studies, as well as future directions.

Estimation of Direct and Indirect Polygenic Effects and Gene-Environment Interactions using Polygenic Scores in Case-Parent Trio Studies

Family-based studies provide a unique opportunity to characterize genetic risks of diseases in the presence of population structure, assortative mating, and indirect genetic effects. We propose a novel framework, PGS-TRI, for the analysis of polygenic scores (PGS) in case-parent trio studies for estimation of the risk of an index condition associated with direct effects of inherited PGS, indirect effects of parental PGS, and gene-environment interactions. Extensive simulation studies demonstrate the robustness of PGS-TRI in the presence of complex population structure and assortative mating compared to alternative methods. We apply PGS-TRI to multi-ancestry trio studies of autism spectrum disorders (Ntrio = 1,517) and orofacial clefts (Ntrio = 1,904) to establish the first transmission-based estimates of risk associated with pre-defined PGS for these conditions and other related traits. For both conditions, we further explored offspring risk associated with polygenic gene-environment interactions, and direct and indirect effects of genetically predicted levels of gene expression and metabolite traits.

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.