A hybrid design: case-parent triads supplemented by control-mother dyads

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.

Innovative approach to identify multigenomic and environmental interactions associated with birth defects in family-based hybrid designs

Genes, including those with transgenerational effects, work in concert with behavioral, environmental, and social factors via complex biological networks to determine human health. Understanding complex relationships between causal factors underlying human health is an essential step towards deciphering biological mechanisms. We propose a new analytical framework to investigate the interactions between maternal and offspring genetic variants or their surrogate single nucleotide polymorphisms (SNPs) and environmental factors using family-based hybrid study design. The proposed approach can analyze diverse genetic and environmental factors and accommodate samples from a variety of family units, including case/control-parental triads, and case/control-parental dyads, while minimizing potential bias introduced by population admixture. Comprehensive simulations demonstrated that our innovative approach outperformed the log-linear approach, the best available method for case-control family data. The proposed approach had greater statistical power and was capable to unbiasedly estimate the maternal and child genetic effects and the effects of environmental factors, while controlling the Type I error rate against population stratification. Using our newly developed approach, we analyzed the associations between maternal and fetal SNPs and obstructive and conotruncal heart defects, with adjustment for demographic and lifestyle factors and dietary supplements. Fourteen and 11 fetal SNPs were associated with obstructive and conotruncal heart defects, respectively. Twenty-seven and 17 maternal SNPs were associated with obstructive and conotruncal heart defects, respectively. In addition, maternal body mass index was a significant risk factor for obstructive defects. The proposed approach is a powerful tool for interrogating the etiological mechanism underlying complex traits.

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.

Effects of maternal and fetal vascular endothelial growth factor a single nucleotide polymorphisms on pre-eclampsia: A hybrid design study

Maternal and fetal gene variants play important roles in the pathology of pre-eclampsia (PE), but most studies investigating the associations between vascular endothelial growth factor A (VEGF-A) gene variates and PE focusing on maternal genetic effects. The present study firstly used a hybrid case-parent and control-mother study design investigating the both maternal and fetal effects of VEGF-A gene polymorphisms on PE among Han Chinese pregnant women. This study recruited 221 PE patients with their partners and infants and 345 normotensive women with their infants. The current study found that, in both maternal and fetal dominant model (GC + CC/GG), VEGF-A rs2010963 polymorphism was associated with an increased risk of PE (OR = 1.85, 95% CI: 1.25-2.75; OR = 1.90, 95% CI: 1.28-2.83, respectively). In the log-liner model analyses, offspring carrying the genotype of GC or CC in the rs2010963 polymorphism could increase the risk of maternal PE (OR = 1.84, 95%CI: 1.18-2.86; OR = 1.89, 95%CI: 1.02-3.49, respectively) compared to the offspring with GG. Meanwhile, the present study also found that passive smoking had a significant interaction with maternal rs2010963 polymorphism (P_LRT = 0.022) on the risk of PE.

The association between maternal and foetal REN gene polymorphisms and preeclampsia/eclampsia: A hybrid design study

OBJECTIVES

Preeclampsia (PE)/eclampsia (E) is an important cause of foetal and maternal morbidity and mortality, and its aetiology is poorly understood. Good evidence suggests that renin (REN) might be associated with PE/E. The risk of PE/E is determined by both maternal and foetal genes, but most previous studies have focused on maternal contributions. This study aimed to explore the association of maternal and foetal REN polymorphisms with PE/E in pregnant Han Chinese women.

METHODS

A case-parents/mother-control study including 347 PE/E patients with their partners and offspring and 700 control mothers with their offspring was conducted. A log-linear model was used to investigate the association between maternal and foetal REN SNPs and PE/E simultaneously, as well as the interaction of REN SNPs and environmental factors on PE/E.

RESULTS

The foetal REN rs5707 AC genotype in combination with a pre-pregnancy BMI ≥ 24 kg/m² was significantly associated with an increased risk of PE/E, with an OR of 2.75 (95%CI = 1.50-5.06). Maternal and foetal rs5707 were significantly associated with an increased risk of PE/E under the recessive model (AA + AC/CC). In haplotype analyses, foetal CCT (in the order of rs2368564, rs5707, rs5705) and TAT genotypes were positively associated with the risk of PE/E. There was no significant association between maternal and foetal REN SNP genotypes and PE/E in the transmission disequilibrium test (TDT) and log-linear model analysis.

CONCLUSIONS

Findings from this study indicate that foetal rs5707 polymorphisms may play a significant role in PE/E development, especially among overweight or obese pregnant women in China.

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.

PDGFRA gene, maternal binge drinking and obstructive heart defects

Obstructive heart defects (OHDs) are a major health concern worldwide. The platelet-derived growth factor (PDGF) genes are known to have regulatory functions that are essential for proper heart development. In a zebrafish model, Pdgfra was further demonstrated to interact with ethanol during craniofacial development. In this article, we investigated interactions between variants in PDGF genes and periconceptional alcohol exposure on the risk of OHDs by applying log-linear models to 806 OHD case and 995 control families enrolled in the National Birth Defects Prevention Study. The interactions between four variants in PDGFA and maternal binge drinking reached a nominal significance level. The maternal T allele of rs869978 was estimated to increase OHD risk among women who binge drink, while infant genotypes of rs2291591, rs2228230, rs1547904, and rs869978 may reduce the risk. Although none of these associations remain statistically significant after multiple testing adjustment and the estimated maternal effect may be influenced by unknown confounding factors, such as maternal smoking, these findings are consistent with previous animal studies supporting potential interactions between the PDGFRA gene and maternal alcohol exposure. Replication studies with larger sample sizes are needed to further elucidate this potential interplay and its influence on OHD risks.

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.

RFC-1 80G>A polymorphism in case-mother/control-mother dyads is associated with risk of nephroblastoma and neuroblastoma

AIM

Embryonic tumors are associated with an interruption during normal organ development; they may be related to disturbances in the folate pathway involved in DNA synthesis, methylation, and repair. Prenatal supplementation with folic acid is associated with a decreased risk of neuroblastoma, brain tumors, retinoblastoma, and nephroblastoma. The aim of this study was to investigate the association between MTHFR rs1801133 (C677T) and RFC-1 rs1051266 (G80A) genotypes with the risk of developing nephroblastoma and neuroblastoma.

MATERIALS AND METHODS

Case-mother/control-mother dyad study. Samples from Brazilian children with nephroblastoma (n=80), neuroblastoma (n=66), healthy controls (n=453), and their mothers (case n=93; control n=75) were analyzed. Genomic DNA was isolated from peripheral blood cells and/or buccal cells and genotyped to identify MTHFR C677T and RFC-1 G80A polymorphisms. Differences in genotype distribution between patients and controls were tested by multiple logistic regression analysis.

RESULTS

Risk for nephroblastoma and neuroblastoma was two- to fourfold increased among children with RFC-1 polymorphisms. An increased four- to eightfold risk for neuroblastoma and nephroblastoma was seen when the child and maternal genotypes were combined.

CONCLUSION

Our results suggest that mother and child RFC-1 G80A genotypes play a role on the risk of neuroblastoma and nephroblastoma since this polymorphism may impair the intracellular levels of folate, through carrying fewer folate molecules to the cell interior, and thus, the intracellular concentration is not enough to maintain regular DNA synthesis and methylation pathways.

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.

Application of a novel hybrid study design to explore gene-environment interactions in orofacial clefts

Orofacial clefts are common birth defects with strong evidence for both genetic and environmental causal factors. Candidate gene studies combined with exposures known to influence the outcome provide a highly targeted approach to detecting GxE interactions. We developed a new statistical approach that combines the case-control and offspring-parent triad designs into a "hybrid design" to search for GxE interactions among 334 autosomal cleft candidate genes and maternal first-trimester exposure to smoking, alcohol, coffee, folic acid supplements, dietary folate and vitamin A. The study population comprised 425 case-parent triads of isolated clefts and 562 control-parent triads derived from a nationwide study of orofacial clefts in Norway (1996-2001). A full maximum-likelihood model was used in combination with a Wald test statistic to screen for statistically significant GxE interaction between strata of exposed and unexposed mothers. In addition, we performed pathway-based analyses on 28 detoxification genes and 21 genes involved in folic acid metabolism. With the possible exception of the T-box 4 gene (TBX4) and dietary folate interaction in isolated CPO, there was little evidence overall of GxE interaction in our data. This study is the largest to date aimed at detecting interactions between orofacial clefts candidate genes and well-established risk exposures.

Environmental epigenetics: prospects for studying epigenetic mediation of exposure-response relationships

Changes in epigenetic marks such as DNA methylation and histone acetylation are associated with a broad range of disease traits, including cancer, asthma, metabolic disorders, and various reproductive conditions. It seems plausible that changes in epigenetic state may be induced by environmental exposures such as malnutrition, tobacco smoke, air pollutants, metals, organic chemicals, other sources of oxidative stress, and the microbiome, particularly if the exposure occurs during key periods of development. Thus, epigenetic changes could represent an important pathway by which environmental factors influence disease risks, both within individuals and across generations. We discuss some of the challenges in studying epigenetic mediation of pathogenesis and describe some unique opportunities for exploring these phenomena.

Analysis of genetic interactions involving maternal and offspring genotypes at different Loci: power simulation and application to testicular cancer

The analyses of genetic interaction between maternal and offspring genotypes are usually conducted considering a single locus. Here, we propose testing maternal × offspring (M×O) and maternal × maternal (M×M) genotype interactions involving two unlinked loci. We reformulate the log-linear approach of analyzing cases and their parents (family trios) to accommodate two loci, fit fuller models to avoid confounding in a first analysis step and propose that the model be reduced to the most prominent effects in a second step. We conduct extensive simulations to assess the validity and power of this approach under various model assumptions. We show that the approach is valid and has good power to detect M×O and M×M interactions. For example, the power to detect a dominant interaction relative risk of 1.5 (both M×O and M×M) is 70% with 300 trios and approaches 100% with 1,000 trios. Unlike the main effects, M×O and M×M interactions are conditionally independent of mating types, and consequently, their power is not affected by missing paternal genotypes. When applied to single-locus M×O interaction, our method is as powerful as other existing methods. Applying the method to testicular cancer, we found a nominally significant M×M interaction between single nucleotide polymorphisms from C-Kit Ligand (KITLG) and Sex Hormone Binding Globulin (SHBG) using 210 families (relative risk 2.2, P = 0.03). This finding supports a role of maternal hormones in offspring testicular cancer and warrants confirmation in a larger dataset.

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

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

Candidate gene analysis of spontaneous preterm delivery: new insights from re-analysis of a case-control study using case-parent triads and control-mother dyads

Background

Spontaneous preterm delivery (PTD) has a multifactorial etiology with evidence of a genetic contribution to its pathogenesis. A number of candidate gene case-control studies have been performed on spontaneous PTD, but the results have been inconsistent, and do not fully assess the role of how two genotypes can impact outcome. To elucidate this latter point we re-analyzed data from a previously published case-control candidate gene study, using a case-parent triad design and a hybrid design combining case-parent triads and control-mother dyads. These methods offer a robust approach to genetic association studies for PTD compared to traditional case-control designs.

Methods

The study participants were obtained from the Norwegian Mother and Child Cohort Study (MoBa). A total of 196 case triads and 211 control dyads were selected for the analysis. A case-parent triad design as well as a hybrid design was used to analyze 1,326 SNPs from 159 candidate genes. We compared our results to those from a previous case-control study on the same samples. Haplotypes were analyzed using a sliding window of three SNPs and a pathway analysis was performed to gain biological insight into the pathophysiology of preterm delivery.

Results

The most consistent significant fetal gene across all analyses was COL5A2. The functionally similar COL5A1 was significant when combining fetal and maternal genotypes. PON1 was significant with analytical approaches for single locus association of fetal genes alone, but was possibly confounded by maternal effects. Focal adhesion (hsa04510), Cell Communication (hsa01430) and ECM receptor interaction (hsa04512) were the most constant significant pathways.

Conclusion

This study suggests a fetal association of COL5A2 and a combined fetal-maternal association of COL5A1 with spontaneous PTD. In addition, the pathway analysis implied interactions of genes affecting cell communication and extracellular matrix.

Exploration and comparison of methods for combining population- and family-based genetic association using the Genetic Analysis Workshop 17 mini-exome

We examine the performance of various methods for combining family- and population-based genetic association data. Several approaches have been proposed for situations in which information is collected from both a subset of unrelated subjects and a subset of family members. Analyzing these samples separately is known to be inefficient, and it is important to determine the scenarios for which differing methods perform well. Others have investigated this question; however, no extensive simulations have been conducted, nor have these methods been applied to mini-exome-style data such as that provided by Genetic Analysis Workshop 17. We quantify the empirical power and false-positive rates for three existing methods applied to the Genetic Analysis Workshop 17 mini-exome data and compare relative performance. We use knowledge of the underlying data simulation model to make these assessments.

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

Many complex genetic effects, including epigenetic effects, may be expected to operate via mechanisms in the inter-uterine environment. 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 DNA from affected offspring and their mothers (case/mother duos) and to compare with an appropriate control sample. An alternative design uses data from cases and both parents (case/parent trios) but does not require controls. In this study, we describe a novel implementation of a multinomial modeling approach that allows the estimation of such genetic effects using either case/mother duos or case/parent trios. We investigate the performance of our approach using computer simulations and explore the sample sizes and data structures required to provide high power for detection of effects and accurate estimation of the relative risks conferred. Through the incorporation of additional assumptions (such as Hardy-Weinberg equilibrium, random mating and known allele frequencies) and/or the incorporation of additional types of control sample (such as unrelated controls, controls and their mothers, or both parents of controls), we show that the (relative risk) parameters of interest are identifiable and well estimated. Nevertheless, parameter interpretation can be complex, as we illustrate by demonstrating the mathematical equivalence between various different parameterizations. Our approach scales up easily to allow the analysis of large-scale genome-wide association data, provided both mothers and affected offspring have been genotyped at all variants of interest. Genet. Epidemiol. 35:19–45, 2011. © 2010 Wiley-Liss, Inc.

Detection of fetomaternal genotype associations in early-onset disorders: evaluation of different methods and their application to childhood leukemia

Several designs and analytical approaches have been proposed to dissect offspring from maternal genetic contributions to early-onset diseases. However, lack of parental controls halts the direct verification of the assumption of mating symmetry (MS) required to assess maternally-mediated effects. In this study, we used simulations to investigate the performance of existing methods under mating asymmetry (MA) when parents of controls are missing. Our results show that the log-linear, likelihood-based framework using a case-triad/case-control hybrid design provides valid tests for maternal genetic effects even under MA. Using this approach, we examined fetomaternal associations between 29 SNPs in 12 cell-cycle genes and childhood pre-B acute lymphoblastic leukemia (ALL). We identified putative fetomaternal effects at loci CDKN2A rs36228834 (P = .017) and CDKN2B rs36229158 (P = .022) that modulate the risk of childhood ALL. These data further corroborate the importance of the mother's genotype on the susceptibility to early-onset diseases.

Association of combined maternal-fetal TNF-alpha gene G308A genotypes with preterm delivery: a gene-gene interaction study

Preterm delivery (PTD) is a complicated perinatal adverse event. We were interested in association of G308A polymorphism in tumor necrosis factor-α (TNF-α) gene with PTD; so we conducted a genetic epidemiology study in Anqing City, Anhui Province, China. Case families and control families were all collected between July 1999 and June 2002. To control potential population stratification as we could, all eligible subjects were ethnic Han Chinese. 250 case families and 247 control families were included in data analysis. A hybrid design which combines case-parent triads and control parents was employed, to test maternal-fetal genotype (MFG) incompatibility. The method is based on a log-linear modeling approach. In summary, we found that when the mother's or child's genotype was G/A, there was a reduced risk of PTD; however when the mother's or child's genotype was genotype A/A, there was a relatively higher risk of PTD. Combined maternal-fetal genotype GA/GA showed the most reduced risk of PTD. Comparison of the LRTs showed that the model with maternal-fetal genotype effects fits significantly better than the model with only maternal and fetal genotype main effects (log-likelihood = −719.4, P = .023, significant at 0.05 level). That means that the combined maternal-fetal genotype incompatibility was significantly associated with PTD. The model with maternal-fetal genotype effects can be considered a gene-gene interaction model. We claim that both maternal effects and fetal effects should be considered together while investigating genetic factors of certain perinatal diseases.