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1.  Evaluation of common genetic variants in 82 candidate genes as risk factors for neural tube defects 
BMC Medical Genetics  2012;13:62.
Background
Neural tube defects (NTDs) are common birth defects (~1 in 1000 pregnancies in the US and Europe) that have complex origins, including environmental and genetic factors. A low level of maternal folate is one well-established risk factor, with maternal periconceptional folic acid supplementation reducing the occurrence of NTD pregnancies by 50-70%. Gene variants in the folate metabolic pathway (e.g., MTHFR rs1801133 (677 C > T) and MTHFD1 rs2236225 (R653Q)) have been found to increase NTD risk. We hypothesized that variants in additional folate/B12 pathway genes contribute to NTD risk.
Methods
A tagSNP approach was used to screen common variation in 82 candidate genes selected from the folate/B12 pathway and NTD mouse models. We initially genotyped polymorphisms in 320 Irish triads (NTD cases and their parents), including 301 cases and 341 Irish controls to perform case–control and family based association tests. Significantly associated polymorphisms were genotyped in a secondary set of 250 families that included 229 cases and 658 controls. The combined results for 1441 SNPs were used in a joint analysis to test for case and maternal effects.
Results
Nearly 70 SNPs in 30 genes were found to be associated with NTDs at the p < 0.01 level. The ten strongest association signals (p-value range: 0.0003–0.0023) were found in nine genes (MFTC, CDKN2A, ADA, PEMT, CUBN, GART, DNMT3A, MTHFD1 and T (Brachyury)) and included the known NTD risk factor MTHFD1 R653Q (rs2236225). The single strongest signal was observed in a new candidate, MFTC rs17803441 (OR = 1.61 [1.23-2.08], p = 0.0003 for the minor allele). Though nominally significant, these associations did not remain significant after correction for multiple hypothesis testing.
Conclusions
To our knowledge, with respect to sample size and scope of evaluation of candidate polymorphisms, this is the largest NTD genetic association study reported to date. The scale of the study and the stringency of correction are likely to have contributed to real associations failing to survive correction. We have produced a ranked list of variants with the strongest association signals. Variants in the highest rank of associations are likely to include true associations and should be high priority candidates for further study of NTD risk.
doi:10.1186/1471-2350-13-62
PMCID: PMC3458983  PMID: 22856873
Neural tube defects; Spina bifida; Folic acid; One-carbon metabolism; Candidate gene
2.  The impact of complex informative missingness on the validity of the transmission/disequilibrium test (TDT) 
BMC Proceedings  2007;1(Suppl 1):S26.
The transmission/disequilibrium test was introduced to test for linkage and association between a marker and a putative disease locus using case-parent triads. Several extensions have been proposed to accommodate incomplete triads. Some strategies assumed that parental genotypes were missing completely at random and some methods allowed informative missingness for parental genotypes. However, the above tests assumed that offspring genotypes were missing completely at random and concluded that the transmission/disequilibrium test remained a valid test by excluding incomplete triads from the analysis. In this article, the conditional distribution of ascertained triads allowing informative missingness for offspring genotypes, as well as their parental genotypes, was derived and several tests under such scenarios were evaluated. In simulations, independent triads from the Genetic Analysis Workshop 15 simulated data (Problem 3) was ascertained. When offspring genotypes were missing informatively, simulation results revealed inflated type I error and/or reduced power for the transmission/disequilibrium test excluding incomplete triads.
PMCID: PMC2367473  PMID: 18466523
3.  Association analysis of complex diseases using triads, parent-child dyads and singleton monads 
BMC Genetics  2013;14:78.
Background
Triad families are routinely used to test association between genetic variants and complex diseases. Triad studies are important and popular since they are robust in terms of being less prone to false positives due to population structure. In practice, one may collect not only complete triads, but also incomplete families such as dyads (affected child with one parent) and singleton monads (affected child without parents). Since there is a lack of convenient algorithms and software to analyze the incomplete data, dyads and monads are usually discarded. This may lead to loss of power and insufficient utilization of genetic information in a study.
Results
We develop likelihood-based statistical models and likelihood ratio tests to test for association between complex diseases and genetic markers by using combinations of full triads, parent-child dyads, and affected singleton monads for a unified analysis. A likelihood is calculated directly to facilitate the data analysis without imputation and to avoid computational complexity. This makes it easy to implement the models and to explain the results.
Conclusion
By simulation studies, we show that the proposed models and tests are very robust in terms of accurately controlling type I error evaluations, and are powerful by empirical power evaluations. The methods are applied to test for association between transforming growth factor alpha (TGFA) gene and cleft palate in an Irish study.
doi:10.1186/1471-2156-14-78
PMCID: PMC3844511  PMID: 24007308
Association mapping of complex diseases; Likelihood ratio tests; Transmission disequilibrium tests
4.  Genetic Determinants of Facial Clefting: Analysis of 357 Candidate Genes Using Two National Cleft Studies from Scandinavia 
PLoS ONE  2009;4(4):e5385.
Background
Facial clefts are common birth defects with a strong genetic component. To identify fetal genetic risk factors for clefting, 1536 SNPs in 357 candidate genes were genotyped in two population-based samples from Scandinavia (Norway: 562 case-parent and 592 control-parent triads; Denmark: 235 case-parent triads).
Methodology/Principal Findings
We used two complementary statistical methods, TRIMM and HAPLIN, to look for associations across these two national samples. TRIMM tests for association in each gene by using multi-SNP genotypes from case-parent triads directly without the need to infer haplotypes. HAPLIN on the other hand estimates the full haplotype distribution over a set of SNPs and estimates relative risks associated with each haplotype. For isolated cleft lip with or without cleft palate (I-CL/P), TRIMM and HAPLIN both identified significant associations with IRF6 and ADH1C in both populations, but only HAPLIN found an association with FGF12. For isolated cleft palate (I-CP), TRIMM found associations with ALX3, MKX, and PDGFC in both populations, but only the association with PDGFC was identified by HAPLIN. In addition, HAPLIN identified an association with ETV5 that was not detected by TRIMM.
Conclusion/Significance
Strong associations with seven genes were replicated in the Scandinavian samples and our approach effectively replicated the strongest previously known association in clefting—with IRF6. Based on two national cleft cohorts of similar ancestry, two robust statistical methods and a large panel of SNPs in the most promising cleft candidate genes to date, this study identified a previously unknown association with clefting for ADH1C and provides additional candidates and analytic approaches to advance the field.
doi:10.1371/journal.pone.0005385
PMCID: PMC2671138  PMID: 19401770
5.  A hybrid design: case-parent triads supplemented by control-mother dyads 
Genetic epidemiology  2009;33(2):136.
Hybrid designs arose from an effort to combine the benefits of family-based and population-based study designs. A recently proposed hybrid approach augments case-parent triads with population-based control-parent triads, genotyping everyone except the control offspring. Including parents of controls substantially improves statistical efficiency for testing and estimating both offspring and maternal genetic relative risk parameters relative to using case-parent triads alone. Moreover, it allows testing of required assumptions. Nevertheless, control fathers can be hard to recruit, whereas control offspring and their mothers may be readily available. Consequently, we propose an alternative hybrid design where offspring-mother pairs, instead of parents, serve as population-based controls. We compare the power of our proposed method with several competitors and show that it performs well in various scenarios, though it is slightly less powerful than the hybrid design that uses control parents. We describe approaches for checking whether population stratification will bias inferences that use controls and whether the mating symmetry assumption holds. Surprisingly, if mating symmetry is violated, even though mating-type parameters cannot be directly estimated using control-mother dyads alone, and maternal effects cannot be estimated using case-parent triads alone, combining both sources of data allows estimation of all the parameters. This hybrid design can also be used to study environmental influences on disease risk and gene-by-environment interactions.
doi:10.1002/gepi.20365
PMCID: PMC2819841  PMID: 18759250
genetic relative risk; maternal effect; Single Nucleotide Polymorphism (SNP); association studies; family-based design; population-based design; Poisson regression; early-onset disease
6.  A New Method to Account for Missing Data in Case-Parent Triad Studies 
Human Heredity  2009;68(4):268-277.
Background/Aims
The case-parent triad design is commonly used in genetic association studies. Generally, samples are drawn from an affected offspring, manifesting a phenotype of interest, as well as from the parents. The trio genotypes may be analyzed using a variety of available methods, but we focus on log-linear models because they test for genetic association and additionally estimate the relative risks of transmission. The models need to be modified to adjust for missing genotypes. Furthermore, instability in the parameter estimates can arise when certain kinds of genotype combinations do not appear in the dataset.
Methods
In this paper, we kill two birds with one stone. We propose a new method to simultaneously account for missing genotype data and genotype combinations with zero counts. This method solves a zero-inflated Poisson (ZIP) regression likelihood. The maximum likelihood estimates yield relative risks and the information matrix gives appropriate variance estimates for inference. A likelihood ratio test determines the significance of genetic association.
Results
We compared the ZIP regression to previously proposed methods in both simulation studies and in a dataset that investigates the risk of orofacial clefts. The ZIP likelihood estimates regression coefficients with less bias than other methods when the minor allele frequency is small.
doi:10.1159/000228924
PMCID: PMC2943516  PMID: 19622893
Log-linear models; Case-parent triad design; Missing data
7.  The 677C>T (rs1801133) Polymorphism in the MTHFR Gene Contributes to Colorectal Cancer Risk: A Meta-Analysis Based on 71 Research Studies 
PLoS ONE  2013;8(2):e55332.
Background
The 677C>T polymorphism of methylenetetrahydrofolate reductase (MTHFR) gene is considered to have a significant effect on colorectal cancer susceptibility, but the results are inconsistent. In order to investigate the association between the MTHFR 677C>T polymorphism and the risk of colorectal cancer, a meta-analysis was held based on 71 published studies.
Methods
Eligible studies were identified through searching the MEDLINE, EMBASE, PubMed, Web of Science, Chinese Biomedical Literature database (CBM) and CNKI database. Odds ratios (OR) and 95% confidence intervals (CIs) were used to assess the association. The statistical heterogeneity across studies was examined with x2-based Q-test. Begg's and Egger's test were also carried out to evaluate publication bias. Sensitive and subgroup analysis were also held in this meta-analysis.
Results
Overall, 71 publications including 31,572 cases and 44,066 controls were identified. The MTHFR 677 C>T variant genotypes are significantly associated with increased risk of colorectal cancer. In the stratified analysis by ethnicity, significantly increased risks were also found among Caucasians for CC vs TT (OR = 1.076; 95%CI =  1.008–1.150; I2 = 52.3%), CT vs TT (OR = 1.102; 95%CI = 1.032–1.177; I2 = 51.4%) and dominant model (OR = 1.086; 95%CI = 1.021–1.156; I2 = 53.6%). Asians for CC vs TT (OR  = 1.226; 95%CI  = 1.116–1.346; I2  = 55.3%), CT vs TT (OR  = 1.180; 95%CI  = 1.079–1.291; I2  = 36.2%), recessive (OR  = 1.069; 95%CI  = 1.003-1.140; I2  = 30.9%) and dominant model (OR  = 1.198; 95%CI  = 1.101-1.303; I2  = 52.4%), and Mixed populations for CT vs TT (OR  = 1.142; 95%CI  = 1.005-1.296; I2  = 0.0%). However, no associations were found in Africans for all genetic models.
Conclusion
This meta-analysis suggests that the MTHFR 677C>T polymorphism increases the risk for developing colorectal cancer, while there is no association among Africans found in subgroup analysis by ethnicity.
doi:10.1371/journal.pone.0055332
PMCID: PMC3577825  PMID: 23437053
8.  Application of a novel hybrid study design to explore gene-environment interactions in orofacial clefts 
Annals of Human Genetics  2012;76(3):221-236.
Summary
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.
doi:10.1111/j.1469-1809.2012.00707.x
PMCID: PMC3334353  PMID: 22497478
Birth defects; orofacial cleft; cleft lip; cleft palate; genetic epidemiology
9.  A case-parent triad assessment of folate metabolic genes and the risk of childhood acute lymphoblastic leukemia 
Cancer causes & control : CCC  2012;23(11):1797-1803.
Purpose
We conducted a case-parent triad study evaluating the role of maternal and offspring genotypes in the folate metabolic pathway on childhood acute lymphoblastic leukemia (ALL) risk.
Methods
Childhood ALL case-parent triads (N = 120) were recruited from Texas Children’s Hospital. DNA samples were genotyped using the Sequenom iPLEX MassARRAY for 68 tagSNPs in six folate metabolic pathway genes (MTHFR, MTRR, MTR, DHFR, BHMT, and TYMS). Log-linear modeling was used to examine the associations between maternal and offspring genotypes and ALL.
Results
After controlling for the false discovery rate (<0.1), there were 20 significant maternal effects in the following genes: BHMT (N = 3), MTR (N = 12), and TYMS (N = 5). For instance, maternal genotypes for BHMT rs558133 (relative risk [RR] = 0.51, 95% confidence interval [CI]: 0.30–0.87, P = 0.008, Q = 0.08) and MTR rs2282369 (RR = 0.46, 95% CI: 0.27–0.80, P = 0.004, Q = 0.08) were associated with ALL. There were no significant offspring effects after controlling for the false discovery rate.
Conclusions
This is one of the few studies conducted to evaluate maternal genetic effects in the context of childhood ALL risk. Furthermore, we employed a family-based design that is less susceptible to population stratification bias in the estimation of maternal genetic effects. Our findings suggest that maternal genetic variation in the folate metabolic pathway is relevant in the etiology of childhood ALL. The observed maternal genetic effects support the need for continued research of how the uterine environment may influence risk of ALL.
doi:10.1007/s10552-012-0058-z
PMCID: PMC3472623  PMID: 22941668
Acute lymphoblastic leukemia; case-parent triad; folate; genetic epidemiology; pediatric cancer
10.  Tracking Dynamic Water-borne Outbreaks with Temporal Consistency Constraints 
Objective
We describe a novel graph-based event detection approach which can accurately identify and track dynamic outbreaks (where the affected region changes over time). Our approach enforces soft constraints on temporal consistency, allowing detected regions to grow, shrink, or move while penalizing implausible region dynamics. Using simulated contaminant plumes diffusing through a water distribution system, we demonstrate that our method improves both detection time and spatial-temporal accuracy when tracking dynamic water-borne outbreaks.
Introduction
Space-time scan statistics are often used to identify emerging spatial clusters of disease cases [1,2]. They operate by maximizing a score function (likelihood ratio statistic) over multiple spatio-temporal regions. The temporal component is typically incorporated by aggregating counts across a given time window, thus assuming that the affected region does not change over time. To relax this hard constraint on spatial-temporal “shape” and increase detection power and accuracy when tracking spreading outbreaks, we implement a new graph-based event detection approach which enables identification of dynamic clusters while enforcing temporal consistency constraints between temporally-adjacent spatial regions.
Methods
In the subset scanning framework, temporal consistency constraints may be interpreted as influencing the prior probability pit of location i being included in the optimal spatial subset at time t. We model this prior probability for each location as log(pit/(1−pit))=B0+B1Xit−1 where Xit−1 is 1 if location i was included in the previous time step and 0 otherwise, and maximize the penalized log-likelihood ratio over dynamic spatio-temporal regions. Our efficient algorithm incorporates these constraints into the Graph-Scan method [3] by iteratively optimizing the spatial subset for each time slice conditioned on the previous and next slices. Each individual optimization step is made possible by expressing the score function as an additive function (conditioned on the relative risk), which enables the priors to be included while maintaining computational efficiency.
Results
Outbreak plumes were simulated in a water distribution system for 12 one-hour periods. We assumed noisy binary sensors (with 10% false positive and 90% true positive rates) observed hourly at each pipe junction. Our method (“Dynamic”) was compared to the “Static” method, which aggregates counts across time for each spatial region and is therefore constrained to only return temporal cylinders, and the “Independent” method, which separately optimizes the spatial subset for each time slice without taking temporal consistency into account. The methods were evaluated on spatial-temporal overlap (Figure 1), defined as the number of sensors contained in both the detected and affected space-time regions divided by the number of sensors in either the detected or affected space-time regions. A measure of 1 is a perfect match of spatial subsets across each time window and 0 would reflect disjoint space-time regions. Additionally, average time to detect an outbreak (at a fixed false positive rate of 1/month) was 4.24, 4.56, and 6.65 hours for the dynamic, static, and independent methods respectively.
Conclusions
Relaxing constraints on spatial-temporal region shape must be done carefully. Allowing independent selection of spatial regions loses important temporal information while hard constraints on the spatial-temporal region will fail to capture the dynamics of the outbreak. Our approach for detecting dynamic space-time clusters, while incorporating temporal consistency constraints, addresses these issues and results in higher spatial-temporal accuracy and detection power.
Spatial-temporal overlap for three competing detection methods.
PMCID: PMC3692798
outbreak detection; space-time scan statistics; dynamic event tracking; penalized likelihood ratio
11.  Association of Combined Maternal-Fetal TNF-α 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.
doi:10.1155/2010/396184
PMCID: PMC2836175  PMID: 20224765
12.  Using a Bayesian Hierarchical Model for Identifying Single Nucleotide Polymorphisms Associated with Childhood Acute Lymphoblastic Leukemia Risk in Case-Parent Triads 
PLoS ONE  2013;8(12):e84658.
Childhood acute lymphoblastic leukemia (ALL) is a condition that arises from complex etiologies. The absence of consistent environmental risk factors and the presence of modest familial associations suggest ALL is a complex trait with an underlying genetic component. The identification of genetic factors associated with disease is complicated by complex genetic covariance structures and multiple testing issues. Both issues can be resolved with appropriate Bayesian variable selection methods. The present study was undertaken to extend our hierarchical Bayesian model for case-parent triads to incorporate single nucleotide polymorphisms (SNPs) and incorporate the biological grouping of SNPs within genes. Based on previous evidence that genetic variation in the folate metabolic pathway influences ALL risk, we evaluated 128 tagging SNPs in 16 folate metabolic genes among 118 ALL case-parent triads recruited from the Texas Children’s Cancer Center (Houston, TX) between 2003 and 2010. We used stochastic search gene suggestion (SSGS) in hierarchical Bayesian models to evaluate the association between folate metabolic SNPs and ALL. Using Bayes factors among these variants in childhood ALL case-parent triads, two SNPs were identified with a Bayes factor greater than 1. There was evidence that the minor alleles of NOS3 rs3918186 (OR = 2.16; 95% CI: 1.51-3.15) and SLC19A1 rs1051266 (OR = 2.07; 95% CI: 1.25-3.46) were positively associated with childhood ALL. Our findings are suggestive of the role of inherited genetic variation in the folate metabolic pathway on childhood ALL risk, and they also suggest the utility of Bayesian variable selection methods in the context of case-parent triads for evaluating the role of SNPs on disease risk.
doi:10.1371/journal.pone.0084658
PMCID: PMC3868670  PMID: 24367687
13.  Genetic Variants in the Folate Pathway and the Risk of Neural Tube Defects: A Meta-Analysis of the Published Literature 
PLoS ONE  2013;8(4):e59570.
Background
Neural Tube Defects (NTDs) are among the most prevalent and most severe congenital malformations worldwide. Polymorphisms in key genes involving the folate pathway have been reported to be associated with the risk of NTDs. However, the results from these published studies are conflicting. We surveyed the literature (1996–2011) and performed a comprehensive meta-analysis to provide empirical evidence on the association.
Methods and Findings
We investigated the effects of 5 genetic variants from 47 study populations, for a total of 85 case-control comparisons MTHFR C677T (42 studies; 4374 cases, 7232 controls), MTHFR A1298C (22 studies; 2602 cases, 4070 controls), MTR A2756G (9 studies; 843 cases, 1006 controls), MTRR A66G (8 studies; 703 cases, 1572 controls), and RFC-1 A80G (4 studies; 1107 cases, 1585 controls). We found a convincing evidence of dominant effects of MTHFR C677T (OR 1.23; 95%CI 1.07–1.42) and suggestive evidence of RFC-1 A80G (OR 1.55; 95%CI 1.24–1.92). However, we found no significant effects of MTHFR A1298C, MTR A2756G, MTRR A66G in risk of NTDs in dominant, recessive or in allelic models.
Conclusions
Our meta-analysis strongly suggested a significant association of the variant MTHFR C677T and a suggestive association of RFC-1 A80G with increased risk of NTDs. However, other variants involved in folate pathway do not demonstrate any evidence for a significant marginal association on susceptibility to NTDs.
doi:10.1371/journal.pone.0059570
PMCID: PMC3617174  PMID: 23593147
14.  Using Imputed Genotypes for Relative Risk Estimation in Case-Parent Studies 
American Journal of Epidemiology  2011;173(5):553-559.
Meta-analyses of genome-wide association studies are often based on imputed single nucleotide polymorphism (SNP) data, because component studies were genotyped using different platforms. One would like to include case-parent triad studies along with case-control studies in such meta-analyses. However, there are no published methods for estimating relative risks from imputed data for case-parent triad studies. The authors propose a method for estimating the relative risk for a variant SNP allele based on a log-additive model. Their simulations first confirm that the proposed method performs well with genotyped SNP data. As an empirical test of the method's behavior with imputed SNPs, the authors then apply it to chromosome 22 data from the Mexico City Childhood Asthma Study (1998–2003). For chromosome 22, the authors had data on 7,293 SNPs that were both genotyped and imputed using the software MACH, which relies on linkage disequilibrium with nearby SNPs. Correlation between estimated relative risks based on the actual genotypes and those based on the imputed genotypes was remarkably high (r2 = 0.95), validating this method of relative risk estimation for the case-parent study design. This method should be useful to investigators who wish to conduct meta-analyses using imputed SNP data from both case-parent triad and case-control studies.
doi:10.1093/aje/kwq363
PMCID: PMC3291117  PMID: 21296892
epidemiologic methods; genome-wide association study; genotype; imputation; meta-analysis; risk
15.  Calculating Asymptotic Significance Levels of the Constrained Likelihood Ratio Test with Application to Multivariate Genetic Linkage Analysis 
The asymptotic distribution of the multivariate variance component linkage analysis likelihood ratio test has provoked some contradictory accounts in the literature. In this paper we confirm that some previous results are not correct by deriving the asymptotic distribution in one special case. It is shown that this special case is a good approximation to the distribution in many situations. We also introduce a new approach to simulating from the asymptotic distribution of the likelihood ratio test statistic in constrained testing problems. It is shown that this method is very efficient for small p-values, and is applicable even when the constraints are not convex. The method is related to a multivariate integration problem. We illustrate how the approach can be applied to multivariate linkage analysis in a simulation study. Some more philosophical issues relating to one-sided tests in variance components linkage analysis are discussed.
doi:10.2202/1544-6115.1456
PMCID: PMC2861321  PMID: 19799558
16.  Maternal Genes and Facial Clefts in Offspring: A Comprehensive Search for Genetic Associations in Two Population-Based Cleft Studies from Scandinavia 
PLoS ONE  2010;5(7):e11493.
Background
Fetal conditions can in principle be affected by the mother's genotype working through the prenatal environment.
Methodology/Principal Findings
Genotypes for 1536 SNPs in 357 cleft candidate genes were available from a previous analysis in which we focused on fetal gene effects [1]. After data-cleaning, genotypes for 1315 SNPs in 334 autosomal genes were available for the current analysis of maternal gene effects. Two complementary statistical methods, TRIMM and HAPLIN, were used to detect multi-marker effects in population-based samples from Norway (562 case-parent and 592 control-parent triads) and Denmark (235 case-parent triads). We analyzed isolated cleft lip with or without cleft palate (iCL/P) and isolated cleft palate only (iCP) separately and assessed replication by looking for genes detected in both populations by both methods. In iCL/P, neither TRIMM nor HAPLIN detected more genes than expected by chance alone; furthermore, the selected genes were not replicated across the two methods. In iCP, however, FLNB was identified by both methods in both populations. Although HIC1 and ZNF189 did not fully satisfy our stringency criterion for replication, they were strongly associated with iCP in TRIMM analyses of the Norwegian triads.
Conclusion/Significance
Except for FLNB, HIC1 and ZNF189, maternal genes did not appear to influence the risk of clefting in our data. This is consistent with recent epidemiological findings showing no apparent difference between mother-to-offspring and father-to-offspring recurrence of clefts in these two populations. It is likely that fetal genes make the major genetic contribution to clefting risk in these populations, but we cannot rule out the possibility that maternal genes can affect risk through interactions with specific teratogens or fetal genes.
doi:10.1371/journal.pone.0011493
PMCID: PMC2901336  PMID: 20634891
17.  ZDHHC8 as a candidate gene for schizophrenia: Analysis of a putative functional intronic marker in case-control and family-based association studies 
BMC Psychiatry  2005;5:35.
Background
The chromosome 22q11 region is proposed as a major candidate locus for susceptibility genes to schizophrenia. Recently, the gene ZDHHC8 encoding a putative palmitoyltransferase at 22q11 was proposed to increase liability to schizophrenia based on both animal models and human association studies by significant over-transmission of allele rs175174A in female, but not male subjects with schizophrenia.
Methods
Given the genetic complexity of schizophrenia and the potential genetic heterogeneity in different populations, we examined rs175174 in 204 German proband-parent triads and in an independent case-control study (schizophrenic cases: n = 433; controls: n = 186).
Results
In the triads heterozygous parents transmitted allele G preferentially to females, and allele A to males (heterogeneity χ2 = 4.43; p = 0.035). The case-control sample provided no further evidence for overall or gender-specific effects regarding allele and genotype frequency distributions.
Conclusion
The findings on rs175174 at ZDHHC8 are still far from being conclusive, but evidence for sexual dimorphism is moderate, and our data do not support a significant genetic contribution of rs175174 to the aetiopathogenesis of schizophrenia.
doi:10.1186/1471-244X-5-35
PMCID: PMC1274335  PMID: 16225675
18.  Association of 677 C>T (rs1801133) and 1298 A>C (rs1801131) Polymorphisms in the MTHFR Gene and Breast Cancer Susceptibility: A Meta-Analysis Based on 57 Individual Studies 
PLoS ONE  2014;9(6):e71290.
Objective
The 677 C>T and 1298 A>C polymorphisms of methylenetetrahydrofolate reductase (MTHFR) gene have been widely reported and considered to have a significant effect on breast cancer risk, but the results are inconsistent. A meta-analysis based on 57 eligible studies was carried out to clarify the role of MTHFR gene polymorphisms in breast cancer.
Methods and Results
Eligible articles were identified by searching databases including PubMed, Web of Science, EMBASE, CNKI and CBM for the period up to August 2012. Finally, a total of 57 studies were included in this meta-analysis. Crude ORs with 95% CIs were used to assess the association between the MTHFR polymorphisms and breast cancer risk. The pooled ORs were performed with additive model, dominant model and recessive model, respectively. Subgroup analysis was also performed by ethnicity. The statistical heterogeneity across studies was examined with χ2-based Q-test. A meta-analysis was performed using the Stata 12.0 software. Overall, the 677 C allele was significantly associated with breast cancer risk (OR = 0.942, 95%CI = 0.898 to 0.988) when compared with the 677 T allele in the additive model, and the same results were also revealed under other genetic models. Simultaneously, the 1298 A allele was not associated with the breast cancer susceptibility when compared with the 1298 C allele (OR = 0.993, 95%CI = 0.978 to 1.009). Furthermore, analyses under the dominant, recessive and the allele contrast model yielded similar results.
Conclusions
The results of this meta-analysis suggest that 677 C>T polymorphism in the MTHFR gene may contribute to breast cancer development. However, the 1298 A>C polymorphism is not significantly associated with increased risks of breast cancer.
doi:10.1371/journal.pone.0071290
PMCID: PMC4063741  PMID: 24945727
19.  Diabetes and Obesity-Related Genes and the Risk of Neural Tube Defects in the National Birth Defects Prevention Study 
American Journal of Epidemiology  2012;176(12):1101-1109.
Few studies have evaluated genetic susceptibility related to diabetes and obesity as a risk factor for neural tube defects (NTDs). The authors investigated 23 single nucleotide polymorphisms among 9 genes (ADRB3, ENPP1, FTO, LEP, PPARG, PPARGC1A, SLC2A2, TCF7L2, and UCP2) associated with type 2 diabetes or obesity. Samples were obtained from 737 NTD case-parent triads included in the National Birth Defects Prevention Study during 1999–2007. Log-linear models were used to evaluate maternal and offspring genetic effects. After application of the false discovery rate, there were 5 significant maternal genetic effects. The less common alleles at the 4 FTO single nucleotide polymorphisms showed a reduction of NTD risk (for rs1421085, relative risk (RR) = 0.73 (95% confidence interval (CI): 0.62, 0.87); for rs8050136, RR = 0.79 (95% CI: 0.67, 0.93); for rs9939609, RR = 0.79 (95% CI: 0.67, 0.94); and for rs17187449, RR = 0.80 (95% CI: 0.68, 0.95)). Additionally, maternal LEP rs2071045 (RR = 1.31, 95% CI: 1.08, 1.60) and offspring UCP2 rs660339 (RR = 1.32, 95% CI: 1.06, 1.64) were associated with NTD risk. Furthermore, the maternal genotype for TCF7L2 rs3814573 suggested an increased NTD risk among obese women. These findings indicate that maternal genetic variants associated with glucose homeostasis may modify the risk of having an NTD-affected pregnancy.
doi:10.1093/aje/kws190
PMCID: PMC3571234  PMID: 23132673
case-parent triads; diabetes; genetics; neural tube defects; obesity
20.  Gene–gene interaction in folate-related genes and risk of neural tube defects in a UK population 
Journal of Medical Genetics  2004;41(4):256-260.
Objective: To investigate the contribution of polymorphic variation in genes involved in the folate-dependent homocysteine pathway in the aetiology of neural tube defects (NTD).
Design: Case-control association study.
Subjects: A total of 530 individuals from families affected by NTD, 645 maternal controls, and 602 healthy newborn controls from the northern UK.
Main outcome measures: Seven polymorphisms in six genes coding for proteins in the folate-dependent homocysteine pathway (MTHFR 677C→T, MTHFR 1298A→C, MTRR 66A→G, SHMT 1420C→T, CßS 844ins68, GCPII 1561C→T, RFC-1 80G→A). The impact of each polymorphism and the effect of gene–gene interactions (epistasis) upon risk of NTD were assessed using logistic regression analysis.
Results: The MTHFR 677C→T polymorphism was shown to represent a risk factor in NTD cases (CC v CT+TT odds ratio (OR) 2.03 [95% confidence interval (CI) 1.09, 3.79] p = 0.025) and the MTRR 66A→G polymorphism was shown to exert a protective effect in NTD cases (AA v AG+GG OR 0.31 [95% CI 0.10, 0.94] p = 0.04). When statistical tests for interaction were conducted, three genotype combinations in cases (MTRR/GCPII; MTHFR 677/CßS; MTHFR 677/MTRR) and one combination in case mothers (CßS/RFC-1) were shown to elevate NTD risk. Maternal–fetal interaction was also detected when offspring carried the MTHFR 677C→T variant and mothers carried the MTRR 66A→G variant, resulting in a significantly elevated risk of NTD.
Conclusion: Both independent genetic effects and gene–gene interaction were observed in relation to NTD risk. Multi-locus rather than single locus analysis might be preferable to gain an accurate assessment of genetic susceptibility to NTD.
doi:10.1136/jmg.2003.010694
PMCID: PMC1735724  PMID: 15060097
21.  Homocysteine and Coronary Heart Disease: Meta-analysis of MTHFR Case-Control Studies, Avoiding Publication Bias 
PLoS Medicine  2012;9(2):e1001177.
Robert Clarke and colleagues conduct a meta-analysis of unpublished datasets to examine the causal relationship between elevation of homocysteine levels in the blood and the risk of coronary heart disease. Their data suggest that an increase in homocysteine levels is not likely to result in an increase in risk of coronary heart disease.
Background
Moderately elevated blood levels of homocysteine are weakly correlated with coronary heart disease (CHD) risk, but causality remains uncertain. When folate levels are low, the TT genotype of the common C677T polymorphism (rs1801133) of the methylene tetrahydrofolate reductase gene (MTHFR) appreciably increases homocysteine levels, so “Mendelian randomization” studies using this variant as an instrumental variable could help test causality.
Methods and Findings
Nineteen unpublished datasets were obtained (total 48,175 CHD cases and 67,961 controls) in which multiple genetic variants had been measured, including MTHFR C677T. These datasets did not include measurements of blood homocysteine, but homocysteine levels would be expected to be about 20% higher with TT than with CC genotype in the populations studied. In meta-analyses of these unpublished datasets, the case-control CHD odds ratio (OR) and 95% CI comparing TT versus CC homozygotes was 1.02 (0.98–1.07; p = 0.28) overall, and 1.01 (0.95–1.07) in unsupplemented low-folate populations. By contrast, in a slightly updated meta-analysis of the 86 published studies (28,617 CHD cases and 41,857 controls), the OR was 1.15 (1.09–1.21), significantly discrepant (p = 0.001) with the OR in the unpublished datasets. Within the meta-analysis of published studies, the OR was 1.12 (1.04–1.21) in the 14 larger studies (those with variance of log OR<0.05; total 13,119 cases) and 1.18 (1.09–1.28) in the 72 smaller ones (total 15,498 cases).
Conclusions
The CI for the overall result from large unpublished datasets shows lifelong moderate homocysteine elevation has little or no effect on CHD. The discrepant overall result from previously published studies reflects publication bias or methodological problems.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Coronary heart disease (CHD) is the leading cause of death among adults in developed countries. With age, fatty deposits (atherosclerotic plaques) coat the walls of the coronary arteries, the blood vessels that supply the heart with oxygen and nutrients. The resultant restriction of the heart's blood supply causes shortness of breath, angina (chest pains that are usually relieved by rest), and sometimes fatal heart attacks. Many established risk factors for CHD, including smoking, physical inactivity, being overweight, and eating a fat-rich diet, can be modified by lifestyle changes. Another possible modifiable risk factor for CHD is a high blood level of the amino acid homocysteine. Methylene tetrahydofolate reductase, which is encoded by the MTHFR gene, uses folate to break down and remove homocysteine so fortification of cereals with folate can reduce population homocysteine blood levels. Pooled results from prospective observational studies that have looked for an association between homocysteine levels and later development of CHD suggest that the reduction in homocysteine levels that can be achieved by folate supplementation is associated with an 11% lower CHD risk.
Why Was This Study Done?
Prospective observational studies cannot prove that high homocysteine levels cause CHD because of confounding, the potential presence of other unknown shared characteristics that really cause CHD. However, an approach called “Mendelian randomization” can test whether high blood homocysteine causes CHD. A common genetic variant of the MTHFR gene—the C677T polymorphism—reduces MTHFR efficiency so TT homozygotes (individuals in whom both copies of the MTHFR gene have the nucleotide thymine at position 677; the human genome contains two copies of most genes) have 25% higher blood homocysteine levels than CC homozygotes. In meta-analyses (statistical pooling of the results of several studies) of published Mendelian randomized studies, TT homozygotes have a higher CHD risk than CC homozygotes. Because gene variants are inherited randomly, they are not subject to confounding, so this result suggests that high blood homocysteine causes CHD. But what if only Mendelian randomization studies that found an association have been published? Such publication bias would affect this aggregate result. Here, the researchers investigate the association of the MTHFR C677T polymorphism with CHD in unpublished datasets that have analyzed this polymorphism incidentally during other genetic studies.
What Did the Researchers Do and Find?
The researchers obtained 19 unpublished datasets that contained data on the MTHFR C677T polymorphism in thousands of people with and without CHD. Meta-analysis of these datasets indicates that the excess CHD risk in TT homozygotes compared to CC homozygotes was 2% (much lower than predicted from the prospective observational studies), a nonsignificant difference (that is, it could have occurred by chance). When the probable folate status of the study populations (based on when national folic acid fortification legislation came into effect) was taken into account, there was still no evidence that TT homozygotes had an excess CHD risk. By contrast, in an updated meta-analysis of 86 published studies of the association of the polymorphism with CHD, the excess CHD risk in TT homozygotes compared to CC homozygotes was 15%. Finally, in a meta-analysis of randomized trials on the use of vitamin B supplements for homocysteine reduction, folate supplementation had no significant effect on the 5-year incidence of CHD.
What Do These Findings Mean?
These analyses of unpublished datasets are consistent with lifelong moderate elevation of homocysteine levels having no significant effect on CHD risk. In other words, these findings indicate that circulating homocysteine levels within the normal range are not causally related to CHD risk. The meta-analysis of the randomized trials of folate supplementation also supports this conclusion. So why is there a discrepancy between these findings and those of meta-analyses of published Mendelian randomization studies? The discrepancy is too large to be dismissed as a chance finding, suggest the researchers, but could be the result of publication bias—some studies might have been prioritized for publication because of the positive nature of their results whereas the unpublished datasets used in this study would not have been affected by any failure to publish null results. Overall, these findings reveal a serious example of publication bias and argue against the use of folate supplements as a means of reducing CHD risk.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001177.
The American Heart Association provides information about CHD and tips on keeping the heart healthy; it also provides information on homocysteine, folic acid, and CHD, general information on supplements and heart health, and personal stories about CHD
The UK National Health Service Choices website provides information about CHD, including personal stories about CHD
Information is available from the British Heart Foundation on heart disease and keeping the heart healthy
The US National Heart Lung and Blood Institute also provides information on CHD (in English and Spanish)
MedlinePlus provides links to many other sources of information on CHD (in English and Spanish)
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001177
PMCID: PMC3283559  PMID: 22363213
22.  MI-GWAS: a SAS platform for the analysis of inherited and maternal genetic effects in genome-wide association studies using log-linear models 
BMC Bioinformatics  2011;12:117.
Background
Several platforms for the analysis of genome-wide association data are available. However, these platforms focus on the evaluation of the genotype inherited by affected (i.e. case) individuals, whereas for some conditions (e.g. birth defects) the genotype of the mothers of affected individuals may also contribute to risk. For such conditions, it is critical to evaluate associations with both the maternal and the inherited (i.e. case) genotype. When genotype data are available for case-parent triads, a likelihood-based approach using log-linear modeling can be used to assess both the maternal and inherited genotypes. However, available software packages for log-linear analyses are not well suited to the analysis of typical genome-wide association data (e.g. including missing data).
Results
An integrated platform, Maternal and Inherited Analyses for Genome-wide Association Studies (MI-GWAS) for log-linear analyses of maternal and inherited genetic effects in large, genome-wide datasets, is described. MI-GWAS uses SAS and LEM software in combination to appropriately format data, perform the log-linear analyses and summarize the results. This platform was evaluated using existing genome-wide data and was shown to perform accurately and relatively efficiently.
Conclusions
The MI-GWAS platform provides a valuable tool for the analysis of association of a phenotype or condition with maternal and inherited genotypes using genome-wide data from case-parent triads. The source code for this platform is freely available at http://www.sph.uth.tmc.edu/sbrr/mi-gwas.htm.
doi:10.1186/1471-2105-12-117
PMCID: PMC3110146  PMID: 21513519
23.  Using Cases and Parents to Study Multiplicative Gene-by-Environment Interaction 
American Journal of Epidemiology  2009;170(3):393-400.
With case-parent triads, one can estimate genotype relative risks by measuring the apparent overtransmission of susceptibility genotypes from parents to affected offspring. Results obtained using such designs, properly analyzed, resist both bias due to population structure and bias due to self-selection. Most diseases are not purely genetic, and environmental cofactors can also be important. In this paper, the authors describe how a polytomous logistic regression method previously developed for studying genetic effects on a quantitative trait can be used with case-parent data to study multiplicative gene-by-environment interaction. The idea is that if the joint effect of exposure and genotype on risk is submultiplicative or supermultiplicative, then, conditional on the parental genotypes, inheritance of a susceptibility genotype by affected offspring will appear to have been influenced by the offspring's exposure level. The authors' approach tolerates exposure-complicated genetic population structure, and simulations suggest power and Type I error rates comparable to those of competitors. With this approach, one can estimate the usual interaction parameters under a much less stringent assumption than gene-environment independence in the source population. Incompletely genotyped triads can contribute through an expectation-maximization algorithm. To illustrate, the authors consider polymorphisms in detoxification pathway genes and maternal smoking in relation to the birth defect oral cleft.
doi:10.1093/aje/kwp118
PMCID: PMC2733309  PMID: 19483188
case-control studies; epidemiologic methods; genetic epidemiology; genetic markers; genotype-environment interaction; logistic models
24.  Less is more, except when less is less: Studying joint effects 
Genomics  2008;93(1):10-12.
Most diseases are complex in that they are caused by the joint action of multiple factors, both genetic and environmental. Over the past few decades, the mathematical convenience of logistic regression has served to enshrine the multiplicative model, to the point where many epidemiologists believe that departure from additivity on a log scale implies that two factors interact in causing disease. Other terminology in epidemiology, where students are told that inequality of relative risks across levels of a second factor should be seen as “effect modification,” reinforces an uncritical acceptance of multiplicative joint effect as the biologically meaningful no-interaction null. Our first task, when studying joint effects, is to understand the limitations of our definitions for “interaction,” and recognize that what statisticians mean and what biologists might want to mean by interaction may not coincide.
Joint effects are notoriously hard to identify and characterize, even when asking a simple and unsatisfying question – like whether two effects are log-additive. The rule of thumb for such efforts is that a factor-of-four sample size is needed, compared to that needed to demonstrate main effects of either genes or exposures. So strategies have been devised that focus on the most informative individuals, either through risk-based sampling for a cohort, or case-control sampling, extreme phenotype sampling, pooling, two-stage sampling, exposed-only, or case-only designs. These designs gain efficiency, but at a cost of flexibility in models for joint effects.
A relatively new approach avoids population controls by genotyping case-parent triads. Because it requires parents, the method works best for diseases with onset early in life. With this design, the role of autosomal genetic variants is assessed by in effect treating the nontransmitted parental alleles as controls for affected offspring. Despite advantages for looking at genetic effects, the triad design faces limitations when examining joint effects of genetic and environmental factors. Because population-based controls are not included, main effects for exposures cannot be estimated, and consequently one only has access to inference related to a multiplicative null. We have proposed a hybrid approach, which offers the best features of both a case-parent and a case-control design. By genotyping parents of population-based controls and assuming Mendelian transmission, power is markedly enhanced. One can also estimate main effects for exposures and now flexibly assess models for joint effects.
doi:10.1016/j.ygeno.2008.06.002
PMCID: PMC2752945  PMID: 18598750
25.  Genetic polymorphisms in arginase I and II and childhood asthma and atopy 
Background
A recent microarray study implicated arginase I (ARG1) and arginase II (ARG2) in mouse allergic asthma models and human asthma.
Objectives
To examine the association between genetic variation in ARG1 and ARG2 and childhood asthma and atopy risk.
Methods
We enrolled 433 case-parent triads, consisting of asthmatics 4 to 17 years and their biologic parents, from the allergy clinic of a public hospital in Mexico City between 1998 and 2003. Atopy to 24 aeroallergens was determined by skin prick tests. We genotyped 4 single nucleotide polymorphisms (SNPs) of ARG1 and 4 SNPs of ARG2 with minor allele frequencies over 10% using the TaqMan assay.
Results
ARG1 SNPs and haplotypes were not associated with asthma but all four ARG1 SNPs were associated with the number of positive skin tests (P = 0.007 to 0.018). Carrying two copies of minor alleles for either of two highly associated ARG2 SNPs was associated with a statistically significant increased relative risk (RR) of asthma [1.5, 95% confidence interval (CI) 1.1–2.1 for arg2s1; RR = 1.6, 95% CI = 1.1–2.3 for arg2s2]. The association was slightly stronger among children with a smoking parent (arg2s1 RR = 2.1, 95% CI = 1.2 – 3.9 with a smoking parent; RR =1.2, 95% CI = 0.8–1.9 without, interaction P = 0.025). Haplotype analyses reduced the sample size but supported the single SNP results. One ARG2 SNP was related to the number of positive skin tests (P = 0.027).
Conclusions
Variation in arginase genes may contribute to asthma and atopy in children.
doi:10.1016/j.jaci.2005.09.026
PMCID: PMC1450009  PMID: 16387594
ARG1; ARG2; “genetic predisposition to disease”; SNP; “polymorphism; single nucleotide”; “respiratory hypersensitivity”; “skin tests”; asthma; “tobacco smoke pollution”; ARG1 = arginase I; ARG2 = arginase II; CI = confidence interval; D′ = Lewontin’s standardized disequilibrium coefficient; eNOS = endothelial nitric oxide synthase; IgE = immunoglobulin E; IL-13 = interleukin-13; IL-4 = interleukin-4; LD = linkage disequilibrium; NO = nitric oxide; NOS = nitric oxide synthase; r2 = squared correlation coefficient; RR = relative risk; SNP = single nucleotide polymorphism; STAT6 = signal transducer and activator of transcription 6; TDT = transmission disequilibrium test; Th2= T helper lymphocytes type 2

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