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Abstract Previous studies have shown cord-blood DNA methylation differences in newborns conceived using assisted reproductive technologies (ART) compared to those conceived naturally. However, whether these ART-related DNA methylation differences vary with children’s sex is unknown. We hypothesize that the DNA methylation differences in cord blood between ART-conceived and naturally conceived newborns also varies by the sex of the child, with distinct patterns of differential methylation present in males and females. We investigated sex differences in cord-blood DNA methylation variation according to conception by ART using the Illumina MethylationEPIC platform, comparing 456 ART-conceived versus 507 naturally-conceived girls, and 503 ART-conceived and 473 naturally-conceived boys. We identified 37 differentially methylated CpGs according to ART-conception among girls, and 70 differentially methylated CpGs according to ART-conception among boys, when we used a 1% false discovery rate to account for multiple testing. Ten CpGs were differentially methylated according to conception by ART in both sexes. Among the genes that were associated with these CpGs, we found the BRCA1; NBR2 gene (two CpGs) was hypermethylated in girls while the APC2 (two CpGs) and NECAB3;ACTL10, (four CpGs) related to cellular signaling were hypomethylated in boys. These findings confirm the presence of sex-specific epigenetic differences, illustrating the nuanced impact of ART on the fetal epigenome. There is a need for further explorations into the implications for sex-specific developmental trajectories and health outcomes in ART-conceived children.

Abstract Background DNA methylation (DNAm) is robustly associated with chronological age in children and adults, and gestational age (GA) in newborns. This property has enabled the development of several epigenetic clocks that can accurately predict chronological age and GA. However, the lack of overlap in predictive CpGs across different epigenetic clocks remains elusive. Our main aim was therefore to identify and characterize CpGs that are stably predictive of GA. Results We applied a statistical approach called ‘stability selection’ to DNAm data from 2138 newborns in the Norwegian Mother, Father, and Child Cohort study. Stability selection combines subsampling with variable selection to restrict the number of false discoveries in the set of selected variables. Twenty-four CpGs were identified as being stably predictive of GA. Intriguingly, only up to 10% of the CpGs in previous GA clocks were found to be stably selected. Based on these results, we used generalized additive model regression to develop a new GA clock consisting of only five CpGs, which showed a similar predictive performance as previous GA clocks (R 2 = 0.674, median absolute deviation = 4.4 days). These CpGs were in or near genes and regulatory regions involved in immune responses, metabolism, and developmental processes. Furthermore, accounting for nonlinear associations improved prediction performance in preterm newborns. Conclusion We present a methodological framework for feature selection that is broadly applicable to any trait that can be predicted from DNAm data. We demonstrate its utility by identifying CpGs that are highly predictive of GA and present a new and highly performant GA clock based on only five CpGs that is more amenable to a clinical setting.

Abstract Background Assisted reproductive technologies (ART) may perturb DNA methylation (DNAm) in early embryonic development. Although a handful of epigenome-wide association studies of ART have been published, none have investigated CpGs on the X chromosome. To bridge this knowledge gap, we leveraged one of the largest collections of mother–father–newborn trios of ART and non-ART (natural) conceptions to date to investigate sex-specific DNAm differences on the X chromosome. The discovery cohort consisted of 982 ART and 963 non-ART trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa). To verify our results from the MoBa cohort, we used an external cohort of 149 ART and 58 non-ART neonates from the Australian ‘Clinical review of the Health of adults conceived following Assisted Reproductive Technologies’ (CHART) study. The Illumina EPIC array was used to measure DNAm in both datasets. In the MoBa cohort, we performed a set of X-chromosome-wide association studies (‘XWASs’ hereafter) to search for sex-specific DNAm differences between ART and non-ART newborns. We tested several models to investigate the influence of various confounders, including parental DNAm. We also searched for differentially methylated regions (DMRs) and regions of co-methylation flanking the most significant CpGs. Additionally, we ran an analogous model to our main model on the external CHART dataset. Results In the MoBa cohort, we found more differentially methylated CpGs and DMRs in girls than boys. Most of the associations persisted after controlling for parental DNAm and other confounders. Many of the significant CpGs and DMRs were in gene-promoter regions, and several of the genes linked to these CpGs are expressed in tissues relevant for both ART and sex (testis, placenta, and fallopian tube). We found no support for parental DNAm-dependent features as an explanation for the observed associations in the newborns. The most significant CpG in the boys-only analysis was in UBE2DNL, which is expressed in testes but with unknown function. The most significant CpGs in the girls-only analysis were in EIF2S3 and AMOT. These three loci also displayed differential DNAm in the CHART cohort. Conclusions Genes that co-localized with the significant CpGs and DMRs associated with ART are implicated in several key biological processes (e.g., neurodevelopment) and disorders (e.g., intellectual disability and autism). These connections are particularly compelling in light of previous findings indicating that neurodevelopmental outcomes differ in ART-conceived children compared to those naturally conceived.

CpG sites associated with gestational age are predominantly found in nucleated red blood cells, which point to an epigenetic signature of erythropoiesis as being partly responsible for this association.

Background The Bergen Growth Study 2 (BGS2) aims to characterise somatic and endocrine changes in healthy Norwegian children using a novel methodology. Subjects and methods A cross-sectional sample of 1285 children aged 6–16 years was examined in 2016 using novel objective ultrasound assessments of breast developmental stages and testicular volume in addition to the traditional Tanner pubertal stages. Blood samples allowed for measurements of pubertal hormones, endocrine disruptive chemicals, and genetic analyses. Results Ultrasound staging of breast development in girls showed a high degree of agreement within and between observers, and ultrasound measurement of testicular volume in boys also showed small intra- and interobserver differences. The median age was 10.4 years for Tanner B2 (pubertal onset) and 12.7 years for menarche. Norwegian boys reached a pubertal testicular volume at a mean age of 11.7 years. Continuous reference curves for testicular volume and sex hormones were constructed using the LMS method. Conclusions Ultrasound-based assessments of puberty provided novel references for breast developmental stages and enabled the measurement of testicular volume on a continuous scale. Endocrine z-scores allowed for an intuitive interpretation of changing hormonal levels during puberty on a quantitative scale, which, in turn, provides opportunities for further analysis of pubertal development using machine-learning approaches.

Abstract Although substantial progress has been made in managing COVID-19, it is still difficult to predict a patient’s prognosis. We explored the epigenetic signatures of COVID-19 in peripheral blood using data from an ongoing prospective observational study of COVID-19 called the Norwegian Corona Cohort Study. A series of EWASs were performed to compare the DNA methylation profiles between COVID-19 cases and controls three months post-infection. We also investigated differences associated with severity and long-COVID. Three CpGs—cg22399236, cg03607951, and cg09829636—were significantly hypomethylated (FDR

Abstract Background We combined an unsupervised learning methodology for analyzing mitogenome sequences with maximum likelihood (ML) phylogenetics to make detailed inferences about the evolution and diversification of mitochondrial DNA (mtDNA) haplogroup U5, which appears at high frequencies in northern Europe. Methods Haplogroup U5 mitogenome sequences were gathered from GenBank. The hierarchal Bayesian Analysis of Population Structure (hierBAPS) method was used to generate groups of sequences that were then projected onto a rooted maximum likelihood (ML) phylogenetic tree to visualize the pattern of clustering. The haplogroup statuses of the individual sequences were assessed using Haplogrep2. Results A total of 23 hierBAPS groups were identified, all of which corresponded to subclades defined in Phylotree, v.17. The hierBAPS groups projected onto the ML phylogeny accurately clustered all haplotypes belonging to a specific haplogroup in accordance with Haplogrep2. By incorporating the geographic source of each sequence and subclade age estimates into this framework, inferences about the diversification of U5 mtDNAs were made. Haplogroup U5 has been present in northern Europe since the Mesolithic, and spread in both eastern and western directions, undergoing significant diversification within Scandinavia. A review of historical and archeological evidence attests to some of the population interactions contributing to this pattern. Conclusions The hierBAPS algorithm accurately grouped mitogenome sequences into subclades in a phylogenetically robust manner. This analysis provided new insights into the phylogeographic structure of haplogroup U5 diversity in northern Europe, revealing a detailed perspective on the diversity of subclades in this region and their distribution in Scandinavian populations.

Timing of assisted reproduction technology (ART) procedures coincides with extensive epigenetic remodeling early after conception. Here the authors identify 176 DNA methylation differences in cord blood of newborns conceived with ART. including genes related to growth, neurodevelopment, and cancer.

Abstract Background Traditional methods for single-variant genome-wide association study (GWAS) incur a substantial multiple-testing burden because of the need to test for associations with a vast number of single-nucleotide polymorphisms (SNPs) simultaneously. Further, by ignoring more complex joint effects of nearby SNPs within a given region, these methods fail to consider the genomic context of an association with the outcome. Results To address these shortcomings, we present a more powerful method for GWAS, coined ‘Wavelet Screening’ (WS), that greatly reduces the number of tests to be performed. This is achieved through the use of a sliding-window approach based on wavelets to sequentially screen the entire genome for associations. Wavelets are oscillatory functions that are useful for analyzing the local frequency and time behavior of signals. The signals can then be divided into different scale components and analyzed separately. In the current setting, we consider a sequence of SNPs as a genetic signal, and for each screened region, we transform the genetic signal into the wavelet space. The null and alternative hypotheses are modeled using the posterior distribution of the wavelet coefficients. WS is enhanced by using additional information from the regression coefficients and by taking advantage of the pyramidal structure of wavelets. When faced with more complex genetic signals than single-SNP associations, we show via simulations that WS provides a substantial gain in power compared to both the traditional GWAS modeling and another popular regional association test called SNP-set (Sequence) Kernel Association Test (SKAT). To demonstrate feasibility, we applied WS to a large Norwegian cohort (N=8006) with genotypes and information available on gestational duration. Conclusions WS is a powerful and versatile approach to analyzing whole-genome data and lends itself easily to investigating various omics data types. Given its broader focus on the genomic context of an association, WS may provide additional insight into trait etiology by revealing genes and loci that might have been missed by previous efforts.

Bias from weak instruments may undermine the ability to estimate causal effects in instrumental variable regression (IVR). We present here a new approach to handling weak instrument bias through the application of a new type of instrumental variable coined 'Cross-Fitted Instrument' (CFI). CFI splits the data at random and estimates the impact of the instrument on the exposure in each partition. These estimates are then used to perform an IVR on each partition. We adapt CFI to the Mendelian randomization (MR) setting and term this adaptation 'Cross-Fitting for Mendelian Randomization' (CFMR). We show that, even when using weak instruments, CFMR is, at worst, biased towards the null, which makes it a conservative one-sample MR approach. In particular, CFMR remains conservative even when the two samples used to perform the MR analysis completely overlap, whereas current state-of-the-art approaches (e.g., MR RAPS) display substantial bias in this setting. Another major advantage of CFMR lies in its use of all of the available data to select genetic instruments, which maximizes statistical power, as opposed to traditional two-sample MR where only part of the data is used to select the instrument. Consequently, CFMR is able to enhance statistical power in consortia-led meta-analyses by enabling a conservative one-sample MR to be performed in each cohort prior to a meta-analysis of the results across all the cohorts. In addition, CFMR enables a cross-ethnic MR analysis by accounting for ethnic heterogeneity, which is particularly important in meta-analyses where the participating cohorts may have different ethnicities. To our knowledge, none of the current MR approaches can account for such heterogeneity. Finally, CFMR enables the application of MR to exposures that are either rare or difficult to measure, which would normally preclude their analysis in the regular two-sample MR setting.

Abstract Background Birth weight (BW) is one of the most widely studied anthropometric traits in humans because of its role in various adult-onset diseases. The number of loci associated with BW has increased dramatically since the advent of whole-genome screening approaches such as genome-wide association studies (GWASes) and meta-analyses of GWASes (GWAMAs). To further contribute to elucidating the genetic architecture of BW, we analyzed a genotyped Norwegian dataset with information on child’s BW (N=9,063) using a slightly modified version of a wavelet-based method by Shim and Stephens (2015) called WaveQTL. Results WaveQTL uses wavelet regression for regional testing and offers a more flexible functional modeling framework compared to conventional GWAS methods. To further improve WaveQTL, we added a novel feature termed “zooming strategy” to enhance the detection of associations in typically small regions. The modified WaveQTL replicated five out of the 133 loci previously identified by the largest GWAMA of BW to date by Warrington et al. (2019), even though our sample size was 26 times smaller than that study and 18 times smaller than the second largest GWAMA of BW by Horikoshi et al. (2016). In addition, the modified WaveQTL performed better in regions of high LD between SNPs. Conclusions This study is the first adaptation of the original WaveQTL method to the analysis of genome-wide genotypic data. Our results highlight the utility of the modified WaveQTL as a complementary tool for identifying loci that might escape detection by conventional genome-wide screening methods due to power issues. An attractive application of the modified WaveQTL would be to select traits from various public GWAS repositories to investigate whether they might benefit from a second analysis.

Abstract Background We present here a computational shortcut to improve a powerful wavelet-based method by Shim and Stephens (Ann Appl Stat 9(2):665–686, 2015. https://doi.org/10.1214/14-AOAS776 ) called WaveQTL that was originally designed to identify DNase I hypersensitivity quantitative trait loci (dsQTL). Results WaveQTL relies on permutations to evaluate the significance of an association. We applied a recent method by Zhou and Guan (J Am Stat Assoc 113(523):1362–1371, 2017. https://doi.org/10.1080/01621459.2017.1328361 ) to boost computational speed, which involves calculating the distribution of Bayes factors and estimating the significance of an association by simulations rather than permutations. We called this simulation-based approach “fast functional wavelet” (FFW), and tested it on a publicly available DNA methylation (DNAm) dataset on colorectal cancer. The simulations confirmed a substantial gain in computational speed compared to the permutation-based approach in WaveQTL. Furthermore, we show that FFW controls the type I error satisfactorily and has good power for detecting differentially methylated regions. Conclusions Our approach has broad utility and can be applied to detect associations between different types of functions and phenotypes. As more and more DNAm datasets are being made available through public repositories, an attractive application of FFW would be to re-analyze these data and identify associations that might have been missed by previous efforts. The full R package for FFW is freely available at GitHub https://github.com/william-denault/ffw .

Abstract Background Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age. Results We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set. Conclusions Our ABECs predicted adults’ chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.

Male sex and advanced age are associated with severe symptoms of COVID-19. Sex and age also exhibit substantial associations with genome-wide DNA methylation (DNAm) differences in humans. Using a random sample of Illumina EPIC-based genome-wide methylomes from peripheral whole blood of 1,976 parents, participating in The Norwegian Mother, Father and Child Cohort Study (MoBa), we explored whether DNAm in genes linked to SARS-CoV-2 host cell entry and to severe COVID-19 were associated with sex and age. This was carried out by testing 1,572 DNAm sites (CpGs) located near 45 genes for associations with age and sex. We found that DNAm in 281 and 231 of 1,572 CpGs were associated (pFDR

Abstract Background Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or sample size is an important first step in the planning of any scientific study, there is currently a lack of software for genetic power calculations in family-based study designs. Here, we address this shortcoming through new implementations of power calculations in the R package Haplin, which is a flexible and robust software for genetic epidemiological analyses. Power calculations in Haplin can be performed analytically using the asymptotic variance-covariance structure of the parameter estimator, or else by a straightforward simulation approach. Haplin performs power calculations for child, parent-of-origin and maternal effects, as well as for gene-environment interactions. The power can be calculated for both single SNPs and haplotypes, either autosomal or X-linked. Moreover, Haplin enables power calculations for different child-parent configurations, including (but not limited to) case-parent triads, case-mother dyads, and case-parent triads in combination with unrelated control-parent triads. Results We compared the asymptotic power approximations to the power of analysis attained with Haplin. For external validation, the results were further compared to the power of analysis attained by the EMIM software using data simulations from Haplin. Consistency observed between Haplin and EMIM across various genetic scenarios confirms the computational accuracy of the inference methods used in both programs. The results also demonstrate that power calculations in Haplin are applicable to genetic association studies using either log-linear or multinomial modeling approaches. Conclusions Haplin provides a robust and reliable framework for power calculations in genetic association analyses for a wide range of genetic effects and etiologic scenarios, based on genotype data from a variety of child-parent configurations.

A Correction to this paper has been published: https://doi.org/10.1186/s12859-021-03979-y

Background: Although both genetic and environmental factors have been reported to influence the risk of isolated cleft lip with or without cleft palate (CL/P), the exact mechanisms behind CL/P are still largely unaccounted for. We recently developed new methods to identify parent-of-origin (PoO) interactions with environmental exposures (PoOxE) and now apply them to data from a genome-wide association study (GWAS) of families with children born with isolated CL/P. Methods: Genotypes from 1594 complete triads and 314 dyads (1908 nuclear families in total) with CL/P were available for the current analyses. Of these families, 1024 were Asian, 825 were European and 59 had other ancestries. After quality control, 341,191 SNPs remained from the original 569,244. The exposures were maternal cigarette smoking, use of alcohol, and use of vitamin supplements in the periconceptional period. Our new methodology detects if PoO effects are different across environmental strata and is implemented in the R-package Haplin. Results: Among Europeans, there was evidence of a PoOxSmoke effect for ANK3 with three SNPs (rs3793861, q=0.20, p=2.6e-6; rs7087489, q=0.20, p=3.1e-6; rs4310561, q=0.67, p=4.0e-5) and a PoOxAlcohol effect for ARHGEF10 with two SNPs (rs2294035, q=0.32, p=2.9e-6; rs4876274, q=0.76, p=1.3e-5). Conclusion: Our results indicate that the detected PoOxE effects have a plausible biological basis, and thus warrant replication in other independent cleft samples. Our demonstration of the feasibility of identifying complex interactions between relevant environmental exposures and PoO effects offers new avenues for future research aimed at unravelling the complex etiology of cleft lip defects.

Background: It is widely accepted that cleft lip with or without cleft palate (CL/P) results from the complex interplay between multiple genetic and environmental factors. However, a robust investigation of these gene-environment (GxE) interactions at a genome-wide level is still lacking for isolated CL/P.Materials and Methods: We used our R-package Haplin to perform a genome-wide search for GxE effects in isolated CL/P. From a previously published GWAS, genotypes and information on maternal periconceptional cigarette smoking, alcohol intake, and vitamin use were available on 1908 isolated CL/P triads of predominantly European or Asian ancestry. A GxE effect is present if the relative risk estimates for gene-effects in the offspring are different across exposure strata. We tested this using the relative risk ratio (RRR). Besides analyzing all ethnicities combined (“pooled analysis”), separate analyses were conducted on Europeans and Asians to investigate ethnicity-specific effects. To control for multiple testing, q-values were calculated from the p-values.Results: We identified significant GxVitamin interactions with three SNPs in “Estrogen-related receptor gamma” (ESRRG) in the pooled analysis. The RRRs (95% confidence intervals) were 0.56 (0.45–0.69) with rs1339221 (q = 0.011), 0.57 (0.46–0.70) with rs11117745 (q = 0.011), and 0.62 (0.50–0.76) with rs2099557 (q = 0.037). The associations were stronger when these SNPs were analyzed as haplotypes composed of two-SNP and three-SNP combinations. The strongest effect was with the “t-t-t” haplotype of the rs1339221-rs11117745-rs2099557 combination [RRR = 0.50 (0.40–0.64)], suggesting that the effects observed with the other SNP combinations, including those in the single-SNP analyses, were mainly driven by this haplotype. Although there were potential GxVitamin effects with rs17734557 and rs1316471 and GxAlcohol effects with rs9653456 and rs921876 in the European sample, respectively, none of the SNPs was located in or near genes with strong links to orofacial clefts. GxAlcohol and GxSmoke effects were not assessed in the Asian sample because of a lack of observations for these exposures.Discussion/Conclusion: We identified significant interactions between vitamin use and variants in ESRRG in the pooled analysis. These GxE effects are novel and warrant further investigations to elucidate their roles in orofacial clefting. If validated, they could provide prospects for exploring the impact of estrogens and vitamins on clefting, with potential translational applications.

Background: Although both the mother's and father's alleles are present in the offspring, they may not operate at the same level. These parent-of-origin (PoO) effects have not yet been explored on the X chromosome, which motivated us to develop new methods for detecting such effects. Orofacial clefts (OFCs) exhibit sex-specific differences in prevalence and are examples of traits where a search for various types of effects on the X chromosome might be relevant.Materials and Methods: We upgraded our R-package Haplin to enable genome-wide analyses of PoO effects, as well as power simulations for different statistical models. 14,486 X-chromosome SNPs in 1,291 Asian and 1,118 European case-parent triads of isolated OFCs were available from a previous GWAS. For each ethnicity, cleft lip with or without cleft palate (CL/P) and cleft palate only (CPO) were analyzed separately using two X-inactivation models and a sliding-window approach to haplotype analysis. In addition, we performed analyses restricted to female offspring.Results: Associations were identified in “Dystrophin” (DMD, Xp21.2-p21.1), “Fibroblast growth factor 13” (FGF13, Xq26.3-q27.1) and “EGF-like domain multiple 6” (EGFL6, Xp22.2), with biologically plausible links to OFCs. Unlike EGFL6, the other associations on chromosomal region Xp22.2 had no apparent connections to OFCs. However, the Xp22.2 region itself is of potential interest because it contains genes for clefting syndromes [for example, “Oral-facial-digital syndrome 1” (OFD1) and “Midline 1” (MID1)]. Overall, the identified associations were highly specific for ethnicity, cleft subtype and X-inactivation model, except for DMD in which associations were identified in both CPO and CL/P, in the model with X-inactivation and in Europeans only.Discussion/Conclusion: The specificity of the associations for ethnicity, cleft subtype and X-inactivation model underscores the utility of conducting subanalyses, despite the ensuing need to adjust for additional multiple testing. Further investigations are needed to confirm the associations with DMD, EGF16, and FGF13. Furthermore, chromosomal region Xp22.2 appears to be a hotspot for genes implicated in clefting syndromes and thus constitutes an exciting direction to pursue in future OFCs research. More generally, the new methods presented here are readily adaptable to the study of X-linked PoO effects in other outcomes that use a family-based design.

Cleft palate only is a common birth defect with high heritability. Only a small fraction of this heritability is explained by the genetic variants identified so far, underscoring the need to investigate other disease mechanisms, such as gene-environment (GxE) interactions and parent-of-origin (PoO) effects. Furthermore, PoO effects may vary across exposure levels (PoOxE effects). Such variation is the focus of this study. We upgraded the R-package Haplin to enable direct tests of PoOxE effects at the genome-wide level. From a previous GWAS, we had genotypes for 550 case-parent trios, of mainly European and Asian ancestry, and data on three maternal exposures (smoking, alcohol, and vitamins). Data were analyzed for Europeans and Asians separately, and also for all ethnicities combined. To account for multiple testing, a false discovery rate method was used, where q-values were generated from the p-values. In the Europeans-only analyses, interactions with maternal smoking yielded the lowest q-values. Two SNPs in the 'Interactor of little elongation complex ELL subunit 1' (ICE1) gene had a q-value of 0.14, and five of the 20 most significant SNPs were in the 'N-acetylated alpha-linked acidic dipeptidase-like 2' (NAALADL2) gene. No evidence of PoOxE effects was found in the other analyses. The connections to ICE1 and NAALADL2 are novel and warrant further investigation. More generally, the new methodology presented here is easily applicable to other traits and exposures in which a family-based study design has been implemented.

BACKGROUND:GWAS discoveries on the X-chromosome are underrepresented in the literature primarily because the analytical tools that have been applied were originally designed for autosomal markers. Our objective here is to employ a new robust and flexible tool for chromosome-wide analysis of X-linked markers in complex traits. Orofacial clefts are good candidates for such analysis because of the consistently observed excess of females with cleft palate only (CPO) and excess of males with cleft lip with or without cleft palate (CL/P). METHODS:Genotypes for 14,486 X-chromosome SNPs in 1,291 Asian and 1,118 European isolated cleft triads were available from a previously published GWAS. The R-package HAPLIN enables genome-wide-level analyses as well as statistical power simulations for a range of biologic scenarios. We analyzed isolated CL/P and isolated CPO for each ethnicity in HAPLIN, using a sliding-window approach to haplotype analysis and two different statistical models, with and without X-inactivation in females. RESULTS:There was a larger number of associations in the Asian versus the European sample, and similar to previous reports that have analyzed the same GWAS dataset using different methods, we identified associations with EFNB1/PJA1 and DMD. In addition, new associations were detected with several other genes, among which KLHL4, TBX22, CPXCR1 and BCOR were noteworthy because of their roles in clefting syndromes. A few of the associations were only detected by one particular X-inactivation model, whereas a few others were only detected in one sex. DISCUSSION/CONCLUSION:We found new support for the involvement of X-linked variants in isolated clefts. The associations were specific for ethnicity, sex and model parameterization, highlighting the need for flexible tools that are capable of detecting and estimating such effects. Further efforts are needed to verify and elucidate the potential roles of EFNB1/PJA1, KLHL4, TBX22, CPXCR1 and BCOR in isolated clefts.

A compelling literature substantiates that our social worlds have significant and far-reaching effects on health and well-being throughout life. Yet, few studies of social factors and their effects on health have been embedded within the twin design. Towards this end, we have initiated a new twin study on social factors and health which will investigate the genetic and environmental influences on social environments, and explore how social environments mediate these influences on physical and mental health. Herein, we describe the study sample, response rates and measures. Twins born 1935-1960 were invited to complete a questionnaire and these data were supplemented with information on cardiovascular disease and cancer through linkage to national health registries. Among the 10655 twins who were contacted, responses were received from 5446 individuals (1989 pairs and 1468 single responders). The subsample of pairs where both twins responded includes 1004 identical (MZ) pairs and 985 fraternal (DZ) pairs. The overall individual and pairwise response rates were 51% and 37%, respectively. The average age is 61.54 years, 56.1% of the responders are female and 46.1% are identical twins. MZ twins were more likely to participate than DZ twins. Sex and age effects were statistically significant for many of the psychosocial measures and for measures of support and strain in the social network. There were no differences in the social networks between twins in pairs where both twins responded and twins in pairs where only one twin responded.

Recent epidemiological studies suggest that the maternal genome is an important contributor to spontaneous preterm delivery (PTD). There is also a significant excess of males among preterm born infants, which may imply an X-linked mode of inheritance for a subset of cases. To explore this, we examined the effect of maternal and fetal X-chromosomal single nucleotide polymorphisms (SNPs) on the risk of PTD in two independent genome-wide association studies and one replication study.Participants were recruited from the Danish National Birth Cohort and the Norwegian Mother and Child cohort studies. Data from these two populations were first analyzed independently, and then combined in a meta-analysis. Overall, we evaluated 12,211 SNPs in 1,535 case-mother dyads and 1,487 control-mother dyads. Analyses were done using a hybrid design that combines case-mother dyads and control-mother dyads, as implemented in the Haplin statistical software package. A sex-stratified analysis was performed for the fetal SNPs. In the replication study, 10 maternal and 16 fetal SNPs were analyzed using case-parent triads from independent studies of PTD in the United States, Argentina and Denmark.In the meta-analysis, the G allele at the maternal SNP rs2747022 in the FERM domain containing 7 gene (FRMD7) increased the risk of spontaneous PTD by 1.2 (95% confidence interval (CI): 1.1, 1.4). Although an association with this SNP was confirmed in the replication study, it was no longer statistically significant after a Bonferroni correction for multiple testing.We did not find strong evidence in our data to implicate X-chromosomal SNPs in the etiology of spontaneous PTD. Although non-significant after correction for multiple testing, the mother's G allele at rs2747022 in FRMD7 increased the risk of spontaneous PTD across all populations in this study, thus warranting further investigation in other populations.

Orofacial clefts are common birth defects of complex etiology, with an excess of males among babies with cleft lip and palate, and an excess of females among those with cleft palate only. Although genes on the X chromosome have been implicated in clefting, there has been no association analysis of X-linked markers.We added new functionalities in the HAPLIN statistical software to enable association analysis of X-linked markers and an exploration of various causal scenarios relevant to orofacial clefts. Genotypes for 48 SNPs in 18 candidate genes on the X chromosome were analyzed in two population-based samples from Scandinavia (562 Norwegian and 235 Danish case-parent triads). For haplotype analysis, we used a sliding-window approach and assessed isolated cleft lip with or without cleft palate (iCL/P) separately from isolated cleft palate only (iCPO). We tested three statistical models in HAPLIN, allowing for: i) the same relative risk in males and females, ii) sex-specific relative risks, and iii) X-inactivation in females. We found weak but consistent associations with the oral-facial-digital syndrome 1 (OFD1) gene (formerly known as CXORF5) in the Danish iCL/P samples across all models, but not in the Norwegian iCL/P samples. In sex-specific analyses, the association with OFD1 was in male cases only. No analyses showed associations with iCPO in either the Norwegian or the Danish sample.The association of OFD1 with iCL/P is plausible given the biological relevance of this gene. However, the lack of replication in the Norwegian samples highlights the need to verify these preliminary findings in other large datasets. More generally, the novel analytic methods presented here are widely applicable to investigations of the role of X-linked genes in complex traits.

BackgroundFetal conditions can in principle be affected by the mother's genotype working through the prenatal environment.Methodology/principal findingsGenotypes for 1536 SNPs in 357 cleft candidate genes were available from a previous analysis in which we focused on fetal gene effects. 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/significanceExcept 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.

BackgroundFacial 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 findingsWe 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/significanceStrong 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.