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Determining if specific cell type(s) are responsible for an association between DNA methylation (DNAm) and a given phenotype is important for understanding the biological mechanisms underlying the association. Our EWAS of gestational age (GA) in 953 newborns from the Norwegian MoBa study identified 13,660 CpGs significantly associated with GA (pBonferroni

Background: Mitochondrial DNA haplogroup J is the third most frequent haplogroup in modern-day Scandinavia, although it did not originate there. To infer the genetic history of haplogroup J in Scandinavia, we examined worldwide mitogenome sequences using a maximum-likelihood phylogenetic approach. Methods: Haplogroup J mitogenome sequences were gathered from GenBank (n = 2245) and aligned against the ancestral Reconstructed Sapiens Reference Sequence. We also analyzed haplogroup J Viking Age sequences from the European Nucleotide Archive (n = 54). Genetic distances were estimated from these data and projected onto a maximum likelihood rooted phylogenetic tree to analyze clustering and branching dates. Results: Haplogroup J originated approximately 42.6 kya (95% CI: 30.0–64.7), with several of its earliest branches being found within the Arabian Peninsula and Northern Africa. J1b was found most frequently in the Near East and Arabian Peninsula, while J1c occurred most frequently in Europe. Based on phylogenetic dating, subhaplogroup J1c has its early roots in the Mediterranean and Western Balkans. Otherwise, the majority of the branches found in Scandinavia are younger than those seen elsewhere, indicating that haplogroup J dispersed relatively recently into Northern Europe, most plausibly with Neolithic farmers. Conclusions: Haplogroup J appeared when Scandinavia was transitioning to agriculture over 6 kya, with J1c being the most common lineage there today. Changes in the distribution of haplogroup J mtDNAs were likely driven by the expansion of farming from West Asia into Southern Europe, followed by a later expansion into Scandinavia, with other J subhaplogroups appearing among Scandinavian groups as early as the Viking Age. publishedVersion

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.

Objectives: Earlier studies suggest that being married in later life protects against dementia, and that being single in old age increases the risk of dementia. In this study, we examine midlife marital status trajectories and their association with dementia and mild cognitive impairment (MCI) at ages 70 plus using a large population based sample from Norway. Methods: Based on a general population sample linked to population registries ( N = 8706), we used multinomial logistic regression to examine the associations between six types of marital trajectories (unmarried, continuously divorced, intermittently divorced, widowed, continuously married, intermittently married) between age 44 and 68 years from national registries and a clinical dementia or a MCI diagnosis after age 70. We estimated relative risk ratios (RRR) and used mediation analyses adjusting for education, number of children, smoking, hypertension, obesity, physical inactivity, diabetes, mental distress, and having no close friends in midlife. Inverse probability weighting and multiple imputations were applied. The population attributable fraction was estimated to assess the potential reduction in dementia cases due to marital histories. Results: Overall, 11.6% of the participants were diagnosed with dementia and 35.3% with MCI. Dementia prevalence was lowest among the continuously married (11.2%). Adjusting for confounders, the risk of dementia was higher for the unmarried (RRR = 1.73; 95% CI: 1.24, 2.40), continuously divorced (RRR = 1.66; 95% CI: 1.14, 2.43), and intermittently divorced (RRR = 1.50; 95% CI: 1.09, 2.06) compared to the continuously married. In general, marital trajectory was less associated with MCI than with dementia. In the counterfactual scenario, where all participants had the same risk of receiving a dementia diagnosis as the continuously married group, there would be 6.0% fewer dementia cases. Discussion: Our data confirm that staying married in midlife is associated with a lower risk of dementia and that divorced people account for a substantial share of dementia cases.

BackgroundAssisted 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 DNAm differences on the X chromosome.Materials and MethodsThe discovery cohort consisted of 982 ART and 963 non-ART trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa). The replication cohort consisted 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 DNA methylation (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. For replication purposes, we ran an analogous model to our main model on the CHART dataset.Results and conclusionsIn the MoBa cohort, we found more differentially methylated CpGs and DMRs in girls than boys. Most of the associations persisted even 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 infertility as an explanation for the observed associations in the newborns. The most significant CpG in the boys-only analysis was inUBE2DNL, which is expressed in testes but with unknown function. The most significant CpGs in the girls-only analysis were inEIF2S3andAMOT. These three loci also displayed differential DNAm in the CHART cohort. Overall, genes that co-localized with the significant CpGs and DMRs 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 naturally-conceived.

Background: While well known for its Viking past, Norway's population history and the influences that have shaped its genetic diversity are less well understood. This is particularly true with respect to its demography, migration patterns, and dialectal regions, despite there being curated historical records for the past several centuries. In this study, we undertook an analysis of mitochondrial DNA (mtDNA) diversity within the country to elaborate this history from a matrilineal genetic perspective. Methods: We aggregated 1174 partial modern Norwegian mtDNA sequences from the published literature and subjected them to detailed statistical and phylogenetic analysis by dialectal regions and localities. We further contextualized the matrilineal ancestry of modern Norwegians with data from Mesolithic, Iron Age, and historic period populations. Results: Modern Norwegian mtDNAs fell into eight West Eurasian (N, HV, JT, I, U, K, X, W), five East Eurasian (A, F, G, N11, Z), and one African (L2) haplogroups. Pairwise analysis of molecular variance (AMOVA) estimates for all Norwegians indicated they were differentiated from each other at 1.68% (p

Children born after assisted reproductive technologies (ART) differ in birthweight from those naturally conceived. It has been hypothesized that this might be explained by epigenetic mechanisms. We examined whether cord blood DNA methylation mediated the birthweight difference between 890 newborns conceived by ART (764 by fresh embryo transfer and 126 frozen thawed embryo transfer) and 983 naturally conceived newborns from the Norwegian Mother, Father, and Child Cohort Study (MoBa). DNA methylation was measured by the Illumina Infinium MethylationEPIC array. We conducted mediation analyses to assess whether differentially methylated CpGs mediated the differences in birthweight observed between: (1) fresh embryo transfer and natural conception and (2) frozen and fresh embryo transfer.We observed a difference in birthweight between fresh embryo transfer and naturally conceived offspring of - 120 g. 44% (95% confidence interval [CI] 26% to 81%) of this difference in birthweight between fresh embryo transfer and naturally conceived offspring was explained by differences in methylation levels at four CpGs near LOXL1, CDH20, and DRC1. DNA methylation differences at two CpGs near PTGS1 and RASGRP4 jointly mediated 22% (95% CI 8.1% to 50.3%) of the birthweight differences between fresh and frozen embryo transfer.Our findings suggest that DNA methylation is an important mechanism in explaining birthweight differences according to the mode of conception. Further research should examine how gene regulation at these loci influences fetal growth.

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 IFI44L which is involved in innate response to viral infection and several systemic autoimmune diseases. cg09829636 is located in ANKRD9, a gene implicated in a wide variety of cellular processes, including the degradation of IMPDH2. The link between ANKRD9 and IMPDH2 is striking given that IMPDHs are considered therapeutic targets for COVID-19. Furthermore, gene ontology analyses revealed pathways involved in response to viruses. The lack of significant differences associated with severity and long-COVID may be real or reflect limitations in sample size. Our findings support the involvement of interferon responsive genes in the pathophysiology of COVID-19 and indicate a possible link to systemic autoimmune diseases.

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.

Assisted reproductive technology (ART) may affect fetal development through epigenetic mechanisms as the timing of ART procedures coincides with the extensive epigenetic remodeling occurring between fertilization and embryo implantation. However, it is unknown to what extent ART procedures alter the fetal epigenome. Underlying parental characteristics and subfertility may also play a role. Here we identify differences in cord blood DNA methylation, measured using the Illumina EPIC platform, between 962 ART conceived and 983 naturally conceived singleton newborns. We show that ART conceived newborns display widespread differences in DNA methylation, and overall less methylation across the genome. There were 607 genome-wide differentially methylated CpGs. We find differences in 176 known genes, including genes related to growth, neurodevelopment, and other health outcomes that have been associated with ART. Both fresh and frozen embryo transfer show DNA methylation differences. Associations persist after controlling for parents’ DNA methylation, and are not explained by parental subfertility.

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 (pFDRACE2 receptor gene (located on the X-chromosome), which was only associated with sex (pFDR2 = 0.77, p = 0.09) than the CpGs sampled from random genomic regions; age was actually found to be significantly less so (R2 = 0.36, p = 0.04). Hence, while we found wide-spread associations between sex and age at CpGs linked to genes implicated with SARS-CoV-2 host cell entry and severe COVID-19, the effect from the sum of these CpGs was not stronger than that from randomly sampled CpGs; for age it was significantly less so. These findings could suggest that advanced age and male sex may not be unsurmountable barriers for the SARS-CoV-2 virus to evolve increased infectiousness.

Background Children born after assisted reproductive technologies (ART) differ in birthweight from those naturally conceived. It has been hypothesized that this might be explained by epigenetic mechanisms. We examined whether cord blood DNA methylation mediated the birthweight difference between 890 newborns conceived by ART (764 by fresh embryo transfer and 126 frozen thawed embryo transfer) and 983 naturally conceived newborns from the Norwegian Mother, Father, and Child Cohort Study (MoBa). DNA methylation was measured by the Illumina Infinium MethylationEPIC array. We conducted mediation analyses to assess whether differentially methylated CpGs mediated the differences in birthweight observed between: (1) fresh embryo transfer and natural conception and (2) frozen and fresh embryo transfer. Results We observed a difference in birthweight between fresh embryo transfer and naturally conceived offspring of − 120 g. 44% (95% confidence interval [CI] 26% to 81%) of this difference in birthweight between fresh embryo transfer and naturally conceived offspring was explained by differences in methylation levels at four CpGs near LOXL1, CDH20, and DRC1. DNA methylation differences at two CpGs near PTGS1 and RASGRP4 jointly mediated 22% (95% CI 8.1% to 50.3%) of the birthweight differences between fresh and frozen embryo transfer. Conclusion Our findings suggest that DNA methylation is an important mechanism in explaining birthweight differences according to the mode of conception. Further research should examine how gene regulation at these loci influences fetal growth.

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.

International audience; We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

Assisted reproductive technology (ART) may affect fetal development through epigenetic mechanisms as the timing of ART procedures coincides with the extensive epigenetic remodeling occurring between fertilization and embryo implantation. However, it is unknown to what extent ART procedures alter the fetal epigenome. Underlying parental characteristics and subfertility may also play a role. Here we identify differences in cord blood DNA methylation, measured using the Illumina EPIC platform, between 962 ART conceived and 983 naturally conceived singleton newborns. We show that ART conceived newborns display widespread differences in DNA methylation, and overall less methylation across the genome. There were 607 genome-wide differentially methylated CpGs. We find differences in 176 known genes, including genes related to growth, neurodevelopment, and other health outcomes that have been associated with ART. Both fresh and frozen embryo transfer show DNA methylation differences. Associations persist after controlling for parents' DNA methylation, and are not explained by parental subfertility.

SummaryBias from weak instruments may undermine the ability to estimate causal effects in instrumental variable regression (IVR). We present here a simple solution for handling weak instrument bias by introducing a new type of instrumental variable called ‘cross-fitted instrument’ (CFI). CFI splits the data at random and estimates the impact of the instrument on the exposure in each partition. The estimates are then used to perform an IVR on each partition. We adapt CFI to Mendelian randomization (MR) and term this adaptation ‘Cross-Fitting for Mendelian Randomization’ (CFMR). A major advantage of CFMR is its use of all the available data to select genetic instruments, as opposed to traditional two-sample MR where a large part of the data is only used for instrument selection. Consequently, CFMR has the potential to enhance the power of MR in a meta-analysis setting by enabling an unbiased one-sample MR to be performed in each cohort prior to meta-analyzing the results across all the cohorts. In a similar fashion, CFMR enables a cross-ethnic MR analysis by accounting for ethnic heterogeneity, which is particularly important in consortia-led meta-analyses where the participating cohorts might be of different ethnicities. To our knowledge, there are currently no MR approach that can account for such heterogeneity. Finally, CFMR enables the application of MR to exposures that are rare or difficult to measure, which would normally preclude their analysis in the regular two-sample MR setting.Key messagesWe develop a new method to enable an unbiased one-sample Mendelian Randomization.The new method provides the same power as the standard two-sample Mendelian Randomization approach and does not require summary statistics from a genome-wide association study in an independent cohort.Our approach enables a cross-ethnic instrumental variable regression to account for heterogeneity in a sample consisting of multiple ethnicities.

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.

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. 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. 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.

Additional file 1: Figure S4. ROC curves at given standard deviations of the prior. The thin solid curves are the output of FFW; the thick dashed curves are the output of WaveQTL. The ROC curves match for standard deviations of the prior of 0.5 and 1.

DNA methylation is the most widely studied epigenetic mark in humans and plays an essential role in normal biological processes as well as in disease development. More focus has recently been placed on understanding functional aspects of methylation, prompting the development of methods to investigate the relationship between heterogeneity in methylation patterns and disease risk. However, most of these methods are limited in that they use simplified models that may rely on arbitrarily chosen parameters, they can only detect differentially methylated regions (DMRs) one at a time, or they are computationally intensive. To address these shortcomings, we present a wavelet-based method called ‘Wavelet Screening’ (WS) that can perform an epigenome-wide association study (EWAS) of thousands of individuals on a single CPU in only a matter of hours. By detecting multiple DMRs located near each other, WS identifies more complex patterns that can differentiate between different methylation profiles. We performed an extensive set of simulations to demonstrate the robustness and high power of WS, before applying it to a previously published EWAS dataset of orofacial clefts (OFCs). WS identified 82 associated regions containing several known genes and loci for OFCs, while other findings are novel and warrant replication in other OFCs cohorts.

SummaryWe present here an alternative method for genome-wide association study (GWAS) that is more powerful than traditional GWAS methods for locus detection. Single-variant GWAS methods incur a substantial multiple-testing burden because of the vast number of single nucleotide polymorphisms (SNPs) being tested simultaneously. Furthermore, these methods do not consider the functional genetic effect on the outcome because they ignore more complex joint effects of nearby SNPs within a region. By contrast, our method reduces the number of tests to be performed by screening the entire genome for associations using a sliding-window approach based on wavelets. In this context, a sequence of SNPs represents a genetic signal, and for each screened region, we transform the genetic signal into the wavelet space. The null and alternative hypotheses are modelled using the posterior distribution of the wavelet coefficients. We enhance our decision procedure by using additional information from the regression coefficients and by taking advantage of the pyramidal structure of wavelets. When faced with more complex signals than single-SNP associations, we show through simulations that Wavelet Screening provides a substantial gain in power compared to both the traditional GWAS modelling as well as another popular regional-based association test called ‘SNP-set (Sequence) Kernel Association Test’ (SKAT). To demonstrate feasibility, we re-analysed data from the large Norwegian HARVEST cohort.

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.

Additional file 3. This file includes 1) further details (sample selection, DNA extraction, and quality control) of EPIPREG, 2) cross-validation curves of mean squared error over lambda and alpha values for eABEC, 3) determination of the reduced sample sizes for Fig. 4, and 4) further information regarding batch adjustment in developing the ABECs.

Additional file 2 Details of the statistical methods.

Additional file 1 File containing supplementary figures and tables.

Additional file 2. This file includes 1) a figure displaying the age prediction of cABEC, 2) a table containing the bootstrapped 95% confidence intervals for the r values in Figs. 4, 5 and 6) figures displaying the age prediction of the ABECs and the other published clocks in EPIPREG and GSE132203, 4) a figure illustrating the regression-to-the-mean effect and 5) histograms displaying the age distribution of individuals in each cohort.

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).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.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 .

Telomere length is associated with age-related diseases and is highly heritable. It is unclear, however, to what extent epigenetic modifications are associated with leukocyte telomere length (LTL). In this study, we conducted a large-scale epigenome-wide association study (EWAS) of LTL using seven large cohorts (n=5,713) – the Framingham Heart Study, the Jackson Heart Study, the Women’s Health Initiative, the Bogalusa Heart Study, the Lothian Birth Cohorts of 1921 and 1936, and the Longitudinal Study of Aging Danish Twins. Our stratified analysis suggests that EWAS findings for women of African ancestry may be distinct from those of three other groups: males of African ancestry, and males and females of European ancestry. Using a meta-analysis framework, we identified DNA methylation (DNAm) levels at 823 CpG sites to be significantly associated (P

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 Current technology allows rapid assessment of DNA sequences and methylation levels at a single-site resolution for hundreds of thousands of sites in the human genome, in thousands of individuals simultaneously. This has led to an increase in epigenome-wide association studies (EWAS) of complex traits, particularly those that are poorly explained by previous genome-wide association studies (GWAS). However, the genome and epigenome are intertwined, e.g., DNA methylation is known to affect gene expression through, for example, genomic imprinting. There is thus a need to go beyond single-omics data analyses and develop interaction models that allow a meaningful combination of information from EWAS and GWAS. Results We present two new methods for genetic association analyses that treat offspring DNA methylation levels as environmental exposure. Our approach searches for statistical interactions between SNP alleles and DNA methylation (G ×Me) and between parent-of-origin effects and DNA methylation (PoO ×Me), using case-parent triads or dyads. We use summarized methylation levels over nearby genomic region to ease biological interpretation. The methods were tested on a dataset of parent–offspring dyads, with EWAS data on the offspring. Our results showed that methylation levels around a SNP can significantly alter the estimated relative risk. Moreover, we show how a control dataset can identify false positives. Conclusions The new methods, G ×Me and PoO ×Me, integrate DNA methylation in the assessment of genetic relative risks and thus enable a more comprehensive biological interpretation of genome-wide scans. Moreover, our strategy of condensing DNA methylation levels within regions helps overcome specific disadvantages of using sparse chip-based measurements. The methods are implemented in the freely available R package Haplin (https://cran.r-project.org/package=Haplin), enabling fast scans of multi-omics datasets.

Background Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or sample size is an important first step in the planning of any scientific study, there is currently a lack of software for genetic power calculations in family-based study designs. Here, we address this shortcoming through new implementations of power calculations in the R package Haplin, which is a flexible and robust software for genetic epidemiological analyses. Power calculations in Haplin can be performed analytically using the asymptotic variance-covariance structure of the parameter estimator, or else by a straightforward simulation approach. Haplin performs power calculations for child, parent-of-origin and maternal effects, as well as for gene-environment interactions. The power can be calculated for both single SNPs and haplotypes, either autosomal or X-linked. Moreover, Haplin enables power calculations for different child-parent configurations, including (but not limited to) case-parent triads, case-mother dyads, and case-parent triads in combination with unrelated control-parent triads. Results We compared the asymptotic power approximations to the power of analysis attained with Haplin. For external validation, the results were further compared to the power of analysis attained by the EMIM software using data simulations from Haplin. Consistency observed between Haplin and EMIM across various genetic scenarios confirms the computational accuracy of the inference methods used in both programs. The results also demonstrate that power calculations in Haplin are applicable to genetic association studies using either log-linear or multinomial modeling approaches. Conclusions Haplin provides a robust and reliable framework for power calculations in genetic association analyses for a wide range of genetic effects and etiologic scenarios, based on genotype data from a variety of child-parent configurations. Electronic supplementary material The online version of this article (10.1186/s12859-019-2727-3) contains supplementary material, which is available to authorized users.

The human pan-tissue epigenetic clock is widely used for estimating age across the entire lifespan, but it does not lend itself well to estimating gestational age (GA) based on placental DNAm methylation (DNAm) data. We replicate previous findings demonstrating a strong correlation between GA and genome-wide DNAm changes. Using substantially more DNAm arrays (n=1,102 in the training set) than a previous study, we present three new placental epigenetic clocks: 1) a robust placental clock (RPC) which is unaffected by common pregnancy complications (e.g., gestational diabetes, preeclampsia), and 2) a control placental clock (CPC) constructed using placental samples from pregnancies without known placental pathology, and 3) a refined RPC for uncomplicated term pregnancies. These placental clocks are highly accurate estimators of GA based on placental tissue; e.g., predicted GA based on RPC is highly correlated with actual GA (r>0.95 in test data, median error less than one week). We show that epigenetic clocks derived from cord blood or other tissues do not accurately estimate GA in placental samples. While fundamentally different from Horvath’s pan-tissue epigenetic clock, placental clocks closely track fetal age during development and may have interesting applications. publishedVersion

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 applied them to families with children born with isolated cleft palate only. Here, we used the same genome-wide association study (GWAS) dataset and methodology to screen for PoOxE effects in the larger sample of CL/P triads. 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. The methodology applied in the analyses 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.

Power and sample size calculations in Haplin. (PDF 369 kb)

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n=35,584 total samples, 11,986 with ASD). Using an enhanced Bayesian framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate ≤ 0.1. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 53 show higher frequencies in individuals ascertained for ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most of the risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In human cortex single-cell gene expression data, expression of risk genes is enriched in both excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory/inhibitory imbalance underlying ASD.

An asymptotic approximation of ÎŁ. (PDF 184 kb)

SummaryWe present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n=35,584 total samples, 11,986 with ASD). Using an enhanced Bayesian framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate ≤ 0.1. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 53 show higher frequencies in individuals ascertained for ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most of the risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In human cortex single-cell gene expression data, expression of risk genes is enriched in both excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory/inhibitory imbalance underlying ASD.

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. publishedVersion

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. publishedVersion

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. publishedVersion

With case–parent triad data, one can frequently deduce parent of origin of the child's alleles. This allows a parent‐of‐origin (PoO) effect to be estimated as the ratio of relative risks associated with the alleles inherited from the mother and the father, respectively. A possible cause of PoO effects is DNA methylation, leading to genomic imprinting. Because environmental exposures may influence methylation patterns, gene–environment interaction studies should be extended to allow for interactions between PoO effects and environmental exposures (i.e., PoOxE). One should thus search for loci where the environmental exposure modifies the PoO effect. We have developed an extensive framework to analyze PoOxE effects in genome‐wide association studies (GWAS), based on complete or incomplete case–parent triads with or without independent control triads. The interaction approach is based on analyzing triads in each exposure stratum using maximum likelihood estimation in a log‐linear model. Interactions are then tested applying a Wald‐based posttest of parameters across strata. Our framework includes a complete setup for power calculations. We have implemented the models in the R software package Haplin. To illustrate our PoOxE test, we applied the new methodology to top hits from our previous GWAS, assessing whether smoking during the periconceptional period modifies PoO effects on cleft palate only. publishedVersion

The American Psychiatric Association estimates that 3 to 7 per cent of all school aged children are diagnosed with attention deficit hyperactivity disorder (ADHD). Even after correcting for general cognitive ability, numerous studies report a negative association between ADHD and educational achievement. With polygenic scores we examined whether genetic variants that have a positive influence on educational attainment have a protective effect against ADHD. The effect sizes from a large GWA meta-analysis of educational attainment in adults were used to calculate polygenic scores in an independent sample of 12-year-old children from the Netherlands Twin Register. Linear mixed models showed that the polygenic scores significantly predicted educational achievement, school performance, ADHD symptoms and attention problems in children. These results confirm the genetic overlap between ADHD and educational achievement, indicating that one way to gain insight into genetic variants responsible for variation in ADHD is to include data on educational achievement, which are available at a larger scale. (C) 2014 Wiley Periodicals, Inc.

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total n deaths = 79,702) and ∼2.4% lower risk for fathers (total n deaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity. Marioni RE, Ritchie SJ, Joshi PK, Hagenaars SP, Okbay A, Fischer K, Adams MJ, Hill WD, Davies G, Social Science Genetic Association Consortium, Nagy R, Amador C, Läll K, Metspalu A, Liewald DC, Campbell A, Wilson JF, Hayward C, Esko T, Porteous DJ, Proceedings of the National Academy of Sciences of the United States of America, 2016, vol. 113, no. 47, pp. 13366-13371, 2016 Refereed/Peer-reviewed

More than a million childhood diarrhoeal episodes occur worldwide each year, and in developed countries a considerable part of them are caused by viral infections. In this study, we aimed to search for genetic variants associated with diarrhoeal disease in young children by meta-analyzing genome-wide association studies, and to elucidate plausible biological mechanisms. The study was conducted in the context of the Early Genetics and Lifecourse Epidemiology (EAGLE) consortium. Data about diarrhoeal disease in two time windows (around 1 year of age and around 2 years of age) was obtained via parental questionnaires, doctor interviews or medical records. Standard quality control and statistical tests were applied to the 1000 Genomes imputed genotypic data. The meta-analysis (N = 5758) followed by replication (N = 3784) identified a genome-wide significant association between rs8111874 and diarrhoea at age 1 year. Conditional analysis suggested that the causal variant could be rs601338 (W154X) in the FUT2 gene. Children with the A allele, which results in a truncated FUT2 protein, had lower risk of diarrhoea. FUT2 participates in the production of histo-blood group antigens and has previously been implicated in the susceptibility to infections, including Rotavirus and Norovirus. Gene-set enrichment analysis suggested pathways related to the histo-blood group antigen production, and the regulation of ion transport and blood pressure. Among others, the gastrointestinal tract, and the immune and neuro-secretory systems were detected as relevant organs. In summary, this genome-wide association meta-analysis suggests the implication of the FUT2 gene in diarrhoeal disease in young children from the general population.

Contains fulltext : 167137.pdf (Publisher’s version ) (Closed access) Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

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 and 1967-1974 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.

Barban N, Jansen R, de Vlaming R, Vaez A, Mandemakers JJ, Tropf FC, Shen X, Wilson JF, Chasman DI, Nolte IM, Tragante V, van der Laan SW, Perry JR, Kong A; BIOS Consortium, Ahluwalia TS, Albrecht E, Yerges-Armstrong L, Atzmon G, Auro K, Ayers K, Bakshi A, Ben-Avraham D, Berger K, Bergman A, Bertram L, Bielak LF, Bjornsdottir G, Bonder MJ, Broer L, Bui M, Barbieri C, Cavadino A, Chavarro JE, Turman C, Concas MP, Cordell HJ, Davies G, Eibich P, Eriksson N, Esko T, Eriksson J, Falahi F, Felix JF, Fontana MA, Franke L, Gandin I, Gaskins AJ, Gieger C, Gunderson EP, Guo X, Hayward C, He C, Hofer E, Huang H, Joshi PK, Kanoni S, Karlsson R, Kiechl S, Kifley A, Kluttig A, Kraft P, Lagou V, Lecoeur C, Lahti J, Li-Gao R, Lind PA, Liu T, Makalic E, Mamasoula C, Matteson L, Mbarek H, McArdle PF, McMahon G, Meddens SF, Mihailov E, Miller M, Missmer SA, Monnereau C, van der Most PJ, Myhre R, Nalls MA, Nutile T, Kalafati IP, Porcu E, Prokopenko I, Rajan KB, Rich-Edwards J, Rietveld CA, Robino A, Rose LM, Rueedi R, Ryan KA, Saba Y, Schmidt D, Smith JA, Stolk L, Streeten E, Tönjes A, Thorleifsson G, Ulivi S, Wedenoja J, Wellmann J, Willeit P, Yao J, Yengo L, Zhao JH, Zhao W, Zhernakova DV, Amin N, Andrews H, Balkau B, Barzilai N, Bergmann S, Biino G, Bisgaard H, Bønnelykke K, Boomsma DI, Buring JE, Campbell H, Cappellani S, Ciullo M, Cox SR, Cucca F, Toniolo D, Davey-Smith G, Deary IJ, Dedoussis G, Deloukas P, van Duijn CM, de Geus EJ, Eriksson JG, Evans DA, Faul JD, Sala CF, Froguel P, Gasparini P, Girotto G, Grabe HJ, Greiser KH, Groenen PJ, de Haan HG, Haerting J, Harris TB, Heath AC, Heikkilä K, Hofman A, Homuth G, Holliday EG, Hopper J, Hyppönen E, Jacobsson B, Jaddoe VW, Johannesson M, Jugessur A, Kähönen M, Kajantie E, Kardia SL, Keavney B, Kolcic I, Koponen P, Kovacs P, Kronenberg F, Kutalik Z, La Bianca M, Lachance G, Iacono WG, Lai S, Lehtimäki T, Liewald DC; LifeLines Cohort Study, Lindgren CM, Liu Y, Luben R, Lucht M, Luoto R, Magnus P, Magnusson PK, Martin NG, McGue M, McQuillan R, Medland SE, Meisinger C, Mellström D, Metspalu A, Traglia M, Milani L, Mitchell P, Montgomery GW, Mook-Kanamori D, de Mutsert R, Nohr EA, Ohlsson C, Olsen J, Ong KK, Paternoster L, Pattie A, Penninx BW, Perola M, Peyser PA, Pirastu M, Polasek O, Power C, Kaprio J, Raffel LJ, Räikkönen K, Raitakari O, Ridker PM, Ring SM, Roll K, Rudan I, Ruggiero D, Rujescu D, Salomaa V, Schlessinger D, Schmidt H, Schmidt R, Schupf N, Smit J, Sorice R, Spector TD, Starr JM, Stöckl D, Strauch K, Stumvoll M, Swertz MA, Thorsteinsdottir U, Thurik AR, Timpson NJ, Tung JY, Uitterlinden AG, Vaccargiu S, Viikari J, Vitart V, Völzke H, Vollenweider P, Vuckovic D, Waage J, Wagner GG, Wang JJ, Wareham NJ, Weir DR, Willemsen G, Willeit J, Wright AF, Zondervan KT, Stefansson K, Krueger RF, Lee JJ, Benjamin DJ, Cesarini D, Koellinger PD, den Hoed M, Snieder H, Mills MC.

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.

Summary Introduction. Clinical practice and the results of some studies may indicate that physical exercise in the form of endurance training may influence the development of atrial fibrillation (AF). The aim of this paper is to evaluate the scientific background for the hypothesis that there is a connection between physical activity and AF. Material and method. This paper is a review article based on searches in PubMed on specific topics, limited to the period 1995 through March 2011. We found 17 original articles and three relatively recent reviews. Each was read by at least two of the authors and then discussed. Seven of the original articles were excluded for methodo- logical reasons, and we therefore discuss the other ten. Results. We found support for the hypothesis that systematic high inten- sity endurance training such as running can increase the risk of AF, whereas the studies provide no evidence that less intensive physical exercise such as walking increases the risk. Several of the studies have methodological