Effect of polygenic scores of telomere length alleles on telomere length in newborns and parents.

In adults, polygenic scores (PGSs) of telomere length (TL) alleles explain about 4.5% of the variance in TL, as measured by quantitative polymerase chain reaction (qPCR). Yet, these PGSs strongly infer a causal role of telomeres in aging-related diseases. To better understand the determinants of TL through the lifespan, it is essential to examine to what extent these PGSs explain TL in newborns. This study investigates the effect of PGSs on TL in both newborns and their parents, with TL measured by Southern blotting and expressed in base-pairs (bp). Additionally, the study explores the impact of PGSs related to transmitted or non-transmitted alleles on TL in newborns. For parents and newborns, the PGS effects on TL were 172 bp (p = 2.03 × 10-15) and 161 bp (p = 3.06 × 10-8), explaining 6.6% and 5.2% of the TL variance, respectively. The strongest PGS effect was shown for maternally transmitted alleles in newborn girls, amounting to 214 bp (p = 3.77 × 10-6) and explaining 7.8% of the TL variance. The PGS effect of non-transmitted alleles was 56 bp (p = 0.0593) and explained 0.6% of the TL variance. Our findings highlight the importance of TL genetics in understanding early-life determinants of TL. They point to the potential utility of PGSs composed of TL alleles in identifying susceptibility to aging-related diseases from birth and reveal the presence of sexual dimorphism in the effect of TL alleles on TL in newborns. Finally, we attribute the higher TL variance explained by PGSs in our study to TL measurement by Southern blotting.

Telomere length in relation to fecundability and use of assisted reproductive technologies: the Norwegian Mother, Father, and Child Cohort Study.

In women, shorter telomeres have been reported to be associated with conditions such as endometriosis and polycystic ovary syndrome, whereas other studies have reported the opposite. In men, studies mostly report associations between shorter telomeres and sperm quality. To our knowledge, no studies have thus far investigated the associations between TL and fecundability or the use of ART. This study is based on the Norwegian Mother, Father, and Child Cohort (MoBa) Study and uses data from the Medical Birth Registry of Norway (MBRN). We included women (24,645 with genotype data and 1,054 with TL measurements) and men (18,339 with genotype data and 965 with TL measurements) participating between 1998 and 2008. We investigated the associations between leukocyte TL and fecundability, infertility, and the use of ART. We also repeated the analyses using instrumental variables for TL, including genetic risk scores for TL and genetically predicted TL. Approximately 11% of couples had experienced infertility and 4% had used ART. TL was not associated with fecundability among women (fecundability ratio [FR], 0.98; 95% confidence interval [CI], 0.92-1.04) or men (FR, 0.99; CI, 0.93-1.06), nor with infertility among women (odds ratio [OR], 1.03; CI, 0.85-1.24) or men (OR, 1.05; CI, 0.87-1.28). We observed an increased likelihood of using ART with increasing TL among men (OR, 1.22; CI, 1.03-1.46), but not among women (OR, 1.10; CI, 0.92-1.31). No significant associations were observed using the instrumental variables. Our results indicate that TL is a poor biomarker of fecundability, infertility and use of ART in MoBa. Additional studies are required to replicate the association observed between TL and ART in men.

Statistical methods to detect mother-father genetic interaction effects on risk of infertility: A genome-wide approach.

Infertility is a heterogeneous phenotype, and for many couples, the causes of fertility problems remain unknown. One understudied hypothesis is that allelic interactions between the genotypes of the two parents may influence the risk of infertility. Our aim was, therefore, to investigate how allelic interactions can be modeled using parental genotype data linked to 15,789 pregnancies selected from the Norwegian Mother, Father, and Child Cohort Study. The newborns in 1304 of these pregnancies were conceived using assisted reproductive technologies (ART), and the remainder were conceived naturally. Treating the use of ART as a proxy for infertility, different parameterizations were implemented in a genome-wide screen for interaction effects between maternal and paternal alleles at the same locus. Some of the models were more similar in the way they were parameterized, and some produced similar results when implemented on a genome-wide scale. The results showed near-significant interaction effects in genes relevant to the phenotype under study, such as Dynein axonemal heavy chain 17 (DNAH17) with a recognized role in male infertility. More generally, the interaction models presented here are readily adaptable to the study of other phenotypes in which maternal and paternal allelic interactions are likely to be involved.

The X-factor in ART: does the use of assisted reproductive technologies influence DNA methylation on the X chromosome?

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.

Effectiveness of mRNA Booster Vaccination Against Mild, Moderate, and Severe COVID-19 Caused by the Omicron Variant in a Large, Population-Based, Norwegian Cohort.

BACKGROUND: Understanding how booster vaccination can prevent moderate and severe illness without hospitalization is crucial to evaluate the full advantage of mRNA boosters. METHODS: We followed 85 801 participants (aged 31-81 years) in 2 large population-based cohorts during the Omicron BA.1/2 wave. Information on home testing, PCR testing, and symptoms of coronavirus disease 2019 (COVID-19) was extracted from biweekly questionnaires covering the period 12 January 2022 to 7 April 2022. Vaccination status and data on previous SARS-CoV-2 infection were obtained from national registries. Cox regression was used to estimate the effectiveness of booster vaccination compared to receipt of 2-dose primary series >130 days previously. RESULTS: The effectiveness of booster vaccination increased with increasing severity of COVID-19 and decreased with time since booster vaccination. The effectiveness against severe COVID-19 was reduced from 80.9% shortly after booster vaccination to 63.4% in the period >90 days after vaccination. There was hardly any effect against mild COVID-19. The effectiveness tended to be lower among subjects aged ≥60 years than those aged <50 years. CONCLUSIONS: This is the first population-based study to evaluate booster effectiveness against self-reported mild, moderate, and severe COVID-19. Our findings contribute valuable information on duration of protection and thus timing of additional booster vaccinations.

DNA methylation in newborns conceived by assisted reproductive technology.

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.

Association of SARS-CoV-2 Vaccination During Pregnancy With Pregnancy Outcomes.

Importance: Data about the safety of vaccines against SARS-CoV-2 during pregnancy are limited. Objective: To examine the risk of adverse pregnancy outcomes after vaccination against SARS-CoV-2 during pregnancy. Design, Setting, and Participants: This registry-based retrospective cohort study included 157 521 singleton pregnancies ending after 22 gestational weeks from January 1, 2021, until January 12, 2022 (Sweden), or January 15, 2022 (Norway). The Pregnancy Register in Sweden and the Medical Birth Registry of Norway were linked to vaccination and other registries for identification of exposure and background characteristics. Exposures: Data on mRNA vaccines-BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna)-and 1 viral vector vaccine-AZD1222 (AstraZeneca)-were collected from national vaccination registries. Main Outcomes and Measures: The risk of preterm birth and stillbirth was evaluated using Cox regression models, with gestational day as the time metric and vaccination as a time-dependent exposure variable. The risk of small for gestational age, low Apgar score, and neonatal care admission was evaluated using logistic regression. Random-effects meta-analysis was used to combine results between countries. Results: Among the 157 521 singleton births included in the study (103 409 in Sweden and 54 112 in Norway), the mean maternal age at the time of delivery was 31 years, and 28 506 (18%) were vaccinated against SARS-CoV-2 (12.9% with BNT162b2, 4.8% with mRNA-1273, and 0.3% with AZD1222) while pregnant. A total of 0.7%, 8.3%, and 9.1% of individuals delivering were vaccinated during the first, second, and third trimester, respectively. Vaccination against SARS-CoV-2 was not significantly associated with increased risk of preterm birth (6.2 vs 4.9 per 10 000 pregnancy days; adjusted hazard ratio [aHR], 0.98 [95% CI, 0.91 to 1.05]; I2 = 0%; P for heterogeneity = .60), stillbirth (2.1 vs 2.4 per 100 000 pregnancy days; aHR, 0.86 [95% CI, 0.63 to 1.17]), small for gestational age (7.8% vs 8.5%; difference, -0.6% [95% CI, -1.3% to 0.2%]; adjusted OR [aOR], 0.97 [95% CI, 0.90 to 1.04]), low Apgar score (1.5% vs 1.6%; difference, -0.05% [95% CI, -0.3% to 0.1%]; aOR, 0.97 [95% CI, 0.87 to 1.08]), or neonatal care admission (8.5% vs 8.5%; difference, 0.003% [95% CI, -0.9% to 0.9%]; aOR, 0.97 [95% CI, 0.86 to 1.10]). Conclusions and Relevance: In this population-based study conducted in Sweden and Norway, vaccination against SARS-CoV-2 during pregnancy, compared with no SARS-CoV-2 vaccination during pregnancy, was not significantly associated with an increased risk of adverse pregnancy outcomes. The majority of the vaccinations were with mRNA vaccines during the second and third trimesters of pregnancy, which should be considered in interpreting the findings.

Wavelet Screening: a novel approach to analyzing GWAS data.

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.

A fast wavelet-based functional association analysis replicates several susceptibility loci for birth weight in a Norwegian population.

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.

Wavelet Screening identifies regions highly enriched for differentially methylated loci for orofacial clefts.

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.

An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies.

BACKGROUND: Gestational age is a useful proxy for assessing developmental maturity, but correct estimation of gestational age is difficult using clinical measures. DNA methylation at birth has proven to be an accurate predictor of gestational age. Previous predictors of epigenetic gestational age were based on DNA methylation data from the Illumina HumanMethylation 27 K or 450 K array, which have subsequently been replaced by the Illumina MethylationEPIC 850 K array (EPIC). Our aims here were to build an epigenetic gestational age clock specific for the EPIC array and to evaluate its precision and accuracy using the embryo transfer date of newborns from the largest EPIC-derived dataset to date on assisted reproductive technologies (ART). METHODS: We built an epigenetic gestational age clock using Lasso regression trained on 755 randomly selected non-ART newborns from the Norwegian Study of Assisted Reproductive Technologies (START)-a substudy of the Norwegian Mother, Father, and Child Cohort Study (MoBa). For the ART-conceived newborns, the START dataset had detailed information on the embryo transfer date and the specific ART procedure used for conception. The predicted gestational age was compared to clinically estimated gestational age in 200 non-ART and 838 ART newborns using MM-type robust regression. The performance of the clock was compared to previously published gestational age clocks in an independent replication sample of 148 newborns from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restrictions (PREDO) study-a prospective pregnancy cohort of Finnish women. RESULTS: Our new epigenetic gestational age clock showed higher precision and accuracy in predicting gestational age than previous gestational age clocks (R2 = 0.724, median absolute deviation (MAD) = 3.14 days). Restricting the analysis to CpGs shared between 450 K and EPIC did not reduce the precision of the clock. Furthermore, validating the clock on ART newborns with known embryo transfer date confirmed that DNA methylation is an accurate predictor of gestational age (R2 = 0.767, MAD = 3.7 days). CONCLUSIONS: We present the first EPIC-based predictor of gestational age and demonstrate its robustness and precision in ART and non-ART newborns. As more datasets are being generated on the EPIC platform, this clock will be valuable in studies using gestational age to assess neonatal development.

Growth in children conceived by ART.

STUDY QUESTION: Is the growth pattern of children conceived by ART different compared to naturally conceived children. SUMMARY ANSWER: Both ART and underlying parental subfertility may contribute to differences in early childhood growth between children conceived with and without the use of ART. WHAT IS KNOWN ALREADY: Children conceived by ART weigh less and are shorter at the time of delivery. The extent to which differences in growth according to mode of conception persist during childhood, and the role of underlying parental subfertility, remains unclear. STUDY DESIGN, SIZE, DURATION: We conducted a prospective study population-based study. We studied 81 461 children participating in the Norwegian Mother, Father and Child Cohort Study (MoBa) and 544 113 adolescents screened for military conscription. PARTICIPANTS/MATERIALS, SETTING, METHODS: Conception by ART as registered in the Medical Birth Registry. We compared maternally reported length/height and weight among children in MoBa from mid-pregnancy to age 7 according to mode of conception using mixed-effects linear regression. Differences in self-reported height and weight at 17 years of age at screening for military conscription were assessed with linear regression. MAIN RESULTS AND THE ROLE OF CHANCE: At birth, children conceived by ART were shorter (boys -0.3 cm; 95% CI, -0.5 to -0.1), girls -0.4 cm; 95% CI, -0.5 to -0.3) and lighter (boys -113 grams; 95% CI, -201 to -25, girls -107 grams; 95% CI, -197 to -17). After birth, children conceived by ART grew more rapidly, achieving both greater height and weight at age 3. Children conceived by ART had a greater height up to age 7, but did not have a greater height or weight by age 17. Naturally conceived children of parents taking longer time to conceive had growth patterns similar to ART children. Children born after frozen embryo transfer had larger ultrasound measures and were longer and heavier the first 2 years than those born after fresh embryo transfer. LIMITATIONS, REASONS FOR CAUTIONS: Selection bias could have been introduced due to the modest participation rate in the MoBa cohort. Our reliance on self-reported measures of length/height and weight could have introduced measurement error. WIDER IMPLICATIONS OF THE FINDINGS: : Our findings provide reassurance that offspring conceived by ART are not different in height, weight or BMI from naturally conceived once they reach adolescence. STUDY FUNDING/COMPETING INTEREST(S): Research Council of Norway; Medical Research Council; National Institute of Environmental Health Sciences. The authors have no competing interest. TRIAL REGISTRATION NUMBER: N/A.

Heritability curves: A local measure of heritability in family models.

Classical heritability models for family data split the phenotype variance into genetic and environmental components. For instance, the ACE model in twin studies assumes the phenotype variance decomposes as a2 + c2 + e2 , representing (additive) genetic effects, common (shared) environment, and residual environment, respectively. However, for some phenotypes it is biologically plausible that the genetic and environmental components may vary over the range of the phenotype. For instance, very large or small values of the phenotype may be caused by "sporadic" environmental factors, whereas the mid-range phenotype variation may be more under the control of common genetic factors. This article introduces a "local" measure of heritability, where the genetic and environmental components are allowed to depend on the value of the phenotype itself. Our starting point is a general formula for local correlation between two random variables. For estimation purposes, we use a multivariate Gaussian mixture, which is able to capture nonlinear dependence and respects certain distributional constraints. We derive an analytical expression for the associated correlation curve, and show how to decompose the correlation curve into genetic and environmental parts, for instance, a2 (y) + c2 (y) + e2 (y) for the ACE model, where we estimate the components as functions of the phenotype y. Furthermore, our model allows switching, for instance, from the ACE model to the ADE model within the range of the same phenotype. When applied to birth weight (BW) data on Norwegian mother-father-child trios, we conclude from the model that low and high BW are less heritable traits than medium BW. We also demonstrate switching between the ACE and ADE model when studying body mass index in adult monozygotic and dizygotic twins.

Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array.

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.

Gene-methylation interactions: discovering region-wise DNA methylation levels that modify SNP-associated disease risk.

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.

PHLDA2 gene polymorphisms and risk of HELLP syndrome and severe preeclampsia.

OBJECTIVE: Pleckstrin homology-like domain, family A, member 2 (PHLDA2) is a maternally expressed imprinted gene. Loss of imprinting in PHLDA2 is associated with abnormal placental development and fetal growth restriction. Our objective was to determine whether genetic variation in PHLDA2 is also associated with risk of HELLP syndrome and preeclampsia (PE) with severe features. STUDY DESIGN: Case (n = 162) and control (n = 33) mother-father-child triads were recruited using an internet-based method. Medical records were reviewed to verify clinical diagnosis of self-reported cases. DNA was genotyped for three polymorphisms in the PHLDA2 gene using TaqMan assays: rs13390, rs1056819, rs2583435. MAIN OUTCOME MEASURES: To examine the association between minor alleles and haplotypes with HELLP syndrome and PE with severe features, relative risks and 95% confidence intervals were estimated using log-linear models, adjusting for the correlation between familial genotypes, using HAPLIN. RESULTS: There was no association identified between PHLDA2 gene polymorphisms or haplotypes and HELLP syndrome and PE with severe features. No parent-of-origin effects were observed. CONCLUSION: Genetic variation in the PHLDA2 gene is not associated with HELLP syndrome or PE with severe features.

Design efficiency in genetic association studies.

Selecting the best design for genetic association studies requires careful deliberation; different study designs can be used to scan for different genetic effects, and each design has its own set of strengths and limitations. A variety of family and unrelated control configurations are amenable to genetic association analyses, including the case-control design, case-parent triads, and case-parent triads in combination with unrelated controls or control-parent triads. Ultimately, the goal is to choose the design that achieves the highest statistical power using the lowest cost. For given parameter values and genotyped individuals, designs can be compared directly by computing the power. However, a more informative and general design comparison can be achieved by studying the relative efficiency, defined as the ratio of variances of two different parameter estimators, corresponding to two separate designs. Using log-linear modeling, we derive the relative efficiency from the asymptotic variance of the parameter estimators and relate it to the concept of Pitman efficiency. The relative efficiency takes into account the fact that different designs impose different costs relative to the number of genotyped individuals. We show that while optimal efficiency for analyses of regular autosomal effects is achieved using the standard case-control design, the case-parent triad design without unrelated controls is efficient when searching for parent-of-origin effects. Due to the potential loss of efficiency, maternal genes should generally not be adjusted for in an initial genome-wide association study scan of offspring genes but instead checked post hoc. The relative efficiency calculations are implemented in our R package Haplin.

Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels.

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.