Sex-dependent placental methylation quantitative trait loci provide insight into the prenatal origins of childhood onset traits and conditions.

Molecular quantitative trait loci (QTLs) allow us to understand the biology captured in genome-wide association studies (GWASs). The placenta regulates fetal development and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explain variation in genetic risk for childhood onset traits, and that effects differ by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with mQTL and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions that typically affect gene expression in prenatal tissues. All mQTL were also enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.

A developmental framework for understanding the influence of sex and gender on health: Pediatric pain as an exemplar.

Sex differences are a robust finding in many areas of adult health, including cardiovascular disease, psychiatric disorders, and chronic pain. However, many sex differences are not consistently observed until after the onset of puberty. This has led to the hypothesis that hormones are primary contributors to sex differences in health outcomes, largely ignoring the relative contributions of early developmental influences, emerging psychosocial factors, gender, and the interaction between these variables. In this paper, we argue that a comprehensive understanding of sex and gender contributions to health outcomes should start as early as conception and take an iterative biopsychosocial-developmental perspective that considers intersecting social positions. We present a conceptual framework, informed by a review of the literature in basic, clinical, and social science that captures how critical developmental stages for both sex and gender can affect children's health and longer-term outcomes. The literature on pediatric chronic pain is used as a worked example of how the framework can be applied to understanding different chronic conditions.

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta.

Background : Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied. Results : Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, but reassuringly were robust to placental processing time. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component. Conclusions : This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. Further, we demonstrate that estimating epiphenotype variables from the DNAme data itself, when possible, provides both an independent check of clinically-obtained data and can provide a robust approach to compare variables across different datasets.

Who's afraid of the X? Incorporating the X and Y chromosomes into the analysis of DNA methylation array data.

BACKGROUND: Many human disease phenotypes manifest differently by sex, making the development of methods for incorporating X and Y-chromosome data into analyses vital. Unfortunately, X and Y chromosome data are frequently excluded from large-scale analyses of the human genome and epigenome due to analytical complexity associated with sex chromosome dosage differences between XX and XY individuals, and the impact of X-chromosome inactivation (XCI) on the epigenome. As such, little attention has been given to considering the methods by which sex chromosome data may be included in analyses of DNA methylation (DNAme) array data. RESULTS: With Illumina Infinium HumanMethylation450 DNAme array data from 634 placental samples, we investigated the effects of probe filtering, normalization, and batch correction on DNAme data from the X and Y chromosomes. Processing steps were evaluated in both mixed-sex and sex-stratified subsets of the analysis cohort to identify whether including both sexes impacted processing results. We found that identification of probes that have a high detection p-value, or that are non-variable, should be performed in sex-stratified data subsets to avoid over- and under-estimation of the quantity of probes eligible for removal, respectively. All normalization techniques investigated returned X and Y DNAme data that were highly correlated with the raw data from the same samples. We found no difference in batch correction results after application to mixed-sex or sex-stratified cohorts. Additionally, we identify two analytical methods suitable for XY chromosome data, the choice between which should be guided by the research question of interest, and we performed a proof-of-concept analysis studying differential DNAme on the X and Y chromosome in the context of placental acute chorioamnionitis. Finally, we provide an annotation of probe types that may be desirable to filter in X and Y chromosome analyses, including probes in repetitive elements, the X-transposed region, and cancer-testis gene promoters. CONCLUSION: While there may be no single "best" approach for analyzing DNAme array data from the X and Y chromosome, analysts must consider key factors during processing and analysis of sex chromosome data to accommodate the underlying biology of these chromosomes, and the technical limitations of DNA methylation arrays.

Profiling placental DNA methylation associated with maternal SSRI treatment during pregnancy.

Selective serotonin reuptake inhibitors (SSRIs) for treatment of prenatal maternal depression have been associated with neonatal neurobehavioral disturbances, though the molecular mechanisms remain poorly understood.  In utero exposure to SSRIs may affect DNA methylation (DNAme) in the human placenta, an epigenetic mark that is established during development and is associated with gene expression. Chorionic villus samples from 64 human placentas were profiled with the Illumina MethylationEPIC BeadChip; clinical assessments of maternal mood and SSRI treatment records were collected at multiple time points during pregnancy. Case distribution was 20 SSRI-exposed cases and 44 SSRI non-exposed cases. Maternal depression was defined using a mean maternal Hamilton Depression score > 8 to indicate symptomatic depressed mood ("maternally-depressed"), and we further classified cases into SSRI-exposed, maternally-depressed (n = 14); SSRI-exposed, not maternally-depressed (n = 6); SSRI non-exposed, maternally-depressed (n = 20); and SSRI non-exposed, not maternally-depressed (n = 24). For replication, Illumina 450K DNAme profiles were obtained from 34 additional cases from an independent cohort (n = 17 SSRI-exposed, n = 17 SSRI non-exposed). No CpGs were differentially methylated at FDR < 0.05 comparing SSRI-exposed to non-exposed placentas, in a model adjusted for mean maternal Hamilton Depression score, or in a model restricted to maternally-depressed cases with and without SSRI exposure. However, at a relaxed threshold of FDR < 0.25, five CpGs were differentially methylated (|Δß| > 0.03) by SSRI exposure status. Four were covered by the replication cohort measured by the 450K array, but none replicated. No CpGs were differentially methylated (FDR < 0.25) comparing maternally depressed to not depressed cases. In sex-stratified analyses for SSRI-exposed versus non-exposed cases (females n = 31; males n = 33), three additional CpGs in females, but none in males, were differentially methylated at the relaxed FDR < 0.25 cut-off. We did not observe large-scale alterations of DNAme in placentas exposed to maternal SSRI treatment, as compared to placentas with no SSRI exposure. We also found no evidence for altered DNAme in maternal depression-exposed versus depression non-exposed placentas. This novel work in a prospectively-recruited cohort with clinician-ascertained SSRI exposure and mood assessments would benefit from future replication.

Are sex differences in cognitive impairment reflected in epigenetic age acceleration metrics?

Sex differences are well-established in Alzheimer's disease (AD) frequency and pathogenesis, but are not mechanistically understood. Accelerated epigenetic age has been associated with both cognitive aging and AD pathophysiology, but has not been studied by sex in AD or related cognitive impairment. Using the ADNI cohort, we found that none of sex, cognitive impairment diagnosis, nor load of APOEε4 alleles (strongest genetic AD risk factor) were associated with epigenetic age acceleration (DNAmAge, Intrinsic DNAmAge, PhenoAge, or GrimAge), although females exhibit more accelerated epigenetic aging using the Skin & Blood clock in the transition from normal cognition to cognitive impairment than males.

Risk-focused differences in molecular processes implicated in SARS-CoV-2 infection: corollaries in DNA methylation and gene expression.

BACKGROUND: Understanding the molecular basis of susceptibility factors to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health imperative. It is well-established that males are more likely to acquire SARS-CoV-2 infection and exhibit more severe outcomes. Similarly, exposure to air pollutants and pre-existing respiratory chronic conditions, such as asthma and chronic obstructive respiratory disease (COPD) confer an increased risk to coronavirus disease 2019 (COVID-19). METHODS: We investigated molecular patterns associated with risk factors in 398 candidate genes relevant to COVID-19 biology. To accomplish this, we downloaded DNA methylation and gene expression data sets from publicly available repositories (GEO and GTEx Portal) and utilized data from an empirical controlled human exposure study conducted by our team. RESULTS: First, we observed sex-biased DNA methylation patterns in autosomal immune genes, such as NLRP2, TLE1, GPX1, and ARRB2 (FDR < 0.05, magnitude of DNA methylation difference Δß > 0.05). Second, our analysis on the X-linked genes identified sex associated DNA methylation profiles in genes, such as ACE2, CA5B, and HS6ST2 (FDR < 0.05, Δß > 0.05). These associations were observed across multiple respiratory tissues (lung, nasal epithelia, airway epithelia, and bronchoalveolar lavage) and in whole blood. Some of these genes, such as NLRP2 and CA5B, also exhibited sex-biased gene expression patterns. In addition, we found differential DNA methylation patterns by COVID-19 status for genes, such as NLRP2 and ACE2 in an exploratory analysis of an empirical data set reporting on human COVID-9 infections. Third, we identified modest DNA methylation changes in CpGs associated with PRIM2 and TATDN1 (FDR < 0.1, Δß > 0.05) in response to particle-depleted diesel exhaust in bronchoalveolar lavage. Finally, we captured a DNA methylation signature associated with COPD diagnosis in a gene involved in nicotine dependence (COMT) (FDR < 0.1, Δß > 0.05). CONCLUSION: Our findings on sex differences might be of clinical relevance given that they revealed molecular associations of sex-biased differences in COVID-19. Specifically, our results hinted at a potentially exaggerated immune response in males linked to autosomal genes, such as NLRP2. In contrast, our findings at X-linked loci such as ACE2 suggested a potentially distinct DNA methylation pattern in females that may interact with its mRNA expression and inactivation status. We also found tissue-specific DNA methylation differences in response to particulate exposure potentially capturing a nitrogen dioxide (NO2) effect-a contributor to COVID-19 susceptibility. While we identified a molecular signature associated with COPD, all COPD-affected individuals were smokers, which may either reflect an association with the disease, smoking, or may highlight a compounded effect of these two risk factors in COVID-19. Overall, our findings point towards a molecular basis of variation in susceptibility factors that may partly explain disparities in the risk for SARS-CoV-2 infection.

Dysregulated BMP2 in the Placenta May Contribute to Early-Onset Preeclampsia by Regulating Human Trophoblast Expression of Extracellular Matrix and Adhesion Molecules.

Many pregnancy disorders, including early-onset preeclampsia (EOPE), are associated with defects in placental trophoblast cell invasion and differentiation during early placental development. Bone morphogenetic protein 2 (BMP2) belongs to the TGF-ß superfamily and controls various physiological and developmental processes. However, the expression of BMP2 in the placenta and underlying molecular mechanisms of how BMP2 regulates trophoblast function remain unclear. In this study, we analyzed several publicly available microarray and RNA-seq datasets and revealed differences in expression of TGF-ß superfamily members between gestational age-matched non-preeclamptic control and EOPE placentas. Importantly, BMP2 levels were significantly reduced in EOPE placentas compared with controls, and RNAscope in situ hybridization further demonstrated BMP2 expression was disrupted in EOPE placental villi. To explore the molecular mechanisms of BMP2-regulated early trophoblast differentiation, we examined BMP2 expression in first-trimester human placenta and found it to be localized to all subtypes of trophoblasts and the decidua. RNA-seq analysis on control and BMP2-treated primary human trophoblast cells identified 431 differentially expressed genes, including several canonical TGF-ß/BMP signaling targets (BAMBI, ID1, INHBA, IGFBP3). Gene ontology annotations revealed that differentially expressed genes were involved in cell adhesion and extracellular matrix organization. Furthermore, we identified adhesion molecule with IgG-like domain 2 (AMIGO2) as a novel target for BMP2 that contributed to BMP2-induced trophoblast invasion and endothelial-like tube formation. Overall, our findings provide insight into the molecular processes controlled by BMP2 during early placental development that may contribute to the pathogenesis of EOPE.

Autosomal sex-associated co-methylated regions predict biological sex from DNA methylation.

Sex is a modulator of health that has been historically overlooked in biomedical research. Recognizing this knowledge gap, funding agencies now mandate the inclusion of sex as a biological variable with the goal of stimulating efforts to illuminate the molecular underpinnings of sex biases in health and disease. DNA methylation (DNAm) is a strong molecular candidate for mediating such sex biases; however, a robust and well characterized annotation of sex differences in DNAm is yet to emerge. Beginning with a large (n = 3795) dataset of DNAm profiles from normative adult whole blood samples, we identified, validated and characterized autosomal sex-associated co-methylated genomic regions (sCMRs). Strikingly, sCMRs showed consistent sex differences in DNAm over the life course and a subset were also consistent across cell, tissue and cancer types. sCMRs included sites with known sex differences in DNAm and links to health conditions with sex biased effects. The robustness of sCMRs enabled the generation of an autosomal DNAm-based predictor of sex with 96% accuracy. Testing this tool on blood DNAm profiles from individuals with sex chromosome aneuploidies (Klinefelter [47,XXY], Turner [45,X] and 47,XXX syndrome) revealed an intimate relationship between sex chromosomes and sex-biased autosomal DNAm.

Sex Differences Are Here to Stay: Relevance to Prenatal Care.

Sex differences exist in the incidence and presentation of many pregnancy complications, including but not limited to pregnancy loss, spontaneous preterm birth, and fetal growth restriction. Sex differences arise very early in development due to differential gene expression from the X and Y chromosomes, and later may also be influenced by the action of gonadal steroid hormones. Though offspring sex is not considered in most prenatal diagnostic or therapeutic strategies currently in use, it may be beneficial to consider sex differences and the associated mechanisms underlying pregnancy complications. This review will cover (i) the prevalence and presentation of sex differences that occur in perinatal complications, particularly with a focus on the placenta; (ii) possible mechanisms underlying the development of sex differences in placental function and pregnancy phenotypes; and (iii) knowledge gaps that should be addressed in the development of diagnostic or risk prediction tools for such complications, with an emphasis on those for which it would be important to consider sex.

A cross-cohort analysis of autosomal DNA methylation sex differences in the term placenta.

BACKGROUND: Human placental DNA methylation (DNAme) data is a valuable resource for studying sex differences during gestation, as DNAme profiles after delivery reflect the cumulative effects of gene expression patterns and exposures across gestation. Here, we present an analysis of sex differences in autosomal DNAme in the uncomplicated term placenta (n = 343) using the Illumina 450K array. RESULTS: At a false discovery rate < 0.05 and a mean sex difference in DNAme beta value of > 0.10, we identified 162 autosomal CpG sites that were differentially methylated by sex and replicated in an independent cohort of samples (n = 293). Several of these differentially methylated CpG sites were part of larger correlated regions of sex differential DNAme. Although global DNAme levels did not differ by sex, the majority of significantly differentially methylated CpGs were more highly methylated in male placentae, the opposite of what is seen in differential methylation analyses of somatic tissues. Patterns of autosomal DNAme at these 162 CpGs were significantly associated with maternal age (in males) and newborn birthweight standard deviation (in females). CONCLUSIONS: Our results provide a comprehensive analysis of sex differences in autosomal DNAme in the term human placenta. We report a list of high-confidence autosomal sex-associated differentially methylated CpGs and identify several key features of these loci that suggest their relevance to sex differences observed in normative and complicated pregnancies.

Inflammation in Alzheimer's Disease: Do Sex and APOE Matter?

BACKGROUND: Alzheimer's disease (AD) disproportionately affects females with steeper cognitive decline and more neuropathology compared to males, which is exacerbated in females carrying the APOEɛ4 allele. The risk of developing AD is also higher in female APOEɛ4 carriers in earlier age groups (aged 65-75), and the progression from cognitively normal to mild cognitive impairment (MCI) and to AD may be influenced by sex. Inflammation is observed in AD and is related to aging, stress, and neuroplasticity, and although studies are scarce, sex differences are noted in inflammation. OBJECTIVE: The objective of this study was to investigate underlying physiological inflammatory mechanisms that may help explain why there are sex differences in AD and APOEɛ4 carriers. METHODS: We investigated, using the ADNI database, the effect of sex and APOE genotype (non-carriers or carriers of 1 and 2 APOEɛ4 alleles) and sex and diagnosis (cognitively normal (CN), MCI, AD) on CSF (N = 279) and plasma (N = 527) markers of stress and inflammation. RESULTS: We found CSF IL-16 and IL-8 levels differed by sex and APOE genotype, as IL-16 was higher in female APOEɛ4 carriers compared to non-carriers, while the opposite pattern was observed in males with IL-8. Furthermore, females had on average higher levels of plasma CRP and ICAM1 but lower levels of CSF ICAM1, IL-8, IL-16, and IgA than males. Carrying APOEɛ4 alleles and diagnosis (MCI and AD) decreased plasma CRP in both sexes. CONCLUSION: Sex and APOE genotype differences in CSF and plasma inflammatory biomarkers support that the underlying physiological changes during aging differ by sex and tissue origin.

Altered levels of placental miR-338-3p and miR-518b are associated with acute chorioamnionitis and IL6 genotype.

Placental-derived miRNAs are attractive candidates as biomarkers of placental health, but their associations with specific pathologies, such as acute chorioamnionitis (aCA), are not well explored. Samples of chorionic villi from 57 placentas (33 aCA and 24 non-aCA) were analyzed. Expression was quantified for six candidate miRNAs (miR-146a, miR-210, miR-223, miR-338-3p, miR-411, and miR-518b), using quantitative real-time PCR. miR-518b and miR-338-3p were differentially expressed between aCA cases and non-aCA cases (Bonferroni-corrected p < 0.05). Further, we observed that placental miR-518b expression was associated with an IL6 SNP (rs1800796), a polymorphism we previously reported as a risk-conferring variant for aCA.