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The prevalence and severity of many diseases differs by sex, potentially due to sex-specific patterns in DNA methylation. Autosomal sex-specific differences in DNA methylation have been observed in cord blood and placental tissue but are not well studied in saliva or in diverse populations. We sought to characterize sex-specific DNA methylation on autosomal chromosomes in saliva samples from children in the Future of Families and Child Wellbeing Study, a multi-ethnic prospective birth cohort containing an oversampling of Black, Hispanic and low-income families. DNA methylation from saliva samples was analysed on 796 children (50.6% male) at both ages 9 and 15 with DNA methylation measured using the Illumina HumanMethylation 450k array. An epigenome-wide association analysis of the age 9 samples identified 8,430 sex-differentiated autosomal DNA methylation sites (P < 2.4 × 10-7), of which 76.2% had higher DNA methylation in female children. The strongest sex-difference was in the cg26921482 probe, in the AMDHD2 gene, with 30.6% higher DNA methylation in female compared to male children (P < 1 × 10-300). Treating the age 15 samples as an internal replication set, we observed highly consistent results between the ages 9 and 15 measurements, indicating stable and replicable sex-differentiation. Further, we directly compared our results to previously published DNA methylation sex differences in both cord blood and saliva and again found strong consistency. Our findings support widespread and robust sex-differential DNA methylation across age, human tissues, and populations. These findings help inform our understanding of potential biological processes contributing to sex differences in human physiology and disease. [ABSTRACT FROM AUTHOR]

Exposure in utero to particulate matter (PM2.5 and PM10) is associated with maladaptive health outcomes. Although exposure to prenatal PM2.5 and PM10 has cord blood DNA methylation signatures at birth, signature persistence into childhood and saliva cross-tissue applicability has not been tested. In the Fragile Families and Child Wellbeing Study, a United States 20-city birth cohort, average residential PM2.5 and PM10 during the three months prior to birth was estimated using air quality monitors with inverse distance weighting. Saliva DNA methylation at ages 9 (n = 749) and 15 (n = 793) was measured using the Illumina HumanMethylation 450 k BeadArray. Cumulative DNA methylation scores for particulate matter were estimated by weighting participant DNA methylation at each site by independent meta-analysis effect estimates and standardizing the sums. Using a mixed-effects regression analysis, we tested the associations between cumulative DNA methylation scores at ages 9 and 15 and PM exposure during pregnancy, adjusted for child sex, age, race/ethnicity, maternal income-to-needs ratio, nonmartial birth status, and saliva cell-type proportions. Our study sample was 50.5% male, 56.3% non-Hispanic Black, and 19.8% Hispanic, with a median income-to-needs ratio of 1.4. Mean exposure levels for PM2.5 were 27.9 μg/m3/day (standard deviation: 7.0; 23.7% of observations exceeded safety standards) and for PM10 were 15.0 μg/m3/day (standard deviation: 3.1). An interquartile range increase in PM2.5 exposure (10.73 μg/m3/day) was associated with a −0.0287 standard deviation lower cumulative DNA methylation score for PM2.5 (95% CI: −0.0732, 0.0158, p = 0.20) across all participants. An interquartile range increase in PM10 exposure (3.20 μg/m3/day) was associated with a −0.1472 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: −0.3038, 0.0095, p = 0.06) across all participants. The PM10 findings were driven by the age 15 subset where an interquartile range increase in PM10 exposure was associated with a −0.024 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: −0.043, −0.005, p = 0.012). Findings were robust to adjustment for PM exposure at ages 1 and 3. In utero PM10-associated DNA methylation differences were identified at age 15 in saliva. Benchmarking the timing and cell-type generalizability is critical for epigenetic exposure biomarker assessment. [ABSTRACT FROM AUTHOR]