Adiposity associated DNA methylation signatures in adolescents are related to leptin and perinatal factors.

Epigenetics links perinatal influences with later obesity. We identifed differentially methylated CpG (dmCpG) loci measured at 17 years associated with concurrent adiposity measures and examined whether these were associated with hsCRP, adipokines, and early life environmental factors. Genome-wide DNA methylation from 1192 Raine Study participants at 17 years, identified 29 dmCpGs (Bonferroni corrected p < 1.06E-07) associated with body mass index (BMI), 10 with waist circumference (WC) and 9 with subcutaneous fat thickness. DmCpGs within Ras Association (RalGDS/AF-6), Pleckstrin Homology Domains 1 (RAPH1), Musashi RNA-Binding Protein 2 (MSI2), and solute carrier family 25 member 10 (SLC25A10) are associated with both BMI and WC. Validation by pyrosequencing confirmed these associations and showed that MSI2 , SLC25A10 , and RAPH1 methylation was positively associated with serum leptin. These were  also associated with the early environment; MSI2 methylation (ß = 0.81, p = 0.0004) was associated with pregnancy maternal smoking, SLC25A10 (CpG2 ß = 0.12, p = 0.002) with pre- and early pregnancy BMI, and RAPH1 (ß = -1.49, p = 0.036) with gestational weight gain. Adjusting for perinatal factors, methylation of the dmCpGs within MSI2, RAPH1, and SLC25A10 independently predicted BMI, accounting for 24% of variance. MSI2 methylation was additionally associated with BMI over time (17 years old ß = 0.026, p = 0.0025; 20 years old ß = 0.027, p = 0.0029) and between generations (mother ß = 0.044, p = 7.5e-04). Overall findings suggest that DNA methylation in MSI2, RAPH1, and SLC25A10 in blood may be robust markers, mediating through early life factors.

DNA methylation patterns within whole blood of adolescents born from assisted reproductive technology are not different from adolescents born from natural conception.

STUDY QUESTION: Do the epigenome-wide DNA methylation profiles of adolescents born from ART differ from the epigenome of naturally conceived counterparts? SUMMARY ANSWER: No significant differences in the DNA methylation profiles of adolescents born from ART [IVF or ICSI] were observed when compared to their naturally conceived, similar aged counterparts. WHAT IS KNOWN ALREADY: Short-term and longer-term studies have investigated the general health outcomes of children born from IVF treatment, albeit without common agreement as to the cause and underlying mechanisms of these adverse health findings. Growing evidence suggests that the reported adverse health outcomes in IVF-born offspring might have underlying epigenetic mechanisms. STUDY DESIGN, SIZE, DURATION: The Growing Up Healthy Study (GUHS) is a prospective study that recruited 303 adolescents and young adults, conceived through ART, to compare various long-term health outcomes and DNA methylation profiles with similar aged counterparts from Generation 2 from the Raine Study. GUHS assessments were conducted between 2013 and 2017. The effect of ART on DNA methylation levels of 231 adolescents mean age 15.96 ± 1.59 years (52.8% male) was compared to 1188 naturally conceived counterparts, 17.25 ± 0.58 years (50.9% male) from the Raine Study. PARTICIPANTS/MATERIALS, SETTING, METHODS: DNA methylation profiles from a subset of 231 adolescents (13-19.9 years) from the GUHS, generated using the Infinium Methylation Epic Bead Chip (EPIC) array were compared to 1188 profiles from the Raine Study previously measured using the Illumina 450K array. We conducted epigenome-wide association approach (EWAS) and tested for an association between the cohorts applying Firth's bias reduced logistic regression against the outcome of ART versus naturally conceived offspring. Additionally, within the GUHS cohort, we investigated differences in methylation status in fresh versus frozen embryo transfers, cause of infertility as well as IVF versus ICSI conceived offspring. Following the EWAS analysis we investigated nominally significant probes using Gene Set Enrichment Analysis (GSEA) to identify enriched biological pathways. Finally, within GUHS we compared four estimates (Horvath, Hanuum, PhenoAge [Levine], and skin Horvath) of epigenetic age and their correlation with chronological age. MAIN RESULTS AND THE ROLE OF CHANCE: Between the two cohorts, we did not identify any DNA methylation probes that reached a Bonferroni corrected P-value < 1.24E-0.7. When comparing IVF versus ICSI conceived adolescents within the GUHS cohort, after adjustment for participant age, sex, maternal smoking, multiple births, and batch effect, three methylation probes (cg15016734, cg26744878 and cg20233073) reached a Bonferroni correction of 6.31E-08. After correcting for cell count heterogeneity, two of the aforementioned probes remained significant and an additional two probes (cg 0331628 and cg 20235051) were identified. A general trend towards hypomethylation in the ICSI offspring was observed. All four measures of epigenetic age were highly correlated with chronological age and showed no evidence of accelerated epigenetic aging within their whole blood. LIMITATIONS, REASONS FOR CAUTION: The small sample size coupled with the use of whole blood, where epigenetic differences may occur in other tissue. This was corrected by the utilized statistical method that accounts for imbalanced sample size between groups and adjusting for cell count heterogeneity. Only a small portion of the methylome was analysed and rare individual differences may be missed. WIDER IMPLICATIONS OF THE FINDINGS: Our findings provide further reassurance that the effects of the ART manipulations occurring during early embryogenesis, existing in the neonatal period are indeed of a transient nature and do not persist into adolescence. However, we have not excluded that alternative epigenetic mechanisms may be at play. STUDY FUNDING/COMPETING INTEREST(S): This project was supported by NHMRC project Grant no. 1042269 and R.J.H. received funding support from Ferring Pharmaceuticals Pty Ltd. R.J.H. is the Medical Director of Fertility Specialists of Western Australia and a shareholder in Western IVF. He has received educational sponsorship from Merck Sharp & Dohme Corp.- Australia, Merck-Serono Australia Pty Ltd and Ferring Pharmaceuticals Pty Ltd. P.B. is the Scientific Director of Concept Fertility Centre, Subiaco, Western Australia. J.L.Y. is the Medical Director of PIVET Medical Centre, Perth, Western Australia. The remaining authors have no conflicts of interest.

Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification.

BACKGROUND: Machine learning is a sub-field of artificial intelligence, which utilises large data sets to make predictions for future events. Although most algorithms used in machine learning were developed as far back as the 1950s, the advent of big data in combination with dramatically increased computing power has spurred renewed interest in this technology over the last two decades. MAIN BODY: Within the medical field, machine learning is promising in the development of assistive clinical tools for detection of e.g. cancers and prediction of disease. Recent advances in deep learning technologies, a sub-discipline of machine learning that requires less user input but more data and processing power, has provided even greater promise in assisting physicians to achieve accurate diagnoses. Within the fields of genetics and its sub-field epigenetics, both prime examples of complex data, machine learning methods are on the rise, as the field of personalised medicine is aiming for treatment of the individual based on their genetic and epigenetic profiles. CONCLUSION: We now have an ever-growing number of reported epigenetic alterations in disease, and this offers a chance to increase sensitivity and specificity of future diagnostics and therapies. Currently, there are limited studies using machine learning applied to epigenetics. They pertain to a wide variety of disease states and have used mostly supervised machine learning methods.

Patterns of DNA Methylation Across the Leptin Core Promoter in Four Diverse Asian and North American Populations.

DNA methylation is the most widely studied of epigenetic mechanisms, with environmental effects recorded through patterned attachments of methyl groups along the DNA that are capable of modifying gene expression without altering the DNA sequencing. The degree to which these patterns of DNA methylation are heritable, the expected range of normality across populations, and the phenotypic relevance of pattern variation remain unclear. Genes regulating metabolic pathways appear to be vulnerable to ongoing nutritional programming over the life course, as dietary nutrients are significant environmental determinants of DNA methylation, supplying both the methyl groups and energy to generate the methylation process. Here we examine methylation patterns along a region of the metabolic gene leptin (LEP). LEP's putative functions include regulation of energy homeostasis, with its signals affecting energy intake and expenditure, adipogenesis and energy storage, lipid and glucose metabolism, bone metabolism, and reproductive endocrine function. A pattern of differential methylation across CpG sites of the LEP core promoter has been previously identified; however, any consistency of pattern or its phenotypic significance is not fully elucidated among populations. Using DNA extracted from unfractionated white blood cells of peripheral blood samples, our pilot study, divided into two parts, examined the significance of variation in DNA methylation patterns along the leptin core promoter in four populations (phase 1) and used biomarkers reflecting leptin's functional process in two of those populations, western Buryat of Siberia and the Mennonite of central Kansas, to investigate the relevance of the ethnic variation identified in the DNA methylation (phase 2). LEP's core promoter region contains both the binding site for C/EBPα (CCAAT/enhancer binding protein alpha), which tempers the final step in adipocyte maturity and capacity to synthesize leptin, and the TATA motif controlling leptin synthesis. Previous studies report that increased methylation in this region is correlated to decreased gene expression, suggesting tissue-specific methylation variation at this region ( Melzner et al. 2002 ). We hypothesized that evidence of nutritional epigenetic programming would be identified through variation in patterns of DNA methylation and that functional relevance of that variation among populations would be identified through biomarkers that reflect leptin's metabolic signals: serum leptin levels, lipoproteins of the lipid transport system, and anthropometric measures. In phase 1, our combined analyses of 313 individuals documented a distinct and consistent overall pattern of differential DNA methylation across seven CpG sites of LEP core promoter in all ethnicities and both sexes. This pattern replicates those identified in previous studies, suggesting a conserved core promoter region across populations. Phase 2 analyses of two of the four populations (n = 239), correlating methylation at the C/EBPα transcription binding site (TBS) with metabolic and anthropometric biomarkers reflecting LEP roles, showed that stature, which reflects bone growth and remodeling, was significantly and inversely correlated with the percentage of DNA methylation at this site in both sexes. We suggest that variation in DNA methylation along the LEP core promoter plays a substantial role in energy signals affecting both adipogenesis and bone metabolism.