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Within-subject Changes in Methylome Profile Identify Individual Signatures of Early-life Adversity, with a Potential to Predict Neuropsychiatric Outcome

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Journal bioRxiv
Date 2024 Jan 8
PMID 38187766
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Abstract

Background: Adverse early-life experiences (ELA), including poverty, trauma and neglect, affect a majority of the world's children. Whereas the impact of ELA on cognitive and emotional health throughout the lifespan is well-established, it is not clear how distinct types of ELA influence child development, and there are no tools to predict for an individual child their vulnerability or resilience to the consequences of ELAs. Epigenetic markers including DNA-methylation profiles of peripheral cells may encode ELA and provide a predictive outcome marker. However, the rapid dynamic changes in DNA methylation in childhood and the inter-individual variance of the human genome pose barriers to identifying profiles predicting outcomes of ELA exposure. Here, we examined the relation of several dimensions of ELA to changes of DNA methylation, using a longitudinal within-subject design and a high threshold for methylation changes in the hope of mitigating the above challenges.

Methods: We analyzed DNA methylation in buccal swab samples collected twice for each of 110 infants: neonatally and at 12 months. We identified CpGs differentially methylated across time, calculated methylation changes for each child, and determined whether several indicators of ELA associated with changes of DNA methylation for individual infants. We then correlated select dimensions of ELA with methylation changes as well as with measures of executive function at age 5 years. We examined for sex differences, and derived a sex-dependent 'impact score' based on sites that most contributed to the methylation changes.

Findings: Setting a high threshold for methylation changes, we discovered that changes in methylation between two samples of an individual child reflected age-related trends towards augmented methylation, and also correlated with executive function years later. Among the tested factors and ELA dimensions, including income to needs ratios, maternal sensitivity, body mass index and sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, an interaction was observed between a measure of high early-life unpredictability and methylation changes, in presaging executive function.

Interpretation: These findings establish longitudinal, within-subject changes in methylation profiles as a signature of some types of ELA in an individual child. Notably, such changes are detectable beyond the age-associated DNA methylation dynamics. Future studies are required to determine if the methylation profile changes identified here provide a predictive marker of vulnerabilities to poorer cognitive and emotional outcomes.

References
1.
Lussier A, Zhu Y, Smith B, Simpkin A, Smith A, Suderman M . Sensitive Periods for the Effect of Childhood Adversity on DNA Methylation: Updated Results From a Prospective, Longitudinal Study. Biol Psychiatry Glob Open Sci. 2023; 3(3):567-571. PMC: 10382690. DOI: 10.1016/j.bpsgos.2022.04.002. View

2.
Simpkin A, Hemani G, Suderman M, Gaunt T, Lyttleton O, McArdle W . Prenatal and early life influences on epigenetic age in children: a study of mother-offspring pairs from two cohort studies. Hum Mol Genet. 2015; 25(1):191-201. PMC: 4690495. DOI: 10.1093/hmg/ddv456. View

3.
Szepsenwol O, Simpson J, Griskevicius V, Zamir O, Young E, Shoshani A . The effects of childhood unpredictability and harshness on emotional control and relationship quality: A life history perspective. Dev Psychopathol. 2021; 34(2):607-620. DOI: 10.1017/S0954579421001371. View

4.
McLaughlin K, Weissman D, Bitran D . Childhood Adversity and Neural Development: A Systematic Review. Annu Rev Dev Psychol. 2020; 1:277-312. PMC: 7243625. DOI: 10.1146/annurev-devpsych-121318-084950. View

5.
Horvath S, Raj K . DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet. 2018; 19(6):371-384. DOI: 10.1038/s41576-018-0004-3. View