Epigenetic predictors of time-varying exposures to childhood adversity and depression

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ABSTRACT: Depression is one of the most common, costly, and disabling mental disorders and is on track to be the leading cause of disease burden worldwide by 2030. Exposure to adversity during childhood, such as abuse, trauma, poverty, or family disruption, can have profound effects on mental health, more than doubling the risk for depression later in life. These effects are particularly deleterious when they occur during sensitive periods, developmental windows when life experiences can exert greater influences on future outcomes. Although the biological mechanisms underlying this increased vulnerability remain unknown, DNA methylation (DNAm) – a type of epigenetic modification – has emerged as a prime candidate to explain the long-term effects of childhood adversity and its links to depression. However, the predictive power of single DNAm loci is limited, and, as such, recent studies have begun to create composite DNAm risk scores (abbreviated as MRS). Yet, no studies have determined whether sensitive period effects can be integrated into MRS and the extent to which these MRS of time-varying childhood adversity can predict future depressive outcomes. Here, we propose to develop and implement novel methodologies to incorporate the time-varying effects of childhood adversity into MRS, as well as assess the ability of these MRS to explain and predict adult incident depression. We will analyze data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a longitudinal birth cohort that has collected repeated, prospective measures of childhood adversity from ages 0-11, DNAm data in adolescence (age 15-17), and repeated measures of depression between ages 18-28 (n=1,899). In aim 1, we will develop the methodologies necessary to create MRS of time-varying childhood adversity (denoted MRSADV) and determine the extent to which these MRSADV capture prior exposures to childhood adversity. To this end, we will leverage a unique and independent set of summary statistics from our recent meta-analyses of five different types of time-varying childhood adversity and DNAm, which will be used as independent weights in our MRS calculations. In aim 2, we will determine the extent to which MRSADV explain subsequent risk for incident depression, as well as compare the predictive power of MRSADV to self-reports of prior childhood adversity. In sum, this study will: (1) develop new methodologies that can be leveraged to integrate time-varying measures into MRS studies; (2) identify novel epigenetic biomarkers of childhood adversity that can be used to quantify prior exposures to adversity; and (3) determine the extent to which MRS of childhood adversity predict future psychopathology. These findings will not only provide a novel paradigm for studies of MRS and epigenetic mechanisms but will also identify biomarkers that can predict the lifelong consequences of childhood adversity, which will ultimately help target prevention and treatment efforts to people at higher risk for mental illness. The proposed research will also generate preliminary evidence towards future grants focused on socio-biological factors that link childhood adversity to mental health across the life course.