Associations between the development of PTSD symptoms and longitudinal changes in the DNA methylome of deployed military servicemen: A comparison with polygenic risk scores

Prominent genetic variants and epigenetic changes in post-traumatic stress disorder among combat veterans

Post-traumatic stress disorder (PTSD) is one of the most widespread and disabling psychiatric disorders among combat veterans. Substantial interindividual variability in susceptibility to PTSD suggests the presence of different risk factors for this disorder. Twin and family studies confirm genetic factors as important risk factors for PTSD. In addition to genetic factors, epigenetic factors, especially DNA methylation, can be considered as a potential mechanism in changing the risk of PTSD. So far, many genetic and epigenetic association studies have been conducted in relation to PTSD. In genetic studies, many single nucleotide polymorphisms have been identified as PTSD risk factors. Meanwhile, the variations in catecholamines-related genes, serotonin transporter and receptors, brain-derived neurotrophic factor, inflammatory factors, and apolipoprotein E are the most prominent candidates. CpG methylation in the upstream regions of many genes is also considered a PTSD risk factor. Accurate identification of genetic and epigenetic changes associated with PTSD can lead to the presentation of suitable biomarkers for susceptible individuals to this disorder. This study aimed to delineate prominent genetic variations and epigenetic changes associated with post-traumatic stress disorder in military veterans who have experienced combat, focusing on genetic and epigenetic association studies.

Within-subject changes in methylome profile identify individual signatures of early-life adversity, with a potential to predict neuropsychiatric outcome

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.

A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking

Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components from CpG-level data as input for biological age prediction. Our retrained principal-component versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or prior knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of principal component-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies, and clinical trials of aging interventions.