Epigenome-wide association of PTSD from heterogeneous cohorts with a common multi-site analysis pipeline.
Andrew D RatanatharathornMarco P BoksAdam X MaihoferAllison E AielloAnanda B AmstadterAllison E Ashley-KochDewleen G BakerJean C BeckhamEvelyn BrometMichelle DennisMelanie E GarrettElbert GeuzeGuia GuffantiMichael A HauserVarun KilaruNathan A KimbrelKarestan C KoenenPei-Fen KuanMark W LogueBenjamin J LuftMark W MillerColter MitchellNicole R NugentKerry J ResslerBart P F RuttenMurray B SteinEric VermettenChristiaan H VinkersNagy A Youssefnull nullnull nullMonica UddinCaroline M NievergeltAlicia K SmithPublished in: American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics (2017)
Compelling evidence suggests that epigenetic mechanisms such as DNA methylation play a role in stress regulation and in the etiologic basis of stress related disorders such as Post traumatic Stress Disorder (PTSD). Here we describe the purpose and methods of an international consortium that was developed to study the role of epigenetics in PTSD. Inspired by the approach used in the Psychiatric Genomics Consortium, we brought together investigators representing seven cohorts with a collective sample size of N = 1147 that included detailed information on trauma exposure, PTSD symptoms, and genome-wide DNA methylation data. The objective of this consortium is to increase the analytical sample size by pooling data and combining expertise so that DNA methylation patterns associated with PTSD can be identified. Several quality control and analytical pipelines were evaluated for their control of genomic inflation and technical artifacts with a joint analysis procedure established to derive comparable data over the cohorts for meta-analysis. We propose methods to deal with ancestry population stratification and type I error inflation and discuss the advantages and disadvantages of applying robust error estimates. To evaluate our pipeline, we report results from an epigenome-wide association study (EWAS) of age, which is a well-characterized phenotype with known epigenetic associations. Overall, while EWAS are highly complex and subject to similar challenges as genome-wide association studies (GWAS), we demonstrate that an epigenetic meta-analysis with a relatively modest sample size can be well-powered to identify epigenetic associations. Our pipeline can be used as a framework for consortium efforts for EWAS.
Keyphrases
- single cell
- dna methylation
- genome wide
- systematic review
- gene expression
- social support
- posttraumatic stress disorder
- copy number
- quality control
- electronic health record
- case control
- big data
- genome wide association
- meta analyses
- depressive symptoms
- randomized controlled trial
- magnetic resonance
- mental health
- computed tomography
- machine learning
- healthcare
- physical activity
- social media
- liquid chromatography
- minimally invasive
- quality improvement
- mass spectrometry
- artificial intelligence
- sleep quality