Publications by authors named "M J Logue"
Article Synopsis
- The study explores the biological differences linked to PTSD by examining DNA methylation changes in blood, suggesting they could indicate susceptibility or effects of trauma.
- Conducted by the Psychiatric Genomics Consortium, the research included nearly 5,100 participants to identify specific genetic markers associated with PTSD.
- Results showed 11 significant CpG sites related to PTSD, with some also showing correlations between blood and brain tissue methylation, highlighting their potential role in understanding PTSD biology.
Background: The age distribution and diversity of the VA Million Veteran Program (MVP) cohort make it a valuable resource for studying the genetics of Alzheimer's disease (AD) and related dementias (ADRD).
Objective: We present and evaluate the performance of several International Classification of Diseases (ICD) code-based classification algorithms for AD, ADRD, and dementia for use in MVP genetic studies and other studies using VA electronic medical record (EMR) data. These were benchmarked relative to existing ICD algorithms and AD-medication-identified cases.
Chronic graft-versus-host disease (cGVHD) represents a common long-term complication after allogeneic hematopoietic stem cell transplantation (HSCT). It imposes a significant morbidity burden and is the leading cause of non-relapse mortality among long-term HSCT survivors. cGVHD can manifest in nearly any organ, severely affecting the quality of life of a transplant survivor.
View Article and Find Full Text PDFGenetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for 34 brain regions recently reported in the ENIGMA cortical GWAS.
View Article and Find Full Text PDFArticle Synopsis
- Researchers aimed to create and validate Methylation Risk Scores (MRS) using machine learning to identify individuals at risk for PTSD based on genomic and trauma exposure data.
- The study developed three models: eMRS (which combines trauma exposure and methylation data), MoRS (which relies only on methylation data), and MoRSAE (which adjusts MoRS for trauma exposure).
- The eMRS model showed the best performance with a 92% accuracy, and all models were able to predict post-deployment PTSD significantly, suggesting that including trauma exposure improves risk assessment.