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An area of significant research focus has been on identifying factors that may distinguish between individuals who do and do not develop PTSD, including pre-trauma biological vulnerability. Not surprisingly, given the role of the stress response in posttrauma responding, many studies have examined individual differences in modulators of our response to stress, particularly the role of the hypothalamic-pituitary-adrenal (HPA) axis. HPA-axis function is influenced by genetic variation, and this variation in turn may influence PTSD risk  (Carvalho, Coimbra, Ota, Mello, & Belangero, 2017; Yehuda, Koenen, Galea, & Flory, 2011). This has led researchers interested in genetic vulnerability to PTSD to focus on variation in genes involved in the HPA axis system. Evidence for a link between PTSD and genetic variants within this system, such as a variant in ADCYAP1R1 and variants in FKBP5, has been compelling (Banerjee, Morrison, & Ressler, 2017; Smoller, 2016).

However, as with studies of other candidate genes, limitations include frequent lack of replication and often conflicting results (Cornelius et al., 2010; Smoller, 2016). There are also likely high rates of false positive findings in the literature (Koenen, 2007) due to issues such as small sample sizes and low power (Banerjee et al., 2017), differences in study design and methodology (Cornelius et al., 2010), flaws in interpretation, and publication practices (Sullivan, 2007). One approach to address the inconsistencies is to meta-analyze existing studies (Koenen, 2007), which has increased in recent years (serotonin, Gressier et al., 2013; BDNF, Bountress et al., 2017; ADCYAP1R1, Lind et al., 2017; dopamine, Li et al., 2016). Notably, though, a challenge in meta-analyzing a broad candidate gene system is the analysis of different markers/variants within genes, because few studies examine the same genetic variants, making interpretation of findings across studies difficult (Koenen, 2007). With that in mind, developing an approach to meta-analyze numerous markers within the same gene is a useful method to summarize the existing, mixed, candidate gene information and make broader conclusions with regard to the HPA axis system genes in relation to PTSD.

That was the aim of our work, to perform meta-analyses at both the level of single nucleotide polymorphisms (SNP) variants and of the genes they comprise. Existing candidate gene studies examining the main effects of HPA axis related genes associated with PTSD were identified from existing literature through PubMed and PsycINFO databases. In total, 415 article abstracts were screened; the full text of 41 articles were then reviewed, with 27 meeting initial eligibility criteria (original research, human subjects, association study of HPA axis gene, PTSD as an outcome, and trauma-exposed control group). Following further assessment, 23 unique articles across four genes were included in analyses, resulting in a total of 10 samples (9 manuscripts) included in the meta-analysis for ADCYAP1R1, 6 samples in the meta-analysis of CRHR1, 10 samples (9 manuscripts) in the meta-analysis of FKBP5, and 4 samples in the meta-analysis of NR3C1.

We first conducted SNP level meta-analyses, utilizing existing methods. Then, because traditional meta-analytic approaches do not translate to a gene level analytic approach (as different SNPs are measured in different studies for a given gene), we developed novel methods to aggregate markers in the same gene. Because there were numerous differences in variables across studies (e.g., genetic model tested, diagnosis or severity outcomes, gender and ethnicity distributions), meta-analyses by SNP were performed using a random effect. Custom R scripts were developed for the study aims, based on formulas developed specifically to conduct these analyses. Additional steps were taken for the gene level analyses. More specifically, Z-scores were combined for all SNPs from a gene in a Mahalanobis type statistic. As not all SNPs are measured in all studies and the linkage disequilibrium (LD) structure (i.e., correlations) of SNPs is different among different ethnicities/ancestries, models computed the exact correlation between SNP meta-analysis statistics in the presence of missingness using the largest observed ancestral groups with 1000 genome Phase 1 reference data (Abecasis et al., 2010). The overall covariance of the statistics in mixed ancestry studies were computed with novel formulas and scripts.

Results of the SNP meta-analyses indicated that only two of 48 variants examined (FKBP5 rs9296158, p = .001 and NR3C1 rs258747, p = .001) remained significant after Bonferroni adjustment for multiple testing (.05/total number of SNPs, p = .001) but did not retain significance in a sensitivity analysis when assuming a non-trivial rate of unreported studies. Gene level meta-analytic results showed that NR3C1 (p = .003), CRHR1 (p = .017) and FKBP5 (p = .011) yielded significant signals following Bonferroni correction (at .05/4 genes, p = .0125). Sensitivity analyses suggested that the signal in CRHR1 was marginal, while more robust signals were found for NR3C1 and FKBP5.

Overall, findings provide support at the gene level, but not the SNP-level, for HPA markers (particularly FKBP5 and NR3C1) as candidate genes associated with PTSD and help to resolve inconsistencies in the candidate gene literature. Perhaps the most important finding observed here is the valuable contribution of adopting gene-level approaches to examining the associations of markers with PTSD. Given that many markers examined within genes are explicitly intended to “tag” an area of influence rather than necessarily having a known functional SNP variation, as well as the potential for this gene-based approach to benefit from enhanced power of multiple markers, it is perhaps not surprising to observe more robust effects using a gene-based approach. Future meta-analytic studies that adopt gene based approaches will continue to inform our understanding of the potential for variation within the HPA axis to be associated with PTSD. The longstanding critique of candidate approaches is not addressed using this approach. However, meta-analyses as used here may begin to address some critiques through enhancing power to detect small individual gene effects and explicitly testing the degree to which findings may be robust to the “file drawer problem” of unpublished null results.


Abecasis, G. R., Altshuler, D., Auton, A., Brooks, L. D., Durbin, R. M., Gibbs, R. A., . . . McVean, G. A. (2010). A map of human genome variation from population-scale sequencing. Nature, 467(7319), 1061-1073. doi:10.1038/nature09534

Banerjee, S. B., Morrison, F. G., & Ressler, K. J. (2017). Genetic approaches for the study of PTSD: Advances and challenges. Neurosci Lett, 649, 139-146. doi:10.1016/j.neulet.2017.02.058

Bountress, K. E., Bacanu, S. A., Tomko, R. L., Korte, K. J., Hicks, T., Sheerin, C., . . . Amstadter, A. B. (2017). The Effects of a BDNF Val66Met Polymorphism on Posttraumatic Stress Disorder: A Meta-Analysis. Neuropsychobiology, 76(3), 136-142. doi:10.1159/000489407

Gressier, F., Calati, R., Balestri, M., Marsano, A., Alberti, S., Antypa, N., & Serretti, A. (2013). The 5-HTTLPR polymorphism and posttraumatic stress disorder: a meta-analysis. J Trauma Stress, 26(6), 645-653. doi:10.1002/jts.21855

Carvalho, C. M., Coimbra, B. M., Ota, V. K., Mello, M. F., & Belangero, S. I. (2017). Single-nucleotide polymorphisms in genes related to the hypothalamic-pituitary-adrenal axis as risk factors for posttraumatic stress disorder. Am J Med Genet B Neuropsychiatr Genet, 174(7), 671-682. doi:10.1002/ajmg.b.32564

Cornelius, J. R., Kirisci, L., Reynolds, M., Clark, D. B., Hayes, J., & Tarter, R. (2010). PTSD contributes to teen and young adult cannabis use disorders. Addict Behav, 35(2), 91-94. doi:10.1016/j.addbeh.2009.09.007

Koenen, K. C. (2007). Genetics of posttraumatic stress disorder: Review and recommendations for future studies. J Trauma Stress, 20(5), 737-750. doi:10.1002/jts.20205

Li, L., Bao, Y., He, S., Wang, G., Guan, Y., Ma, D., . . . Yang, J. (2016). The Association Between Genetic Variants in the Dopaminergic System and Posttraumatic Stress Disorder: A Meta-Analysis. Medicine (Baltimore), 95(11), e3074. doi:10.1097/md.0000000000003074

Lind, M. J., Marraccini, M. E., Sheerin, C. M., Bountress, K., Bacanu, S. A., Amstadter, A. B., & Nugent, N. R. (2017). Association of Posttraumatic Stress Disorder With rs2267735 in the ADCYAP1R1 Gene: A Meta-Analysis. J Trauma Stress, 30(4), 389-398. doi:10.1002/jts.22211

Smoller, J. W. (2016). The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders. Neuropsychopharmacology, 41(1), 297-319. doi:10.1038/npp.2015.266

Sullivan, P. F. (2007). Spurious genetic associations. Biol Psychiatry, 61(10), 1121-1126. doi:10.1016/j.biopsych.2006.11.010

Yehuda, R., Koenen, K. C., Galea, S., & Flory, J. D. (2011). The role of genes in defining a molecular biology of PTSD. Dis Markers, 30(2-3), 67-76. doi:10.3233/dma-2011-0794

Reference Article

Sheerin, C.M.*, Lind, M.J.*, Bountress, K.E., Marraccini, M.E., Amstadter**, A.B, Bacanu**, S., and Nugent**, N.R. (in press). Meta-analysis of HPA-axis genes and PTSD. Journal of Traumatic Stress. *denote co-first authorship; **denotes co-final authorship

Questions for Discussion

  1. In what way is the HPA axis system, and it’s genetic underpinnings, associated with PTSD?
  2. How does meta-analytic work help to aggregate and summarize a mixed literature on the association with PTSD?
  3. What is the take-home message regarding gene-level significant associations findings in the absence of variant/SNP-level findings?

About the Authors

Christina Sheerin, Ph.D., is an assistant professor of Psychiatry in the Virginia Institute for Psychiatric and Behavioral Genetics and Virginia Commonwealth University. Her research focuses on the characterization of biologic, genetic, and psychosocial underpinnings of the effects of trauma, primarily PTSD and alcohol use disorder and their comorbidity.
Ananda Amstadter, Ph.D., is an associate professor Psychiatry, Psychology, and Human Genetics in the Virginia Institute for Psychiatric and Behavioral Genetics and Virginia Commonwealth University. Her program of research focuses on the identification of risk and resiliency factors, biologic and psychosocial in nature, for traumatic-stress related conditions with a focus on PTSD and alcohol use disorder.