Low Socioeconomic Status, Adverse Gene Expression Profiles, and Clinical Outcomes in Hematopoietic Stem Cell Transplant Recipients

Abstract

Purpose Low socioeconomic status (SES) is associated with adverse outcomes among unrelated donor hematopoietic stem cell transplant (HCT) recipients, but the biological mechanisms contributing to this health disparity are poorly understood. Therefore, we examined whether social environment affects expression of a stress-related gene expression profile known as the conserved transcriptional response to adversity (CTRA), which involves up-regulation of pro-inflammatory genes and down-regulation of genes involved in type I IFN response and antibody synthesis. Experimental Design We compared pre-transplant leukocyte CTRA gene expression between a group of 78 high vs. low SES recipients of unrelated donor HCT for acute myelogenous leukemia in first remission. Post hoc exploratory analyses also evaluated whether CTRA gene expression was associated with poor clinical outcomes. Results Peripheral blood mononuclear cells collected pre-HCT from low SES individuals demonstrated significant CTRA up-regulation compared to matched HCT recipients of high SES. Promoter-based bioinformatics implicated distinct patterns of transcription factor activity including increased CREB signaling and decreased IRF and GR signaling. High expression of the CTRA gene profile was also associated with increased relapse risk and decreased leukemia-free survival. Conclusions Low SES is associated with increased expression of the CTRA gene profile, and CTRA gene expression is associated with adverse HCT clinical outcomes. These findings provide a biologic framework within which to understand how social environmental conditions may influence immune function and clinical outcomes in allogeneic HCT.

Kindness in the blood: A randomized controlled trial of the gene regulatory impact of prosocial behavior

“…Second, the health significance of the present genomic findings needs to be interpreted with caution until more is known about the quantitative relationship between CTRA gene expression and disease risk in healthy populations such as this one. Even though prosocial behavior causally influenced CTRA expression in this study, and CTRA expression has been linked elsewhere to clinical health outcomes (e.g., Antoni et al, 2016;Cole et al, 2015a;Knight et al, 2016), this study contains no measures of clinical health outcomes. In addition, although we postulate that our prosocial behavior intervention informs the understanding of the link between relationships and health, we did not directly measure whether our manipulation led to objective changes in participants' relationships.…”

Patient-Reported Outcomes and Socioeconomic Status as Predictors of Clinical Outcomes after Hematopoietic Stem Cell Transplantation: A Study from the Blood and Marrow Transplant Clinical Trials Network 0902 Trial

“…Lifestyle and stress associated with low SES can activate psychobiological processes that lead to altered neural, endocrine, and immune activation [20,21]. A recent study suggests that low SES among unrelated donor HCT recipients is associated with increased gene expression patterns representative of chronic adversity [22]. This gene profile is predictive of adverse clinical outcomes including increased relapse and decreased leukemia-free survival [22].…”

“…A recent study suggests that low SES among unrelated donor HCT recipients is associated with increased gene expression patterns representative of chronic adversity [22]. This gene profile is predictive of adverse clinical outcomes including increased relapse and decreased leukemia-free survival [22]. …”

No Evidence for Differential Relations of Hedonic Well-Being and Eudaimonic Well-Being to Gene Expression: A Comment on Statistical Problems in Fredrickson et al. ()

“…Two recent studies (Knight et al, 2016;Vedhara et al, 2015) co-authored by one of the co-authors of the Fredrickson et al (2013) study (Steven W. Cole) used the same analytic method as Fredrickson et al (2013) but altered the bootstrapping method for generating standard errors for the one-sample t tests "to account for potential correlation among residuals across genes" (Knight et al, 2016, p. 71). This change to the analysis is a tacit admission that the computation of p values in study was not correct, but no corrigendum to, or retraction of, that article has appeared.…”