Narrative centrality and negative affectivity: independent and interactive contributors to stress reactions.

Reactions to stressful negative events have long been studied using approaches based on either the narrative interpretation of the event or the traits of the individual. Here, we integrate these 2 approaches by using individual-differences measures of both the narrative interpretation of the stressful event as central to one's life and the personality characteristic of negative affectivity. We show that they each have independent contributions to stress reactions and that high levels on both produce greater than additive effects. The effects on posttraumatic stress symptoms are substantial for both undergraduates (Study 1, n = 2,296; Study 3, n = 488) and veterans (Study 2, n = 104), with mean levels for participants low on both measures near floor on posttraumatic stress symptoms and those high on both measures scoring at or above diagnostic thresholds. Study 3 included 3 measures of narrative centrality and 3 of negative affectivity to demonstrate that the effects were not limited to a single measure. In Study 4 (n = 987), measures associated with symptoms of posttraumatic stress correlated substantially with either measures of narrative centrality or measures of negative affectivity. The concepts of narrative centrality and negative affectivity and the results are consistent with findings from clinical populations using similar measures and with current approaches to therapy. In broad nonclinical populations, such as those used here, the results suggest that we might be able to substantially increase our ability to account for the severity of stress response by including both concepts.

Integrated pathway and epistasis analysis reveals interactive effect of genetic variants at TERF1 and AFAP1L2 loci on melanoma risk.

Genome-wide association studies (GWASs) have characterized 13 loci associated with melanoma, which only account for a small part of melanoma risk. To identify new genes with too small an effect to be detected individually but which collectively influence melanoma risk and/or show interactive effects, we used a two-step analysis strategy including pathway analysis of genome-wide SNP data, in a first step, and epistasis analysis within significant pathways, in a second step. Pathway analysis, using the gene-set enrichment analysis (GSEA) approach and the gene ontology (GO) database, was applied to the outcomes of MELARISK (3,976 subjects) and MDACC (2,827 subjects) GWASs. Cross-gene SNP-SNP interaction analysis within melanoma-associated GOs was performed using the INTERSNP software. Five GO categories were significantly enriched in genes associated with melanoma (false discovery rate ≤ 5% in both studies): response to light stimulus, regulation of mitotic cell cycle, induction of programmed cell death, cytokine activity and oxidative phosphorylation. Epistasis analysis, within each of the five significant GOs, showed significant evidence for interaction for one SNP pair at TERF1 and AFAP1L2 loci (pmeta-int  = 2.0 × 10(-7) , which met both the pathway and overall multiple-testing corrected thresholds that are equal to 9.8 × 10(-7) and 2.0 × 10(-7) , respectively) and suggestive evidence for another pair involving correlated SNPs at the same loci (pmeta-int  = 3.6 × 10(-6) ). This interaction has important biological relevance given the key role of TERF1 in telomere biology and the reported physical interaction between TERF1 and AFAP1L2 proteins. This finding brings a novel piece of evidence for the emerging role of telomere dysfunction into melanoma development.