RESUMO
ABSTRACT: Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulatory technique with the potential to provide pain relief. However, tDCS effects on pain are variable across existing studies, possibly related to differences in stimulation protocols and expectancy effects. We investigated the independent and joint effects of contralateral motor cortex tDCS (anodal vs cathodal) and socially induced expectations (analgesia vs hyperalgesia) about tDCS on thermal pain. We employed a double-blind, randomized 2 × 2 factorial cross-over design, with 5 sessions per participant on separate days. After calibration in Session 1, Sessions 2 to 5 crossed anodal or cathodal tDCS (20 minutes 2 mA) with socially induced analgesic or hyperalgesic expectations, with 6 to 7 days between the sessions. The social manipulation involved videos of previous "participants" (confederates) describing tDCS as inducing a low-pain state ("analgesic expectancy") or hypersensitivity to sensation ("hyperalgesic expectancy"). Anodal tDCS reduced pain compared with cathodal stimulation (F(1,19.9) = 19.53, P < 0.001, Cohen d = 0.86) and analgesic expectancy reduced pain compared with hyperalgesic expectancy (F(1,19.8) = 5.62, P = 0.027, Cohen d = 0.56). There was no significant interaction between tDCS and social expectations. Effects of social suggestions were related to expectations, whereas tDCS effects were unrelated to expectancies. The observed additive effects provide novel evidence that tDCS and socially induced expectations operate through independent processes. They extend clinical tDCS studies by showing tDCS effects on controlled nociceptive pain independent of expectancy effects. In addition, they show that social suggestions about neurostimulation effects can elicit potent placebo effects.
RESUMO
ABSTRACT: Chronic pain conditions frequently co-occur, suggesting common risks and paths to prevention and treatment. Previous studies have reported genetic correlations among specific groups of pain conditions and reported genetic risk for within-individual multisite pain counts (≤7). Here, we identified genetic risk for multiple distinct pain disorders across individuals using 24 chronic pain conditions and genomic structural equation modeling (Genomic SEM). First, we ran individual genome-wide association studies (GWASs) on all 24 conditions in the UK Biobank ( N ≤ 436,000) and estimated their pairwise genetic correlations. Then we used these correlations to model their genetic factor structure in Genomic SEM, using both hypothesis- and data-driven exploratory approaches. A complementary network analysis enabled us to visualize these genetic relationships in an unstructured manner. Genomic SEM analysis revealed a general factor explaining most of the shared genetic variance across all pain conditions and a second, more specific factor explaining genetic covariance across musculoskeletal pain conditions. Network analysis revealed a large cluster of conditions and identified arthropathic, back, and neck pain as potential hubs for cross-condition chronic pain. Additionally, we ran GWASs on both factors extracted in Genomic SEM and annotated them functionally. Annotation identified pathways associated with organogenesis, metabolism, transcription, and DNA repair, with overrepresentation of strongly associated genes exclusively in brain tissues. Cross-reference with previous GWASs showed genetic overlap with cognition, mood, and brain structure. These results identify common genetic risks and suggest neurobiological and psychosocial mechanisms that should be targeted to prevent and treat cross-condition chronic pain.