A shared genetic signature for common chronic pain conditions and its impact on biopsychosocial traits

Abstract

Background: The multifactorial heterogenous nature of chronic pain with its multiple comorbidities presents a formidable challenge in disentangling the aetiology underlying patient symptoms. Methods: Here, we performed genome-wide association studies (GWAS) of eight types of regional chronic pain using UK Biobank data (N=4,037-79,089 cases; N=239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. Findings: We report evidence of a shared genetic signature in common regional chronic pain types, with their genetic correlations and causal directions being broadly consistent across a wide array of biopsychosocial traits. Furthermore, we identified 5,942 significant genetic correlations, of which 570 trait pairs showed evidence of a likely causal association (|GCP| > 0.6; 5% false discovery rate), including 488 traits contributing to chronic pain while 82 were affected by pain. A range of somatic pathologies (e.g., musculoskeletal, visceral), psychiatric factors (e.g., depression, trauma, anxiety, mania, bipolar disorder), socioeconomic factors (e.g., occupation) and other medical comorbidities (e.g., cardiovascular disease) contributed to an increased risk of regional chronic pain. Conversely, each chronic pain type contributed to various other traits such as increased medication use (e.g., analgesics) and risk of ischaemic heart disease and depression. Interpretation: Findings of this data-driven study, through comprehensive analysis of a vast range of biopsychosocial factors, are indicative of a common genetic signature underlying eight regional chronic pain types. We identify a broad range of traits with genetic causal effects upon chronic pain, which may inform development of novel diagnostic and therapeutic strategies, as well as provide convergent support for various existing approaches.

Genome-wide meta-analysis conducted in three large biobanks expands the genetic landscape of lumbar disc herniations

“…In the previous studies, patients with lower socioeconomic status have been found to be more symptomatic, with worse pain outcomes, and more depression 35 . People with higher education usually have a better income level, they tend to seek treatment at an earlier stage after the onset of LDH, and they often have better pain management methods and generally healthier lifestyles 35,36 . Additionally, we noted a potential causal relationship between LDH and the frequency of tiredness in last two weeks (beta=0.02, pFDR=0.046, Fig.…”