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Cross-Disorder Genomics Data Analysis Elucidates a Shared Genetic Basis Between Major Depression and Osteoarthritis Pain.

ABSTRACT: Osteoarthritis (OA) and major depression (MD) are two debilitating disorders that frequently co-occur and affect millions of the elderly each year. Despite the greater symptom severity, poorer clinical outcomes, and increased mortality of the comorbid conditions, we have a limited understanding of their etiologic relationships. In this study, we conducted the first cross-disorder investigations of OA and MD, using genome-wide association data representing over 247K cases and 475K controls. Along with significant positive genome-wide genetic correlations (r _g = 0.299 ± 0.026, p = 9.10 × 10^-31), Mendelian randomization (MR) analysis identified a bidirectional causal effect between OA and MD (β_OA _→ _MD = 0.09, SE = 0.02, z-score p-value < 1.02 × 10^-5; β_MD _→ _OA = 0.19, SE = 0.026, p < 2.67 × 10^-13), indicating genetic variants affecting OA risk are, in part, shared with those influencing MD risk. Cross-disorder meta-analysis of OA and MD identified 56 genomic risk loci (P _meta ≤ 5 × 10^-8), which show heightened expression of the associated genes in the brain and pituitary. Gene-set enrichment analysis highlighted "mechanosensory behavior" genes (GO:0007638; P _{gene_set} = 2.45 × 10^-8) as potential biological mechanisms that simultaneously increase susceptibility to these mental and physical health conditions. Taken together, these findings show that OA and MD share common genetic risk mechanisms, one of which centers on the neural response to the sensation of mechanical stimulus. Further investigation is warranted to elaborate the etiologic mechanisms of the pleiotropic risk genes, as well as to develop early intervention and integrative clinical care of these serious conditions that disproportionally affect the aging population.

SUBMITTER: Barowsky S

PROVIDER: S-EPMC8481820 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAttachment insecurity relates to the onset and course of chronic pain via dysfunctional reactions to pain. However, few studies have investigated the proportion of insecure attachment styles in different pain conditions, and results regarding associations between attachment, pain severity, and disability in chronic pain are inconsistent. This study aims to clarify the relationships between insecure attachment and occurrence or severity of chronic pain with and without clearly defined organic cause. To detect potential differences in the importance of global and romantic attachment representations, we included both concepts in our study.Methods85 patients with medically unexplained musculoskeletal pain (UMP) and 89 patients with joint pain from osteoarthritis (OA) completed self-report measures of global and romantic attachment, pain intensity, physical functioning, and depression.ResultsPatients reporting global insecure attachment representations were more likely to suffer from medically unexplained musculoskeletal pain (OR 3.4), compared to securely attached patients. Romantic attachment did not differ between pain conditions. Pain intensity was associated with romantic attachment anxiety, and this relationship was more pronounced in the OA group compared to the UMP group. Both global and romantic attachment anxiety predicted depression, accounting for 15% and 17% of the variance, respectively. Disability was independent from attachment patterns.ConclusionsOur results indicate that global insecure attachment is associated with the experience of medically unexplained musculoskeletal pain, but not with osteoarthritis. In contrast, insecure attachment patterns seem to be linked to pain intensity and pain-related depression in unexplained musculoskeletal pain and in osteoarthritis. These findings suggest that relationship-informed focused treatment strategies may alleviate pain severity and psychological distress in chronic pain independent of underlying pathology.

Project description:ObjectivesTo analyse how comorbidity among patients with back pain, depression and osteoarthritis influences healthcare costs per patient. A special focus was made on the distribution of costs for primary healthcare compared with specialist care, hospital care and drugs.DesignPopulation-based cross-sectional study.SettingThe County of Östergötland, Sweden.PatientsData on diagnoses and healthcare costs for all 266 354 individuals between 20 and 75 years of age, who were residents of the County of Östergötland, Sweden, in the year 2006, were extracted from the local healthcare register and the national register of drug prescriptions.Main outcome measuresThe effects of comorbidity on healthcare costs were estimated as interactions in regression models that also included age, sex, number of other health conditions and education.ResultsThe largest diagnosed group was back pain (11 178 patients) followed by depression (7412 patients) and osteoarthritis (5174 patients). The largest comorbidity subgroup was the combination of back pain and depression (772 patients), followed by the combination of back pain and osteoarthritis (527 patients) and the combination of depression and osteoarthritis (206 patients). For patients having both a depression diagnosis and a back pain diagnosis, there was a significant negative interaction effect on total healthcare costs. The average healthcare costs among patients with depression and back pain was SEK 11 806 lower for a patient with both diagnoses. In this comorbidity group, there were tendencies of a positive interaction for general practitioner visits and negative interactions for all other visits and hospital days. Small or no interactions at all were seen between depression diagnoses and osteoarthritis diagnoses.ConclusionsA small increase in primary healthcare visits in comorbid back pain and depression patients was accompanied with a substantial reduction in total healthcare costs and in hospital costs. Our results can be of value in analysing the cost effects of comorbidity and how the coordination of primary and secondary care may have an impact on healthcare costs.

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Cross-Disorder Genomics Data Analysis Elucidates a Shared Genetic Basis Between Major Depression and Osteoarthritis Pain.

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