Harvey, Hollie
(2017)
Epidemiology and genetics of catastrophizing and pain in OA.
PhD thesis, University of Nottingham.
Abstract
Background:
Pain is the main reason patients present with Osteoarthritis (OA). There are many risk factors for increased pain but one risk factor that is the focus of this thesis is catastrophizing. There is a discrepancy between the amount of radiographic damage to the joint and the pain intensity felt by the OA patient, which leads to the hypothesis that there must be other non-structural factors such as catastrophizing that could explain this discrepancy.
Objectives:
(1) To assess the effect of catastrophizing on joint and body pain in individuals who have undergone total joint replacement surgery after accounting for sleep quality, anxiety and depression in people diagnosed with large joint OA and controls. X-rays and resulting K/L grade also used to account for joint damage.
(2) To identify if there are specific genes and pathways that could explain the relationship between catastrophizing and pain, also whether catastrophizing is a trait in its own right which is not dependent on depression or bad quality sleep.
(3) To identify genetic factors which contribute to the effect of catastrophizing on pain intensity in OA by comparing those with symptomatic OA to those with asymptomatic OA.
Methods:
Pain post- Total Joint Replacement (TJR) (Chapter 3): This is a case-control study design. Cases were derived from the Nottingham genetics of OA study (NGOAS) and the Genetics of Osteoarthritis and Lifestyle Study (GOAL) cohorts that have undergone joint replacement. Controls were derived from participants in the GOAL cohort that were selected as controls for OA. 1093 individuals from the NGOAS cohort who had been diagnosed with knee or hip OA were recruited from secondary care (82% post-total joint replacement (TJR) none on waiting list) and completed a questionnaire which included items on: joint pain, neuropathic pain like symptoms (using the painDETECT questionnaire), anxiety (using the hospital anxiety and depression scale (HADS) questionnaire), depression (using the HADS questionnaire) and the 13-item pain catastrophizing scale (PCS). A similar questionnaire was sent to participants from a case control OA study known as the GOAL involving 679 cases all with hip or knee OA (59.7% post-TJR, none on waiting list) and 402 non-OA controls. TJR used as cases due to this being the end point of OA with those undergoing TJR most likely in pain from OA.
High pain catastrophizing was defined as being in the top tertile of the PCS (score≥9).
SPSS was then used to calculate descriptive statistics such as percentage of participants that were female, mean age, BMI. This would give a picture of the cohort being used. Then binary logistic regressions were used to calculate odds ratios (ORs) for sleep, depression, anxiety and catastrophizing whilst adjusting for confounding factors such as age, BMI, gender.
Genetics (Chapter 4 and 5): Quantile-Quantile (QQ) and Manhattan plots were produced using R to quality test the genomic data. A Manhattan plot is a type of scatter plot, usually used to display data with a large number of data-points - many of non-zero amplitude, and with a distribution of higher-magnitude values, for instance in genome-wide association studies (GWAS). The statistics program R (version 3.0.2) was used to create Manhattan and QQ plots using the “ggplot2” library and “qqplot” script.
A genome wide association scan (GWAS) and single nucleotide polymorphism (SNP) extractions, conducted using Plink, were carried out on a subset of 1113 post TJR cases from the NGOAS cohort and pathway analysis was then conducted based on significant SNPs found in the GWAS.
In chapter 4 replication and meta-analysis were then carried out using a separate cohort of 679 participants, taken from the GOAL study.
Results:
Pain post- total joint replacement (TJR) (Chapter 3): The prevalence of high catastrophizing was not significantly higher in OA and post TJR cases (36.8%) than in controls (33.1%)(p<0.07), however as controls were from intravenous urography (IVU) clinics they would have higher levels of cardio-vascular disease, stroke, kidney disease for example than general population. The main factors associated with catastrophizing were older age, higher body mass index, high pain intensity, anxiety, depression and multiple regional pain. High catastrophizing was associated with increased risk of severe joint (hip or knee) pain after adjustment for sleep quality, anxiety and depression (OR= 2.99, 95% CI= 2.20-4.04, p< 1.54E-12). Similarly, high catastrophizing was associated with body pain (OR=1.47, CI=1.16-1.86, P<0.0002) and neuropathic-like pain symptoms (OR=5.35, CI=4.16-6.90, P<1.42E-35). I also explored if these associations with pain were due to the presence of comorbidities which are common in OA patients and post-TJR. I did find that pain catastrophizing scores were also associated with cardiovascular disease (CVD) after adjustment for depression and sleep quality as well as BMI, age and gender (OR= 1.44, 95% CI= 1.14-1.81, p< 0.001).
Genetics (Chapter 4 and 5): Several SNPs were linked to high catastrophizing scores with a p-value <0.00005.
ADRA2C was the only gene associated with catastrophizing that replicated in chapter 4 after meta-analysis. This variant was associated with OR=0.67, 95% CI= 0.56-0.80, p-value=7.8x10[-6]. It is involved in the formation of adrenergic receptors and therefore the regulation of possibly many pain pathways including the sympathetic nervous system and the hypothalamic–pituitary–adrenal axis as well as being required for normal presynaptic control of transmitter release in the heart.
PRR20 was another interesting finding in chapter 4. It is involved in dopamine receptors, so possibly influencing that particular pain pathway.
These data demonstrate that catastrophizing does influence pain intensity and implicates certain molecular pathways that may be involved in this relationship.
LEPRE1 and COL6A1 are both implicated in chapter 5. Both of these genes are involved in collagen formation and destruction thereby could affect the progression of OA and joint structure leading to pain. LEPRE1 is further known as one of the genetic causes of Osteogenesis imperfecta type VIII another bone formation disorder.
Conclusion:
Pain catastrophizing is associated with joint and body pain in individuals with OA after TJR and this effect is not mediated by sleep quality, anxiety or depression. Therefore catastrophizing can be said to be a trait in its own right.
Many genes and pain pathways were implicated by the genetics studies, mainly involving adrenaline and dopamine, so more focus on these neurotransmitters could be suggested for future study.
Another interesting finding that could be investigated further is the link between cardiovascular disorders and catastrophizing as this is a relatively unexplored area, made more interesting by the finding of ADRA2C both indicating involvement of the sympathetic nervous system and other central mechanisms.
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