The causal role of smoking on the risk of hip or knee replacement due to primary osteoarthritis: a Mendelian randomisation analysis of the HUNT study

The causal impact of smoking behavior on osteoarthritis: a Mendelian randomization analysis

Objective

Although smoking and osteoarthritis (OA) have been linked in a number of studies, the exact cause of the association is still unknown and the conclusion is controversial. The purpose of this study was to use Mendelian randomization (MR) analysis to investigate the causal relationship between smoking phenotypes and OA risk from a genetically informed standpoint.

Methods

As instrumental variables (IVs) based on single nucleotide polymorphisms (SNPs), this study used the summary-level data of corresponding genome-wide association study (GWAS) for five smoking phenotypes involving 1,694,781 samples. The outcomes comprised both a discovery and a replication cohort. The discovery MR analysis involved 12 OA traits (177,517 cases and 649,173 controls) while the replication MR analysis incorporated an additional OA GWAS dataset consisting of 36,185 cases and 135,185 controls. The main analytic approach we used was the inverse variance weighted (IVW) method. MR Egger, Weighted median, Weighted mode, and Simple mode were among the other methods that were tested. We conducted meta-analysis to combine the MR results. To confirm the robustness of the results, sensitivity analysis using Leave-One-Out (LOO), level pleiotropy testing (MR Egger intercept test and MR-PRESSO), and heterogeneity testing were performed.

Results

Summary-level MR analysis revealed a positive correlation between genetic predisposition for smoking and the likelihood of developing OA. The meta-analysis merge showed that smoking initiation increased the risk of knee OA by 20%, hip OA by 16%, and knee/hip OA by 19% (all p < 0.001). Similarly, lifetime smoking elevated the risk of knee OA by 101%, hip OA by 55%, and knee/hip OA by 84% (all p < 0.001). The sensitivity analysis's findings reinforced the reliability of these findings.

Conclusion

According to our research, smoking increases the likelihood of developing OA from a genetic standpoint. Reducing tobacco use could, therefore, be beneficial in lowering the incidence of OA.

The effect of tobacco use on clinical outcomes in total knee arthroplasty patients

Introduction

Previous research has established that smoking significantly increases the complication rate of total knee arthroplasty (TKA). Risk of infection, prosthetic loosening, fractures, wound healing issues, and revisions are increased in smokers, but research is limited on the long-term clinical outcomes of pain, range of motion, stability, and functionality between smokers, nonsmokers, and former smokers, specifically utilizing Knee Society Scores (KSS).

Methods

This was a retrospective chart review of primary TKA patients (n = 203) at a single university hospital. The patients were divided by smoking status: nonsmoker, current smoker, or former smoker. One-way analysis of variance with associated f ratios was performed to assess variance in KSS by smoking status over time. Relative risk ratio analyses were employed to assess patients' predictive risk of acquiring postoperative infection and requiring additional surgery following TKA based on smoking status.

Results

Postoperative KSS were significantly lower in the smoker group compared to nonsmokers and former smokers at 6 weeks and 1 year. For every 20 months a former smoker used tobacco, an approximate 1-point decrease in KSS was expected. The relative risk ratios for postoperative infection rates and patients requiring additional surgery were 2.13 and 1.44, respectively, when current smokers were compared to nonsmokers.

Conclusions

This analysis found that current smokers had lower KSS and higher infection rates following TKA when compared to nonsmoking controls. In addition, increased duration of smoking was correlated with poorer outcomes within the former smoker group.

Association of smoking with knee osteoarthritis structural defects and symptoms: an individual participant data meta-analysis

Prior meta-analyses have suggested a protective link between smoking and knee osteoarthritis (KOA), but they relied on aggregate data, potentially obscuring the true relationship. To address this limitation, we conducted an Individual Participant Data (IPD) meta-analysis using data from three large cohorts: the Osteoarthritis Initiative (OAI), the Multicenter Osteoarthritis Study (MOST), and the Cohort Hip and Cohort Knee (CHECK) study. Participants from 16 centers in the USA and Netherlands were categorized as current, former, or never smokers. We assessed six outcomes, three related to structural changes over 4-5 years of follow-up, and three related to changes in KOA symptoms over 2-2.5 years, 5 years, and 7-8 years of follow-up. First, the incidence of radiographic KOA was evaluated in 10,072 knees, defined as having a Kellgren-Lawrence grade ≥ 2 ('radiographic KOA') at follow-up but not at baseline. Second, the progression of radiographic KOA was evaluated in 5274 knees, defined as an increase in Kellgren-Lawrence grade between baseline and follow-up in knees that had radiographic KOA at baseline. Third, the incidence of symptomatic KOA was evaluated in 12,910 knees, defined as having radiographic KOA in addition to symptoms at follow-up but not at baseline. Fourth, fifth, and sixth, we investigated changes between baseline and all follow-ups in scores for the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) subscales of pain, disability, and stiffness (in 2640 knees). There were no differences between smoking groups in any of these six outcomes. Our study, leveraging data from three large cohorts and the advantages of IPD, finds no evidence that smoking offers any protection against KOA, refuting the notion that smoking may benefit joint health.

A Guide to Understanding Mendelian Randomization Studies

Epidemiology provides a powerful framework for characterizing exposure-disease relationships, but its utility for making causal inferences is limited because epidemiologic data are observational in nature and subject to biases stemming from undetected confounding variables and reverse causation. Mendelian randomization (MR) is an increasingly popular method used to circumvent these limitations. MR uses genetic variants, or instruments, as a natural experiment to proxy an exposure, thus allowing estimation of causal effects upon an outcome that are minimally affected by the usual biases present in epidemiologic studies. Notably, MR relies on three core assumptions related to the selection of the genetic instruments, and adherence to these assumptions must be carefully evaluated to assess the validity of the causal estimates. The goal of this review is to provide readers with a basic understanding of MR studies and how to read and evaluate them. Specifically, we outline the basics of how MR analysis is conducted, the assumptions underlying instrument selection, and how to assess the quality of MR studies.

Causal relationship between periodontal disease-related phenotype and knee osteoarthritis: A two-sample mendelian randomization analysis

OBJECTIVE

This study aimed to explore the bidirectional causal relationship between periodontal disease-related phenotype (PDRP) and knee osteoarthritis (KOA) in a European population using a two-sample Mendelian Randomization (MR) approach.

METHODS

We leveraged publicly available GWAS summary statistics for PDRP (n = 975) and KOA (n = 403,124), assessing their roles as both exposures and outcomes. Our comprehensive MR analysis employed various methods, including inverse variance weighting (IVW), weighted median, Egger regression, simple mode, and weighted mode, to enhance the robustness of our findings. To ensure the reliability of our instrumental variables, we implemented a rigorous screening process based on p-values and F-values, utilized Phenoscanner to investigate potential confounders, and conducted sensitivity analyses.

RESULTS

Our analysis identified five SNPs associated with PDRP and three SNPs with KOA, all surpassing the genome-wide significance threshold, as instrumental variables. The IVW method demonstrated a significant causal relationship from PDRP to KOA (beta = 0.013, SE = 0.007, P = 0.035), without evidence of directional pleiotropy (MR-Egger regression intercept = 0.021, P = 0.706). No support was found for reverse causality from KOA to PDRP, as further MR analyses yielded non-significant P-values. Additionally, funnel plots and Cochran's Q test detected no significant heterogeneity or directional pleiotropy, confirming the robustness of our results. In multivariate analysis, when considering smoking, alcohol consumption, BMI collectively no direct causal relationship between KOA and PDRP. Conversely, smoking and higher BMI were independently associated with an increased risk of KOA.

CONCLUSION

In conclusion, our analysis revealed no direct causal relationship from KOA to PDRP. However, a causal relationship from PDRP to KOA was observed. Notably, when adjusting for potential confounders like smoking, alcohol intake, and BMI, both the causal connection from PDRP to KOA and the inverse relationship were not substantiated.

Causal Factors for Osteoarthritis: A Scoping Review of Mendelian Randomization Studies

OBJECTIVE

Mendelian randomization (MR) has increasingly been utilized as a tool for establishing causal relations between modifiable exposures and osteoarthritis (OA). The goal of this review was to summarize available MR studies of OA that evaluate the causal role of modifiable risk factors on OA.

METHODS

This review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews model. We performed a literature search for relevant studies published before December 2021 across multiple databases using the search terms "osteoarthritis" and ("Mendelian randomization" or "polygenic risk score"). We reported the MR estimates of causal associations between exposures and OA and then assessed methodologic quality of abstracted studies according to their efforts to validate the three key MR assumptions.

RESULTS

Our search identified 45 studies reporting on 141 exposure-association analyses. All studies performed a formal instrumental variable analysis to estimate the causal effect of exposure on OA. Causal associations (P < 0.05) were reported in 60 of these analyses representing 36 unique publications, and MR-Egger sensitivity analyses were performed in 45 of these analyses. MR studies provided support for causal associations of OA with increased levels of adiposity, coffee consumption, bone mineral density, and sleep disturbance, and decreased levels of serum calcium and low-density lipoprotein cholesterol.

CONCLUSION

These results highlight the potential benefits of weight reduction and improvement of sleep quality to reduce the risk of OA and call for a better understanding of the relations of coffee consumption and serum calcium to OA risk.

The Causal Association between Alcohol, Smoking, Coffee Consumption, and the Risk of Arthritis: A Meta-Analysis of Mendelian Randomization Studies

Objective: To evaluate the genetic causality between alcohol intake, smoking, coffee consumption, and arthritis. Methods: Mendelian randomization (MR) studies with alcohol, smoking, and coffee consumption behaviors as exposures, and osteoarthritis (OA) and rheumatoid arthritis (RA) as outcomes were retrieved from up to July 2023. Two researchers with relevant professional backgrounds independently assessed the quality and extracted data from the included studies. Meanwhile, we applied MR analyses of four lifestyle exposures and five arthritis outcomes (two for OA and three for RA) with gene-wide association study (GWAS) data that were different from the included studies, and the results were also included in the meta-analysis. Statistical analyses were performed using Stata 16.0 and R software version 4.3.1. Results: A total of 84 studies were assessed. Of these, 11 were selected for meta-analysis. As a whole, the included studies were considered to be at a low risk of bias and were of high quality. Results of the meta-analysis showed no significant genetic causality between alcohol intake and arthritis (odds ratio (OR): 1.02 (0.94-1.11)). Smoking and arthritis had a positive genetic causal association (OR: 1.44 (1.27-1.64)) with both OA (1.44 (1.22-1.71)) and RA (1.37 (1.26-1.50)). Coffee consumption and arthritis also had a positive genetic causal association (OR: 1.02 (1.01-1.03)). Results from the subgroup analysis showed a positive genetic causality between coffee consumption and both OA (OR: 1.02 (1.00-1.03)) and RA (OR: 1.56 (1.19-2.05)). Conclusion: There is positive genetic causality between smoking and coffee consumption and arthritis (OA and RA), while there is insufficient evidence for genetic causality between alcohol intake and arthritis.

How to Distinguish Correlation From Causation in Orthopaedic Research

Correlations in observational studies are commonly misinterpreted as causation. Although correlation is necessary to establish a causal relationship between two variables, correlations may also arise due to chance, reverse causality, or confounding. There are several methods available to orthopaedic researchers to determine whether the observed correlations are causal. These methods depend on the key components of the study including, but not limited to, study design and data availability on confounders. In this article, we illustrate the main concepts surrounding correlation and causation using intuitive real-world examples from the orthopaedic literature. Please visit the following https://www.youtube.com/watch?v=WW7pFudZbHA&t=52s for a video that explains the highlights of the paper in practical terms.

Mendelian Randomization Studies of Lifestyle-Related Risk Factors for Osteoarthritis: A PRISMA Review and Meta-Analysis

Risk factors for osteoarthritis (OA) often exert effects over protracted time-courses. Mendelian randomization (MR) studies therefore have an advantage over conventional observational studies when studying the causal effect of long-term lifestyle-related risk factors on OA. However, given the heterogeneous design of existing MR studies on OA, the reported causal estimates of these effects remain inconsistent, thus obscuring the true extent of the biological effects of OA lifestyle-risk factors. We conducted a PRISMA systematic review and specifically included MR studies that investigated the causal effect between lifestyle-related risk factors and OA, where causal estimates for various lifestyle factors were pooled for meta-analysis. Quality of studies was assessed according to STROBE-MR guidelines. A total of 1576 studies were evaluated and 23 were included. Overall, the studies included were of high quality and had a low risk of bias. Our meta-analysis demonstrates the positive causal effect of BMI (ORIVW-random effects 1.49 [1.23-1.80]) and negative causal effects of serum calcium (ORIVW-random effects 0.69 [0.57-0.83]) and LDL levels (ORIVW-random effects 0.93 [0.90-0.96]) on OA. Despite the heterogeneous designs and estimates of causal effects provided by various MR studies, our meta-analysis suggests that lifestyle-related risk factors in the form of BMI, serum calcium, and LDL have true biological effects on the development of OA.

Association Between History of Gestational Diabetes Mellitus and the Risk of Arthritis in Women

Objective

The association between gestational diabetes mellitus (GDM) and the risk of arthritis has not been reported. GDM increases the risk of long-term complications including diabetes and metabolic syndrome that are positively associated with the risk of arthritis. This study aimed to explore the association between GDM and the risk of arthritis.

Methods

Women (age ≥ 20 years) who had delivered at least one live birth were included from the 2007 to 2018 National Health and Nutrition Examination Survey cohort (N = 11,997). Patients who had a history of GDM and arthritis were identified by in-home interview. Subgroup analyses were conducted by arthritis types and status of obesity, current diabetes, metabolic syndrome, smoking, alcohol drinking, and physical activity.

Results

GDM was associated with increased odds of arthritis [multivariable-adjusted odds ratio (95% confidence interval): 1.31 (1.06–1.62)], and the result was similar in sensitivity analysis with further adjustment for metabolic syndrome [1.30 (1.05–1.60)]. In subgroup analyses, GDM was associated with increased odds of osteoarthritis [1.47 (1.05–2.06)], while no association was observed with rheumatoid arthritis [1.04 (0.69–1.57)] and other types [1.26 (0.94–1.68)]. GDM was associated with increased odds of arthritis in women without metabolic syndrome [1.34 (1.00–1.78)] and diabetes [1.35 (1.03–1.76)], in obese individuals [1.64 (1.24–2.16)], current/former smokers [1.43 (1.05–1.95)], and current drinkers [1.76 (1.00–3.14)], and in individuals engaging in higher levels of physical activity [1.53 (1.06–2.20)].

Conclusions

GDM was associated with increased odds of arthritis, and the association was independent of type 2 diabetes and metabolic syndrome.

The associations of implant and patient factors with migration of the tibial component differ by sex : a radiostereometric study on more than 400 total knee arthroplasties

AIMS

Thresholds of acceptable early migration of the components in total knee arthroplasty (TKA) have traditionally ignored the effects of patient and implant factors that may influence migration. The aim of this study was to determine which of these factors are associated with overall longitudinal migration of well-fixed tibial components following TKA.

METHODS

Radiostereometric analysis (RSA) data over a two-year period were available for 419 successful primary TKAs (267 cemented and 152 uncemented in 257 female and 162 male patients). Longitudinal analysis of data using marginal models was performed to examine the associations of patient factors (age, sex, BMI, smoking status) and implant factors (cemented or uncemented, the size of the implant) with maximum total point motion (MTPM) migration. Analyses were also performed on subgroups based on sex and fixation.

RESULTS

In the overall group, only fixation was significantly associated with migration (p < 0.001). For uncemented tibial components in males, smoking was significantly associated with lower migration (p = 0.030) and BMI approached significance (p = 0.061). For females with uncemented components, smoking (p = 0.081) and age (p = 0.063) approached significance and were both associated with increased migration. The small number of self-reported smokers in this study warrants cautious interpretation and further investigation. For cemented components in females, larger sizes of tibial component were significantly associated with increased migration (p = 0.004). No factors were significant for cemented components in males.

CONCLUSION

The migration of uncemented tibial components was more sensitive to patient factors than cemented implants. These differences were not consistent by sex, suggesting that it may be of value to evaluate female and male patients separately following TKA. Cite this article: Bone Joint J 2022;104-B(4):444-451.

Cardiometabolic traits mediating the effect of education on osteoarthritis risk: a Mendelian randomization study

OBJECTIVE

To investigate which cardiometabolic factors underlie clustering of osteoarthritis (OA) with cardiovascular disease, and the extent to which these mediate an effect of education.

DESIGN

Genome-wide association study (GWAS) of OA was performed in UK Biobank (60,800 cases and 328,251 controls) to obtain genetic association estimates for OA risk. Genetic instruments and association estimates for body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), smoking and education were obtained from existing GWAS summary data (sample sizes 188,577-866,834 individuals). Two-sample Mendelian randomization (MR) analyses were performed to investigate the effects of exposure traits on OA risk. MR mediation analyses were undertaken to investigate whether the cardiometabolic traits mediate any effect of education on OA risk.

RESULTS

MR analyses identified protective effects of higher genetically predicted education (main MR analysis odds ratio (OR) per standard deviation increase 0.59, 95% confidence interval (CI) 0.54-0.64) and LDL-C levels (OR 0.94, 95%CI 0.91-0.98) on OA risk, and unfavourable effects of higher genetically predicted BMI (OR 1.82, 95%CI 1.73-1.92) and smoking (OR 2.23, 95%CI 1.85-2.68). There was no strong evidence of an effect of genetically predicted SBP on OA risk (OR 0.98, 95% CI 0.90-1.06). The proportion of the effect of genetically predicted education mediated through genetically predicted BMI and smoking was 35% (95%CI 13-57%).

CONCLUSIONS

These findings highlight education, obesity and smoking as common mechanisms underlying OA and cardiovascular disease. These risk factors represent clinical and public health targets for reducing multi-morbidity related to the burden these common conditions.

Household air pollution and arthritis in low-and middle-income countries: Cross-sectional evidence from the World Health Organization's study on Global Ageing and Adult Health

Background

Evidence points to a clear link between air pollution exposure and several chronic diseases though investigations regarding arthritis are still lacking. Emerging evidence suggests an association between ambient air pollution and rheumatoid arthritis. Household air pollution exposure, conversely, is largely unstudied but may be an important consideration for arthritis, particularly in low- and middle-income countries (LMICs), where cooking and heating activities can generate high indoor air pollutant levels.

Methods

We investigated the association of household air pollution (electricity vs. gas; kerosene/paraffin; coal/charcoal; wood; or agriculture/crop/animal dung/shrubs/grass as the main fuel used for cooking) and arthritis in six LMICs (China, Ghana, India, Mexico, the Russian Federation, South Africa) using data from Wave I of the World Health Organization Study on Global AGEing and Adult Health (SAGE) (2007–2010). Multivariable analyses were adjusted for sociodemographic, household and lifestyle characteristics and several comorbidities.

Results

The use of gas (aOR = 1.76, 95%CI: 1.40–2.21); coal (aOR = 1.74, 95%CI: 1.22–2.47); wood (aOR = 1.69, 95%CI: 1.30–2.19); or agriculture/crop/animal dung/shrubs/grass: aOR = 1.95 (1.46–2.61) fuels for cooking were strongly associated with an increased odds of arthritis, compared to electricity in cluster and stratified adjusted analyses. Gender (female), age (≥50 years), overweight (25.0 ≤BMI<30.0 kg/m²), obesity (BMI ≥30.0 kg/m²), former and current alcohol consumption, and the comorbidities angina pectoris, diabetes, chronic lung disease, depression and hypertension were also associated with a higher odds of arthritis. Underweight (BMI<18.5 kg/m²) and higher education levels (college/university completed/post-graduate studies) were associated with a lower odds of arthritis.

Conclusions

These findings suggest that exposure to household air pollution from cook fuels is associated with an increased odds of arthritis in these regions, which warrants further investigation.

Development and validation of prediction models to estimate risk of primary total hip and knee replacements using data from the UK: two prospective open cohorts using the UK Clinical Practice Research Datalink

OBJECTIVES

The ability to efficiently and accurately predict future risk of primary total hip and knee replacement (THR/TKR) in earlier stages of osteoarthritis (OA) has potentially important applications. We aimed to develop and validate two models to estimate an individual's risk of primary THR and TKR in patients newly presenting to primary care.

METHODS

We identified two cohorts of patients aged ≥40 years newly consulting hip pain/OA and knee pain/OA in the Clinical Practice Research Datalink. Candidate predictors were identified by systematic review, novel hypothesis-free 'Record-Wide Association Study' with replication, and panel consensus. Cox proportional hazards models accounting for competing risk of death were applied to derive risk algorithms for THR and TKR. Internal-external cross-validation (IECV) was then applied over geographical regions to validate two models.

RESULTS

45 predictors for THR and 53 for TKR were identified, reviewed and selected by the panel. 301 052 and 416 030 patients newly consulting between 1992 and 2015 were identified in the hip and knee cohorts, respectively (median follow-up 6 years). The resultant model C-statistics is 0.73 (0.72, 0.73) and 0.79 (0.78, 0.79) for THR (with 20 predictors) and TKR model (with 24 predictors), respectively. The IECV C-statistics ranged between 0.70-0.74 (THR model) and 0.76-0.82 (TKR model); the IECV calibration slope ranged between 0.93-1.07 (THR model) and 0.92-1.12 (TKR model).

CONCLUSIONS

Two prediction models with good discrimination and calibration that estimate individuals' risk of THR and TKR have been developed and validated in large-scale, nationally representative data, and are readily automated in electronic patient records.

The Effect of Tobacco Smoking on Musculoskeletal Health: A Systematic Review

This systematic review explored associations between smoking and health outcomes involving the musculoskeletal system. AMSTAR criteria were followed. A comprehensive search of PubMed, Web of Science, and Science Direct returned 243 articles meeting inclusion criteria. A majority of studies found smoking has negative effects on the musculoskeletal system. In research on bones, smoking was associated with lower BMD, increased fracture risk, periodontitis, alveolar bone loss, and dental implant failure. In research on joints, smoking was associated with increased joint disease activity, poor functional outcomes, and poor therapeutic response. There was also evidence of adverse effects on muscles, tendons, cartilage, and ligaments. There were few studies on the musculoskeletal health outcomes of secondhand smoke, smoking cessation, or other modes of smoking, such as waterpipes or electronic cigarettes. This review found evidence that suggests tobacco smoking has negative effects on the health outcomes of the musculoskeletal system. There is a need for further research to understand mechanisms of action for the effects of smoking on the musculoskeletal system and to increase awareness of healthcare providers and community members of the adverse effects of smoking on the musculoskeletal system.

Osteoarthritis, cerebrovascular dysfunction and the common denominator of inflammation: a narrative review

OBJECTIVE

Population-based cohort studies suggest an association between osteoarthritis (OA) and cerebrovascular disease, yet the mechanisms underlying vascular comorbidities in OA remain unclear. The purpose of this narrative review is to discuss the literature examining inflammation in OA with a focus on physiological mechanisms, and whether overlapping mechanisms exist in cerebrovascular dysfunction.

METHOD

A literature search was conducted in PubMed using combinations of search terms: osteoarthritis, cerebrovascular (disease/dysfunction/risk), cardiovascular (disease/dysfunction/risk), aging/ageing, inflammation, inflammatory mediators, cytokine, c-reactive protein, interleukin, advanced glycation end-products, metabolic syndrome, reactive oxidative species, cognitive impairment, (vascular-related) dementia, small cerebral vessel disease, endothelial function, blood-brain barrier, gender/sex, hypertension, peripheral vascular health, and physical activity. Reference lists of identified articles were also researched manually.

RESULTS

Overlapping inflammatory factors that may contribute to onset and progression of both OA and cerebrovascular dysfunction are presented. We describe oxidative mechanisms involving pro-inflammatory cytokines and oxidative species, advanced glycation end-products, sex hormones, microvascular dysfunction and osteoprotegerin, and their specific roles in potentially contributing to OA and cerebrovascular dysfunction.

CONCLUSION

Synthesis of the current literature suggests future investigations may benefit from directly testing cerebrovascular hemodynamics and cognitive function in individuals with or at risk of OA to elucidate common physiological mechanisms.

Genetic polymorphisms associated with smoking behaviour predict the risk of surgery in patients with Crohn's disease

BACKGROUND

Smoking is a strong environmental factor leading to adverse outcomes in Crohn's disease, but a more benign course in ulcerative colitis. Several single nucleotide polymorphisms (SNPs) are associated with smoking quantity and behaviour.

AIM

To assess whether smoking-associated SNPs interact with smoking to influence the clinical course of inflammatory bowel diseases.

METHODS

Genetic and prospectively obtained clinical data from 1434 Swiss inflammatory bowel disease cohort patients (821 Crohn's disease and 613 ulcerative colitis) were analysed. Six SNPs associated with smoking quantity and behaviour (rs588765, rs1051730, rs1329650, rs4105144, rs6474412 and rs3733829) were combined to form a risk score (range: 0-12) by adding the number of risk alleles. We calculated multivariate models for smoking, risk of surgery, fistula, Crohn's disease location and ulcerative colitis disease extent.

RESULTS

In Crohn's disease patients who smoke, the number of surgeries was associated with the genetic risk score. This translates to a predicted 3.5-fold (95% confidence interval: 2.4- to 5.7-fold, P<.0001) higher number of surgical procedures in smokers with 12 risk alleles than individuals with the lowest risk. Patients with a risk score >7 had a significantly shorter time to first intestinal surgery. The genetic risk score did not predict surgery in ulcerative colitis or occurrence of fistulae in Crohn's disease. SNP rs6265 was associated with ileal disease in Crohn's disease (P<.05) and proctitis in ulcerative colitis (P<.05).

CONCLUSIONS

SNPs associated with smoking quantity is associated with an increased risk for surgery in Crohn's disease patients who smoke. Our data provide an example of genetics interacting with the environment to influence the disease course of inflammatory bowel disease.