Immune-mediated Diseases and Risk of Crohn's Disease or Ulcerative Colitis

A Prospective Cohort Study

Chun-Han Lo; Hamed Khalili; Paul Lochhead; Mingyang Song; Emily W. Lopes; Kristin E. Burke; James M. Richter; Andrew T. Chan; Ashwin N. Ananthakrishnan

Disclosures

Aliment Pharmacol Ther. 2021;53(5):598-607. 

In This Article

Methods

Study Population

The Nurses' Health Study (NHS) II, established in 1989, is an ongoing prospective cohort of 116 429 female registered nurses in the United States who were between the ages of 25 and 42 years at the time of enrolment. Self-reported questionnaires were mailed to each participant at baseline and every 2 years thereafter to obtain detailed information regarding demographics, lifestyle factors and medical history. Diet was assessed using validated semi-quantitative food frequency questionnaires (FFQs) beginning in 1991 and updated every 4 years. For the current study, we used 1995 as the baseline since this was the earliest year in which data on all prevalent IMDs were available. We excluded those who had been diagnosed with CD, UC or cancer (except for non-melanoma skin cancer) at the start of follow-up. After these exclusions, data on 101 019 women were available for analysis. The study protocol was approved by the Institutional Review Boards of the Brigham and Women's Hospital and the Harvard TH Chan School of Public Health.

Ascertainment of IMDs

Our primary exposure of interest was the presence of concurrent IMDs prior to the diagnosis of CD or UC. The IMDs of interest included asthma, atopic dermatitis (AD), psoriasis, rosacea, type 1 diabetes mellitus (T1D), Guillain-Barré syndrome (GBS), multiple sclerosis (MS), RA and SLE. Table S1 presents the details of ascertainment for each individual IMD. In biennial questionnaires, participants were asked to report a diagnosis of asthma (biennially beginning in 1991), AD (2013), psoriasis (2005, 2009, 2013), rosacea (2005), diabetes mellitus (biennially beginning in 1989), MS (biennially beginning in 1991), RA (biennially beginning in 1991 except 1995) and SLE (biennially beginning in 1993 except 1995). For each disease, participants were sent a detailed supplemental questionnaire regarding symptoms, diagnostic testing and medications. For most diseases, either medical records were reviewed, or strict algorithms were developed for a subset of patients to establish high validity of self-reported diagnosis (Table S1). Information on type of diabetes (T1D vs T2D) was confirmed through supplemental questionnaire and medical record review. GBS was not inquired specifically in the biennial questionnaires and therefore all reports were of participants who wrote in their diagnosis. All write-in diagnoses were reviewed and assigned an ICD code. We identified GBS cases with ICD-8 code 354.0.

Ascertainment of IBD

We have previously detailed our methods for defining cases of CD and UC.[21,22] Briefly, participants were asked to self-report a physician diagnosis of CD or UC in biennial questionnaires. For those who reported ever having been diagnosed with CD or UC, we obtained permission to review their medical records. A detailed supplemental questionnaire was also sent to these participants inquiring type of IBD, date of diagnosis, disease complications and treatment. From participants who provided consent, medical records were obtained and independently reviewed by two board-certified gastroenterologists (HK, ANA, PL, EWL, KEB, JMR) blinded to exposure and outcome. A diagnosis of CD or UC was made based on accepted clinical criteria incorporating symptoms, endoscopic, histologic, radiographic or operative findings.[23,24] Disagreements on case definition were infrequent and resolved through consensus.

Assessment of Covariates

In the baseline and biennial follow-up questionnaires, we assessed participants' demographic and lifestyle factors including race, smoking, body mass index (BMI), physical activity and medication use including nonsteroidal anti-inflammatory drugs (NSAIDs), oral contraceptive pills and menopausal hormone therapy. Physical activity was measured by multiplying the typical intensity expressed in metabolic equivalent of task (MET) by the reported hours spent per week. Region of residence was obtained using geocoded residential addresses to the street or ZIP code level and updated every 2 years beginning in 1989. Median household income was determined from the US Census data for the census tract of residence updated every 2 years. In the 2013 questionnaire, participants were asked to indicate if their biological siblings, offspring or parents have ever had CD, UC, asthma, MS or RA. Family history of IBD was defined by the presence of first degree relative with reported CD or UC, while family history of other IMDs indicated the presence of asthma, MS or RA in family members. Dietary information was assessed every 4 years using semi-quantitative validated FFQs.[24] As a covariate in our multivariable model, we adjusted for total fibre intake which has been previously reported to modify the risk of CD.[25]

Statistical Analysis

Person-years were accrued from the return date of baseline questionnaire until a diagnosis of CD or UC, death or the end of follow-up (June 1, 2017), whichever occurred first. Cox proportional hazards models stratified by age and calendar year were used to estimate the age-adjusted and multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). All multivariable models were adjusted for race, area of residence, median household income, family history of IBD, family history of IMD, smoking, BMI, physical activity, total fibre intake, regular NSAIDs use, oral contraceptive pills and menopausal hormone therapy.

IMDs of interest included asthma, AD, psoriasis, rosacea, T1D, GBS, MS, RA and SLE. Status for all diseases was time-updated throughout the course of follow-up. For our main analysis, we examined the association between number of IMDs and risk of subsequent CD and UC. We grouped participants into three categories: 0, 1 and ≥2 IMDs. Tests for linear trend were conducted by modelling number of IMDs (range 0–7) as a continuous variable in the regression models. Test for heterogeneity of associations comparing CD and UC was conducted using a likelihood ratio test comparing a model that allows separate associations for the 2 IBD subtypes with a model that assumes a common association. We also examined the individual associations of incident CD or UC with four common IMDs—asthma, AD, psoriasis and rosacea. As the number of participants with each of the other IMDs was small, we pooled together participants with any of the following less frequent diagnoses: RA, SLE, T1D, MS and GBS. To minimise competing effects from multiple IMDs, we censored participants at the time of diagnosis of other IMDs in the main analysis. In a sensitivity analysis, we allowed these individuals to contribute person-years to the reference group.

We performed a sensitivity analysis by adjusting for Mediterranean dietary pattern quantified using the aMED score as this dietary pattern has been linked to IBD risk in some studies.[26] We also repeated the analysis adjusting for intake of vitamin D which has been associated inversely with various IMDs.[27] In addition, we excluded those with family history of IBD and tested the heterogeneity of the associations between number of IMDs and the two IBD subtypes. In a stratified analysis, we examined the association of any IMDs with CD and UC according to family history of other IMDs. Test for interaction was calculated by including a cross-product interaction term in the model and estimating the significance using a likelihood ratio test. All analyses were conducted using the SAS software (SAS Institute, Inc, Version 9.4). All statistical analyses were two-sided with a P value less than 0.05 indicating statistical significance.

Patient and Public Involvement

This research was done without public involvement. Participants were not invited to comment on the study design and were not consulted to develop relevant outcomes or interpret the results. Participants were not invited to contribute to the writing or editing of this paper for readability or accuracy.

Comments

3090D553-9492-4563-8681-AD288FA52ACE

processing....