Respiratory Viral Infections and the Risk of Rheumatoid Arthritis

Young Bin Joo; Youn-Hee Lim; Ki-Jo Kim; Kyung-Su Park; Yune-Jung Park

Arthritis Res Ther. 2019;21(199)

Abstract and Introduction

Abstract

Background: We aimed to investigate the effects of ambient respiratory viral infections in the general population on rheumatoid arthritis (RA) development.

Methods: Data of weekly incident RA (2012–2013) were obtained from the Korean National Health Insurance claims database, and those of weekly observations on eight respiratory viral infections were obtained from the Korea Centers for Disease Control and Prevention database. We estimated the percentage change in incident RA associated with ambient mean respiratory viral infections using a generalized linear model, after adjusting for time trend, air pollution, and meteorological data.

Results: A total of 24,117 cases of incident RA (mean age 54.7 years, 18,688 [77.5%] women) were analyzed. Ambient respiratory viral infections in the population were associated with a higher number of incident RA over time, and its effect peaked 6 or 7 weeks after exposure. Among the 8 viruses, parainfluenza virus (4.8% for 1% respiratory viral infection increase, 95% CI 1.6 to 8.1, P = .003), coronavirus (9.2%, 3.9 to 14.8, P < .001), and metapneumovirus (44%, 2.0 to 103.4, P = .038) were associated with increased number of incident RA. The impact of these respiratory viral infections remained significant in women (3.8%, 12.1%, and 67.4%, respectively, P < .05) and in older patients (10.7%, 14.6%, and 118.2%, respectively, P < .05).

Conclusions: Ambient respiratory viral infections in the population were associated with an increased number of incident RA, especially in women and older patients, suggesting that respiratory viral infections can be a novel environmental risk factor for the development of RA.

Introduction

Rheumatoid arthritis (RA) is an immune-mediated disease involving interactions between genetic and environmental factors.^[1,2] It has been considered that a pre-clinical RA phase comprising the generation of autoantibodies in genetically susceptible individuals lasts months to years then transitions to a clinical RA event by virtue of other driving factors.^[2] These driving factors are currently poorly understood, but it is suspected that microvascular, neuroregulatory, microtrauma-related, or transient infection-dependent pathways are involved.^[2,3]

We are interested in determining whether respiratory viral infections have the capacity to driving RA development, for several reasons. Smoking, periodontitis, and microbiomes—all prominent environmental risk factors for RA—interact with mucosal surfaces including the lungs, oral mucosa, and gastrointestinal tract.^[4] It is thought that these local tissue stresses on the mucosa lead to post-translational modification of peptides involved in RA pathogenesis.^[2,5,6] Initial respiratory virus infections usually involve both the oral mucosa and the lungs, and this may be relevant to the generation of immune responses potentially associated with RA development. Previous studies suggest that RA exhibits seasonal tendencies, whereby RA onset is more frequent in winter,^[7] and relapses are more frequent in summer.^[8] Thus, we hypothesized that respiratory viral infections that exhibit seasonality may be associated with RA development. This hypothesis is supported by studies investigating other autoimmune diseases.^[9–17] Multiple sclerosis which exhibits seasonal tendencies has been associated with upper respiratory picornavirus, rhinovirus, and influenza infections.^[9–15] Influenza virus infections triggered disease in a genetic model of experimental autoimmune encephalomyelitis.^[16] Furthermore, the occurrence of pediatric Henoch-Schönlein purpura was highest in the spring and lowest in the summer, and it was associated with an outbreak of influenza.^[17]

A few studies have investigated a potential link between respiratory viral infections and the development of RA.^[18,19] In the population-based case-control study, previous respiratory tract infections including sinusitis and tonsillitis treated with antibiotics, and pneumonia showed no association with a risk of RA.^[18] In this study, it is not certain whether respiratory infections were caused by viruses or bacteria, but rather bacterial respiratory infections seemed to be considered more. Another study, however, showed that viral infection symptoms confirmed by questionnaire were more frequent in patients with a new-onset RA in the previous year compared to healthy control, but this was a small-sized study using 59 RA patients and 69 controls.^[19]

Reliable data reflecting respiratory viral epidemic burden in South Korea are available, because the Korea Centers for Disease Control and Prevention (KCDC) operates a well-established surveillance system for the detection of respiratory viruses via polymerase chain reaction (PCR) diagnosis in patients with respiratory symptoms.^[20,21] In addition, population-based incident RA can be identified via claims data because the Korean National Health Insurance (KNHI) covers almost the entire South Korean population.

In the present study, the effects of ambient respiratory viral infections on the number of incident RA in South Korea were investigated using national public data. First, patterns of incident RA over time were investigated using claims data. A time-series analysis was then conducted to investigate associations between the detection rate of ambient respiratory viral infections and the number of incident RA.

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Arthritis Res Ther. 2019;21(199) © 2019 BioMed Central, Ltd.
Copyright to this article is held by the author(s), licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original citation.

Abstract and Introduction
Methods
Results
Discussion
Conclusions
References

Table 1. Characteristics of patients newly diagnosed with rheumatoid arthritis in 2012 or 2013
Clinical values	Patients (n = 24,117)
Age
Overall mean ± SD (years)	54.7 ± 13.2
Age group frequencies (n and %)
19–39 years	3174 (13.2%)
40–59 years	12,332 (51.1%)
≥ 60 years	8611 (35.7%)
Sex (n and %)
Women	18,688 (77.5%)
Men	5429 (22.5%)
Previous respiratory diseases (n and %)
Absence	14,273 (59.18%)
Presence	9844 (40.82%)
Number of patients per year (n and %)
2012	12,024
2013	12,093

SD standard deviation

Table 2. The effects of ambient respiratory virus on incident RA
Virus	Percent change in incident RA per 1-unit change in the detection rate of virus^a	95% CI	P value
Adenovirus at lag1–6w	1.93	− 1.14 to 5.09	.220
Parainfluenza virus at lag1–7w	4.80	1.57 to 8.14	.003
Respiratory syncytial virus at lag1w	− 0.06	− 0.82 to 0.71	.873
Influenza virus at lag1–6w	0.42	− 0.68 to 1.53	.446
Corona virus at lag1–6w	9.20	3.85 to 14.82	< .001
Rhinovirus at lag1–8w	1.54	− 2.19 to 5.42	.423
Bocavirus at lag1–8w	13.33	− 1.57 to 30.48	.082
Metapneumovirus at lag1–6w	44.02	1.98 to 103.39	.038

The moving average lag up to 8 lag weeks (lag1–8) was used in the analysis. For example, "lag1–8" refers to a moving average lag model for respiratory viral infections over the previous 8 weeks
CI confidence interval
^aRelative risk adjusted for mean particulate matter < 10 μg/m³ in aerodynamic diameter, ozone, temperature, humidity, amount of solar exposure, and seasonality

Table 3. The effects of ambient respiratory virus on incident RA in subgroups of patients
Subgroup	Percent change in incident RA per 1-unit change in the detection rate of virus^a	95% CI	P value
Sex
Men
Parainfluenza virus at lag1–7w	8.24	1.34, 15.61	.019
Corona virus at lag1–6w	0.20	− 9.77, 11.28	.971
Metapneumovirus at lag1–6w	− 5.11	− 58.96, 75.59	.659
Women
Parainfluenza virus at lag1–7w	3.82	0.18, 7.59	.040
Corona virus at lag1–6w	12.11	5.87, 18.71	< .001
Metapneumovirus at lag1–6w	67.4	13.04, 147.88	< .001
Age
< 40 years
Parainfluenza virus at lag1–7w	10.02	0.73, 20.17	.034
Corona virus at lag1–6w	7.97	− 6.31, 24.43	.289
Metapneumovirus at lag1–6w	45.89	− 43.27, 275.18	.433
40–59 years
Parainfluenza virus at lag1–7w	− 0.11	− 4.38, 4.35	.962
Corona virus at lag1–6w	5.64	− 1.50, 13.3	.124
Metapneumovirus at lag1–6w	5.52	− 34.93, 71.09	.828
≥ 60 years
Parainfluenza virus at lag1–7w	10.66	4.96, 16.67	< .001
Corona virus at lag1–6w	14.64	5.41, 24.67	.001
Metapneumovirus at lag1–6w	118.19	22.19, 289.61	.008
Previous respiratory disease
Without respiratory disease
Parainfluenza virus at lag1–7w	4.48	0.26, 8.87	.037
Corona virus at lag1–6w	10.61	3.58, 18.11	.003
Metapneumovirus at lag1–6w	23.87	− 21.09, 94.47	.352
With respiratory disease
Parainfluenza virus at lag1–7w	5.66	0.61, 10.97	.028
Corona virus at lag1–6w	6.72	− 1.43, 15.53	.108
Metapneumovirus at lag1–6w	79.18	4.52, 207.16	.034

Table S1. Payer type and institutions of patients newly diagnosed with rheumatoid arthritis in 2012 or 2013.
Clinical values	Patients (n = 24,117)
Payer type (n and %)
National Health Insurance	22,922 (95.0%)
Medicaid	1,195 (4.7%)
Government-sponsored	70 (0.3%)
Type of institutions (n and %)
Tertiary hospital	7,630 (31.6%)
General hospital	5,746 (23.8%)
Clinic and community hospital	10,741 (44.6%)

Table S2. Monthly and weekly number of Incident RA
	total	Weekly mean ± SD	P value*
In 2012	12,024
January	781	182.6 ± 29.3	0.0006
February	966	227.3 ± 15.3	0.0092
March	1,035	240.0± 31.3	0.0548
April	1,104	259.8 ± 15.6	0.1065
May	1,233	276.0± 20.1	0.5266
June	1,133	266.8 ± 15.6	0.2548
July	1,274	288.0± 31.0	-
August	1,067	235.8 ± 26.9	0.0325
September	953	213.8 ± 43.4	0.0144
October	889	206.5 ± 15.6	0.0021
November	814	187.5 ± 21.1	0.0009
December	775	179.3 ± 13.9	0.0003
In 2013	12,093
January	1,057	231.8 ± 16.0	0.0393
February	919	221.3 ± 19.7	0.0236
March	1,088	266.4 ± 27.9	0.7391
April	1,091	239.3 ± 14.0	0.1220
May	1,211	274.0± 21.9	0.3968
June	1,080	265.5 ± 18.7	0.7492
July	1,212	261.0± 21.2	-
August	1,013	230.0± 22.0	0.0689
September	828	194.4 ± 59.5	0.0461
October	924	207.5 ± 27.7	0.0131
November	817	191.8 ± 32.1	0.0058
December	853	170.6 ± 50.8	0.0063

*The differences in weekly mean number of incident RA cases between the "top peaks" in July (reference) and other months were established by independent Student's t-test.