Psoriatic and Psoriatic Arthritis Patients With and Without Jet-lag: Does it Matter for Disease Severity Scores? Insights and Implications from a Pilot, Prospective Study

Abstract

Background

Jet-lag may affect air-travelers crossing at least 2 time-zones and has several healthcare implications. It occurs when the human biological rhythms are out of synch with respect to the day-night cycle at the country destination. Its effect in psoriasis is missing. We aimed to evaluate the effect of Jet-lag in psoriatic patients’ management.

Methods

This is a prospective observational study that enrolled psoriatic patients that underwent a flight: patients who experienced jet-lag were compared to patients who did not experience jet-lag. Before the flight, a dermatologist recorded clinical and demographical data with particular attention to Psoriasis Area Severity Index (PASI) and Disease Activity in PSoriatic Arthritis (DAPSA). Patients performed Self-Administered Psoriasis Area Severity Index (SAPASI), the Dermatology Life Quality Index (DLQI) and the pruritus Visual Analog Scale (VAS) scores. After the flight, patients completed the SAPASI, DLQI and pruritus-VAS scores.

Results

The sample recruited comprised of 70 psoriatic patients aged 42.4 ± 9.7 years (median 42.5 years). Thirty (42.9%) were males, mean BMI was 25.5 ± 2.2 kg/m². Average disease duration was 15.2 ±7.1 years, and 20 (28.6%) subjects had developed PsA. Average hours of flight were 5.4 ±3.5 (median 3.5 hours), with 34 (48.6%) subjects reporting jet-lag. At the multivariate regression analysis, the change in the SAPASI score resulted correlated with jet-lag (regression coefficient 1.63, p = 0.0092), as well the change in the DLQI score (regression coefficient = 1.73, p = 0.0009), but no change on the pruritus VAS scale was found.

Conclusions

The present study suggests that jet-lag may influence disease severity and DLQI scores, but not itch in psoriatic patients.

1. INTRODUCTION

Psoriasis is a systemic, chronic, inflammatory skin disorder clinically characterized by scaly, infiltrated, erythematous patches [1], sometimes itch[2], and biologically perturbated keratinocytes life-cycle in a seated in a pro-inflammatory microenvironment[3]. There are no valid biomarkers available for monitoring psoriasis [4,5]. It is a common and widespread condition, affecting up to 125 million individuals worldwide [6], with a prevalence rate ranging from 0.91% to 8.5% [7]. Some psoriatic patients can suffer from joint involvement and develop psoriatic arthritis (PsA) [1]. Other frequently reported co-morbidities [8] included metabolic [9–11], autoimmune[12,13], respiratory [14–16], psychiatric diseases [17] and sleep-related disorders [18].

With the globalization, airline flights, especially the international flights, are on the rise. According to the latest statistical data available, in 2017, 36.8 million flights have been operated worldwide. Jet-lag can affect air-travelers crossing several time-zones. It occurs when the human biological rhythms are out of phase with respect to the day-night cycle at the country destination [19,20].

Given the increase in air travel (particularly flights crossing time zones) it is pertinent to be aware of its medical implications and potential consequences. From the literature it is known that air transportation can play a major role in the transmission and spreading of infectious disorders (including inter alia airborne diseases such as tuberculosis, severe acute respiratory syndrome (SARS), influenza, smallpox, and measles). [21] and that traveling by airplane can exacerbate or trigger some medical conditions due to air pressure and humidity including abdominal pain, psychiatric disorders or ear, nose and throat pathologies [22]. There are increased risk of thromboembolic events [22] (known as the “traveler’s thromboembolic disease” [23], the “economy class syndrome” [24,25] or the “surgical flight syndrome” [26]). There are sporadic reports of acute respiratory failure [22], stroke [27] or cardiac arrest [22,28] associated with air travel.

However, there is a dearth of data concerning the risk of developing or exacerbating some skin disorders, including psoriasis and PsA, beyond anecdotal case-reports e.g [29]. Therefore, the present study was conducted in order to fill this gap in knowledge.

2. METHODS

2.1. Ethical approval

The study protocol is compliant with 1964 Helsinki ethical declaration and its subsequent amendments and was approved by Ethical Committees of the involved institutions. Patients who volunteered to take part into the study signed an informed consent form, after being carefully and extensively advised about the aim of the investigation.

2.2. Patient selection: inclusion and exclusion criteria

This is a 3 years prospective multicenter observational study conducted between (January) 01.2016 to (December) 12.2019. Patients were included in the present study if: i) aged ≥18 years, ii) with a diagnosis of plaque psoriasis performed by two independent board-certified dermatologists, iii) with a Psoriasis Area Severity Index (PASI) ≥10 before starting the systemic treatment and a stable disease (Delta PASI in two consecutive controls <10%) at the study baseline, iv) under systemic anti-psoriatic treatment, v) under biologics in maintenance and having achieved at least PASI 75, or vi) receiving intramuscular for methotrexate since at least 2 months and having achieved a PASI at least of 50.

Patients were excluded if: i) suffering from chronic-degenerative diseases (including diabetes mellitus, asthma, chronic obstructive pulmonary disease (COPD) and other respiratory diseases), ii) suffering from sleep-related disorders, iii) suffering from chronic infections (human immunodeficiency virus (HIV), hepatitis B virus (HBV), or hepatitis C virus (HCV) infections), iv) with an incident acute infection during the study period, v) pregnancy, vi) drug addiction, vii) previous deep vein thrombosis, viii) concurrent rheumatologic disorders, or ix) had a dose non-steroidal pain killers 48 hours prior to the flight, x) received oral melatonin during the study, xi) positivity to the Epworth Sleepiness Scale, Insomnia Severity Index and Hamilton severity scale for depression. Smokers were not excluded, based on the fact that on-board smoking (cigarette, cigars and e-cigarettes) is not allowed.

In accord with the American Academy of Sleep Medicine (AASM, 2014) and the International Classification of Sleep Disorders (ICDS-3), Jet-lag was self-diagnosed if the patient had: i) insomnia or sleepiness with impaired total day time after crossing a minimum of 2 time zones, ii) general malaise, diurnal dysfunction and/or somatic symptoms 1–2 days after the trip, iii) the previous findings cannot be provoked by other causes. In order to facilitate self-evaluation of Jet-lag patients were also trained to respond to the Columbia Jet-Lag Scale that was repeated for five days at the same hour after arrival and if the patients were positive once they were enrolled as cases.

2.3. Disease severity scores and dermatologic assessment

The following disease severity scores were collected: namely, PASI, Self-Administered PASI (SAPASI) [30], Dermatology Life Quality Index (DLQI) and Pruritus Visual Analog Scale (VAS) scores for psoriatic patients, and the Disease Activity index for PSoriatic Arthritis (DAPSA) [31] for PsA patients. Before the flight a qualified, experienced dermatologist recorded clinical and demographic data, including PASI and DAPSA.

Patients were also were previously instructed to self-assess before and after flight the following: Self-Administered PASI (SAPASI), Dermatology Life Quality Index (DLQI) and Pruritus Visual Analog Scale (VAS) scores. All the tools

Remarkably, during the dermatologic assessment all psoriatic patients without a diagnosis of PsA underwent Psoriasis Epidemiology Screening Tool (PEST) to detect a neglected PsA the may deserve further instrumental tests [32].

2.4. Statistical analysis

Before proceeding with data handling and processing, data were visually inspected to capture potential outliers. Normality of data distribution was assessed computing the Shapiro-Wilk’s test: given the small sample size utilized, this test was preferred over other tests (such as the D’Agostino-Pearson omnibus test). Continuous and categorical data were expressed as means ± standard deviation and percentages, respectively.

Correlation between the baseline PASI and SAPASI scores was performed and the strength of this correlation was assessed using the following rule of thumb: the correlation was deemed negligible if the coefficient ranged from 0.00 to 0.30, was judged low with the coefficient going from 0.30 to 0.50. It was considerate moderate with the coefficient from 0.50 to 0.70, high from 0.70 to 0.90, and, very high from 0.90 to 1.00.

Student’s t-test for paired samples was conducted for computing the changes in the disease severity scores (namely, the SAPASI, DLQI, and pruritus VAS scores) before and after the flight Furthermore, multivariate regression analyses were carried out in order to shed light on the determinants of such changes.

All statistical analyses were carried out by means of the commercial software “Statistical Package for Social Sciences” (SPSS for Windows, version 24.0, IBM, Armonk, NY, USA). Graphs were generated utilizing the commercial software MedCalc version 18.11.3 (MedCalc Software bvba, Ostend, Belgium). For all statistical analyses, figures with p-values less than or equal to 0.05 were considered to be statistically significant.

3. RESULTS

The sample comprehended 70 psoriatic patients aged 42.4 ± 9.7 years (median 42.5 years). Thirty (42.9%) were males, 37 (52.9%) were married and further 37 (52.9%) had attended high-schools, whereas 33 (47.1%) had attended university. Mean body mass index (BMI) was 25.5 ± 2.2 kg/m². Average disease duration was 15.2 ± 7.1 years, and 20 (28.6%) subjects had polyarticular PsA. Nobody had axial PsA. Most patients (n = 20, 28.6% of the entire sample) received intramuscular methotrexate whereas 10 (14.3%) individuals were under secukinumab, 9 (12.9%) patients were treated with apremilast, 8 (11.4%) with adalimumab, and a further 8 (11.4%) with ixekizumab. Other 8 (11.4%) individuals received ustekinumab 90 mg, while 5 (7.1%) patients were administered etanercept and 2 (2.9% of the sample) were under narrow-band ultraviolet B (UVB).

Eleven (15.7%) patients had not chosen medication. At the baseline, DAPSA, DLQI, PASI, SAPASI and pruritus-VAS scores were 4.6 ± 7.54, 13.2 ± 2.71, 3.1 ± 1.8, 4.83 ± 2.85 and 2.1 ± 2.35 mm, respectively. The average number of hours of flight in the 34 (48.6%) patients that report jet-lag was 8.5 ± 2,3 (median 8,5) and in controls without jet-lag was 2.6 ± 0.8 (median 3). Further details are shown in Table 1.

Table 1.

Main baseline characteristics of the studied population.

Parameter	Variable
Age	42.44±9.74
Sex
Male	30 (42.9%)
Female	40 (57.1%)
BMI	25.50±2.22
Marital status
Married	37 (52.9%)
Not married	33 (47.1%)
Educational level
High-school	37 (52.9%)
University	33 (47.1%)
PsA	20 (28.6%)
Disease duration	15.16±7.05
Treatment
Adalimumab	8 (11.4%)
Apremilast	9 (12.9%)
Etanercept	5 (7.1%)
Ixekizumab	8 (11.4%)
Methotrexate	20 (28.6%)
Narrow-band UVB	2 (2.9%)
Secukinumab	10 (14.3%)
Ustekinumab	8 (11.4%)
Biologics naïve	11 (15.7%)
DAPSA T0	4.63±7.54
DLQI T0	13.21±2.71
PASI T0	3.09±1.84
SAPASI T0	4.83±2.85
Pruritus VAS T0	2.06±2.35
Hours of flight	5.38±3.46
Reporting jet-lag	34 (48.6%)

The PASI and SAPASI baseline scores were found to correlate between each other (r = 0.88 [95% CI 0.82–0.93, p < 0.0001), indicating a good congruence between physician-made and self-assessed measures.

After the flight, the SAPASI score increased up to 5.9 ± 3.6 (mean difference 1.09 ± 1.6 [95% CI 0.7–1.5], t = 5.83, p < 0.0001), as shown in Figure S1.

Similarly, the DLQI and the pruritus VAS scores increased up to 13.80±2.96 (Figure S2) and up to 2.41±2.73 (mean difference 0.36±0.74 [95%CI 0.18–0.53], t=4.02, p=0.0001) (Figure S3), respectively.

At the multivariate regression analysis, the change in the SAPASI score resulted correlated with the jet-lag (regression coefficient 1.63, standard error=0.61, t=2.69, p=0.0092, r_partial=0.33), as reported in Table 2.

Table 2.

Multivariate regression analysis investigating covariates associated with change in the SAPASI score.

Variable	Coefficient	Standard Error	t	p-value	rpartial
(Constant)	−1.66
Age	0.03	0.02	1.58	0.1198	0.20
Gender	0.27	0.36	0.75	0.4571	0.10
BMI	0.00	0.08	−0.04	0.9689	−0.01
Marital status	−0.02	0.35	−0.06	0.9562	−0.01
Educational level	0.13	0.36	0.37	0.7097	0.05
Disease duration	0.00	0.03	0.13	0.8940	0.02
PsA	0.32	0.42	0.76	0.4531	0.10
SAPASI T0	0.09	0.06	1.46	0.1502	0.19
Biologics naïve	0.87	0.49	1.78	0.0798	0.23
Hours of flight	−0.03	0.09	−0.35	0.7287	−0.05
Jet-lag	1.63	0.61	2.69	0.0092	0.33

A similar finding was obtained for the change in the DLQI score (regression coefficient=1.73, standard error = 0.50, t = 3.50, p = 0.0009, r_partial= 0.42) (Table 3).

Table 3.

Multivariate regression analysis investigating covariates associated with change in the Dermatology Life Quality Index (DLQI) score.

Variable	Coefficient	Standard Error	t	p-value	rpartial
(Constant)	0.37
Age	0.02	0.02	1.13	0.2631	0.15
Gender	0.39	0.29	1.33	0.1880	0.17
BMI	−0.04	0.07	−0.64	0.5268	−0.08
Marital status	0.44	0.29	1.53	0.1324	0.20
Educational level	0.30	0.30	1.02	0.3132	0.13
Disease duration	0.00	0.02	0.02	0.9839	0.00
PsA	0.18	0.34	0.52	0.6032	0.07
DLQI T0	−0.03	0.05	−0.62	0.5364	−0.08
Biologics naïve	0.59	0.40	1.50	0.1403	0.19
Hours of flight	−0.10	0.07	−1.35	0.1809	−0.18
Jet-lag	1.73	0.50	3.50	0.0009	0.42

Concerning the change in the pruritus VAS scale, the pruritus VAS score at T₀ (regression coefficient=0.13, standard error=0.03, t=3.83, p=0.0003, r_partial=0.45), but not the jet-lag (regression coefficient=0.15, standard error = 0.29, t=0.54, p=0.5934, r_partial=0.07) was found to be an independent predictor (Table 4).

Table 4.

Multivariate regression analysis investigating covariates associated with change in the pruritus visual analog scale (VAS) score.

Variable	Coefficient	Standard Error	t	p-value	rpartial
(Constant)	−0.90
Age	0.00	0.01	0.31	0.7567	0.04
Gender	−0.20	0.17	−1.19	0.2373	−0.15
BMI	0.03	0.04	0.86	0.3959	0.11
Marital status	0.16	0.17	0.95	0.3439	0.12
Educational level	−0.21	0.17	−1.24	0.2190	−0.16
Disease duration	−0.02	0.01	−1.77	0.0814	−0.23
PsA	0.31	0.20	1.55	0.1269	0.20
Pruritus VAS T0	0.13	0.03	3.83	0.0003	0.45
Biologics naïve	0.27	0.23	1.18	0.2415	0.15
Hours of flight	0.05	0.04	1.24	0.2197	0.16
Jet-lag	0.15	0.29	0.54	0.5934	0.07

No differences were detected in Westward vs Eastward flights for the evaluated outcomes.

4. DISCUSSION

To the best of our knowledge, this is the first study assessing the impact of the jet-lag in travelling psoriatic patients. We found that the jet-lag influenced the changes in the SAPASI and DLQI scores after the flight, but not the change in the pruritus VAS score. In other words, the jet-lag impacted on the subjective perceived disease severity but not on pruritus.

A plausible mechanistic explanation in biological terms of the effect of the jet-lag in psoriatic patients is lacking [33]. We speculate that this effect could be linked to disrupted circadian rhythms, aberrant melatonin production and release [33]. These biological changes in circadian control are generally overlooked in the literature, with few studies addressing such relationships. It is known that psoriasis is characterized by lower melatonin levels than healthy controls, with the absence of its night-time peak. In a pioneering study, Mozzanica and colleagues [34], exploring a sample of 13 psoriatic male patients, found that plasma melatonin concentrations were lower at 2 a.m., but higher at 6 and 8 a.m. and at 12 noon, compared to 13 healthy males. This suggests a phase delay effect. These findings have been confirmed by further studies [35,36]. Melatonin has an anti-oxidant effect [37,38] and, in dermal fibroblasts, can foster the activation of heme degrading enzymes and counteract or, at least, mitigate the UVA-induced photodamage [39].

Melatonin receptors, including MT1, MT2 and MT3, as well as the nuclear receptors RORα1, RORα2, and RZR, have been found in skin, at the level of epidermis and hair follicles, suggesting that melatonin may play a major role in skin physiology (modulating the keratinocyte proliferation and cell cycle) and physiopathology (being involved, for instance, in the etiopathogenesis of melanoma) [40].

Recently, Damiani and colleagues [41] have assessed the impact of the circadian rhythms on psoriasis through the model of the Ramadan fast, which is characterized by alternate abstinence and re-feeding periods, currently being the most popular model of circadian or intermittent fasting [42]. For this purpose they recruited a sample of 108 moderate-to-severe plaque psoriasis patients (aged 42.8 ±13.6 years, 62 males, 46 females). A statistically significant decrease in the PASI score after the Ramadan fast (mean difference −0.89±1.21, p <0.0001) was found, reflecting the potential influence of the dieting strategy, the human biological clock, and the circadian rhythms on the management of plaque psoriasis. Adawi et al. [43] investigated the effect of the intermittent circadian Ramadan fasting in a sample of 37 PsA patients (23 females and 14 males) with a mean age of 43.32±7.81 years). After a month of fasting, C-reactive protein levels decreased from 14.08±4.65 to 12.16±4.46 (p <0.0001), as well as the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) score from 2.83±1.03 to 2.08±0.67 (p=0.0078). Similarly, the PASI and the DAPSA scores decreased from 7.46±2.43 to 5.86 ± 2.37 (p <0.0001) and from 28.11±4.51 to 25.76±4.48 (p <0.0001), respectively.

It is noteworthy to add that cosinor analysis could not detect any statistically significant change in the acrophase of melatonin levels in a sample of 8 healthy volunteers aged 26.6±4.9 years and with a mean BMI of 23.7±3.5 kg/m², suggesting that melatonin concentration is not impaired during the Ramadan fasting [44]. The amplitude of the melatonin rhythm may be decreased during the month of Ramadan [45,46], however without significantly affecting its chronobiology [44].

It appears, therefore, than in models in which melatonin production is not impaired, psoriasis disease severity does not worsen or even tends to decrease. Contrarily, in models in which there are major disruptions in circadian rhythms and in melatonin release, for instance in night-shift workers [47,48] or in patients with sleep-related disorders [49,50], there is, instead, a higher risk of developing a number of rheumatic conditions, including psoriasis [50,51], as well as a higher risk of a worse prognosis.

Li and coauthors [51], with data drawn from two large, prospective cohort studies of shift work the “Nurses’ Health study I” (NHS I) (1988–2008) and NHS II (1989–2005), detected 1,887 incident psoriasis cases with a multivariate-adjusted hazard-ratio (HR), of 1.26 [95%CI 1.09–1.47] in NHS I, and of 1.14 [95%CI 1.01–1.28] in NHS II, and of 1.19 [95%CI 1.07–1.32].

Summarizing, there seems to be a consistent pattern that links melatonin rhythm, production, release and levels with psoriasis disease severity. Models characterized by absence of melatonin impairments (e.g Ramadan fast) showed a better prognosis for psoriasis compared to models in which there are sleep disruptions (i.e., night-shift working, sleep-related disorders and jet-lag).

The effect of night-shift work appears more nuanced in other rheumatic disorders, such as rheumatoid arthritis (RA). For example, Hedström and collaborators [52] found that, in a sample of 1,951 cases and age-, gender- and residential area-matched 2,225 controls, rotating shift work and day-oriented shift work significantly increased the risk of developing anti-citrullinated peptide antibodies (ACPA)-positive RA (odds-ratio, OR 1.3 [95%CI 1.0–1.7] and OR 1.3 [95%CI 1.0–1.6], respectively), but not ACPA-negative RA.

The present study has a number of strengths, including its novelty and its methodological rigor. On the other hand a limitation is the modest sample size furthermore biomarker (for instance, melatonin levels) was assessed in the current investigation and should be a component of further research.

5. CONCLUSION

The present study demonstrated a statistically significant effect of the jet-lag, which could explain the changes in the SAPASI and DLQI scores, before and after a flight, but not the change in the pruritus VAS score. This could have broad clinical implications for patients.