Rhinitis

In this genome-wide association study, we used a two-stage design to identify novel and significant genome-wide associations that confer susceptibility to moderate-to-severe asthma. We used a two-stage case-control design, with variants that showed suggestive association (p<1 × 10⁻⁶) in stage 1 tested in stage 2 and then meta-analysed across the two stages to maximise power.
For stage 1, we selected individuals of European ancestry with moderate-to-severe asthma who had been recruited from primary and secondary care settings across the UK as part of the Genetics of Asthma Severity and Phenotypes (GASP) initiative, with additional cases included from the U-BIOPRED asthma cohort²⁶ (link) and the UK Biobank May, 2015,27 , 28 (link) genetic data release (appendix). Genotyped data were assessed for quality control (details are in the appendix). From GASP and U-BIOPRED, we identified patients with moderate-to-severe asthma by assessing clinical records that indicated that a patient was taking medication required for patients defined as having moderate-to-severe asthma according to the British Thoracic Society (BTS) 2014 guidelines.²⁹ From the UK Biobank, cases of moderate-to-severe asthma were defined as having asthma diagnosed by a doctor, taking medication for asthma, no diagnosis of emphysema or chronic bronchitis by a doctor, and meeting the definition of moderate-to-severe asthma by BTS criteria. Therefore, cases were selected from individuals for whom medication information was available and who met BTS stage 3–5 criteria—ie, for stage 3, taking a long-acting β₂ agonist plus inhaled corticosteroid; stage 4, taking higher dose inhaled corticosteroids than stage 3 patients, and addition of a fourth drug (eg, leukotriene receptor antagonist, theophylline); and stage 5, taking oral corticosteroid or omalizumab, or both. A complete list of medications used to identify patients with moderate-to-severe asthma is in the appendix. Controls for stage 1 were identified from the UK Biobank by taking the remaining subjects for whom genotyped data were available that passed quality control and excluding individuals with asthma, rhinitis, eczema, allergy, emphysema, or chronic bronchitis as diagnosed by a doctor, or if medication data were not available to assign to either the mild-moderate or moderate-severe asthma group. Additional controls for stage 1 were included from U-BIOPRED to ensure we had controls from each cohort. Patients in the U-BIOPRED cohort had not been screened for rhinitis or eczema, and so this information was not available for these controls at time of selection. For stage 2, both cases and controls were selected from the UK Biobank May, 2017, release using the same criteria to define cases and controls as in stage 1. There was no overlap in the patients included in stage 1 and stage 2. A case-control ratio of 1:5 was chosen for both stages to balance power and computational time. Cases and controls were matched across age and sex strata, and in stage 1 across genotyping arrays. All cohorts included individuals with self-reported European ancestry; individuals of non-European ancestry were excluded to reduce confounding of the study by ancestry.
UK Biobank has ethical approval from the UK National Health Service (NHS) National Research Ethics Service (Ref 11/NW/0382). All other studies were approved by an appropriate ethics committee. Informed consent was obtained from all participants.

Seinäjoki Adult Asthma Study (SAAS) is a single-centre (Department of Respiratory Medicine, Seinäjoki Central Hospital, Seinäjoki, Finland) 12-year follow-up study of a total cohort of 259 patients having new-onset asthma that was diagnosed at adult age. However, two patients were excluded because they were later found to have a previous diagnosis of asthma during childhood, leaving 257 patients in the original cohort. The study was divided in two parts (Figure 1): the collection of the original cohort (phase I) and follow-up visit (phase II). The original cohort was collected between 6 October 1999 and 17 April 2002. Patients were referred to the hospital by primary-care practitioners because of suspicion of asthma. Inclusion and exclusion criteria are shown in Table 1. Patients with simultaneous asthma and COPD were not excluded, and the study population includes patients who could be defined as having asthma–COPD overlap syndrome, even though the inclusion criteria for those patients are not exactly the same as currently used criteria for asthma–COPD overlap syndrome.^{1 ,11 ,12 (link)}After 12 years, patients were invited to a follow-up visit (phase II; 10 December 2012 and 31 October 2013) in which asthma status, co-morbidities (chronic rhinitis or obstructed nose, allergic rhinitis or conjunctivitis, diabetes, hypertension, coronary heart disease, COPD and any other patient-reported disease), medication (including medication to other diseases and the disease treated), control, severity and lung function were evaluated (Figure 1). In addition to the data gathered at these visits, data on asthma follow-up visits, exacerbations, hospitalisations, possible occupationally induced asthma and prescribed asthma medication were collected from hospital clinics, primary health care, occupational health care and private practices for the whole 12-year follow-up period. In addition, the use of medication that was realised, i.e., medication bought from pharmacy, will be retrieved. In addition to asthma-specific factors, data include occupational, lifestyle and socioeconomic factors at the follow-up visit.

This work was performed in compliance with the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Hospital, Chengdu University of Traditional Chinese Medicine (NO: 2021KL-094). A WeChat mini-program was used to execute questionnaires for selecting volunteers in Chengdu, China. All participants provided written informed consent before the study. MPASD volunteers and healthy controls were recruited by the MPATS and PSQI. The MPATS contains 16 questions, including withdrawal symptoms, salience, social comfort, and mood changes. The inclusion criteria of MPASD subjects were ≥ 40 (MPATS) and ≥ 7 (PSQI) scores (31 ). To minimize the interference of severe sleep disorders upon MPA, those characterized as “poor” sleepers (7 ≥ PSQI ≥ 15 scores) were recruited from a non-clinical population (32 (link)). The PQSI score was made up of questions including sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, daytime dysfunction, and medication use. The exclusion criteria included one of the following conditions: (1) Oral diseases, including periodontitis, bleeding gums or tooth decay. (2) The antibiotic regimen within the last 3 months. (3) Upper respiratory tract infection or rhinitis or pharyngitis whinth 1 month. (4) Smokers and alcohol abusers and other types of addicts. Healthy controls were simultaneously recruited into group N. All enrolled subjects completed the 72-h constant routine.