Causes And MEchanisms foR non-atopic Asthma in Children (CAMERA) Study: rationale and protocol

Causes And MEchanisms foR non-atopic Asthma in Children (CAMERA) Study: rationale and protocol | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Causes And MEchanisms foR non-atopic Asthma in Children (CAMERA) Study: rationale and protocol View ORCID Profile Mary Njoroge , Gabriela Pimentel Pinheiro , Cinthia Vila Nova Santana , Hajar Ali , Stephanie Hobbs , Santiago Mena-Bucheli , Natalia Romero-Sandoval , Steven Robertson , Charlotte E Rutter , Donna Davoren , Collin Brooks , Jeroen Douwes , Philip J Cooper , Harriet Mpairwe , View ORCID Profile Camila A Figueiredo , Alvaro A Cruz , Mauricio L Barreto , Neil Pearce , Lucy Pembrey , the CAMERA study group doi: https://doi.org/10.1101/2025.01.20.25320833 Mary Njoroge 1 Department of Medical Statistics, London School of Hygiene and Tropical Medicine Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mary Njoroge For correspondence: Mary.Njoroge{at}lshtm.ac.uk Gabriela Pimentel Pinheiro 8 ProAR Foundation and Federal University of Bahia , Salvador, Brazil Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cinthia Vila Nova Santana 8 ProAR Foundation and Federal University of Bahia , Salvador, Brazil Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hajar Ali 4 Centre for Public Health Research, Massey University , Wellington, New Zealand Find this author on Google Scholar Find this author on PubMed Search for this author on this site Stephanie Hobbs 4 Centre for Public Health Research, Massey University , Wellington, New Zealand Find this author on Google Scholar Find this author on PubMed Search for this author on this site Santiago Mena-Bucheli 6 School of Medicine, Universidad Internacional del Ecuador , Quito, Ecuador Find this author on Google Scholar Find this author on PubMed Search for this author on this site Natalia Romero-Sandoval 6 School of Medicine, Universidad Internacional del Ecuador , Quito, Ecuador Find this author on Google Scholar Find this author on PubMed Search for this author on this site Steven Robertson 1 Department of Medical Statistics, London School of Hygiene and Tropical Medicine Find this author on Google Scholar Find this author on PubMed Search for this author on this site Charlotte E Rutter 1 Department of Medical Statistics, London School of Hygiene and Tropical Medicine Find this author on Google Scholar Find this author on PubMed Search for this author on this site Donna Davoren 1 Department of Medical Statistics, London School of Hygiene and Tropical Medicine Find this author on Google Scholar Find this author on PubMed Search for this author on this site Collin Brooks 4 Centre for Public Health Research, Massey University , Wellington, New Zealand Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jeroen Douwes 4 Centre for Public Health Research, Massey University , Wellington, New Zealand Find this author on Google Scholar Find this author on PubMed Search for this author on this site Philip J Cooper 5 Fundacion Ecuatoriana Para Investigacion en Salud , Quito, Ecuador 6 School of Medicine, Universidad Internacional del Ecuador , Quito, Ecuador 7 Institute of Infection and Immunity, St George’s University of London , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Harriet Mpairwe 2 MRC/UVRI and LSHTM Uganda Research Unit , Entebbe, Uganda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Camila A Figueiredo 3 Institute of Health Sciences, Federal University of Bahia , Salvador, Brazil Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Camila A Figueiredo Alvaro A Cruz 8 ProAR Foundation and Federal University of Bahia , Salvador, Brazil Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mauricio L Barreto 3 Institute of Health Sciences, Federal University of Bahia , Salvador, Brazil 9 The Centre for Data and Knowledge Integration for Health (CIDACS) , Fiocruz, Bahia, Brazil Find this author on Google Scholar Find this author on PubMed Search for this author on this site Neil Pearce 1 Department of Medical Statistics, London School of Hygiene and Tropical Medicine Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lucy Pembrey 1 Department of Medical Statistics, London School of Hygiene and Tropical Medicine Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract The Causes And MEchanisms foR non-atopic Asthma in children (CAMERA) study was designed to investigate risk factors and mechanisms of non-atopic asthma in children and young adults in Brazil, Ecuador, Uganda, and New Zealand. Initial epidemiological analyses using existing datasets identified and compared risk factors for both atopic and non-atopic asthma. The focus of this paper is the protocol for sample collection and analysis of clinical data on possible non-atopic mechanisms. In each of the four centres, the CAMERA study will enroll 160 participants aged 10 – 28 years, equally distributed among atopic asthmatics (AA), non-atopic asthmatics (NAA), atopic non-asthmatics and non-atopic non-asthmatics. Participants will be new recruits or returning World ASthma Phenotypes (WASP) study participants. Phase I consists of skin prick tests to define atopy, a general CAMERA questionnaire that covers respiratory and general health to identify asthma cases, followed by an asthma control questionnaire for asthmatics only. Phase II consists of a stress questionnaire and the following clinical assessments: lung function, nasal cytology, blood sampling, in vitro whole blood stimulation to assess IFN-γ production, hair cortisol concentration, dry air and capsaicin challenges, plus in a subset, cold air challenges. Analyses will compare inflammatory, physiological and clinical parameters across the four groups overall and by country. Here, we present the protocol for the CAMERA study, to provide relevant methodological details for CAMERA publications and to allow other centres globally to conduct similar analyses. The findings of this mechanistic multi-centre study will inform new and phenotype-specific prevention and treatment approaches. Introduction Childhood asthma is a major global public health burden with increasing prevalence in low-and- middle-income-countries (LMICs) ( 1 ), and generally high (but varied) asthma prevalence across high-income countries (HICs) ( 2 ). Asthma is now considered to be a heterogenous disease associated with multiple causal pathways that result in similar clinical effects including respiratory symptoms and variable airways obstruction ( 3 ). The mechanisms underlying different asthma phenotypes vary, and those associated with non-atopic disease remain poorly understood. The concepts of atopic and non-atopic asthma have evolved since their introduction in the late 1940s by Rackemann, who referred to them as extrinsic and intrinsic asthma respectively ( 4 ). Atopic asthma (AA) is classified based on symptoms triggered by common allergens, and confirmed by serum specific IgE or a positive skin prick test (SPT) to relevant aeroallergens. It is often associated with Th2-mediated eosinophilic airway inflammation ( 5 , 6 ). On the other hand, the mechanisms underlying non-atopic asthma (NAA) ( 7 ), remain unclear. While studies in the 1990s demonstrated elevated Th2 cytokines in some cases, non-Th2 pathways are also implicated, including neutrophilic inflammation associated with Th1 and Th17 responses and increased levels of IL-8, IL-17A, and IL-1β in certain patient subgroups ( 8 ). However, there is often no clear evidence of any airway inflammation (i.e. paucigranulocytic), and, paradoxically, eosinophilic airway inflammation may be present ( 9 ). NAA can be exacerbated by triggers such as exercise and environmental exposures such as cold and dry air rather than allergens ( 10 ). Even though neural pathways, non-atopic, non-Th2 inflammatory processes and chronic stress are possible mechanisms underlying NAA, evidence for this is scant. This is likely to be because NAA has been relatively understudied; possibly due to high AA prevalence in HICs and the prevailing dogma over several decades that asthma is an allergic condition. However NAA is relatively common in LMICs compared to HICs ( 11 ). It is therefore important to understand the causes and mechanisms of NAA to identify potential risk factors and elucidate underlying mechanisms to enable the development of targeted disease management approaches in both HICs and resource-limited LMIC settings. Our previous World Asthma Phenotypes (WASP) study found that asthma characteristics in LMICs and HICs varied substantially; around half were non-eosinophilic in New Zealand (NZ) and United Kingdom and around two-thirds were non-eosinophilic in Ecuador, Brazil and Uganda ( 12 ). Initial work on the CAMERA study using existing datasets showed that although atopy increases asthma risk, risk factors for developing asthma were similar in atopic and non-atopic people. However, as the mechanisms of NAA are not well understood, there could be other important risk factors that were not captured ( 13 ). Studies have increasingly focused on understanding the underlying mechanisms of NAA in addition to identifying risk factors. For example, previously reported data from Brazil showed that interferon-gamma (IFN-γ) production in House dust mite (Dermatophagoides pteronyssinus) allergen-stimulated peripheral blood leukocytes was higher in NAA than in AA ( 14 ). Given that non-eosinophilic asthma (based on sputum) and NAA overlap by approximately 60-70% ( 15 , 16 ), and Chen et al. reported overlap in both inflammatory and clinical characteristics ( 17 ), we will analyse inflammatory phenotypes (using nasal lavage) and atopic status (using SPT) to better characterise immunopathology in these distinct but related phenotypes. To investigate non-inflammatory mechanisms, we will use specific challenge tests: dry/cold air challenges to assess airway hyperresponsiveness, and capsaicin challenges to evaluate sensory nerve reactivity. A small study by Ali et al. reported enhanced capsaicin sensitivity among non-eosinophilic asthmatics compared to non-asthmatics, with a similar trend observed when compared to eosinophilic asthmatics (but only weak evidence of a difference for the latter). Notably, capsaicin sensitivity was not associated with atopic status, highlighting the potential role of sensory nerve reactivity in the pathophysiology of NAA ( 17 ). The CAMERA study will clarify the role of these potential mechanisms by assessing a wider range of participants from varying settings with respect to geography, asthma prevalence, socioeconomic status, ethnicity, and environmental exposures. The CAMERA study therefore builds on the WASP study findings and framework to investigate possible neural and non-neural mechanisms relevant to NAA across diverse populations (Figure S1). Here, we present the rationale, design, and study procedures for the CAMERA study clinical investigations. Study Protocol Study centres, groups and recruitment CAMERA is a cross-sectional design that will enrol children, adolescents and young adults aged 10 – 28 years; recruitment methods and ages vary by centre. Brazil (12 – 28 years) will recruit from the previous WASP study and the Programme for Control of Asthma in Salvador (ProAR) database. Ecuador (10 – 24 years) will recruit new participants with asthma from a public specialist hospital registry in Portoviejo, Manabi province, and in the community where patients live (1 per case). Uganda (13 – 23 years) will recruit WASP participants and additional participants from primary, secondary, and tertiary schools in Wakiso district, Entebbe. New Zealand (16 – 22 years) will recruit from the WASP study population and local community (schools, universities and medical centres). Each centre will enrol 160 eligible participants to obtain four groups of 40 participants representing AA, NAA, atopic non-asthmatics, and non-atopic non-asthmatics. Atopy will be defined by SPT positivity to a standardised allergen panel (Table S1) using WASP protocol methodology ( 18 ). Identification of asthma cases and non-asthmatics Asthma cases will be identified on the basis of current asthma symptoms and/or medication-use in the past 12 months using a screening questionnaire ( 19 ). Non-asthmatics will have had no asthma diagnosis and no current/previous asthma symptoms ( Table 1 ). View this table: View inline View popup Table 1: General exclusion criteria for asthmatic and non-asthmatic participants Data collection Data will be collected using standardised instruments and clinical tests using validated protocols. Questionnaires will assess respiratory health, asthma control ( 20 ) and perceived stress ( 21 ). Blood, hair and nasal samples will be collected. Respiratory assessments will include lung function testing, capsaicin challenge, dry air challenge, and cold air challenge. Questionnaires The asthma and triggers questionnaire (adapted from the ISAAC phase II questionnaire ( 19 )) will collect data about respiratory health (asthma history, symptoms and triggers) and medication use in the year before recruitment, active smoking and vaping, and general health. The Asthma Control Questionnaire will collect data on current asthma symptoms and management ( 20 ) from asthma cases only. A questionnaire based on the standard Cohen questionnaire ( 21 ) will be administered on the day of hair sample collection to evaluate participants’ stress levels in the last four weeks, the occurrence of potential stressful events and whether they have induced or worsened respiratory symptoms. Skin Prick Test (SPT) The SPT will follow a standardised protocol ( 22 ). Histamine and saline will be used as positive and negative controls, respectively. A positive reaction will be defined as a mean wheal size of ≥3mm (after subtracting the negative control wheal size) fifteen minutes after the test. A positive reaction to at least one allergen from the panel will be considered a positive SPT. The panel includes house dust mite, cat/dog dander, mixed tree pollen and centre-specific allergens (Immunotech USA and Inmunotek Europe) (Table S1). Lung Function Test (LFT) LFT will be conducted according to American Thoracic Society (ATS) criteria ( 23 ). Spirometry will be performed using portable ultrasonic devices (e.g. EasyOne ndd Medical Technologies, Zurich, Switzerland). All spirometers will undergo regular tests by the suppliers. Participants will maintain a sitting position during the test, and the best of three reproducible forced expiratory manoeuvres will be used to obtain the following lung function parameters: Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 second (FEV 1 ), FEV/FVC ratio, Maximal Mid-Expiratory Flow (MMEF) and Peak Expiratory Flow (PEF). Nasal lavage Nasal lavage will be conducted using a standardised protocol ( 24 ). Mucosal Atomisation Devices (MAD) will be used to deliver sterile saline or phosphate buffered saline (PBS) solution (2 ml) into each nostril, and the sample will be collected using a conical tube/funnel once the participant blows strongly through the nostril into the funnel; this will be repeated for the other nostril. Cell suspensions will be counted, centrifuged, and stained (Diff-Quik; Dade Behring, Deerfield, Illinois, USA). The laboratory in Brazil will complete the inflammatory cell counts for all centres. Blood sampling 10 mL of venous blood will be collected using Vacutainer tubes (Sodium heparin and serum separator tube, Becton Dickinson) for eosinophil counts, whole blood culture for IFN-γ, and total and allergen-specific IgE (asIgE) measurement. Samples will undergo processing within 4-6 hours of collection. IFN-γ Heparinised whole blood will be diluted at a 1:4 ratio in Roswell Park Memorial Institute (RPMI) medium containing 10 mM glutamine and 100 ug/mL gentamicin in 0.5 ml tissue culture wells and maintained at 37 0 C in a humidified 5% CO 2 incubator for five days. Culture conditions will include unstimulated (medium alone), pokeweed mitogen (Sigma/Merck) (2.5µg/ml), and Dermatophagoides pteronyssinus antigen (LoTox Der p 1, 20µg/mL, catalog number: LTN-DP1-1, Inbio Charlottesville, USA). Supernatants will be collected into 1.5 mL tubes and stored at -70°C until analysis. Supernatants will be analysed using an IFN-γ enzyme-linked immunosorbent assay (ELISA) following the manufacturer’s instructions (R&D Systems/ BD OptEIA™ Phamingen San Diego, USA). Hair cortisol Hair samples (approximately 50-350mg or 1cm long) will be collected from the posterior vertex region of the scalp, cut close to the scalp surface, stored in specimen paper within resealable envelopes, and maintained at room temperature in dark conditions ( 25 ). Cumulative cortisol concentration, a stress biomarker ( 26 ), will be measured from ≥10 mg of hair cut from the scalp end per sample. The sample will be cut into pieces and incubated overnight in 1ml methanol at 52°C. The resulting supernatant will be air-dried in a refrigerator and reconstituted in PBS based on sample weight. Cortisol levels in the hair supernatant will be quantified using an ELISA cortisol kit ( Biomatik Cortisol (Cor) ELISA kit, cat# EKU03476, Wilmington, USA). Dry air challenge Bronchial provocation using dry mixed air (21% O 2 , 74% N 2, with 5% CO 2 to prevent dizziness) will follow a well-defined protocol ( 27 ). Spirometry will be conducted to measure baseline FEV 1 , and the challenge will only be conducted if FEV 1 ≥75% predicted value. Dry mixed air will be continuously provided through two 20L breathing bags, with participants inhaling for six minutes (via mouthpiece with nose clipped). During this time, participants will increase and sustain their ventilation rate at 60% of the maximum voluntary ventilation (MVV; or FEV 1 × 35), with an acceptable ventilation range of 16-25 times baseline FEV 1 ( 28 , 29 ). The minute ventilation rate will be monitored and guided using a ventilation meter (TAC-7715, Equilibrated Bio Systems, Inc., Melville, New York, USA); verbal guidance will be provided throughout the test. For safety, a fingertip pulse oximeter will be used throughout to ensure oxygen saturation levels (saO 2 ) remain above 85%. After the challenge, participants will undergo spirometry at 5, 10, 15 and 30 minutes. A ≥10% fall in FEV 1 post-challenge will be considered a positive eucapnic voluntary hyperpnea (EVH) test ( 30 ). Salbutamol (200 mcg) will be administered if there is a FEV 1 drop ≥ 15%. Participants will be monitored closely post-challenge for any adverse reactions using centre-specific safety assessment procedures. Capsaicin challenge Capsaicin challenge using inhaled capsaicin solution (Stockport Pharmaceuticals, UK) will be conducted based on European Respiratory Society (ERS) guidelines ( 31 ). Solutions will be prepared daily following a standardised capsaicin dilution protocol, with doubling concentrations (0.98 – 500 μM) and a negative (saline) control ( 32 ). With participants in a sitting position, a compressed air-driven jet nebuliser controlled by a dosimeter (ProvoX, Ganshorn, Germany) will be used to administer single doses of aerosolised capsaicin solution via a mouthpiece. After dose administration, the number of coughs during the subsequent 30 seconds will be recorded. After this period, urge to cough (using a Borg scale) and instances of throat clearing (TC) will also be recorded. This will then be repeated with the increasing capsaicin dosages, with a one-minute delay before administering the next concentration. The lowest concentration that elicits two and five coughs, C2 and C5, respectively, will be recorded ( 33 ). For safety, spirometry will be conducted at baseline, mid-point (for participants with dyspnoea) and post-challenge. Salbutamol (200 mcg) will be administered if FEV 1 drops below 75% of predicted. Participants will be monitored closely post-challenge for any adverse reactions using centre-specific safety assessment procedures. Cold air challenge Bronchial provocation will be assessed in NZ and Uganda using cold, dry mixed air according to a well-defined existing protocol ( 27 , 34 ). Following baseline spirometry, participants will inhale cold (- 20°c), dry air (21% O 2 , 74% N 2 , with 5% CO 2 to prevent dizziness) for 3 minutes at rest. They will then be asked to increase ventilation rate (hyperventilate) at a target ventilation rate of 60% of MVV, with an acceptable range of ventilation of 16-25 times baseline FEV 1 during the challenge ( 35 ). The minute ventilation rate and safety will be monitored and guided as described for the dry air challenge. Participants will undergo spirometry at 5, 10, 15 and 30 minutes post challenge and a positive challenge response will be defined as a 10-15% decrease in FEV1. Data Management and Analysis Electronic data will be collected using Kobo Toolbox or REDCap (Research Electronic Data Capture) databases. For NZ, data will be backed up using Microsoft Access database. Centre-specific quality control measures include mandatory completion of electronic fields, medical record review and completion verification within 48 hours of each visit, and internal data audits before data transfer. Pseudonymised data, identifiable by participants’ identification number and date of birth (age in years), will be transferred securely to the London School of Hygiene and Tropical Medicine (LSHTM) for centralised processing and review. Data cleaning and quality checks will be conducted regularly by LSHTM researchers according to a detailed data transfer guide and study manual. Data will be analysed using STATA 18 ( 36 ) and R v 4.3.3 ( 37 ). Descriptive analyses will be conducted to describe AA/NAA and atopic/non-atopic non-asthmatics using demographic data, respiratory health, asthma characteristics (triggers, control, treatment), active smoking, baseline/post-challenge predicted lung function parameters, SPT/asIgE data, and blood eosinophils. Primary analyses will compare continuous outcomes from test data collected in the four study groups within each centre. Statistical analysis will include t-tests to compare geometric means of capsaicin cough concentrations, inflammatory markers and IFN-γ levels; generation of standard hair cortisol concentration curves; comparison of FEV 1 reductions from baseline values for dry and cold air challenges, across study groups and centres; evaluation of capsaicin cough concentrations by country, ethnicity, and asthma medication use. We will also assess differences in FEV 1 responses between dry and cold air challenges in NZ and Uganda. Multivariable linear regression adjusting for study centre and potential confounders will be used to examine associations between mechanistic outcomes and atopy/non-atopy. We will test if associations differ by study centre and stratify if indicated. Any between-centre differences will be explored, accounting for variations in geographic settings, environmental exposures, socioeconomic factors and asthma prevalence. Study size and power Based on previous estimates ( 17 ), the CAMERA study will have 80% power to detect a 0.65 standard deviation difference between groups for continuous outcomes, with 40 participants per group (AA, NAA, atopic non-asthmatics, non-atopic non-asthmatics) per centre. Pooling findings across centres will further increase the power to detect smaller differences. For binary outcomes, assuming a 25% outcome in one group and 50% in another, there will be 82% power to detect a 50% difference in proportions between different groups, with 160 participants in each of the four groups of interest overall. Ethical considerations Ethical approval was obtained from LSHTM (ref: 26308 - 1) and all participating centres prior to commencing the study as follows: the Brazilian National Research Ethics Council (number 59164922.6.0000.5577), Hospital San Francisco de Quito (Unique Approval Ethics Committee Code CEISH-HGSF-2022-023), NZ Health and Disability Ethics Committees (ref: 2022 EXP 12986) and Uganda National Council for Science and Technology (ref: 2022 EXP 12986). Discussion In light of the poorly understood and understudied mechanisms of NAA and degree of overlap with non-eosinophilic asthma in LMICs and HICs, the findings of this multi-centre study will inform new and phenotype-specific prevention and treatment approaches. Identifying different mechanisms (i.e. physiological, inflammatory or neural) could help inform policies around non-pharmacological approaches, such as physical exercise/weight loss ( 38 ), improving indoor air quality ( 38 ), smoking cessation, and stress management techniques ( 3 ), to tackling NAA in different settings. Understanding neural mechanisms could help guide the development of novel pharmacological interventions targeting non-eosinophilic inflammatory mechanisms in asthma. By leveraging multidimensional data, including inflammatory markers, lung function, and neural sensitivity tests, we aim to uncover previously unrecognised mechanisms driving NAA in diverse populations. Given that this is a multi-country study, we have carefully standardised methods and protocols for each procedure for consistency, and have conducted extensive procedure training, quality control, and training on equipment use and assembly and specific clinical tests and challenges. This study promotes equitable, ethical and mutually beneficial partnerships ensuring that the main outcomes align with local public health needs and priorities. The data management and analysis process aims to leverage local resources equitably while respecting intellectual property rights and adhering to local regulations. Ultimately, we will use these standardised protocols to compare geographically diverse populations and will incorporate challenge tests beyond those typically included in epidemiological studies to focus on the poorly understood but very important NAA phenotype. The CAMERA protocol incorporates more detailed mechanistic investigations compared to previous studies, such as the WASP study ( 16 ). This study will provide novel insights into the mechanisms of NAA across HICs and LMICs and potentially help address the disproportionate burden of NAA across different geographical and income settings. To our knowledge, this observational study will be the first to provide an in-depth evaluation of mechanisms underlying NAA in children and young adults globally. We are presenting this protocol to allow reproducibility of the methods and procedures, and to enable other researchers to conduct studies within HICs or LMICs using a standardised protocol. Data Availability As this study is currently ongoing, no data are available at this time. Conflict of interest CB is supported by a Health Research Council of New Zealand, Sir Charles Hercus Fellowship. JD has served on the Board of the New Zealand Health Research Council, which is completely independent from the CAMERA study work. AAC has received grants from ERC, EMS and Boehringer Ingelheim, honoraria payment for lectures from Eurofarma, Astrazeneca, Chiesi, GSK, Sanofi and Farmoquimica; and serves on the board of the Global Initiative for Asthma (GINA). All other authors declare no competing interests. Support statement The CAMERA project was supported by the European Research Council under ERC grants 668954 and 101020088. The CAMERA Study group: United Kingdom, London: Neil Pearce, Lucy Pembrey, Mary Njoroge, Steven Robertson, Charlotte E Rutter, Donna Davoren, David Rebellon Sanchez Brazil: Alvaro Cruz, Camila Figueiredo, Mauricio Barreto, Cinthia Vila Nova Santana, Gabriela Pimentel Pinheiro, Gilvaneide Lima, Leticia Marques, Auxiliadora Damiane Costa, Karla Nicole, Candace Andrade, Bianca Sampaio Dotto Fiuza, Luciano Gama da Silva Gomes,, Louise Correia de Lima, Mel Matos de Carvalho Espinheira, Manoela Souza Trindade Fontes, Carolina Barbosa Souza Santos, Emile Ivana Fernandes Santos Costa, Rayane Anselmo dos Santos Ribeiro, Thalia Raney Alves Pereira Santos. Ecuador: Philip Cooper, Natalia Romero-Sandoval, Santiago Mena, Lucia Alonzo, Genesis Palma, Maria Fernanda Arias, Jessica Alchundia, Karla Solorzano, Martha Chico. New Zealand: Jeroen Douwes, Collin Brooks, Hajar Ali, Jeroen Burmanje, Stephanie Hobbs Uganda: Harriet Mpairwe, Irene Nambuya, Pius Tumwesige, Milly Namutebi, Marble Nnaluwooza, Mike Mukasa Acknowledgements We are grateful to the returning WASP and new CAMERA participants, researchers and lab technicians for conducting clinical tests and sample processing, LSHTM researchers for data management and analysis and the hospitals and institutions at ProAR, Massey University, MRC Uganda and Manabí, Ecuador, for allowing CAMERA researchers to use their facilities during phase II of the study. References 1. ↵ Global Initiative for Asthma . Global strategy for Asthma Management and Prevention . 2021 . 2. ↵ GAN . The Global Asthma Report asthma symptoms controlled symptoms essential asthma medicines . Vol. 26 , Int J Tuberc Lung Dis . 2022 . 3. ↵ Pauddyal P , Jones C , Grindey C , Dawood R , Smith H . Meditation for asthma: Systematic review and meta-analysis . J Asthma . 2018 ; 55 ( 7 ): 771 – 8 . OpenUrl PubMed 4. ↵ Rackemann FM . A working classification of asthma . Am J Med . 1947 ; 3 ( 5 ): 601 – 6 . OpenUrl CrossRef PubMed 5. ↵ Howell I , Howell A , Pavord ID . Type 2 inflammation and biological therapies in asthma: Targeted medicine taking flight . J Exp Med . 2023 ; 220 ( 7 ): 1 – 12 . OpenUrl 6. ↵ Hussain M , Liu G . Eosinophilic Asthma: Pathophysiology and Therapeutic Horizons . Cells . 2024 ; 13 ( 5 ). 7. ↵ Gerday S , Schleich F , Henket M . Revisiting differences between atopic and non-atopic asthmatics : When age is shaping airway in fl ammatory pro fi le . 2022 ;( March ): 1 – 14 . 8. ↵ Sze E , Bhalla A , Nair P . Mechanisms and therapeutic strategies for non - T2 asthma . Eur J Allergy Clin Immunol . 2020 ; 75 : 311 – 25 . OpenUrl 9. ↵ Jutel M , Agache I , Zemelka-Wiacek M , Akdis M , Chivato T , del Giacco S , et al. Nomenclature of allergic diseases and hypersensitivity reactions: Adapted to modern needs: An EAACI position paper. Allergy Eur J Allergy Clin Immunol . 2023 ; 78 ( 11 ): 2851 – 74 . OpenUrl 10. ↵ Klain A , Dinardo G , Salvatori A , Indolfi C , Contieri M , Brindisi G , et al. An Overview on the Primary Factors That Contribute to Non-Allergic Asthma in Children . J Clin Med . 2022 ; 11 ( 21 ): 6567 . OpenUrl PubMed 11. ↵ Asher MI , García-marcos L , Pearce NE , Strachan DP . Trends in worldwide asthma prevalence . (June 2020 ): 1 – 14 . Available from : doi: 10.1183/13993003.02094-2020 OpenUrl Abstract / FREE Full Text 12. ↵ Pembrey L , Brooks C , Mpairwe H , Figueiredo CA , Oviedo AY , Chico M , et al. Asthma inflammatory phenotypes on four continents: most asthma is non-eosinophilic . 2022 ; 1 – 13 . 13. ↵ Rutter CE , Mpairwe H , Figueiredo CA , Njoroge M , Robertson S , Ali H , et al. Risk factors for atopic and non-atopic asthma in school-aged children from high-, and low-and-middle-income countries . medRxiv [Internet] . 2024 Jan 1;2024.06.03.24308369. Available from: http://medrxiv.org/content/early/2024/06/25/2024.06.03.24308369.abstract 14. ↵ Figueiredo CA , Rodrigues LC , Alcantara-Neves NM , Cooper PJ , Amorim LD , Silva NB , et al. Does IFN-γ play a role on the pathogenesis of non-atopic asthma in Latin America children? Allergy , Asthma Clin Immunol [Internet] . 2012 ; 8 ( 1 ): 1 . Available from: Allergy, Asthma & Clinical Immunology OpenUrl 15. ↵ Ricciardolo FLM , Guida G , Bertolini F , Di Stefano A , Carriero V . Phenotype overlap in the natural history of asthma . Eur Respir Rev [Internet] . 2023 ; 32 ( 168 ). Available from : doi: 10.1183/16000617.0201-2022 OpenUrl Abstract / FREE Full Text 16. ↵ Berry M , Morgan A , Shaw DE , Parker D , Green R , Brightling C , et al. Pathological features and inhaled corticosteroid response of eosinophilic and non-eosinophilic asthma . Thorax . 2007 ; 62 ( 12 ): 1043 – 9 . OpenUrl Abstract / FREE Full Text 17. ↵ Ali H , Brooks C , Crane J , Beasley R , Holgate S , Gibson P , et al. Enhanced airway sensory nerve reactivity in non-eosinophilic asthma . BMJ Open Respir Res . 2021 ; 8 ( 1 ). 18. ↵ Pembrey L , Barreto ML , Douwes J , Cooper P , Henderson J , Mpairwe H , et al. Understanding asthma phenotypes: The world asthma phenotypes (WASP) international collaboration . ERJ Open Res [Internet] . 2018 ; 4 ( 3 ). Available from : doi: 10.1183/23120541.00013-2018 OpenUrl Abstract / FREE Full Text 19. ↵ Weiland SK , Björkstén B , Brunekreef B , Cookson WOC , von Mutius E , Strachan DP , et al. Phase II of the International Study of Asthma and Allergies in Childhood (ISAAC II): Rationale and methods . Eur Respir J . 2004 ; 24 ( 3 ): 406 – 12 . OpenUrl Abstract / FREE Full Text 20. ↵ Juniper EF , Byrne PMO , Guyatt GH , Ferrie PJ , King DR . Development and validation of a questionnaire to measure asthma control . 1999 ; 902 – 7 . 21. ↵ Cohen , Sheldon ; Karmarck , Tom ; Mermelstein R . A global measure of perceived stress . J Heal Soc Behav . 1983 ; 24 ( 4 ): 385 – 96 . OpenUrl 22. ↵ Weiland SK , Bjo B . Phase II of the International Study of Asthma and Allergies in Childhood (ISAAC II): rationale and methods . 2004 ; 406 – 12 . 23. ↵ Miller MR , Crapo R , Hankinson J , Brusasco V , Burgos F , Casaburi R , et al. General considerations for lung function testing . Eur Respir J . 2005 ; 26 ( 1 ): 153 – 61 . OpenUrl FREE Full Text 24. ↵ Ardura-Garcia C , Arias E , Hurtado P , Bonnett LJ , Sandoval C , Maldonado A , et al. Predictors of severe asthma attack re-attendance in Ecuadorian children: A cohort study . Eur Respir J [Internet] . 2019 ; 54 ( 5 ). Available from : doi: 10.1183/13993003.02419-2018 OpenUrl Abstract / FREE Full Text 25. ↵ Meyer J , Novak M , Hamel A , Rosenberg K . Extraction and analysis of cortisol from human and monkey hair . J Vis Exp . 2014 ;( 83 ): 1 – 6 . OpenUrl 26. ↵ Stephens MAC , Wand G . Stress and the HPA axis: Role of glucocorticoids in alcohol dependence . Alcohol Res Curr Rev . 2012 ; 34 ( 4 ): 468 – 83 . OpenUrl 27. ↵ Hallstrand TS , Leuppi JD , Joos G , Hall GL , Carlsen KH , Kaminsky DA , et al. ERS technical standard on bronchial challenge testing: Pathophysiology and methodology of indirect airway challenge testing . Eur Respir J . 2018 ; 52 ( 5 ). 28. ↵ Anderson SD , Argyros GJ , Magnussen H , Holzer K . Provocation by eucapnic voluntary hyperpnoea to identify exercise induced bronchoconstriction . Br J Sports Med . 2001 ; 35 ( 5 ): 344 – 7 . OpenUrl Abstract / FREE Full Text 29. ↵ Brannan JD , Kippelen P . Bronchial Provocation Testing for the Identification of Exercise-Induced Bronchoconstriction . J Allergy Clin Immunol Pract [Internet] . 2020 ; 8 ( 7 ): 2156 – 64 . Available from : doi: 10.1016/j.jaip.2020.03.034 OpenUrl CrossRef 30. ↵ Rizzo J. , de Barros Albuquerque LC. , Medeiros D . Ventilation Rates Achieved in Eucapnic Voluntary Hyperpnea Challenge and Exercise-Induced Bronchoconstriction Diagnosis in Young Patients with Asthma . Lung . 2022 ; 200 : 229 – 36 . OpenUrl PubMed 31. ↵ Morice AH , Fontana GA , Belvisi MG , Birring SS , Chung KF . ERS TASK FORCE ERS guidelines on the assessment of cough SUMMARY OF KEY POINTS AND . 2007 ; 1256 – 76 . 32. ↵ Doherty MJ , Mister R , Pearson MG , Calverley PMA . Capsaicin responsiveness and cough in asthma and chronic obstructive pulmonary disease . Thorax . 2000 ; 55 ( 8 ): 643 – 9 . OpenUrl Abstract / FREE Full Text 33. ↵ Mai Y , Fang L , Zhong S , Shaniya SD , Silva H De , Chen R. Methods for assessing cough sensitivity . 2020 ; 12 ( 9 ): 5224 – 37 . OpenUrl 34. ↵ Systems EB . Cold Air Bronchial Provocation Technical Theoretical Issues and Issues Protocol Project Editor : Ira Bauer . 1998 ;( 631 ). Available from: www.ebsmed.com 35. ↵ Anderson SD , Kippelen P. Assessment of EIB. What You Need to Know to Optimize Test Results . Immunol Allergy Clin North Am . 2013 ; 33 ( 3 ): 363 – 80 . OpenUrl CrossRef PubMed 36. ↵ StataCorp . Stata Statistical Software: Release 18 . College Station, TX: StataCorp LLC. [Internet] . 2023 . Available from: https://www.stata.com/ 37. ↵ R Core Team . R: A language and environment for statistical computing (Version 4.3.3) [Internet] . Viena, Austria : R Foundation for Statistical Computing ; 2023 . Available from: https://www.r-project.org 38. ↵ Dias-Júnior SA , Reis M , De Carvalho-Pinto RM , Stelmach R , Halpern A , Cukier A . Effects of weight loss on asthma control in obese patients with severe asthma . Eur Respir J . 2014 ; 43 ( 5 ): 1368 – 77 . OpenUrl Abstract / FREE Full Text View the discussion thread. Back to top Previous Next Posted January 20, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Causes And MEchanisms foR non-atopic Asthma in Children (CAMERA) Study: rationale and protocol Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Causes And MEchanisms foR non-atopic Asthma in Children (CAMERA) Study: rationale and protocol Mary Njoroge , Gabriela Pimentel Pinheiro , Cinthia Vila Nova Santana , Hajar Ali , Stephanie Hobbs , Santiago Mena-Bucheli , Natalia Romero-Sandoval , Steven Robertson , Charlotte E Rutter , Donna Davoren , Collin Brooks , Jeroen Douwes , Philip J Cooper , Harriet Mpairwe , Camila A Figueiredo , Alvaro A Cruz , Mauricio L Barreto , Neil Pearce , Lucy Pembrey , the CAMERA study group medRxiv 2025.01.20.25320833; doi: https://doi.org/10.1101/2025.01.20.25320833 Share This Article: Copy Citation Tools Causes And MEchanisms foR non-atopic Asthma in Children (CAMERA) Study: rationale and protocol Mary Njoroge , Gabriela Pimentel Pinheiro , Cinthia Vila Nova Santana , Hajar Ali , Stephanie Hobbs , Santiago Mena-Bucheli , Natalia Romero-Sandoval , Steven Robertson , Charlotte E Rutter , Donna Davoren , Collin Brooks , Jeroen Douwes , Philip J Cooper , Harriet Mpairwe , Camila A Figueiredo , Alvaro A Cruz , Mauricio L Barreto , Neil Pearce , Lucy Pembrey , the CAMERA study group medRxiv 2025.01.20.25320833; doi: https://doi.org/10.1101/2025.01.20.25320833 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Epidemiology Subject Areas All Articles Addiction Medicine (570) Allergy and Immunology (864) Anesthesia (302) Cardiovascular Medicine (4445) Dentistry and Oral Medicine (444) Dermatology (383) Emergency Medicine (609) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1515) Epidemiology (15236) Forensic Medicine (30) Gastroenterology (1127) Genetic and Genomic Medicine (6610) Geriatric Medicine (669) Health Economics (1000) Health Informatics (4549) Health Policy (1370) Health Systems and Quality Improvement (1613) Hematology (543) HIV/AIDS (1266) Infectious Diseases (except HIV/AIDS) (15926) Intensive Care and Critical Care Medicine (1104) Medical Education (623) Medical Ethics (147) Nephrology (668) Neurology (6613) Nursing (346) Nutrition (999) Obstetrics and Gynecology (1147) Occupational and Environmental Health (957) Oncology (3341) Ophthalmology (975) Orthopedics (369) Otolaryngology (420) Pain Medicine (436) Palliative Medicine (130) Pathology (665) Pediatrics (1694) Pharmacology and Therapeutics (693) Primary Care Research (714) Psychiatry and Clinical Psychology (5458) Public and Global Health (9244) Radiology and Imaging (2205) Rehabilitation Medicine and Physical Therapy (1370) Respiratory Medicine (1197) Rheumatology (596) Sexual and Reproductive Health (715) Sports Medicine (530) Surgery (713) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a02354d70966dfa9',t:'MTc3OTg2NzIwNg=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();