MD, PhD Guillaume Sacco
email: yogisacco@gmail.com

MD Gonzague Foucault
email: foucault.gonzague@chu-angers.fr

BS Olivier Briere
email: olivierbriere53@gmail.com

MD, PhD Cédric Annweiler
email: cedric.annweiler@chu-angers.fr

COVID-19 in seniors: Findings and lessons from mass screening in a nursing home

Keywords: COVID-19, SARS-CoV-2, prognosis, symptoms, older adults, nursing home

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Since December 2019, the SARS-CoV-2 virus is propagating worldwide from China. As of 4 May 2020, the COVID-19 pandemic has infected more than 3 500 000 people in 194 countries around the world, leaving 248 800 dead, mostly in frail older adults aged 70 years and over. First epidemiological data confirm that older adults are more prone to develop severe and lethal forms of COVID-19 [START_REF] Deng | Clinical characteristics of fatal and recovered cases of coronavirus disease 2019 (COVID-19) in Wuhan, China: a retrospective study[END_REF]. Clinical data regarding older patients' symptomatology are yet limited [START_REF] Sacco | Symptoms of COVID-19 among older adults: systematic review of biomedical literature[END_REF], and the first report on oldest-old people (i.e., aged 80 years and over) with major neurocognitive disorders revealed clinical peculiarities that make difficult to diagnose COVID-19 during the first days of the infection [START_REF] Annweiler | National French survey of symptoms in people aged 70 and over diagnosed with COVID-19[END_REF]. What is more, previous studies described individuals for whom tests had been performed following a clinical suspicion, which could have biased the prevalence of some symptoms [START_REF] Annweiler | National French survey of symptoms in people aged 70 and over diagnosed with COVID-19[END_REF]. Thus, specific attention should be paid to older people in nursing homes for whom mass screening had been organized. Whilst residents of nursing homes seem seriously affected by the SARS-CoV-2 infection [START_REF] Mcmichael | COVID-19 in a Long-Term Care Facility -King County[END_REF], clinical and epidemiological data remain yet fragmented thus far [START_REF] Roxby | Detection of SARS-CoV-2 Among Residents and Staff Members of an Independent and Assisted Living Community for Older Adults -Seattle, Washington, 2020[END_REF][START_REF] Kimball | Asymptomatic and Presymptomatic SARS-CoV-2 Infections in Residents of a Long-Term Care Skilled Nursing Facility -King County, Washington, March 2020[END_REF]. The objective of the present study was to clarify symptoms and chronological aspects of the propagation of the SARS-CoV-2 in a nursing home, both in residents and staff members.

METHODS

Design and settings

The study consisted in a five-week retrospective observational cohort study in a middle-sized nursing home in Maine-et-Loire, West of France, having performed COVID-19 mass screening of residents (n=87) and staff members (n=92).

The nursing home is dedicated to patients with major neurocognitive disorders combined with behavioral disturbances. The facility includes 86 apartments (with one couple living in a single apartment), along with communal dining, library, and activity areas. The nursing home is divided into five units: one day care unit, one open unit, and three secured closed units. The open unit is dedicated to patients with mild major neurocognitive disorders but poor autonomy. Closed units are dedicated to patients with severe behavioral disturbances including wandering.

All 87 residents were allowed to move around the building until 16 March 2020, while social distancing and other preventive measures were implemented. Residents were isolated in their rooms with no communal meals or group activities. No visitors, including families, were allowed in the nursing home since 10 March 2020. Walks in the garden were organized for the residents one by one, in the presence of one staff member. Residents could receive and update their families by phone or video. Mail and packages were stored 24h before being delivered to residents. Enhanced hygiene measures were implemented, including cleaning and disinfection of frequently touched surfaces, permanent face masks, and additional hand hygiene stations for staff members.

In total, 92 individuals were working as staff members during the study. The teams change three times a day, i.e. in the morning, in the afternoon and at night.

The study was conducted in accordance with the ethical standards set forth in the Helsinki Declaration (1983). No participant objected to the use of anonymized clinical and biological data for research purposes. The study was approved by an independent institutional review board under the number 2020/51. The study protocol was declared to the National Commission for Information Technology and civil Liberties (CNIL) under number ar20-0053v0. Infection with COVID-19 was defined for both residents and staff members as a positive result on RT-PCR tests of a specimen collected with nasopharyngeal swab in accordance with the World Health Organization standards [START_REF] Corman | Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR[END_REF]. Five residents had a test in hospital due to suggestive symptoms between 6 March 2020 and 24 March 2020, before tests were made available outside of the hospital. Other residents and staff members had a test as part of the mass screening on 2 April 2020 (5 staff members), 6 April (2 residents and 3 staff members), 8 April (18 residents and 6 staff members), 9 April (13 residents and 10 staff members), 14 April (18 residents and 12 staff members), 15 April (18 staff members), 16 April (16 residents and 14 staff members), 21 April (7 staff members) and 23 April 2020 (7 staff members). For patients who died without RT-PCR test, the cause of death indicated on the death certificate (i.e. related or not to COVID-19) was collected.

Data Collection

Residents

The following measures were collected for each resident: demographic (age, gender, residence unit), vaccinal status regarding influenza virus for the current year, clinical signs, date and result of the RT-PCR test, hospitalization (all-cause or specifically due to COVID- [START_REF] Wang | Updated understanding of the outbreak of 2019 novel coronavirus (2019-nCoV) in Wuhan, China[END_REF], and mortality (all-cause or specifically due to COVID-19). Finally, medical history of residents was extracted for the whole population using the PATHOS data [START_REF]Le modèle « PATHOS » Guide d'utilisation 2017[END_REF]. The mean weighted PATHOS is used in nursing homes to describe the care profile of residents. In fact 49 pertinent pathological statuses (but not the whole ICD 10) are described, including major neurocognitive disorders or abdominal pain for instance. Each pathological status is qualified by one of the 12 possible care profiles according to the clinical context (e.g., profile T2: requiring multiweekly medical supervision and 24-hour nursing care).

The following measures were collected for each staff member: date and result of the RT-PCR test, date of first COVID-19 symptoms if applicable, and position in the nursing home by distinguishing between caregivers (i.e. physician, nurses, assistant nurses, animator, physiotherapist, occupational therapist, psychomotrician), non-caregivers who had contact with residents (i.e. restaurant, laundry and housekeepers), and non-caregivers who had no contact with residents (administrative functions).

Statistical analyses

The participants' characteristics were summarized using mean and standard deviation (SD), median and 95% confidence interval (95CI), or frequency and percentage, as appropriate.

Normality of data was assessed using Kolmogorov-Smirnov test.

First, the case fatality rate (i.e., the number of deaths from COVID-19 divided by the total number of people diagnosed with COVID-19 during the study), the attack rate (i.e., the number of new cases during the study divided by the number of residents), and the persontime incidence rate per 100 person-days (i.e., as the number of new cases during the study divided by the sum of persons exposed each day during the study [considering that each new case was no longer exposed after COVID-19 diagnosis] divided by 100) were calculated.

Each positive case was excluded from people exposed either on the date of the first symptom, or on the date of the positive RT-PCR test for asymptomatic people, or on the date of work disruption for staff members when the two previous conditions were not met. For those with positive RT-PCR test but no symptoms, the date of the screening test was used to calculate the incidence rate.

Second, participants were divided into three groups according to the COVID-19 status, i.e. the "COVID-19 group" for those with a positive RT-PCR test or death attributed to COVID-19, the "non-COVID-19 group" for those with a negative RT-PCR test or death not attributed to COVID-19, and the "non-tested group" for the survivors with no RT-PCR test. Comparisons were performed using Chi square test or exact Fisher test for qualitative variables, and Student t test or Mann-Whitney U test for quantitative variables, as appropriate.

Third, a classification tree (Chi-square Automatic Interaction Detector, CHAID) was performed using all available residents' data at once [START_REF] Magidson | The CHAID approach to segmentation modeling: chi-squared automatic interaction detection[END_REF]. The CHAID analysis is an algorithm used for discovering relationships between a categorical response variable (i.e., COVID-19 here) and other categorical predictor variables (i.e., all clinical variables collected as part of the study). It splits a parent group into two subgroups ("nodes") within which covariates are homogenous and between which outcome is distinct. The CHAID analysis is useful when looking for patterns in datasets with lots of categorical variables and is a convenient way of summarizing the data as the relationships can be easily visualized. Here, we forced the use of age 90 years (median) as the first split, and the CHAID analysis was adjusted for age. The probability of COVID-19 (relative risk with 95CI) was calculated for each end node using the end node with the lowest prevalence of COVID-19 as a reference (node 7) [START_REF] Katz | Obtaining Confidence Intervals for the Risk Ratio in Cohort Studies[END_REF]. Two-sided P-values were considered as significant if <0.05. All statistics were performed using SPSS (v23.0; IBM corp, Chicago, IL).

RESULTS

A total of 87 residents (mean±SD age, 87.9±7.2 years; 71% female) and 92 staff members (mean, 38.3±11.7 years; 89% female) were included in the study. As illustrated in Figure 1, the first confirmed COVID-19 cases were reported on 17 and 27 March 2020 for residents and staff members, respectively. Seventy-seven residents were tested for COVID-19 between 6

March and 16 April 2020 (10 deaths before testing), and 84 (91.3%) staff members between 2 and 23 April 2020. The attack rate was 47% in residents, and 24% in staff members. The incidence rate was 1.54 per 100 persons-days among residents, and 0.88 persons-days among staff members (respectively, 0.48 among caregivers, 0.36 among non-caregivers with contact to residents, and 0.04 among non-caregivers without contact) (Figure 1). The case fatality rate was 27% among residents. The all-cause mortality rate was 15% among residents, compared 3% on average during the same period in the preceding five years. No staff members died during the study period. Epidemic curves revealed that the epidemic started in residents, and then spread to caregivers, non-caregivers and finally to staff members with no contact to the residents (Figure 1). Demographic characteristics and medical history of residents are detailed in Table 1.

Residents exhibited 13 chronic pathological statuses on average. Among all residents, 41 had a confirmed infection with SARS-CoV-2 (mean, 89.0±6.9 years; 66% female).

As illustrated in Table 2, the most frequent symptoms retrieved in COVID-19 residents were thermal changes (n=28, 68%); 59% of patients having hyperthermia (i.e., temperature >38°C) and 10% hypothermia (i.e., temperature <36°C). Dyspnea was retrieved in 61% (n=25) of COVID-19, with 46% of low pulse oximetry (n=19) and 42% of polypnea (n=17). Twenty (49%) COVID-19 residents presented with cough (n=20), 14 (34%) with marked asthenia, and 5 (12%) with diarrhea. It is noticeable that the comparison with non-COVID-19 residents showed multiple symptomatic differences, in particular a greater number of simultaneous clinical signs (Table 2). Finally, 3 COVID-19 residents (7%) were totally asymptomatic and finally diagnosed through mass screening. All of them had major neurocognitive disorders related to alcohol use. One had hypertension and mild chronic renal failure, another one had hypertension and moderate chronic renal failure, and the last one had polyvascular disease with brain and heart lesions.

The classification tree identified 7 end groups among residents for the prediction of COVID-19 (Figure 2). The first split was dyspnea below 90 years of age, and anorexia above 90 years.

Among individuals younger than 90 and without dyspnea, those who reported no cough formed the end node with the lowest prevalence of COVID-19 (6%; node 7). Compared to this reference node, the probability of COVID-19 was 7.4-fold higher among those older than 90 without anorexia and without altered consciousness (43% COVID-19), 7.9-fold higher among those younger than 90 without dyspnea but with cough (46% COVID-19), and 10.2fold higher among those younger than 90 with dyspnea but no falls (60% COVID-19).

Finally, we found a 100% COVID-19 probability in the following groups: i) those younger than 90 with dyspnea and falls; ii) those older than 90 with anorexia; iii) those older than 90 without anorexia but with altered consciousness. Table 3 presents the characteristics of the staff members. In total, 22 had a confirmed infection with SARS-CoV-2 (mean, 38.1±11.3 years; 96% female). Caregivers represented 64% (n=14) of infected staff members, non-caregivers with contact to residents 32% (n=7), and staff members without contact to residents 5% (n=1). Most frequent symptoms were fever (32%, n=7), general signs (i.e. asthenia, anorexia, myalgia) (27%, n=6), cough (23%, n=5), and ENT signs (18%, n=4). Nine staff members were asymptomatic and identified through mass screening.

DISCUSSION

The present report of COVID-19 mass screening in a nursing home showed a high prevalence of asymptomatic infected staff members, and confirmed that older residents exhibit few and mainly nonspecific symptoms. We were nevertheless able to clarify the symptomatology of COVID-19 residents, and to specify three different clinical profiles of residents with 100% infection within a nursing home affected by the SARS-CoV-2.

This monocentric observational study contributes to emerging understanding of the presentation and trajectory of COVID-19 in nursing-home residents. This case series showed that frail older adults exhibit relatively few symptoms, and notably less often fever, cough [START_REF] Borges Do Nascimento | Novel Coronavirus Infection (COVID-19) in Humans: A Scoping Review and Meta-Analysis[END_REF] and ENT signs [START_REF] Lechien | Olfactory and gustatory dysfunctions as a clinical presentation of mild-to-moderate forms of the coronavirus disease (COVID-19): a multicenter European study[END_REF] than younger adults. In this sense, our results are consistent with the few previous studies on symptoms met in older adults infected with COVID-19 [START_REF] Sacco | Symptoms of COVID-19 among older adults: systematic review of biomedical literature[END_REF][START_REF] Annweiler | National French survey of symptoms in people aged 70 and over diagnosed with COVID-19[END_REF]. It is also consistent with the clinical presentation of other viral infections in older adults such as influenza [START_REF] Czaja | Age-Related Differences in Hospitalization Rates, Clinical Presentation, and Outcomes Among Older Adults Hospitalized With Influenza-U.S. Influenza Hospitalization Surveillance Network (FluSurv-NET)[END_REF]. Here, the residents exhibited both general and respiratory signs (59% hyperthermia, 49% cough, 42% polypnea) together with gastro-intestinal signs (12% diarrhea) and geriatric syndromes (15% falls, 10% altered consciousness). Surprisingly, delirium was less frequent compared to one previous report in adults aged 70 and over (7% here versus 26.7% previously) [START_REF] Annweiler | National French survey of symptoms in people aged 70 and over diagnosed with COVID-19[END_REF]. This may be explained by the characteristics of the present sample, which involved mainly frail older residents with major neurocognitive disorders and behavioral disturbances. Delirium is commonly under-recognized when superimposed to major neurocognitive disorders, especially during the severe stages of the disease since a clear distinction between symptoms attributable to delirium or to underlying dementia proves difficult [START_REF] Morandi | Delirium superimposed on dementia[END_REF].

We also found that the COVID-19 disease was asymptomatic in 8% of the residents. This result is in accordance with recent results reporting 5% of asymptomatic patients (3/57) in a nursing facility [START_REF] Arons | Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility[END_REF]. It suggests that COVID-19 may have either non-expressive forms, or nonspecific symptoms that have gone unnoticed, or symptoms not expressed by older adults with advanced cognitive disorders. Moreover, positive RT-PCR for SARS-CoV-2 was found in the absence of any symptom in 41% of the staff members; a large group likely involving both asymptomatic and presymptomatic individuals [START_REF] Gandhi | Asymptomatic Transmission, the Achilles' Heel of Current Strategies to Control Covid-19[END_REF]. These findings encourage systematic screening in nursing homes of all residents and staff members, starting with caregivers.

Our classification tree is thought to be an interesting tool to assist clinicians in prioritizing tests and in rapid decision-making for older residents. Three clinical profiles should particularly draw the clinicians' attention as they were associated with 100% COVID-19 probability in our study. These are residents i) younger than 90 with dyspnea and falls, ii) older than 90 with anorexia, and iii) older than 90 without anorexia but with altered consciousness. Thus, even if these results need to be confirmed by further and preferentially prospective analyses, it seems reasonable, in a nursing home affected by COVID-19 epidemic, to quickly isolate residents with one of these combinations of symptoms, and to test them as a priority to make the diagnosis of COVID-19.

We found a case fatality rate of 27%, consistent with previous findings ranging between 26% and 33.7% in similar populations [START_REF] Arons | Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility[END_REF]17]. Such high lethality rate in older patients should be considered in light of the worldwide COVID-19 lethality rate for all ages, which is around 7% [START_REF] Dong | An interactive web-based dashboard to track COVID-19 in real time[END_REF]. The over-mortality in older patients was early reported by Wang et al. [START_REF] Wang | Updated understanding of the outbreak of 2019 novel coronavirus (2019-nCoV) in Wuhan, China[END_REF] and by the Novel Coronavirus Pneumonia Emergency Response Epidemiology Team [START_REF]Novel Coronavirus Pneumonia Emergency Response Epidemiology Team, [The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China], Zhonghua Liu Xing Bing Xue Za Zhi[END_REF]. It is likely explained by the higher prevalence of severe infections in older patients compared to younger ones, due to the higher prevalence of multimorbidity leading to cascading decompensation in this population [START_REF] Du | Clinical Features of 85 Fatal Cases of COVID-19 from Wuhan: A Retrospective Observational Study[END_REF][START_REF] Du | Hospitalization and Critical Care of 109 Decedents with COVID-19 Pneumonia in Wuhan, China[END_REF]. Consistently, the studied residents exhibited 13 chronic pathological statuses on average here. Finally, we found that the attack rate was 47% among the residents in our study, which was close to the 43.5% rate previously established in a call center in South Korea [START_REF] Park | Coronavirus Disease Outbreak in Call Center, South Korea[END_REF], but twice as high as the attack rate among the staff members. This differential was possibly explained by a presymptomatic phase among staff members [START_REF] Gandhi | Asymptomatic Transmission, the Achilles' Heel of Current Strategies to Control Covid-19[END_REF] as they were affected by SARS-CoV-2 later than the residents. In our study, it is noticeable that the epidemic started in the nursing home among residents (Figure 1) and then spread to staff. Since residents were unable to leave the nursing home, this suggests that the SARS-CoV-2 was likely imported into the nursing home by a family member before containment and before visiting bans. Thus, the isolation measures from the outside imposed by some governments appear justified to limit and slow down the spread of the virus in nursing homes. However, such isolation of residents also raises questions about the quality of life of those with short life expectancy. Many initiatives are proposed in nursing homes to keep social life during this period, i.e. animations in corridors, music playing, individual walks, individual activities in the garden, sports coach, singing activities, or dematerialized communications with relatives; all alternative solutions, the degree of satisfaction of which needs to be evaluated (NCT04333849).

Our study has some limitations. First, it is an observational study conducted on a relatively limited sample of older adults living in a single nursing home and who may be not fully representative of the general population of residents as they all suffered from major neurocognitive disorders. Second, even if data were collected each day during the epidemic in a standardized manner, recall and reporting bias in retrospective studies cannot be ruled out especially regarding the symptoms of staff members. Third, the diagnosis of COVID-19 was based either on death certificate or RT-PCR test, although the first one assumes a high clinical probability but no biological confirmation of COVID-19, and the second one suffers from a relatively low sensitivity of 72% with high risk of false negatives [START_REF] Yang | Evaluating the accuracy of different respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections[END_REF].

CONCLUSION

In conclusion, the pauci-symptomatic expression of COVID-19 in older residents, together with the high prevalence of asymptomatic forms in caregivers, justifies conducting mass screening in nursing homes, possibly prioritizing residents with suggestive combinations of clinical signs including dyspnea, falls, anorexia and/or altered consciousness. Moreover, the finding of an initial contamination likely brought by non-professional visitors encourages isolation measures in nursing homes to break the contamination chain.

Contributors

Guillaume Sacco contributed to study concept and design, analysis and interpretation of data, and drafting of the manuscript.

Gonzague Foucault contributed to study concept and design, acquisition of data, analysis and interpretation of data, critical revision of the manuscript for important intellectual content, and administrative, technical, or material support.

Olivier Briere contributed to critical revision of the manuscript for important intellectual content.

Provenance and peer review

This article was not commissioned. Peer review was directed by Leon Flicker independently of Cédric Annweiler, an author and Maturitas editor, who was blinded to the process.

Research data (data sharing and collaboration)

There are no linked research data sets for this paper. Data will be made available on request.

Highlights

• There were peculiarities of COVID-19 symptoms among residents of a nursing home. • A 100% COVID-19 probability was found in three groups: residents younger than 90 with dyspnea and falls; residents older than 90 with anorexia; residents older than 90 without anorexia but with altered consciousness.

• Mass screening in nursing homes should prioritize residents with suggestive combinations of clinical signs including dyspnea, falls, anorexia and/or altered consciousness.

  ' clinical signs and results of the reverse-transcriptase-polymerase-chain-reaction (RT-PCR) tests were retrospectively obtained by reviewing medical records of the nursing home from 17 March 2020. Staff members' clinical signs and results of the RT-PCR tests were retrospectively obtained from the nursing home coordinating doctor. Data were censored at the time of data cutoff, which occurred on 26 April 2020.

Table 1 . Characteristics of nursing home residents (N=87)

 1

	Total
	N=87
	n (%)	95% CI

Table 2 . Clinical signs retrieved in nursing home residents (N=87)

 2

	Residents	Residents	P-value
	without	diagnosed with
	COVID-19	COVID-19
	(n=46)	(n=41)

Epidemic curve (A: residents, B: staff members) Figure 2: Classification tree for the prediction of COVID-19 (i.e., RT-PCR positive test result) among residents (N=87).

  For each node: node number; N of residents with COVID-19 within node; proportion of residents with COVID-19 within node (N with COVID-19 / N node). RR: relative risk; 95CI: 95% confidence interval.

Acknowledgments

The authors have listed everyone who contributed significantly to the work in the Acknowledgments section. Permission has been obtained from all persons named in the Acknowledgments section.

-Melinda Beaudenon, MSc, Romain Simon, MSc, and Jennifer Gautier, MSc, from the Research Center on Autonomy and Longevity, University Hospital of Angers, France, for daily assistance. There was no compensation for this contribution.

Funding

GS is supported by a postdoctoral grant from the Research Center on Autonomy and Longevity, University Hospital of Angers, France (2019-2020).

The sponsors had no role in the design and conduct of the study, in the collection, management, analysis, and interpretation of the data, or in the preparation, review, or approval of the manuscript.

Cédric Annweiler contributed to study concept and design, analysis and interpretation of data, drafting of the manuscript, and study supervision, and has full access to all of the data in the study, takes responsibility for the data, the analyses and interpretation and has the right to publish any and all data, separate and apart from the attitudes of the sponsors.

All authors have read and approved the manuscript.

Conflict of interest

All authors state that they have no conflicts of interest with this paper. The authors have no relevant personal financial interest in this manuscript.

Ethical approval

The study was conducted in accordance with the ethical standards set forth in the Helsinki Declaration (1983). No participant objected to the use of anonymized clinical and biological data for research purposes. The study was approved by an independent institutional review board under the number 2020/51. The study protocol was declared to the National Commission for Information Technology and civil Liberties (CNIL) under number ar20-0053v0.


P Firmani

R Vitale

C Ruckebusch

F Marini

ANOVA-Simultaneous Component Analysis modelling of low-level-fused spectroscopic data: a food chemistry case-study

Keywords: Raman spectroscopy, Mid-InfraRed (MIR) spectroscopy, ANOVA-Simultaneous Component Analysis (ASCA), cheddar cheese, low-level data fusion

Ripening is a crucial step to guarantee the high commercial value of cheddar cheese, one of the dairy products the European Union exports the most. Although several methods have lately been proposed to assess its ageing process from a chemical point of view, most of them are not particularly time-efficient and imply destructive analytical tests, thus, exhibiting limitations for, e.g., industrial applications. Here, a fast approach based on combining Raman and Mid-InfraRed (MIR) spectroscopy with ANOVA-Simultaneous Component Analysis (ASCA) is proposed in a low-level data fusion framework. It allowed to evaluate how storage temperature and time (as well as their interaction) influence cheddar ripening in a relatively cheap, rapid and green fashion.

Introduction

. Ivens et al. exploited Enzyme-Linked Immunosorbent Assays (ELISA) to investigate the effect of proteolysis on the

detection of milk protein residues during cheddar cheese ripening [START_REF] Ivens | Effect of proteolysis during Cheddar cheese aging on the detection of milk protein residues by ELISA[END_REF]. Gan et al. developed a method based on Atmospheric Pressure Chemical Ionization-Mass Spectrometry (APCI-MS) coupled to Gas Chromatography-Mass Spectrometry (GC-MS) to determine the volatile compounds of cheddar cheese samples of different maturity [START_REF] Gan | Development and validation of an APCI-MS/GC-MS approach for the classification and prediction of Cheddar cheese maturity[END_REF]. Finally, Bean et al. identified specific compounds whose appearance was somehow correlated to cheddar cheese ageing time by using Secondary ElectroSpray Ionization-Mass Spectrometry (SESI-MS) [START_REF] Bean | Profiling Aged Artisanal Cheddar Cheese Using Secondary Electrospray Ionization Mass Spectrometry[END_REF].

In spite of the high information content provided by all the aforementioned techniques, their utilization in industrial scenarios is often jeopardized by their destructive nature. In order to overcome this fundamental limitation and enable a better understanding of the physico-chemical phenomena behind the cheddar cheese ageing process, an approach based on coupling Raman and Mid-Infrared (MIR) spectroscopy is here proposed. If on the one hand, Raman and MIR spectroscopy constitute relatively cheap, rapid and green analytical platforms, on the other hand they yield multivariate data that require the application of chemometric approaches for their interpretation and assessment. In this specific case, ANOVA-Simultaneous Component Analysis (ASCA) [START_REF] Jansen | ASCA: Analysis of multivariate data obtained from an experimental design[END_REF][START_REF] Smilde | ANOVA-simultaneous component analysis (ASCA): A new tool for analyzing designed metabolomics data[END_REF] will be resorted to. ASCA permits to investigate whether a particular factor (like cheese storage temperature) has a statistically significant effect on the variation of the collected spectral data and how these data actually evolve under such an effect, by fusing the advantages of multivariate data analysis with the structure of the underlying design according to which cheddar monitoring experiments are usually carried out. In recent years, the analysis of spectral measurements by ASCA has often been performed for the resolution of food-related issues [START_REF] Bevilacqua | Application of near infrared (NIR) spectroscopy coupled to chemometrics for dried egg-pasta characterization and egg content quantification[END_REF][START_REF] De Luca | Characterization of the effects of different roasting conditions on coffee samples of different geographical origins by HPLC-DAD, NIR and chemometrics[END_REF][START_REF] Mazerolles | Analysis of experimental design with multivariate response: A contribution using multiblock techniques[END_REF]. Keeping this in mind, the present article aims at providing a comprehensive and meaningful description of cheddar cheese ripening by means of low-level data fusion of Raman and MIR spectroscopic data. More specifically, ASCA will be used to evaluate the influence of storage temperature and ageing time (as well as their interaction) on the physico-chemical phenomena driving such a process and captured in the Raman and MIR domain. Even though these two experimental factors are probably the most relevant parameters affecting cheese ageing [START_REF] Adhikari | Effect of storage time and temperature on the viability of E. coli O157:H7, Salmonella spp., Listeria innocua, Staphylococcus aureus, and Clostridium sporogenes vegetative cells and spores in vacuum-packed canned pasteurized milk cheese[END_REF][START_REF] Soodam | Effect of elevated temperature on the microstructure of full fat Cheddar cheese during ripening[END_REF]), yet, to the best of the authors' knowledge, no study has been conducted so far to highlight their effect on cheddar chemical composition along with the ripening progression.

Materials and methods

Sample preparation

Two slices of commercially available cheddar cheese were cut and from each slice five disks (5 samples) of equal diameter (approximately 2 cm) were obtained. Each disk was subsequently divided into 3 sectors (3 technical replicates per sample for a total amount of 30 sectors). 15 sectors were stored at 4°C and the other 15 at room temperature (25°C). Ripening was monitored during a 2-week period: on each established day (day 3, 5, 8, 10 and 12), 2 samples (one stored at 4°C and one stored at 25°C -namely 6 sectors) were subjected to spectroscopic measurements.

Spectroscopic measurements

Raman measurements

Raman measurements were carried out by means of a Horiba Scientific Labram HR Evolution spectrophotometer in a spectral range between 900 and 3600 cm -1 with a nominal resolution of 1.53 cm -1 . Spectra were acquired at random positions on the sample surface using a green light laser (Nd:YAG, 532 nm) and a 600 lines/mm grating with a 50x objective. Acquisition time was 10 s and 5 scans were collected and averaged to improve signal-to-noise ratio. The spectroscopic platform was equipped with a Linkam THM600 sample holder to keep the cheese at a constant temperature during the experiments and, therefore, to avoid sample degradation due to laser heating. Raman spectra were recorded by LabSpec 6 Spectroscopy Suite Software (Horiba Scientific) and afterwards imported in Matlab (The MathWorks, Natick, MA, USA, version R2015a). Three replicate spectra were registered per position and averaged prior to analysis. Fluorescent-related baseline drifts were corrected by applying the smoothing algorithm described by de Rooi et al. [START_REF] De Rooi | Mixture models for twodimensional baseline correction, applied to artifact elimination in time-resolved spectroscopy[END_REF]. The spectral range of interest was further reduced to encompass only the Raman fingerprint region (from 900 to about 1635 cm -1 ), which yielded a final array of size 30x425 (see Figure 1a).

MIR measurements

MIR measurements were carried out by means of a Bruker Vertex 70 FTIR equipped with a Bruker Hyperion 3000 IR microscope and an ATR system carrying a Germanium crystal in the wavenumber range between 900 and 3850 cm -1 with a nominal resolution of 8 cm -1 . A series of spectral profiles was acquired at room temperature by means of a 20x objective on a sample area of 160μmx160μm (64x64 pixels). 1000 scans were performed which resulted in a mean recording time of about 15 minutes. Spectra were registered by OPUS Spectroscopy Software (Bruker), imported in Matlab and afterwards averaged to obtain a single representative profile per acquisition run [START_REF] Islam | Noninvasive Determination of Firmness and Dry Matter Content of Stored Onion Bulbs Using Shortwave Infrared Imaging with Whole Spectra and Selected Wavelengths[END_REF]. Baseline drifts were here corrected by a Savitzky-Golay first-order derivation [START_REF] Savitzky | Smoothing and Differentiation of Data by Simplified Least Squares Procedures[END_REF]) encompassing a 9-data point moving window and a second-order polynomial function. The spectral range was further reduced to encompass only the MIR fingerprint region (from 900 to about 1860 cm -1 ), which yielded a final matrix of size 30x250 (see Figure 1b).

[INSERT FIGURE 1 HERE]

ANOVA-Simultaneous Component Analysis (ASCA)

As detailed before, ASCA combines the advantages of both design of experiments and multivariate exploratory analysis permitting to study whether the recorded data are significantly affected by certain experimental parameters or factors (or by the interaction of multiple of them) and to assess how they actually vary under their influence. Mathematically speaking, ASCA decomposes the centred data matrix ( ) into the sum of several arrays according to the ANOVA scheme. In this work, as the effect of storage temperature (factor A) and ageing time (factor B) on cheddar ripening will be investigated, the partition of is carried out as:

= + + + (1)
where , and account for the variability induced by the effect of factor A, factor B, and factor A/factor B interaction, respectively, while carries the residuals not explained by the ANOVA model. In order to evaluate whether the effect of a factor/interaction on the data variation is statistically significant, the sum-of-squares of the corresponding sub-matrix is computed as in Eq. 2:

SSQ = || || ∀ = A, B, AB (2)
with ‖ ‖ denoting the Euclidean norm. SSQ is afterwards contrasted against a nulldistribution non-parametrically estimated by permutation testing [START_REF] Anderson | Permutation tests for multi-factorial analysis of variance[END_REF][START_REF] Vis | Statistical validation of megavariate effects in ASCA[END_REF]. If the observed sum-of-squares is found to be systematically larger than the values of such a null-distribution (p-value<0.05), the tested effect is then assumed to be statistically significant and decomposed by Simultaneous Component Analysis (SCA) as:

= (3)
being and the scores and the loadings matrices resulting from a Principal Component Analysis (PCA) model constructed under the ANOVA scheme constraint.

ASCA will be here utilized in a data fusion context. Despite data fusion has been widely exploited in, e.g., classification or regression problems [START_REF] Biancolillo | Data Fusion Strategies in Food Analysis[END_REF], there is no reported application of ASCA for the analysis of fused data sets in literature. Given the complementary nature of the information provided by Raman and MIR spectroscopy, the individual spectroscopic data obtained by these two modalities will be integrated at a low-level for a more comprehensive description of the ageing process of cheddar cheese.

Results and discussion

To prevent results from being biased due to between-modality spectral intensity differences, Raman and IR spectra (data blocks #1 and #2) were first normalized by their corresponding Frobenius' norm. Afterwards, a single row-wise augmented matrix was constructed by horizontally concatenating blocks #1 and #2. As detailed in Section 2.3, the augmented data were mean-centred prior to the application of ASCA and then partitioned as in Eq. 1. 1000 permutation rounds were performed to assess whether the effect of the two considered factors and their interaction was statistically significant or not (note that permutations were carried out on the sum of each factor/interaction matrix and the residuals of the ASCA model). , and explained 9.25%, 44.21% and 19.13% of the total data variance, respectively. For the effect of factor A (storage temperature), permutation testing returned a p-value<<0.05.

was therefore decomposed as in Eq. 3 and SCA scores accounting for within-level sample variability were estimated as [START_REF] Zwanenburg | ANOVA-Principal Component Analysis and ANOVA-Simultaneous Component Analysis: a comparison[END_REF]

: = + (4)
The representation of the aforementioned scores in Figure 2a permits to better highlight the difference between the samples characterized at the two different storage temperature conditions1 .

[INSERT FIGURE 2 HERE]

In order to evaluate which spectral features were mainly responsible for such a differentiation, the loadings in Figures 2b and2c were also investigated. Basically, only few scattered variables of the Raman spectra (block #1) significantly contribute to the effect of factor A, while multiple spectral bands of the MIR data (block #2) are pointed out as directly associated to it. These latter bands are located between 1400 and 1800 cm -1 , a range representative of signals generated by C-H and C-O ester linkage of lipids [START_REF] Rodriguez-Saona | Rapid Determination of Swiss Cheese Composition by Fourier Transform Infrared/Attenuated Total Reflectance Spectroscopy[END_REF][START_REF] Subramanian | Rapid Prediction of Composition and Flavor Quality of Cheddar Cheese Using ATR-FTIR Spectroscopy[END_REF][START_REF] Smith | Raman imaging processed cheese and its components: Raman imaging processed cheese and its components[END_REF] and C=O stretching mode of lipids and Amide I and II modes of peptides and amino acids (1500-1755 cm -1 ). This can be reasonably interpreted considering that soluble peptides and amino acids result from the degradation of primary proteins and polypeptides during the evolution of the proteolysis process in cheddar cheese [START_REF] Swearingen | Factors Affecting Calcium Lactate and Liquid Expulsion Defects in Cheddar Cheese[END_REF]. Highlighted is also the C-O ester linkage of lipids mode at around 1150 cm -1 . Some studies reported, in fact, that carotenoids tend to degrade and isomerize depending on the temperature they are subjected to [START_REF] Colle | Carotene Degradation and Isomerization during Thermal Processing: A Review on the Kinetic Aspects[END_REF]. In addition, temperature directly affects the catabolism of fatty acids (lipolysis), which are converted into esters, methyl ketones, lactones and secondary alcohols. In this regard, it is worth recalling that large amounts of high-molecular mass lactones due to fatty acids catabolism have been detected in rancid cheddar cheese by [START_REF] Thierry | Lipolysis and Metabolism of Fatty Acids in Cheese[END_REF]. The effect of factor B (ageing time) and of the interaction between factor A and factor B were also found to be statistically significant by permutation testing (p-value<<0.05). In Figure 3, the longitudinal plots of the + scores (see also Eq. 4) together with their corresponding loadings profiles are graphed. In contrast to what was observed for , two SCA components (denoted SC #1 and SC #2) can be calculated for as the variation of factor B is spanned at three different levels. Longitudinal plots show the evolution over time of the two SCA component scores. Along SC #1 (see Figure 3a), a clear effect related to the transition between early and late ripening can be observed (see, in particular, the negative score value for day 12). For both Raman and MIR data, the SC #1 loadings (see Figures 3b and3e) pinpoint that almost all the main spectral bands are somehow relevant for explaining such an effect: the phenylalanine band at around 1000 cm -1 (this amino acid is catabolized by lactic acid bacteria and its degradation products are associated to off-flavours in cheddar cheese - [START_REF] Yvon | Cheese flavour formation by amino acid catabolism[END_REF], the C-C stretching band at around 1160 cm -1 , the antisymmetric phosphoryl stretching band at around 1190 cm -1 and the C=C mode of βcarotene at around 1520 cm -1 . On the other hand, a distinction between the first and the second half of the ageing process can be evidently observed along SC #2 (see Figure 3d), which can be somehow explained in the light of a possible change in the concentration of several chemical constituents of the cheddar sample along time.

[ INSERT FIGURE 3 HERE] In a last step and as recommended in previous works [START_REF] De Luca | Characterization of the effects of different roasting conditions on coffee samples of different geographical origins by HPLC-DAD, NIR and chemometrics[END_REF], SCA was performed on + to more systematically explore how the time evolution of the ripening process of cheddar cheese is affected by the different storage conditions. In Figures 4a and4d, + scores longitudinal plots are represented for the first two extracted factors. The dotted-dashed blue lines relate to the longitudinal behaviour of the samples stored at 4°C (level #1 of factor A), while the dashed red lines describe the longitudinal behaviour of the samples stored at 25°C (level #2 of factor A). Here, SC #1 highlights that the two groups of specimens evolve according to a similar trend during ageing, but that such a trend is shifted to longer times at 4°C. This means that i) similar chemical reactions take place at both 4°C and 25°C and ii) these reactions are delayed at lower temperatures. Such an effect is even clearer if one has a look at the SC #2 scores longitudinal plot, that is a further evidence of the strong significance of the combined effect of storage temperature and ripening time on cheddar ageing. On day 10, the samples stored at 25°C exhibit a strong deviation (along SC #1) from what would be a smooth temporal evolution. This deviation is associated to some spectral differences detected between 990 and 1100 cm -1 (not shown), which may stem from the formation of specific chemical species subsequently undergoing degradation (most probably fatty acids). For the sake of interpretation, as the + loadings profiles along SC #1 and SC #2 for both data blocks in Figures 4b,4c, 4e and 4f indicate, phenylalanine and carotenoids spectral bands appear to have the most meaningful contributions to both components.

[INSERT FIGURE 4 HERE]

Conclusion

In this article, the effect of storage temperature and ripening time on the chemical composition of cheddar cheese during ageing were investigated by means of two complementary spectroscopic modalities, Raman and MIR, coupled to ANOVA-Simultaneous Component Analysis. The spectral data were acquired following an upstream experimental protocol designed and fused at low-level to provide more comprehensive description of the aforementioned process, which highlighted the occurrence of both proteo-and lypolisis phenomena in a non-destructive, relatively cheap, rapid and green fashion. Altogether, the reported outcomes showed the proposed strategy is an easily implementable tool that could possibly be widely applied for food quality control in both laboratory and industrial scenarios.

Figure captions

Figure 1 Figure 3 -

 13 Figure 1 -a) Raman and b) Mid-Infrared (MIR) acquired spectral profiles

It is important to stress that as factor A was varied at

distinct levels (4°C and 25°C), only one SCA component can be estimated.

Acknowledgements

The authors want to thank Myriam Moreau and Isabelle de Waele (Laboratoire de Spectrochimie Infrarouge et Raman -UMR 8516, Université de Lille) for their technical support during the data acquisition stage.


Dr Thibaud Soumagne
email: thibaud_soumagne@live.fr

Bruno Degano

Alicia Guillien

Isabella Annesi-Maesano

Pascal Andujar

Sophie Hüe

Olivier Adotevi

Stéphane Jouneau

Martial Botebol

Jean-Jacques Laplante

Sophie Hue

Jean- Jacques Laplante

Nicolas Roche

Jean-Charles Dalphin

Characterization of chronic obstructive pulmonary disease in dairy farmers

Keywords:

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The burden of chronic obstructive pulmonary disease (COPD) is very high in terms of morbidity, mortality and direct and indirect costs [START_REF] Rabe | Chronic obstructive pulmonary disease[END_REF]GBD 2017 DALYs andHALE Collaborators, 2018). Early diagnosis and appropriate management are encouraged to reduce mortality and disability and to improve patients' quality of life as well as their social and occupational life [START_REF] Singh | Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease: the GOLD science committee report 2019[END_REF]. A case-finding approach with spirometry has its place in identifying COPD in order to make an appropriate diagnosis in subjects who report exposure to at least one risk factor for the disease [START_REF] Guillien | Case-finding for persistent airway obstruction in farmers: a questionnaire with optimal diagnosis criteria[END_REF].

Although tobacco smoking is the single most important causal factor for COPD, about 20% of cases can be attributed to non-smoking risk factors such as indoor and outdoor air pollutants and occupational causes such as dairy farming [START_REF] Salvi | Chronic obstructive pulmonary disease in non-smokers[END_REF][START_REF] Lamprecht | COPD in never smokers: results from the population-based burden of obstructive lung disease study[END_REF]. Several studies have indicated that the prevalence of persistent airflow limitation and of COPD is higher among dairy farmers than in the general population [START_REF] Stoleski | Chronic obstructive pulmonary disease in never-smoking dairy farmers[END_REF][START_REF] Guillien | Prevalence and risk factors for COPD in farmers: a cross-sectional controlled study[END_REF][START_REF] Marescaux | Impact of farm modernity on the prevalence of chronic obstructive pulmonary disease in dairy farmers[END_REF][START_REF] Guillien | COPD, airflow limitation and chronic bronchitis in farmers: a systematic review and meta-analysis[END_REF], although the prevalence of tobacco smoking is lower [START_REF] Roux | Smoking habits in French farmers: a crosssectional study[END_REF]. As dairy farmers are exposed to high concentrations of organic dusts, this increased risk seems mainly driven by chronic exposure to these dusts [START_REF] Basinas | Exposure-affecting factors of dairy farmers' exposure to inhalable dust and endotoxin[END_REF][START_REF] Pfister | Factors determining the exposure of dairy farmers to thoracic organic dust[END_REF]. Organic dusts contain particles of plant, animal and microbial origin [START_REF] Douwes | Bioaerosol health effects and exposure assessment: progress and prospects[END_REF]. The main agent in organic dust is endotoxin, a major component of the outer membrane of Gram-negative bacteria, but components of Gram-positive bacteria (peptidoglycans) and fungi (glucans) are also present. An "immunoallergic" and inflammatory reaction following the inhalation of organic dust contained in hay has been proposed to explain this phenomenon [START_REF] Dalphin | Etiologic factors of chronic bronchitis in dairy farmers. Case control study in the Doubs region of France[END_REF][START_REF] Eduard | Chronic bronchitis, COPD, and lung function in farmers: the role of biological agents[END_REF][START_REF] Poole | Immunological and inflammatory responses to organic dust in agriculture[END_REF]. Bronchial hyperresponsiveness during exposure to organic particles could be an indicator associated with the subsequent onset of COPD [START_REF] Dalphin | Etiologic factors of chronic bronchitis in dairy farmers. Case control study in the Doubs region of France[END_REF][START_REF] Westeel | Relationships of immunoglobulins E and G sensitization to respiratory function in dairy farmers[END_REF]. However, current knowledge on occupational COPD in dairy farming remains sparse, not only with regard to its mechanisms but also to its specific clinical characteristics. We therefore conducted a prospective crosssectional study (i) to assess the frequency of COPD among dairy farmers and (ii) to characterize COPD among dairy farmers in terms of dyspnea, quality of life, pulmonary function, exercise capacity and systemic inflammation, and to compare it with COPD secondary to tobacco.

Methods

Identification of patients and controls

The BALISTIC project (COPD in dairy farmers: screening, characterization and constitution of a cohort; ClinicalTrials.gov Identifier: NCT02540408) was conducted from 2011 to 2015 at the University Hospital of Besançon, France, in collaboration with the French national social security system for agricultural workers (Mutualité Sociale Agricole, MSA) and the federation of community health practices of Franche-Comté (Fédération des Maisons de Santé Comtoises, FeMaSaC) [START_REF] Degano | COPD in dairy farmers: screening, characterization and constitution of a cohort. The BALISTIC study[END_REF][START_REF] Soumagne | Quantitative and qualitative evaluation of spirometry for COPD screening in general practice[END_REF].

Subjects with COPD and matched controls were recruited through two parallel screening programs (the screening phase of the BALISTIC study) as described elsewhere (Soumagne et al., 2019). Inclusion criteria in the screening programs were: men or women aged 40-74 years, with no previous diagnosis of asthma or hypersensitivity pneumonitis, and who were either dairy farmers (dairy farmer subgroups) or unexposed to any of the occupational hazards that have ever been associated with COPD (non-farmer subgroups). One of these two screening programs was conducted during free health check-ups organized by the MSA for their affiliated members, where COPD screening with spirometry was proposed to all subjects who attended the health check-up and fulfilled the inclusion criteria. In parallel, general practitioners of the FeMaSaC conducted a second COPD screening program targeting all their patients who met the same inclusion criteria. For COPD screening, both programs used the same material, that is, a pneumotachograph (MedGraphics, MSE Medical, Strasbourg, France) calibrated at least once daily using a 3-L syringe, and the same protocol (Soumagne et al., 2019).

Study groups

A diagnosis of COPD was retained on the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criterion or on the lower limit of normal (LLN) criterion [START_REF] Rabe | Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary[END_REF][START_REF] Swanney | Using the lower limit of normal for the FEV1/FVC ratio reduces the misclassification of airway obstruction[END_REF]. The GOLD criterion defines airflow limitation as a post-bronchodilator (post-BD) FEV1/FVC ratio below the fixed value of 0.70. This fixed GOLD criterion does not consider the normal decline of FEV1/FVC ratio with age. Thus, a lower limit of normal (LLN) for FEV1/FVC that takes age into account is increasingly used to define airflow limitation [START_REF] Quanjer | Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations[END_REF]. The LLN approach also allows calculation of a z-score, and airflow limitation is defined as FEV1/FVC < LLN (i.e., z-score < -1.64). In practice, the use of the fixed ratio of 0.70 (GOLD) may result in more frequent diagnosis of airflow limitation in the elderly and less frequent diagnosis in younger adults. By contrast, using an LLN cut-off based on age results in more frequent diagnosis of airflow limitation in younger adults and less frequent diagnosis in older subjects [START_REF] Mannino | Chronic obstructive pulmonary disease in the older adult: what defines abnormal lung function?[END_REF][START_REF] Guillien | The new reference equations of the Global Lung function Initiative (GLI) for pulmonary function tests[END_REF]. We therefore used both GOLD and LLN criteria to present the frequency of COPD.

Spirometry was considered normal when the FEV1/FVC ratio was > 0.70 and FEV1 was > 80% of the predicted value before bronchodilator administration according to the GLI-2012 equations [START_REF] Quanjer | Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations[END_REF][START_REF] Singh | Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease: the GOLD science committee report 2019[END_REF].

During the study period, all subjects with COPD detected during the screening phase of the BALISTIC study were invited to participate in the characterization phase of the study. Those who accepted were included in two subgroups, namely dairy farmers with COPD (DF-COPD) and non-farmers with COPD (NF-COPD). Patients from these two groups were frequencymatched with subjects with normal spirometry (as defined above) in terms of age, tobacco smoking (in pack-years and smoking status) and sex; these two groups were named DFcontrols and NF-controls. Patients were in stable condition (no exacerbation of COPD during the previous 6 weeks) and were not taking any oral or inhaled anti-inflammatory drugs, including oral corticosteroids. Subjects were asked to interrupt short and long-acting bronchodilators 72 hours prior to the visit. Exclusion criteria were long-term oxygen therapy, a history of asthma, pulmonary fibrosis, tuberculosis or bronchiectasis, and pregnancy in women.

Subjects of these 4 groups participated in the characterization phase of the study. They attended a visit at the University Hospital of Besançon, during which examinations and questionnaires were performed.

Ethical approval was received from the local Ethics Committee (CPP Est; 11/617), and written consent was obtained from all subjects.

Procedures

Lung function and exercise testing.

Routine spirometry, constant-volume body plethysmography and single breath lung transfer for carbon monoxide (TLCO) were performed in accordance with current standards (Platinum Elite, MGC Diagnostics Corporation, Saint Paul, Minnesota, USA). Subjects with post-BD airway limitation were rated either as stage 1 (FEV1 > 80% of the predicted value) or stage 2+ (FEV1 ≤ 80% of the predicted value). Symptom-limited incremental cardiopulmonary exercise testing (CPET) was performed on an electronically-braked cycle ergometer (Ergometrics 900, Ergoline, Bitz, Germany) as previously described [START_REF] Soumagne | Asymptomatic subjects with airway obstruction have significant impairment at exercise[END_REF].

Laboratory analysis.

For each patient, blood gases were measured from samples drawn from the arterialized earlobe and measurements were corrected in order to estimate arterial oxygen partial pressure (PaO2) [START_REF] Aguilaniu | Detection of disturbances in pulmonary gas exchanges during exercise from arterialized earlobe PO2[END_REF]. In addition, a venous blood sample was collected in the fasting state and serum samples were stored at -80°C for further analyses.

The biomarkers periostin, monocyte chemoattractant protein 2 (MCP-2) and IgE were measured and were chosen as markers of Th2-type inflammation. Soluble tumor necrosis factor receptor 1 (sTNFR1), interleukin (IL)-6 and IL-8 were selected because they have been widely studied in COPD. Surfactant protein (SP-D), produced in type II pneumocytes, was selected as a marker of lung injury. Other common inflammatory biomarkers such as highsensitivity C-reactive protein (hsCRP) and fibrinogen were also measured, because they are acute-phase reactants known to be associated with COPD. Periostin was measured using an ELISA kit (Thermo Scientific, Courtaboeuf, France) and IL-6, IL-8, sTNFR1, SP-D and MCP-2 were measured using a bead-based cytometric immunoassay (R&D Systems Europe, Abingdon, UK). Serum high-sensitivity C-reactive protein (hsCRP) concentrations were measured using a highly sensitive immunonephelometric assay.

Questionnaires.

A medical questionnaire (completed by the physician) collected data on demographic characteristics, medical history, treatments, symptoms and smoking history.

In addition, an adapted French translation of the long version of the European Community

Respiratory Health Survey questionnaire was completed by the subjects [START_REF] Dalphin | Prevalence of asthma and respiratory symptoms in dairy farmers in the French province of the Doubs[END_REF]). An occupational questionnaire was sent to the subjects 10 days before their medical examination, collected during the visit, and reviewed in their presence [START_REF] Marescaux | Impact of farm modernity on the prevalence of chronic obstructive pulmonary disease in dairy farmers[END_REF][START_REF] Mauny | Longitudinal study of respiratory health in dairy farmers: influence of artificial barn fodder drying[END_REF].

Statistical analysis

Data are presented as number (percent) and mean ± standard deviation for qualitative and quantitative variables, respectively. Quantitative variables were compared with the Student t test. Qualitative variables were compared with the Chi-square (χ 2 ) test. To identify factors associated with pulmonary function, exercise capacity and symptoms, linear regression analysis and logistic regression analysis for all candidate factors were performed. In addition, in order to take into account the confounding effect of tobacco smoking, a subgroup analysis between NF-COPD and non-smoking DF-COPD was performed.

A p value < 0.05 was considered statistically significant. Analyses were performed using SAS software (version 9.3, SAS Institute, Inc., Cary, NC, USA).

Results

Among the 8106 subjects who attended the screening sessions, 4788 met the inclusion criteria for the study and had interpretable spirometry (59.1%), including 3627 subjects recruited through the MSA program and 1161 subjects through the FeMaSaC program (Fig. 1). A diagnosis of COPD was found in 8.0% (GOLD definition) and in 6.2% (LLN definition) of dairy farmers and in 7.3% (GOLD) and 5.2% (LLN) of non-farmers (Fig. 1). All subjects who had COPD according to the LLN definition also had COPD according to the GOLD definition. The frequency of COPD, whether defined by GOLD or by LLN, was similar in dairy farmers and non-farmers. Nevertheless, prevalence of tobacco smoking was much lower in DF-COPD (21% of current smokers and 34% of subjects who had smoked more than 15 pack-years) than in NF-COPD (52% of current smokers and 72% of subjects who had smoked more than 15 pack-years; p < 0.0001 between farmers and non-farmers) (supplementary table S1).

Population characteristics

A total of 186 subjects with COPD and 187 matched controls with normal spirometry were included in the characterization phase of the study. All groups had similar sex distribution, age and BMI (Table 1). Among these 373 subjects included in the characterization phase of the study, the number of former and current smokers was much lower among dairy farmers than among non-farmers. In farmers as well as in non-farmers, the distribution of nonsmokers, former smokers and current smokers was similar in subjects with COPD and in controls, but cumulative smoking (in pack-years) was higher in subjects with COPD than in controls (Table 1). Among non-farmers, 61% worked in the tertiary sector (mainly financial and professional services), 23% in the secondary sector (mainly car and watch manufacturing) and 16% were unemployed (supplementary Fig. S1). About 40% of patients with COPD had mild disease and 13% were taking long-term bronchodilators at the time of screening (supplementary Table S2).

Occupational characteristics of dairy farmers

Several occupational characteristics among dairy farmers were assessed (supplementary tables S3, S4 and S5). Activity level, farm characteristics, hay conditioning, exposure to organic dusts and chemical products were similar between DF-COPD and DF-controls.

Pulmonary function

A large majority of subjects with COPD had preserved FEV1. Post-BD FEV1 and TLCO were significantly higher in DF-COPD than in NF-COPD (Table 2). After adjustment on post-BD FEV1, TLCO remained significantly higher in DF-COPD. Comparison between nonsmoking DF-COPD and NF-COPD showed similar results, i.e., a higher TLCO in nonsmoking farmers with COPD than in non-farmers with COPD (supplementary Table S6).

Symptoms and quality of life

In DF-COPD, chronic bronchitis and wheezing were more frequent than in DF-controls but were similar to NF-COPD (Table 3). Frequency and severity of exacerbations were similar in DF-COPD and NF-COPD. Dyspnea (assessed by BDI and mMRC) was less and quality of life (assessed by CAT and SGRQ) was less impaired in DF-COPD than in NF-COPD.

Nevertheless, after adjustment on TLCO, post-BD FEV1 or both, only BDI remained significantly better in DF-COPD (p < 0.0001).

Comorbidities

The main comorbidities in dairy farmers were hypertension, dyslipidemia and gastroesophageal reflux; frequency of these comorbidities was similar in DF-COPD and DFcontrols (Fig. 2). Diabetes mellitus and osteoporosis were less frequent in DF-COPD than in NF-COPD. In addition, DF-COPD were taking less medication (in particular anti-aggregates and proton pump inhibitors) than NF-COPD (supplementary Table S2).

Exercise capacity

All patients performed a maximal exercise test (respiratory exchange ratio > 1.1). Patients with COPD had significantly lower exercise capacity than controls (Table 4). DF-COPD had higher peak work rate (WR) and higher peak oxygen consumption (VO2) than NF-COPD (Table 4). Nevertheless, after adjustment on both post bronchodilator FEV1 and TLCO, only peak VO2 remained higher in DF-COPD than in NF-COPD. Finally, the distance walked in 6 min was similar in both groups with COPD.

Systemic inflammation

Comparison of serum biomarkers showed that NF-COPD had higher levels of inflammatory markers (hsCRP and fibrinogen) than DF-COPD and controls (Fig. 3). By contrast, the levels of some Th2-related markers (periostin, MCP-2 and IgE) were higher in DF-COPD than in other subjects (Fig. 3).

Discussion

This study issued from large screening populations shows that (i) the frequency of COPD in dairy farmers was 8.0% using the GOLD criterion and 6.2% using the LLN criterion. It was similar to the prevalence observed in non-farmers, although tobacco consumption was markedly lower in farmers; (ii) DF-COPD had greater pulmonary function, exercise capacity and quality of life and fewer symptoms, comorbidities and systemic inflammation than nonfarmers with COPD (mostly tobacco-related) matched on age, BMI and gender; (iii) COPD in dairy farmers is associated with some Th2 phenotype markers. In addition, (iv) the absence of relationship between COPD and occupational exposure factors in farmers supports the role of host factors in the pathogenesis of COPD in this specific population.

In the current study, we observed a prevalence of COPD among farmers that is in the range of previous studies [START_REF] Eduard | Chronic bronchitis, COPD, and lung function in farmers: the role of biological agents[END_REF][START_REF] Stoleski | Chronic obstructive pulmonary disease in never-smoking dairy farmers[END_REF][START_REF] Jouneau | Prevalence and risk factors of chronic obstructive pulmonary disease in dairy farmers: AIRBAg study[END_REF][START_REF] Fix | Gender differences in respiratory health outcomes among farming cohorts around the globe: findings from the AGRICOH consortium[END_REF]. Although farming is often considered a risk factor for COPD, there are few and conflicting data regarding COPD prevalence and the magnitude of the risk in dairy farmers. In a study performed in Macedonia, Stoleski et al. reported a COPD prevalence of 10.7% in dairy farmers whereas in a study performed in Brittany, Jouneau et al. found a COPD prevalence of only 1.3% [START_REF] Stoleski | Chronic obstructive pulmonary disease in never-smoking dairy farmers[END_REF][START_REF] Jouneau | Prevalence and risk factors of chronic obstructive pulmonary disease in dairy farmers: AIRBAg study[END_REF]. The differences in COPD prevalence could be due to differences in the level of organic dusts exposure in these different regions. In a previous study by our team, prevalence of COPD in farmers in fact varied from one region to another due to differences in farming activity (livestock, dairy production), meteorological data (climate, altitude), and farm size and modernity [START_REF] Guillien | Prevalence and risk factors for COPD in farmers: a cross-sectional controlled study[END_REF][START_REF] Marescaux | Impact of farm modernity on the prevalence of chronic obstructive pulmonary disease in dairy farmers[END_REF]. In our region, where farms are mainly traditional [START_REF] Stein | Innate immunity and asthma risk in Amish and Hutterite farm children[END_REF], prevalence of COPD among farmers is higher than in Brittany [START_REF] Guillien | Prevalence and risk factors for COPD in farmers: a cross-sectional controlled study[END_REF]. However, characteristics of the farm and level of organic dust exposure alone may not explain the occurrence of COPD in dairy farmers, as we found no difference in exposure between DF-COPD and controls. In addition, other data obtained in the same cohort as the current study showed similar exposure patterns between DF-COPD and DF-controls, and therefore exposure could not explain the occurrence of COPD (Barrera et al., 2018).

To our knowledge, this is the first study comparing clinical, functional and blood parameters among DF-COPD patients, tobacco-smoking COPD patients and healthy dairy farmers and non-farmers. Several studies have shown that dairy farming is associated with an excess of respiratory symptoms including chronic bronchitis and related symptoms (cough, phlegm, wheezing) compared with the general population [START_REF] Dalphin | Prevalence of asthma and respiratory symptoms in dairy farmers in the French province of the Doubs[END_REF][START_REF] Chaudemanche | Respiratory status in dairy farmers in France; cross sectional and longitudinal analyses[END_REF][START_REF] Guillien | COPD, airflow limitation and chronic bronchitis in farmers: a systematic review and meta-analysis[END_REF]. In the current study we found a similar prevalence of respiratory symptoms between dairy farmers and non-farmers in the overall population.

Compared with NF-COPD, DF-COPD developed less severe airway limitation even though duration of exposure to toxic inhalants was similar in both groups. In addition, TLCO was significantly higher in DF-COPD even after adjustment on FEV1. Low TLCO has been clearly linked to structural markers of early emphysema [START_REF] Tan | Characteristics of COPD in never-smokers and ever-smokers in the general population: results from the CanCOLD study[END_REF]. We therefore suggest that dairy farming exposure, which has been shown to have pro-inflammatory effects in vitro, may be associated with a less damaging effect on lung parenchyma than tobacco smoking [START_REF] Pfister | Granulometry, microbial composition and biological activity of dusts collected in French dairy farms[END_REF]. High resolution computed tomography (HRCT) was however not available for emphysema quantification, but is planned to be performed in the upcoming second part of the BALISTIC project (NCT03468101). Nevertheless, these results are in line with those found in COPD induced by exposure to biomass smoke, where emphysema is rarely found [START_REF] Solleiro-Villavicencio | Chronic obstructive pulmonary disease induced by exposure to biomass smoke is associated with a Th2 cytokine production profile[END_REF][START_REF] Olloquequi | Comparative analysis of COPD associated with tobacco smoking, biomass smoke exposure or both[END_REF].

COPD is an inflammatory lung disease associated with systemic inflammation. It has been shown that levels of inflammatory markers such as TNFα, fibrinogen, IL-6 and CRP are higher than in non-COPD smokers, regardless of the severity of airway obstruction. The mechanisms of systemic inflammation are multifactorial and are still not completely understood. One hypothesis is that chronic inflammation arises from the spillover of inflammatory molecules from the lungs into the systemic circulation, while other mechanisms have been proposed including a direct effect of tobacco smoke on the activation of neutrophils or passage in the circulation of toxic gases or inhaled particles. In non-smoking COPD, it has been shown that patients exhibit higher levels of inflammatory biomarkers than healthy subjects [START_REF] Montano | FEV1 inversely correlates with metalloproteinases 1, 7, 9 and CRP in COPD by biomass smoke exposure[END_REF]Golpe et al., 2017b). Systemic inflammation is somewhat lower in non-smoking than in smoking-induced COPD [START_REF] Montano | FEV1 inversely correlates with metalloproteinases 1, 7, 9 and CRP in COPD by biomass smoke exposure[END_REF]Golpe et al., 2017b). In dairy farming, COPD was associated with a lower systemic inflammatory status than in NF-COPD. This could in part explain the lower prevalence of comorbidities in DF-COPD. A pathophysiological link between persistent low-grade systemic inflammation and comorbidities in COPD has in fact been suggested [START_REF] Sin | Why are patients with chronic obstructive pulmonary disease at increased risk of cardiovascular diseases? The potential role of systemic inflammation in chronic obstructive pulmonary disease[END_REF][START_REF] Gan | Association between chronic obstructive pulmonary disease and systemic inflammation: a systematic review and a meta-analysis[END_REF]. A similar lower prevalence of comorbidities was found in COPD induced by biomass exposure (Golpe et al., 2017a). It is plausible that the nature of the noxious agents (tobacco or organic dust exposure) could have a different impact on the occurrence of these comorbidities. In addition, it has been shown that people living and working on dairy farms have a rich and distinct nasal microbiome compared with that of non-farmers [START_REF] Shukla | The nasal microbiota of dairy farmers is more complex than oral microbiota, reflects occupational exposure, and provides competition for staphylococci[END_REF]. This increased microbial diversity may contribute to protection from chronic inflammatory conditions [START_REF] Rook | 99th Dahlem conference on infection, inflammation and chronic inflammatory disorders: Darwinian medicine and the 'hygiene' or 'old friends' hypothesis[END_REF]. Finally, we found that DF-COPD patients may have a predominantly Th2 phenotype, as has been shown in biomass COPD [START_REF] Solleiro-Villavicencio | Chronic obstructive pulmonary disease induced by exposure to biomass smoke is associated with a Th2 cytokine production profile[END_REF]. Periostin and MCP-2/CCL8, which are known to mediate Th2 inflammation with a specific potential to drive chronic eosinophilic inflammation, have been found at higher levels in DF-COPD [START_REF] Debes | CCL8 and skin T cells--an allergic attraction[END_REF][START_REF] De Llano | Mixed Th2 and non-Th2 inflammatory pattern in the asthma-COPD overlap: a network approach[END_REF]. In addition, we found in the same population that IgE-mediated reactions (atopy) may play a role in the development of COPD in dairy farming [START_REF] Veil-Picard | Is atopy a risk indicator of chronic obstructive pulmonary disease in dairy farmers?[END_REF].

All reasonable precautions were taken to verify the absence of asthma, including spirometry performed by trained nurses and careful medical examination. All subjects with self-reported asthma were excluded. Our findings therefore reinforce the so-called "Dutch hypothesis" that postulates that chronic obstructive airway disease may occur on a continuum, with "pure" forms of asthma and COPD representing the extremes of the same disease and the various forms of chronic obstructive airway disease being different expressions of a single disease entity [START_REF] Orie | Chronic nonspecific respiratory diseases[END_REF][START_REF] Postma | Revisiting the Dutch hypothesis[END_REF].

Our study has limitations inherent to large screening programs. Only subjects who agreed to undergo a health check-up were included in the COPD screening program. In addition, only half the subjects who had COPD detected by screening agreed to attend the hospital visit for characterization. It has previously been reported that among all subjects who were invited to health check-ups organized by the French agricultural health insurance system, those who attend such check-ups and those who do not have different health characteristics [START_REF] Guillien | Prevalence and risk factors for COPD in farmers: a cross-sectional controlled study[END_REF]. Our study population, however, did not differ from the target population in terms of smoking habits.

Conclusion

This study demonstrates that dairy farmers have a similar frequency of COPD (8%) as unexposed subjects despite a much lower prevalence of tobacco smoking. Dairy farming therefore represents a relevant cause of occupational COPD. Patients with COPD secondary to organic dust exposure (i.e. dairy farming) have better lung function and quality of life and fewer comorbidities than patients with COPD secondary to tobacco smoking. This suggests that dairy farming may exert less damaging effects on lung parenchyma than tobacco smoking over a similar duration. Differences in biomarkers suggest that the inflammatory response induced by exposure to organic dust is more Th2-oriented than in tobacco smoking-induced COPD.

Figure legends

Fig. 1 .

 1 Fig. 1. Flow chart of participants included in the study. Subjects were recruited through screening

Fig. 2 .

 2 Fig. 2. Prevalence of comorbidities in patients with COPD and control subjects. * p < 0.05: dairy farmers with COPD vs non-farmers with COPD; # p < 0.05: dairy farmers with COPD

Fig. 3 .

 3 Fig. 3. Scatter plot showing the relationship between of mean z-score of several cytokines

Acknowledgements

We would like to express our appreciation to the patients who participated in the study. We also thank the clinical staff who contributed to the measurements. We are indebted to Antonin Grisey, Fanny Petitcuenot, Pauline Roux and Marc Laplante who performed most of the spirometric tests of the screening program. The authors thank Nina Crowte for editorial assistance.

The COPD screening program (BalistiC) was supported by a grant from Novartis Pharma, Don du Souffle and Le Nouveau Souffle.

Ethical approval: Ethical approval was received from the local Ethics Committee (CPP Est; 11/617), and written consent was obtained from all subjects.

Author Contributions:

All authors listed above agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Authors made the following contributions: JCD and BD made substantial contributions to the conception and design of the work.

TS and AG performed all analyses.

JCD and BD obtained study funding.

All authors made substantial contributions to the acquisition, analysis, or interpretation of data for the work. TS wrote the first draft of the manuscript. BD, TS, AG, IAM, PA, SH, OA, SJ, MB, JJL, NR and JCD revised the manuscript for important intellectual content. All authors approved the manuscript.