PhD Laure Rouch
email: rouch.l@chu-toulouse.fr

Virecoulon Kelly

Christelle Giudici

Sophie Cantet

Julien Guyonnet

Philippe Delrieu

Daniel Legrand

Sandrine Catheline

Michael Andrieu

Philipe Weiner

Souto De

Barreto

PhD Kelly Virecoulon Giudici

MSc Christelle Cantet

PhD Sophie Guyonnet

MD Julien Delrieu

PhD Philippe Legrand

PhD Daniel Catheline

MD, PhD Sandrine Andrieu

MD, PhD Michael W Weiner

Philipe De

PhD Souto Barreto

MD, PhD Bruno Vellas

Shared Autorship

Associations of erythrocyte omega-3 fatty acids with cognition, brain imaging and biomarkers in the Alzheimer's Disease Neuroimaging Initiative

Keywords: cognitive subscale, ADCS-PACC, Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite, ADNI, Alzheimer's Disease Neuroimaging Initiative, ALA, α-linolenic acid, ApoE, apolipoprotein E, BMI, body mass index, CDR, Clinical Dementia Rating, CN, cognitively normal, DHA, docosahexaenoic acid, DSST, Digit Symbol Substitution Test, EDTA, ethylenediamine tetraacetic acid, EPA, eicosapentaenoic MoCA, Montreal Cognitive Assessment, PET, positron emission tomography, PUFA, polyunsaturated fatty acids, RBC, red blood cells, RCT, randomized controlled trial, SAS, Statistical Analysis Software, SUVr, standard uptake value ratio, TIV, total intracranial volume, omega-3, cognition, brain imaging, biomarkers, Alzheimer's disease, mild cognitive impairment, docosahexaenoic acid, eicosapentaenoic acid

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

Introduction

Omega-3 (ω-3) polyunsaturated fatty acids (PUFA), mainly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), have received substantial attention due to their beneficial effect on brain functioning [START_REF] Dyall | Long-chain omega-3 fatty acids and the brain: a review of the independent and shared effects of EPA, DPA and DHA[END_REF]. Several studies reported associations between higher ω-3 PUFA intake or blood concentrations and lower cognitive decline, lower risk of dementia or preserved brain structure (2); however, much less is known about the association of erythrocyte ω-3 fatty acids with brain imaging and biomarkers of cognitive function.

Erythrocyte ω-3 index, defined as the sum of EPA and DHA proportion from the total membrane lipid content, represents a more reliable measurement of nutritional status since fatty acids are stable in the erythrocytes' membranes for up to 3 months (3). In the Multidomain Alzheimer Preventive Trial (MAPT), dementia-free older adults with low ω-3 index were at greater risk of cognitive decline [START_REF] Coley | Defining the Optimal Target Population for Trials of Polyunsaturated Fatty Acid Supplementation Using the Erythrocyte Omega-3 Index: A Step Towards Personalized Prevention of Cognitive Decline?[END_REF]. Consistent results were found among dementia-free Framingham Study participants, with lower erythrocyte DHA being associated with smaller brain volumes and a vascular pattern of cognitive impairment [START_REF] Tan | Red blood cell ω-3 fatty acid levels and markers of accelerated brain aging[END_REF]. In animal studies, DHA and EPA ACCEPTED MANUSCRIPT / CLEAN COPY 6 have also been shown to reduce amyloid-β (Aβ) peptide production, particularly by altering amyloid precursor protein (APP) processing [START_REF] Grimm | Docosahexaenoic acid reduces amyloid beta production via multiple pleiotropic mechanisms[END_REF]. In the MAPT Study, multidomain interventions both with and without ω-3 PUFA supplementation were associated with lower cerebral Aβ [START_REF] Hooper | DSA study group. Cortical β-Amyloid in Older Adults Is Associated with Multidomain Interventions with and without Omega 3 Polyunsaturated Fatty Acid Supplementation[END_REF]. To our knowledge, only one study investigated the association between serum DHA levels and Aβ positron-emission tomography (PET) imaging, and reported an inverse correlation with brain Aβ load [START_REF] Yassine | Association of Serum Docosahexaenoic Acid With Cerebral Amyloidosis[END_REF]. Although even less is known, DHA could also additionally contribute to the inhibition of tau phosphorylation [START_REF] Vela | DHA Selectively Protects SAMP-8-Associated Cognitive Deficits Through Inhibition of JNK[END_REF]. Finally, the beneficial effects of ω-3 PUFA on cognition have been most often seen in cognitively healthy individuals or individuals with mild cognitive impairment (MCI) [START_REF] Macaron | Associations of Omega-3 fatty acids with brain morphology and volume in cognitively healthy older adults: A narrative review[END_REF]. A recent Cochrane meta-analysis found no convincing evidence for the efficacy of ω-3 PUFA supplements in the treatment of mild to moderate Alzheimer's disease (AD) [START_REF] Burckhardt | Omega-3 fatty acids for the treatment of dementia[END_REF].

Interestingly, previous studies also showed that the presence of Apolipoprotein E (ApoE) ε4 allele might modify the relationship between ω-3 PUFA and brain functioning, but results are still conflicting [START_REF] Daiello | Alzheimer's Disease Neuroimaging Initiative. Association of fish oil supplement use with preservation of brain volume and cognitive function[END_REF][START_REF] Yassine | Association of Docosahexaenoic Acid Supplementation With Alzheimer Disease Stage in Apolipoprotein E ε4 Carriers: A Review[END_REF][START_REF] Coughlan | APOE ε4 alters associations between docosahexaenoic acid and preclinical markers of Alzheimer's disease[END_REF]. Overall, in the literature, most studies were only cross-sectional, investigated ω-3 intake or plasma/serum measurements and their association with cognitive function, with very few analyses on brain imaging, biomarkers especially PET-Tau, and on the potential modifying effect of ApoE ε4 genotype.

We therefore aimed to assess the cross-sectional and retrospective longitudinal associations between erythrocyte ω-3 index, cognition and neuroimaging biomarkers (hippocampal and white matter hyperintensities -WMH volume, amyloid and Tau PET) among community-dwelling older adults. Sub-group analyses were also conducted according to cognitive status (cognitively normal CN, MCI and AD) and ApoE ε4 genotype. We hypothesized that participants with low erythrocyte ω-3 index would present lower cognitive function, lower hippocampal volume, higher WMH volume, brain amyloid and Tau accumulation.

Methods

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Study design and population

Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). The ADNI, a multi-center observational study conducted in 60 sites in the United States and Canada [START_REF] Weiner | The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement[END_REF], was launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI was to test whether serial magnetic resonance imaging (MRI), PET, other biological markers, and clinical and neuropsychological assessment could be combined to measure the progression of MCI and early AD. After three waves (ADNI-1, ADNI-Grand Opportunity -ADNI-GO, and ADNI-2), the ongoing ADNI-3 wave began on August 1, 2016. Older adults aged 55 to 97 years with CN status (with or without subjective memory concerns), MCI (both early and late MCI) or AD, newly enrolled in ADNI-3 or previously recruited in other ADNI waves, were included in our study. Main exclusion criteria were having a major neurologic or psychiatric illness; a history of substance abuse; a screening MRI showing evidence of infection, infarction, or other focal lesions (including multiple lacunes, or lacunes in a critical memory structure). Detailed inclusion and exclusion criteria for joining ADNI according to each of these three cognitive status' categories are described elsewhere [START_REF]Inclusion and exclusion criteria for joining ADNI according to cognitive status[END_REF]. Study flowchart is presented in Figure 1. Among the 849 participants with fatty acids measurements during the ADNI-3 wave, 832 were included in our cross-sectional analysis (cognition, brain imaging and biomarkers measured simultaneously in the ADNI-3 wave). After exclusion of 482 participants without ADNI-1, ADNI-GO or ADNI-2 data, 350 participants were included in our retrospective longitudinal analysis (cognition, brain imaging and biomarkers assessed over time using data from all waves). ADNI-3 was registered in www.ClinicalTrials.gov under the protocol NCT02854033. All subjects were informed about the aims of the study and signed a consent form.

Isolation of erythrocytes and fatty acids measurement

ACCEPTED MANUSCRIPT / CLEAN COPY Fatty acids were measured during the ADNI-3 wave. Red blood cells (RBC) were isolated from the whole blood (10 mL) collected into ethylenediamine tetra-acetic acid (EDTA) tubes, according to the standardized procedures at ADNI sites (ω-3 PUFA measurement is not affected by the presence of anti-coagulant). The blood was centrifuged at 3,000 gravitational force (g) for 15 minutes at 4°C. This results in the formation of a RBC pellet, an intermediate layer containing the leukocytes and platelets (buffy coat) and an upper phase comprising plasma. Following removal of the plasma and buffy coat, RBC was stored immediately at -80°C in EDTA tubes.

Fatty acids analysis was performed at biochemical laboratory of Institut Agro Rennes, France according to previous publication [START_REF] Guillocheau | Retroconversion of dietary trans-vaccenic (trans-C18:1 n-7) acid to trans-palmitoleic acid (trans-C16:1 n-7): proof of concept and quantification in both cultured rat hepatocytes and pregnant rats[END_REF]. Briefly, lipids were extracted twice from RBC (475 to 525 mg) samples with a mixture of hexane/isopropanol (3:2 v/v), after acidification with 1 mL hydrochloric acid (HCl) 3M [START_REF] Drouin | Comparative effects of dietary n-3 docosapentaenoic acid (DPA), DHA and EPA on plasma lipid parameters, oxidative status and fatty acid tissue composition[END_REF], containing 5 ppm butylated hydroxytoluene (BHT). Margaric acid (C17:0) was added as internal standard. Total lipid extracts were saponified with 1mL of 0.5M sodium hydroxide (NaOH) in methanol for 30 minutes at 70°C and methylated with 1 mL of boron trifluoride (BF3) methanol solution (12% w/v in methanol) for 15 min at 70°C. Fatty acid methyl esters (FAME) were extracted twice with pentane. Solvent was removed under nitrogen and FAME were redissolved in 200µL of hexane. Analyses were performed using an Agilent Technologies 7890N gas chromatograph (Bios Analytic, Toulouse, France) fitted with a split injector (10:1) at 250°C (injection volume 1µL) and a bonded silica capillary column (BPX 70, 60m long 250µm inner diameter and 0.25µm film thickness; SGE, Villeneuve-St Georges, France). Helium was used as a carrier gas (constant flow: 1.8 mL/min, 36 cm/sec). The column temperature program started at 170°C, increased by 4°C/min to 250°C and held at 250°C for 2 minutes. Transfer line was at 270°C. Mass spectra were obtained with an Agilent 5975C spectrometer used in electron impact mode (EI) with 70 eV energy; source temperature was set at 150°C and quadrupole at 230°C. Acquisition was performed in the full scan mode ranging from 50 to 500 amu (3 scan/s). Identification of FAME was based on retention times obtained for FAME ACCEPTED MANUSCRIPT / CLEAN COPY prepared from fatty acid standards and confirmed by comparison of their MS spectra with those of the NIST bank (V.2.2, 2014). Quantification was achieved by determining the area under the peaks with Mass Hunter software (version B.07.00 SP2, 2015, Agilent).

Results of EPA and DHA were expressed as % of total identified fatty acids. ω-3 index was calculated as the sum of %EPA and %DHA, and thus also expressed in % from total fatty acids. Low ω-3 index was characterized by the lowest quartile within the populations investigated (≤3.70% for the cross-sectional analysis and ≤3.62% for the retrospective longitudinal analysis).

Distribution of ω-3 index is shown in Supplementary Figure 1. [START_REF] Folstein | Mini-mental state". A practical method for grading the cognitive state of patients for the clinician[END_REF] and the Wechsler Memory Scale (WMS) delayed recall [START_REF] Elia | Wechsler Memory Scale: a critical appraisal of the normative studies[END_REF]. The modified composite score was determined using standardized Z-scores. They were calculated by dividing each of the component scores by the sample standard deviation of that component and by subtracting each of the component scores by the mean of that component. The Z-scores of delayed recall from the ADAS-Cog and from the TMT-B were then multiplied by -1 to account for the fact that, differently than the other tests, higher scores mean worse cognitive performance. All four Z-scores were then summed to form the composite score. For all subjects, the MMSE total score, WMS delayed recall, WMS immediate recall, Category Fluency test [START_REF] Gladsjo | Norms for letter and category fluency: demographic corrections for age, education, and ethnicity[END_REF], Montreal Cognitive Assessment (MoCA) (25) (higher scores mean better cognitive function for these 5 tests) and delayed word ACCEPTED MANUSCRIPT / CLEAN COPY recall ADAS-Cog, total ADAS-Cog, TMT-A, TMT-B, Clinical Dementia Rating Sum of Boxes (CDR-SB) (26) (higher scores mean worse cognitive function for these 5 tests) were also examined. Total MMSE, ADAS-Cog, MOCA and CDR-SB were used to assess global cognition; ADAS-Cog delayed recall, WMS immediate and delayed recall were used to assess memory and category fluency, TMT-A and TMT-B tests were used to assess executive functions.

Cognition, brain imaging and biomarkers

Secondary outcomes were brain imaging and biomarkers variables and included hippocampal subcortical volume (in left hemisphere, right hemisphere, and total), WMH volume [START_REF] Schwarz | Fully-automated white matter hyperintensity detection with anatomical prior knowledge and without FLAIR[END_REF], assessed by 3 Tesla (3T) MRI, and brain A and hyper-phosphorylated paired helical filaments (PHF) tau, measured by PET. MRI was performed using unified parameter scanning protocols available on: https://adni.loni.usc.edu/methods/documents/mri-protocols/. Amyloid positive status (Aβ+) was defined as 18 F-florbetapir PET cortical standardized uptake value ratio (SUVr) normalized by the whole cerebellum reference region (SUVr) >1.11 for the cross-sectional analysis and SUVr based on the composite reference region (SUVr > 0.78) for the longitudinal analysis [START_REF] Landau | Amyloid PET imaging in Alzheimer's disease: A comparison of three radiotracers[END_REF]. Tau PET was assessed during the ADNI-3 wave in meta-temporal region and in Braak stages 1 to 6 (29) after intravenous bolus injection of [ 18 F]-radiolabeled AV1451.

Potential confounders

Potential confounders included: age (years), education (years), body mass index (BMI, calculated as body weight in kg divided by height 2 in m 2 ), ApoE ε4 genotype (carriers, noncarriers), history of cardiovascular disease (yes, no), and total intracranial volume (TIV) (cm 3 ), this last only for WMH and hippocampal volume.

Statistical analysis

Characteristics of the population were presented as mean and standard deviation (SD) for continuous variables and as frequencies and percentages for categorical variables. They were compared according to ω-3 index (1 st quartile vs. others) using Student t-test for continuous

ACCEPTED MANUSCRIPT / CLEAN COPY variables (with log transformation if necessary) with normal distribution (or non-parametric

Kruskal-Wallis test for other quantitative variables) and Pearson's chi-squared test for qualitative variables. In cross-sectional analyses, linear regression models were performed to assess the association between ω-3 index (1 st quartile vs. others), cognitive, brain imaging and biomarkers variables and whether the associations differed according to cognitive status (CN, MCI, and AD) or ApoE4 genotype (carriers vs. non-carriers). For this purpose, an interaction in each model was introduced between ω-3 index and cognitive status or ApoE ε4 genotype. If interactions were significant or marginally significant (p<0.10), within-group estimates were further explored using model estimates with interaction. Linear mixed models with random intercepts and slopes were used in the longitudinal analyses. Differences in retrospective change of cognitive, brain imaging and biomarkers variables between participants in the lowest omega-3 index quartile and those in the other 3 quartiles were assessed at 24, 36, 60 and 120 months except for MoCA, WMH volume and amyloid PET (whose maximum retrospective follow-up was 6 years). Analyses were adjusted for potential confounders (age, education, BMI, ApoE ε4 genotype, history of cardiovascular disease and TIV (the last one only for WMH and hippocampal volume). Given the exploratory nature of our study, we did not correct for multiplicity. We finally conducted cross-sectional and longitudinal sensitivity analyses by excluding participants with AD and also investigated among cognitively normal and individuals with MCI whether the associations differed according to amyloid status (amyloid positive status, Aβ+ vs. amyloid negative status, Aβ-). Analyses were performed using the Statistical Analysis Software (SAS) version 9.4 (Cary, NC, USA), with a significance level established as 5%.

Results

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We included 832 individuals (mean (SD) age 74.0 (7.9) years; 50.8% female; 37.7% ApoE ε4 carriers): 465 (55.9%) had a CN status, 272 (32.7%) had MCI and 95 (11.4%) had AD. Mean ω-3 index was 4.85% (SD=1.52). The distribution was as follows: median, 4.68%; interquartile range, 3.70%-5.83%; minimum, 1.77%; maximum, 11.37%. Among fish oil supplements users, only 45 (13.2%) were in the lowest ω-3 index quartile compared to 162 (33.1%) among non-users (p<0.001). Participants in the lowest ω-3 index quartile (≤ 3.70%) were less educated (mean (SD) years of education: 15.8 (2.4) vs. 16.8 (2.4); p<0.0001) than those in the 3 other quartiles. No other differences were found in terms of population characteristics. The proportion of participants with low ω-3 index did not significantly differ according to cognitive status or ApoE ԑ4 genotype (Table 1).

In our cross-sectional analysis, low ω-3 index was not significantly associated with cognitive function (composite cognitive score or any cognitive test), hippocampal volume, WMH, brain Aβ and tau accumulation in unadjusted models or after adjustment for age, education, ApoE ԑ4 genotype, history of cardiovascular disease, BMI and TIV (the last one only for WMH and hippocampal volume) (Table 1). Interactions were found between low ω-3 index and ApoE ε4 genotype (Table 2). Among the subgroup of ApoE ε4 carriers, low ω-3 index was significantly associated in unadjusted models with lower performance on WMS-Delayed and Immediate recall and with higher tau accumulation in several regions. After adjustment, a similar result with lower performance on WMS-Delayed recall (β=-1.81, SE=0.73, p=0.014) was found and a tendency was observed with higher tau accumulation (Table 3). Interactions were also found between low ω-3 index and cognitive status on MMSE, MoCA, hippocampal volume, and Tau accumulation (Supplementary Table 1), with significant better cognitive, brain imaging and biomarkers conditions among the subgroup of AD if ω-3 index was low (Supplementary Table 2). In our cross-sectional sensitivity analyses after exclusion of participants with AD, low ω-3 index was not ACCEPTED MANUSCRIPT / CLEAN COPY significantly associated with cognitive function, WMH, brain Aβ load (SUVr) and tau accumulation after adjustment but was significantly associated with lower right hippocampal volume (β=-85.64, SE=43.03, p=0.047). Interactions were found between low ω-3 index, ApoE ε4 genotype and amyloid status but not cognitive status. Among ApoE ε4 carriers only, low ω-3 index was significantly associated with lower right hippocampal volume after adjustment (β=-212.50, SE=73.39, p=0.004) and with higher Tau accumulation in several regions. Among Aβ+ participants only, we observed a trend toward statistical significance after adjustment between low ω-3 index and higher tau accumulation (Tau 18 F-AV1451 Braak stage 2: β=0.08, SE=0.04, p=0.078).

In our retrospective longitudinal analysis, consistent across all time periods (p=0.003), individuals in the lowest ω-3 index quartile had significantly greater Aβ accumulation over time compared to those in the 3 other quartiles (adjusted β= 0.02, 95% CI [0.01, 0.03]; p=0.003 between M-60 and M0 months) (Table 4 and Figure 2). No significant differences were observed between the two ω-3 index groups for WMH volume or the composite cognitive score. WMS-Delayed recall cognitive trajectories tended to differ (global p=0.066) between individuals in the lowest ω-3 index quartile versus those in the 3 other quartiles (Table 4 and Supplementary Figure 2). In both groups, cognitive performances declined between M-60 and M0 months (lowest ω-3 index quartile: unadjusted β= -1.25, 95% CI [-2.12, -0.38]; 3 highest ω-3 index quartiles: unadjusted β= -0.08, 95% CI [-0.59, 0.42]). Compared to those in the 3 highest ω-3 index quartiles, individuals in the lowest ω-3 index quartile had a significant greater cognitive decline (adjusted β= -1.18, 95% CI [-2.16, -0.19]; p=0.019). Total ADAS-Cog cognitive trajectories were also different between the two ω-3 index groups, with low ω-3 index unexpectedly associated with lower cognitive decline across certain time periods (Table 4 and Supplementary Figure 2). In our retrospective longitudinal analysis, cognitive, brain imaging and biomarkers trajectories between participants in the 2 ω-3 index groups did not statistically differ according to ApoE ε4 ACCEPTED MANUSCRIPT / CLEAN COPY genotype (Supplementary Table 3). Total MMSE, TMT-A, TMT-B and MoCA cognitive trajectories between participants in the 2 ω-3 index groups significantly differed according to cognitive status, particularly in participants with AD compared to those with a CN status (Supplementary Table 4 and Supplementary Figure 3). Unlike individuals with MCI or a CN status, whose cognitive trajectories did not significantly differ between ω-3 index groups, participants with AD in the lowest ω-3 index quartile compared to those in the 3 highest quartiles had a significant lower cognitive decline in our retrospective analysis (Supplementary Table 4 and Supplementary Figure 3). In our retrospective longitudinal sensitivity analyses after exclusion of participants with AD, consistent across all time periods (p=0.038), individuals in the lowest ω-3 index quartile had significantly greater Aβ accumulation (adjusted β= 0.01, 95% CI [0.00, 0.03]; p=0.038 between M-60 and M0 months). MOCA trajectories also differed between the 2 omega-3 index groups (p=0.053 across all time periods). Individuals in the lowest ω-3 index quartile had a borderline significant greater cognitive decline between M-60 and M0 months (adjusted β= -0.53, 95% CI [-1.07, 0.01]; p=0.053). Although not significant across all time periods, individuals in the lowest ω-3 index quartile had a significant greater cognitive decline between M-60 and M0 months on the WMS-immediate recall (adjusted β= -1.00, 95% CI [-1.88, -0.13]; p=0.025) and on the WMS-delayed recall (adjusted β= -0.94, 95% CI [-1.87, -0.00]; p=0.050). Although not significant across all time periods, individuals in the lowest ω-3 index quartile had an unexpected lower cognitive decline on total ADAS-Cog between M-60 and M0 months (adjusted β= -0.11, 95% CI [-0.22, -0.01]; p=0.030). No interactions were found between low ω-3 index, cognitive or amyloid status. However, unlike non-carriers, ApoE ε4 carriers in the lowest ω-3 index quartile experienced a significant higher cognitive decline on MMSE between M-60 and M0 months (adjusted β= -0.56, 95% CI [-1.12, -0.01]; p=0.045).

Discussion

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Our study explored the cross-sectional and retrospective longitudinal associations between erythrocyte ω-3 index and cognitive tests, MRI data, PET Aβ and tau accumulation among community-dwelling older adults. In the cross-sectional analysis, we did not find any significant association between low ω-3 index and cognitive or brain outcomes in the whole population. In the retrospective longitudinal analysis, low ω-3 index was significantly associated with greater Aβ accumulation over time. Although no differences were observed on the composite cognitive scores, individuals with low ω-3 index had greater cognitive decline on the WMS-Delayed recall but unexpectedly lower cognitive decline on the total ADAS-Cog.

Several studies explored the association between erythrocyte omega-3 index and cognitive outcomes (Table 5); however, to our knowledge, our study is the first to investigate the association between erythrocyte ω-3 index and both PET Aβ and tau accumulation. Only one cross-sectional study with 61 older adults reported an inverse correlation between serum DHA levels and brain amyloid load on PET imaging (8); however, the longitudinal association had never been investigated. Although there is evidence suggesting that DHA could confer neuroprotection in part through the direct inhibition of Tau phosphorylation (9,30), we did not find any significant association between erythrocyte ω-3 index and Tau PET. Further longitudinal studies on omega-3 fatty acids and Tau PET are needed to assess this important relationship.

Studies investigating the relationship between ω-3 PUFA, brain morphology and volumes have also provided mixed findings [START_REF] Macaron | Associations of Omega-3 fatty acids with brain morphology and volume in cognitively healthy older adults: A narrative review[END_REF]. Higher erythrocyte ω-3 index was correlated with larger total normal brain volume and hippocampal volume in females after menopause from the Women's Health Initiative Memory Study [START_REF] Pottala | Higher RBC EPA + DHA corresponds with larger total brain and hippocampal volumes: WHIMS-MRI study[END_REF]. However, no relationships were observed between erythrocyte omega-3 index and total hippocampal volume among dementia-free Framingham Study participants [START_REF] Tan | Red blood cell ω-3 fatty acid levels and markers of accelerated brain aging[END_REF]. Although accumulating evidence has reported a beneficial role of ω-3 PUFA on cognitive aging, previous studies have examined different exposures and findings have been mixed overall [START_REF] Cederholm | ω-3 fatty acids in the prevention of cognitive decline in humans[END_REF]. Consistent with our findings on WMS-Delayed recall, higher levels of ACCEPTED MANUSCRIPT / CLEAN COPY 16 plasma ω-3 index were associated with lower cognitive decline and risk of dementia among older adults from the Three-City (3C) Study [START_REF] Thomas | Blood polyunsaturated omega-3 fatty acids, brain atrophy, cognitive decline, and dementia risk[END_REF]. Conversely, in a recent meta-analysis including 181,580 participants from 21 prospective studies [START_REF] Zhang | Intakes of fish and polyunsaturated fatty acids and mild-to-severe cognitive impairment risks: a dose-response meta-analysis of 21 cohort studies[END_REF], DHA intake (but not blood DHA) was associated with lower risk of cognitive impairment or dementia, and total blood ω-3 PUFA were not related to dementia outcomes. Finally, our unexpected results on the total ADAS-Cog need further investigation. The ADAS-Cog is not an optimal outcome measure for pre-dementia studies and is limited in measuring progression of cognitive impairment over the course of the disease progression [START_REF] Kueper | The Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog): Modifications and Responsiveness in Pre-Dementia Populations. A Narrative Review[END_REF]. Its low sensitivity is primarily due to most of its items suffering from either floor or ceiling effects.

Although we did not find any association between low ω-3 index and cognitive or brain outcomes in the whole population, our cross-sectional (but not retrospective longitudinal) findings, reported a significant interaction between low ω-3 index and ApoE ε4 genotype on certain cognitive tests and tau accumulation. Accumulating evidence also suggests that ApoE genotype could be one of the most important moderators of ω-3 PUFA effectiveness in the aging brain. Some studies reported associations of better cognitive effectiveness in ApoE ε4 non carriers [START_REF] Beydoun | Plasma n-3 fatty acids and the risk of cognitive decline in older adults: the Atherosclerosis Risk in Communities Study[END_REF][START_REF] Barberger-Gateau | Dietary patterns and risk of dementia: the Three-City cohort study[END_REF][START_REF] Whalley | n-3 Fatty acid erythrocyte membrane content, APOE varepsilon4, and cognitive variation: an observational follow-up study in late adulthood[END_REF][START_REF] Huang | Benefits of fatty fish on dementia risk are stronger for those without APOE epsilon4[END_REF], whereas others showed benefits among ApoE ε4 carriers only [START_REF] Yassine | Association of Docosahexaenoic Acid Supplementation With Alzheimer Disease Stage in Apolipoprotein E ε4 Carriers: A Review[END_REF]. In the Three-City (3C) Study, greater plasma DHA and EPA were associated with lower cognitive decline in ApoE ε4 carriers [START_REF] Samieri | ω-3 fatty acids and cognitive decline: modulation by ApoEε4 allele and depression[END_REF]. Similar findings were observed in secondary analyses from the Rush Memory and Aging Project, with ApoE ε4 carriers exhibiting slower rates of cognitive decline upon weekly seafood consumption [START_REF] Van De Rest | APOE ε4 and the associations of seafood and long-chain omega-3 fatty acids with cognitive decline[END_REF]. This is consistent with the study by Morris et al. [START_REF] Morris | Consumption of fish and n-3 fatty acids and risk of incident Alzheimer disease[END_REF] in which consumption of α-linolenic acid (ALA) was only protective towards incident AD in ApoE ε4 carriers. In cognitively unimpaired ApoE ε4 homozygotes from the Alzheimer and Families study (ALFA), dietary DHA intake also related to structural patterns that may result in greater resilience to AD pathology [START_REF] Sala-Vila | DHA intake relates to better cerebrovascular and neurodegeneration neuroimaging phenotypes in middle-aged adults at increased genetic risk of Alzheimer disease[END_REF]. Finally, very recent findings from the Framingham Offspring Cohort showed that risk for incident AD in the highest red blood cell DHA quintile was 49% lower ACCEPTED MANUSCRIPT / CLEAN COPY compared with the lowest quintile and that ApoE ε4 carriers may benefit more from higher DHA levels than non-carriers [START_REF] Sala-Vila | Red Blood Cell DHA Is Inversely Associated with Risk of Incident Alzheimer's Disease and All-Cause Dementia: Framingham Offspring Study[END_REF]. There is a biological rationale for a vulnerability of ApoE ε4 carriers to lower ω-3 PUFA status, especially in early AD, since several mechanisms linked ApoE ԑ4 with reduced brain DHA metabolism [START_REF] Yassine | Association of Docosahexaenoic Acid Supplementation With Alzheimer Disease Stage in Apolipoprotein E ε4 Carriers: A Review[END_REF]. It has been suggested that ApoE ε4 carriers β-oxidize DHA at greater rates than non-carriers [START_REF] Chouinard-Watkins | Fatty acid metabolism in carriers of apolipoprotein E epsilon 4 allele: is it contributing to higher risk of cognitive decline and coronary heart disease?[END_REF], and are more likely to exhibit dysfunctions in blood-brain barrier [START_REF] Montagne | APOE4 leads to blood-brain barrier dysfunction predicting cognitive decline[END_REF], which can impair the DHA delivery to the brain [START_REF] Chouinard-Watkins | Fatty acid metabolism in carriers of apolipoprotein E epsilon 4 allele: is it contributing to higher risk of cognitive decline and coronary heart disease?[END_REF][START_REF] Vandal | Reduction in DHA transport to the brain of mice expressing human APOE4 compared to APOE2[END_REF].

In spite of the aforementioned interesting findings, we observed in our cross-sectional study an unexpected association between low ω-3 index and better cognition, higher total hippocampal volume and lower Tau accumulation in patients with AD only. Similarly, participants with AD in the lowest ω-3 index quartile exhibited lower cognitive decline than those in the 3 highest quartiles in our retrospective longitudinal analysis. Given the distributions of the cognitive tests among participants with AD, we ruled out the possibility of a floor effect, which might have partly explained some of these unexpected findings. The existing literature shows that the association between ω-3 PUFA and brain outcomes may differ according to the cognitive status. A recent systematic review of clinical trials showed that interventions were promising for people with mild or subjective cognitive impairment but not in those already diagnosed with dementia [START_REF] Gkotzamanis | Dietary interventions and cognition: A systematic review of clinical trials[END_REF]. Further in-depth investigations of the differential effects of ω-3 PUFAs according to cognitive status are required. Sensitivity analyses after exclusion of participants with AD did not notably change our findings. They strengthened the negative effects of low omega-3 index on cognitive health, including on Aβ accumulation and confirmed the greater vulnerability of ApoE4 ε4 carriers to lower ω-3 PUFA status. We also observed a trend towards higher tau accumulation among Aβ+ participants with low omega-3 index, which was not confirmed in the retrospective longitudinal analysis. Finally, low omega-3 index was overall mostly associated with lower global cognitive performances and complex memory tests. Other studies [START_REF] Kosti | Fish intake, n-3 fatty acid body status, and risk of cognitive decline: a systematic review and a doseresponse meta-analysis of observational and experimental studies[END_REF] showed that EPA and DHA could ACCEPTED MANUSCRIPT / CLEAN COPY benefit executive functions but not overall cognition. Further studies are needed to clarify the effects of ω-3 PUFA on different cognitive domains.

The present study adds important elements to the field by evaluating several cognitive outcomes (including several clinical tests comprising different cognitive domains, MRI data and brain Aβ and tau accumulation) and their association with ω-3 PUFA status among a large sample of older adults with different cognitive and ApoE ε4 status. We were also able to analyze not only the cross-sectional but also the retrospective longitudinal associations between erythrocyte ω-3 index, cognition and neuroimaging biomarkers. Another strength to be noted is the assessment of ω-3 status through erythrocyte fatty acid concentrations, considered a more reliable measurement of ω-3 PUFA intake compared to plasma or serum measurements (since fatty acids are stable in erythrocyte membranes over its lifespan, i.e. up to 3 months) [START_REF] Von Schacky | Importance of EPA and DHA Blood Levels in Brain Structure and Function[END_REF][START_REF] Arab | Biomarkers of fat and fatty acid intake[END_REF], and known to reflect fatty acids concentrations of other tissues [START_REF] Harris | Omega-3 fatty acids in cardiac biopsies from heart transplantation patients: correlation with erythrocytes and response to supplementation[END_REF]. However, some limitations must be considered. Our findings are based on an observational study, and residual confounding may still exist despite extensive efforts to account for possible confounders. ADNI participants were predominantly white, highly educated, with relatively few comorbidities, which may limit the generalizability of our findings. PET scan and MRI were not performed for all subjects; in addition, hippocampal volume and Tau PET were not assessed in our retrospective longitudinal analysis because of differences in methods used over time, which could have affected the comparability of the results.

Our sub-group analyses according to cognitive status included few individuals with AD in the longitudinal analysis, therefore, the results should be taken with caution. Erythrocyte fatty acids assessment was only performed once at baseline during ADNI-3 wave, on defreeze samples after blood collection, which might have underestimated ω-3 PUFA values due to partial oxidative degradation [START_REF] Metherel | The stability of blood fatty acids during storage and potential mechanisms of degradation: A review[END_REF]. However, the storage under -80°C might have minimized such possible occurrence. In addition, fish oil consumption was associated with higher omega-3 index, supporting the reliability of our erythrocyte fatty acids assessment. However, although our ACCEPTED MANUSCRIPT / CLEAN COPY analytical method, which is the most widely used in the research setting, makes findings internally valid, they can only be compared to studies that used the same analytic approach. Finally, the analytical variability has been determined formerly in a precedent trial and was about 2%, which is very low and negligible compared to the patients' value variability [START_REF] Vellas | MAPT STUDY: A MULTIDOMAIN APPROACH FOR PREVENTING ALZHEIMER'S DISEASE: DESIGN AND BASELINE DATA[END_REF].

Conclusions

Our cross-sectional analysis did not find any significant association between erythrocyte ω-3 index and cognitive tests, brain imaging and biomarkers in the general sample of older adults with different cognitive status. In our retrospective longitudinal analysis, low ω-3 index was associated with greater Aβ accumulation over time and cognitive decline on the WMS test, but unexpectedly with lower cognitive decline on the total ADAS-Cog. Low ω-3 index was associated with lower cognition and higher Tau accumulation in certain brain regions among ApoE ε4 carriers in the cross-sectional analysis. Our findings are consistent with the vulnerability of ApoE ε4 carriers to lower ω-3 PUFA status reported in the literature and reinforce the group of evidence supporting the potential use of ω-3 PUFA for cognitive decline and AD prevention among ApoE ε4 carriers.

Identifying individuals who may benefit more from this dietary and/or supplementation approach is of high interest, given that increasing ω-3 intake is a generally safe, simple and well-tolerated intervention. This is critical from a public health perspective, not only in terms of preserving cognition but also given the potential benefits on other health conditions such as inflammation and cardiovascular events [START_REF] Abumweis | Eicosapentaenoic acid and docosahexaenoic acid containing supplements modulate risk factors for cardiovascular disease: a meta-analysis of randomised placebo-control human clinical trials[END_REF]. Our analysis was exploratory, and prospective longitudinal studies further evaluating the topic are encouraged. They should be conducted with large sample sizes, sufficient follow-ups, detailed dietary information and greater heterogeneity of participants, especially those with MCI and AD. supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856).

  Cognitive, brain imaging and biomarkers variables were collected over time in the different ADNI waves. The primary outcome was cognitive function which was assessed using a modified form of the Alzheimer's Disease Cooperative Study Preclinical Alzheimer Cognitive Composite (ADCS-PACC) (19). The modified composite score included the delayed word recall from the Alzheimer's Disease Assessment Scale -Cognitive Subscale (ADAS-Cog) (20), the Trail Making Test B (TMT-B) (21), the Mini Mental State Examination (MMSE) total score

31 63.

 31 Lukaschek K, von Schacky C, Kruse J, Ladwig K-H. Cognitive Impairment Is Associated with a Low Omega-3 Index in the Elderly: Results from the KORA-Age Study. Dement Geriatr Cogn Disord 2016;42:236-45. 64. Witte AV, Kerti L, Hermannstädter HM, Fiebach JB, Schreiber SJ, Schuchardt JP, Hahn A, Flöel A. Long-chain omega-3 fatty acids improve brain function and structure in older adults. Cereb Cortex N Y N 1991 2014;24:3059-68.

Figure 1 .

 1 Figure 1. Study flowchart ADNI: Alzheimer's Disease Neuroimaging Initiative

Figure 2 .

 2 Figure 2. Aβ trajectories over time according to the lowest vs. highest ω-3 index quartiles

Table 1 .

 1 Population characteristics, cognitive, brain imaging and biomarkers variables according to ω-3 index status (cross-sectional analysis) The modified composite score included the delayed word recall from the Alzheimer's Disease Assessment Scale -Cognitive Subscale (ADAS-Cog), the Trail Making Test B (TMT-B), the MMSE total score and the Wechsler Memory Scale delayed recall; ω-3 index defined as erythrocyte % docosahexaenoic acid (DHA) + % eicosapentaenoic acid (EPA); p-values based on Student's T-test5 , Kruskal-Wallis test6 or Chisquare test4 , after log transformation when needed; Significant p-values are presented in bold, and marginally significant p-values are presented in italics;

	-72	-60	-48	-36	-24	-12	0
	Omega-3 index
	assessed at time 0:	3 highest quartiles	lower 95% CI		upper 95% CI
		lowest quartile		lower 95% CI		upper 95% CI

Table 2 .

 2 Interactions between ω-3 index (lowest vs. 3 highest quartiles) and ApoE ε4 genotype (carriers vs. non-carriers) on cognitive, brain imaging and biomarkers variables among community-dwelling older adults (cross-sectional analysis) The modified composite score included the delayed word recall from the Alzheimer's Disease Assessment Scale -Cognitive Subscale (ADAS-Cog), the Trail Making Test B (TMT-B), the MMSE total score and the Wechsler Memory Scale delayed recall; ω-3 index defined as erythrocyte % docosahexaenoic acid (DHA) + % eicosapentaenoic acid (EPA). Model 2 was adjusted for age, education, history of cardiovascular disease, body mass index and total intracranial volume (this last only for white matter hyperintensities and hippocampal volume); 1 Variable with log transformation; Significant p-values are presented in bold, and marginally significant p-values are presented in italics. Results from linear regression models.

		ω-3 index x
		ApoE ε4 carrier
	n	ApoE ε4 non-carrier
			p-
		β	SE
			value

Table 3 .

 3 Associations between ω-3 index (lowest vs. 3 highest quartiles) and cognitive and brain biomarkers variables among communitydwelling older adults ApoE ε4 carriers and non-carriers (within-group estimates according to the interaction between ω-3 index and ApoE ε4 status presented in Table2) (cross-sectional analysis) Model 2 was adjusted for age, education, history of cardiovascular disease, body mass index and total intracranial volume (this last only for white matter hyperintensities and hippocampal volume); 1 Variable with log transformation; Significant p-values are presented in bold, and marginally significant p-values are presented in italics. Results from linear regression models.

	ApoE ε4 non-carriers	ApoE ε4 carriers
	β	SE	p-value	β	SE	p-value

SE, standard error; ω-3 index defined as erythrocyte % docosahexaenoic acid (DHA) + % eicosapentaenoic acid (EPA).

Table 4 .

 4 Differences in retrospective change of cognitive, brain imaging and biomarkers variables between the lowest ω-3 index quartile and the 3 highest quartiles (longitudinal analysis)

	Outcome	Time	Lowest ω-3 index quartile	3 highest ω-3 index quartiles	Lowest vs highest ω-3 index quartiles
					unadjusted				adjusted 1
			N	β	95% CI	N	β	95% CI	β	95% CI	p-value
		M0	83			250
		M0 -M-24	44	-0.88 [-1.28, -0.47]	120	-0.68 [-0.91, -0.44] -0.19	[-0.67, 0.29]	0.436
		M0 -M-36	31	-1.25 [-1.82, -0.68]	94	-0.95 [-1.28, -0.62] -0.27	[-0.93, 0.39]	0.426
	Composite
	cognitive score	M0 -M-60	34	-1.87 [-2.68, -1.05]	125	-1.37 [-1.85, -0.90] -0.40	[-1.33, 0.54]	0.408
		M0 -M-120 14	-2.66 [-3.84, -1.48]	28	-1.69 [-2.37, -1.00] -0.53	[-1.90, 0.83]	0.440
		Whatever time								0.701
		M0	88			259
		M0 -M-24	46	-0.47 [-0.76, -0.18]	127	-0.43 [-0.59, -0.26]	0.00	[-0.34, 0.35]	0.985
		M0 -M-36	34	-0.68 [-1.09, -0.27]	97	-0.60 [-0.84, -0.37] -0.01	[-0.49, 0.48]	0.977
	Total MMSE	M0 -M-60	52	-1.04 [-1.62, -0.47]	167	-0.90 [-1.23, -0.56] -0.05	[-0.74, 0.63]	0.880
		M0 -M-120 18	-1.64 [-2.36, -0.92]	35	-1.24 [-1.65, -0.82] -0.31	[-1.15, 0.53]	0.471
		Whatever time								0.379
	Total ADAS-Cog 2 M0	88			257

variables with log transformation; Analyses adjusted for age, education, ApoE ԑ4 genotype, history of cardiovascular disease, body mass index and total intracranial volume (the last one only for white matter hyperintensities and hippocampal volume) with a linear regression model for the quantitative outcomes and with a logistic regression model for the qualitative outcomes.

Acknowledgements

ACCEPTED MANUSCRIPT / CLEAN COPY

This work was supported by the ADNI-3 grant: project 5U19AG024904-14; funding source: NIH; total project funding: $76,994,438; annual funding: $2,112,288. The present article was performed in the context of the Gérontopôle of Toulouse University Hospital and the INSPIRE Platform, supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856).

Funding

This work was supported by the ADNI-3 grant: project 5U19AG024904-14; funding source: NIH; total project funding: $76,994,438; annual funding: $2,112,288. The present article was performed in the context of the Gérontopôle of Toulouse University Hospital and the INSPIRE Platform,

Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer '

Conflict of interest statement

SA reports grants from EU programs (H2020, JPND, FP7), Fondation de l'avenir, personal fees from Nestlé, Nestec SA, Sanofi, MSD, and non-financial support from Biogen, Pfizer, grants from France Alzheimer Association, grants from AMPA Association outside the submitted work. BV is an investigator in clinical trials sponsored by Biogen, Lilly, Roche, Eisai Pharmaceuticals and the Toulouse University Hospital (Inspire Geroscience Program). He has served as SAB member for Biogen, Alzheon, Green Valey, Norvo Nordisk , Longeveron, but received no personal compensation. He has served as consultant and/or SAB member for Roche, Lilly, Eisai, TauX with personal compensation. The other authors declare no conflict of interest.

Data availability

The data set is owned by a third-party organization; the Alzheimer's Disease Neuroimaging Initiative (ADNI). Data are publicly available at http://adni.loni.usc.edu/data-samples/access-data/ ACCEPTED MANUSCRIPT / CLEAN COPY


PharmD Alicia Moreno-Sabater

PhD a , Delphine Sterlin Pharmd

Imamovic Lejla

Phd

PhD Fabienne Bon

PhD Anne-Cecile Normand

Cecile Gonnin Msc

Marianne Gazzano Msc

PhD Karim Dorgham

Elyes Ben Salah

Aniss Acherar Msc

PhD Christophe Parizot

MD, MSc Virginie Rigourd

PhD Hervé Begue

PharmD Frederic Dalle

MD, MSc Claude Bachmeyer

MD Christophe Hennequin

PhD Hans Yssel

MD, MSc Marion Malphettes

MD Claire Fieschi

MD Jehane Fadlallah

MD Guy Gorochov
email: guy.gorochov@sorbonne-universite.fr

PhD b . *D L Sterlin

Imamovic

Moreno-Sabater Page

Intestinal Candida albicans overgrowth in IgA deficiency Running title: IgA impact on host-fungal mutualism

Keywords: albicans overgrowth in IgA deficiency Healthy status Selective IgA deficiency IgM opsonization Mycobiota, homeostatic IgA, IgA deficiency, IgM, Candida albicans Amplicon sequence variants HD : Healthy donors IL : Interleukin MFI : Median fluorescence intensity PCA: Principal component analysis sIgA : Secretory immunoglobulin Selective IgA deficiency

Intestinal Candida

Introduction

Mounting evidence of gut mycobiota involvement in human health and disease has increased the interest in the immune mechanisms controlling host microbiota mutualism. [START_REF] Li | Gut Mycobiota in Immunity and Inflammatory Disease[END_REF] Commensal fungi induce innate responses, implicating CX3CR1 + macrophages via CARD-9 signaling pathway, as well as Th17 cell-mediated adaptive responses which are essential to maintain mycobiota homeostasis. 2 Th17 cells also exert innate immune mechanisms, notably via the production of interleukin (IL)-17A and IL-17F, both cytokines promoting local neutrophil recruitment and playing an active role in the maintenance of integrity of epithelial barrier sites. [START_REF] Swidergall | Immunosurveillance of Candida albicans commensalism by the adaptive immune system[END_REF] The role of antibodies in intestinal host-fungi symbiosis remains in contrast poorly characterized. Secretory immunoglobulin A (sIgA) is of particular interest, because of its mucosal localization and its reported involvement in mediating microbial commensalism. [START_REF] Weis | Microbiota-antibody interactions that regulate gut homeostasis[END_REF] Although the human mycobiota contains a large number of fungal genera, [START_REF] Nash | The gut mycobiome of the Human Microbiome Project healthy cohort[END_REF] sIgA-fungal interactions have focused on Candida albicans, a human commensal and a major fungal pathogen. [START_REF] Enfert | The impact of the Fungus-Host-Microbiota interplay upon Candida albicans infections: current knowledge and new perspectives[END_REF] Hence, in a mouse model of oropharyngeal candidiasis, opsonization of this commensal by sIgA prevented fungal epithelial adhesion and invasion, contributing to control commensal C. albicans carriage. [START_REF] Millet | Mucosal IgA Prevents Commensal Candida albicans Dysbiosis in the Oral Cavity[END_REF] Central to the pathogenic potential of C. albicans is its ability to convert from round yeast cells to a hyphenated form able to invade mucosal epithelial cells, leading to blood infection. Importantly, sIgA mainly recognizes the latter morphotype, suggesting that sIgA opsonization constitutes a regulatory mechanism of intestinal fungal commensalism. [START_REF] Doron | Human gut mycobiota tune immunity via CARD9-dependent induction of anti-fungal IgG antibodies[END_REF][START_REF] Ost | Adaptive immunity induces mutualism between commensal eukaryotes[END_REF] Indeed, in patients with Crohn's disease, reduced gut sIgA reactivity to Candida hyphae-produced proteins was found to correlate with an increase in hyphal fungal morphology. [START_REF] Doron | Human gut mycobiota tune immunity via CARD9-dependent induction of anti-fungal IgG antibodies[END_REF] Moreno-Sabater, page 6

In addition to the regulatory role of intestinal sIgA, the involvement of systemic IgG in hostmycobiota interactions has recently been highlighted. Systemic IgG responses targeting Saccharomyces cerevisiae were initially considered secondary to fungal translocations due to gut barrier defects in relation with intestinal bowel disease. [START_REF] Chandrakumar | Anti-Saccharomyces cerevisiae Antibodies as a Prognostic Biomarker in Children With Crohn Disease[END_REF][11][START_REF] Lang | Intestinal Fungal Dysbiosis and Systemic Immune Response to Fungi in Patients With Alcoholic Hepatitis[END_REF][START_REF] Standaert-Vitse | Candida albicans colonization and ASCA in familial Crohn's disease[END_REF] We however recently reported that systemic IgG responses against commensal fungi can also be detected in healthy subjects, [START_REF] Moreno-Sabater | Systemic anti-commensal response to fungi analyzed by flow cytometry is related to gut mycobiome ecology[END_REF] while CARD9-deficient patients with systemic candidiasis present decreased anti-fungal commensal IgG levels. [START_REF] Doron | Mycobiota-induced IgA antibodies regulate fungal commensalism in the gut and are dysregulated in Crohn's disease[END_REF] Finally, in a CARD9-deficiency murine model, intestinal C. albicans interactions with CX3CR1 + macrophages failed to elicit IgG class switch recombination and germinal center B cell expansion. [START_REF] Doron | Human gut mycobiota tune immunity via CARD9-dependent induction of anti-fungal IgG antibodies[END_REF] The above-mentioned recent studies support the view that, besides cellular responses, antifungal IgG responses are associated with a status of host-fungal mutualism. We postulated that it is IgA that plays a key role in the establishment of this equilibrium by preserving gut mycobiota diversity and intestinal barrier homeostasis. Here, we characterized fecal, systemic, and maternal antifungal humoral responses in a cohort of healthy donors and evaluated alterations of gut fungal diversity in a cohort of selective IgA deficient patients.

Moreno-Sabater, page 7

Material and methods

Human samples

Samples from patients with a selective IgA deficiency (SIgAd) and healthy donors (HD) used in the present cross-sectional study are part of a previously published collection. [START_REF] Fadlallah | Microbial ecology perturbation in human IgA deficiency[END_REF] The main criterium for the inclusion of SIgAd patients were undetectable serum IgA (<0.07 mg/mL), but normal IgG levels. Exclusion criteria were antibiotic therapy and laxative drug use during the last 3 months before stool collection. Clinical and biological data were collected at inclusion time. Fresh stool, fecal waters, purified microbiota, DNA from fresh stools, serum samples and data from immunological status of HD and SIgAd patients were generated, as described previously. [START_REF] Fadlallah | Microbial ecology perturbation in human IgA deficiency[END_REF] Oral and written consent was obtained from patients before inclusion in the study.

Fresh breast milk of healthy lactating women was obtained from the Lactarium Regional d'Ile de France (Hopital Necker Enfants Malades, Pôle Mère-Enfant). Breast milk sample use for research was approved by the ethical committee (Avis CENEM 2020-VR Biocol_lactothèque_v1.0 _20190408). IgA was purified from breast milk and IgM from sera of SIgAd patients using peptide M (InvivoGen).

Fungal strains and culture conditions

A fungal biobank, including 14 fungal strains, was generated from different genera commonly described in human skin, lung, and intestinal mycobiota. [START_REF] Moreno-Sabater | Systemic anti-commensal response to fungi analyzed by flow cytometry is related to gut mycobiome ecology[END_REF] Fungal reference strains were obtained for C. albicans (ATCC90028) and Aspergillus fumigatus (ATCC204305), whereas other fungal strains, isolated for clinical purpose, were obtained from in vitro culture of human stool, skin and bronchoalveolar lavage samples. Fungi were cultured in Sabouraud agar medium (Bio-Rad) between 30 and 35 °C, depending on the fungus studied. To generate budding forms, yeast or spores from filamentous fungi were kept at 4 °C in RPMI-1640 medium (Gibco) for 2 h and then cultured at 30 °C under stirring for 9 h. At the end of the incubation period, cultures Moreno-Sabater, page 8 were centrifuged at 21,000 g for 20 min. Supernatant was removed and fungi were resuspended in cryopreservation medium.

Quantification of humoral responses

Systemic, as well as fecal water-and breast milk-derived, secretory IgA responses were determined using the Fungi-flow method, [START_REF] Moreno-Sabater | Systemic anti-commensal response to fungi analyzed by flow cytometry is related to gut mycobiome ecology[END_REF] as follows. Twenty-five microliters of fixed (2% PFA/PBS) samples containing 2.5 10 5 fungi were distributed in a 96 well conic bottom plate.

Twenty-five microliters of normalized samples were then distributed in each well and incubated for 20 min at 4 °C. Seventy microliters of PBS were added and samples were centrifuged at 3200g during 10 min. After removal of supernatant, fungi were incubated with a 25 μL mix (

Quantification of in vivo antibody-binding levels to commensal fungi

Whole microbiota was extracted by gradient purification in anaerobic conditions (Freter chamber) as previously described. [START_REF] Juste | Bacterial protein signals are associated with Crohn's disease[END_REF] Microbiota samples were stored at -80°C and thawed before use. Three microliters (10 7 microorganisms/μL) were fixed in 500 μL of 2% (w/v) PFA in PBS, supplemented with 4 % of calcofluor white dye (Sigma) for 20 min at 4°C. After washing with 1 mL PBS (9000 g for 10min at 4°C), bacteria and fungi were resuspended in PBS at a concentration of 3x10 7 /mL with the appropriate secondary staining antibody, washed Moreno-Sabater, page 9 and analyzed as above. An IgA isotype control antibody (FITC ChromPure Goat Serum, Jackson Immunoresearch) was used to correct for unspecific binding. In order to better define mycobiota flow cytometry events among fecal microbiota, we determined the SSC/FSC distribution of a fungal mock population containing most prevalent fungi found in human mycobiota, [START_REF] Nash | The gut mycobiome of the Human Microbiome Project healthy cohort[END_REF] to determine flow cytometry gates (Fig E1,A).

DNA sequencing

Sequencing libraries were constructed by amplifying the 18S rRNA gene ITS2 region using the PCR amplification protocol previously described. [START_REF] Moreno-Sabater | Systemic anti-commensal response to fungi analyzed by flow cytometry is related to gut mycobiome ecology[END_REF] [START_REF] Nilsson | The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications[END_REF] All ASVs not matching taxa in the UNITE database were given the designation "NA" (unassigned). ASVs without identified phylum were excluded from the analysis. To incorporate the ASVs that included all taxonomically unassigned sequences, multiple sequencing comparisons were performed using Blast. [START_REF] Zhang | A greedy algorithm for aligning DNA sequences[END_REF] The ASV sequences with > 97% similarity were identified as the same species, > 95 % using as the same genus.

Mycobiome alpha and beta diversity were studied with the Phyloseq (version 1.36.0) and vegan R package (2.5-7). Rarefaction was used to simulate an even number of reads per sample. The rarefaction depth chosen was 90% of the minimum sample depth in the dataset (in this case 11725 reads per sample). DESeq2 21 was used to produce a matrix containing differential abundance values (e.g. log2 fold changes) corresponding significance measures for species and genus abundance (p and adjusted p values). An adjusted p-value < 0.01 was considered statistically significant.

Peripheral blood CD4+ T cell profiling

Cytokines secreting T cells from frozen PBMC samples were detected after a 6-hour Phorbol

Intestine enterocyte cell (IEC) line and growth conditions

The cell line Caco-2, derived from a human colon adenocarcinoma, was purchased from the American Type Culture Collection (ATCC n°HTB-37™). Cells were grown in Dulbecco's modified Eagle's minimum essential medium (Gibco, Life Technologies) supplemented with 10% FBS (PAN Biotech) and 0.1mM non-essential amino acids (Dominique Dutscher), without antibiotics or antifungal agents. Three hundred thousand cells were seeded onto 14 mm diameter glass coverslips previously placed in 24-well plates. Cells were maintained in a humidified incubator at 37°C with 5% CO2 and were used for experiments 15 to 21 days after seeding (Passages 10 to 20) after full differentiation.

C. albicans filamentation adhesion and invasion assays

For filamentation, adhesion and invasion assays, C. albicans (SC5314) were grown in liquid YPD medium (yeast extract 1%, bacto-peptone 2%, and dextrose 2%, Fischer Bioreagent) overnight at 37°C, in a shaking incubator. Fungal cells were then diluted in fresh liquid YPD medium to a OD600nm of 0.28 to 0.32 and then grown to log phase for another 2 hours in the same conditions. A pellet of 5.10 4 yeasts was resuspended with 100 μg/mL purified sIgA or IgM. After an incubation for 20 min at 4°C, the yeast concentration was adjusted to 5.10 4 yeasts/mL in cell culture media for further investigation. For filamentous assays, C. albicans, either pre-treated or not with sIgA or IgM in RPMI-1640 medium were incubated into a 6 plastic dishes for 3 hours at 37°C, 5% CO2. Fungal cells were then washed with PBS, scrapped from the dishes and observed with a BX51 microscope using a X40 magnification (Olympus).

Adhesion and invasion assays were performed using differentiated Caco-2 cells. Briefly, Moreno-Sabater, page 12 intestinal cells cultured on coverslips were infected with C. albicans pre-treated or not with sIgA or IgM for 30 min or 2 hours at 37°C, respectively, as described elsewhere. 22

Statistical analysis

Statistical analysis was performed using GraphPad Prism (version 9) and JMP Pro (version 17).

Mann

C. albicans overgrowth in SIgAd patients

To decipher the impact of IgA on homeostasis of gut mycobiota and its diversity, we

Mycobiota dysbiosis in symptomatic SIgAd patients

Although many IgA-deficient individuals are asymptomatic, some are affected by recurrent infections, have metabolic and gastrointestinal diseases and are at greater risk for developing colorectal cancer. [START_REF] Ludvigsson | Association between IgA deficiency & other autoimmune conditions: a population-based matched cohort study[END_REF] To explore whether mycobiota composition could be related to clinical

Symptomatic IgA-deficient individuals present with decreased Th17/22 counts

As C. albicans is known to have an inflammatory effect, [START_REF] Enfert | The impact of the Fungus-Host-Microbiota interplay upon Candida albicans infections: current knowledge and new perspectives[END_REF] we then compared the frequency of cytokine-secreting circulating CD4 + T cells in asymptomatic and symptomatic IgA-deficient individuals (Fig 3 , D-E). Proportions of interferon-g (IFN-g) + CD4 + T cells differed between HD and asymptomatic but no differences were observed in SIgAd patients (18.8 ± 14 % vs 26.1 ± 6.4 %, p=0.516). IL-17 + -and IL-22 + -secreting CD4 + T cells were increased in both populations of SIgAd patients however, these cell populations were significantly lower in symptomatic patients (1.14 ± 0.7 % vs 2.5 ± 0.9 %, p=0.014 and 0.75 ± 0.5 % vs 2.0 ± 1.3 %, p=0.019 respectively). Double-positive IFNg + IL-17 + CD4 + T cells were also decreased in symptomatic patients as compared with asymptomatic patients (0.18 ± 0.1 % vs 0.4 ± 0.2 , p=0.034 respectively). Despite the limited number of individuals studied, our results underscore a significant decrease of systemic Th17-type lymphocyte responses in symptomatic IgAdeficient individuals.

Secretory IgA controls C. albicans development and intestinal cell invasion

The

Compensatory secretory IgM binding to commensal fungi in SIgAd patients

Although we did not in vitro measure a significant impact of IgM on C. albicans budding and cell invasion, previous studies have nevertheless suggested that IgM might play in vivo a compensatory role which might explain why IgA deficiency is not associated with massive perturbations of gut microbial ecology. [START_REF] Fadlallah | Microbial ecology perturbation in human IgA deficiency[END_REF][START_REF] Brandtzaeg | The clinical condition of IgA-deficient patients is related to the proportion of IgD-and IgMproducing cells in their nasal mucosa[END_REF][START_REF] Mellander | Secretory antibodies in IgAdeficient and immunosuppressed individuals[END_REF] To explore whether sIgM could exert a similar effect resulting in the preservation of gut mycobiota homeostasis in SIgAd patients, we analyzed the sIgM-opsonized fungal community in purified microbiota. Indeed, sIgM was detected at mycobiota surface in all SIgAd patients tested (53.3 % ± 16.2) (Fig 5,A). We also characterized sIgM responses in fecal waters (Fig 5 ,B). We observed a profile similar to that observed for sIgA in HD population with a higher binding for those fungi that are less represented in the gut, such as Aspergillus, Malassezia or Thrichosporon as compared with that observed for fungi from the Saccharomycetales order. This finding might suggest that Moreno-Sabater, page 18 antibodies specific for abundant targets, such as fungi from the Saccharomycetales order, are adsorbed at the surface of the latter and, are thus, less represented in fecal waters.

One classically described function of secretory immunoglobulins is immune exclusion of its targets, in which antibody binding retains antigen in the intestinal lumen, thereby precluding the priming of other immune responses, and lethal dissemination of commensal bacteria. [START_REF] Bunker | IgA Responses to Microbiota[END_REF] To indirectly determine whether sIgM could play a role in the immune exclusion of fungal targets, Moreno-Sabater, page 19

Discussion

Here we show that homeostatic IgA binds to distinct strains of commensal fungi with a body fluid-selective pattern of recognition in a cohort of healthy subjects. The profile of fungal recognition by free sIgA in fecal waters was characterized by a reduced binding to the more abundant genera, Saccharomyces, Debaryomyces and Candida and was related with a high rate of opsonization of mycobiota by intestinal IgA. In contrast, systemic IgA was found to preferentially target genera mainly implicated in human allergic responses or invasive fungal infections, including Penicillium, Candida, Fusarium and Aspergillus, [START_REF] Enfert | The impact of the Fungus-Host-Microbiota interplay upon Candida albicans infections: current knowledge and new perspectives[END_REF][START_REF] Hughes | Impact of Fungal Spores on Asthma Prevalence and Hospitalization[END_REF][START_REF] Nucci | Invasive Fusariosis in Patients with Hematologic Diseases[END_REF][START_REF] Van De Veerdonk | Aspergillus fumigatus morphology and dynamic host interactions[END_REF] . Finally, breast milk-derived IgA responses were directed against Candida, Debaryomyces and Malassezia, previously reported to colonize the mycobiota of healthy lactating mothers and their infants [START_REF] Ward | Infant fungal communities: current knowledge and research opportunities[END_REF] and, in case of fungal overgrowth, to be associated with the occurrence of inflammatory bowel disease. [START_REF] Jain | Debaryomyces is enriched in Crohn's disease intestinal tissue and impairs healing in mice[END_REF][START_REF] Limon | Malassezia Is Associated with Crohn's Disease and Exacerbates Colitis in Mouse Models[END_REF][START_REF] Sokol | Fungal microbiota dysbiosis in IBD[END_REF] To get further insight into the impact of IgA on host-mycobiota mutualism, we then compared the gut mycobiota of IgA-deficient individuals and healthy subjects. Molecular characterization of fungal commensal communities in both populations showed that IgA deficiency is not associated with a significant perturbation of gut microbial ecology, given that, in SIgAd patients, only an increase in intestinal diversity of fungal species belonging to the rare mycobiota biosphere was observed. However, results from differential ASV analysis between the mycobiota of HD and SIgAd patients assigned at order, class, family, genus and species level showed an association of IgA deficiency with a significant proliferation of C. albicans. showing that systematic SIgAd is associated with immune response defects 37 that may account for their mycobiota altered ecological status and clinical manifestations observed in some SIgAd patients. This interpretation is nevertheless limited by the fact that we did not have access to gut biopsies in order to confirm that a global Th17 decrease is observed in symptomatic SIgAd patients.

This proliferation was associated with a reduction of other

C. albicans is a commensal fungus of the human gut, but also causes life-threatening invasive infections. [START_REF] Pappas | Invasive candidiasis[END_REF] As reported previously in an experimental mouse model [START_REF] Ost | Adaptive immunity induces mutualism between commensal eukaryotes[END_REF][START_REF] Doron | Mycobiota-induced IgA antibodies regulate fungal commensalism in the gut and are dysregulated in Crohn's disease[END_REF] and corroborated by the present study, the pathogenic hyphal morphotype of C. albicans, once established, is targeted by intestinal IgA. However, the in vivo study of IgA C. albicans-interaction on human fungal-host mutualism is challenging given that C. albicans is not a mouse commensal. The demonstration in the present study that sIgA significantly reduces hyphae development corroborates a previous report showing that the lack of sIgA, directed against the C. albicansspecific hypha antigen Sap6, in Crohn disease patients was associated with an increase in hyphal fungal morphology. [START_REF] Doron | Mycobiota-induced IgA antibodies regulate fungal commensalism in the gut and are dysregulated in Crohn's disease[END_REF] Moreover, sIgA was found to significantly reduce C. albicans intestinal cell invasion, thereby implying that C. albicans opsonization by sIgA controls fungal fitness and could reduce pathogenic fungal migration through the intestinal barrier.

Moreno-Sabater, page 21

It has been previously reported that IgA uniquely uncouples fungi colonization from pathogenesis in humans. [START_REF] Ost | Adaptive immunity induces mutualism between commensal eukaryotes[END_REF] The clear in vivo and in vitro effects of IgA on C. albicans development notwithstanding, it is important to stress that increased C. albicans fitness leading to invasive or mucocutaneus candidiasis is never observed in human IgA deficiency. [START_REF] Yazdani | Selective IgA Deficiency: Epidemiology, Pathogenesis, Clinical Phenotype, Diagnosis, Prognosis and Management[END_REF] Reminiscent to the compensatory effect of IgM specific for bacterial microbiota in human IgA deficiency, we show that, in SIgAd patients, gut mycobiota is opsonized by IgM and that free sIgM is able to recognize a diversity of fungal genera. The lack of gut fungal dysbiosis in these patients therefore points to a compensatory role of IgM-fungal opsonization in order to maintain mycobiota diversity. Our results also suggest that IgM might play an important role in For adherence and invasiveness assays, C. albicans (yeast form) pre-incubated with or without purified antibodies for 30 min or 2 hours, respectively, at 37°C. C. albicans assay concentration were 5.10 4 cfu/mL. Purified sIgA from nine healthy lactating women and purified IgM from six SIgAd patients were used at a final concentration of 100 μg/mL. Bar plots show the ratio between IgA or IgM conditions and control conditions of three independent assays, P values were calculated using a Mann-Whitney test. Images were created with BioRender.com.

  10 μg/mL) of goat anti-human IgG-Alexa Fluor 647 (Jackson Immunoresearch) or goat antihuman IgA-FITC (Jackson Immunoresearch) or donkey anti-human IgM-PE (Jackson Immunoresearch) for 20 min at 4 °C. After one washing step with PBS, fungi were resuspended in 150 μL of PBS and analyzed on a Cytoflex flow cytometer (Beckman coulter). Unstained spores or budding forms were used as negative control to determine background fluorescence. Flow cytometry data were analyzed using the FlowJo program (version 10; Becton Dickinson) and expressed as median fluorescence intensity (MFI).

12 -

 12 Myristate 13-Acetate (PMA) -Ionomycin calcium salt (Sigma Aldrich) stimulation and Golgi blocking (Golgi stop, BD Biosciences) and stained with: CD4-APC-Cy7 (BD Biosciences), CD3-PerCP (BD Biosciences), Aqua (LIVE/DEAD® Fixable Dead Cell Stain Kit, Invitrogen), IL-22-A647 (e-Bioscience), IFN-γ-FITC (BD Biosciences), IL-17A-PE Moreno-Sabater, page 11 (eBioscience) and analyzed on a FACSCanto II flow cytometer (BD Biosciences) and FACS Diva (BD) software (BD Biosciences).

-

  Whitney test, Wilcoxon/Kruskal-Wallis test and Chi-square test were used whenever necessary. Principal component Analysis (PCA) was performed using RStudio v1.3.1093 with FactoMineR PCA and Factoextra fviz_pca_biplot functions on MFI values. Moreno-Sabater, page 13 Results Intestinal, systemic and maternal IgA differentially target commensal fungi Characterization of homeostatic IgA binding to 14 fungal strains from different genera of the two main divisions Ascomycota and Basidiomycota was carried out by flow cytometry in fecal waters, serum, and breast milk from a cohort of HD (Fig 1, A). Free sIgA fecal water binding was observed against all fungal genera studied and showed high inter-individual variability (Fig 1, B). sIgA responses against members of the Ascomycota phylum, and Saccharomycetales order, such as Saccharomyces, Debaryomyces, Candida, Cyberlindnera and Yarrowia were lower than those of the Hypocreales order, Fusarium or Acremonium, or those of the Basidiomycota phylum, Rhodotorula, Malassezia and Trichosporon. Analysis of Ig-opsonized fungi in human purified gut microbiota (Fig 1, C and Fig E1, A) showed a preponderance of sIgA + as compared to sIgM + fungal populations (38.2 ± 23 % vs 5.7 ± 10 %; p<0.0001).Systemic IgA responses exhibited also an inter-taxonomic variability, even against closely related taxons of the Saccharomycetales order (Fig1, D). The more intense responses were observed against the Candida genus but also against Aspergillus, Fusarium, Acremonium and Penicillium. Finally, as the maternal milk IgA repertoire largely mirrored the intestinal IgA repertoire,[START_REF] Lindner | Diversification of memory B cells drives the continuous adaptation of secretory antibodies to gut microbiota[END_REF] we characterized anti-fungal IgA activity in breast milk from healthy lactating women (Fig1, E). sIgA responses were mainly observed against Debaryomyces, Candida and Malassezia. We also assessed IgA responses against the filamentous forms of Candida, Aspergillus, and Fusarium. Interestingly, the more intense responses were observed against Candida hyphae in serum and so less in breast milk as well, as compared to Fusarium and Aspergillus (Fig 1, B-E). Principal component analysis (PCA) highlighted three distinct patterns of IgA anti-mycobiota combined reactivity profiles (Fig 1, F) and further underline the focalization of serum IgA responses against Candida hyphae as compared to Aspergillus and Fusarium in healthy individuals (Fig 1, G). Together, these results show that homeostatic IgA Moreno-Sabater, page 14 responses preferentially target specific members of the fungal community and suggest that intestinal, systemic and maternal IgA repertoires are focused on different combinations of genera, as underlined by combined PCA.

  characterized the mycobiota composition in a cohort of IgA deficient patients (Fig2,A and FigE1, B). Using the strategy described above, we first analyzed the percentage of fungal cells in purified microbiota samples from HD and SIgAd patients (Fig2, B). The results show that the proportion of the fungal population in mycobiota was similar in HD and SIgAd patients (1.1% ± 1,15 and 0.71% ± 0.64, respectively). We then analyzed the percentage of IgA-opsonized fungi. As expected, 38.2% ± 23.32 of the gut fungal population was opsonized by intestinal IgA in the HD population, whereas the IgA-opsonized population was absent in all but two SIgAd patients.To determine how the lack of IgA could alter the gut mycobiota ecology, we performed ITSgene sequencing of DNA obtained fecal samples (Fig2, C-F). We observed a trend toward increased diversity in SIgAd subjects for multiple alpha diversity metrics (observed ASVs, Shannon Diversity Index and Chao1), although none of these differences reached statistical significance (p<0.05). We then analyzed whether IgA deficiency might affect the composition of fungal populations from the phylum to the species level in terms of ASVs, relative abundancy and prevalence. Interestingly, at the phylum level, significant differences were observed for the Ascomycota phylum between the gut mycobiota of SIgAd subjects and that of HD (p=0.003) (Fig2, D). We detected 72 fungal genera, with Saccharomyces being the more prevalent one, followed by Candida, Debaryomyces, Penicillium, Malassezia and Yaworria genera (FigE2).Moreno-Sabater, page 15Thirty-three out of 72 genera described were common to both populations whereas the other 39 genera, were either present in HD or SIgAd donors and belonged to the mycobiota rare biosphere. Genera only present in the SIgAd population were yeasts such as Nakaseomyces or Metschnikowia or filamentous fungi associated with diet or environment like Aspergillus, Podosphaera or Claviceps.Analysis at the class, order, family, genus and species level revealed important differences between both populations with a significant increase in C. albicans overgrowth in SIgAd mycobiota (p=0.0046) (Fig2, E). We furthermore observed a loss of species diversity among the Candida genus (Fig2, F). Whereas five Candida species, in particular C. sake, were present in HD, only three Candida species were identified in SIgAd patients with C. albicans being the most abundant. This phenomenon was also observed for Penicillium species. In contrast, we observed an increase in the species diversity of the Kazarstania and Yaworria genera in fecal samples of SIgAd patients. Therefore, although IgA deficiency does not induce a global dysbiosis, it is associated with a promotion of C. albicans development.

  phenotypes in the SIgAd population, we compared the intestinal mycobiota of HD and asymptomatic SIgAd patients with that of symptomatic patients suffering from auto-immunity, infections and/or intestinal disorders. The results show that alpha diversity, in particular the Shannon, Simpson and invSimpson index, are significantly higher in symptomatic patients when compared with HD and SIgAd patients (Fig 3, A). No significant differences were Moreno-Sabater, page 16 observed in alpha diversity metrics between mycobiota of HD and asymptomatic SIgAd patients. Comparison of relative abundance at class, order, genus and species level pointed out that C. albicans and S. cerevisiae were overrepresented in symptomatic patients or asymptomatic patients, respectively (Fig 3, B). Analysis of the observed ASV in both groups illustrated a shift of mycobiota composition related to clinical phenotype, with a significant increase of C. albicans and a decrease of S. cerevisiae in symptomatic patients (Fig 3, C).

  we compared antifungal systemic IgG responses in SIgAd and HD subjects. The results show that IgG responses in both groups were similar with only significant differences in IgG responses against two fungal genera (Fusarium, p=0.0188; Trichosporon, p=0.0006) (Fig5, C).We then compared systemic anti-fungal IgM responses in both populations (Fig E3). SystemicIgM bound a large range of commensal fungi in HD as well as in SIgAd patients, with a comparable inter-individual variability. Finally, the profile of systemic IgA responses in HD was compared with that observed for IgM in SIgAd population in order to unveil a potential compensatory role for IgM. Our results show that the IgA and IgM recognition patterns of the sporulated forms did not differ between both groups (Fig 5, D). In contrast, comparison of the patterns of filamentous form recognition showed that systemic IgA had a more selective reactivity profile than IgM, with a preferential targeting of the C. albicans filament. Altogether, these results confirm a partial compensatory impact of IgM on gut mycobiota in the absence of IgA that does not fully extend to C. albicans.

  Candida species in SIgAd patients, as compared with HD, suggesting an elective role of sIgA on species regulation inside the Candida genus or revealing the preferential fitness of C. albicans over other species. Intestinal mycobiota analysis within the population of the SIgAd patients also revealed a significantly Moreno-Sabater, page 20 higher diversity with an overrepresentation of C. albicans in those presenting clinical complications that contrasted with the dominant presence of S. cerevisiae in asymptomatic SIgAd patients. The known anti-inflammatory and pro-inflammatory effects of S. cerevisiae[START_REF] Siesto | In Vitro Study of Probiotic, Antioxidant and Anti-Inflammatory Activities among Indigenous Saccharomyces cerevisiae Strains[END_REF] and C. albicans[START_REF] Enfert | The impact of the Fungus-Host-Microbiota interplay upon Candida albicans infections: current knowledge and new perspectives[END_REF] respectively, might contribute to the clinical phenotype observed in the SIgAd population. While gut proliferation of C. albicans is associated with an increased CD4 + Th17 systemic response,[START_REF] Shao | Commensal Candida albicans Positively Calibrates Systemic Th17 Immunological Responses[END_REF] C. albicans SIgAd-colonized patients showed lower IL-17 + CD4 + , IL-22 + CD4 + and IFN-g + IL17 + responses. These results corroborate and extend previous findings

Figure 1 .

 1 Figures Legends

Figure 2 .Figure 3 .

 23 Figure 2. Fungal gut ecology perturbation in selective IgA deficient (SIgAd) patients. (A)

Figure 4 .

 4 Figure 4. Impact of secretory IgA and IgM on C. albicans host mutualism. (A) C. albicans

Figure 5 . 31 Figure E1 .

 531E1 Figure 5. Compensatory role of IgM in selective IgA deficiency (SIgAd). (A) Percentage of

Figure E2 .

 E2 Figure E2. Comparative analysis of gut mycobiota diversity performed at genus level

Figure E3 .

 E3 Figure E3. Systemic IgM response against commensal fungi. Characterization by flow

  The impact of purified systemic IgM from six SIgAd patients was also evaluated. SIgA from nine different donors were found to significantly reduce C. albicans

	hyphae development with reduction rates ranging from 10.27% to 23.8% (p=0.002; IgA versus
	no-IgA conditions) (Fig 4, A). Breast-milk-derived sIgA also reduced yeast adhesion to Caco-
	2 cells (reduction rates: 27.5% to 60%), although these differences did not reach statistical
	significance (Fig 4B). Interestingly, yeast intestinal cell invasion was significantly reduced by
	sIgA from eight of nine donors tested with a mean reduction rate of 33.68 ± 4,3% (p=0.0012;
	IgA versus no IgA conditions) (Fig 4, C). In comparison, purified IgM did not significantly

increase in C. albicans prevalence in the mycobiota of SIgAd donors prompted us to study the impact of IgA responses in C. albicans yeast-to-hyphal transition, intestinal cell adhesion and invasion. To this aim, we used an in vitro model of C. albicans-Caco-2 cells and IgA Moreno-Sabater, page 17 purified from breast milk. impact hyphae development, nor intestinal cell adhesion or invasion. Thus, it appears that in vitro antibody-mediated repression of C. albicans budding, intestinal cell adhesion and invasion is mainly IgA-mediated.

Acremonium; Rho: Rhodotorula; Mal: Malassezia; Tri: Trichosporon; Cry: Cryptococcus.

Acknowledgments

The study was financed by the Emergence program of Sorbonne Université (MycELIA-SU-16-R-EMR-45; Principal investigator A. Moreno-Sabater) and by Fédération Hospitalo-Universitaire (FHU) PaCeMM « Paris Center for Microbiome Médicine » (Grant to A. Moreno-Sabater). Work in the G. Gorochov's team is supported by Institut National de la Santé et de la Recherche Médicale (INSERM) and Sorbonne Université. L. Imamovic was partly supported by Agence Nationale de la Recherche (ANR "BactRIA" R21219DD).