M1-like macrophages are potent producers of anti-viral interferons and M1-associated marker-positive lung macrophages are decreased during rhinovirus-induced asthma exacerbations.

Macrophages (Mф) can be M1/M2 polarized by Th1/2 signals, respectively. M2-like Mф are thought to be important in asthma pathogenesis, and M1-like in anti-infective immunity, however their roles in virus-induced asthma exacerbations are unknown. Our objectives were (i) to assess polarised Mф phenotype responses to rhinovirus (RV) infection in vitro and (ii) to assess Mф phenotypes in healthy subjects and people with asthma before and during experimental RV infection in vivo. We investigated characteristics of polarized/unpolarized human monocyte-derived Mф (MDM, from 3-6 independent donors) in vitro and evaluated frequencies of M1/M2-like bronchoalveolar lavage (BAL) Mф in experimental RV-induced asthma exacerbation in 7 healthy controls and 17 (at baseline) and 18 (at day 4 post infection) people with asthma. We observed in vitro: M1-like but not M2-like or unpolarized MDM are potent producers of type I and III interferons in response to RV infection (P<0.0001), and M1-like are more resistant to RV infection (P<0.05); compared to M1-like, M2-like MDM constitutively produced higher levels of CCL22/MDC (P = 0.007) and CCL17/TARC (P<0.0001); RV-infected M1-like MDM were characterized as CD14+CD80+CD197+ (P = 0.002 vs M2-like, P<0.0001 vs unpolarized MDM). In vivo we found reduced percentages of M1-like CD14+CD80+CD197+ BAL Mф in asthma during experimental RV16 infection compared to baseline (P = 0.024). Human M1-like BAL Mф are likely important contributors to anti-viral immunity and their numbers are reduced in patients with allergic asthma during RV-induced asthma exacerbations. This mechanism may be one explanation why RV-triggered clinical and pathologic outcomes are more severe in allergic patients than in healthy subjects. ERC FP7 Advanced grant 233015, MRC Centre Grant G1000758, Asthma UK grant 08-048, NIHR Biomedical Research Centre funding scheme, NIHR BRC Centre grant P26095, the Predicta FP7 Collaborative Project grant 260895, RSF grant 19-15-00272, Megagrant No 14.W03.31.0024.