Paying for treatments? Influences on negotiating clinical need and decision-making for dental implant treatment

Background The aim of this study is to examine how clinicians and patients negotiate clinical need and treatment decisions within a context of finite resources. Dental implant treatment is an effective treatment for missing teeth, but is only available via the NHS in some specific clinical circumstances. The majority of people who receive this treatment therefore pay privately, often at substantial cost to themselves. People are used to paying towards dental treatment costs. However, dental implant treatment is much more expensive than existing treatments – such as removable dentures. We know very little about how dentists make decisions about whether to offer such treatments, or what patients consider when deciding whether or not to pay for them. Methods/Design Mixed methods will be employed to provide insight and understanding into how clinical need is determined, and what influences people's decision making processes when deciding whether or not to pursue a dental implant treatment. Phase 1 will use a structured scoping questionnaire with all the General dental practitioners (GDPs) in three Primary Care Trust areas (n = 300) to provide base-line data about existing practice in relation to dental implant treatment, and to provide data to develop a systematic sampling procedure for Phase 2. Phases 2 (GDPs) and 3 (patients) use qualitative focused one to one interviews with a sample of these practitioners (up to 30) and their patients (up to 60) to examine their views and experiences of decision making in relation to dental implant treatment. Purposive sampling for phases 2 and 3 will be carried out to ensure participants represent a range of socio-economic circumstances, and choices made. Discussion Most dental implant treatment is conducted in primary care. Very little information was available prior to this study about the quantity and type of treatment carried out privately. It became apparent during phase 2 that ISOD treatment was an unusual treatment in primary care. We thus extended our sample criteria for Phase 3 to include people who had had other implant supported restorations, although not single tooth replacements

Particulate air pollutants, APOE alleles and their contributions to cognitive impairment in older women and to amyloidogenesis in experimental models

Exposure to particulate matter (PM) in the ambient air and its interactions with APOE alleles may contribute to the acceleration of brain aging and the pathogenesis of Alzheimer's disease (AD). Neurodegenerative effects of particulate air pollutants were examined in a US-wide cohort of older women from the Women's Health Initiative Memory Study (WHIMS) and in experimental mouse models. Residing in places with fine PM exceeding EPA standards increased the risks for global cognitive decline and all-cause dementia respectively by 81 and 92%, with stronger adverse effects in APOE ɛ4/4 carriers. Female EFAD transgenic mice (5xFAD+/−/human APOE ɛ3 or ɛ4+/+) with 225 h exposure to urban nanosized PM (nPM) over 15 weeks showed increased cerebral β-amyloid by thioflavin S for fibrillary amyloid and by immunocytochemistry for Aβ deposits, both exacerbated by APOE ɛ4. Moreover, nPM exposure increased Aβ oligomers, caused selective atrophy of hippocampal CA1 neurites, and decreased the glutamate GluR1 subunit. Wildtype C57BL/6 female mice also showed nPM-induced CA1 atrophy and GluR1 decrease. In vitro nPM exposure of neuroblastoma cells (N2a-APP/swe) increased the pro-amyloidogenic processing of the amyloid precursor protein (APP). We suggest that airborne PM exposure promotes pathological brain aging in older women, with potentially a greater impact in ɛ4 carriers. The underlying mechanisms may involve increased cerebral Aβ production and selective changes in hippocampal CA1 neurons and glutamate receptor subunits

J/ψ polarization in p+p collisions at s=200 GeV in STAR

AbstractWe report on a polarization measurement of inclusive J/ψ mesons in the di-electron decay channel at mid-rapidity at 2<pT<6 GeV/c in p+p collisions at s=200 GeV. Data were taken with the STAR detector at RHIC. The J/ψ polarization measurement should help to distinguish between different models of the J/ψ production mechanism since they predict different pT dependences of the J/ψ polarization. In this analysis, J/ψ polarization is studied in the helicity frame. The polarization parameter λθ measured at RHIC becomes smaller towards high pT, indicating more longitudinal J/ψ polarization as pT increases. The result is compared with predictions of presently available models

Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury

Dielectron Azimuthal Anisotropy At Mid-rapidity In Au+au Collisions At Snn =200 Gev

We report on the first measurement of the azimuthal anisotropy (v2) of dielectrons (e+e- pairs) at mid-rapidity from sNN=200 GeV Au+Au collisions with the STAR detector at the Relativistic Heavy Ion Collider (RHIC), presented as a function of transverse momentum (pT) for different invariant-mass regions. In the mass region Mee<1.1 GeV/c2 the dielectron v2 measurements are found to be consistent with expectations from π0,η,ω, and φ decay contributions. In the mass region 1.1<Mee<2.9GeV/c2, the measured dielectron v2 is consistent, within experimental uncertainties, with that from the cc¯ contributions.906Adams, J., (2005) Nucl. Phys. A, 757, p. 102. , NUPABL 0375-9474Arsene, I., (2005) Nucl. Phys. A, 757, p. 1. , NUPABL 0375-9474Adcox, K., (2005) Nucl. Phys. A, 757, p. 184. , NUPABL 0375-9474Back, B.B., (2005) Nucl. Phys. A, 757, p. 28. , NUPABL 0375-9474Rapp, R., Wambach, J., (2002) Adv. Nucl. Phys., 25, p. 1. , 0065-2970David, G., Rapp, R., Xu, Z., (2008) Phys. Rep., 462, p. 176. , PRPLCM 0370-1573Agakichiev, G., (2005) Eur. Phys. J. C, 41, p. 475. , EPCFFB 1434-6044Arnaldi, R., (2006) Phys. Rev. Lett., 96, p. 162302. , PRLTAO 0031-9007Brown, G.E., Rho, M., (1996) Phys. Rep., 269, p. 333. , PRPLCM 0370-1573Rapp, R., Wambach, J., (1999) Eur. Phys. J. A, 6, p. 415. , EPJAFV 1434-6001Dusling, K., Teaney, D., Zahed, I., (2007) Phys. Rev. C, 75, p. 024908. , PRVCAN 0556-2813Van Hees, H., Rapp, R., (2008) Nucl. Phys. A, 806, p. 339. , NUPABL 0375-9474Renk, T., Ruppert, J., (2008) Phys. Rev. C, 77, p. 024907. , PRVCAN 0556-2813Adare, A., (2010) Phys. Rev. C, 81, p. 034911. , PRVCAN 0556-2813Adamczyk, L., (2014) Phys. Rev. Lett., 113, p. 022301. , a longer version (unpublished). PRLTAO 0031-9007Rapp, R., Wambach, J., Van Hees, H., (2010) Relativistic Heavy-Ion Physics, , in, edited by R. Stock, Landolt Börnstein New Series I/23A (Springer, Berlin), Chap. 4-1Linnyk, O., Cassing, W., Manninen, J., Bratkovskaya, E.L., Ko, C.M., (2012) Phys. Rev. C, 85, p. 024910. , PRVCAN 0556-2813Xu, J.-H., Chen, H.F., Dong, X., Wang, Q., Zhang, Y.F., (2012) Phys. Rev. C, 85, p. 024906. , PRVCAN 0556-2813Adare, A., (2010) Phys. Rev. Lett., 104, p. 132301. , PRLTAO 0031-9007Poskanzer, A.M., Voloshin, S.A., (1998) Phys. Rev. C, 58, p. 1671. , PRVCAN 0556-2813Adare, A., (2012) Phys. Rev. Lett., 109, p. 122302. , PRLTAO 0031-9007Van Hees, H., Gale, C., Rapp, R., (2011) Phys. Rev. C, 84, p. 054906. , PRVCAN 0556-2813Chatterjee, R., Srivastava, D.K., Heinz, U., Gale, C., (2007) Phys. Rev. C, 75, p. 054909. , PRVCAN 0556-2813Adare, A., (2009) Phys. Lett. B, 670, p. 313. , PYLBAJ 0370-2693Bonner, B., (2003) Nucl. Instrum. Methods A, 508, p. 181. , NIMAER 0168-9002Shao, M., (2002) Nucl. Instrum. Methods A, 492, p. 344Wu, J., (2005) Nucl. Instrum. Methods A, 538, p. 243. , NIMAER 0168-9002Landgraf, J.M., (2003) Nucl. Instrum. Methods A, 499, p. 762. , NIMAER 0168-9002Ackermann, K.H., (2003) Nucl. Instrum. Methods A, 499, p. 624. , NIMAER 0168-9002Anderson, M., (2003) Nucl. Instrum. Methods A, 499, p. 659. , NIMAER 0168-9002Bichsel, H., (2006) Nucl. Instrum. Methods A, 562, p. 154. , NIMAER 0168-9002Xu, Y., (2010) Nucl. Instrum. Methods A, 614, p. 28. , NIMAER 0168-9002Shao, M., (2006) Nucl. Instrum. Methods A, 558, p. 419. , NIMAER 0168-9002Adams, J., (2005) Phys. Lett. B, 616, p. 8. , PYLBAJ 0370-2693Ruan, L., Ph.D. thesis, University of Science and Technology of China, 2005, arXiv:nucl-ex/0503018 (unpublished)Llope, W.J., (2004) Nucl. Instrum. Methods A, 522, p. 252. , NIMAER 0168-9002Adler, C., (2002) Phys. Rev. Lett., 89, p. 202301. , PRLTAO 0031-9007Adams, J., (2005) Phys. Rev. Lett., 94, p. 062301. , PRLTAO 0031-9007Adamczyk, L., (2012) Phys. Rev. C, 86, p. 024906. , PRVCAN 0556-2813Zhao, J., (2013), https://drupal.star.bnl.gov/STAR/theses/phd-32, Ph.D. thesis, Shanghai Institute of Applied Physics, (unpublished)Voloshin, S.A., Poskanzer, A.M., Snellings, R., (2010) Relativistic Heavy Ion Physics, pp. 5-54. , in, Landolt-Börnstein Vol. 1/23 (Springer-Verlag, Berlin), ppAdamczyk, L., (2013) Phys. Rev. C, 88, p. 014902. , PRVCAN 0556-2813Abelev, B.I., (2008) Phys. Rev. C, 77, p. 054901. , PRVCAN 0556-2813Abelev, B.I., (2006) Phys. Rev. Lett., 97, p. 152301. , PRLTAO 0031-9007Abelev, B.I., (2009) Phys. Rev. C, 79, p. 034909. , PRVCAN 0556-2813Abelev, B.I., (2009) Phys. Rev. C, 79, p. 064903. , PRVCAN 0556-2813Adams, J., (2005) Phys. Lett. B, 612, p. 181. , PYLBAJ 0370-2693Adler, S.S., (2007) Phys. Rev. C, 75, p. 024909. , PRVCAN 0556-2813Tang, Z., Xu, Y., Ruan, L., Van Buren, G., Wang, F., Xu, Z., (2009) Phys. Rev. C, 79, p. 051901. , (R) () PRVCAN 0556-2813Shao, M., Yi, L., Tang, Z., Chen, H., Li, C., Xu, Z., (2010) J. Phys. G, 37, p. 085104. , JPGPED 0954-3899Afanasiev, S., (2009) Phys. Rev. C, 80, p. 054907. , PRVCAN 0556-2813Adams, J., (2005) Phys. Rev. C, 72, p. 014904. , PRVCAN 0556-2813Abelev, B.I., (2007) Phys. Rev. Lett., 99, p. 112301. , PRLTAO 0031-9007Kroll, N.M., Wada, W., (1955) Phys. Rev., 98, p. 1355. , PHRVAO 0031-899XRuan, L., (2011) Nucl. Phys. A, 855, p. 269. , NUPABL 0375-9474Huang, B., (2011), Ph.D. thesis, University of Science and Technology of China, (unpublished)Sjöstrand, T., (2001) Comput. Phys. Commun., 135, p. 238. , CPHCBZ 0010-4655Adamczyk, L., (2012) Phys. Rev. D, 86, p. 072013. , PRVDAQ 1550-7998Agakishiev, H., (2011) Phys. Rev. D, 83, p. 052006. , PRVDAQ 1550-7998Adare, A., (2011) Phys. Rev. C, 84, p. 044905. , PRVCAN 0556-2813Adare, A., (2012) Phys. Rev. C, 85, p. 064914. , PRVCAN 0556-2813Adare, A., (2007) Phys. Rev. Lett., 98, p. 162301. , PRLTAO 0031-9007Adams, J., (2004) Phys. Rev. Lett., 92, p. 052302. , PRLTAO 0031-9007Vujanovic, G., Young, C., Schenke, B., Jeon, S., Rapp, R., Gale, C., (2013) Nucl. Phys. A, 904-905, p. 557c. , NUPABL 0375-9474Vujanovic, G., Young, C., Schenke, B., Jeon, S., Rapp, R., Gale, C., (2014) Phys. Rev. C, 89, p. 034904. , PRVCAN 0556-281

Fluctuations Of Charge Separation Perpendicular To The Event Plane And Local Parity Violation In S Nn = 200 Gev Au + Au Collisions At The Bnl Relativistic Heavy Ion Collider

Previous experimental results based on data (∼15×106 events) collected by the STAR detector at the BNL Relativistic Heavy Ion Collider suggest event-by-event charge-separation fluctuations perpendicular to the event plane in noncentral heavy-ion collisions. Here we present the correlator previously used split into its two component parts to reveal correlations parallel and perpendicular to the event plane. The results are from a high-statistics 200-GeV Au + Au collisions data set (57×106 events) collected by the STAR experiment. We explicitly count units of charge separation from which we find clear evidence for more charge-separation fluctuations perpendicular than parallel to the event plane. We also employ a modified correlator to study the possible P-even background in same- and opposite-charge correlations, and find that the P-even background may largely be explained by momentum conservation and collective motion. © 2013 American Physical Society.886NRF-2012004024; National Research FoundationLee, T.D., Yang, C.N., (1956) Phys. Rev., 104. , 1, 254. 0031-899X PHRVAO 10.1103/PhysRev.104.254Vafa, C., Witten, E., (1984) Phys. Rev. Lett., 53. , 2, 535. 0031-9007 PRLTAO 10.1103/PhysRevLett.53.535Lee, T.D., (1973) Phys. Rev. D, 8. , 3, 1226. 0556-2821 10.1103/PhysRevD.8.1226Lee, T.D., Wick, G.C., (1974) Phys. Rev. D, 9. , 4, 2291. 0556-2821 10.1103/PhysRevD.9.2291Kharzeev, D., Parity violation in hot QCD: Why it can happen, and how to look for it (2006) Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 633 (2-3), pp. 260-264. , DOI 10.1016/j.physletb.2005.11.075, PII S0370269305017430Kharzeev, D., Zhitnitsky, A., (2007) Nucl. Phys. A, 797. , 6, 67. 0375-9474 NUPABL 10.1016/j.nuclphysa.2007.10.001Kharzeev, D., McLerran, L.D., Warringa, H.J., (2008) Nucl. Phys. A, 803. , 7, 227. 0375-9474 NUPABL 10.1016/j.nuclphysa.2008.02.298Fukushima, K., Kharzeev, D.E., Warringa, H.J., (2008) Phys. Rev. D, 78. , 8, 074033. 1550-7998 PRVDAQ 10.1103/PhysRevD.78.074033Abelev, B.I., (2009) Phys. Rev. Lett., 103. , 9 (STAR Collaboration), 251601. 0031-9007 PRLTAO 10.1103/PhysRevLett.103. 251601Abelev, B.I., (2010) Phys. Rev. C, 81. , 10 (STAR Collaboration), 054908. 0556-2813 PRVCAN 10.1103/PhysRevC.81. 054908Abelev, B.I., (2013) Phys. Rev. Lett., 110. , 11 (ALICE Collaboration), 012301. 0031-9007 PRLTAO 10.1103/PhysRevLett. 110.012301Ackermann, K.H., Adams, N., Adler, C., Ahammed, Z., Ahmad, S., Allgower, C., Amonett, J., Harris, J.W., STAR detector overview (2003) Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 499 (2-3), pp. 624-632. , DOI 10.1016/S0168-9002(02)01960-5Adams, J., Aggarwal, M.M., Ahammed, Z., Amonett, J., Anderson, B.D., Arkhipkin, D., Averichev, G.S., Bai, Y., Directed flow in Au+Au collisions at sNN=62.4 GeV (2006) Physical Review C - Nuclear Physics, 73 (3), pp. 1-7. , http://oai.aps.org/oai?verb=GetRecord&Identifier=oai:aps.org: PhysRevC.73.034903&metadataPrefix=oai_apsmeta_2, DOI 10.1103/PhysRevC.73.034903, 034903Adamczyk, L., (2012) Phys. Rev. Lett., 108. , 14 (STAR Collaboration), 202301. 0031-9007 PRLTAO 10.1103/PhysRevLett. 108.202301Voloshin, S.A., Parity violation in hot QCD: How to detect it (2004) Physical Review C - Nuclear Physics, 70 (5), pp. 0579011-0579012. , DOI 10.1103/PhysRevC.70.057901, 057901Poskanzer, A.M., Voloshin, S.A., Methods for analyzing anisotropic flow in relativistic nuclear collisions (1998) Physical Review C - Nuclear Physics, 58 (3), pp. 1671-1678. , DOI 10.1103/PhysRevC.58.1671Ollitrault, J.-Y., Poskanzer, A.M., Voloshin, S.A., (2009) Phys. Rev. C, 80. , 17, 014904. 0556-2813 PRVCAN 10.1103/PhysRevC.80.014904Pratt, S., Schlichting, S., Gavin, S., (2011) Phys. Rev. C, 84. , 18, 024909. 0556-2813 PRVCAN 10.1103/PhysRevC.84.024909Schlichting, S., Pratt, S., (2011) Phys. Rev. C, 83. , 19, 014913. 0556-2813 PRVCAN 10.1103/PhysRevC.83.014913Selyuzhenkov, I., Voloshin, S., (2008) Phys. Rev. C, 77. , 20, 034904. 0556-2813 PRVCAN 10.1103/PhysRevC.77.034904Kisiel, A., (2006) Comput. Phys. Commun., 174. , 21, 669. 0010-4655 CPHCBZ 10.1016/j.cpc.2005.11.010Bzdak, A., Koch, V., Liao, J., (2011) Phys. Rev. C, 83. , 22, 014905. 0556-2813 PRVCAN 10.1103/PhysRevC.83.014905Adams, J., Aggarwal, M.M., Ahammed, Z., Amonett, J., Anderson, B.D., Arkhipkin, D., Averichev, G.S., Grebenyuk, O., Azimuthal anisotropy in Au+Au collisions at sNN=200GeV (2005) Physical Review C - Nuclear Physics, 72 (1), pp. 1-23. , http://oai.aps.org/oai/?verb=ListRecords&metadataPrefix= oai_apsmeta_2&set=journal:PRC:72, DOI 10.1103/PhysRevC.72.014904, 014904Ray, R.L., Longacre, R.S., 24, arXiv:nucl-ex/0008009 and private communicationKopylov, G.I., Podgoretsky, M.I., Kopylov, G.I., Podgoretsky, M.I., (1972) Sov. J. Nucl. Phys., 15. , 25a, 219 ()25b, Phys. Lett. B. 50, 472 (1974) 0370-2693 PYLBAJ 10.1016/0370-2693(74)90263-925c, Sov. J. Part. Nucl. 20, 266 (1989)Goldhaber, G., Goldhaber, S., Lee, W., Pais, A., (1960) Phys. Rev., 120. , 26, 325. 0031-899X PHRVAO 10.1103/PhysRev.120.32

Effects of sleep disturbance on dyspnoea and impaired lung function following hospital admission due to COVID-19 in the UK: a prospective multicentre cohort study

Background: Sleep disturbance is common following hospital admission both for COVID-19 and other causes. The clinical associations of this for recovery after hospital admission are poorly understood despite sleep disturbance contributing to morbidity in other scenarios. We aimed to investigate the prevalence and nature of sleep disturbance after discharge following hospital admission for COVID-19 and to assess whether this was associated with dyspnoea. Methods: CircCOVID was a prospective multicentre cohort substudy designed to investigate the effects of circadian disruption and sleep disturbance on recovery after COVID-19 in a cohort of participants aged 18 years or older, admitted to hospital for COVID-19 in the UK, and discharged between March, 2020, and October, 2021. Participants were recruited from the Post-hospitalisation COVID-19 study (PHOSP-COVID). Follow-up data were collected at two timepoints: an early time point 2–7 months after hospital discharge and a later time point 10–14 months after hospital discharge. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire and a numerical rating scale. Sleep quality was also assessed with an accelerometer worn on the wrist (actigraphy) for 14 days. Participants were also clinically phenotyped, including assessment of symptoms (ie, anxiety [Generalised Anxiety Disorder 7-item scale questionnaire], muscle function [SARC-F questionnaire], dyspnoea [Dyspnoea-12 questionnaire] and measurement of lung function), at the early timepoint after discharge. Actigraphy results were also compared to a matched UK Biobank cohort (non-hospitalised individuals and recently hospitalised individuals). Multivariable linear regression was used to define associations of sleep disturbance with the primary outcome of breathlessness and the other clinical symptoms. PHOSP-COVID is registered on the ISRCTN Registry (ISRCTN10980107). Findings: 2320 of 2468 participants in the PHOSP-COVID study attended an early timepoint research visit a median of 5 months (IQR 4–6) following discharge from 83 hospitals in the UK. Data for sleep quality were assessed by subjective measures (the Pittsburgh Sleep Quality Index questionnaire and the numerical rating scale) for 638 participants at the early time point. Sleep quality was also assessed using device-based measures (actigraphy) a median of 7 months (IQR 5–8 months) after discharge from hospital for 729 participants. After discharge from hospital, the majority (396 [62%] of 638) of participants who had been admitted to hospital for COVID-19 reported poor sleep quality in response to the Pittsburgh Sleep Quality Index questionnaire. A comparable proportion (338 [53%] of 638) of participants felt their sleep quality had deteriorated following discharge after COVID-19 admission, as assessed by the numerical rating scale. Device-based measurements were compared to an age-matched, sex-matched, BMI-matched, and time from discharge-matched UK Biobank cohort who had recently been admitted to hospital. Compared to the recently hospitalised matched UK Biobank cohort, participants in our study slept on average 65 min (95% CI 59 to 71) longer, had a lower sleep regularity index (–19%; 95% CI –20 to –16), and a lower sleep efficiency (3·83 percentage points; 95% CI 3·40 to 4·26). Similar results were obtained when comparisons were made with the non-hospitalised UK Biobank cohort. Overall sleep quality (unadjusted effect estimate 3·94; 95% CI 2·78 to 5·10), deterioration in sleep quality following hospital admission (3·00; 1·82 to 4·28), and sleep regularity (4·38; 2·10 to 6·65) were associated with higher dyspnoea scores. Poor sleep quality, deterioration in sleep quality, and sleep regularity were also associated with impaired lung function, as assessed by forced vital capacity. Depending on the sleep metric, anxiety mediated 18–39% of the effect of sleep disturbance on dyspnoea, while muscle weakness mediated 27–41% of this effect. Interpretation: Sleep disturbance following hospital admission for COVID-19 is associated with dyspnoea, anxiety, and muscle weakness. Due to the association with multiple symptoms, targeting sleep disturbance might be beneficial in treating the post-COVID-19 condition. Funding: UK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council

SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination

BACKGROUND: Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. METHODS: In this follow up study, plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. FINDINGS: Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months (p < 0.0001). Nasal and plasma anti-S IgG remained elevated for at least 12 months (p < 0.0001) with plasma neutralising titres that were raised against all variants compared to controls (p < 0.0001). Of 323 with complete data, 307 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal (1.46-fold change after 10 months, p = 0.011) and the median remained below the positive threshold determined by pre-pandemic controls. Samples 12 months after admission showed no association between nasal IgA and plasma IgG anti-S responses (R = 0.05, p = 0.18), indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. INTERPRETATION: The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. FUNDING: This study has been supported by ISARIC4C and PHOSP-COVID consortia. ISARIC4C is supported by grants from the National Institute for Health and Care Research and the Medical Research Council. Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research. The PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute of Health and Care Research. The funders were not involved in the study design, interpretation of data or the writing of this manuscript

Accelarated immune ageing is associated with COVID-19 disease severity

Background The striking increase in COVID-19 severity in older adults provides a clear example of immunesenescence, the age-related remodelling of the immune system. To better characterise the association between convalescent immunesenescence and acute disease severity, we determined the immune phenotype of COVID-19 survivors and non-infected controls. Results We performed detailed immune phenotyping of peripheral blood mononuclear cells isolated from 103 COVID-19 survivors 3–5 months post recovery who were classified as having had severe (n = 56; age 53.12 ± 11.30 years), moderate (n = 32; age 52.28 ± 11.43 years) or mild (n = 15; age 49.67 ± 7.30 years) disease and compared with age and sex-matched healthy adults (n = 59; age 50.49 ± 10.68 years). We assessed a broad range of immune cell phenotypes to generate a composite score, IMM-AGE, to determine the degree of immune senescence. We found increased immunesenescence features in severe COVID-19 survivors compared to controls including: a reduced frequency and number of naïve CD4 and CD8 T cells (p < 0.0001); increased frequency of EMRA CD4 (p < 0.003) and CD8 T cells (p < 0.001); a higher frequency (p < 0.0001) and absolute numbers (p < 0.001) of CD28−ve CD57+ve senescent CD4 and CD8 T cells; higher frequency (p < 0.003) and absolute numbers (p < 0.02) of PD-1 expressing exhausted CD8 T cells; a two-fold increase in Th17 polarisation (p < 0.0001); higher frequency of memory B cells (p < 0.001) and increased frequency (p < 0.0001) and numbers (p < 0.001) of CD57+ve senescent NK cells. As a result, the IMM-AGE score was significantly higher in severe COVID-19 survivors than in controls (p < 0.001). Few differences were seen for those with moderate disease and none for mild disease. Regression analysis revealed the only pre-existing variable influencing the IMM-AGE score was South Asian ethnicity ( = 0.174, p = 0.043), with a major influence being disease severity ( = 0.188, p = 0.01). Conclusions Our analyses reveal a state of enhanced immune ageing in survivors of severe COVID-19 and suggest this could be related to SARS-Cov-2 infection. Our data support the rationale for trials of anti-immune ageing interventions for improving clinical outcomes in these patients with severe disease