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Ross FA, Hawley SA, Russell FM, Goodman N, Hardie DG. Frequent loss-of-function mutations in the AMPK-α2 catalytic subunit suggest a tumour suppressor role in human skin cancers. Biochem J 2023; 480:1951-1968. [PMID: 37962491 PMCID: PMC10754287 DOI: 10.1042/bcj20230380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 11/07/2023] [Accepted: 11/13/2023] [Indexed: 11/15/2023]
Abstract
The AMP-activated protein kinase (AMPK) is a sensor of cellular energy status activated by increases in AMP or ADP relative to ATP. Once activated, it phosphorylates targets that promote ATP-generating catabolic pathways or inhibit ATP-consuming anabolic pathways, helping to restore cellular energy balance. Analysis of human cancer genome studies reveals that the PRKAA2 gene (encoding the α2 isoform of the catalytic subunit) is often subject to mis-sense mutations in cancer, particularly in melanoma and non-melanoma skin cancers, where up to 70 mis-sense mutations have been documented, often accompanied by loss of the tumour suppressor NF1. Recently it has been reported that knockout of PRKAA2 in NF1-deficient melanoma cells promoted anchorage-independent growth in vitro, as well as growth as xenografts in immunodeficient mice in vivo, suggesting that AMPK-α2 can act as a tumour suppressor in that context. However, very few of the mis-sense mutations in PRKAA2 that occur in human skin cancer and melanoma have been tested to see whether they cause loss-of-function. We have addressed this by making most of the reported mutations and testing their activity when expressed in AMPK knockout cells. Of 55 different mis-sense mutations (representing 75 cases), 9 (12%) appeared to cause a total loss of activity, 18 (24%) a partial loss, 11 (15%) an increase in phenformin-stimulated kinase activity, while just 37 (49%) had no clear effect on kinase activity. This supports the idea that AMPK-α2 acts as a tumour suppressor in the context of human skin cancer.
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Affiliation(s)
- Fiona A. Ross
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Scotland, U.K
| | - Simon A. Hawley
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Scotland, U.K
| | - Fiona M. Russell
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Scotland, U.K
| | - Nicola Goodman
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Scotland, U.K
| | - D. Grahame Hardie
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Scotland, U.K
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Raman B, McCracken C, Cassar MP, Moss AJ, Finnigan L, Samat AHA, Ogbole G, Tunnicliffe EM, Alfaro-Almagro F, Menke R, Xie C, Gleeson F, Lukaschuk E, Lamlum H, McGlynn K, Popescu IA, Sanders ZB, Saunders LC, Piechnik SK, Ferreira VM, Nikolaidou C, Rahman NM, Ho LP, Harris VC, Shikotra A, Singapuri A, Pfeffer P, Manisty C, Kon OM, Beggs M, O'Regan DP, Fuld J, Weir-McCall JR, Parekh D, Steeds R, Poinasamy K, Cuthbertson DJ, Kemp GJ, Semple MG, Horsley A, Miller CA, O'Brien C, Shah AM, Chiribiri A, Leavy OC, Richardson M, Elneima O, McAuley HJC, Sereno M, Saunders RM, Houchen-Wolloff L, Greening NJ, Bolton CE, Brown JS, Choudhury G, Diar Bakerly N, Easom N, Echevarria C, Marks M, Hurst JR, Jones MG, Wootton DG, Chalder T, Davies MJ, De Soyza A, Geddes JR, Greenhalf W, Howard LS, Jacob J, Man WDC, Openshaw PJM, Porter JC, Rowland MJ, Scott JT, Singh SJ, Thomas DC, Toshner M, Lewis KE, Heaney LG, Harrison EM, Kerr S, Docherty AB, Lone NI, Quint J, Sheikh A, Zheng B, Jenkins RG, Cox E, 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Parkes M, McQueen A, Oliver C, Williams J, Paradowski K, Broad L, Knibbs L, Haynes M, Sabit R, Milligan L, Sampson C, Hancock A, Evenden C, Lynch C, Hancock K, Roche L, Rees M, Stroud N, Thomas-Woods T, Heller S, Robertson E, Young B, Wassall H, Babores M, Holland M, Keenan N, Shashaa S, Price C, Beranova E, Ramos H, Weston H, Deery J, Austin L, Solly R, Turney S, Cosier T, Hazelton T, Ralser M, Wilson A, Pearce L, Pugmire S, Stoker W, McCormick W, Dewar A, Arbane G, Kaltsakas G, Kerslake H, Rossdale J, Bisnauthsing K, Aguilar Jimenez LA, Martinez LM, Ostermann M, Magtoto MM, Hart N, Marino P, Betts S, Solano TS, Arias AM, Prabhu A, Reed A, Wrey Brown C, Griffin D, Bevan E, Martin J, Owen J, Alvarez Corral M, Williams N, Payne S, Storrar W, Layton A, Lawson C, Mills C, Featherstone J, Stephenson L, Burdett T, Ellis Y, Richards A, Wright C, Sykes DL, Brindle K, Drury K, Holdsworth L, Crooks MG, Atkin P, Flockton R, Thackray-Nocera S, Mohamed A, Taylor A, Perkins E, Ross G, McGuinness H, 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Glossop J, Murira J, Rangeley J, Woods J, Hall L, Dalton M, Window N, Beirne P, Hardy T, Coakley G, Turtle L, Berridge A, Cross A, Key AL, Rowe A, Allt AM, Mears C, Malein F, Madzamba G, Hardwick HE, Earley J, Hawkes J, Pratt J, Wyles J, Tripp KA, Hainey K, Allerton L, Lavelle-Langham L, Melling L, Wajero LO, Poll L, Noonan MJ, French N, Lewis-Burke N, Williams-Howard SA, Cooper S, Kaprowska S, Dobson SL, Marsh S, Highett V, Shaw V, Beadsworth M, Defres S, Watson E, Tiongson GF, Papineni P, Gurram S, Diwanji SN, Quaid S, Briggs A, Hastie C, Rogers N, Stensel D, Bishop L, McIvor K, Rivera-Ortega P, Al-Sheklly B, Avram C, Faluyi D, Blaikely J, Piper Hanley K, Radhakrishnan K, Buch M, Hanley NA, Odell N, Osbourne R, Stockdale S, Felton T, Gorsuch T, Hussell T, Kausar Z, Kabir T, McAllister-Williams H, Paddick S, Burn D, Ayoub A, Greenhalgh A, Sayer A, Young A, Price D, Burns G, MacGowan G, Fisher H, Tedd H, Simpson J, Jiwa K, Witham M, Hogarth P, West S, Wright S, McMahon MJ, Neill P, Dougherty A, Morrow A, Anderson D, Grieve D, Bayes H, Fallon K, Mangion K, Gilmour L, Basu N, Sykes R, Berry C, McInnes IB, Donaldson A, Sage EK, Barrett F, Welsh B, Bell M, Quigley J, Leitch K, Macliver L, Patel M, Hamil R, Deans A, Furniss J, Clohisey S, Elliott A, Solstice AR, Deas C, Tee C, Connell D, Sutherland D, George J, Mohammed S, Bunker J, Holmes K, Dipper A, Morley A, Arnold D, Adamali H, Welch H, Morrison L, Stadon L, Maskell N, Barratt S, Dunn S, Waterson S, Jayaraman B, Light T, Selby N, Hosseini A, Shaw K, Almeida P, Needham R, Thomas AK, Matthews L, Gupta A, Nikolaidis A, Dupont C, Bonnington J, Chrystal M, Greenhaff PL, Linford S, Prosper S, Jang W, Alamoudi A, Bloss A, Megson C, Nicoll D, Fraser E, Pacpaco E, Conneh F, Ogg G, McShane H, Koychev I, Chen J, Pimm J, Ainsworth M, Pavlides M, Sharpe M, Havinden-Williams M, Petousi N, Talbot N, Carter P, Kurupati P, Dong T, Peng Y, Burns A, Kanellakis N, Korszun A, Connolly B, Busby J, Peto T, Patel B, Nolan CM, Cristiano D, Walsh JA, Liyanage K, Gummadi M, Dormand N, Polgar O, George P, Barker RE, Patel S, Price L, Gibbons M, Matila D, Jarvis H, Lim L, Olaosebikan O, Ahmad S, Brill S, Mandal S, Laing C, Michael A, Reddy A, Johnson C, Baxendale H, Parfrey H, Mackie J, Newman J, Pack J, Parmar J, Paques K, Garner L, Harvey A, Summersgill C, Holgate D, Hardy E, Oxton J, Pendlebury J, McMorrow L, Mairs N, Majeed N, Dark P, Ugwuoke R, Knight S, Whittaker S, Strong-Sheldrake S, Matimba-Mupaya W, Chowienczyk P, Pattenadk D, Hurditch E, Chan F, Carborn H, Foot H, Bagshaw J, Hockridge J, Sidebottom J, Lee JH, Birchall K, Turner K, Haslam L, Holt L, Milner L, Begum M, Marshall M, Steele N, Tinker N, Ravencroft P, Butcher R, Misra S, Walker S, Coburn Z, Fairman A, Ford A, Holbourn A, Howell A, Lawrie A, Lye A, Mbuyisa A, Zawia A, Holroyd-Hind B, Thamu B, Clark C, Jarman C, Norman C, Roddis C, Foote D, Lee E, Ilyas F, Stephens G, Newell H, Turton H, Macharia I, Wilson I, Cole J, McNeill J, Meiring J, Rodger J, Watson J, Chapman K, Harrington K, Chetham L, Hesselden L, Nwafor L, Dixon M, Plowright M, Wade P, Gregory R, Lenagh R, Stimpson R, Megson S, Newman T, Cheng Y, Goodwin C, Heeley C, Sissons D, Sowter D, Gregory H, Wynter I, Hutchinson J, Kirk J, Bennett K, Slack K, Allsop L, Holloway L, Flynn M, Gill M, Greatorex M, Holmes M, Buckley P, Shelton S, Turner S, Sewell TA, Whitworth V, Lovegrove W, Tomlinson J, Warburton L, Painter S, Vickers C, Redwood D, Tilley J, Palmer S, Wainwright T, Breen G, Hotopf M, Dunleavy A, Teixeira J, Ali M, Mencias M, Msimanga N, Siddique S, Samakomva T, Tavoukjian V, Forton D, Ahmed R, Cook A, Thaivalappil F, Connor L, Rees T, McNarry M, Williams N, McCormick J, McIntosh J, Vere J, Coulding M, Kilroy S, Turner V, Butt AT, Savill H, Fraile E, Ugoji J, Landers G, Lota H, Portukhay S, Nasseri M, Daniels A, Hormis A, Ingham J, Zeidan L, Osborne L, Chablani M, Banerjee A, David A, Pakzad A, Rangelov B, Williams B, Denneny E, Willoughby J, Xu M, Mehta P, Batterham R, Bell R, Aslani S, Lilaonitkul W, Checkley A, Bang D, Basire D, Lomas D, Wall E, Plant H, Roy K, Heightman M, Lipman M, Merida Morillas M, Ahwireng N, Chambers RC, Jastrub R, Logan S, Hillman T, Botkai A, Casey A, Neal A, Newton-Cox A, Cooper B, Atkin C, McGee C, Welch C, Wilson D, Sapey E, Qureshi H, Hazeldine J, Lord JM, Nyaboko J, Short J, Stockley J, Dasgin J, Draxlbauer K, Isaacs K, Mcgee K, Yip KP, Ratcliffe L, Bates M, Ventura M, Ahmad Haider N, Gautam N, Baggott R, Holden S, Madathil S, Walder S, Yasmin S, Hiwot T, Jackson T, Soulsby T, Kamwa V, Peterkin Z, Suleiman Z, Chaudhuri N, Wheeler H, Djukanovic R, Samuel R, Sass T, Wallis T, Marshall B, Childs C, Marouzet E, Harvey M, Fletcher S, Dickens C, Beckett P, Nanda U, Daynes E, Charalambou A, Yousuf AJ, Lea A, Prickett A, Gooptu B, Hargadon B, Bourne C, Christie C, Edwardson C, Lee D, Baldry E, Stringer E, Woodhead F, Mills G, Arnold H, Aung H, Qureshi IN, Finch J, Skeemer J, Hadley K, Khunti K, Carr L, Ingram L, Aljaroof M, Bakali M, Bakau M, Baldwin M, Bourne M, Pareek M, Soares M, Tobin M, Armstrong N, Brunskill N, Goodman N, Cairns P, Haldar P, McCourt P, Dowling R, Russell R, Diver S, Edwards S, Glover S, Parker S, Siddiqui S, Ward TJC, Mcnally T, Thornton T, Yates T, Ibrahim W, Monteiro W, Thickett D, Wilkinson D, Broome M, McArdle P, Upthegrove R, Wraith D, Langenberg C, Summers C, Bullmore E, Heeney JL, Schwaeble W, Sudlow CL, Adeloye D, Newby DE, Rudan I, Shankar-Hari M, Thorpe M, Pius R, Walmsley S, McGovern A, Ballard C, Allan L, Dennis J, Cavanagh J, Petrie J, O'Donnell K, Spears M, Sattar N, MacDonald S, Guthrie E, Henderson M, Guillen Guio B, Zhao B, Lawson C, Overton C, Taylor C, Tong C, Mukaetova-Ladinska E, Turner E, Pearl JE, Sargant J, Wormleighton J, Bingham M, Sharma M, Steiner M, Samani N, Novotny P, Free R, Allen RJ, Finney S, Terry S, Brugha T, Plekhanova T, McArdle A, Vinson B, Spencer LG, Reynolds W, Ashworth M, Deakin B, Chinoy H, Abel K, Harvie M, Stanel S, Rostron A, Coleman C, Baguley D, Hufton E, Khan F, Hall I, Stewart I, Fabbri L, Wright L, Kitterick P, Morriss R, Johnson S, Bates A, Antoniades C, Clark D, Bhui K, Channon KM, Motohashi K, Sigfrid L, Husain M, Webster M, Fu X, Li X, Kingham L, Klenerman P, Miiler K, Carson G, Simons G, Huneke N, Calder PC, Baldwin D, Bain S, Lasserson D, Daines L, Bright E, Stern M, Crisp P, Dharmagunawardena R, Reddington A, Wight A, Bailey L, Ashish A, Robinson E, Cooper J, Broadley A, Turnbull A, Brookes C, Sarginson C, Ionita D, Redfearn H, Elliott K, Barman L, Griffiths L, Guy Z, Gill R, Nathu R, Harris E, Moss P, Finnigan J, Saunders K, Saunders P, Kon S, Kon SS, O'Brien L, Shah K, Shah P, Richardson E, Brown V, Brown M, Brown J, Brown J, Brown A, Brown A, Brown M, Choudhury N, Jones S, Jones H, Jones L, Jones I, Jones G, Jones H, Jones D, Davies F, Davies E, Davies K, Davies G, Davies GA, Howard K, Porter J, Rowland J, Rowland A, Scott K, Singh S, Singh C, Thomas S, Thomas C, Lewis V, Lewis J, Lewis D, Harrison P, Francis C, Francis R, Hughes RA, Hughes J, Hughes AD, Thompson T, Kelly S, Smith D, Smith N, Smith A, Smith J, Smith L, Smith S, Evans T, Evans RI, Evans D, Evans R, Evans H, Evans J. Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study. Lancet Respir Med 2023; 11:1003-1019. [PMID: 37748493 PMCID: PMC7615263 DOI: 10.1016/s2213-2600(23)00262-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 06/16/2023] [Accepted: 06/30/2023] [Indexed: 09/27/2023]
Abstract
INTRODUCTION The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. METHODS In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. FINDINGS Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2-6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5-5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4-10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32-4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23-11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. INTERPRETATION After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification. FUNDING UK Research and Innovation and National Institute for Health Research.
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Evans RA, Leavy OC, Richardson M, Elneima O, McAuley HJC, Shikotra A, Singapuri A, Sereno M, Saunders RM, Harris VC, Houchen-Wolloff L, Aul R, Beirne P, Bolton CE, Brown JS, Choudhury G, Diar-Bakerly N, Easom N, Echevarria C, Fuld J, Hart N, Hurst J, Jones MG, Parekh D, Pfeffer P, Rahman NM, Rowland-Jones SL, Shah AM, Wootton DG, Chalder T, Davies MJ, De Soyza A, Geddes JR, Greenhalf W, Greening NJ, Heaney LG, Heller S, Howard LS, Jacob J, Jenkins RG, Lord JM, Man WDC, McCann GP, Neubauer S, Openshaw PJM, Porter JC, Rowland MJ, Scott JT, Semple MG, Singh SJ, Thomas DC, Toshner M, Lewis KE, Thwaites RS, Briggs A, Docherty AB, Kerr S, Lone NI, Quint J, Sheikh A, Thorpe M, Zheng B, Chalmers JD, Ho LP, Horsley A, Marks M, Poinasamy K, Raman B, Harrison EM, Wain LV, Brightling CE, Abel K, Adamali H, Adeloye D, Adeyemi O, Adrego R, Aguilar Jimenez LA, Ahmad S, Ahmad Haider N, Ahmed R, Ahwireng N, Ainsworth M, Al-Sheklly B, Alamoudi A, Ali M, Aljaroof M, All AM, Allan L, Allen RJ, Allerton L, Allsop L, Almeida P, Altmann D, Alvarez Corral M, Amoils S, Anderson D, Antoniades C, Arbane G, Arias A, Armour C, Armstrong L, Armstrong N, Arnold D, Arnold H, Ashish A, Ashworth A, Ashworth M, Aslani S, Assefa-Kebede H, Atkin C, Atkin P, Aung H, Austin L, Avram C, Ayoub A, Babores M, Baggott R, Bagshaw J, Baguley D, Bailey L, Baillie JK, Bain S, Bakali M, Bakau M, Baldry E, Baldwin D, Ballard C, Banerjee A, Bang B, Barker RE, Barman L, Barratt S, Barrett F, Basire D, Basu N, Bates M, Bates A, Batterham R, Baxendale H, Bayes H, Beadsworth M, Beckett P, Beggs M, Begum M, Bell D, Bell R, Bennett K, Beranova E, Bermperi A, Berridge A, Berry C, Betts S, Bevan E, Bhui K, Bingham M, Birchall K, Bishop L, Bisnauthsing K, Blaikely J, Bloss A, Bolger A, Bonnington J, Botkai A, Bourne C, Bourne M, Bramham K, Brear L, Breen G, Breeze J, Bright E, Brill S, Brindle K, Broad L, Broadley A, Brookes C, Broome M, Brown A, Brown A, Brown J, Brown J, Brown M, Brown M, Brown V, Brugha T, Brunskill N, Buch M, Buckley P, Bularga A, Bullmore E, Burden L, Burdett T, Burn D, Burns G, Burns A, Busby J, Butcher R, Butt A, Byrne S, Cairns P, Calder PC, Calvelo E, Carborn H, Card B, Carr C, Carr L, Carson G, Carter P, Casey A, Cassar M, Cavanagh J, Chablani M, Chambers RC, Chan F, Channon KM, Chapman K, Charalambou A, Chaudhuri N, Checkley A, Chen J, Cheng Y, Chetham L, Childs C, Chilvers ER, Chinoy H, Chiribiri A, Chong-James K, Choudhury N, Chowienczyk P, Christie C, Chrystal M, Clark D, Clark C, Clarke J, Clohisey S, Coakley G, Coburn Z, Coetzee S, Cole J, Coleman C, Conneh F, Connell D, Connolly B, Connor L, Cook A, Cooper B, Cooper J, Cooper S, Copeland D, Cosier T, Coulding M, Coupland C, Cox E, Craig T, Crisp P, Cristiano D, Crooks MG, Cross A, Cruz I, Cullinan P, Cuthbertson D, Daines L, Dalton M, Daly P, Daniels A, Dark P, Dasgin J, David A, David C, Davies E, Davies F, Davies G, Davies GA, Davies K, Dawson J, Daynes E, Deakin B, Deans A, Deas C, Deery J, Defres S, Dell A, Dempsey K, Denneny E, Dennis J, Dewar A, Dharmagunawardena R, Dickens C, Dipper A, Diver S, Diwanji SN, Dixon M, Djukanovic R, Dobson H, Dobson SL, Donaldson A, Dong T, Dormand N, Dougherty A, Dowling R, Drain S, Draxlbauer K, Drury K, Dulawan P, Dunleavy A, Dunn S, Earley J, Edwards S, Edwardson C, El-Taweel H, Elliott A, Elliott K, Ellis Y, Elmer A, Evans D, Evans H, Evans J, Evans R, Evans RI, Evans T, Evenden C, Evison L, Fabbri L, Fairbairn S, Fairman A, Fallon K, Faluyi D, Favager C, Fayzan T, Featherstone J, Felton T, Finch J, Finney S, Finnigan J, Finnigan L, Fisher H, Fletcher S, Flockton R, Flynn M, Foot H, Foote D, Ford A, Forton D, Fraile E, Francis C, Francis R, Francis S, Frankel A, Fraser E, Free R, French N, Fu X, Furniss J, Garner L, Gautam N, George J, George P, Gibbons M, Gill M, Gilmour L, Gleeson F, Glossop J, Glover S, Goodman N, Goodwin C, Gooptu B, Gordon H, Gorsuch T, Greatorex M, Greenhaff PL, Greenhalgh A, Greenwood J, Gregory H, Gregory R, Grieve D, Griffin D, Griffiths L, Guerdette AM, Guillen Guio B, Gummadi M, Gupta A, Gurram S, Guthrie E, Guy Z, H Henson H, Hadley K, Haggar A, Hainey K, Hairsine B, Haldar P, Hall I, Hall L, Halling-Brown M, Hamil R, Hancock A, Hancock K, Hanley NA, Haq S, Hardwick HE, Hardy E, Hardy T, Hargadon B, Harrington K, Harris E, Harrison P, Harvey A, Harvey M, Harvie M, Haslam L, Havinden-Williams M, Hawkes J, Hawkings N, Haworth J, Hayday A, Haynes M, Hazeldine J, Hazelton T, Heeley C, Heeney JL, Heightman M, Henderson M, Hesselden L, Hewitt M, Highett V, Hillman T, Hiwot T, Hoare A, Hoare M, Hockridge J, Hogarth P, Holbourn A, Holden S, Holdsworth L, Holgate D, Holland M, Holloway L, Holmes K, Holmes M, Holroyd-Hind B, Holt L, Hormis A, Hosseini A, Hotopf M, Howard K, Howell A, Hufton E, Hughes AD, Hughes J, Hughes R, Humphries A, Huneke N, Hurditch E, Husain M, Hussell T, Hutchinson J, Ibrahim W, Ilyas F, Ingham J, Ingram L, Ionita D, Isaacs K, Ismail K, Jackson T, James WY, Jarman C, Jarrold I, Jarvis H, Jastrub R, Jayaraman B, Jezzard P, Jiwa K, Johnson C, Johnson S, Johnston D, Jolley CJ, Jones D, Jones G, Jones H, Jones H, Jones I, Jones L, Jones S, Jose S, Kabir T, Kaltsakas G, Kamwa V, Kanellakis N, Kaprowska S, Kausar Z, Keenan N, Kelly S, Kemp G, Kerslake H, Key AL, Khan F, Khunti K, Kilroy S, King B, King C, Kingham L, Kirk J, Kitterick P, Klenerman P, Knibbs L, Knight S, Knighton A, Kon O, Kon S, Kon SS, Koprowska S, Korszun A, Koychev I, Kurasz C, Kurupati P, Laing C, Lamlum H, Landers G, Langenberg C, Lasserson D, Lavelle-Langham L, Lawrie A, Lawson C, Lawson C, Layton A, Lea A, Lee D, Lee JH, Lee E, Leitch K, Lenagh R, Lewis D, Lewis J, Lewis V, Lewis-Burke N, Li X, Light T, Lightstone L, Lilaonitkul W, Lim L, Linford S, Lingford-Hughes A, Lipman M, Liyanage K, Lloyd A, Logan S, Lomas D, Loosley R, Lota H, Lovegrove W, Lucey A, Lukaschuk E, Lye A, Lynch C, MacDonald S, MacGowan G, Macharia I, Mackie J, Macliver L, Madathil S, Madzamba G, Magee N, Magtoto MM, Mairs N, Majeed N, Major E, Malein F, Malim M, Mallison G, Mandal S, Mangion K, Manisty C, Manley R, March K, Marciniak S, Marino P, Mariveles M, Marouzet E, Marsh S, Marshall B, Marshall M, Martin J, Martineau A, Martinez LM, Maskell N, Matila D, Matimba-Mupaya W, Matthews L, Mbuyisa A, McAdoo S, Weir McCall J, McAllister-Williams H, McArdle A, McArdle P, McAulay D, McCormick J, McCormick W, McCourt P, McGarvey L, McGee C, Mcgee K, McGinness J, McGlynn K, McGovern A, McGuinness H, McInnes IB, McIntosh J, McIvor E, McIvor K, McLeavey L, McMahon A, McMahon MJ, McMorrow L, Mcnally T, McNarry M, McNeill J, McQueen A, McShane H, Mears C, Megson C, Megson S, Mehta P, Meiring J, Melling L, Mencias M, Menzies D, Merida Morillas M, Michael A, Milligan L, Miller C, Mills C, Mills NL, Milner L, Misra S, Mitchell J, Mohamed A, Mohamed N, Mohammed S, Molyneaux PL, Monteiro W, Moriera S, Morley A, Morrison L, Morriss R, Morrow A, Moss AJ, Moss P, Motohashi K, Msimanga N, Mukaetova-Ladinska E, Munawar U, Murira J, Nanda U, Nassa H, Nasseri M, Neal A, Needham R, Neill P, Newell H, Newman T, Newton-Cox A, Nicholson T, Nicoll D, Nolan CM, Noonan MJ, Norman C, Novotny P, Nunag J, Nwafor L, Nwanguma U, Nyaboko J, O'Donnell K, O'Brien C, O'Brien L, O'Regan D, Odell N, Ogg G, Olaosebikan O, Oliver C, Omar Z, Orriss-Dib L, Osborne L, Osbourne R, Ostermann M, Overton C, Owen J, Oxton J, Pack J, Pacpaco E, Paddick S, Painter S, Pakzad A, Palmer S, Papineni P, Paques K, Paradowski K, Pareek M, Parfrey H, Pariante C, Parker S, Parkes M, Parmar J, Patale S, Patel B, Patel M, Patel S, Pattenadk D, Pavlides M, Payne S, Pearce L, Pearl JE, Peckham D, Pendlebury J, Peng Y, Pennington C, Peralta I, Perkins E, Peterkin Z, Peto T, Petousi N, Petrie J, Phipps J, Pimm J, Piper Hanley K, Pius R, Plant H, Plein S, Plekhanova T, Plowright M, Polgar O, Poll L, Porter J, Portukhay S, Powell N, Prabhu A, Pratt J, Price A, Price C, Price C, Price D, Price L, Price L, Prickett A, Propescu J, Pugmire S, Quaid S, Quigley J, Qureshi H, Qureshi IN, Radhakrishnan K, Ralser M, Ramos A, Ramos H, Rangeley J, Rangelov B, Ratcliffe L, Ravencroft P, Reddington A, Reddy R, Redfearn H, Redwood D, Reed A, Rees M, Rees T, Regan K, Reynolds W, Ribeiro C, Richards A, Richardson E, Rivera-Ortega P, Roberts K, Robertson E, Robinson E, Robinson L, Roche L, Roddis C, Rodger J, Ross A, Ross G, Rossdale J, Rostron A, Rowe A, Rowland A, Rowland J, Roy K, Roy M, Rudan I, Russell R, Russell E, Saalmink G, Sabit R, Sage EK, Samakomva T, Samani N, Sampson C, Samuel K, Samuel R, Sanderson A, Sapey E, Saralaya D, Sargant J, Sarginson C, Sass T, Sattar N, Saunders K, Saunders P, Saunders LC, Savill H, Saxon W, Sayer A, Schronce J, Schwaeble W, Scott K, Selby N, Sewell TA, Shah K, Shah P, Shankar-Hari M, Sharma M, Sharpe C, Sharpe M, Shashaa S, Shaw A, Shaw K, Shaw V, Shelton S, Shenton L, Shevket K, Short J, Siddique S, Siddiqui S, Sidebottom J, Sigfrid L, Simons G, Simpson J, Simpson N, Singh C, Singh S, Sissons D, Skeemer J, Slack K, Smith A, Smith D, Smith S, Smith J, Smith L, Soares M, Solano TS, Solly R, Solstice AR, Soulsby T, Southern D, Sowter D, Spears M, Spencer LG, Speranza F, Stadon L, Stanel S, Steele N, Steiner M, Stensel D, Stephens G, Stephenson L, Stern M, Stewart I, Stimpson R, Stockdale S, Stockley J, Stoker W, Stone R, Storrar W, Storrie A, Storton K, Stringer E, Strong-Sheldrake S, Stroud N, Subbe C, Sudlow CL, Suleiman Z, Summers C, Summersgill C, Sutherland D, Sykes DL, Sykes R, Talbot N, Tan AL, Tarusan L, Tavoukjian V, Taylor A, Taylor C, Taylor J, Te A, Tedd H, Tee CJ, Teixeira J, Tench H, Terry S, Thackray-Nocera S, Thaivalappil F, Thamu B, Thickett D, Thomas C, Thomas S, Thomas AK, Thomas-Woods T, Thompson T, Thompson AAR, Thornton T, Tilley J, Tinker N, Tiongson GF, Tobin M, Tomlinson J, Tong C, Touyz R, Tripp KA, Tunnicliffe E, Turnbull A, Turner E, Turner S, Turner V, Turner K, Turney S, Turtle L, Turton H, Ugoji J, Ugwuoke R, Upthegrove R, Valabhji J, Ventura M, Vere J, Vickers C, Vinson B, Wade E, Wade P, Wainwright T, Wajero LO, Walder S, Walker S, Walker S, Wall E, Wallis T, Walmsley S, Walsh JA, Walsh S, Warburton L, Ward TJC, Warwick K, Wassall H, Waterson S, Watson E, Watson L, Watson J, Welch C, Welch H, Welsh B, Wessely S, West S, Weston H, Wheeler H, White S, Whitehead V, Whitney J, Whittaker S, Whittam B, Whitworth V, Wight A, Wild J, Wilkins M, Wilkinson D, Williams N, Williams N, Williams J, Williams-Howard SA, Willicombe M, Willis G, Willoughby J, Wilson A, Wilson D, Wilson I, Window N, Witham M, Wolf-Roberts R, Wood C, Woodhead F, Woods J, Wormleighton J, Worsley J, Wraith D, Wrey Brown C, Wright C, Wright L, Wright S, Wyles J, Wynter I, Xu M, Yasmin N, Yasmin S, Yates T, Yip KP, Young B, Young S, Young A, Yousuf AJ, Zawia A, Zeidan L, Zhao B, Zongo O. Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study. Lancet Respir Med 2022; 10:761-775. [PMID: 35472304 PMCID: PMC9034855 DOI: 10.1016/s2213-2600(22)00127-8] [Citation(s) in RCA: 144] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/23/2022] [Accepted: 03/31/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge. METHODS The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing. FINDINGS 2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7-9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46-0·99]), obesity (0·50 [0·34-0·74]) and invasive mechanical ventilation (0·42 [0·23-0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74-1·00]), at 5 months (0·74 [0·64-0·88]) to 1 year (0·75 [0·62-0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters. INTERPRETATION The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials. FUNDING UK Research and Innovation and National Institute for Health Research.
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Cramer A, Goodman N, Cross T, Gant V, Dziadzio M. Analytical evaluation and critical appraisal of early commercial SARS-CoV-2 immunoassays for routine use in a diagnostic laboratory. Br J Biomed Sci 2021; 78:141-146. [PMID: 33308026 PMCID: PMC7885716 DOI: 10.1080/09674845.2020.1864108] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background: The objective of this study was to evaluate the performance characteristics of early commercial SARS-CoV-2 antibody assays in mild and asymptomatic subjects to enable the selection of suitable immunoassays for routine diagnostic use. Methods: We used serum samples from a pre-COVID era patient cohort (n = 50, pre-December 2019), designated SARS-CoV-2 negative, and serum samples from a SARS-CoV-2 RT-PCR-positive cohort (n = 90) taken > 14 days post-symptom onset (April–May 2020). Six ELISA assays were evaluated, including one confirmation assay to investigate antibody specificity. We also evaluated one point-of-care lateral flow device (LFIA) and one high throughput electrochemiluminescence immunoassay (CLIA). Results: The ELISA specificities ranged from 84% to 100%, with sensitivities ranging from 75.3% to 90.0%. The LFIA showed 100% specificity and 80% sensitivity using smaller sample numbers. The Roche CLIA immunoassay showed 100% specificity and 90.7% sensitivity. When used in conjunction, the Euroimmun nucleocapsid (NC) and spike-1 (S1) IgG ELISA assays had a sensitivity of 95.6%. The confirmation Dia.Pro IgG assay showed 92.6% of samples tested contained both NC and S1 antibodies, 32.7% had NC, S1 and S2 and 0% had either S1 or S2 only. Conclusions: The Roche assay and the Euroimmun NC and S1 assays had the best sensitivity overall. Combining the assays detecting NC and S1/S2 antibody increased diagnostic yield. These first-generation assays were not calibrated against reference material and the results were reported qualitatively. A portfolio of next-generation SARS-CoV-2 immunoassays will be necessary to investigate herd and vaccine-induced immunity.
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Affiliation(s)
- A Cramer
- Department of Immunology, HCA Healthcare UK, Shropshire House, London, UK
| | - N Goodman
- Department of Immunology, HCA Healthcare UK, Shropshire House, London, UK
| | - T Cross
- Department of Immunology, HCA Healthcare UK, Shropshire House, London, UK
| | - V Gant
- Department of Immunology, HCA Healthcare UK, Shropshire House, London, UK.,Division of Infection and Immunity, University College London, London, UK
| | - M Dziadzio
- Department of Immunology, HCA Healthcare UK, Shropshire House, London, UK.,UCL Ear Institute, University College London, London, UK
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5
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Rihn SJ, Merits A, Bakshi S, Turnbull ML, Wickenhagen A, Alexander AJT, Baillie C, Brennan B, Brown F, Brunker K, Bryden SR, Burness KA, Carmichael S, Cole SJ, Cowton VM, Davies P, Davis C, De Lorenzo G, Donald CL, Dorward M, Dunlop JI, Elliott M, Fares M, da Silva Filipe A, Freitas JR, Furnon W, Gestuveo RJ, Geyer A, Giesel D, Goldfarb DM, Goodman N, Gunson R, Hastie CJ, Herder V, Hughes J, Johnson C, Johnson N, Kohl A, Kerr K, Leech H, Lello LS, Li K, Lieber G, Liu X, Lingala R, Loney C, Mair D, McElwee MJ, McFarlane S, Nichols J, Nomikou K, Orr A, Orton RJ, Palmarini M, Parr YA, Pinto RM, Raggett S, Reid E, Robertson DL, Royle J, Cameron-Ruiz N, Shepherd JG, Smollett K, Stewart DG, Stewart M, Sugrue E, Szemiel AM, Taggart A, Thomson EC, Tong L, Torrie LS, Toth R, Varjak M, Wang S, Wilkinson SG, Wyatt PG, Zusinaite E, Alessi DR, Patel AH, Zaid A, Wilson SJ, Mahalingam S. A plasmid DNA-launched SARS-CoV-2 reverse genetics system and coronavirus toolkit for COVID-19 research. PLoS Biol 2021; 19:e3001091. [PMID: 33630831 PMCID: PMC7906417 DOI: 10.1371/journal.pbio.3001091] [Citation(s) in RCA: 112] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 01/05/2021] [Indexed: 12/30/2022] Open
Abstract
The recent emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the underlying cause of Coronavirus Disease 2019 (COVID-19), has led to a worldwide pandemic causing substantial morbidity, mortality, and economic devastation. In response, many laboratories have redirected attention to SARS-CoV-2, meaning there is an urgent need for tools that can be used in laboratories unaccustomed to working with coronaviruses. Here we report a range of tools for SARS-CoV-2 research. First, we describe a facile single plasmid SARS-CoV-2 reverse genetics system that is simple to genetically manipulate and can be used to rescue infectious virus through transient transfection (without in vitro transcription or additional expression plasmids). The rescue system is accompanied by our panel of SARS-CoV-2 antibodies (against nearly every viral protein), SARS-CoV-2 clinical isolates, and SARS-CoV-2 permissive cell lines, which are all openly available to the scientific community. Using these tools, we demonstrate here that the controversial ORF10 protein is expressed in infected cells. Furthermore, we show that the promising repurposed antiviral activity of apilimod is dependent on TMPRSS2 expression. Altogether, our SARS-CoV-2 toolkit, which can be directly accessed via our website at https://mrcppu-covid.bio/, constitutes a resource with considerable potential to advance COVID-19 vaccine design, drug testing, and discovery science.
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Affiliation(s)
- Suzannah J. Rihn
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Andres Merits
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Siddharth Bakshi
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Matthew L. Turnbull
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Arthur Wickenhagen
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | | | - Carla Baillie
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Benjamin Brennan
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Fiona Brown
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Kirstyn Brunker
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, United Kingdom
| | - Steven R. Bryden
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Kerry A. Burness
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Stephen Carmichael
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Sarah J. Cole
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Vanessa M. Cowton
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Paul Davies
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Chris Davis
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Giuditta De Lorenzo
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Claire L. Donald
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Mark Dorward
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - James I. Dunlop
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Matthew Elliott
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Mazigh Fares
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Ana da Silva Filipe
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Joseph R. Freitas
- Emerging Viruses, Inflammation and Therapeutics Group, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
| | - Wilhelm Furnon
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Rommel J. Gestuveo
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
- Division of Biological Sciences, College of Arts and Sciences, University of the Philippines Visayas, Miagao, Iloilo, Philippines
| | - Anna Geyer
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Daniel Giesel
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Daniel M. Goldfarb
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Nicola Goodman
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Rory Gunson
- West of Scotland Specialist Virology Centre, Glasgow, United Kingdom
| | - C. James Hastie
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Vanessa Herder
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Joseph Hughes
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Clare Johnson
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Natasha Johnson
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Alain Kohl
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Karen Kerr
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Hannah Leech
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | | | - Kathy Li
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Gauthier Lieber
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Xiang Liu
- Emerging Viruses, Inflammation and Therapeutics Group, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
| | - Rajendra Lingala
- Indian Immunologicals Ltd (IIL), Rakshapuram, Gachibowli Post, Hyderabad Telangana, India
| | - Colin Loney
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Daniel Mair
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Marion J. McElwee
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Steven McFarlane
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Jenna Nichols
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Kyriaki Nomikou
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Anne Orr
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Richard J. Orton
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Massimo Palmarini
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Yasmin A. Parr
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Rute Maria Pinto
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Samantha Raggett
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Elaine Reid
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - David L. Robertson
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Jamie Royle
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Natalia Cameron-Ruiz
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - James G. Shepherd
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Katherine Smollett
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Douglas G. Stewart
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Meredith Stewart
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Elena Sugrue
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Agnieszka M. Szemiel
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Aislynn Taggart
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Emma C. Thomson
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Lily Tong
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Leah S. Torrie
- Drug Discovery Unit (DDU), Wellcome Centre for Anti-Infectives Research, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Rachel Toth
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Margus Varjak
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Sainan Wang
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Stuart G. Wilkinson
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Paul G. Wyatt
- Drug Discovery Unit (DDU), Wellcome Centre for Anti-Infectives Research, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Eva Zusinaite
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Dario R. Alessi
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Arvind H. Patel
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Ali Zaid
- Emerging Viruses, Inflammation and Therapeutics Group, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
- School of Medical Sciences, Griffith University, Gold Coast, Queensland, Australia
| | - Sam J. Wilson
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Suresh Mahalingam
- Emerging Viruses, Inflammation and Therapeutics Group, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
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6
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Lalayiannis AD, Fewtrell M, Biassoni L, Silva S, Goodman N, Shroff R, Crabtree NJ. Studying bone mineral density in young people: The complexity of choosing a pQCT reference database. Bone 2021; 143:115713. [PMID: 33122089 DOI: 10.1016/j.bone.2020.115713] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 10/07/2020] [Accepted: 10/24/2020] [Indexed: 01/28/2023]
Abstract
BACKGROUND Many chronic illnesses affect bone health, and commonly lead to mineralization abnormalities in young people. As cortical and trabecular bone may be differentially affected in certain diseases, an imaging technique that allows for detailed study of the bone structure is required. Peripheral quantitative computed tomography (pQCT) overcomes the limitations of dual energy X-ray absorptiometry (DXA) and is perhaps more widely available for use in research than bone biopsy. However, in contrast to DXA, where there are large reference datasets, this is not the case for pQCT. METHODS Fifty-five children and young adults aged 7 to 30 years had the non-dominant tibia scanned at the 3% & 4% sites for trabecular bone mineral density and the 38% site for cortical bone mineral density and bone mineral content. Image acquisition and analysis was undertaken according to the protocols of two of the largest reference datasets for tibial pQCT. The Z-scores generated were compared to examine the differences between protocols and the differences from the expected median of zero in a healthy population. RESULTS The trabecular bone mineral density Z-scores generated by the two protocols were similar. The same was true for cortical mineral content Z-scores at the 38% site. Cortical bone mineral density was significantly different between protocols and likely affected by differences in the ethnicity of our cohort compared to the reference datasets. Only one reference dataset extended from childhood to young adulthood. Only trabecular bone mineral density, periosteal and endosteal circumference Z-scores from one methodology were not significantly biased when tested for deviation of the median from zero. CONCLUSIONS pQCT is a useful tool for studying trabecular and cortical compartments separately but, there are variations in pQCT scanning protocols, analysis methodology, and a paucity of reference data. Reference datasets may not be generalizable to local study populations, even when analysed using identical analysis protocols.
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Affiliation(s)
- A D Lalayiannis
- UCL Great Ormond Street Hospital Institute of Child Health, London, UK.
| | - M Fewtrell
- UCL Great Ormond Street Hospital Institute of Child Health, London, UK
| | - L Biassoni
- UCL Great Ormond Street Hospital Institute of Child Health, London, UK
| | - S Silva
- UCL Great Ormond Street Hospital Institute of Child Health, London, UK
| | - N Goodman
- UCL Great Ormond Street Hospital Institute of Child Health, London, UK
| | - R Shroff
- UCL Great Ormond Street Hospital Institute of Child Health, London, UK
| | - N J Crabtree
- Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
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7
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Gordon DE, Hiatt J, Bouhaddou M, Rezelj VV, Ulferts S, Braberg H, Jureka AS, Obernier K, Guo JZ, Batra J, Kaake RM, Weckstein AR, Owens TW, Gupta M, Pourmal S, Titus EW, Cakir M, Soucheray M, McGregor M, Cakir Z, Jang G, O'Meara MJ, Tummino TA, Zhang Z, Foussard H, Rojc A, Zhou Y, Kuchenov D, Hüttenhain R, Xu J, Eckhardt M, Swaney DL, Fabius JM, Ummadi M, Tutuncuoglu B, Rathore U, Modak M, Haas P, Haas KM, Naing ZZC, Pulido EH, Shi Y, Barrio-Hernandez I, Memon D, Petsalaki E, Dunham A, Marrero MC, Burke D, Koh C, Vallet T, Silvas JA, Azumaya CM, Billesbølle C, Brilot AF, Campbell MG, Diallo A, Dickinson MS, Diwanji D, Herrera N, Hoppe N, Kratochvil HT, Liu Y, Merz GE, Moritz M, Nguyen HC, Nowotny C, Puchades C, Rizo AN, Schulze-Gahmen U, Smith AM, Sun M, Young ID, Zhao J, Asarnow D, Biel J, Bowen A, Braxton JR, Chen J, Chio CM, Chio US, Deshpande I, Doan L, Faust B, Flores S, Jin M, Kim K, Lam VL, Li F, Li J, Li YL, Li Y, Liu X, Lo M, Lopez KE, Melo AA, Moss FR, Nguyen P, Paulino J, Pawar KI, Peters JK, Pospiech TH, Safari M, Sangwan S, Schaefer K, Thomas PV, Thwin AC, Trenker R, Tse E, Tsui TKM, Wang F, Whitis N, Yu Z, Zhang K, Zhang Y, Zhou F, Saltzberg D, Hodder AJ, Shun-Shion AS, Williams DM, White KM, Rosales R, Kehrer T, Miorin L, Moreno E, Patel AH, Rihn S, Khalid MM, Vallejo-Gracia A, Fozouni P, Simoneau CR, Roth TL, Wu D, Karim MA, Ghoussaini M, Dunham I, Berardi F, Weigang S, Chazal M, Park J, Logue J, McGrath M, Weston S, Haupt R, Hastie CJ, Elliott M, Brown F, Burness KA, Reid E, Dorward M, Johnson C, Wilkinson SG, Geyer A, Giesel DM, Baillie C, Raggett S, Leech H, Toth R, Goodman N, Keough KC, Lind AL, Klesh RJ, Hemphill KR, Carlson-Stevermer J, Oki J, Holden K, Maures T, Pollard KS, Sali A, Agard DA, Cheng Y, Fraser JS, Frost A, Jura N, Kortemme T, Manglik A, Southworth DR, Stroud RM, Alessi DR, Davies P, Frieman MB, Ideker T, Abate C, Jouvenet N, Kochs G, Shoichet B, Ott M, Palmarini M, Shokat KM, García-Sastre A, Rassen JA, Grosse R, Rosenberg OS, Verba KA, Basler CF, Vignuzzi M, Peden AA, Beltrao P, Krogan NJ. Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms. Science 2020; 370:eabe9403. [PMID: 33060197 PMCID: PMC7808408 DOI: 10.1126/science.abe9403] [Citation(s) in RCA: 427] [Impact Index Per Article: 106.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 10/12/2020] [Indexed: 01/18/2023]
Abstract
The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 is closely related to the more lethal but less transmissible coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction and viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on coronavirus proliferation, including Tom70, a mitochondrial chaperone protein that interacts with both SARS-CoV-1 and SARS-CoV-2 ORF9b, an interaction we structurally characterized using cryo-electron microscopy. Combining genetically validated host factors with both COVID-19 patient genetic data and medical billing records identified molecular mechanisms and potential drug treatments that merit further molecular and clinical study.
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Affiliation(s)
- David E Gordon
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Joseph Hiatt
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Medical Scientist Training Program, University of California, San Francisco, CA 94143, USA
- Department of Microbiology and Immunology, University of California, San Francisco, CA 94143, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Mehdi Bouhaddou
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Veronica V Rezelj
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724, Paris, cedex 15, France
| | - Svenja Ulferts
- Institute for Clinical and Experimental Pharmacology and Toxicology I, University of Freiburg, 79104 Freiburg, Germany
| | - Hannes Braberg
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Alexander S Jureka
- Center for Microbial Pathogenesis, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30303, USA
| | - Kirsten Obernier
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jeffrey Z Guo
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jyoti Batra
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Robyn M Kaake
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | | | - Tristan W Owens
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Meghna Gupta
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Sergei Pourmal
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Erron W Titus
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Merve Cakir
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Margaret Soucheray
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Michael McGregor
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Zeynep Cakir
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Gwendolyn Jang
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Matthew J O'Meara
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Tia A Tummino
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Ziyang Zhang
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- Howard Hughes Medical Institute, San Francisco, CA 94158, USA
| | - Helene Foussard
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Ajda Rojc
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Yuan Zhou
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Dmitry Kuchenov
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Ruth Hüttenhain
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jiewei Xu
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Manon Eckhardt
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Danielle L Swaney
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jacqueline M Fabius
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
| | - Manisha Ummadi
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Beril Tutuncuoglu
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Ujjwal Rathore
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Maya Modak
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Paige Haas
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Kelsey M Haas
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Zun Zar Chi Naing
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Ernst H Pulido
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Ying Shi
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- Howard Hughes Medical Institute, San Francisco, CA 94158, USA
| | - Inigo Barrio-Hernandez
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Danish Memon
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Eirini Petsalaki
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Alistair Dunham
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Miguel Correa Marrero
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - David Burke
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Cassandra Koh
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724, Paris, cedex 15, France
| | - Thomas Vallet
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724, Paris, cedex 15, France
| | - Jesus A Silvas
- Center for Microbial Pathogenesis, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30303, USA
| | - Caleigh M Azumaya
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Christian Billesbølle
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Axel F Brilot
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Melody G Campbell
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Amy Diallo
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Miles Sasha Dickinson
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Devan Diwanji
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Nadia Herrera
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Nick Hoppe
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Huong T Kratochvil
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Yanxin Liu
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Gregory E Merz
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Michelle Moritz
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Henry C Nguyen
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Carlos Nowotny
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Cristina Puchades
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Alexandrea N Rizo
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Ursula Schulze-Gahmen
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Amber M Smith
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Ming Sun
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Beam Therapeutics, Cambridge, MA 02139, USA
| | - Iris D Young
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Jianhua Zhao
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Daniel Asarnow
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Justin Biel
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Alisa Bowen
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Julian R Braxton
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Jen Chen
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Cynthia M Chio
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Un Seng Chio
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Ishan Deshpande
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Loan Doan
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Bryan Faust
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Sebastian Flores
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Mingliang Jin
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Kate Kim
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Victor L Lam
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Fei Li
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Junrui Li
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Yen-Li Li
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Yang Li
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Xi Liu
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Megan Lo
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Kyle E Lopez
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Arthur A Melo
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Frank R Moss
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Phuong Nguyen
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Joana Paulino
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Komal Ishwar Pawar
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Jessica K Peters
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Thomas H Pospiech
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Maliheh Safari
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Smriti Sangwan
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Kaitlin Schaefer
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Paul V Thomas
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Aye C Thwin
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Raphael Trenker
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Eric Tse
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Tsz Kin Martin Tsui
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Feng Wang
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Natalie Whitis
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Zanlin Yu
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Kaihua Zhang
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Yang Zhang
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Fengbo Zhou
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
| | - Daniel Saltzberg
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA
| | - Anthony J Hodder
- Department of Biomedical Science, Centre for Membrane Interactions and Dynamics, University of Sheffield, Firth Court, Sheffield S10 2TN, UK
| | - Amber S Shun-Shion
- Department of Biomedical Science, Centre for Membrane Interactions and Dynamics, University of Sheffield, Firth Court, Sheffield S10 2TN, UK
| | - Daniel M Williams
- Department of Biomedical Science, Centre for Membrane Interactions and Dynamics, University of Sheffield, Firth Court, Sheffield S10 2TN, UK
| | - Kris M White
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Romel Rosales
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Thomas Kehrer
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lisa Miorin
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Elena Moreno
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Arvind H Patel
- MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, Scotland, UK
| | - Suzannah Rihn
- MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, Scotland, UK
| | - Mir M Khalid
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | | | - Parinaz Fozouni
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Medical Scientist Training Program, University of California, San Francisco, CA 94143, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Camille R Simoneau
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Theodore L Roth
- Medical Scientist Training Program, University of California, San Francisco, CA 94143, USA
- Department of Microbiology and Immunology, University of California, San Francisco, CA 94143, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - David Wu
- Medical Scientist Training Program, University of California, San Francisco, CA 94143, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Mohd Anisul Karim
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Maya Ghoussaini
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Ian Dunham
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Francesco Berardi
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari 'ALDO MORO', Via Orabona, 4 70125, Bari, Italy
| | - Sebastian Weigang
- Institute of Virology, Medical Center-University of Freiburg, 79104 Freiburg, Germany
| | - Maxime Chazal
- Département de Virologie, CNRS UMR 3569, Institut Pasteur, Paris 75015, France
| | - Jisoo Park
- Department of Medicine, University of California, San Diego, CA 92093, USA
| | - James Logue
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Marisa McGrath
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Stuart Weston
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Robert Haupt
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - C James Hastie
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Matthew Elliott
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Fiona Brown
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Kerry A Burness
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Elaine Reid
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Mark Dorward
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Clare Johnson
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Stuart G Wilkinson
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Anna Geyer
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Daniel M Giesel
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Carla Baillie
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Samantha Raggett
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Hannah Leech
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Rachel Toth
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Nicola Goodman
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | | | - Abigail L Lind
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | | | - Kafi R Hemphill
- Department of Neurology, University of California, San Francisco, CA 94143, USA
| | | | - Jennifer Oki
- Synthego Corporation, Redwood City, CA 94063, USA
| | - Kevin Holden
- Synthego Corporation, Redwood City, CA 94063, USA
| | | | - Katherine S Pollard
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA 94158, USA
- Chan-Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Andrej Sali
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA
| | - David A Agard
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
| | - Yifan Cheng
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Howard Hughes Medical Institute, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
| | - James S Fraser
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA
| | - Adam Frost
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
| | - Natalia Jura
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Cardiovascular Research Institute, University of California, San Francisco, CA 94158, USA
| | - Tanja Kortemme
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA
- The University of California, Berkeley-University of California, San Francisco Graduate Program in Bioengineering, University of California, San Francisco, CA 94158, USA
| | - Aashish Manglik
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Daniel R Southworth
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
| | - Robert M Stroud
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
| | - Dario R Alessi
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Paul Davies
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK
| | - Matthew B Frieman
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Trey Ideker
- Department of Medicine, University of California, San Diego, CA 92093, USA
- Department to Bioengineering, University of California, San Diego, CA 92093, USA
| | - Carmen Abate
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari 'ALDO MORO', Via Orabona, 4 70125, Bari, Italy
| | - Nolwenn Jouvenet
- Institute of Virology, Medical Center-University of Freiburg, 79104 Freiburg, Germany
- Département de Virologie, CNRS UMR 3569, Institut Pasteur, Paris 75015, France
| | - Georg Kochs
- Institute of Virology, Medical Center-University of Freiburg, 79104 Freiburg, Germany
| | - Brian Shoichet
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Melanie Ott
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Medicine, University of California, San Francisco, CA 94143, USA
| | - Massimo Palmarini
- MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, Scotland, UK
| | - Kevan M Shokat
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- Howard Hughes Medical Institute, San Francisco, CA 94158, USA
| | - Adolfo García-Sastre
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Robert Grosse
- Institute for Clinical and Experimental Pharmacology and Toxicology I, University of Freiburg, 79104 Freiburg, Germany.
- Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, 79104 Freiburg, Germany
| | - Oren S Rosenberg
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA.
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Chan-Zuckerberg Biohub, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
- Department of Medicine, University of California, San Francisco, CA 94143, USA
| | - Kliment A Verba
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA.
- QBI, University of California, San Francisco, CA 94158, USA
- QBI Coronavirus Research Group Structural Biology Consortium, University of California, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Christopher F Basler
- Center for Microbial Pathogenesis, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30303, USA.
| | - Marco Vignuzzi
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724, Paris, cedex 15, France.
| | - Andrew A Peden
- Department of Biomedical Science, Centre for Membrane Interactions and Dynamics, University of Sheffield, Firth Court, Sheffield S10 2TN, UK.
| | - Pedro Beltrao
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.
| | - Nevan J Krogan
- Quantitative Biosciences Institute (QBI) COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA.
- QBI, University of California, San Francisco, CA 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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8
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Bozic M, van den Bekerom L, Milne BA, Goodman N, Roberston L, Prescott AR, Macartney TJ, Dawe N, McEwan DG. A conserved ATG2-GABARAP family interaction is critical for phagophore formation. EMBO Rep 2020; 21:e48412. [PMID: 32009292 PMCID: PMC7054675 DOI: 10.15252/embr.201948412] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 12/16/2019] [Accepted: 12/23/2019] [Indexed: 01/08/2023] Open
Abstract
The intracellular trafficking pathway, macroautophagy, is a recycling and disposal service that can be upregulated during periods of stress to maintain cellular homeostasis. An essential phase is the elongation and closure of the phagophore to seal and isolate unwanted cargo prior to lysosomal degradation. Human ATG2A and ATG2B proteins, through their interaction with WIPI proteins, are thought to be key players during phagophore elongation and closure, but little mechanistic detail is known about their function. We have identified a highly conserved motif driving the interaction between human ATG2 and GABARAP proteins that is in close proximity to the ATG2‐WIPI4 interaction site. We show that the ATG2A‐GABARAP interaction mutants are unable to form and close phagophores resulting in blocked autophagy, similar to ATG2A/ATG2B double‐knockout cells. In contrast, the ATG2A‐WIPI4 interaction mutant fully restored phagophore formation and autophagy flux, similar to wild‐type ATG2A. Taken together, we provide new mechanistic insights into the requirements for ATG2 function at the phagophore and suggest that an ATG2‐GABARAP/GABARAP‐L1 interaction is essential for phagophore formation, whereas ATG2‐WIPI4 interaction is dispensable.
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Affiliation(s)
- Mihaela Bozic
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee, UK.,Edinburgh Cancer Research UK Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Luuk van den Bekerom
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee, UK.,MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, UK
| | - Beth A Milne
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee, UK
| | - Nicola Goodman
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee, UK.,MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, UK
| | - Lisa Roberston
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee, UK
| | - Alan R Prescott
- Dundee Imaging Facility, School of Life Sciences, University of Dundee, Dundee, UK
| | - Thomas J Macartney
- MRC Protein Phosphorylation and Ubiquitylation Unit, School of Life Sciences, University of Dundee, Dundee, UK
| | - Nina Dawe
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee, UK
| | - David G McEwan
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee, UK.,Cancer Research UK Beatson Institute, Glasgow, UK
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9
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DeMichele A, Shih NNC, Koehler M, Huang Bartlett C, Jiang Y, Harwick J, Huang D, Zheng X, Clark AS, Colameco C, Feldman MD, Gallagher M, Goodman N, O'Dwyer P, Rejto P. Abstract P4-13-04: Upregulation of cell cycle pathway genes without loss of RB1 contributes to acquired resistance to single-agent treatment with palbociclib in breast cancer. Cancer Res 2016. [DOI: 10.1158/1538-7445.sabcs15-p4-13-04] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: The oral cdk4/6 inhibitor, Palbociclib (Palbo), has been shown to prolong progression-free survival when combined with anti-estrogen therapy and have single-agent activity in metastatic breast cancer (MBC). Progressive disease (PD) on therapy does occur, however, and little is known about resistance mechanisms. Preclinical data have suggested that cell cycle gene expression changes are a potential mechanism of resistance. We performed comprehensive genomic analyses on serial tumor samples from an exceptional responder to single-agent Palbo to determine whether such changes occur in vivo.
Methods: Serial biopsies were obtained from a 67 year old patient with MBC treated on a phase II trial of single-agent Palbo at the University of Pennsylvania. Tissue was obtained from the primary lesion (1999, Stage 3, ER-/PR+/Her2+) and first recurrence (2005, contralateral breast, bone, lung; ER+/PR-/Her2+, treated with Herceptin/letrozole). At PD (2010), pt received single-agent P, 50 mg daily for 21 days each 28-day cycle, with PR for 33 months. A sample from metastatic skin lesion at PD on P (2013) was obtained. Next generation targeted sequencing was performed at Foundation Medicine using the Heme Panel. RNA was profiled using a 784-gene custom Nanostring array including cell cycle genes and ER pathway genes. Determination of pathway enrichment was performed using GSEA and the statistical significance of network neighborhood over-representation was calculated using cumulative hypergeometric distribution.
Results: There was no genetic evidence suggesting loss of RB1, or alterations in p16, cyclin D1, cdk4, PIK3CA or ESR1, and the genomic profile did not change between the primary and recurrent tissue samples. As expected, amplification of ERRB2 was present in all samples. In contrast, expression of cell cycle-regulated genes (PLK1, TOP2A, CDK1, BUB1, CDC20, CCNA2, CCNE2, CCNB1 BIRC5) increased more than two-fold at PD on Palbo compared to pre-Palbo, along with evidence of activation of the FOXM1 network.
Conclusion: Gene expression changes associated with cell cycle activation and FOXM1 activation may lead to acquired resistance to Palbociclib, despite wild-type RB1. These data demonstrate the importance of pre-/post-treatment biopsies and the feasibility of high-level genomic assessment in archival tissues to elucidate resistance mechanisms of novel therapies.
Citation Format: DeMichele A, Shih NNC, Koehler M, Huang Bartlett C, Jiang Y, Harwick J, Huang D, Zheng X, Clark AS, Colameco C, Feldman MD, Gallagher M, Goodman N, O'Dwyer P, Rejto P. Upregulation of cell cycle pathway genes without loss of RB1 contributes to acquired resistance to single-agent treatment with palbociclib in breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-13-04.
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Affiliation(s)
- A DeMichele
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - NNC Shih
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - M Koehler
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - C Huang Bartlett
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - Y Jiang
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - J Harwick
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - D Huang
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - X Zheng
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - AS Clark
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - C Colameco
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - MD Feldman
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - M Gallagher
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - N Goodman
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - P O'Dwyer
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
| | - P Rejto
- University of Pennsylvania School of Medicine, Philadelphia, PA; Abramson Cancer Center, Philadelphia, PA; Pfizer Oncology, NY, NY; Pfizer Oncology Research, San Diego, CA
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10
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Soucier-Ernst D, Colameco C, Troxel AB, Clark C, Shih N, Maxwell KN, Morrissette J, Lieberman D, Feldman M, Goodman N, Bradbury A, Clark A, Domchek S, Fox K, Glick J, Matro J, Nathanson K, Chodosh L, DeMichele A. Abstract P6-07-05: Mutational spectrum and tumor response in metastatic breast cancer. Cancer Res 2016. [DOI: 10.1158/1538-7445.sabcs15-p6-07-05] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: While several comprehensive genomic sequencing tests are clinically available for breast cancer(BC), little is known about the spectrum of findings reported in the general population and clinical utility of findings for patients(pts). Here we report tumor sequencing from the METAMORPH study, a comprehensive genomic testing approach in pts with metastatic(met) BC.
Methods: Pts with either known or suspected BC mets consented to and clinically underwent concurrent diagnostic and research tumor biopsies(bx). FFPE specimens were profiled via Illumina TruSeq Cancer Panel next generation sequencing platform covering 212 amplicons in 47 cancer genes. Pathology, treatment and outcome data were prospectively collected and tracked. Aside from Her2-directed treatment, therapy was not mutation (mut)-matched.
Results: 64 pts enrolled between 11/2013 – 05/2015. Of these, 48 had bx successfully sequenced (75%). Of those without sequencing, 5 had negative/insufficient tissue, 2 had insufficient DNA, remainder no bx/pending. Median age of those sequenced was 56 (range 31-78); 81% Caucasian, 17% African American. 25% (12 pts) presented with de novo stage IV disease. Of those with recurrence (n=36), 83% had prior adjuvant chemotherapy; 81% hormone receptor positive(HR+) had prior endocrine therapy. Median # prior lines of therapy for met disease was 2 (IQR 0 – 8). Tumor characteristics, including mut analyses, are shown in Table 1. # muts did not differ significantly by subtype(p=0.22). Frequency of TP53 and PIK3CA hotspot muts was nearly identical to TCGA. Median # muts was 1 for pts with both de novo mets and recurrence(p=0.79). # of muts was not associated with time to recurrence(p=0.80). Excluding pts found to have TP53 mut only or ERBB2 alterations in known Her2+ disease, 42% of pts were identified as having at least one potentially actionable alteration (PIK3CA mut, AKT1 mut or EGFR amplification). Median time to treatment failure(TTF) on subsequent therapy was 4.1 months for overall group, and 4.1, 6.2, and 1.6 months for HR+/Her2-, any Her2+ and TN, respectively, adjusted for line of therapy(p=0.03). After adjustment for # lines of prior met therapy, TTF was 4.7 vs. 4.1 months for pts with any mut vs. none(p=0.89); 5.7 vs 4.1 months for PIK3CA+ vs. not (p=0.94); 3.3 vs. 6.5 months for TP53+ vs. not (p=0.03).
Conclusion: Pts with met BC have frequent and potentially actionable muts.While overall # of muts did not affect response, tumors with TP53 muts had shorter response to subsequent therapy in this cohort. Additional data are needed to determine the clinical utility of mut testing in met BC, for both standard and mut-matched therapy.
Total (n=48)HR+/Her2- (n=28)Any HER2+ (n=7)TN (n=13)Receptor concordant with primary 100%78%77%# Mutations Median (Range)1 (0-4)1 (0-3)1 (1-2)1 (0-4)014 (29%)10 (36 %)04 (31%)118 (38%)11 (39%)4 (57%)3 (23%)213 (27%)5 (18%)3 (43%)5 (38%)3+3 (6%)2 (7%)01 (8%)Prevalent Mutations (>20%)TP53 (38%), PIK3CA (35%)PIK3CA (50%), TP53 (25%)TP53 (60%), ERBB2amp (86%)TP53 (62%),PIK3CA (23%)Other Alterations (#)ATM (1), KIT (1), PDGFRA (1), PTEN(1), RB1 (1), SMAD4 (1), SMO (1), STK11 (1)AKT1 (1), ATM VUS (1), ERBB2 (1), PTEN (1), SMAD4 VUS (1), SMO VUS (1)ERBB2 (1), STK11(1)EGFR amp (2), KIT amp (1),PDGFRA amp (1), RB1 VUS (1)
Citation Format: Soucier-Ernst D, Colameco C, Troxel AB, Clark C, Shih N, Maxwell KN, Morrissette J, Lieberman D, Feldman M, Goodman N, Bradbury A, Clark A, Domchek S, Fox K, Glick J, Matro J, Nathanson K, Chodosh L, DeMichele A. Mutational spectrum and tumor response in metastatic breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-07-05.
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Affiliation(s)
| | - C Colameco
- University of Pennsylvania, Philadelphia, PA
| | - AB Troxel
- University of Pennsylvania, Philadelphia, PA
| | - C Clark
- University of Pennsylvania, Philadelphia, PA
| | - N Shih
- University of Pennsylvania, Philadelphia, PA
| | - KN Maxwell
- University of Pennsylvania, Philadelphia, PA
| | | | - D Lieberman
- University of Pennsylvania, Philadelphia, PA
| | - M Feldman
- University of Pennsylvania, Philadelphia, PA
| | - N Goodman
- University of Pennsylvania, Philadelphia, PA
| | - A Bradbury
- University of Pennsylvania, Philadelphia, PA
| | - A Clark
- University of Pennsylvania, Philadelphia, PA
| | - S Domchek
- University of Pennsylvania, Philadelphia, PA
| | - K Fox
- University of Pennsylvania, Philadelphia, PA
| | - J Glick
- University of Pennsylvania, Philadelphia, PA
| | - J Matro
- University of Pennsylvania, Philadelphia, PA
| | - K Nathanson
- University of Pennsylvania, Philadelphia, PA
| | - L Chodosh
- University of Pennsylvania, Philadelphia, PA
| | - A DeMichele
- University of Pennsylvania, Philadelphia, PA
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Goodman N. Would you post a comment if youweren'tinterested? Anaesthesia 2015; 71:116. [DOI: 10.1111/anae.13326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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12
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Goodman N. Diagnosis by subterfuge. Assoc Med J 2015. [DOI: 10.1136/bmj.h1813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Beale DJ, Tjandraatmadja G, Toifl M, Goodman N. Headspace gas chromatography with flame ionization detection (HS-GC-FID) for the determination of dissolved methane in wastewater. Water Sci Technol 2014; 70:901-908. [PMID: 25225939 DOI: 10.2166/wst.2014.298] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
There is currently a need for a simple, accurate and reproducible method that quantifies the amount of dissolved methane in wastewater in order to realize the potential methane that can be recovered and account for any emissions. This paper presents such a method, using gas chromatography with flame ionization detection fitted with a GS-Gas PRO column coupled with a headspace auto sampler. A practical limit of detection for methane of 0.9 mg L(-1), with a retention time of 1.24 min, was obtained. It was found that the reproducibility and accuracy of the method increased significantly when samples were collected using an in-house constructed bailer sampling device and with the addition of 100 μL hydrochloric acid (HCl) and 25% sodium chloride (NaCl) and sonication for 30 min prior to analysis. Analysis of wastewater samples and wastewater sludge collected from a treatment facility were observed to range from 12.51 to 15.79 mg L(-1) (relative standard deviation (RSD) 8.1%) and 17.56 to 18.67 mg L(-1) (RSD 3.4%) respectively. The performance of this method was validated by repeatedly measuring a mid-level standard (n=8; 10 mg L(-1)), with an observed RSD of 4.6%.
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Affiliation(s)
- D J Beale
- Land and Water, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PO Box 56, Highett VIC 3190, Australia E-mail:
| | - G Tjandraatmadja
- Land and Water, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PO Box 56, Highett VIC 3190, Australia E-mail:
| | - M Toifl
- Land and Water, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PO Box 56, Highett VIC 3190, Australia E-mail:
| | - N Goodman
- Land and Water, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PO Box 56, Highett VIC 3190, Australia E-mail:
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Keosaian J, Dresner D, Cerrada C, Kwong L, Goodman N, Tam M, Godersky M, Sherman K, Weinberg J, Boah A, Saper R. P02.127. Recruitment strategies for community-based yoga research in a predominant minority population. BMC Complement Altern Med 2012. [PMCID: PMC3373598 DOI: 10.1186/1472-6882-12-s1-p183] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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15
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Mikhail I, Austin E, Buckman S, Lee C, Goodman N, White J. P03.14. Cancer complementary and alternative medicine research among NCI’s cancer centers program and the integrative medicine programs: an inventory. Altern Ther Health Med 2012. [PMCID: PMC3373353 DOI: 10.1186/1472-6882-12-s1-p267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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16
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van Duijn E, Groves M, Craufurd D, Anderson K, Guttman M, Wexler E, Perlman S, Rosenblatt A, van Kammen DP, Giuliano J, Burgunder JM, Goodman N, Goodman L. J13 Prescription usage for treatment of irritability, perseverative behaviors, and chorea in huntington's disease. J Neurol Psychiatry 2010. [DOI: 10.1136/jnnp.2010.222661.13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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17
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Frank M, Kenney A, Goodman N, Tenenbaum J, Torralba A, Oliva A. Predicting object and scene descriptions with an information-theoretic model of pragmatics. J Vis 2010. [DOI: 10.1167/10.7.1241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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18
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Flamez D, Roland I, Berton A, Kutlu B, Dufrane D, Beckers MC, De Waele E, Rooman I, Bouwens L, Clark A, Lonneux M, Jamar JF, Goldman S, Maréchal D, Goodman N, Gianello P, Van Huffel C, Salmon I, Eizirik DL. A genomic-based approach identifies FXYD domain containing ion transport regulator 2 (FXYD2)gammaa as a pancreatic beta cell-specific biomarker. Diabetologia 2010; 53:1372-83. [PMID: 20379810 DOI: 10.1007/s00125-010-1714-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2009] [Accepted: 01/13/2010] [Indexed: 01/09/2023]
Abstract
AIMS/HYPOTHESIS Non-invasive imaging of the pancreatic beta cell mass (BCM) requires the identification of novel and specific beta cell biomarkers. We have developed a systems biology approach to the identification of promising beta cell markers. METHODS We followed a functional genomics strategy based on massive parallel signal sequencing (MPSS) and microarray data obtained in human islets, purified primary rat beta cells, non-beta cells and INS-1E cells to identify promising beta cell markers. Candidate biomarkers were validated and screened using established human and macaque (Macacus cynomolgus) tissue microarrays. RESULTS After a series of filtering steps, 12 beta cell-specific membrane proteins were identified. For four of the proteins we selected or produced antibodies targeting specifically the human proteins and their splice variants; all four candidates were confirmed as islet-specific in human pancreas. Two splice variants of FXYD domain containing ion transport regulator 2 (FXYD2), a regulating subunit of the Na(+)-K(+)-ATPase, were identified as preferentially present in human pancreatic islets. The presence of FXYD2gammaa was restricted to pancreatic islets and selectively detected in pancreatic beta cells. Analysis of human fetal pancreas samples showed the presence of FXYD2gammaa at an early stage (15 weeks). Histological examination of pancreatic sections from individuals with type 1 diabetes or sections from pancreases of streptozotocin-treated Macacus cynomolgus monkeys indicated a close correlation between loss of FXYD2gammaa and loss of insulin-positive cells. CONCLUSIONS/INTERPRETATION We propose human FXYD2gammaa as a novel beta cell-specific biomarker.
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Affiliation(s)
- D Flamez
- Laboratory of Experimental Medicine, Université Libre de Bruxelles, Route de Lennik 808, 1070, Brussels, Belgium.
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19
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Goodman N, Morgan M, Nikander K, Hinch S, Coughlin S. Evaluation of patient-reported outcomes and quality of life with the I-neb AAD system in patients with chronic obstructive pulmonary disease. J Aerosol Med Pulm Drug Deliv 2010; 23 Suppl 1:S61-70. [PMID: 20373911 PMCID: PMC3116632 DOI: 10.1089/jamp.2009.0767] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND The I-neb Adaptive Aerosol Delivery (AAD) System is a novel portable mesh nebulizer that provides patient feedback regarding adherence to prescribed treatment and compliance with the correct use of the device. METHODS This multicenter study was composed of 98 patients aged 53-80 years with Chronic Obstructive Pulmonary Disease (COPD). The primary variables were ease of use and satisfaction, which were assessed after 3 months of use of the I-neb AAD System (assessed at visit 2) and after 3 months of use of the patient's previous nebulizer system (assessed at visit 1) using matched questions from pre- and poststudy questionnaires. Quality of life was also assessed at visits 1 and 2 using the validated Chronic Respiratory Questionnaire (CRQ), which consists of dyspnea, emotional function, fatigue, and mastery domains. Differences in the distribution of responses between the pre- and poststudy ease of use and satisfaction questions were analyzed using the Marginal Homogeneity test. Differences in mean CRQ scores between the pre- and poststudy assessments were analyzed using the Wilcoxon Signed-Rank test. RESULTS Patient responses on the ease of use and satisfaction questions significantly (p < or = 0.001) favored the I-neb AAD System compared with the patient's previous nebulizer system. In addition, significant (p < or = 0.015) improvements in the CRQ dimensions of dyspnea and fatigue were reported with the I-neb AAD System compared with the patients' previous nebulizer systems. CONCLUSIONS The results from this study demonstrated that patients were more satisfied with the I-neb AAD System and found it easier to use than their previous nebulizer systems. In addition, the I-neb AAD System significantly improved dyspnea and fatigue compared with the patients' previous nebulizer systems, which may reflect improved adherence or more correct use of the nebulizer system with the I-neb AAD System.
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Lejeune J, Taeter C, Duquenne V, Goodman N. P01-101 - Unique: assessing the efficacy of quetiapine fumarate augmentation of SSRI or SNRI treatment in SSRI- or SNRI-resistant major depressive disorder. Eur Psychiatry 2010. [DOI: 10.1016/s0924-9338(10)70217-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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21
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Kutlu B, Kayali AG, Jung S, Parnaud G, Baxter D, Glusman G, Goodman N, Behie LA, Hayek A, Hood L. Meta-analysis of gene expression in human pancreatic islets after in vitro expansion. Physiol Genomics 2009; 39:72-81. [PMID: 19622797 DOI: 10.1152/physiolgenomics.00063.2009] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Pancreatic islet transplantation as a potential cure for type 1 diabetes (T1D) cannot be scaled up due to a scarcity of human pancreas donors. In vitro expansion of beta-cells from mature human pancreatic islets provides an alternative source of insulin-producing cells. The exact nature of the expanded cells produced by diverse expansion protocols and their potential for differentiation into functional beta-cells remain elusive. We performed a large-scale meta-analysis of gene expression in human pancreatic islet cells, which were processed using three different previously described protocols for expansion and for which redifferentiation was attempted. All three expansion protocols induced dramatic changes in the expression profiles of pancreatic islets; many of these changes are shared among the three protocols. Attempts at redifferentiation of expanded cells induce a limited number of gene expression changes. Nevertheless, these fail to restore a pancreatic islet-like gene expression pattern. Comparison with a collection of public microarray datasets confirmed that expanded cells are highly comparable to mesenchymal stem cells. Genes induced in expanded cells are also enriched for targets of transcription factors important for pluripotency induction. The present data increase our understanding of the active pathways in expanded and redifferentiated islets. Knowledge of the mesenchymal stem cell potential may help development of drug therapeutics to restore beta-cell mass in T1D patients.
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Affiliation(s)
- B Kutlu
- Institute for Systems Biology, Seattle, Washington, USA.
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Fritz R, Goodman N, Duquenne V, Taeter C. Results of the ALEGRIA study in Luxembourg. An epidemiological, observational study to describe symptom impact and control in patients with GERD and an evaluation of the GERD Impact Scale. Bull Soc Sci Med Grand Duche Luxemb 2009:141-152. [PMID: 19999624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
BACKGROUND AND STUDY AIMS The aim of this observational study was to perform the first epidemiology study in a primary care patient population with GERD in the Grand Duchy of Luxembourg and to evaluate the added value of the GERD Impact Scale (GIS) patient questionnaire. PATIENTS AND METHODS 152 Patients with symptoms of GERD from 20 study centers were included. At visit 1, demographic data including lifestyle factors and the patients' symptoms were recorded. GERD symptoms and their severity, treatment changes and the GIS were all assessed at baseline (visit 1), visit 2 (4-6 weeks) and visit 3 (8-14 weeks). Analyses were performed on an intent-to-treat basis. RESULTS 142 patients were included in the analysis, which comprised 50% men and 50% women with a mean BMI of 27 kg/m2. Documented lifestyle factors included consumption of caffeine-containing beverages (87% of patients), stress (62%) and alcohol consumption (53%); 44% of patients were smokers or ex-smokers. The median duration of GERD was 2.0 years. Upon inclusion, 46% were receiving, or had received, proton pump inhibitors (PPIs), antacids (44%), H2-receptor antagonists (21%) or no treatment (21%). PPIs were prescribed at the first visit in the majority of cases (94%) with 75% of patients being prescribed esomeprazole with a median daily dose of 40 mg. The GIS score correlated well with the clinician's judgment of symptom severity and was reported to help determine the appropriate treatment and evaluate the patient's response in approximately 80% of patients. CONCLUSIONS In this, the first epidemiological study on GERD patients in the Grand Duchy of Luxembourg, data was obtained as planned. The novel patient questionnaire was judged to be helpful by the physician and data shows that the GIS may have an added value over current assessments.
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Affiliation(s)
- R Fritz
- Centre Hospitalier Emile Mayrisch, Luxembourg
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Abstract
Several large retrospective cohort studies demonstrate that pre-eclampsia is common in asthmatics. Whether airway hyperresponsiveness (AHR), a hallmark of asthma, is associated with pre-eclampsia is unknown. We measured AHR, using a methacholine challenge, and atopy in 19 women 3-60 months postpartum following pre-eclamptic or normotensive pregnancies. The geometric mean (95% CI) concentration of methacholine required to produce a >20% fall in the forced expiratory volume in 1 second (PC20 FEV1) was 8.9 (2.2-36) mg/ml in pre-eclamptics versus 72 (32-131) mg/ml in controls (P = 0.01) and 9 (1.9-40) mg/ml in atopic pre-eclamptics without asthma versus 54 (17-174) mg/ml (P = 0.038) in matched controls. Therefore, AHR was increased in women who have had pre-eclampsia. This association and its possible mechanisms warrant further investigation.
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Affiliation(s)
- S Siddiqui
- Institute of Lung Health, University of Leicester, Leicester, UK
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Kamoun M, Israni AK, Joffe MM, Hoy T, Kearns J, Mange KC, Feldman D, Goodman N, Rosas SE, Abrams JD, Brayman KL, Feldman HI. Assessment of differences in HLA-A, -B, and -DRB1 allele mismatches among African-American and non-African-American recipients of deceased kidney transplants. Transplant Proc 2007; 39:55-63. [PMID: 17275474 DOI: 10.1016/j.transproceed.2006.10.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2006] [Indexed: 02/08/2023]
Abstract
Among recipients of deceased donor kidney transplants, African-Americans experience a more rapid rate of kidney allograft loss than non-African-Americans. The purpose of this study was to characterize and quantify the HLA-A, -B, and -DRB1 allele mismatches and amino acid substitutions at antigen recognition sites among African-American and non-African-American recipients of deceased donor kidney transplants matched at the antigen level. In recipients with zero HLA antigen mismatches, the degree of one or two HLA allele mismatches for both racial groups combined was 47%, 29%, and 11% at HLA-DRB1, HLA-B, and HLA-A, respectively. There was a greater number of allele mismatches in African-Americans than non-African-Americans at HLA-A (P < .0001), -B (P = .096), and -DRB1 loci (P < .0001). For both racial groups, the HLA allele mismatches were predominantly at A2 for HLA-A; B35 and B44 for HLA-B; but multiple specificities for HLA-DRB1. The observed amino acid mismatches were concentrated at a few functional positions in the antigen binding site of HLA-A and -B and -DRB1 molecules. Future studies are ongoing to assess the impact of these HLA mismatches on kidney allograft loss.
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Affiliation(s)
- M Kamoun
- Department of Pathology and Laboratory Medicine, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
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Goodman N. Now do it our way. J R Soc Med 2005. [DOI: 10.1258/jrsm.98.11.526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Abstract
BACKGROUND To reduce the risk of sensitization and the elicitation of allergy symptoms, it is important to reduce the level of allergens in the home. It has previously been demonstrated that corona discharge, the process by which ionizers produce ions, can destroy the major house dust mite allergen Der p 1. OBJECTIVE In this paper the denaturing efficacy of an experimental ionizer and two commercially available products are evaluated. METHODS The first test was conducted in an electrically grounded chamber with samples of Der p 1 placed in various positions for 1, 2 and 3 weeks. The second test was conducted in situ in an unoccupied, furnished office room for 1 week. Der p 1 concentration was quantified by two-site monoclonal antibody enzyme-linked immunosorbent assay (ELISA). RESULTS All ionizers in both tests caused significant reductions in allergen concentration (P < 0.05), reaching a maximum of 92% with the experimental ionizer in the chamber after 3 weeks. The percentage reductions observed in situ with the experimental and the larger commercial ionizer were similar, reaching a maximum of 32% at a distance of 4 m away from the experimental ionizer after 1 week of exposure. CONCLUSION With a revised protocol for use, air ionizers may offer a simple, efficient and inexpensive way to reduce allergen levels in the domestic environment.
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Affiliation(s)
- N Goodman
- Bioelectrostatics Research Centre, Department of Electronics and Computer Science, University of Southampton, Southampton, UK.
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Abstract
BACKGROUND Reduction of house dust mite allergens in the domestic environment can play an important part in reducing sensitization and in the amelioration of symptoms in atopic individuals. Chemical and physical methods have been tried with varied levels of success. The present paper presents a novel electrostatic way of destroying Der p 1, the major mite allergen. OBJECTIVE To assess the efficacy of negative Trichel, negative continuous glow, positive pulse and positive continuous glow corona in destroying Der p 1. To determine whether ozone has any effect on the integrity of Der p 1 in the experimental conditions present. METHODS A simple point-to-plane apparatus was used to irradiate samples of Der p 1 for periods of 1, 15, 30, 45, 60, 120, 180, 240 and 300 min. Controls were exposed to the atmosphere with no corona products present for the equivalent time. The effect of the corona by-product ozone was investigated alone by exposing samples of Der p 1 to molecular ozone for 60 min. Der p 1 concentration was quantified by two-site monoclonal antibody ELISA. RESULTS High current negative glow resulted in a 67.37% reduction in Der p 1 concentration after 300 min compared with a 50.5% reduction from a low current Trichel regime. High current positive glow corona gave a reduction of 25.22% while a low current positive pulse corona caused a 13.72% reduction after 300 min. All these reductions were statistically significant (P < 0.05) compared with unexposed controls. Negative corona always gave greater percentage reductions in Der p 1 concentration for each time exposure investigated. The pattern of percentage reduction follows an exponential rise to maximum relationship in respect to time. Samples of Der p 1 were not affected by exposure to molecular ozone. CONCLUSION These data indicate corona products to be a powerful new method of destroying Der p 1 allergen that is not dependent on the presence of the oxidizing corona product ozone.
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Affiliation(s)
- N Goodman
- Bioelectrostatics Research Centre, Department of Electronics and Computer Science, Faculty of Engineering and Applied Science, University of Southampton, Highfield, Southampton, UK.
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Abstract
Bioinformatics is an art and science concerned with the use of computing in biological research areas such as genomics, transcriptomics, proteomics, genetics, and evolution. This review paints a broad picture of bioinformatics, drawing examples from genomic sequencing and microarray analysis. I highlight the role of bioinformatics at multiple points along the path from high-tech data generation to biological discovery.
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Fritsch E, Ellman P, Basseches H, Elmendorf S, Goodman N, Helm F, Rockwell S. The riddle of femininity: the interplay of primary femininity and the castration complex in analytic listening. Int J Psychoanal 2001; 82:1171-83. [PMID: 11802689 DOI: 10.1516/0020757011601479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
This study elucidates the application of an analytic attitude to questions of gender and sexuality. The paper reports on a study group's exploration of the relative heuristic use of two important organising concepts in analytic work with female analysands: primary feminity and the phallic castration complex. A tendency to cling to one position over the other skews analytic listening. Two cases are presented of women struggling to consolidate positive feminine identifications and, to that end, working through conflicting feminine identifications and defences against a resolution of the awareness of gender differences. Analytic listening requires a view of each psychic construction as a layer to be understood in its own right yet as a cloak soon to reveal the next layer--a different construction. The study includes observations on perverse fantasies in women.
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Goodman N. Explanations for the credulous. Br J Gen Pract 2001; 51:952-3. [PMID: 11761224 PMCID: PMC1314167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023] Open
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Abstract
MOTIVATION The methods for analyzing overlap data are distinct from those for analyzing probe data, making integration of the two forms awkward. Conversion of overlap data to probe-like data elements would facilitate comparison and uniform integration of overlap data and probe data using software developed for analysis of STS data. RESULTS We show that overlap data can be effectively converted to probe-like data elements by extracting maximal sets of mutually overlapping clones. We call these sets virtual probes, since each set determines a site in the genome corresponding to the region which is common among the clones of the set. Finding the virtual probes is equivalent to finding the maximal cliques of a graph. We modify a known maximal-clique algorithm such that it finds all virtual probes in a large dataset within minutes. We illustrate the algorithm by converting fingerprint and Alu-PCR overlap data to virtual probes. The virtual probes are then analyzed using double-linkage intersection graphs and structure graphs to show that methods designed for STS data are also applicable to overlap data represented as virtual probes. Next we show that virtual probes can produce a uniform integration of different kinds of mapping data, in particular STS probe data and fingerprint and Alu-PCR overlap data. The integrated virtual probes produce longer double-linkage contigs than STS probes alone, and in conjunction with structure graphs they facilitate the identification and elimination of anomalies. Thus, the virtual-probe technique provides: (i) a new way to examine overlap data; (ii) a basis on which to compare overlap data and probe data using the same systems and standards; and (iii) a unique and useful way to uniformly integrate overlap data with probe data.
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Affiliation(s)
- E Harley
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada M5S 1A4.
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Westcott J, Davis SD, Fleishon H, Gefter WB, Henschke CI, McLoud TC, Pugatch RD, Sostman HD, Tocino I, White CS, Yankelevitz D, Bode FR, Goodman N. Rib fractures. American College of Radiology. ACR Appropriateness Criteria. Radiology 2000; 215 Suppl:637-9. [PMID: 11037476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Affiliation(s)
- J Westcott
- Hospital of St. Raphael, New Haven, Conn., USA
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Abstract
BACKGROUND AND PURPOSE The best management of patients with low-stage, high-grade prostate cancer remains unclear. In an attempt to improve the outcomes of this high-risk group, we have offered those with Gleason > or =7 cancers removable-source high-dose-rate (HDR) brachytherapy in combination with external-beam radiation. PATIENTS AND METHODS We reviewed the clinical histories of 61 consecutive patients with high-grade clinical stage T1-T2 lesions who received the combination radiation therapy between March 1997 and November 1998. The average Gleason score was 7.5. The HDR brachytherapy was given in three sessions with removable-source afterloaded (192)Ir to a minimum peripheral dose of 6 Gy. Conformal external-beam radiation in 25 fractions to a dose of 50 Gy was given beginning 1 week later. Patients with prostate volumes >40 cc received a luteinizing hormone-releasing hormone analog before brachytherapy. RESULTS Among the 52 patients available for follow-up (average duration 11.8 months), there has been one death from prostate cancer. After treatment, only one patient had an initial rise in serum prostate specific antigen (PSA) concentration. In addition to the patient who died, there have been three confirmed treatment failures. Toxicity was mild, with only two patients having RTOG grade 3 or 4 effects. Neither of them required surgery. CONCLUSION Although long-term results are not available, available data suggest that HDR brachytherapy plus external-beam radiation is at least as effective as any single therapy for high-risk, low-stage prostate cancer. The toxicity is acceptable.
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Affiliation(s)
- M J Curran
- Department of Urology, Lahey Clinic Medical Center, Burlington, Massachusetts 01805, USA
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Elam CL, Wilson JF, Johnson R, Wiggs JS, Goodman N. A retrospective review of medical school admission files of academically at-risk matriculants. Acad Med 1999; 74:S58-S61. [PMID: 10536594 DOI: 10.1097/00001888-199910000-00040] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Affiliation(s)
- C L Elam
- University of Kentucky College of Medicine, Lexington 40536-0298, USA
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Abstract
MOTIVATION STS-content data for genomic mapping contain numerous errors and anomalies resulting in cross-links among distant regions of the genome. Identification of contigs within the data is an important and difficult problem. RESULTS This paper introduces a graph algorithm which creates a simplified view of STS-content data. The shape of the resulting structure graph provides a quality check - coherent data produce a straight line, while anomalous data produce branches and loops. In the latter case, it is sometimes possible to disentangle the various paths into subsets of the data covering contiguous regions of the genome, i.e. contigs. These straight subgraphs can then be analyzed in standard ways to construct a physical map. A theoretical basis for the method is presented along with examples of its application to current STS data from human genome centers. AVAILABILITY Freely available on request.
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Affiliation(s)
- E Harley
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada M5S 1A4.
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Goodman N, Rozen S, Stein LD. The LabFlow system for workflow management in large scale biology research laboratories. Proc Int Conf Intell Syst Mol Biol 1998; 6:69-77. [PMID: 9783211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
LabFlow is a workflow management system designed for large scale biology research laboratories. It provides a workflow model in which objects flow from task to task under programmatic control. The model supports parallelism, meaning that an object can flow down several paths simultaneously, and sub-workflows which can be invoked subroutine-style from a task. The system allocates tasks to Unix processes to achieve requisite levels of multiprocessing. The system uses the LabBase data management system to store workflow-state and laboratory results. LabFlow provides a Per15 object-oriented framework for defining workflows, and an engine for executing these. The software is freely available.
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Affiliation(s)
- N Goodman
- Jackson Laboratory, Bar Harbor ME, USA.
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Abstract
MOTIVATION Integration of molecular biology databases remains limited in practice despite its practical importance and considerable research effort. The complexity of the problem is such that an experimental approach is mandatory, yet this very complexity makes it hard to design definitive experiments. This dilemma is common in science, and one tried-and-true strategy is to work with model systems. We propose a model system for this problem, namely a database of genes integrating diverse data across organisms, and describe an experiment using this model. RESULTS We attempted to construct a database of human and mouse genes integrating data from GenBank and the human and mouse genome-databases. We discovered numerous errors in these well-respected databases: approximately 15% of genes are apparently missing from the genome-databases; links between the sequence and genome-databases are missing for another 5-10% of the cases; about a third of likely homology links are missing between the genome-databases; 10-20% of entries classified as 'genes' are apparently misclassified. By using a model system, we were able to study the problems caused by anomalous data without having to face all the hard problems of database integration. CONTACT nat@jax.org
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Affiliation(s)
- J Macauley
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA
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Abstract
MOTIVATION The development of laboratory information management systems (LIMSs) for large scale biology research projects can be a challenging problem. Many such projects generate complex datasets via complex procedures that undergo continuous refinement. A key software challenge is to simplify the database-development task so that databases can be built and modified quickly enough to keep pace with changing project-requirements. RESULTS LabBase extends the facilities offered by relational database systems to simplify the task of creating databases for large scale biology research projects. LabBase provides a structural object data model, similar to ACEDB, and adds to this the concepts of Materials, Steps, and States: Materials are objects representing the identifiable things that participate in a laboratory protocol; Steps are objects reporting the results of a laboratory or analytical procedure; and States are objects denoting places in a laboratory protocol. The system provides a data definition language for succinctly defining laboratory databases, and operations for conveniently storing and retrieving data in such databases. The system also provides support for workflow management. LabBase is implemented in Perl5 and provides a natural interface for laboratory application programs written in Perl. AVAILABILITY The software is freely available. Contact the authors. CONTACT nat@jax.org
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Affiliation(s)
- N Goodman
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609-1500, USA, Whitehead Institute for Biomedical Research, Cambridge, MA, USA.
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Lurie N, Straub MJ, Goodman N, Bauer EJ. Incorporating asthma education into a traditional school curriculum. Am J Public Health 1998; 88:822-3. [PMID: 9585757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- N Lurie
- University of Minnesota School of Public Health, Minneapolis, USA
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Abstract
We mapped 75 genes that collectively encode >90% of the proteins found in human ribosomes. Because localization of ribosomal protein genes (rp genes) is complicated by the existence of processed pseudogenes, multiple strategies were devised to identify PCR-detectable sequence-tagged sites (STSs) at introns. In some cases we exploited specific, pre-existing information about the intron/exon structure of a given human rp gene or its homolog in another vertebrate. When such information was unavailable, selection of PCR primer pairs was guided by general insights gleaned from analysis of all mammalian rp genes whose intron/exon structures have been published. For many genes, PCR amplification of introns was facilitated by use of YAC pool DNAs rather than total human genomic DNA as templates. We then assigned the rp gene STSs to individual human chromosomes by typing human-rodent hybrid cell lines. The genes were placed more precisely on the physical map of the human genome by typing of radiation hybrids or screening YAC libraries. Fifty-one previously unmapped rp genes were localized, and 24 previously reported rp gene localizations were confirmed, refined, or corrected. Though functionally related and coordinately expressed, the 75 mapped genes are widely dispersed: Both sex chromosomes and at least 20 of the 22 autosomes carry one or more rp genes. Chromosome 19, known to have a high gene density, contains an unusually large number of rp genes (12). This map provides a foundation for the study of the possible roles of ribosomal protein deficiencies in chromosomal and Mendelian disorders.
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Affiliation(s)
- N Kenmochi
- Howard Hughes Medical Institute, Whitehead Institute and Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA.
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Abstract
Databases for biologists are becoming increasingly important. Some of these can be regarded as 'core' resources, such as the bibliographic databases, whereas others are of greater interest to specialists. As comparative genomics develops, however, even databases limited in their scope (e.g. to a single organism) are of great interest to a wider community.
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Affiliation(s)
- M Ashburner
- Department of Genetics, University of Cambridge, UK.
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Goodman N. Health education: taking it with a pinch of salt. Br J Hosp Med (Lond) 1997; 58:463. [PMID: 9619211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Goodman N, Benesch B, Andrulis D. A tale of two New Jersey cities. N J Med 1997; 94:47-53. [PMID: 9164104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Judging from the social and health measures considered in this article, Newark and Jersey City face similar challenges as other large cities. For Newark, the challenges are more extreme. The high rates of poverty and violence, coupled with a low rate of high school graduation and a large number of single parent households bode ill for the city. The hospitals in Newark and Jersey City have undergone major changes in meeting the needs of their communities. They have adjusted their size, shortened their lengths of stay, and provided more intensive care services and outpatient services. Of special concern for New Jersey's hospitals is the reliance on Medicaid financing. If dramatic changes are made to the Medicaid program, Newark hospitals should be on high alert. Legislatures need to tread carefully in designing policies that address the needs of New Jersey's large cities. The state is undergoing major changes in its health care system. The demise of the all-payer rate setting system, the establishment of the Health Care Subsidy Fund to finance uncompensated care and subsidize insurance for low and middle-income families, modifications to the community rating system for private insurance, and changes to the welfare system that affect eligibility for Medicaid all require legislators to consider the context in which these programs operate.
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Dame JB, Arnot DE, Bourke PF, Chakrabarti D, Christodoulou Z, Coppel RL, Cowman AF, Craig AG, Fischer K, Foster J, Goodman N, Hinterberg K, Holder AA, Holt DC, Kemp DJ, Lanzer M, Lim A, Newbold CI, Ravetch JV, Reddy GR, Rubio J, Schuster SM, Su XZ, Thompson JK, Werner EB. Current status of the Plasmodium falciparum genome project. Mol Biochem Parasitol 1996; 79:1-12. [PMID: 8844667 DOI: 10.1016/0166-6851(96)02641-2] [Citation(s) in RCA: 43] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
The Plasmodium falciparum Genome Project is a collaborative effort by many laboratories that will provide detailed molecular information about the parasite, which may be used for developing practical control measures. Initial goals are to prepare an electronically indexed clone bank containing partially sequenced clones representing up to 80% of the parasite's genes and to prepare an ordered set of overlapping clones spanning each of the parasite's 14 chromosomes. Currently, clones of genomic DNA, prepared as yeast artificial chromosomes, are arranged into contigs covering approximately 70% of the genome of parasite clone 3D7, gene sequence tags are available from more than contigs covering approximately 70% of the genome of parasite clone 3D7, gene sequence tags are available from more than 20% of the parasite's genes, and approximately 5% of the parasite's genes are tentatively identified from similarity searches of entries in the international sequence databases. A total of > 0.5 Mb of P. falciparum sequence tag data is available. The gene sequence tags are presently being used to complete YAC contig assembly and localize the cloned genes to positions on the physical map in preparation for sequencing the genome. Routes of access to project information and services are described.
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Affiliation(s)
- J B Dame
- University of Florida, Gainesville, 32611, USA.
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Harley E, Bonner AJ, Goodman N. Good maps are straight. Proc Int Conf Intell Syst Mol Biol 1996; 4:88-97. [PMID: 8877508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
This paper proposes a simplified approach to the assembly of large physical genome maps. The approach focuses on two key problems: (i) the integration of diverse forms of data from numerous sources, and (ii) the detection and removal of errors and anomalies in the data. The approach simplifies map assembly by dividing it into three phases-overlap, linkage and ordering. In the first phase, all forms of overlap data are integrated into a simple abstract structure, called clusters, where each cluster is a set of mutually-overlapping DNA segments. This phase filters out many questionable overlaps in the mapping data. In the second phase, clusters are linked together into a weighted intersection graph. False links between widely separated regions of the genome show up as crooked, branching structures in the graph. Removing these false links produces graphs that are straight, reflecting the linear structure of chromosomes. From these straight graphs, the third phase constructs a physical map. Graph algorithms and graph visualization play key roles in implementing the approach. At present, the approach is at an early stage of development: it has been tested on real and simulated mapping data, and the results look promising. This paper describes the first two phases of the approach in detail, and reports on our progress to date.
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Affiliation(s)
- E Harley
- University of Toronto, Dept. of Computer Science, Ont., Canada.
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Hudson TJ, Stein LD, Gerety SS, Ma J, Castle AB, Silva J, Slonim DK, Baptista R, Kruglyak L, Xu SH, Hu X, Colbert AM, Rosenberg C, Reeve-Daly MP, Rozen S, Hui L, Wu X, Vestergaard C, Wilson KM, Bae JS, Maitra S, Ganiatsas S, Evans CA, DeAngelis MM, Ingalls KA, Nahf RW, Horton LT, Anderson MO, Collymore AJ, Ye W, Kouyoumjian V, Zemsteva IS, Tam J, Devine R, Courtney DF, Renaud MT, Nguyen H, O'Connor TJ, Fizames C, Fauré S, Gyapay G, Dib C, Morissette J, Orlin JB, Birren BW, Goodman N, Weissenbach J, Hawkins TL, Foote S, Page DC, Lander ES. An STS-based map of the human genome. Science 1995; 270:1945-54. [PMID: 8533086 DOI: 10.1126/science.270.5244.1945] [Citation(s) in RCA: 565] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
A physical map has been constructed of the human genome containing 15,086 sequence-tagged sites (STSs), with an average spacing of 199 kilobases. The project involved assembly of a radiation hybrid map of the human genome containing 6193 loci and incorporated a genetic linkage map of the human genome containing 5264 loci. This information was combined with the results of STS-content screening of 10,850 loci against a yeast artificial chromosome library to produce an integrated map, anchored by the radiation hybrid and genetic maps. The map provides radiation hybrid coverage of 99 percent and physical coverage of 94 percent of the human genome. The map also represents an early step in an international project to generate a transcript map of the human genome, with more than 3235 expressed sequences localized. The STSs in the map provide a scaffold for initiating large-scale sequencing of the human genome.
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Affiliation(s)
- T J Hudson
- Whitehead-MIT Center for Genome Research, Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
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