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Ruzbarsky JJ, Peebles AM, Watkins L, Kruse AR, Lilley BM, Eble SK, Denard PJ, Romeo AA, Provencher MT. Effect of osteophyte removal on simulated range of motion using 3-dimensional preoperative planning software for reverse total shoulder arthroplasty. JSES Int 2024; 8:104-110. [PMID: 38312277 PMCID: PMC10837730 DOI: 10.1016/j.jseint.2023.08.011] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2024] Open
Abstract
Background Glenohumeral osteophytes (OPs) can adversely influence postoperative range of motion (ROM) following shoulder arthroplasty due to mechanical impingement. Though commercial three-dimensional preoperative planning software (3D PPS) is available to simulate ROM before and after OP resection, little is known about the magnitude of effect OPs and their subsequent removal have on simulated glenohumeral ROM. Methods Included patients were 1) indicated for reverse total shoulder arthroplasty (rTSA) using 3D PPS and 2) presented with glenoid and/or humeral head OPs on preoperative two-dimensional computed tomography (2D-CT) imaging. Thirty patients met the inclusion criteria (9 females, 21 males; mean age 70.45 ± 4.99 years, range 63-80 years). All subjects (n = 30) presented with humeral OPs (mean volume: 2905.16 mm3, range 109.1-11,246 mm3), while 11 subjects also presented with glenoid OPs (mean volume 108.06 mm3, range 37.59-791.4 mm3). Preoperative CTs were used to calculate OP volume (mm3) and OP circumferential extent (clockface). Mean clockface position for circumferential humeral OPs originated at 6:09 (range 4:30-7:15) and extended to 8:51 (range 8:15-10:15). Mean clockface position for glenoid OPs originated at 3:00 (range 2:00-5:00) and extended to 6:16 (range 3:00-7:30). 3D implants on PPS were standardized to achieve 0° of version, 0° of inclination and 4 mm of net lateralization. Thirty-nine and thirty-six mm glenospheres were used for males and females, respectively. 3D PPS was used to evaluate simulated ROM differences before and after OP removal in the planes of adduction (ADD), abduction, internal rotation (IR), external rotation (ER), extension, and flexion. Impact of OP volume and circumferential extent on pre and postop removal ROM were also analyzed. Results Humeral OP removal significantly increased impingement-free ADD, IR, ER, extension, and flexion. Removal of larger (mm3) humeral OPs positively correlated with improvement in IR (R = 0.452, P = .011), ER (R = 0.394, P = .033), and flexion (R = 0.500, P < .01). Greater circumferential extent of humeral OPs correlated with worse preremoval ROM in the planes of ADD (R = 0.364, P = .02) and extension (R = 0.403, P = .04), and improvements in ER postop removal (R = 0.431, P = .03). Conclusion Humeral OP removal significantly increases impingement-free ADD, IR, ER, extension, and flexion in simulated 3D PPS models following rTSA. Magnitude of simulated ROM improvement is influenced by initial humeral OP volume and circumferential clockface extent. Surgeons should consider these effects when using 3D PPS for rTSA planning to optimize postoperative ROM prognostics.
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Affiliation(s)
- Joseph J Ruzbarsky
- The Steadman Clinic, Vail, CO, USA
- Steadman Philippon Research Institute, Vail, CO, USA
| | | | | | - Amelia R Kruse
- Steadman Philippon Research Institute, Vail, CO, USA
- William Beaumont School of Medicine, Rochester, MI, USA
| | | | - Stephanie K Eble
- Geisel School of Medicine at Dartmouth College, Hanover, NH, USA
| | | | - Anthony A Romeo
- Department of Orthopaedic Surgery, DuPage Medical Group, Chicago, IL, USA
| | - Matthew T Provencher
- The Steadman Clinic, Vail, CO, USA
- Steadman Philippon Research Institute, Vail, CO, USA
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Peebles AM, Ganokroj P, Macey RL, Lilley BM, Provencher MT. Revision Anterior Cruciate Ligament, Lateral Collateral Ligament Reconstruction, and Osteochondral Allograft Transplantation for Complex Knee Instability. Arthrosc Tech 2022; 11:e2153-e2159. [PMID: 36632389 PMCID: PMC9826972 DOI: 10.1016/j.eats.2022.08.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 08/10/2022] [Indexed: 11/19/2022] Open
Abstract
Anterior cruciate ligament (ACL) injuries rarely occur as an isolated event and often include associated meniscal, subchondral bone, and collateral ligament injuries. Concomitant pathology frequently complicates primary and revision ACL reconstruction and must be addressed to ensure comprehensive diagnosis and treatment. In this Technical Note, we describe our method for treatment of complex knee instability following multiple failed ACL reconstruction using a multiligament reconstruction technique with an osteochondral allograft transplantation to the lateral femoral condyle. This comprehensive repair technique restores the anatomic load bearing forces of the cruciate and collateral ligaments and promotes biological repair through incorporation of cartilage resurfacing to ultimately achieve optimal kinematics of the knee joint.
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Affiliation(s)
| | - Phob Ganokroj
- Steadman Philippon Research Institute, Vail, Colorado, U.S.A
- Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Reed L. Macey
- Dartmouth Geisel School of Medicine, Hanover, New Hampshire, U.S.A
| | | | - Matthew T. Provencher
- Steadman Philippon Research Institute, Vail, Colorado, U.S.A
- the Steadman Clinic, Vail, Colorado, U.S.A
- Address correspondence to CAPT. Matthew T. Provencher, M.D., M.B.A., M.C., U.S.N.R. (Ret.), Steadman Philippon Research Institute, The Steadman Clinic, 181 W Meadow Dr., Ste 400, Vail, CO 81657.
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Markiewitz ND, Garcia-Munoz J, Lilley BM, Oduwole S, Shah AS, Williams BA. Epidemiologic Changes in Pediatric Fractures Presenting to Emergency Departments During the COVID-19 Pandemic. J Pediatr Orthop 2022; 42:e815-e820. [PMID: 35818171 PMCID: PMC9351512 DOI: 10.1097/bpo.0000000000002194] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Fractures are a common pediatric injury. The coronavirus disease 2019 (COVID-19) pandemic resulted in significant changes in daily life that could impact the incidence of pediatric fractures. The purpose of this study was to compare the incidence of pediatric fractures in the United States during the COVID-19 pandemic to previous seasonally adjusted fracture incidence rates using the National Electronic Injury Surveillance System (NEISS) database and the American Community Survey (ACS). METHODS The NEISS database was queried from 2016 to 2020 for fractures occurring in pediatric (0 to 17 y) patients. ACS population data allowed for the estimation of fracture incidence per 1000 person-years. Using a quasiexperimental interrupted time series design, Poisson regression models were constructed to test the overall and differential impact of COVID-19 on monthly fracture rate by age, sex, fracture site, injury location, and disposition. RESULTS Our sample consisted of 121,803 cases (mean age 9.6±4.6 y, 36.1% female) representing 2,959,421±372,337 fractures nationally. We identified a stable 27% decrease in fractures per month after February 2020 [risk difference (RD) per 1000 youth years=-2.3; 95% confidence interval: -2.98, -1.57]). We found significant effect modification by age, fracture site and injury location ( P <0.05). The fracture incidence among children 5 years or older significantly decreased, as well as the incidence of fractures at school [RD=-0.96 (-1.09, -0.84)] and during sports [risk difference=-1.55 (-1.77, -1.32)]. There was also a trend toward a reduction in upper extremity fractures and fractures requiring admission. CONCLUSION A nationally representative injury database demonstrated a 27% decline in monthly pediatric fractures during the COVID-19 pandemic that persisted into the latter half of 2020. These trends appeared most attributable to a reduction in fractures discharged home and upper extremity fractures among older children sustained at school and in sports. Our findings provide unique insight into the epidemiology of pediatric fractures and demonstrate a baseline need for musculoskeletal care among young children even in the setting of a national shutdown. LEVEL OF EVIDENCE Level II-retrospective prognostic study.
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Affiliation(s)
| | | | | | | | - Apurva S. Shah
- Department of Orthopaedics, The Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Brendan A. Williams
- Department of Orthopaedics, The Children’s Hospital of Philadelphia, Philadelphia, PA
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Lilley BM, Lachance A, Peebles AM, Powell SN, Romeo AA, Denard PJ, Provencher CMT. What is the deviation in 3D preoperative planning software? A systematic review of concordance between plan and actual implant in reverse total shoulder arthroplasty. J Shoulder Elbow Surg 2022; 31:1073-1082. [PMID: 35017079 DOI: 10.1016/j.jse.2021.12.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/02/2021] [Accepted: 12/04/2021] [Indexed: 02/01/2023]
Abstract
BACKGROUND Three-dimensional (3D) preoperative planning software for reverse total shoulder arthroplasty (rTSA) has been implemented in recent years in order to increase accuracy, improve efficiency, and add value to the outcome. A comprehensive literature review is required to determine the utility of preoperative 3D planning software in guiding orthopedic surgeons for implant placement in rTSA. We hypothesize that implementation of 3D preoperative planning software in the setting of rTSA leads to high concordance with minimal deviation from the preoperative plan. METHODS A comprehensive and iterative literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) using the PubMed, Embase, OVID Medline, Scopus, Cinahl, Web of Science, and Cochrane databases for original English-language studies evaluating the impact of preoperative planning software usage on rTSA outcomes published from January 1, 2000, to present. Blinded reviewers conducted multiple screens. All included studies were graded based on level of evidence, and data concerning patient demographics and postoperative outcomes were extracted. RESULTS Nine articles met inclusion criteria (1 level II, 3 level III, and 5 level IV articles), including 415 patients and 422 shoulders. Of the patients who underwent rTSA, 235 were female and 140 were male, although 3 studies (n = 40) did not report sex breakdowns for rTSA patients. The average age was 72.7 years. Four studies (79 shoulders) reported implant final position as mean deviation from planned version and planned inclination. Six studies (n = 236) reported screw angle deviation, fixation, length, and concordance. Concordance with the preoperative plan was measured in 3 studies (n = 178), resulting in complete concordance of 90% (n = 100), arthroplasty type concordance (rTSA vs. TSA) of 100% (n = 100), and glenosphere size concordance between 93% (n = 100) and 88% (n = 76). For screw length concordance, baseplate screw matched by 81% (n = 76) and 100% (n = 2), and upper (n = 35) and lower (n = 35) screw length concordance was observed as 74% and 69%, respectively. The use of preoperative planning (n = 178) was associated with low deviation from preoperative plan, more 2-screw fixations, and longer average screw length in comparison with an unplanned cohort. CONCLUSION The use of preoperative planning software in the setting of rTSA results in minimal deviation from preoperative plan. High levels of concordance in screw angle, screw length, and glenosphere size were observed. Further prospective studies should be conducted to further substantiate these results.
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Affiliation(s)
| | | | | | - Sarah N Powell
- Georgetown University School of Medicine, Washington, DC, USA
| | - Anthony A Romeo
- Department of Orthopaedic Surgery, DuPage Medical Group, Chicago, IL, USA
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Powell SN, Lilley BM, Peebles AM, Dekker TJ, Warner JJ, Romeo AA, Denard PJ, Provencher MT. Impact of fatty infiltration of the rotator cuff on reverse total shoulder arthroplasty outcomes: a systematic review. JSES Rev Rep Tech 2022; 2:125-130. [PMID: 37587967 PMCID: PMC10426473 DOI: 10.1016/j.xrrt.2021.12.001] [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] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/18/2023]
Abstract
Background and hypothesis The impact of preoperative fatty infiltration of specific rotator cuff muscles on the outcomes of reverse total shoulder arthroplasty (rTSA) has not been well defined. Preoperative fatty infiltration of the shoulder musculature will negatively affect rTSA outcomes. Methods A comprehensive literature review was conducted as per the Preferred Reporting Items for Systematic Reviews and Meta-analyses using PubMed, Embase, OVID Medline, Scopus, Cinahl, Web of Science, and Cochrane databases for original, English-language studies evaluating effect of fatty infiltration of shoulder musculature on rTSA outcomes published from January 1, 2000 to present. Blinded reviewers conducted multiple screens. All included studies were graded based on the level of evidence, and data concerning patient demographics and postoperative outcomes were extracted. Results A total of 11 articles were included, including one level I article, three level III articles, and seven level IV articles. The review consisted of 720 patients and 731 shoulders (320 women and 157 men), with a mean age of 72.4 years. A single deltopectoral approach was performed for a majority of studies (627/731 shoulders), followed by a superolateral approach (70/731 shoulders) and a single transdeltoid approach (4/731 patients). Eleven studies reported data specifically about preoperative fatty infiltration of the rotator cuff musculature; the teres minor was studied most widely (298/731 shoulders), followed by the subscapularis (256/731 shoulders) and infraspinatus (232/731 shoulders). The Constant score (562/731 shoulders) and American Shoulder and Elbow Surgeons score (284/731 shoulders) were the most common recorded outcome scores. Fatty infiltration of the teres minor, supraspinatus, and infraspinatus was associated with worse range of motion after rTSA. Conclusion Preoperative fatty infiltration of the rotator cuff, particularly of the teres minor and infraspinatus, has a negative impact on subjective patient outcomes and restoration of range of motion, especially external rotation, after rTSA. The impact of fatty infiltration of the other rotator cuff muscles remains unclear, which may be due to intersurgeon differences in the handling of the remaining rotator cuff muscles or differences in implant design. The evaluated literature provides information on which patients can be educated about probable outcomes and restoration of function after rTSA.
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Affiliation(s)
- Sarah N. Powell
- Georgetown University School of Medicine, Washington, DC, USA
| | | | | | - Travis J. Dekker
- Eglin Air Force Base, 96th Medical Group, United States Air Force, Eglin, FL, USA
| | | | - Anthony A. Romeo
- Department of Orthopaedic Surgery, DuPage Medial Group, Chicago, IL, USA
| | | | - Matthew T. Provencher
- The Steadman Philippon Research Institute, Vail, CO, USA
- The Steadman Clinic, Vail, CO, USA
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Leisman DE, Mehta A, Thompson BT, Charland NC, Gonye ALK, Gushterova I, Kays KR, Khanna HK, LaSalle TJ, Lavin-Parsons KM, Lilley BM, Lodenstein CL, Manakongtreecheep K, Margolin JD, McKaig BN, Rojas-Lopez M, Russo BC, Sharma N, Tantivit J, Thomas MF, Parry BA, Villani AC, Sade-Feldman M, Hacohen N, Filbin MR, Goldberg MB. Alveolar, Endothelial, and Organ Injury Marker Dynamics in Severe COVID-19. Am J Respir Crit Care Med 2022; 205:507-519. [PMID: 34878969 PMCID: PMC8906476 DOI: 10.1164/rccm.202106-1514oc] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 12/07/2021] [Indexed: 11/23/2022] Open
Abstract
Rationale: Alveolar and endothelial injury may be differentially associated with coronavirus disease (COVID-19) severity over time. Objectives: To describe alveolar and endothelial injury dynamics and associations with COVID-19 severity, cardiorenovascular injury, and outcomes. Methods: This single-center observational study enrolled patients with COVID-19 requiring respiratory support at emergency department presentation. More than 40 markers of alveolar (including receptor for advanced glycation endproducts [RAGE]), endothelial (including angiopoietin-2), and cardiorenovascular injury (including renin, kidney injury molecule-1, and troponin-I) were serially compared between invasively and spontaneously ventilated patients using mixed-effects repeated-measures models. Ventilatory ratios were calculated for intubated patients. Associations of biomarkers with modified World Health Organization scale at Day 28 were determined with multivariable proportional-odds regression. Measurements and Main Results: Of 225 patients, 74 (33%) received invasive ventilation at Day 0. RAGE was 1.80-fold higher in invasive ventilation patients at Day 0 (95% confidence interval [CI], 1.50-2.17) versus spontaneous ventilation, but decreased over time in all patients. Changes in alveolar markers did not correlate with changes in endothelial, cardiac, or renal injury markers. In contrast, endothelial markers were similar to lower at Day 0 for invasive ventilation versus spontaneous ventilation, but then increased over time only among intubated patients. In intubated patients, angiopoietin-2 was similar (fold difference, 1.02; 95% CI, 0.89-1.17) to nonintubated patients at Day 0 but 1.80-fold higher (95% CI, 1.56-2.06) at Day 3; cardiorenovascular injury markers showed similar patterns. Endothelial markers were not consistently associated with ventilatory ratios. Endothelial markers were more often significantly associated with 28-day outcomes than alveolar markers. Conclusions: Alveolar injury markers increase early. Endothelial injury markers increase later and are associated with cardiorenovascular injury and 28-day outcome. Alveolar and endothelial injury likely contribute at different times to disease progression in severe COVID-19.
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Affiliation(s)
- Daniel E. Leisman
- Department of Anesthesiology, Critical Care, and Pain Medicine
- Department of Medicine
| | - Arnav Mehta
- Massachusetts General Hospital Cancer Center
- Department of Medicine
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | | | | | - Anna L. K. Gonye
- Center for Cancer Research
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | - Irena Gushterova
- Center for Cancer Research
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | | | | | - Thomas J. LaSalle
- Center for Cancer Research
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | | | | | | | - Kasidet Manakongtreecheep
- Center for Cancer Research
- Center for Immunology and Inflammatory Diseases, and
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | | | | | - Maricarmen Rojas-Lopez
- Center for Bacterial Pathogenesis, Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine
- Department of Microbiology, and
| | - Brian C. Russo
- Center for Bacterial Pathogenesis, Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine
- Department of Microbiology, and
| | - Nihaarika Sharma
- Center for Cancer Research
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | - Jessica Tantivit
- Center for Cancer Research
- Center for Immunology and Inflammatory Diseases, and
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | - Molly F. Thomas
- Center for Cancer Research
- Center for Immunology and Inflammatory Diseases, and
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | | | - Alexandra-Chloé Villani
- Massachusetts General Hospital Cancer Center
- Department of Medicine
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | - Moshe Sade-Feldman
- Massachusetts General Hospital Cancer Center
- Department of Medicine
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | - Nir Hacohen
- Massachusetts General Hospital Cancer Center
- Department of Medicine
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | - Michael R. Filbin
- Department of Emergency Medicine, and
- Department of Emergency Medicine, Harvard Medical School, Boston, Massachusetts
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
| | - Marcia B. Goldberg
- Center for Bacterial Pathogenesis, Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine
- Department of Microbiology, and
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts; and
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Kaplonek P, Wang C, Bartsch Y, Fischinger S, Gorman MJ, Bowman K, Kang J, Dayal D, Martin P, Nowak RP, Villani AC, Hsieh CL, Charland NC, Gonye AL, Gushterova I, Khanna HK, LaSalle TJ, Lavin-Parsons KM, Lilley BM, Lodenstein CL, Manakongtreecheep K, Margolin JD, McKaig BN, Rojas-Lopez M, Russo BC, Sharma N, Tantivit J, Thomas MF, Sade-Feldman M, Feldman J, Julg B, Nilles EJ, Musk ER, Menon AS, Fischer ES, McLellan JS, Schmidt A, Goldberg MB, Filbin MR, Hacohen N, Lauffenburger DA, Alter G. Early cross-coronavirus reactive signatures of humoral immunity against COVID-19. Sci Immunol 2021; 6:eabj2901. [PMID: 34652962 PMCID: PMC8943686 DOI: 10.1126/sciimmunol.abj2901] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [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: 05/05/2021] [Revised: 07/06/2021] [Accepted: 09/01/2021] [Indexed: 12/15/2022]
Abstract
The introduction of vaccines has inspired hope in the battle against SARS-CoV-2. However, the emergence of viral variants, in the absence of potent antivirals, has left the world struggling with the uncertain nature of this disease. Antibodies currently represent the strongest correlate of immunity against SARS-CoV-2, thus we profiled the earliest humoral signatures in a large cohort of acutely ill (survivors and nonsurvivors) and mild or asymptomatic individuals with COVID-19. Although a SARS-CoV-2–specific immune response evolved rapidly in survivors of COVID-19, nonsurvivors exhibited blunted and delayed humoral immune evolution, particularly with respect to S2-specific antibodies. Given the conservation of S2 across β-coronaviruses, we found that the early development of SARS-CoV-2–specific immunity occurred in tandem with preexisting common β-coronavirus OC43 humoral immunity in survivors, which was also selectively expanded in individuals that develop a paucisymptomatic infection. These data point to the importance of cross-coronavirus immunity as a correlate of protection against COVID-19.
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Affiliation(s)
| | - Chuangqi Wang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yannic Bartsch
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | | | | | - Kathryn Bowman
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Jaewon Kang
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Diana Dayal
- Space Exploration Technologies Corporation, Hawthorne, CA, USA
| | - Patrick Martin
- Space Exploration Technologies Corporation, Hawthorne, CA, USA
| | - Radoslaw P. Nowak
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Alexandra-Chloé Villani
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ching-Lin Hsieh
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA
| | - Nicole C. Charland
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anna L.K. Gonye
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Irena Gushterova
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Hargun K. Khanna
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Thomas J. LaSalle
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - Brendan M. Lilley
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Carl L. Lodenstein
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kasidet Manakongtreecheep
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Justin D. Margolin
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brenna N. McKaig
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Maricarmen Rojas-Lopez
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brian C. Russo
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Nihaarika Sharma
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jessica Tantivit
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Molly F. Thomas
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Moshe Sade-Feldman
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jared Feldman
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Boris Julg
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | | | - Elon R. Musk
- Space Exploration Technologies Corporation, Hawthorne, CA, USA
| | - Anil S. Menon
- Space Exploration Technologies Corporation, Hawthorne, CA, USA
| | - Eric S. Fischer
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jason S. McLellan
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA
| | - Aaron Schmidt
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Marcia B. Goldberg
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
- Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Michael R. Filbin
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Nir Hacohen
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | | | - Galit Alter
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
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Li Y, Schneider AM, Mehta A, Sade-Feldman M, Kays KR, Gentili M, Charland NC, Gonye AL, Gushterova I, Khanna HK, LaSalle TJ, Lavin-Parsons KM, Lilley BM, Lodenstein CL, Manakongtreecheep K, Margolin JD, McKaig BN, Parry BA, Rojas-Lopez M, Russo BC, Sharma N, Tantivit J, Thomas MF, Regan J, Flynn JP, Villani AC, Hacohen N, Goldberg MB, Filbin MR, Li JZ. SARS-CoV-2 viremia is associated with distinct proteomic pathways and predicts COVID-19 outcomes. J Clin Invest 2021; 131:148635. [PMID: 34196300 PMCID: PMC8245177 DOI: 10.1172/jci148635] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 05/06/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUNDSARS-CoV-2 plasma viremia has been associated with severe disease and death in COVID-19 in small-scale cohort studies. The mechanisms behind this association remain elusive.METHODSWe evaluated the relationship between SARS-CoV-2 viremia, disease outcome, and inflammatory and proteomic profiles in a cohort of COVID-19 emergency department participants. SARS-CoV-2 viral load was measured using a quantitative reverse transcription PCR-based platform. Proteomic data were generated with Proximity Extension Assay using the Olink platform.RESULTSThis study included 300 participants with nucleic acid test-confirmed COVID-19. Plasma SARS-CoV-2 viremia levels at the time of presentation predicted adverse disease outcomes, with an adjusted OR of 10.6 (95% CI 4.4-25.5, P < 0.001) for severe disease (mechanical ventilation and/or 28-day mortality) and 3.9 (95% CI 1.5-10.1, P = 0.006) for 28-day mortality. Proteomic analyses revealed prominent proteomic pathways associated with SARS-CoV-2 viremia, including upregulation of SARS-CoV-2 entry factors (ACE2, CTSL, FURIN), heightened markers of tissue damage to the lungs, gastrointestinal tract, and endothelium/vasculature, and alterations in coagulation pathways.CONCLUSIONThese results highlight the cascade of vascular and tissue damage associated with SARS-CoV-2 plasma viremia that underlies its ability to predict COVID-19 disease outcomes.FUNDINGMark and Lisa Schwartz; the National Institutes of Health (U19AI082630); the American Lung Association; the Executive Committee on Research at Massachusetts General Hospital; the Chan Zuckerberg Initiative; Arthur, Sandra, and Sarah Irving for the David P. Ryan, MD, Endowed Chair in Cancer Research; an EMBO Long-Term Fellowship (ALTF 486-2018); a Cancer Research Institute/Bristol Myers Squibb Fellowship (CRI2993); the Harvard Catalyst/Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, NIH awards UL1TR001102 and UL1TR002541-01); and by the Harvard University Center for AIDS Research (National Institute of Allergy and Infectious Diseases, 5P30AI060354).
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Affiliation(s)
- Yijia Li
- Brigham and Women’s Hospital and
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Alexis M. Schneider
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Arnav Mehta
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
- Center for Cancer Research, Department of Medicine, and
| | - Moshe Sade-Feldman
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Cancer Research, Department of Medicine, and
| | - Kyle R. Kays
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Matteo Gentili
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Nicole C. Charland
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Anna L.K. Gonye
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Cancer Research, Department of Medicine, and
| | - Irena Gushterova
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Cancer Research, Department of Medicine, and
| | - Hargun K. Khanna
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Thomas J. LaSalle
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Cancer Research, Department of Medicine, and
| | | | - Brendan M. Lilley
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Carl L. Lodenstein
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Kasidet Manakongtreecheep
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Justin D. Margolin
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Brenna N. McKaig
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Blair A. Parry
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Maricarmen Rojas-Lopez
- Center for Bacterial Pathogenesis, Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Brian C. Russo
- Center for Bacterial Pathogenesis, Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Nihaarika Sharma
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Jessica Tantivit
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Molly F. Thomas
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | | | - Alexandra-Chloé Villani
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Nir Hacohen
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Cancer Research, Department of Medicine, and
| | - Marcia B. Goldberg
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Bacterial Pathogenesis, Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Michael R. Filbin
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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Filbin MR, Mehta A, Schneider AM, Kays KR, Guess JR, Gentili M, Fenyves BG, Charland NC, Gonye AL, Gushterova I, Khanna HK, LaSalle TJ, Lavin-Parsons KM, Lilley BM, Lodenstein CL, Manakongtreecheep K, Margolin JD, McKaig BN, Rojas-Lopez M, Russo BC, Sharma N, Tantivit J, Thomas MF, Gerszten RE, Heimberg GS, Hoover PJ, Lieb DJ, Lin B, Ngo D, Pelka K, Reyes M, Smillie CS, Waghray A, Wood TE, Zajac AS, Jennings LL, Grundberg I, Bhattacharyya RP, Parry BA, Villani AC, Sade-Feldman M, Hacohen N, Goldberg MB. Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions. Cell Rep Med 2021; 2:100287. [PMID: 33969320 PMCID: PMC8091031 DOI: 10.1016/j.xcrm.2021.100287] [Citation(s) in RCA: 142] [Impact Index Per Article: 47.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 03/08/2021] [Accepted: 04/23/2021] [Indexed: 02/06/2023]
Abstract
Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNA-seq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune-cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell-type-specific intracellular death signatures, cellular angiotensin-converting enzyme 2 (ACE2) expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease.
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Affiliation(s)
- Michael R. Filbin
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Emergency Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Arnav Mehta
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Alexis M. Schneider
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kyle R. Kays
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - Matteo Gentili
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Bánk G. Fenyves
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Emergency Medicine, Semmelweis University, Budapest, Hungary
| | - Nicole C. Charland
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anna L.K. Gonye
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Irena Gushterova
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Hargun K. Khanna
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Thomas J. LaSalle
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - Brendan M. Lilley
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Carl L. Lodenstein
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kasidet Manakongtreecheep
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Justin D. Margolin
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brenna N. McKaig
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Maricarmen Rojas-Lopez
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
| | - Brian C. Russo
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
| | - Nihaarika Sharma
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jessica Tantivit
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Molly F. Thomas
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Robert E. Gerszten
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- CardioVascular Institute, Department of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Graham S. Heimberg
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Paul J. Hoover
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - David J. Lieb
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Brian Lin
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Regenerative Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Debby Ngo
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Karin Pelka
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Miguel Reyes
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Christopher S. Smillie
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Avinash Waghray
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Regenerative Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Thomas E. Wood
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
| | - Amanda S. Zajac
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
| | | | | | - Roby P. Bhattacharyya
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Blair Alden Parry
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alexandra-Chloé Villani
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Moshe Sade-Feldman
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Nir Hacohen
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Marcia B. Goldberg
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Abstract
The findings are reported from a New Zealand Cancer Registry-based case-control study involving 427 male patients with testicular cancer registered during the period 1979-1983 and aged 20 years or more at time of registration. Controls were also males chosen from the Cancer Registry with two controls per case, matched on age and year of registration. It was found that, as in other countries, persons in the upper social class groupings were at increased risk of testicular cancer. Persons in professional occupations were also at increased risk, but the odds ratio of 1.09 was much smaller than found in other studies. The previously reported excess risks for farmers, food and beverage workers, forestry workers, and pulp and paper workers were not supported by the New Zealand data. On the other hand, the previously reported excess risk for sales and service workers including members of the armed forces was supported, to some extent, by the New Zealand data with odds ratios of 1.38 (95% confidence limits 0.98-1.93) and 2.15 (95% confidence limits 0.80-5.79), respectively. Other groups with elevated risk include: physicians (odds ratio = 6.50, 95% confidence limits 1.29-32.6); production supervisors (odds ratio = 2.85,95% confidence limits 1.00-8.13); and motor vehicle mechanics (odds ratio = 2.02, 95% confidence limits 0.93-4.42). However, the New Zealand data generally does not suggest that occupational factors (or lifestyle factors associated with occupation) are of major direct importance in the etiology of testicular cancer. The incidence of testicular cancer has a bimodal age distribution in New Zealand and has risen markedly during the period 1948-1979. The New Zealand data differed from patterns observed in other countries in that the relative increase was approximately uniform across age groups rather than being stronger in the younger age groups.
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Abstract
Mortality studies have indicated that workers in agriculture and forestry may be at increased risk of leukemia. Findings are reported from a New Zealand Cancer Registry-based case-control study involving 546 male leukemia patients registered during 1979-1983 and aged 20 years or more at time of registration. Controls were also males chosen from the Cancer Registry with four controls per case, matched on age and year of registration. The case group contained an excess of the occupational category involving agriculture and forestry (odds ratio (OR) = 1.24, 95% confidence interval (CI) = 0.95-1.61) with the greatest relative risk being for livestock farmers (OR = 3.00, 95% CI = 1.23-7.32). There was also an excess of electrical workers (OR = 1.72, 95% CI = 0.92-3.20). The agricultural excess was greatest in patients aged 65 years or more at time of registration (OR = 1.29, 95% CI = 0.94-1.78), particularly in patients with acute myeloid leukemia (OR = 1.55, 95% CI = 0.90-2.67) or acute monocytic leukemia OR = 10.38, 95% CI = 1.99-54.29), although the latter excess only involved five cases. Acute myeloid leukemia was also elevated in meat workers (OR = 2.51, 95% CI = 1.19-5.30).
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Smith AH, Pool DI, Pearce NE, Lyon JL, Lilley BM, Davis PB, Prior IA. Mortality among New Zealand Maori and non-Maori Mormons. Int J Epidemiol 1985; 14:265-71. [PMID: 4018993 DOI: 10.1093/ije/14.2.265] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Mortality rates for New Zealand Maori and non-Maori Mormons in the period 1970-77 have been compared with those for non-Mormons in the census year 1976 to measure the impact of the Mormon lifestyle on differences in mortality between Maoris and non-Maoris. Maori mortality was much lower among Mormons than non-Mormons suggesting that environmental, rather than genetic factors, play a predominant role in the relatively high overall Maori mortality. However the prevalence of smoking among Maori Mormons was not much lower than for the general Maori population. Reasons for the relative mortality advantage of Maori Mormons were therefore not clear, although attitudes to health and health services utilization, and the influence of strong social support networks, might be involved. Paradoxically, non-Maori Mormon mortality rates were similar to those for non-Mormons. A combination of factors appeared to contribute to this finding including the fact that 26% of non-Maori Mormons were of Pacific Island origin, non-Maori Mormons were of lower socioeconomic status than other non-Maoris, and part Maoris probably constitute a high, but unknown, proportion of Mormons classified as non-Maoris.
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