1
|
Hirst JE, Boniface JJ, Le DP, Polpitiya AD, Fox AC, Vu TTK, Dang TT, Fleischer TC, Bui NTH, Hickok DE, Kearney PE, Thwaites G, Kennedy SH, Kestelyn E, Le TQ. Validating the ratio of insulin like growth factor binding protein 4 to sex hormone binding globulin as a prognostic predictor of preterm birth in Viet Nam: a case-cohort study. J Matern Fetal Neonatal Med 2024; 37:2333923. [PMID: 38584143 DOI: 10.1080/14767058.2024.2333923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 03/13/2024] [Indexed: 04/09/2024]
Abstract
OBJECTIVE To validate a serum biomarker developed in the USA for preterm birth (PTB) risk stratification in Viet Nam. METHODS Women with singleton pregnancies (n = 5000) were recruited between 19+0-23+6 weeks' gestation at Tu Du Hospital, Ho Chi Minh City. Maternal serum was collected from 19+0-22+6 weeks' gestation and participants followed to neonatal discharge. Relative insulin-like growth factor binding protein 4 (IGFBP4) and sex hormone binding globulin (SHBG) abundances were measured by mass spectrometry and their ratio compared between PTB cases and term controls. Discrimination (area under the receiver operating characteristic curve, AUC) and calibration for PTB <37 and <34 weeks' gestation were tested, with model tuning using clinical factors. Measured outcomes included all PTBs (any birth ≤37 weeks' gestation) and spontaneous PTBs (birth ≤37 weeks' gestation with clinical signs of initiation of parturition). RESULTS Complete data were available for 4984 (99.7%) individuals. The cohort PTB rate was 6.7% (n = 335). We observed an inverse association between the IGFBP4/SHBG ratio and gestational age at birth (p = 0.017; AUC 0.60 [95% CI, 0.53-0.68]). Including previous PTB (for multiparous women) or prior miscarriage (for primiparous women) improved performance (AUC 0.65 and 0.70, respectively, for PTB <37 and <34 weeks' gestation). Optimal performance (AUC 0.74) was seen within 19-20 weeks' gestation, for BMI >21 kg/m2 and age 20-35 years. CONCLUSION We have validated a novel serum biomarker for PTB risk stratification in a very different setting to the original study. Further research is required to determine appropriate ratio thresholds based on the prevalence of risk factors and the availability of resources and preventative therapies.
Collapse
Affiliation(s)
- Jane E Hirst
- Department of Global Women's Health, The George Institute for Global Health, Imperial College London, London, UK
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Women's Centre, John Radcliffe Hospital, Oxford, UK
| | | | - Dung Puhong Le
- Department of Obstetrics and Gynaecology, Tu Du Hospital, Ho Chi Minh City, Viet Nam
| | | | - Angela C Fox
- Sera Prognostics, Inc, Salt Lake City, Utah, USA
| | - Thi Thai Kim Vu
- Clinical Trials Unit, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | - Thuan Trong Dang
- Clinical Trials Unit, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | | | - Nhu Thi Hong Bui
- Department of Obstetrics and Gynaecology, Tu Du Hospital, Ho Chi Minh City, Viet Nam
| | | | | | - Guy Thwaites
- Clinical Trials Unit, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Stephen H Kennedy
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Women's Centre, John Radcliffe Hospital, Oxford, UK
| | - Evelyne Kestelyn
- Clinical Trials Unit, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Thanh Quang Le
- Department of Obstetrics and Gynaecology, Tu Du Hospital, Ho Chi Minh City, Viet Nam
| |
Collapse
|
2
|
Sveiven M, Gassman A, Rosenberg J, Chan M, Boniface J, O’Donoghue AJ, Laurent LC, Hall DA. A dual-binding magnetic immunoassay to predict spontaneous preterm birth. Front Bioeng Biotechnol 2023; 11:1256267. [PMID: 37790251 PMCID: PMC10542577 DOI: 10.3389/fbioe.2023.1256267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 08/25/2023] [Indexed: 10/05/2023] Open
Abstract
Complications posed by preterm birth (delivery before 37 weeks of pregnancy) are a leading cause of newborn morbidity and mortality. The previous discovery and validation of an algorithm that includes maternal serum protein biomarkers, sex hormone-binding globulin (SHBG), and insulin-like growth factor-binding protein 4 (IBP4), with clinical factors to predict preterm birth represents an opportunity for the development of a widely accessible point-of-care assay to guide clinical management. Toward this end, we developed SHBG and IBP4 quantification assays for maternal serum using giant magnetoresistive (GMR) sensors and a self-normalizing dual-binding magnetic immunoassay. The assays have a picomolar limit of detections (LOD) with a relatively broad dynamic range that covers the physiological level of the analytes as they change throughout gestation. Measurement of serum from pregnant donors using the GMR assays was highly concordant with those obtained using a clinical mass spectrometry (MS)-based assay for the same protein markers. The MS assay requires capitally intense equipment and highly trained operators with a few days turnaround time, whereas the GMR assays can be performed in minutes on small, inexpensive instruments with minimal personnel training and microfluidic automation. The potential for high sensitivity, accuracy, and speed of the GMR assays, along with low equipment and personnel requirements, make them good candidates for developing point-of-care tests. Rapid turnaround risk assessment for preterm birth would enable patient testing and counseling at the same clinic visit, thereby increasing the timeliness of recommended interventions.
Collapse
Affiliation(s)
- Michael Sveiven
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
| | - Andrew Gassman
- Sera Prognostics, Inc., Salt Lake City, UT, United States
| | - Joshua Rosenberg
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States
| | - Matthew Chan
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States
| | - Jay Boniface
- Sera Prognostics, Inc., Salt Lake City, UT, United States
| | - Anthony J. O’Donoghue
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, United States
| | - Louise C. Laurent
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, La Jolla, CA, United States
| | - Drew A. Hall
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States
| |
Collapse
|
3
|
Burchard J, Saade GR, Boggess KA, Markenson GR, Iams JD, Coonrod DV, Pereira LM, Hoffman MK, Polpitiya AD, Treacy R, Fox AC, Randolph TL, Fleischer TC, Dufford MT, Garite TJ, Critchfield GC, Boniface JJ, Kearney PE. Better Estimation of Spontaneous Preterm Birth Prediction Performance through Improved Gestational Age Dating. J Clin Med 2022; 11:jcm11102885. [PMID: 35629011 PMCID: PMC9146613 DOI: 10.3390/jcm11102885] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/11/2022] [Accepted: 05/18/2022] [Indexed: 02/05/2023] Open
Abstract
The clinical management of pregnancy and spontaneous preterm birth (sPTB) relies on estimates of gestational age (GA). Our objective was to evaluate the effect of GA dating uncertainty on the observed performance of a validated proteomic biomarker risk predictor, and then to test the generalizability of that effect in a broader range of GA at blood draw. In a secondary analysis of a prospective clinical trial (PAPR; NCT01371019), we compared two GA dating categories: both ultrasound and dating by last menstrual period (LMP) (all subjects) and excluding dating by LMP (excluding LMP). The risk predictor's performance was observed at the validated risk predictor threshold both in weeks 191/7-206/7 and extended to weeks 180/7-206/7. Strict blinding and independent statistical analyses were employed. The validated biomarker risk predictor showed greater observed sensitivity of 88% at 75% specificity (increases of 17% and 1%) in more reliably dated (excluding-LMP) subjects, relative to all subjects. Excluding dating by LMP significantly improved the sensitivity in weeks 191/7-206/7. In the broader blood draw window, the previously validated risk predictor threshold significantly stratified higher and lower risk of sPTB, and the risk predictor again showed significantly greater observed sensitivity in excluding-LMP subjects. These findings have implications for testing the performance of models aimed at predicting PTB.
Collapse
Affiliation(s)
- Julja Burchard
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
- Correspondence: ; Tel.: +1-801-990-0597
| | - George R. Saade
- Department of Obstetrics & Gynecology, The University of Texas Medical Branch, Galveston, TX 77555, USA;
| | - Kim A. Boggess
- Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of North Carolina, Chapel Hill, NC 27599, USA;
| | - Glenn R. Markenson
- Maternal Fetal Medicine, Boston University School of Medicine, Boston, MA 02118, USA;
| | - Jay D. Iams
- Department of Obstetrics & Gynecology, The Ohio State University, Columbus, OH 43210, USA;
| | - Dean V. Coonrod
- Department of Obstetrics and Gynecology, Valleywise Health, Phoenix, AZ 85008, USA;
| | - Leonardo M. Pereira
- Division of Maternal-Fetal Medicine, Oregon Health & Science University, Portland, OR 97239, USA;
| | - Matthew K. Hoffman
- Department of Obstetrics & Gynecology, Christiana Care Health System, Newark, DE 19718, USA;
| | - Ashoka D. Polpitiya
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Ryan Treacy
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Angela C. Fox
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Todd L. Randolph
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Tracey C. Fleischer
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Max T. Dufford
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Thomas J. Garite
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Gregory C. Critchfield
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - J. Jay Boniface
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Paul E. Kearney
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (A.D.P.); (R.T.); (A.C.F.); (T.L.R.); (T.C.F.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| |
Collapse
|
4
|
Is there a maternal blood biomarker that can predict spontaneous preterm birth prior to labour onset? A systematic review. PLoS One 2022; 17:e0265853. [PMID: 35377904 PMCID: PMC8979439 DOI: 10.1371/journal.pone.0265853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 03/08/2022] [Indexed: 12/03/2022] Open
Abstract
Introduction The ability to predict spontaneous preterm birth (sPTB) prior to labour onset is a challenge, and it is currently unclear which biomarker(s), may be potentially predictive of sPTB, and whether their predictive power has any utility. A systematic review was conducted to identify maternal blood biomarkers of sPTB. Methods This study was conducted according to PRISMA protocol for systematic reviews. Four databases (MEDLINE, EMBASE, CINAHL, Scopus) were searched up to September 2021 using search terms: “preterm labor”, “biomarker” and “blood OR serum OR plasma”. Studies assessing blood biomarkers prior to labour onset against the outcome sPTB were eligible for inclusion. Risk of bias was assessed based on the Newcastle Ottawa scale. Increased odds of sPTB associated with maternal blood biomarkers, as reported by odds ratios (OR), or predictive scores were synthesized. This review was not prospectively registered. Results Seventy-seven primary research articles met the inclusion criteria, reporting 278 unique markers significantly associated with and/or predictive of sPTB in at least one study. The most frequently investigated biomarkers were those measured during maternal serum screen tests for aneuploidy, or inflammatory cytokines, though no single biomarker was clearly predictive of sPTB based on the synthesized evidence. Immune and signaling pathways were enriched within the set of biomarkers and both at the level of protein and gene expression. Conclusion There is currently no known predictive biomarker for sPTB. Inflammatory and immune biomarkers show promise, but positive reporting bias limits the utility of results. The biomarkers identified may be more predictive in multi-marker models instead of as single predictors. Omics-style studies provide promising avenues for the identification of novel (and multiple) biomarkers. This will require larger studies with adequate power, with consideration of gestational age and the heterogeneity of sPTB to identify a set of biomarkers predictive of sPTB.
Collapse
|
5
|
Burchard J, Markenson GR, Saade GR, Laurent LC, Heyborne KD, Coonrod DV, Schoen CN, Baxter JK, Haas DM, Longo SA, Sullivan SA, Wheeler SM, Pereira LM, Boggess KA, Hawk AF, Crockett AH, Treacy R, Fox AC, Polpitiya AD, Fleischer TC, Garite TJ, Jay Boniface J, Zupancic JAF, Critchfield GC, Kearney PE. Clinical and economic evaluation of a proteomic biomarker preterm birth risk predictor: cost-effectiveness modeling of prenatal interventions applied to predicted higher-risk pregnancies within a large and diverse cohort. J Med Econ 2022; 25:1255-1266. [PMID: 36377363 DOI: 10.1080/13696998.2022.2147771] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
OBJECTIVES Preterm birth occurs in more than 10% of U.S. births and is the leading cause of U.S. neonatal deaths, with estimated annual costs exceeding $25 billion USD. Using real-world data, we modeled the potential clinical and economic utility of a prematurity-reduction program comprising screening in a racially and ethnically diverse population with a validated proteomic biomarker risk predictor, followed by case management with or without pharmacological treatment. METHODS The ACCORDANT microsimulation model used individual patient data from a prespecified, randomly selected sub-cohort (N = 847) of a multicenter, observational study of U.S. subjects receiving standard obstetric care with masked risk predictor assessment (TREETOP; NCT02787213). All subjects were included in three arms across 500 simulated trials: standard of care (SoC, control); risk predictor/case management comprising increased outreach, education and specialist care (RP-CM, active); and multimodal management (risk predictor/case management with pharmacological treatment) (RP-MM, active). In the active arms, only subjects stratified as higher risk by the predictor were modeled as receiving the intervention, whereas lower-risk subjects received standard care. Higher-risk subjects' gestational ages at birth were shifted based on published efficacies, and dependent outcomes, calibrated using national datasets, were changed accordingly. Subjects otherwise retained their original TREETOP outcomes. Arms were compared using survival analysis for neonatal and maternal hospital length of stay, bootstrap intervals for neonatal cost, and Fisher's exact test for neonatal morbidity/mortality (significance, p < .05). RESULTS The model predicted improvements for all outcomes. RP-CM decreased neonatal and maternal hospital stay by 19% (p = .029) and 8.5% (p = .001), respectively; neonatal costs' point estimate by 16% (p = .098); and moderate-to-severe neonatal morbidity/mortality by 29% (p = .025). RP-MM strengthened observed reductions and significance. Point estimates of benefit did not differ by race/ethnicity. CONCLUSIONS Modeled evaluation of a biomarker-based test-and-treat strategy in a diverse population predicts clinically and economically meaningful improvements in neonatal and maternal outcomes.
Collapse
Affiliation(s)
| | - Glenn R Markenson
- Department of Obstetrics and Gynecology, Boston University School of Medicine, Boston, MA, USA
| | - George R Saade
- Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, TX, USA
| | - Louise C Laurent
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, CA, USA
| | - Kent D Heyborne
- Department of Obstetrics and Gynecology, Denver Health and Hospital Authority, Denver, CO, and Department of Obstetrics and Gynecology, University of Colorado Denver, Aurora, CO, USA
| | - Dean V Coonrod
- Department of Obstetrics and Gynecology, Valleywise Health, and Department of Obstetrics and Gynecology, University of Arizona College of Medicine, Phoenix, AZ, USA
| | - Corina N Schoen
- Department of Obstetrics and Gynecology, University of Massachusetts-Baystate, Springfield, MA, USA
| | - Jason K Baxter
- Department of Obstetrics and Gynecology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - David M Haas
- Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sherri A Longo
- Department of Obstetrics and Gynecology, Ochsner Health, New Orleans, LA, USA
| | - Scott A Sullivan
- Department of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, SC, USA
| | - Sarahn M Wheeler
- Department of Obstetrics and Gynecology, Duke University School of Medicine, Durham, NC, USA
| | - Leonardo M Pereira
- Department of Obstetrics and Gynecology, Oregon Health & Science University, Portland, OR, USA
| | - Kim A Boggess
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Angela F Hawk
- Regional Obstetrical Consultants, Chattanooga, TN, USA
| | - Amy H Crockett
- Department of Obstetrics and Gynecology, University of South Carolina School of Medicine Greenville and Prisma Health-Upstate, Greenville, SC, USA
| | - Ryan Treacy
- Sera Prognostics, Inc, Salt Lake City, UT, USA
| | | | | | | | | | | | - John A F Zupancic
- Department of Pediatrics, Harvard Medical School, and Department of Neonatology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | | |
Collapse
|
6
|
Khanam R, Fleischer TC, Boghossian NS, Nisar I, Dhingra U, Rahman S, Fox AC, Ilyas M, Dutta A, Naher N, Polpitiya AD, Mehmood U, Deb S, Choudhury AA, Badsha MB, Muhammad K, Ali SM, Ahmed S, Hickok DE, Iqbal N, Juma MH, Quaiyum MA, Boniface JJ, Yoshida S, Manu A, Bahl R, Jehan F, Sazawal S, Burchard J, Baqui AH. Performance of a validated spontaneous preterm delivery predictor in South Asian and Sub-Saharan African women: a nested case control study. J Matern Fetal Neonatal Med 2021; 35:8878-8886. [PMID: 34847802 DOI: 10.1080/14767058.2021.2005573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVES To address the disproportionate burden of preterm birth (PTB) in low- and middle-income countries, this study aimed to (1) verify the performance of the United States-validated spontaneous PTB (sPTB) predictor, comprised of the IBP4/SHBG protein ratio, in subjects from Bangladesh, Pakistan and Tanzania enrolled in the Alliance for Maternal and Newborn Health Improvement (AMANHI) biorepository study, and (2) discover biomarkers that improve performance of IBP4/SHBG in the AMANHI cohort. STUDY DESIGN The performance of the IBP4/SHBG biomarker was first evaluated in a nested case control validation study, then utilized in a follow-on discovery study performed on the same samples. Levels of serum proteins were measured by targeted mass spectrometry. Differences between the AMANHI and U.S. cohorts were adjusted using body mass index (BMI) and gestational age (GA) at blood draw as covariates. Prediction of sPTB < 37 weeks and < 34 weeks was assessed by area under the receiver operator curve (AUC). In the discovery phase, an artificial intelligence method selected additional protein biomarkers complementary to IBP4/SHBG in the AMANHI cohort. RESULTS The IBP4/SHBG biomarker significantly predicted sPTB < 37 weeks (n = 88 vs. 171 terms ≥ 37 weeks) after adjusting for BMI and GA at blood draw (AUC= 0.64, 95% CI: 0.57-0.71, p < .001). Performance was similar for sPTB < 34 weeks (n = 17 vs. 184 ≥ 34 weeks): AUC = 0.66, 95% CI: 0.51-0.82, p = .012. The discovery phase of the study showed that the addition of endoglin, prolactin, and tetranectin to the above model resulted in the prediction of sPTB < 37 with an AUC= 0.72 (95% CI: 0.66-0.79, p-value < .001) and prediction of sPTB < 34 with an AUC of 0.78 (95% CI: 0.67-0.90, p < .001). CONCLUSION A protein biomarker pair developed in the U.S. may have broader application in diverse non-U.S. populations.
Collapse
Affiliation(s)
- Rasheda Khanam
- Department of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, United States
| | | | - Nansi S Boghossian
- Department of Epidemiology and Biostatistics, University of South Carolina, Arnold School of Public Health, Columbia, United States
| | - Imran Nisar
- Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan
| | - Usha Dhingra
- Global Division, Center for Public Health Kinetics, New Delhi, India
| | | | - Angela C Fox
- Sera Prognostics, Inc., Salt Lake City, United States
| | - Muhammad Ilyas
- Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan
| | - Arup Dutta
- Global Division, Center for Public Health Kinetics, New Delhi, India
| | - Nurun Naher
- Projahnmo Research Foundation, Dhaka, Bangladesh
| | | | - Usma Mehmood
- Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan
| | - Saikat Deb
- Global Division, Center for Public Health Kinetics, New Delhi, India.,Public Health Laboratory-IDC, Pemba, Tanzania
| | | | | | - Karim Muhammad
- Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan
| | | | | | | | - Najeeha Iqbal
- Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan
| | | | - Md Abdul Quaiyum
- International Centre for Diarrheal Disease Research, Dhaka, Bangladesh
| | | | | | - Alexandar Manu
- World Health Organization (MCA/MRD), Geneva, Switzerland
| | - Rajiv Bahl
- World Health Organization (MCA/MRD), Geneva, Switzerland
| | - Fyezah Jehan
- Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan
| | - Sunil Sazawal
- Global Division, Center for Public Health Kinetics, New Delhi, India.,Public Health Laboratory-IDC, Pemba, Tanzania
| | | | - Abdullah H Baqui
- Department of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, United States
| |
Collapse
|
7
|
Burchard J, Polpitiya AD, Fox AC, Randolph TL, Fleischer TC, Dufford MT, Garite TJ, Critchfield GC, Boniface JJ, Saade GR, Kearney PE. Clinical Validation of a Proteomic Biomarker Threshold for Increased Risk of Spontaneous Preterm Birth and Associated Clinical Outcomes: A Replication Study. J Clin Med 2021; 10:5088. [PMID: 34768605 PMCID: PMC8584743 DOI: 10.3390/jcm10215088] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/20/2021] [Accepted: 10/22/2021] [Indexed: 12/22/2022] Open
Abstract
Preterm births are the leading cause of neonatal death in the United States. Previously, a spontaneous preterm birth (sPTB) predictor based on the ratio of two proteins, IBP4/SHBG, was validated as a predictor of sPTB in the Proteomic Assessment of Preterm Risk (PAPR) study. In particular, a proteomic biomarker threshold of -1.37, corresponding to a ~two-fold increase or ~15% risk of sPTB, significantly stratified earlier deliveries. Guidelines for molecular tests advise replication in a second independent study. Here we tested whether the significant association between proteomic biomarker scores above the threshold and sPTB, and associated adverse outcomes, was replicated in a second independent study, the Multicenter Assessment of a Spontaneous Preterm Birth Risk Predictor (TREETOP). The threshold significantly stratified subjects in PAPR and TREETOP for sPTB (p = 0.041, p = 0.041, respectively). Application of the threshold in a Kaplan-Meier analysis demonstrated significant stratification in each study, respectively, for gestational age at birth (p < 001, p = 0.0016) and rate of hospital discharge for both neonate (p < 0.001, p = 0.005) and mother (p < 0.001, p < 0.001). Above the threshold, severe neonatal morbidity/mortality and mortality alone were 2.2 (p = 0.0083,) and 7.4-fold higher (p = 0.018), respectively, in both studies combined. Thus, higher predictor scores were associated with multiple adverse pregnancy outcomes.
Collapse
Affiliation(s)
- Julja Burchard
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Ashoka D. Polpitiya
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Angela C. Fox
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Todd L. Randolph
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Tracey C. Fleischer
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Max T. Dufford
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Thomas J. Garite
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - Gregory C. Critchfield
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - J. Jay Boniface
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| | - George R. Saade
- Department of Obstetrics & Gynecology, University of Texas Medical Branch, Galveston, TX 77555, USA;
| | - Paul E. Kearney
- Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA; (J.B.); (A.D.P.); (A.C.F.); (T.L.R.); (M.T.D.); (T.J.G.); (G.C.C.); (J.J.B.); (P.E.K.)
| |
Collapse
|
8
|
Kaiser NK, Steers M, Nichols CM, Mellert H, Pestano GA. Design and Characterization of a Novel Blood Collection and Transportation Device for Proteomic Applications. Diagnostics (Basel) 2020; 10:E1032. [PMID: 33276497 PMCID: PMC7761483 DOI: 10.3390/diagnostics10121032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 11/27/2020] [Accepted: 11/30/2020] [Indexed: 11/29/2022] Open
Abstract
A major hurdle for blood-based proteomic diagnostics is efficient transport of specimens from the collection site to the testing laboratory. Dried blood spots have shown utility for diagnostic applications, specifically those where red blood cell hemolysis and contamination of specimens with hemoglobin is not confounding. Conversely, applications that are sensitive to the presence of the hemoglobin subunits require blood separation, which relies on centrifugation to collect plasma/serum, and then cold-chain custody during shipping. All these factors introduce complexities and potentially increased costs. Here we report on a novel whole blood-collection device (BCD) that efficiently separates the liquid from cellular components, minimizes hemolysis in the plasma fraction, and maintains protein integrity during ambient transport. The simplicity of the design makes the device ideal for field use. Whole blood is acquired through venipuncture and applied to the device with an exact volume pipette. The BCD design was based on lateral-flow principles in which whole blood was applied to a defined area, allowing two minutes for blood absorption into the separation membrane, then closed for shipment. The diagnostic utility of the device was further demonstrated with shipments from multiple sites (n = 33) across the U.S. sent to two different centralized laboratories for analyses using liquid chromatography/mass spectrometry (LC/MS/MS) and matrix assisted laser desorption/ionization-time of flight (MALDI-ToF) commercial assays. Specimens showed high levels of result label concordance for the LC/MS/MS assay (Negative Predictive Value = 98%) and MALDI-ToF assay (100% result concordance). The overall goal of the device is to simplify specimen transport to the laboratory and produce clinical test results equivalent to established collection methods.
Collapse
Affiliation(s)
- Nathan K. Kaiser
- Biodesix Inc., 2970 Wilderness Place Suite 100, Boulder, CO 80301, USA; (M.S.); (C.M.N.); (H.M.); (G.A.P.)
| | | | | | | | | |
Collapse
|
9
|
Cerciello F, Choi M, Sinicropi-Yao SL, Lomeo K, Amann JM, Felley-Bosco E, Stahel RA, Robinson BWS, Creaney J, Pass HI, Vitek O, Carbone DP. Verification of a Blood-Based Targeted Proteomics Signature for Malignant Pleural Mesothelioma. Cancer Epidemiol Biomarkers Prev 2020; 29:1973-1982. [PMID: 32732250 PMCID: PMC7541795 DOI: 10.1158/1055-9965.epi-20-0543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 06/18/2020] [Accepted: 07/27/2020] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND We have verified a mass spectrometry (MS)-based targeted proteomics signature for the detection of malignant pleural mesothelioma (MPM) from the blood. METHODS A seven-peptide biomarker MPM signature by targeted proteomics in serum was identified in a previous independent study. Here, we have verified the predictive accuracy of a reduced version of that signature, now composed of six-peptide biomarkers. We have applied liquid chromatography-selected reaction monitoring (LC-SRM), also known as multiple-reaction monitoring (MRM), for the investigation of 402 serum samples from 213 patients with MPM and 189 cancer-free asbestos-exposed donors from the United States, Australia, and Europe. RESULTS Each of the biomarkers composing the signature was independently informative, with no apparent functional or physical relation to each other. The multiplexing possibility offered by MS proteomics allowed their integration into a single signature with a higher discriminating capacity than that of the single biomarkers alone. The strategy allowed in this way to increase their potential utility for clinical decisions. The signature discriminated patients with MPM and asbestos-exposed donors with AUC of 0.738. For early-stage MPM, AUC was 0.765. This signature was also prognostic, and Kaplan-Meier analysis showed a significant difference between high- and low-risk groups with an HR of 1.659 (95% CI, 1.075-2.562; P = 0.021). CONCLUSIONS Targeted proteomics allowed the development of a multianalyte signature with diagnostic and prognostic potential for MPM from the blood. IMPACT The proteomic signature represents an additional diagnostic approach for informing clinical decisions for patients at risk for MPM.
Collapse
Affiliation(s)
- Ferdinando Cerciello
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio.
| | - Meena Choi
- College of Computer and Information Science, Northeastern University, Boston, Massachusetts
| | - Sara L Sinicropi-Yao
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio
| | - Katie Lomeo
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio
| | - Joseph M Amann
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio
| | - Emanuela Felley-Bosco
- Laboratory of Molecular Oncology, Division of Thoracic Surgery, University Hospital Zürich, Zürich, Switzerland
| | - Rolf A Stahel
- Department of Oncology, Center of Hematology and Oncology, Comprehensive Cancer Center Zürich, University Hospital Zürich, Zürich, Switzerland
| | - Bruce W S Robinson
- National Centre for Asbestos Related Disease, University of Western Australia, School of Medicine and Pharmacology, Nedlands, Western Australia
| | - Jenette Creaney
- National Centre for Asbestos Related Disease, University of Western Australia, School of Medicine and Pharmacology, Nedlands, Western Australia
| | - Harvey I Pass
- New York University, Langone Medical Center, New York, New York
| | - Olga Vitek
- College of Computer and Information Science, Northeastern University, Boston, Massachusetts
| | - David P Carbone
- James Thoracic Center, James Cancer Center, The Ohio State University Medical Center, Columbus, Ohio.
| |
Collapse
|
10
|
Markenson GR, Saade GR, Laurent LC, Heyborne KD, Coonrod DV, Schoen CN, Baxter JK, Haas DM, Longo S, Grobman WA, Sullivan SA, Major CA, Wheeler SM, Pereira LM, Su EJ, Boggess KA, Hawk AF, Crockett AH, Fox AC, Polpitiya A, Fleischer TC, Critchfield GC, Burchard J, Boniface JJ, Lam GK. Performance of a proteomic preterm delivery predictor in a large independent prospective cohort. Am J Obstet Gynecol MFM 2020; 2:100140. [PMID: 33345877 DOI: 10.1016/j.ajogmf.2020.100140] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 05/05/2020] [Accepted: 05/06/2020] [Indexed: 12/22/2022]
Abstract
BACKGROUND Preterm birth remains a common and devastating complication of pregnancy. There remains a need for effective and accurate screening methods for preterm birth. Using a proteomic approach, we previously discovered and validated (Proteomic Assessment of Preterm Risk study, NCT01371019) a preterm birth predictor comprising a ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin. OBJECTIVE To determine the performance of the ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin to predict both spontaneous and medically indicated very preterm births, in an independent cohort distinct from the one in which it was developed. STUDY DESIGN This was a prospective observational study (Multicenter Assessment of a Spontaneous Preterm Birth Risk Predictor, NCT02787213) at 18 sites in the United States. Women had blood drawn at 170/7 to 216/7 weeks' gestation. For confirmation, we planned to analyze a randomly selected subgroup of women having blood drawn between 191/7 and 206/7 weeks' gestation, with the results of the remaining study participants blinded for future validation studies. Serum from participants was analyzed by mass spectrometry. Neonatal morbidity and mortality were analyzed using a composite score by a method from the PREGNANT trial (NCT00615550, Hassan et al). Scores of 0-3 reflect increasing numbers of morbidities or length of neonatal intensive care unit stay, and 4 represents perinatal mortality. RESULTS A total of 5011 women were enrolled, with 847 included in this planned substudy analysis. There were 9 preterm birth cases at <320/7 weeks' gestation and 838 noncases at ≥320/7 weeks' gestation; 21 of 847 infants had neonatal composite morbidity and mortality index scores of ≥3, and 4 of 21 had a score of 4. The ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin ratio was substantially higher in both preterm births at <320/7 weeks' gestation and there were more severe neonatal outcomes. The ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin ratio was significantly predictive of birth at <320/7 weeks' gestation (area under the receiver operating characteristic curve, 0.71; 95% confidence interval, 0.55-0.87; P=.016). Stratification by body mass index, optimized in the previous validation study (22<body mass index≤37 kg/m2), resulted in an area under the receiver operating characteristic curve of 0.76 (95% confidence interval, 0.59-0.93; P=.023). The ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin ratio predicted neonatal outcomes with respective area under the receiver operating characteristic curve of 0.67 (95% confidence interval, 0.57-0.77; P=.005) and 0.78 (95% confidence interval, 0.63-0.93; P=.026) for neonatal composite morbidity and mortality scores of ≥3 or 4. In addition, the ratio of insulin-like growth factor-binding protein 4 to sex hormone binding globulin significantly stratified neonates with increased length of hospital stay (log rank P=.023). CONCLUSION We confirmed in an independent cohort the ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin ratio as a predictor of very preterm birth, with additional prediction of increased length of neonatal hospital stay and increased severity of adverse neonatal outcomes. Potential uses of the ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin predictor may be to risk stratify patients for implementation of preterm birth preventive strategies and direct patients to appropriate levels of care.
Collapse
Affiliation(s)
- Glenn R Markenson
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Boston Medical Center, Boston, MA
| | - George R Saade
- Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, TX
| | - Louise C Laurent
- Division of Maternal-Fetal Medicine, Department of Reproductive Sciences, University of California, San Diego, CA
| | - Kent D Heyborne
- Department of Obstetrics and Gynecology, Denver Health and Hospital Authority
| | - Dean V Coonrod
- Department of Obstetrics and Gynecology, Maricopa Integrated Health System
| | - Corina N Schoen
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Massachusetts-Baystate
| | - Jason K Baxter
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Thomas Jefferson University Hospital
| | - David M Haas
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Indiana University
| | - Sherri Longo
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Ochsner Baptist Medical Center, New Orleans, LA
| | - William A Grobman
- Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Scott A Sullivan
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, SC
| | - Carol A Major
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of California, Irvine, CA
| | - Sarahn M Wheeler
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Duke University, Durham, NC
| | - Leonardo M Pereira
- Division Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Oregon Health and Science University, Portland, OR
| | - Emily J Su
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado School of Medicine, Aurora, CO
| | - Kim A Boggess
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of North Carolina, Chapel Hill, NC
| | | | - Amy H Crockett
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Greenville Health System, Greenville, SC
| | | | | | | | | | | | | | | |
Collapse
|
11
|
Kearney P, Boniface JJ, Price ND, Hood L. The building blocks of successful translation of proteomics to the clinic. Curr Opin Biotechnol 2018; 51:123-129. [PMID: 29427919 PMCID: PMC6091638 DOI: 10.1016/j.copbio.2017.12.011] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2017] [Accepted: 12/11/2017] [Indexed: 11/28/2022]
Abstract
Recently, the first two multiplexed tests using selective reaction monitoring (SRM-MS) mass spectrometry have entered clinical practice. Despite different areas of indication, risk stratification in lung cancer and preterm birth, they share multiple steps in their development strategies. Here we review these strategies and their implications for successful translation of biomarkers to clinical practice. We believe that the identification of blood protein panels for the identification of disease phenotypes is now a reproducible and standard (albeit complex) process.
Collapse
Affiliation(s)
- Paul Kearney
- Integrated Diagnostics, Seattle, WA, United States
| | | | - Nathan D Price
- Institute for Systems Biology, Seattle, WA, United States
| | - Leroy Hood
- Institute for Systems Biology, Seattle, WA, United States.
| |
Collapse
|