Geoffrey Ginsburg

Overview:

Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms for developing and translating genomic information into medical practice and the integration of personalized medicine into health care.

Positions:

Professor of Medicine

Medicine, Cardiology
School of Medicine

Director of Duke Center for Applied Genomics and Precision Medicine

Duke Center for Applied Genomics and Precision Medicine
School of Medicine

Professor in Pathology

Pathology
School of Medicine

Professor of Biostatistics and Bioinformatics

Biostatistics & Bioinformatics
School of Medicine

Professor in the School of Nursing

School of Nursing
School of Nursing

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

M.D. 1984

Boston University

Ph.D. 1984

Boston University

Medical Resident, Medicine

Beth Israel Deaconess Medical Center

Fellow in Cardiology, Medicine

Beth Israel Deaconess Medical Center

Research Fellow in Cardiology, Medicine

Children's Hospital Boston

Grants:

Building and Deploying a Genomic-Medicine Risk Assessment Model for Diverse Primary Care Populations.

Administered By
Duke Center for Applied Genomics and Precision Medicine
Awarded By
National Institutes of Health
Role
Investigator
Start Date
End Date

The IGNITE II CC: Engagement, Coordination, Demonstration, and Dissemination

Administered By
Duke Center for Applied Genomics and Precision Medicine
Awarded By
National Institutes of Health
Role
Principal Investigator
Start Date
End Date

The IGNITE II CC: Engagement, Coordination, Demonstration, and Dissemination

Administered By
Duke Center for Applied Genomics and Precision Medicine
Awarded By
National Institutes of Health
Role
Principal Investigator
Start Date
End Date

The Role of Junctophilin Type 2 in Cardiac Node Automaticity

Administered By
Pediatrics, Cardiology
Awarded By
National Institutes of Health
Role
Mentor
Start Date
End Date

Predicting prebiotic effects on human microbiota, behavior, and cognition.

Administered By
Molecular Genetics and Microbiology
Awarded By
Office of Naval Research
Role
Collaborator
Start Date
End Date

Publications:

Utility of High-Sensitivity Troponin Among Stable Patients With Chest Pain Undergoing Stress Imaging (from PROMISE).

Authors
Sharma, A; Januzzi, JL; Suchindran, S; Coles, A; Hoffmann, U; Ferencik, M; Patel, MR; Ginsburg, GS; Douglas, PS
MLA Citation
Sharma, Abhinav, et al. “Utility of High-Sensitivity Troponin Among Stable Patients With Chest Pain Undergoing Stress Imaging (from PROMISE).Am J Cardiol, vol. 158, Nov. 2021, pp. 148–49. Pubmed, doi:10.1016/j.amjcard.2021.07.032.
URI
https://scholars.duke.edu/individual/pub1496137
PMID
34454709
Source
pubmed
Published In
Am J Cardiol
Volume
158
Published Date
Start Page
148
End Page
149
DOI
10.1016/j.amjcard.2021.07.032

Experience and Perceptions of a Family Health History Risk Assessment Tool among Multi-Ethnic Asian Breast Cancer Patients.

A family health history-based risk assessment is particularly valuable for guiding cancer screening and treatment strategies, yet an optimal implementation depends upon end-users' values and needs. This is not only true prior to disease development, but also for those already affected. The aim of this study is to explore perceptions of the value of knowing one's family health history (FHH)-based risk, experience using a patient-facing FHH tool and the potential of the tool for wider implementation. Twenty multi-ethnic Asian patients undergoing breast cancer treatment in Singapore completed an FHH-based risk assessment. Semi-structured one-on-one interviews were conducted and data were thematically analyzed. All participants were female and slightly more than half were Chinese. The acceptance and usage of an FHH risk assessment tool for cancers and its broader implementation was affected by a perceived importance of personal control over early detection, patient concerns of anxiety for themselves and their families due to risk results, concerns for genetic discrimination, adequacy of follow-up care plans and Asian cultural beliefs toward disease and dying. This study uniquely sheds light on the factors affecting Asian breast cancer patients' perceptions about undergoing an FHH-based risk assessment, which should inform steps for a broader implementation in Asian healthcare systems.
Authors
Yoon, S; Goh, H; Fung, SM; Tang, S; Matchar, D; Ginsburg, GS; Orlando, LA; Ngeow, J; Wu, RR
MLA Citation
Yoon, Sungwon, et al. “Experience and Perceptions of a Family Health History Risk Assessment Tool among Multi-Ethnic Asian Breast Cancer Patients.J Pers Med, vol. 11, no. 10, Oct. 2021. Pubmed, doi:10.3390/jpm11101046.
URI
https://scholars.duke.edu/individual/pub1499265
PMID
34683187
Source
pubmed
Published In
Journal of Personalized Medicine
Volume
11
Published Date
DOI
10.3390/jpm11101046

Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.

OBJECTIVES: Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test. DESIGN: Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results. SETTING: Four U.S. emergency departments. PATIENTS: Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis. INTERVENTIONS: Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes. MEASUREMENTS AND MAIN RESULTS: Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance. CONCLUSIONS: The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.
Authors
Tsalik, EL; Henao, R; Montgomery, JL; Nawrocki, JW; Aydin, M; Lydon, EC; Ko, ER; Petzold, E; Nicholson, BP; Cairns, CB; Glickman, SW; Quackenbush, E; Kingsmore, SF; Jaehne, AK; Rivers, EP; Langley, RJ; Fowler, VG; McClain, MT; Crisp, RJ; Ginsburg, GS; Burke, TW; Hemmert, AC; Woods, CW; Antibacterial Resistance Leadership Group,
MLA Citation
Tsalik, Ephraim L., et al. “Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.Crit Care Med, vol. 49, no. 10, Oct. 2021, pp. 1651–63. Pubmed, doi:10.1097/CCM.0000000000005085.
URI
https://scholars.duke.edu/individual/pub1481895
PMID
33938716
Source
pubmed
Published In
Crit Care Med
Volume
49
Published Date
Start Page
1651
End Page
1663
DOI
10.1097/CCM.0000000000005085

The National Academies' Roundtable on Genomics and Precision Health: Where we have been and where we are heading.

The clinical application of genetics and genomics to advance precision health is one of the most dynamic and promising areas of medicine. In 2020, building on nearly 15 years of work, the Roundtable on Genomics and Precision Health of the National Academies of Sciences, Engineering, and Medicine undertook a strategic planning process to assess its strengths, consider the current challenges facing the field, and set out new goals for its future work. As a result, the Roundtable has updated its vision and mission and prioritized four major areas of inquiry-innovation, dialogue, equity, and adoption-while keeping true to its founding goal of providing a neutral convening space for the diversity of stakeholders in genomics and precision health. The Roundtable is unique for its breadth of membership and is committed to fostering a new era for precision health built on decades of expanding knowledge and the emergence of new technologies. To achieve its goals, the Roundtable seeks to broaden its membership's diversity and to engage with new audiences. Roundtable members explore how evidence-based discoveries in genomics could be adopted and used in innovative ways to better serve human health, how equitable access to genomic and precision health technologies can be ensured, and how the Roundtable and broader genomics and precision health community can communicate more effectively to inform the public regarding genomics and precision health. As a first principle, the Roundtable is working to support the overall goal that all people benefit from genomics for precision health.
Authors
Ginsburg, G; Penny, M; Feero, WG; Miller, M; Addie, S; Beachy, SH
MLA Citation
Ginsburg, Geoffrey, et al. “The National Academies' Roundtable on Genomics and Precision Health: Where we have been and where we are heading.American Journal of Human Genetics, vol. 108, no. 10, Oct. 2021, pp. 1817–22. Epmc, doi:10.1016/j.ajhg.2021.08.015.
URI
https://scholars.duke.edu/individual/pub1499667
PMID
34626581
Source
epmc
Published In
American Journal of Human Genetics
Volume
108
Published Date
Start Page
1817
End Page
1822
DOI
10.1016/j.ajhg.2021.08.015

Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset.

Importance: Currently, there are no presymptomatic screening methods to identify individuals infected with a respiratory virus to prevent disease spread and to predict their trajectory for resource allocation. Objective: To evaluate the feasibility of using noninvasive, wrist-worn wearable biometric monitoring sensors to detect presymptomatic viral infection after exposure and predict infection severity in patients exposed to H1N1 influenza or human rhinovirus. Design, Setting, and Participants: The cohort H1N1 viral challenge study was conducted during 2018; data were collected from September 11, 2017, to May 4, 2018. The cohort rhinovirus challenge study was conducted during 2015; data were collected from September 14 to 21, 2015. A total of 39 adult participants were recruited for the H1N1 challenge study, and 24 adult participants were recruited for the rhinovirus challenge study. Exclusion criteria for both challenges included chronic respiratory illness and high levels of serum antibodies. Participants in the H1N1 challenge study were isolated in a clinic for a minimum of 8 days after inoculation. The rhinovirus challenge took place on a college campus, and participants were not isolated. Exposures: Participants in the H1N1 challenge study were inoculated via intranasal drops of diluted influenza A/California/03/09 (H1N1) virus with a mean count of 106 using the median tissue culture infectious dose (TCID50) assay. Participants in the rhinovirus challenge study were inoculated via intranasal drops of diluted human rhinovirus strain type 16 with a count of 100 using the TCID50 assay. Main Outcomes and Measures: The primary outcome measures included cross-validated performance metrics of random forest models to screen for presymptomatic infection and predict infection severity, including accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). Results: A total of 31 participants with H1N1 (24 men [77.4%]; mean [SD] age, 34.7 [12.3] years) and 18 participants with rhinovirus (11 men [61.1%]; mean [SD] age, 21.7 [3.1] years) were included in the analysis after data preprocessing. Separate H1N1 and rhinovirus detection models, using only data on wearble devices as input, were able to distinguish between infection and noninfection with accuracies of up to 92% for H1N1 (90% precision, 90% sensitivity, 93% specificity, and 90% F1 score, 0.85 [95% CI, 0.70-1.00] AUC) and 88% for rhinovirus (100% precision, 78% sensitivity, 100% specificity, 88% F1 score, and 0.96 [95% CI, 0.85-1.00] AUC). The infection severity prediction model was able to distinguish between mild and moderate infection 24 hours prior to symptom onset with an accuracy of 90% for H1N1 (88% precision, 88% sensitivity, 92% specificity, 88% F1 score, and 0.88 [95% CI, 0.72-1.00] AUC) and 89% for rhinovirus (100% precision, 75% sensitivity, 100% specificity, 86% F1 score, and 0.95 [95% CI, 0.79-1.00] AUC). Conclusions and Relevance: This cohort study suggests that the use of a noninvasive, wrist-worn wearable device to predict an individual's response to viral exposure prior to symptoms is feasible. Harnessing this technology would support early interventions to limit presymptomatic spread of viral respiratory infections, which is timely in the era of COVID-19.
Authors
Grzesiak, E; Bent, B; McClain, MT; Woods, CW; Tsalik, EL; Nicholson, BP; Veldman, T; Burke, TW; Gardener, Z; Bergstrom, E; Turner, RB; Chiu, C; Doraiswamy, PM; Hero, A; Henao, R; Ginsburg, GS; Dunn, J
MLA Citation
Grzesiak, Emilia, et al. “Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset.Jama Netw Open, vol. 4, no. 9, Sept. 2021, p. e2128534. Pubmed, doi:10.1001/jamanetworkopen.2021.28534.
URI
https://scholars.duke.edu/individual/pub1498711
PMID
34586364
Source
pubmed
Published In
Jama Network Open
Volume
4
Published Date
Start Page
e2128534
DOI
10.1001/jamanetworkopen.2021.28534

Research Areas:

Antigens
Biological Assay
Biosensing Techniques
Cytoskeletal Proteins
Immune System
Membrane Proteins
Nucleic Acid Hybridization
Pneumonia, Viral