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 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:

Family History Assessment Significantly Enhances Delivery of Precision Medicine in the Genomics Era

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs, with less emphasis on family history assessment. We evaluated the utility of family history for genomic sequencing selection.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We analysed whole genome sequences of 1750 healthy research participants, with and without preselection based on standardised family history collection, screening 95 cancer genes.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The frequency of likely pathogenic/ pathogenic (LP/P) variants in 884 participants with no family history available (FH not available group) (2%) versus 866 participants with family history available (FH available group) (3.1%) was not significant (<jats:italic>p</jats:italic>=0.158). However, within the FH available group, amongst 73 participants with an increased family history cancer risk (increased FH risk), 1 in 7 participants carried a LP/P variant inferring a six-fold increase compared with 1 in 47 participants assessed at average family history cancer risk (average FH risk) and a seven-fold increase compared to the FH not available group. The enrichment was further pronounced (up to 18-fold) when assessing the 25 cancer genes in the ACMG 59-gene panel. Furthermore, 63 participants had an increased family history cancer risk in absence of an apparent LP/P variant.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Our findings show that systematic family history collection remains critical for health risk assessment, providing important actionable data and augmenting the yield from genomic data. Family history also highlights the potential impact of additional hereditary, environmental and behavioural influences not reflected by genomic sequencing.</jats:p></jats:sec>
Authors
Bylstra, Y; Lim, WK; Kam, S; Tham, KW; Wu, RR; Teo, JX; Davila, S; Kuan, JL; Chan, SH; Bertin, N; Yang, C; Rozen, S; Teh, BT; Yeo, KK; Cook, SA; Orlando, LA; Jamuar, SS; Ginsburg, GS; Tan, P
MLA Citation
Bylstra, Yasmin, et al. Family History Assessment Significantly Enhances Delivery of Precision Medicine in the Genomics Era. Cold Spring Harbor Laboratory. Crossref, doi:10.1101/2020.01.29.926139.
URI
https://scholars.duke.edu/individual/pub1465251
Source
crossref
DOI
10.1101/2020.01.29.926139

At the intersection of precision medicine and population health: an implementation-effectiveness study of family health history based systematic risk assessment in primary care.

BACKGROUND: Risk assessment is a precision medicine technique that can be used to enhance population health when applied to prevention. Several barriers limit the uptake of risk assessment in health care systems; and little is known about the potential impact that adoption of systematic risk assessment for screening and prevention in the primary care population might have. Here we present results of a first of its kind multi-institutional study of a precision medicine tool for systematic risk assessment. METHODS: We undertook an implementation-effectiveness trial of systematic risk assessment of primary care patients in 19 primary care clinics at four geographically and culturally diverse healthcare systems. All adult English or Spanish speaking patients were invited to enter personal and family health history data into MeTree, a patient-facing family health history driven risk assessment program, for 27 medical conditions. Risk assessment recommendations followed evidence-based guidelines for identifying and managing those at increased disease risk. RESULTS: One thousand eight hundred eighty-nine participants completed MeTree, entering information on N = 25,967 individuals. Mean relatives entered = 13.7 (SD 7.9), range 7-74. N = 1443 (76.4%) participants received increased risk recommendations: 597 (31.6%) for monogenic hereditary conditions, 508 (26.9%) for familial-level risk, and 1056 (56.1%) for risk of a common chronic disease. There were 6617 recommendations given across the 1443 participants. In multivariate analysis, only the total number of relatives entered was significantly associated with receiving a recommendation. CONCLUSIONS: A significant percentage of the general primary care population meet criteria for more intensive risk management. In particular 46% for monogenic hereditary and familial level disease risk. Adopting strategies to facilitate systematic risk assessment in primary care could have a significant impact on populations within the U.S. and even beyond. TRIAL REGISTRATION: Clinicaltrials.gov number NCT01956773 , registered 10/8/2013.
Authors
Orlando, LA; Wu, RR; Myers, RA; Neuner, J; McCarty, C; Haller, IV; Harry, M; Fulda, KG; Dimmock, D; Rakhra-Burris, T; Buchanan, A; Ginsburg, GS
MLA Citation
Orlando, Lori A., et al. “At the intersection of precision medicine and population health: an implementation-effectiveness study of family health history based systematic risk assessment in primary care.Bmc Health Serv Res, vol. 20, no. 1, Nov. 2020, p. 1015. Pubmed, doi:10.1186/s12913-020-05868-1.
URI
https://scholars.duke.edu/individual/pub1464364
PMID
33160339
Source
pubmed
Published In
Bmc Health Services Research
Volume
20
Published Date
Start Page
1015
DOI
10.1186/s12913-020-05868-1

Association of Metabolic Phenotypes With Coronary Artery Disease and Cardiovascular Events in Patients With Stable Chest Pain.

OBJECTIVE: Obesity and metabolic syndrome are associated with major adverse cardiovascular events (MACE). However, whether distinct metabolic phenotypes differ in risk for coronary artery disease (CAD) and MACE is unknown. We sought to determine the association of distinct metabolic phenotypes with CAD and MACE. RESEARCH DESIGN AND METHODS: We included patients from the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) who underwent coronary computed tomography (CT) angiography. Obesity was defined as a BMI ≥30 kg/m2 and metabolically healthy as less than or equal to one metabolic syndrome component except diabetes, distinguishing four metabolic phenotypes: metabolically healthy/unhealthy and nonobese/obese (MHN, MHO, MUN, and MUO). Differences in severe calcification (coronary artery calcification [CAC] ≥400), severe CAD (≥70% stenosis), high-risk plaque (HRP), and MACE were assessed using adjusted logistic and Cox regression models. RESULTS: Of 4,381 patients (48.4% male, 60.5 ± 8.1 years of age), 49.4% were metabolically healthy (30.7% MHN and 18.7% MHO) and 50.6% unhealthy (22.3% MUN and 28.4% MUO). MHO had similar coronary CT findings as compared with MHN (severe CAC/CAD and HRP; P > 0.36 for all). Among metabolically unhealthy patients, those with obesity had similar CT findings as compared with nonobese (P > 0.10 for all). However, both MUN and MUO had unfavorable CAD characteristics as compared with MHN (P ≤ 0.017 for all). A total of 130 events occurred during follow-up (median 26 months). Compared with MHN, MUN (hazard ratio [HR] 1.61 [95% CI 1.02-2.53]) but not MHO (HR 1.06 [0.62-1.82]) or MUO (HR 1.06 [0.66-1.72]) had higher risk for MACE. CONCLUSIONS: In patients with stable chest pain, four metabolic phenotypes exhibit distinctly different CAD characteristics and risk for MACE. Individuals who are metabolically unhealthy despite not being obese were at highest risk in our cohort.
Authors
Kammerlander, AA; Mayrhofer, T; Ferencik, M; Pagidipati, NJ; Karady, J; Ginsburg, GS; Lu, MT; Bittner, DO; Puchner, SB; Bihlmeyer, NA; Meyersohn, NM; Emami, H; Shah, SH; Douglas, PS; Hoffmann, U; PROMISE Investigators,
MLA Citation
Kammerlander, Andreas A., et al. “Association of Metabolic Phenotypes With Coronary Artery Disease and Cardiovascular Events in Patients With Stable Chest Pain.Diabetes Care, vol. 44, no. 4, Apr. 2021, pp. 1038–45. Pubmed, doi:10.2337/dc20-1760.
URI
https://scholars.duke.edu/individual/pub1473667
PMID
33558267
Source
pubmed
Published In
Diabetes Care
Volume
44
Published Date
Start Page
1038
End Page
1045
DOI
10.2337/dc20-1760

Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network.

PURPOSE: A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. METHODS: The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. RESULTS: Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. CONCLUSION: IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers.
Authors
Ginsburg, GS; Cavallari, LH; Chakraborty, H; Cooper-DeHoff, RM; Dexter, PR; Eadon, MT; Ferket, BS; Horowitz, CR; Johnson, JA; Kannry, J; Kucher, N; Madden, EB; Orlando, LA; Parker, W; Peterson, J; Pratt, VM; Rakhra-Burris, TK; Ramos, MA; Skaar, TC; Sperber, N; Steen-Burrell, K-A; Van Driest, SL; Voora, D; Wiisanen, K; Winterstein, AG; Volpi, S; IGNITE PTN,
MLA Citation
Ginsburg, Geoffrey S., et al. “Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network.Genet Med, Mar. 2021. Pubmed, doi:10.1038/s41436-021-01118-9.
URI
https://scholars.duke.edu/individual/pub1477403
PMID
33782552
Source
pubmed
Published In
Genet Med
Published Date
DOI
10.1038/s41436-021-01118-9

Biomarker Profiling for Obstructive Coronary Artery Disease: A PROMISE Substudy

Authors
Jr, LAT; Zhbannikov, I; Douglas, PS; Hoffman, U; Ferencik, M; Shah, S; Kraus, W; Cooper, L; Voora, D; Ginsburg, GS
MLA Citation
Jr, Limkakeng A. T., et al. “Biomarker Profiling for Obstructive Coronary Artery Disease: A PROMISE Substudy.” Annals of Emergency Medicine, vol. 76, no. 4, 2020, pp. S116–S116.
URI
https://scholars.duke.edu/individual/pub1467150
Source
wos-lite
Published In
Annals of Emergency Medicine
Volume
76
Published Date
Start Page
S116
End Page
S116

Research Areas:

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