Daniel C Bartos

Dr. Daniel C Bartos

Agios Pharmaceuticals (United States), Cambridge, Maryland, USA
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 March 2017 in The Journal of Physiology
Verified
Journal Article
Closed access
PDF file
DBDaniel C Bartos
Daniel C Bartos
SMStefano Morotti
Stefano Morotti
KGKenneth S. Ginsburg
Kenneth S. Ginsburg
EGEleonora Grandi
Eleonora Grandi
DBDonald Bers
Donald Bers

Verified
Journal Article
Open access
PDF file
PKPeter Kekenes-Huskey
Peter Kekenes-Huskey
DBDon E. Burgess
Don E. Burgess
BSBin Sun
Bin Sun
DBDaniel C Bartos
Daniel C Bartos
EREzekiel R. Rozmus
Ezekiel R. Rozmus
Brian P. DelisleBrian P. Delisle
Brian P. Delisle
The electrocardiogram (ECG) empowered clinician scientists to measure the electrical activity of the heart noninvasively to identify arrhythmias and heart disease. Shortly after the standardization of the 12-lead ECG for the diagnosis of heart disease, several families with autosomal recessive (Jervell and Lange-Nielsen Syndrome) and dominant (Romano–Ward Syndrome) forms of long QT syndrome (LQTS) were identified. An abnormally long heart rate-corrected QT-interval was established as a biomarker for the risk of sudden cardiac death. Since then, the International LQTS Registry was established; a phenotypic scoring system to identify LQTS patients was developed; the major genes that associate with typical forms of LQTS were identified; and guidelines for the successful management of patients advanced. In this review, we discuss the molecular and cellular mechanisms for LQTS associated with missense variants in KCNQ1 (LQT1) and KCNH2 (LQT2). We move beyond the “benign” to a “pathogenic” binary classification scheme for different KCNQ1 and KCNH2 missense variants and discuss gene- and mutation-specific differences in K+ channel dysfunction, which can predispose people to distinct clinical phenotypes (e.g., concealed, pleiotropic, severe, etc.). We conclude by discussing the emerging computational structural modeling strategies that will distinguish between dysfunctional subtypes of KCNQ1 and KCNH2 variants, with the goal of realizing a layered precision medicine approach focused on individuals.

1 February 2017 in Biophysical Journal
Verified
Journal Article
Closed access
ZLZhandi Liao
Zhandi Liao
KGKenneth S. Ginsburg
Kenneth S. Ginsburg
DBDaniel C Bartos
Daniel C Bartos
YJYanyan Jiang
Yanyan Jiang
SDSanda Despa
Sanda Despa
DBDonald Bers
Donald Bers

1 January 2015 in Biophysical Journal
Verified
Journal Article
Closed access
DBDaniel C Bartos
Daniel C Bartos
SMStefano Morotti
Stefano Morotti
KGKenneth S. Ginsburg
Kenneth S. Ginsburg
EGEleonora Grandi
Eleonora Grandi
DBDonald Bers
Donald Bers