Heart's inner mechanisms to be studied with NIH grant

February 25, 2015

Jianmin Cui, PhD, has received a nearly $1.7 million grant from the National Institutes of Health to study the molecular bases for the function of potassium channels vital for the heart, brain, inner ear and other tissues.

The five-year grant from the National Institute of Neurological Disorders and Stroke will allow Cui, professor of biomedical engineering in the School of Engineering & Applied Science at Washington University in St. Louis, to take a close look at some of the mutations in the potassium ion channels KCNQ1 and KCNE1 and their roles in cardiac disorders, including Long QT syndrome and cardiac arrhythmia.

In the heart, KCNQ1 works with KCNE1, an accessory subunit. When the two are put together, the combination changes the properties of the KCNQ1 channel so dramatically that scientists were once misled to believe that KCNE1 formed an entirely new channel on its own, rather than modifying an existing one. KCNQ1 is so important to the heart's rhythm that there are more than 250 mutations of the channel that have been associated with cardiac arrhythmia.

Specifically, Cui will analyze the mechanisms underlying the properties of these potassium ion channels, which will provide more insight into the diseases associated with the mutations. By better understanding these fundamentals, researchers will be able to develop better treatments that target the channels in the heart without affecting the same channels in the gut, thyroid or brain.

Cui proposes that a novel mechanism for activating KCNQ1 is behind these disorders, which can be fatal. Patients with Long QT syndrome who have mutations in KCNQ1 often experience symptoms of cardiac arrhythmia, such as fainting or sudden death, during exercise. Therefore, this study is significant to better understand long QT syndrome, Cui said.
-end-
For more information on Cui's research, visit here. The School of Engineering & Applied Science at Washington University in St. Louis focuses intellectual efforts through a new convergence paradigm and builds on strengths, particularly as applied to medicine and health, energy and environment, entrepreneurship and security. With 91 tenured/tenure-track and 40 additional full-time faculty, 1,300 undergraduate students, more than 900 graduate students and more than 23,000 alumni, we are working to leverage our partnerships with academic and industry partners -- across disciplines and across the world -- to contribute to solving the greatest global challenges of the 21st century.

Washington University in St. Louis

Related Mutations Articles from Brightsurf:

SARS-CoV-2 mutations do not appear to increase transmissibility
None of the mutations currently documented in the SARS-CoV-2 virus appear to increase its transmissibility in humans, according to a study led by UCL researchers, published in Nature Communications.

Predicting the evolution of genetic mutations
CSHL quantitative biologists have designed a new machine learning technique for predicting evolutionary pathways.

SNIPRs take aim at disease-related mutations
In a new study, lead author Alex Green, a researcher at the Biodesign Center for Molecular Design and Biomimetics and his colleagues describe a new method for detecting point mutations.

Cancer mutations occur decades before diagnosis
A large-scale pan-cancer analysis of the evolutionary history of tumours reveals that cancer-causing mutations occur decades before diagnosis.

Pinpointing rare disease mutations
Scientists have compiled mouse and human cell knockout data to categorise genes based on how essential they are for survival and organism development.

Using deep learning to predict disease-associated mutations
A research team led by Professor Hongzhe Sun from the Department of Chemistry at HKU, implemented a robust deep learning approach to predict disease-associated mutations of the metal-binding sites in a protein.

Cancer: The origin of genetic mutations
In the presence of some disruptive elements, cancer cells are unable to replicate its DNA optimally.

Mutations associated with sensitivity or resistance to immunotherapy in mNSCLC
The relationship between gene alterations and response to anti-PD-L1 with and without anti-CTLA-4 are not well characterized.

Machine learning for damaging mutations prediction
Scientists from Russia and India have proposed a novel machine-learning-based method for predicting damaging mutations in the protein atomic structure.

Discovery of new mutations may lead to better treatment
In the largest study to date on developmental delay, researchers analyzed genomic data from over 31,000 parent-child trios and found more than 45,000 de novo mutations, and 40 novel genes.

Read More: Mutations News and Mutations Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.