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The COVID-19 pandemic has turned a spotlight on the importance of vaccines, but also on key gaps in scientific understanding of how the immune system reacts to vaccines in general. Why does the immune response to some vaccines differ from person to person? What causes immunity to wane after vaccination, and how can that be monitored and even predicted before a person gets sick? Most of all, how can we be better prepared for future disease outbreaks? Now, scientists at the Broad, in collaboration with the Radboud University Medical Center (the Netherlands), report microbiome and genetic factors underlying the immune response to the tuberculosis vaccine and suggest ways to further study and monitor vaccine-induced immunity.
In the journal Circulation, a team led by Shaan Khurshid and Steven Lubitz of Massachusetts General Hospital and the Broad report a new approach for predicting #AtrialFibrillation using standard ECGs. They developed their approach by using an #ArtificialIntelligence model to analyze EGCs from more than 120,000 people. The approach's results synergize well with known clinical risk factors, and could help doctors identify at-risk patients earlier.
Institute member Dyann Wirth is one of the many scientists who contributed to the development of the RTS,S malaria vaccine, recently endorsed by the World Health Organization for use among children in hard-hit areas. She spoke with us about what it means for public health in those regions, and how the Broad’s study of RTS,S paves the way for new, improved vaccines in the future.
After the first draft of the human genome was sequenced, researchers quickly discovered that only 1 percent of the genome codes for proteins. To learn about the function of the other 99 percent, scientists launched the Encyclopedia of DNA Elements (ENCODE) project, an NIH-funded, multi-institutional effort that sought to comprehensively characterize all of the functional elements in DNA, including both genes and non-coding elements that regulate gene activity. For the past 13 years, Chuck Epstein co-led Broad’s ENCODE efforts, leading a team of scientists in generating an encyclopedia of regulatory elements that has been cited in thousands of publications. Now, with ENCODE in its final stage, we spoke with Epstein about ENCODE’s legacy and impact.
Scientists at the Broad, Princeton University Department of Molecular Biology, and UCSF have developed a suite of molecular tools that increase the efficiency of a gene-editing technique called prime editing for a wide variety of cell types and target genes. In two new studies, the researchers used the next generation prime editing systems to correct mutations linked to various neurodegenerative, metabolic, and cardiovascular diseases.
As a clinical data specialist in Count Me In: Patient-Partnered Research, Delia Sosa, MS maps patients’ clinical trajectories to their genetic data. Count Me In is a nonprofit, patient-partnered research initiative led by the Broad, Dana-Farber Cancer Institute, and the Emerson Collective. Sosa says being a LatinX person, a trans nonbinary person, and a person with disabilities has made them highly attuned to roadblocks people face when trying to participate in research. Someday, Sosa hopes to study medicine and become a clinician specializing in trans healthcare. Sosa understands how difficult it can be for trans and nonbinary people to get not just gender-affirming care, but basic healthcare in general. In this #WhyIScience Q&A, Sosa spoke to us about their work, the art they make to educate others about the experience of being trans nonbinary, and how their identity and experiences have influenced their science.
A new tool developed by researchers at the Broad and Dana-Farber Cancer Institute could help guide precision cancer medicine. MOAlmanac incorporates different kinds of data from patients and their tumors to identify features connected to disease prognosis and resistance or sensitivity to treatment. Watch as creators Brendan Reardon and Eli Van Allen discuss how MOAlmanac contributes to the “democratization” of precision oncology — Reardon and Van Allen hope that one day, any physician anywhere will be able to use their tool to help patients.
Broad scientists have been studying the biological basis of diabetes — with an eye on better diagnosis and treatments — since the earliest days of the Broad. Their goal is to find a cure, since most current medications only treat hyperglycemia, or high blood sugar. Other Broad efforts are using genetic information to define more subtypes of diabetes, which could help doctors better tailor existing drugs for individual patients. Diabetes is a complex disease, and so Broad scientists are using a variety of skill sets and expertise to attack the problem from many angles in a collaborative way. The future of diabetes treatment will be determined by the ability of researchers to leverage genetic data, says Jose Florez, who leads the Broad’s diabetes research group. “When I retire, I want to see that the practice of diabetes changed because we had access to the genome and used this information in smart ways.” Learn more about these efforts in our profile of the Broad’s diabetes research group.
Five Broad researchers are among the 33 biomedical researchers nationwide who will become Howard Hughes Medical Institute (HHMI) investigators this fall. Emily Balskus, Flaminia Catteruccia, Cassandra Extavour, Sun Hur, Cigall Kadoch, and Shingo Kajimura will receive long-term, flexible funding from HHMI, providing them the freedom to move their research forward in creative and new directions.
Using machine learning, researchers at the Broad and the Dana-Farber Cancer Institute have developed a new model that can differentiate between the genomic profiles of prostate cancers that are lethal and those that are unlikely to cause symptoms or death. It may also help clinicians predict whether a prostate cancer patient’s tumor will spread to other parts of the body or become more resistant to treatment over time. “This is just the beginning for how we can enable a convergence between cancer biology and machine learning,” said Eli Van Allen. “That convergence is where we believe we can really deliver more discoveries to cancer patients.”
