Tag Archives: Scripps Research Institute

Microbiology

New Study Reveals How Heavy Alcohol Consumption Increases Brain Inflammation

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People with alcohol use disorder (AUD) experience a never-ending vicious cycle of changes in the brain and behavior. AUD can disrupt communication pathways in the brain, leading to an escalation of drinking behavior and further exacerbating the condition.

Scientists at Scripps Research have uncovered new insights into the role of the immune system in the cycle of alcohol use disorder (AUD). In a study published in Brain, Behavior, and Immunity, they found that the levels of the immune signaling molecule interleukin 1β (IL-1β) are elevated in the brains of mice with alcohol dependence. Furthermore, the IL-1β pathway operates differently in these mice, leading to inflammation in crucial regions of the brain that are associated with decision-making.

“These inflammatory changes to the brain could explain some of the risky decision-making and impulsivity we see in people with alcohol use disorder,” says senior author Marisa Roberto, Ph.D., the Schimmel Family Chair of Molecular Medicine and a professor of neuroscience at Scripps Research. “In addition, our findings are incredibly exciting because they suggest a potential way to treat alcohol use disorder with existing anti-inflammatory drugs targeting the IL-1β pathway.”

AUD is characterized by uncontrolled and compulsive drinking, and it encompasses a range of conditions including alcohol abuse, dependence, and binge drinking. Researchers have previously discovered numerous links between the immune system and AUD—many of them centered around IL-1β. People with certain mutations in the gene that codes for the IL-1β molecule, for instance, are more prone to developing AUD. In addition, autopsies of people who had AUD have found higher levels of IL-1β in the brain.

“We suspected that IL-1β was playing a role in AUD, but the exact mechanisms in the brain have been unclear,” says first author Florence Varodayan, Ph.D., an assistant professor at Binghamton University and former postdoctoral fellow in the Roberto lab.

In the new study, Roberto, Varodayan, and their colleagues compared alcohol-dependent mice with animals drinking moderate or no alcohol at all. They discovered that the alcohol-dependent group had about twice as much IL-1β in the medial prefrontal cortex (mPFC), a part of the brain that plays a role in regulating emotions and behaviors.

The team then went on to show that IL-1β signaling in the alcohol-dependent group was not only increased but also fundamentally different. In mice that had not been exposed to alcohol, as well as in mice that had drunk moderate amounts of alcohol, IL-1β activated an anti-inflammatory signaling pathway. In turn, this lowered levels of the inhibitory neurotransmitter gamma-aminobutyric acid (GABA), a signaling molecule known to regulate neural activity in the brain.

However, in alcohol-dependent mice, IL-1β instead activated pro-inflammatory signaling and boosted levels of GABA, likely contributing to some of the changes in brain activity associated with AUD. Notably, these changes in IL-1β signaling in the alcohol-dependent mice persisted even during alcohol withdrawal.

Drugs that block the activity of IL-1β are already approved by the U.S. Food and Drug Administration to treat rheumatoid arthritis and other inflammatory conditions. More work is needed to determine whether these existing drugs could have utility in treating AUD.

“We plan to follow up on this study with more work on exactly how targeting specific components of the IL-1β pathway might be useful in treating alcohol use disorder,” says Roberto.

Reference: “Chronic ethanol induces a pro-inflammatory switch in interleukin-1β regulation of GABAergic signaling in the medial prefrontal cortex of male mice” by F.P. Varodayan, A.R. Pahng, T.D. Davis, P. Gandhi, M. Bajo, M.Q. Steinman, W.B. Kiosses, Y.A. Blednov, M.D. Burkart, S. Edwards, A.J. Roberts and M. Roberto, 28 February 2023, Brain, Behavior, and Immunity.
DOI: 10.1016/j.bbi.2023.02.020

The study was funded by the National Institutes of Health, The Schimmel Family Chair, The Pearson Center for Alcoholism and Addiction Research, and The Scripps Research Institute’s Animal Models Core Facility.

Scripps Research Institute

Microbiology

“COVID Rebound” Is Common – Even in Patients Not Treated With Paxlovid

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Preliminary results from a Scripps Research and eMed digital medicine study show an unexpectedly high proportion of COVID-19 rebound cases in untreated people, as well as those treated with Paxlovid.

“COVID rebound,” in which evidence of the illness disappears and then returns days or weeks later, is surprisingly common—whether or not patients are given the antiviral Paxlovid.

The results, reported recently in the journal Clinical Infectious Diseases by scientists at Scripps Research and the digital health company eMed, are a preliminary readout from an ongoing observational study of people who order SARS-CoV-2 antigen test kits online. The researchers found that in an initial group of 170 eMed Test-to-Treat™ kit users, the disappearance and then return of evidence of the virus on antigen tests and in self-reported COVID-19 symptoms occurred in 9.3% and 7.0% of patients who opted not to take antiviral treatment, and in 14.2% and 18.9% of those who opted for Paxlovid.

Although a higher proportion of the Paxlovid-treated group reported COVID-19 rebound, the difference was not statistically significant in this early snapshot of the ongoing study, which is designed ultimately to enroll a total of 800 patients.

“These preliminary results suggest that rebound after clearance of SARS-CoV-2 test positivity or COVID-19 symptom resolution is more common than previously reported in both treated and untreated patients,” says study lead author Jay Pandit, MD, an assistant professor and director of Digital Medicine at the Scripps Research Translational Institute. “We’re going to need a larger set of participants and more extended follow-up to better understand this rebound phenomenon.”

The study, conducted from August to November of last year, was a collaboration with eMed, including epidemiologist and Chief Science Officer Michael Mina, MD, PhD, previously professor at Harvard T.H. Chan School of Public Health, and others at the Test-to-Treat company, which is also implementing the NIH Home Test to Treat COVID-19 program.

Reports of COVID-19 rebound started appearing in the medical literature in 2022. The cause of rebound has been unclear, although the suggestion in most of these reports has been that rebound occurs more often in patients treated with Paxlovid. The latter, a mix of two antiviral compounds (nirmatrelvir and ritonavir), received emergency use approval in late 2021 from the U.S. Food and Drug Administration (FDA) for treating patients who have mild-to-moderate COVID-19 and are at high risk of developing severe COVID-19.

To help illuminate the rebound phenomenon and any connection to Paxlovid, Pandit and his colleagues teamed up with eMed to drive a “real-world” study of outcomes among people using the company’s COVID-19 Test-to-Treat antigen test kits with telehealth proctoring and telemedicine.

“As the COVID-19 landscape continues to evolve, the importance of making timely and effective treatments accessible and thereby helping reduce severe disease outcomes cannot be overstated,” Mina says. “Collaborations such as this with the Scripps Research Translation Institute are a key part of efforts to gather evidence-based data and answer critical questions associated with treatment outcomes. We are also proud that this study not only offers new data surrounding COVID-19 recovery and treatment outcomes, but also highlights the benefits of industry and academic partnerships to accelerate high-quality public health and translational research.”

The researchers offered Test-to-Treat telehealth kit users participation in the study if they had a verified positive test. If users consented to participate, the researchers sent them more test kits, and asked each participant to take a test and fill out a symptom questionnaire every other day for 16 days. The team then compared the rates of rebound for those who did and didn’t opt to take Paxlovid. Rebound was measured in two ways: a positive test result after a negative test, or a reported recurrence of symptoms after symptom resolution. For this preliminary analysis, there were 127 people in the Paxlovid-treated group, and 43 in the non-Paxlovid group.

Either way rebounds were measured, the Paxlovid group experienced them at a higher rate: 14.2% vs. 9.3% for antigen test rebounds, and 18.9% vs. 7.0% for symptom rebounds. With the small participant numbers included in this preliminary analysis, these differences were not statistically significant. Moreover, on other measures (such as the time from first positive antigen test to first negative antigen test, and time from symptom onset to first symptom resolution), the two groups had essentially identical outcomes. Age, gender and pre-existing conditions also did not appear to influence rebound.

Pandit emphasizes that the study is not currently powered to detect statistically significant results, and a final analysis should include up to 800 participants and thus should have much more power to generate conclusive findings. However, he adds, the preliminary findings already make clear that the rebound rates for both treated and untreated groups are higher than the rates reported in prior studies. For example, an analysis of their clinical trial results by Pfizer, the maker of Paxlovid, found rebound rates of only about 2% in both Paxlovid and placebo groups over a two-week period.

In addition to increasing the number of participants in their ongoing study, Pandit and colleagues plan to start sequencing the virus found in participants and testing participants’ blood samples for antibody levels and other immune markers.

“We’re hoping to answer key questions about the rebound phenomenon, such as whether it’s enhanced by Paxlovid, how much it depends on the viral variant and what is the role of the patient’s immune system,” Pandit says.

He and his team also plan to improve the balance of ethnic and racial representation between the treatment and control groups: In the initial group of 170, Whites were much more likely than Blacks and Latinos to opt for Paxlovid treatment.

Reference: “The COVID-19 Rebound Study: A Prospective Cohort Study to Evaluate Viral and Symptom Rebound Differences in Participants Treated with Nirmatrelvir Plus Ritonavir Versus Untreated Controls” by Jay A Pandit, Jennifer M Radin, Danielle Chiang, Emily G Spencer, Jeff B Pawelek, Mira Diwan, Leila Roumani and Michael J Mina, 22 February 2023, Clinical Infectious Diseases.
DOI: 10.1093/cid/ciad102

Support for the study was provided by eMed, the National Institute of Allergy and Infectious Diseases (3U01AI151812-03S2), and the National Center for Advancing Translational Sciences (NCATS UL1 TR002550).

Scripps Research Institute

Microbiology

A Universal Vaccine? New Computer Model of Flu Virus Shows Promise

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The World Health Organization reports that there are approximately 1 billion cases of influenza annually, with 3-5 million severe cases and as many as 650,000 influenza-related respiratory fatalities worldwide. To be effective, seasonal flu vaccines must be updated each year to align with the predominant strains of the virus. When the vaccine is a match for the prevalent strain, it offers substantial protection. However, if the vaccine and virus strains are not a match, the vaccine may provide limited defense.

The hemagglutinin (HA) and neuraminidase (NA) glycoproteins are the primary targets of the flu vaccine. The HA protein facilitates the virus’s attachment to host cells, while the NA protein acts as a scissor to detach the HA from the cell membrane, enabling the virus to multiply. Despite previous studies on the properties of these glycoproteins, a complete understanding of their movement does not exist.

For the first time, researchers at the University of California San Diego have created an atomic-level computer model of the H1N1 virus that reveals new vulnerabilities through glycoprotein “breathing” and “tilting” movements. This work, published in ACS Central Science, suggests possible strategies for the design of future vaccines and antivirals against influenza.

“When we first saw how dynamic these glycoproteins were, the large degree of breathing and tilting, we actually wondered if there was something wrong with our simulations,” stated Distinguished Professor of Chemistry and Biochemistry Rommie Amaro, who is the principal investigator on the project. “Once we knew our models were correct, we realized the enormous potential this discovery held. This research could be used to develop methods of keeping the protein locked open so that it would be constantly accessible to antibodies.”

Traditionally, flu vaccines have targeted the head of the HA protein based on still images that showed the protein in a tight formation with little movement. Amaro’s model showed the dynamic nature of the HA protein and revealed a breathing movement that exposed a previously unknown site of immune response, known as an epitope.

Computer model of H1N1 influenza virus – 160 million atoms of detail. Credit: University of California – San Diego

This discovery complemented previous work from one of the paper’s co-authors, Ian A. Wilson, Hansen Professor of Structural Biology at The Scripps Research Institute, who had discovered an antibody that was broadly neutralizing — in other words, not strain-specific — and bound to a part of the protein that appeared unexposed. This suggested that the glycoproteins were more dynamic than previously thought, allowing the antibody an opportunity to attach. Simulating the breathing movement of the HA protein established a connection.

NA proteins also showed movement at the atomic level with a head-tilting movement. This provided a key insight to co-authors Julia Lederhofer and Masaru Kanekiyo at the National Institute of Allergy and Infectious Diseases. When they looked at convalescent plasma — that is, plasma from patients recovering from the flu — they found antibodies specifically targeting what is called the “dark side” of NA underneath the head. Without seeing the movement of NA proteins, it wasn’t clear how the antibodies were accessing the epitope. The simulations Amaro’s lab created showed an incredible range of motion that gave insight into how the epitope was exposed for antibody binding.

The H1N1 simulation Amaro’s team created contains an enormous amount of detail — 160 million atoms worth. A simulation of this size and complexity can only run on a few select machines in the world. For this work, the Amaro lab used Titan at Oak Ridge National Lab, formerly one of the largest and fastest computers in the world.

Amaro is making the data available to other researchers who can uncover even more about how the influenza virus moves, grows, and evolves. “We’re mainly interested in HA and NA, but there are other proteins, the M2 ion channel, membrane interactions, glycans, and so many other possibilities,” Amaro stated. “This also paves the way for other groups to apply similar methods to other viruses. We’ve modeled SARS-CoV-2 in the past and now H1N1, but there are other flu variants, MERS, RSV, HIV — this is just the beginning.”

Reference: “Breathing and Tilting: Mesoscale Simulations Illuminate Influenza Glycoprotein Vulnerabilities” by Lorenzo Casalino, Christian Seitz, Julia Lederhofer, Yaroslav Tsybovsky, Ian A. Wilson, Masaru Kanekiyo and Rommie E. Amaro, 8 December 2022, ACS Central Science.
DOI: 10.1021/acscentsci.2c00981

The study was funded by the National Institutes of Health, the National Science Foundation, the US Department of Energy, and the National Science Foundation.

University of California – San Diego