Genetic biomarker may predict severity of food allergy

Offers potential for determining the risk of severe reactions for patients and families with food allergies

Peer-Reviewed Publication

ANN & ROBERT H. LURIE CHILDREN'S HOSPITAL OF CHICAGO

Researchers from Ann & Robert H. Lurie Children’s Hospital of Chicago and colleagues reported for the first time that a genetic biomarker may be able to help predict the severity of food allergy reactions. Currently there is no reliable or readily available clinical biomarker that accurately distinguishes patients with food allergies who are at risk for severe life-threatening reactions versus more mild symptoms. Findings were published in the Journal of Allergy and Clinical Immunology.

Dr. Lang and colleagues found that the presence of an enzyme isoform called α-tryptase, which is encoded by the TPSAB1 gene, correlates with increased prevalence of anaphylaxis or severe reaction to food as compared to subjects without any α-tryptase.

“Determining whether or not a patient with food allergies has α-tryptase can easily be done in clinical practice using a commercially available test to perform genetic sequencing from cheek swabs,” said lead author Abigail Lang, MD, MSc, attending physician and researcher at Lurie Children’s and Assistant Professor of Pediatrics at Northwestern University Feinberg School of Medicine. “If the biomarker is detected, this may help us understand that the child is at a higher risk for a severe reaction or anaphylaxis from their food allergy and should use their epinephrine auto-injector if exposed to the allergen. Our findings also open the door to developing an entirely new treatment strategy for food allergies that would target or block α-tryptase. This is an exciting first step and more research is needed.”

Tryptase is found mainly in mast cells, which are white blood cells that are part of the immune system. Mast cells become activated during allergic reactions. Increased TPSAB1 copy number which leads to increased α-tryptase is already known to be associated with severe reactions in adults with Hymenoptera venom allergy (or anaphylaxis following a bee sting).

Dr. Lang’s study included 119 participants who underwent TPSAB1 genotyping, 82 from an observational food allergy cohort at the National Institute of Allergy and Infectious Diseases (NIAID) and 37 from a cohort of children who reacted to peanut oral food challenge at Lurie Children’s.

“We need to validate our preliminary findings in a much larger study, but these initial results are promising,” says Dr. Lang. “We also still need a better understanding of why and how α-tryptase makes food allergy reactions more severe in order to pursue this avenue for potential treatment.”

Rajesh Kumar, MD, MSc, from Lurie Children’s is the co-senior author on the study. Dr. Kumar is the Interim Division Head of Allergy and Immunology and Professor of Pediatrics at Northwestern University Feinberg School of Medicine.

This work was supported in part by the Midwest Allergy Research Institute (MARI) Food Allergy Pilot Research Award and NIAID-sponsored T32 grant AI083216. This project was funded in part with federal funds from the Division of Intramural Research of the National Institute of Allergy and Infectious Diseases, NIH. This project has also been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. 75N91019D00024.

Research at Ann & Robert H. Lurie Children’s Hospital of Chicago is conducted through Stanley Manne Children’s Research Institute. The Manne Research Institute is focused on improving child health, transforming pediatric medicine and ensuring healthier futures through the relentless pursuit of knowledge. Lurie Children’s is a nonprofit organization committed to providing access to exceptional care for every child. It is ranked as one of the nation’s top children’s hospitals by U.S. News & World Report. Lurie Children’s is the pediatric training ground for Northwestern University Feinberg School of Medicine.

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JOURNAL

Journal of Allergy and Clinical Immunology

DOI

10.1016/j.jaci.2023.07.014 

 

Newly discovered bone stem cell causes premature skull fusion

Peer-Reviewed Publication

WEILL CORNELL MEDICINE

 

IMAGE: A CONCEPTUAL RENDERING OF HOW A NEW STEM CELL IN THE JOINTS BETWEEN THE FLAT BONES OF THE SKULL DRIVES SKULL GROWTH AND FUSION. view more 

CREDIT: AI IMAGE GENERATED USING MIDJOURNEY ON MAY 24, 2023; PROVIDED BY THE GREENBLATT LAB.

Craniosynostosis, the premature fusion of the top of the skull in infants, is caused by an abnormal excess of a previously unknown type of bone-forming stem cell, according to a preclinical study led by researchers at Weill Cornell Medicine.

Craniosynostosis arises from one of several possible gene mutations, and occurs in about one in 2,500 babies. By constricting brain growth, it can lead to abnormal brain development if not corrected surgically. In complex cases, multiple surgeries are needed.

In the study, which appears Sept. 20 in Nature, the researchers examined in detail what happens in the skull of mice with one of the most common mutations found in human craniosynostosis. They found that the mutation drives premature skull fusion by inducing the abnormal proliferation of a type of bone-making stem cell—the DDR2+ stem cell—that had never been described before.

“We can now start to think about treating craniosynostosis not just with surgery but also by blocking this abnormal stem cell activity,” said study co-senior author Dr. Matt Greenblatt, an associate professor of pathology and laboratory medicine at Weill Cornell Medicine and a pathologist at NewYork-Presbyterian/Weill Cornell Medical Center.

The other co-senior author of the study was Dr. Shawon Debnath, a research associate in the Greenblatt laboratory.

In a study published in Nature in 2018, Drs. Debnath and Greenblatt and their colleagues, described the discovery of a type of bone-forming stem cell they called the CTSK+ stem cell. Because this type of cell is present in the top of the skull, or “calvarium,” in mice, they suspected that it has a role in causing craniosynostosis.

In the new study, they investigated that possibility by engineering mice in which CTSK+ stem cells lack one of the genes whose loss of function causes craniosynostosis. They expected that the gene deletion somehow would induce these calvarial stem cells to go into bone-making overdrive. This new bone would fuse the flexible, fibrous material called sutures in the skull that normally allow it to expand in infants.

“We were surprised to find that, instead of the mutation in CTSK+ stem cells leading to these stem cells being activated to fuse the bony plates in the skull as we expected, mutations in the CTSK+ stem cells instead led to the depletion of these stem cells at the sutures—and the greater the depletion, the more complete the fusion of the sutures,” Dr. Debnath said.

The unexpected finding led the team to hypothesize that another type of bone-forming stem cell was driving the abnormal suture fusion. After further experiments, and a detailed analysis of the cells present at fusing sutures, they identified the culprit: the DDR2+ stem cell, whose daughter cells make bone using a different process than that utilized by CTSK+ cells.

The team found that CTSK+ stem cells normally suppress the production of the DDR2+ stem cells. But the craniosynostosis gene mutation causes the CTSK+ stem cells to die off, allowing the DDR2+ cells to proliferate abnormally.

To investigate these stem cells in human tissue, the team formed a collaboration with craniosynostosis surgeon Dr. Caitlin Hoffman, neurogeneticist Dr. Elizabeth Ross, and neuropathologist Dr. David Pisapia, all at Weill Cornell Medicine and NewYork-Presbyterian/Weill Cornell Medical Center; and craniosynostosis surgeon Dr. Thomas Imahiyerobo of Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian/Columbia University Irving Medical Center.

The researchers found the human versions of DDR2+ stem cells and CTSK+ stem cells in calvarial samples from craniosynostosis surgeries—underscoring the likely clinical relevance of their findings in mice.

The findings suggest that inappropriate DDR2+ stem cell proliferation in the calvarium, in infants with craniosynostosis-linked gene mutations, could be treated by suppressing this stem cell population, through mimicking the methods that CTSK+ stem cells normally use to prevent expansion of DDR2+stem cells. The researchers found that the CTSK+ stem cells achieve this suppression by secreting a growth factor protein called IGF-1, and possibly other regulatory proteins.

“We observed that we could partly prevent calvarial fusion by injecting IGF-1 over the calvarium,” said study first author Dr. Seoyeon Bok, a postdoctoral researcher in the Greenblatt laboratory.

“I can imagine DDR2+ stem cell-suppressing drug treatments being used along with surgical management, essentially to limit the number of surgeries needed or enhance outcomes,” Dr. Greenblatt said.

In addition to treatment-oriented research, he and his colleagues now are looking for other bone-forming stem cell populations in the skull.

“This work has uncovered much more complexity in the skull than we ever imagined, and we suspect the complexity doesn’t end with these two stem cell types,” Dr. Greenblatt said.

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JOURNAL

Nature

 

Scientists reveal how the effects of psychosis spread throughout the brain

Scientists detail new capacity to map and model the spread of brain changes in people with different stages of psychoses

Peer-Reviewed Publication

MONASH UNIVERSITY

 

IMAGE: PROFESSOR ALEX FORNITO view more 

CREDIT: MONASH UNIVERSITY

Psychoses like schizophrenia cost billions of dollars annually and derail the lives of people struggling with the disease. Now Monash University researchers have modelled how the effects of psychosis spread through the brain, allowing them to isolate areas where these changes may originate from and which could be targeted by therapies designed to reduce the disease’s progression.

The study, published today in the prestigious Journal of the American Medical Association Psychiatry, details how the scientists were able to map and model the spread of brain changes in people with different stages of psychoses such as schizophrenia,from people newly diagnosed to those who have experienced psychosis for years.

The study, led by  Dr Sid Chopra , from the Turner Institute for Brain and Mental Health and Monash University’s School of Psychological Sciences,  identified the hippocampus, which is important for memory, as a possible  early site of brain changes in psychosis. “This finding could potentially guide  therapies that can target this area of the brain, potentially limiting the impact of the illness or perhaps even reducing the risk of psychosis onset,” he said

The study looked at 534 individuals from four groups, spanning early and late stages of psychotic illness. The researchers used MRI to examine changes in grey matter that occur at the different illness stages

They found that the evolution of psychoses, as measured by changes in great matter, may originate in the hippocampus and gradually  spread  across the brain, over time, via the nerve or axonal connections. According to Dr Chopra, “we found that the pattern of grey matter change seen in psychosis is not randomly distributed across the brain, but is shaped by a complex network of structural connections – in a very similar way to how we see the progression of neurodegenerative diseases in the brain.”

The researchers used a mathematical model to predict  grey matter volume changes  in four different groups of people with schizophrenia, scanned at both early and late stages of illness. According to Professor Alex Fornito, who led the research team, “we found consistent evidence that the hippocampus, an area important for memory and which is known to play an important role in schizophrenia, is a candidate epicentre of brain changes in the illness,” he said.

Importantly the researchers were able to distinguish brain changes associated with disease from those linked to  the use of antipsychotic medication. “Most research has taken place with people who are already taking antipsychotic medications, making it difficult to disentangle the effects of medication from those of  illness,” said Dr Chopra. “Our network-based model was able to account for both medication-related and illness-related brain changes, meaning that brain network architecture represents a fundamental constraint on both types of brain changes in psychosis.” 

According to Dr Chopra, the new approach opens new possibilities for understanding the causes of brain changes in schizophrenia, and for forecasting how they might evolve in individual patients. “Our work demonstrates that it is possible to investigate promising mechanisms behind widespread brain changes in schizophrenia, using fairly simple models” he said. “We hope to further extend these models to identify possible treatment targets and predict how the illness might evolve in individual people.”

 

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JOURNAL

JAMA Psychiatry

DOI

10.1001/jamapsychiatry.2023.3293 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

People

ARTICLE TITLE

Network-based spreading of grey matter changes across different stages of psychosis

ARTICLE PUBLICATION DATE

20-Sep-2023

 

Consumption of ultraprocessed food and risk of depression

JAMA Network Open

Peer-Reviewed Publication

JAMA NETWORK

About The Study: The findings of this study suggest that greater ultraprocessed food (UPF; i.e., energy-dense, palatable, and ready-to-eat items) intake, particularly artificial sweeteners and artificially sweetened beverages, is associated with increased risk of depression. Although the mechanism associating UPF to depression is unknown, recent experimental data suggests that artificial sweeteners elicit purinergic transmission in the brain, which may be involved in the etiopathogenesis of depression. 

Authors: Raaj S. Mehta, M.D., M.P.H., and Andrew T. Chan, M.D., M.P.H., of Massachusetts General Hospital and Harvard Medical School in Boston, are corresponding authors. 

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/ 

(doi:10.1001/jamanetworkopen.2023.34770)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

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Embed this link to provide your readers free access to the full-text article

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About JAMA Network Open: JAMA Network Open is an online-only open access general medical journal from the JAMA Network. On weekdays, the journal publishes peer-reviewed clinical research and commentary in more than 40 medical and health subject areas. Every article is free online from the day of publication. 

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JOURNAL

JAMA Network Open

Researchers discover biomarker for tracking depression recovery

New deep brain stimulation device coupled with powerful AI may improve therapy for treatment-resistant depression

Peer-Reviewed Publication

NIH/NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE

Using a novel deep brain stimulation (DBS) device capable of recording brain signals, researchers have identified a pattern of brain activity or “biomarker” related to clinical signs of recovery from treatment-resistant depression. The findings from this small study are an important step towards using brain data to understand a patient’s response to DBS treatment. The study was published in Nature and supported by the National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies® Initiative, or The BRAIN Initiative®.

Although the approach is still experimental, clinical research shows that DBS can be used safely and effectively to treat cases of depression in which symptoms have not improved with antidepressant medications, referred to as treatment-resistant depression. People receiving DBS undergo surgery to have a thin metal electrode implanted into specific brain areas to deliver electrical impulses that modulate brain activity. How exactly DBS improves symptoms in people with depression is not well-understood, which has made it difficult for researchers to objectively track patients’ response to treatment and adjust as needed.

The small study enrolled 10 adults with treatment-resistant depression, all of whom underwent DBS therapy for six months. Each participant received the same stimulation dose to begin and then stimulation levels were increased once or twice. Later, researchers used artificial intelligence (AI) tools to analyze collected brain data from six patients and observed a common brain activity signature or biomarker that correlated with patients self-reporting feeling symptoms of depression or stable as they recovered. In one patient, researchers identified the biomarker and were retrospectively able to predict that a patient would fall back into a major depressive episode four weeks before clinical interviews showed they were at risk of a relapse occurring.

“This study demonstrates how new technology and a data-driven approach can refine DBS therapy for severe depression, which can be debilitating,” said John Ngai, Ph.D., director of the BRAIN Initiative. “It’s this type of collaborative work made possible by the BRAIN Initiative that moves promising therapies closer to clinical use.”

In the study, patients received DBS targeting the subcallosal cingulate cortex (SCC), a brain region that regulates emotional behavior and is involved in feelings of sadness. DBS of the SCC is an emerging therapy that can provide stable, long-term relief from depressive symptoms for years. However, using DBS to treat depression remains challenging because each patient’s path to stable recovery looks different. Clinicians also must rely on subjective self-reports from patient interviews and psychiatric rating scales to track symptoms, which can fluctuate over time. This makes it hard to distinguish between normal mood variations and more serious situations requiring a tweak in stimulation. In addition, changes in symptoms in response to DBS can take weeks or months to occur, making it difficult to tell how well the therapy is working.

“This biomarker suggests that brain signals can be used to help understand a patient’s response to DBS treatment and adjust the treatment accordingly,” said Joshua A. Gordon, M.D., Ph.D., director of NIH’s National Institute of Mental Health. “The findings mark a major advance in translating a therapy into practice.”

The patients in the study responded well to DBS therapy; after six months, 90% showed a significant improvement in depression symptoms, and 70% were in remission or no longer depressed. This high response rate was a unique opportunity to look back and examine how each patient’s brain responded differently to the stimulation during treatment.

Christopher Rozell, Ph.D., Julian T. Hightower Chair and professor of electrical and computer engineering at Georgia Tech in Atlanta, and his colleagues used a technique called explainable artificial intelligence to understand these subtle changes in brain activity. The algorithm used brain data to distinguish between depressive versus stable recovery states and was able to explain what activity changes in the brain were the main drivers of this transition. Importantly, the biomarker also distinguished between normal day-to-day transient mood changes and sustained worsening symptoms. This algorithm could provide clinicians with an early warning signal that a patient is moving toward a highly depressive state and requires a DBS adjustment and extra clinical care.

“Nine out of 10 patients in the study got better, providing a perfect opportunity to use a novel technology to track the trajectory of their recovery,” said Helen Mayberg, M.D., director of the Nash Family Center for Advanced Circuit Therapeutics at Icahn Mount Sinai in New York City and co-senior author of the study. “Our goal is to identify an objective, neurological signal to help clinicians decide when, or when not, to make a DBS adjustment.”

“We showed that by using a scalable procedure with single electrodes in the same brain region and informed clinical management, we can get people better,” said Dr. Rozell, co-senior author of the study. “This study also gives us an amazing scientific platform to understand the variation between patients, which is key to treating complex psychiatric disorders like treatment-resistant depression.”

Next, the team analyzed data from MRI brain scans collected from patients before surgery. The results revealed structural and functional abnormalities in the specific brain network targeted by the DBS therapy. More severe white matter deficits were related to longer recovery times.

Researchers also used AI tools to analyze changes in facial expression extracted from videos of participant interviews. In a clinical setting, a patient’s facial expression can reflect the severity of their depression symptoms, a change that psychiatrists likely pick up on in routine clinical evaluations. They found patterns in individual patient expressions that coincided with their transition from illness to stable recovery. This could serve as an additional tool and new behavioral marker to track recovery in DBS therapy. More research is needed to determine whether the video analysis can reliably predict current and future disease states.

Both the observed facial expression changes and anatomical deficits correlated with cognitive states captured by the biomarker, supporting the use of this biomarker in managing DBS therapy for depression.

The research team, including Drs. Mayberg and Rozell, and Patricio Riva-Posse, M.D., at Emory University School of Medicine in Atlanta, is now confirming their findings in a second cohort of patients at Mount Sinai. Future studies will continue to explore the antidepressant effects of DBS by using a next-generation device to study the neural basis of moment-to-moment changes in mood.

According to the research team, this study represents a significant advance in early stage DBS therapy for various mental disorders, including severe depression, obsessive-compulsive disorder, post-traumatic stress disorder, binge eating disorder, and substance use disorder. Other DBS studies have identified brain biomarkers for chronic pain, but using brain data to successfully treat patients is still under development.

The study was supported by the NIH BRAIN Initiative (UH3NS103550), the National Science Foundation, the Hope for Depression Research Foundation, and the Julian T. Hightower Chair at Georgia Tech.

Article:

Alagapan, S, et al. Cingulate dynamics track depression recovery with deep brain stimulation. Nature, September 20, 2023. DOI: 10.1038/s41586-023-06541-3.

###

The NIH BRAIN Initiative is managed by 10 Institutes and Centers whose missions and current research portfolios complement the goals of The BRAIN Initiative®: National Center for Complementary and Integrative Health, National Eye Institute, National Institute on Aging, National Institute on Alcohol Abuse and Alcoholism, National Institute of Biomedical Imaging and Bioengineering, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute on Drug Abuse, National Institute on Deafness and other Communication Disorders, National Institute of Mental Health, and National Institute of Neurological Disorders and Stroke.

NINDS is the nation’s leading funder of research on the brain and nervous system. The mission of NINDS is to seek fundamental knowledge about the brain and nervous system and to use that knowledge to reduce the burden of neurological disease.

About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.

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JOURNAL

Nature

DOI

10.1038/s41586-023-06541-3 

ARTICLE TITLE

Cingulate dynamics track depression recovery with deep brain stimulation

ARTICLE PUBLICATION DATE

20-Sep-2023

Decoding depression: Researchers identify crucial biomarker that tracks recovery from treatment-resistant depression

Harnessing the power of explainable AI, researchers have unveiled the first insights into the complex workings of deep-brain stimulation therapy for treatment-resistant depression

Peer-Reviewed Publication

THE MOUNT SINAI HOSPITAL / MOUNT SINAI SCHOOL OF MEDICINE

A team of leading clinicians, engineers, and neuroscientists has made a groundbreaking discovery in the field of treatment-resistant depression. By analyzing the brain activity of patients undergoing deep brain stimulation (DBS), a promising therapy involving implanted electrodes that stimulate the brain, the researchers identified a unique pattern in brain activity that reflects the recovery process in patients with treatment-resistant depression. This pattern, known as a biomarker, serves as a measurable indicator of disease recovery and represents a significant advance in treatment for the most severe and untreatable forms of depression. 

The team’s findings, published online in the journal Nature on September 20, offer the first window into the intricate workings and mechanistic effects of DBS on the brain during treatment for severe depression.

DBS involves implanting thin electrodes in a specific brain area to deliver small electrical pulses, similar to a pacemaker. Although DBS has been approved and used for movement disorders such as Parkinson’s disease for many years, it remains experimental for depression. This study is a crucial step toward using objective data collected directly from the brain via the DBS device to inform clinicians about the patient’s response to treatment. This information can help guide adjustments to DBS therapy, tailoring it to each patient’s unique response and optimizing their treatment outcomes. 

Now, the researchers have shown it’s possible to monitor that antidepressant effect throughout the course of treatment, offering clinicians a tool somewhat analogous to a blood glucose test for diabetes or blood pressure monitoring for heart disease: a readout of the disease state at any given time. Importantly, it distinguishes between typical day-to-day mood fluctuations and the possibility of an impending relapse of the depressive episode.  

The research team, which includes experts from the Georgia Institute of Technology, the Icahn School of Medicine at Mount Sinai, and Emory University School of Medicine, used artificial intelligence (AI) to detect shifts in brain activity that coincided with patients' recovery.

The study, funded by the National Institutes of Health Brain Research Through Advancing Innovative Neurotechnologies ®, or the BRAIN Initiative ®, involved 10 patients with severe treatment-resistant depression, all of whom underwent the DBS procedure at Emory University. The study team used a new DBS device that allowed brain activity to be recorded. Analysis of these brain recordings over six months led to the identification of a common biomarker that changed as each patient recovered from their depression. After six months of DBS therapy, 90 percent of the subjects exhibited a significant improvement in their depression symptoms and 70 percent no longer met the criteria for depression.

The high response rates in this study cohort enabled the researchers to develop algorithms known as "explainable artificial intelligence" that allow humans to understand the decision-making process of AI systems. This technique helped the team identify and understand the unique brain patterns that differentiated a "depressed" brain from a "recovered" brain.

"The use of explainable AI allowed us to identify complex and usable patterns of brain activity that correspond to a depression recovery despite the complex differences in a patient’s recovery,” explained Sankar Alagapan PhD, a Georgia Tech research scientist and lead author of the study. ”This approach enabled us to track the brain’s recovery in a way that was interpretable by the clinical team, making a major advance in the potential for these methods to pioneer new therapies in psychiatry.”

Helen S. Mayberg, MD, co-senior author of the study, led the first experimental trial of subcallosal cingulate cortex (SCC) DBS for treatment-resistant depression patients in 2003, demonstrating that it could have clinical benefit. In 2019, she and the Emory team reported the technique had a sustained and robust antidepressant effect with ongoing treatment over many years for previously treatment-resistant patients.

“This study adds an important new layer to our previous work, providing measurable changes underlying the predictable and sustained antidepressant response seen when patients with treatment-resistant depression are precisely implanted in the SCC region and receive chronic DBS therapy,” said Dr. Mayberg, now Founding Director of the Nash Family Center for Advanced Circuit Therapeutics at Icahn Mount Sinai. “Beyond giving us a neural signal that the treatment has been effective, it appears that this signal can also provide an early warning signal that the patient may require a DBS adjustment in advance of clinical symptoms. This is a game changer for how we might adjust DBS in the future.“  

"Understanding and treating disorders of the brain are some of our most pressing grand challenges, but the complexity of the problem means it's beyond the scope of any one discipline to solve,” said Christopher Rozell, PhD, Julian T. Hightower Chair and Professor of Electrical and Computer Engineering at Georgia Tech and co-senior author of the paper. “This research demonstrates the immense power of interdisciplinary collaboration. By bringing together expertise in engineering, neuroscience, and clinical care, we achieved a significant advance toward translating this much-needed therapy into practice, as well as an increased fundamental understanding that can help guide the development of future therapies."

The team's research also confirmed a longstanding subjective observation by psychiatrists: as patients' brains change and their depression eases, their facial expressions also change. The team's AI tools identified patterns in individual facial expressions that corresponded with the transition from a state of illness to stable recovery. These patterns proved more reliable than current clinical rating scales.

In addition, the team used two types of magnetic resonance imaging to identify both structural and functional abnormalities in the brain’s white matter and interconnected regions that form the network targeted by the treatment. They found these irregularities correlate with the time required for patients to recover, with more pronounced deficits in the targeted brain network correlated to a longer time for the treatment to show maximum effectiveness. These observed facial changes and structural deficits provide behavioral and anatomical evidence supporting the relevance of the electrical activity signature or biomarker.

"When we treat patients with depression, we rely on their reports, a clinical interview, and psychiatric rating scales to monitor symptoms. Direct biological signals from our patients' brains will provide a new level of precision and evidence to guide our treatment decisions,” said Patricio Riva-Posse, MD, Associate Professor and Director of the Interventional Psychiatry Service in the Department of Psychiatry and Behavioral Sciences at Emory University School of Medicine, and lead psychiatrist for the study.

Given these initial promising results, the team is now confirming their findings in another completed cohort of patients at Mount Sinai. They are using the next generation of the dual stimulation/sensing DBS system with the aim of translating these findings into the use of a commercially available version of this technology.

Research reported in this press release was supported by the National Institutes of Health BRAIN Initiative under award number UH3NS103550; the National Science Foundation, grant No. CCF-1350954; the Hope for Depression Research Foundation; and the Julian T. Hightower Chair at Georgia Tech. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of any funding agency.

https://www.mountsinai.org/profiles/helen-s-mayberg

https://www.mountsinai.org/about/newsroom/2019/long-term-follow-up-data-shows-deep-brain-stimulation-is-an-effective-treatment-for-treatment-resistant-depression

https://icahn.mssm.edu/research/advanced-circuit-therapeutics

https://ece.gatech.edu/directory/christopher-john-rozell

https://med.emory.edu/directory/profile/?u=PRIVAPO

https://siplab.gatech.edu/rozell.html

https://www.emoryhealthcare.org/centers-programs/treatment-resistant-depression-program/index.html

 

About the Mount Sinai Health System

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 43,000 employees working across eight hospitals, over 400 outpatient practices, nearly 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advanced health for all people, everywhere, by taking on the most complex health care challenges of our time — discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it.

Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients’ medical and emotional needs at the center of all treatment. The Health System includes approximately 7,300 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status, and are highly ranked: No. 1 in Geriatrics and top 20 in Cardiology/Heart Surgery, Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News & World Report’s “Best Children’s Hospitals” ranks Mount Sinai Kravis Children's Hospital among the country’s best in several pediatric specialties. For more information, visit https://www.mountsinai.org or find Mount Sinai on Facebook, Twitter and YouTube.

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JOURNAL

Nature

DOI

10.1038/s41586-023-06541-3 

ARTICLE PUBLICATION DATE

20-Sep-2023

 

Genetically modifying individual cells in animals

Peer-Reviewed Publication

ETH ZURICH

 

IMAGE: WITH THE NEW METHOD, THE CELLS IN INDIVIDUAL ORGANS OF ANIMALS CAN BE GENETICALLY MODIFIED IN A MOSAIC-LIKE MANNER (SYMBOL IMAGE GENERATED WITH MIDJOURNEY). view more 

CREDIT: ETH ZURICH

One proven method for tracking down the genetic causes of diseases is to knock out a single gene in animals and study the consequences this has for the organism. The problem is that for many diseases, the pathology is determined by multiple genes. This makes it extremely difficult for scientists to determine the extent to which any one of the genes is involved in the disease. To do this, they would have to perform many animal experiments – one for each desired gene modification.

Researchers led by Randall Platt, Professor of Biological Engineering at the Department of Biosystems Science and Engineering at ETH Zurich in Basel, have now developed a method that will greatly simplify and speed up research with laboratory animals: using the CRISPR-Cas gene scissors, they simultaneously make several dozen gene changes in the cells of a single animal, much like a mosaic. While no more than one gene is altered in each cell, the various cells within an organ are altered in different ways. Individual cells can then be precisely analysed. This enables researchers to study the ramifications of many different gene changes in a single experiment.

First time in adult animals

For the first time, the ETH Zurich researchers have now successfully applied this approach in living animals – specifically, in adult mice – as they report in the current issue of Nature. Other scientists had previously developed a similar approach for cells in culture or animal embryos.

To “inform” the mice’s cells as to which genes the CRISPR-Cas gene scissors should destroy, the researchers used the adeno-associated virus (AAV), a delivery strategy that can target any organ. They prepared the viruses so that each virus particle carried the information to destroy a particular gene, then infected the mice with a mixture of viruses carrying different instructions for gene destruction. In this way, they were able to switch off different genes in the cells of one organ. For this study, they chose the brain.

New pathogenic genes discovered

Using this method, the researchers from ETH Zurich, together with colleagues from the University of Geneva, obtained new clues to a rare genetic disorder in humans, known as 22q11.2 deletion syndrome. Patients affected by the disease show many different symptoms, typically diagnosed with other conditions such as schizophrenia and autism spectrum disorder. Before now, it was known that a chromosomal region containing 106 genes is responsible for this disease. It was also known that the disease was associated with multiple genes, however, it was not known which of the genes played which part in the disease.

For their study in mice, the researchers focused on 29 genes of this chromosomal region that are also active in the mouse brain. In each individual mouse brain cell, they modified one of these 29 genes and then analysed the RNA profiles of those brain cells. The scientists were able to show that three of these genes are largely responsible for the dysfunction of brain cells. In addition, they found patterns in the mouse cells that are reminiscent of schizophrenia and autism spectrum disorders. Among the three genes, one was already known, but the other two had not previously been the focus of much scientific attention.

“If we know which genes in a disease have abnormal activity, we can try to develop drugs that compensate for that abnormality,” says António Santinha, a doctoral student in Platt’s group and lead author of the study.

Patent pending

The method would also be suitable for use in studying other genetic disorders. “In many congenital diseases, multiple genes play a role, not just one, Santinha says. “This is also the case with mental illnesses such as schizophrenia. Our technique now lets us study such diseases and their genetic causes directly in fully grown animals.” The number of modified genes could be increased from the current 29 to several hundred genes per experiment.

“It’s a big advantage that we can now do these analyses in living organisms, because cells behave differently in culture to how they do as part of a living body,” Santinha says. Another advantage is that the scientists can simply inject the AAVs into the animals’ bloodstreams. There are various different AAVs with different functional properties. In this study, researchers used a virus that enters the animals’ brains. “Depending on what you’re trying to investigate, though, you could also use AAVs that target other organs,” Santinha says.

ETH Zurich has applied for a patent on the technology. The researchers now want to use it as part of a spin-off they are establishing.

***

Perturbing the genome

The technique presented here is one of a series of new genetic editing methods used to alter the genome of cells in a mosaic-like manner. CRISPR perturbation is the technical term for this research approach that involves the perturbation of the genome using CRISPR-Cas gene scissors. This approach is currently revolutionising research in the life sciences. It makes it possible to obtain a great deal of information from a single scientific experiment. As a result, the approach has the potential to accelerate biomedical research, such as in the search for the molecular causes of genetically complex diseases.

A week ago, another research group from the Department of Biosystems Science and Engineering at ETH Zurich in Basel, working with a team from Vienna, published a study in which they applied CRISPR perturbation in organoids (see ETH News). Organoids are microtissue spheroids that are grown from stem cells and have a similar structure to real organs – in other words, they are a sort of miniature organ. They are an animal-free research method that complements research on animals. Because both methods – CRISPR perturbation in animals and in organoids – can provide more information with fewer experiments, both have the potential to ultimately reduce the number of animal experiments.

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JOURNAL

Nature

DOI

10.1038/s41586-023-06570-y 

ARTICLE TITLE

Transcriptional linkage analysis with in vivo AAV-Perturb-seq

ARTICLE PUBLICATION DATE

20-Sep-2023

 

County-level sociodemographic characteristics and availability of COVID-19 therapeutic drugs

JAMA Network Open

Peer-Reviewed Publication

JAMA NETWORK

About The Study: The results of this study showed sociodemographic-based disparities in geographic clustering of COVID-19 therapeutic drugs, highlighting disparities in access to these drugs. With the end of the COVID-19 Public Health Emergency, these findings highlight an important gap in treatment access. 

Authors: Kosuke Tamura, Ph.D., of the National Institutes of Health in Bethesda, Maryland, is the corresponding author. 

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/ 

(doi:10.1001/jamanetworkopen.2023.34763)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support. 

http://jamanetwork.com/journals/jamanetworkopen/fullarticle/10.1001/jamanetworkopen.2023.34763?utm_source=For_The_Media&utm_medium=referral&utm_campaign=ftm_links&utm_term=092023

About JAMA Network Open: JAMA Network Open is an online-only open access general medical journal from the JAMA Network. On weekdays, the journal publishes peer-reviewed clinical research and commentary in more than 40 medical and health subject areas. Every article is free online from the day of publication. 

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JOURNAL

JAMA Network Open