Distinct Nature of Parkinson’s Disease Gut Microbiome Identified

Research led by University College London has characterized a specific gut microbiome signature found in people with Parkinson’s disease.

Writing in Nature Medicine, the researchers also found that people carrying a genetic mutation in the GBA1 gene that put them at risk of developing Parkinson’s disease had gut microbiomes similar to people with the condition.

Parkinson’s is the second most common neurodegenerative disease in the U.S. after Alzheimer’s disease affecting more than one million people across the country. By the time full-blown motor symptoms emerge, a large degree of neurological damage has already occurred, so much work is underway to find ways to predict and diagnose early disease, as well as to develop more effective treatments.

“In recent years there has been a growing recognition of the links between Parkinson’s disease—a brain disorder—and gut health,” said co-lead author Anthony Schapira, MD, a professor at UCL Queen Square Institute of Neurology, in a press statement.

“Here we have strengthened that evidence and shown that microbes in the gut can reveal signs of Parkinson’s and may be an early warning signal… years before symptom onset.”

For this study, the researchers evaluated gut microbiome samples from 271 Parkinson’s disease patients, 43 people carrying GBA1 risk variants who did not yet have disease symptoms and 150 healthy controls. They also validated their findings in a further 638 people with Parkinson’s and 319 healthy controls from the U.K., Korea, and Turkey.

Schapira and team used DNA sequencing to see which bacterial species were present in each person’s gut. Comparing people with Parkinson’s disease to healthy controls, they found 176 bacterial species that were more or less common in people with the condition.

For example, people with Parkinson’s had more potentially pro‑inflammatory bacteria, including Bifidobacterium longum and B. dentium, Streptococcus mutans, and Lactobacillus paragasseri, than healthy controls.

In contrast, healthy controls had more helpful, butyrate‑producing gut bacteria from including Roseburia intestinalis, R. inulinivorans and some Faecalibacterium species and less pro-inflammatory species.

Notably, people in the at-risk group who carried a GBA1 risk variant had a gut microbiome somewhere between healthy controls and people with Parkinson’s, suggesting that the composition of microbes in the gut may change over time as the disease develops. In this group, 142 of the 176 species that differed in people with Parkinson’s versus healthy controls also showed changed abundance.

“For the first time we identify bacteria in the gut of people with Parkinson’s that can also be found in those with a genetic risk for the disease, but before they develop symptoms. Importantly, these same changes can be found in a small proportion of the general population that may put them at increased risk for Parkinson’s,” said Schapira.

“This discovery opens the way not only to see if the bacteria are a way to identify those at risk of Parkinson’s, but also to see if changing the bacterial population, through dietary changes or medication, can reduce a person’s risk for Parkinson’s.”

The post Distinct Nature of Parkinson’s Disease Gut Microbiome Identified appeared first on Inside Precision Medicine.

STAT+: Trump order to advance psychedelic treatments generates excitement — and worries

President Trump’s executive order aimed at loosening restrictions on psychedelics as mental health treatments was largely applauded by advocates. But some also quietly worry the White House’s role in trying to bolster the field risks politicizing it and undermining the credibility of research.

The order, which was reported to have stemmed at least in part from a text podcaster Joe Rogan sent Trump about psychedelics research, directs the Food and Drug Administration to expedite the review of some compounds and calls for the establishment of a new regulatory pathway for experimental psychedelics to be tried by terminally ill patients. It also allocates funding to states developing research programs.

While the order does not actually reschedule any drugs or change legislation, many advocates and researchers welcomed the move, saying it signals the administration’s interest in advancing psychedelics as treatments and could help ease bottlenecks in expanding access.

Continue to STAT+ to read the full story…

AACR 2026: Cancers of Unknown Primary Identified by DNA Methylation AI Model

SAN DIEGO – Researchers from Kindai University in Japan have developed a machine learning model that accurately predicts the origin of diverse cancer types in patients with cancers of unknown primary (CUP) by analyzing CpG-based DNA methylation. Results showed that the model correctly identified the cancer type in about 95% of cases in the test cohort, and achieved 87% accuracy when applied to an independent validation cohort from 31 cases representing 17 different cancer types. The work was presented at the American Association for Cancer Research (AACR) Annual Meeting.  

“Our findings suggest that DNA-based approaches can help identify where a cancer may have started, even when the original tumor is not visible,” said Marco A. De Velasco, PhD, a faculty member in the department of genome biology at Kindai University in Japan.  

CUP are metastatic malignancies in which the primary cancer site could not be identified. These cancers are often associated with poorer outcomes, as patients are typically treated with broad, nonspecific chemotherapy regimens rather than therapies targeted to a specific cancer type. 

Approximately only 15-20% of patients with CUP show features that allow site-specific therapies. Patients receiving site-directed therapy can survive up to 24 months, compared with six to nine months for those receiving standard treatment. 

Patterns in tumor biology, such as gene activity or chemical modifications to DNA, can differ between cancer types and persist even after the cancer has spread and guide development of these therapies. While some methods have shown promise, they have yet to demonstrate clear survival benefits in clinical trials. 

The model was developed using methylation data from nearly 7,500 patients with 21 different cancer types obtained from The Cancer Genome Atlas Program and other public datasets. Using machine learning, the researchers identified CpG methylation and built methylation profiles that were associated with different tumor types. 

Del Velasco emphasized that the study achieved high accuracy in predicting the origin of diverse cancer types using a small subset of DNA markers, about 1,000 CpG regions selected from hundreds of thousands across the genome. “This is important because it shows that we can simplify complex molecular data while still maintaining strong predictive performance,” he said. 

As a limitation, the model was developed using cancers with known origins, rather than true CUP. Testing in CUP patients is important to understand how well the model performs in clinical settings. Additionally, not all tumors are easily accessible for genetic testing, particularly tumors in advanced stage. Looking ahead, the authors aim to adapt and evaluate the model using blood-based biopsy to analyze circulating tumor DNA instead of relying on DNA from tissue samples. 

The post AACR 2026: Cancers of Unknown Primary Identified by DNA Methylation AI Model appeared first on GEN – Genetic Engineering and Biotechnology News.

AACR 2026: David Parkinson and the Arc of Modern Cancer Therapy

SAN DIEGO, CA – In 1977, when David R. Parkinson, MD, graduated from medical school at the University of Toronto and moved to McGill University to train in internal medicine and eventually hematology, the idea of medical oncology was in its infancy. In Canada, the profession didn’t exist.

“In Canada, there were no medical oncologists,” Parkinson told Inside Precision Medicine. “Radiation therapists administered what little chemotherapy existed. They resisted the development of medical oncology as a specialty.”

David Parkinson - AACR
David R. Parkinson, MD, recipient of the 2026 AACR Outstanding Achievement Award for Service to Cancer Science and Medicine [The American Association for Cancer Research (AACR)]

Through the ensuing 49 years, Parkinson didn’t just see the rise of kinase inhibitors, antibodies, and cell therapies in real-time—he helped create the world of modern cancer therapeutics.

In reflecting on his remarkable career, which was recognized with the 2026 AACR Outstanding Achievement Award for Service to Cancer Science and Medicine, Parkinson said, “I’ve essentially grown alongside the field.”

From scarcity to structure: Oncology’s early years

When Parkinson arrived in Montreal, there were only a handful of chemotherapeutics available. “In those days, there were only one or two drugs available for hematologic malignancies across the entire field,” Parkinson said. “The main treatments were cyclophosphamide and nitrosoureas.”

Even supportive care lagged. “Initially, we had no effective way to control chemotherapy-induced nausea,” he noted of the standard of care for testicular cancer. “Some patients stopped treatment because they couldn’t tolerate it.”

Parkinson explained that early cancer drugs worked best on rapidly dividing tumors, like leukemias and testicular cancers, because that’s what the animal models represented. These therapies targeted DNA and cell division broadly, often with severe toxicity, and were far less effective against slower-growing solid tumors.

After his residency at McGill, Parkinson moved to Boston, first to Tufts New England Medical Center on a modest Canadian fellowship that placed him at the edge of a field just beginning to coalesce. “I was on a Canadian fellowship earning $12,000 a year,” he said. “The exchange rate fluctuated significantly, which made things difficult, and I couldn’t work due to my student visa.”

What he found, however, was momentum. Through connections with Dana-Farber, Parkinson entered formal training in medical oncology as the specialty began to take shape. “I connected with Dana-Farber and took their introductory course for fellows—that was my entry into medical oncology.”

At the same time, breakthroughs in specific cancers hinted at what might be possible. “What really shaped my thinking was the emergence of treatments for testicular cancer just as I entered oncology,” he said. “Platinum-based therapies—and later combination regimens—felt like miracles. We had never seen anything like it. These were often young patients, difficult to manage, but suddenly there were real cures.”

Targeted therapy and the Gleevec moment

Parkinson’s career soon intersected with early efforts to harness the immune system against cancer—decades before immunotherapy became a dominant paradigm. “I became deeply involved in immunotherapy, particularly interleukin-2 and early tumor-infiltrating lymphocyte studies,” he said.

Working at the National Cancer Institute (NCI), he collaborated with leaders, including immunotherapy pioneer Steven Rosenberg, MD, PhD, maintaining a hybrid role that combined research with clinical care. “At the same time, I continued clinical work for a couple of months each year, collaborating with Steve Rosenberg in the surgical branch.”

These early approaches were technically challenging and often unpredictable, but they laid the groundwork for later advances. “We started with basic approaches, moved to tumor-infiltrating lymphocytes, and eventually to engineered CAR T cells,” Parkinson said. “Progress has been steady, though often slower than those treating patients would like.”

If immunotherapy represented one trajectory, targeted therapy represented another—one that depended on a deeper understanding of cancer biology.

“When I joined Novartis in the late 1980s, we were among the first developing kinase inhibitors,” Parkinson said. At the time, the idea was controversial. “Early skepticism suggested kinase inhibitors wouldn’t work due to high intracellular ATP levels and structural challenges.”

But advances in molecular biology were beginning to change the landscape. The discovery of the Philadelphia chromosome and its associated oncogene created a clear therapeutic target. “The Philadelphia chromosome had been known since the 1960s, and by the 1980s the responsible gene was identified,” Parkinson explained.

The result was imatinib (Gleevec), a drug that would become a prototype for precision oncology. “Eventually, a small molecule inhibitor was developed that targeted it precisely.”

The clinical results were extraordinary. “By the third cohort in a Phase I trial, patients with chronic myelogenous leukemia showed dramatic responses—some within 24 hours,” Parkinson said. “It’s probably the only Phase I oncology trial where essentially every patient achieved remission.”

For Parkinson, the implications extended far beyond a single drug. “Of course, [Gleevec] was a unique case,” he said. “But it proved an important point: what once seemed impossible can become possible.”

Since then, the field has expanded dramatically. Hundreds of kinase inhibitors have been developed, with thousands more explored, reflecting a broader shift toward therapies grounded in specific molecular mechanisms.

Precision medicine—and its limits

As oncology evolved, so too did its language. “For years, we called it ‘personalized medicine,’” Parkinson said. “I used to joke that medicine has always been personalized—you’re always trying to determine what’s best for a specific patient in a specific context.”

He credits industry with popularizing a more precise term. “Although Pfizer popularized the term ‘precision medicine,’ I think it’s a better term,” he added, with a note of humor: “I have a few good Pfizer jokes—best shared over a drink.”

Yet the reality of precision medicine has proven more complex than its promise. “The evolution of therapeutics mirrored the models and biological understanding available,” Parkinson said. “Targeted therapies only emerged once we understood the biology. Diagnostics, however, lagged by about two decades.”

That lag remains a structural challenge. Parkinson founded a diagnostics company based on single-cell signaling technology developed at Stanford. “Technically, it worked—we solved major challenges in instrumentation, standardization, and analysis,” he said. “But we couldn’t establish a viable business model.”

The core issue was reimbursement. “Without adequate reimbursement from Medicare, even highly sophisticated diagnostics struggle commercially,” said Parkinson. “Better diagnostics can reduce the use of expensive drugs by identifying who won’t benefit—something that doesn’t always align with pharmaceutical business models.”

In recent years, Parkinson has focused increasingly on large-scale data integration, including his involvement with the GENIE consortium. The initiative aggregates genomic and clinical data across institutions, aiming to accelerate discovery and improve clinical decision-making. “GENIE has been a technical success,” he said. “But its long-term sustainability remains uncertain.”

The broader challenge, he argues, is conceptual as much as technical. “Looking forward, the field is evolving toward integrating multiple data types—genomics, transcriptomics, imaging, and more—to better understand tumor biology,” he said. “Sequencing alone isn’t enough. The challenge now is not a lack of data, but making sense of it—something where artificial intelligence will play an increasingly important role.”

Back to basics

Across academia, government, and industry—including roles at the NCI, Novartis, Amgen, and Biogen Idec—Parkinson sees a single throughline. “I remember an interview with a biotech company where an HR representative told me, ‘You seem to have done a lot of different things,’” he said. “I responded that I had really only done one thing: trying to improve cancer treatment, just from many different angles.”

Not every effort succeeded. “In one case, we developed a drug that performed beautifully in mice but failed in human trials,” he said. “That’s common in oncology—most ideas don’t translate. You don’t think of it as failure but as learning. Still, there’s a limit to how many ‘learnings’ one can appreciate.”

Reflecting on decades of progress, Parkinson emphasizes both how far the field has come and how much remains unresolved. “Outcomes have improved dramatically across several cancers, especially hematologic ones,” he said.

Yet he underscores a fundamental principle: that progress in cancer treatment comes down to understanding biology. “The better we understand it, the more effectively we can develop targeted therapies,” said Parkinson. “Without that understanding, we’re essentially guessing.”

At AACR 2026, Parkinson’s recognition underscores not just past achievements but a continuing trajectory—one shaped by the interplay of discovery, failure, and persistence. “Despite all the challenges,” he said, “[precision medicine] is still the most promising path forward.”

 

The post AACR 2026: David Parkinson and the Arc of Modern Cancer Therapy appeared first on Inside Precision Medicine.

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