Category: 8. Health

A new study has identified early-pregnancy gut microbiota signatures associated with the development of gestational diabetes mellitus, a metabolic disorder that carries substantial risks to both maternal and fetal health. The study, published in the American Society for Microbiology journal Microbiology Spectrum, provides new avenues for gestational diabetes prevention and management.

Gestational diabetes is a prevalent metabolic disorder characterized by abnormal glucose metabolism, primarily in the mid to late stages of pregnancy. Early intervention for gestational diabetes can substantially reduce complications for both mother and baby. Gestational diabetes significantly increases the risk of maternal complications such as gestational hypertension, polyhydramnios, and cesarean delivery, while also posing long-term health risks for the fetus, including asphyxia at birth and increased susceptibility to obesity and diabetes in adulthood.

In the new study, researchers from The Second Hospital, Southern Medical University, and the Third Affiliated Hospital of Guangzhou Medical University, all in Guangzhou, China, set out to identify gut microbiota dysbiosis that is strongly linked to the onset and progression of gestational diabetes that may serve as a critical early-warning biomarker. The scientists analyzed the fecal microbiota of 61 pregnant women during their first trimester of pregnancy using 16S rRNA sequencing. They then correlated these microbial profiles with oral glucose tolerance test results at 24-28 weeks of gestation and clinical delivery outcomes.

The researchers discovered that there were significant differences in gut microbiota composition between those with gestational diabetes and women who had healthy pregnancies. Based on their findings, the researchers developed an early diagnostic model for gestational diabetes, based on genus-level markers, with high diagnostic precision.

“These findings suggest that microbiota-based tools could enable early, non-invasive detection of gestational diabetes mellitus, offering new opportunities for prevention and personalized management,” write the study authors. “This research highlights the role of the gut microbiome in pregnancy and has important implications for improving maternal and fetal health outcomes.”

While glucose, or sugar, is a well-known fuel for the brain, Weill Cornell Medicine researchers have demonstrated that electrical activity in synapses—the junctions between neurons where communication occurs—can lead to the use of lipid or fat droplets as an energy source.

The study, published July 1 in Nature Metabolism, challenges “the long-standing dogma that the brain doesn’t burn fat,” said principal investigator Dr. Timothy A. Ryan, professor of biochemistry and of biochemistry in anesthesiology, and the Tri-Institutional Professor in the Department of Biochemistry at Weill Cornell Medicine. 

The paper’s lead author, Dr. Mukesh Kumar, a postdoctoral associate in biochemistry at Weill Cornell Medicine who has been studying the cell biology of fat droplets, suggested that it makes sense that fat may play a role as an energy source in the brain like it does with other metabolically demanding tissues, such as muscle.

The research team was particularly intrigued by the DDHD2 gene, which encodes a lipase, or enzyme that helps break down fat. Mutations in DDHD2 are linked to a type of hereditary spastic paraplegia, a neurological condition that causes progressive stiffness and weakness in the legs, in addition to cognitive deficits.

Prior research by other investigators has demonstrated that blocking this enzyme in mice causes a build-up of triglycerides—or fat droplets that store energy—throughout the brain.  “To me, this was evidence that maybe the reason we claim the brain doesn’t burn fat is because we never see the fat stores,” Dr. Ryan said. 

Research demonstrates lipids have an important role

The current study explored whether the lipid droplets that build up in the absence of DDHD2 are used as fuel by the brain, particularly when glucose isn’t present, Dr. Ryan said.

Dr. Kumar found that when a synapse contains a lipid droplet filled with triglycerides in mice without DDHD2, neurons can break down this fat into fatty acids and send it to the mitochondria—the cell’s energy factories—so they can produce adenosine triphosphate (ATP), the energy the cell needs to function.

The process of being able to use the fat is controlled by the electrical activity of the neurons, and I was shocked by this finding. If the neuron is busy, it drives this consumption. If it’s at rest, the process isn’t happening.”  

Dr. Timothy A. Ryan, professor of biochemistry and of biochemistry in anesthesiology

In another study, researchers injected a small molecule into mice to block the enzyme carnitine palmitoyltransferase 1 (CPT1), which helps transport fatty acids into the mitochondria for energy production. Blocking CPT1 prevented the brain from using fat droplets, which then led to torpor, a hibernation-like state, in which the body temperature rapidly plummets and the heartbeat slows. “This response convinced us that that there’s an ongoing need for the brain to use these lipid droplets,” Dr. Ryan said.

Implications for future research

This research may encourage the further investigation of neurodegenerative conditions and the role of lipids in the brain. Glucose fluctuations or low levels of glucose can occur with aging or neurological disease, but fatty acids broken down from lipid droplets may help to maintain the brain’s energy, Dr. Kumar said. “We don’t know where this research will go in terms of neurodegenerative conditions, but some evidence suggests that accumulation of fat droplets in the neurons may occur in Parkinson’s disease,” he said.

Researchers also need to better understand the interplay between glucose and lipids in the brain, Dr. Ryan said. “By learning more about these molecular details, we hope to ultimately unlock explanations for neurodegeneration, which would give us opportunities for finding ways to protect the brain.”

This research was supported in part by the National Institute of Neurological Disorders and Stroke and the National Cancer Institute, both part of the National Institutes of Health, through grant numbers NS036942, NS11739 and F31CA278383. Additional support was provided by Aligning Science Across Parkinson’s through grant number ASAP-000580.

Schoolchildren born late in the year are at greater risk of developing mental health problems compared with their older peers, according to a new study.

A recent study by the Norwegian University of Science and Technology (NTNU) has found that children born in October, November or December are statistically more often identified as having a mental health diagnosis than their classmates born earlier in the year. The findings apply to both boys and girls, and regardless of whether they were born full term or prematurely.

Extensive research material

The researchers have followed over one million Norwegians aged 4 to 17 years (all born between 1991 and 2012) through Norwegian health registries.

The aim of the study was to identify what are known as ‘relative age effects’. In other words, whether children and adolescents born late in the year are more frequently diagnosed with mental health disorders than their peers born early in the year (January, February and March).

Our findings show that the youngest members of a school class tend to be diagnosed with a mental illness more frequently than the oldest.

This is most obvious with regard to ADHD, where we saw an increase in incidence of 20-80 per cent for the youngest class members, depending on whether the children were born full term or prematurely.”

Christine Strand Bachmann, a PhD research fellow at the Norwegian University of Science and Technology (NTNU’s) Department of Public Health and Nursing

The researchers found the same trend for ‘other neuropsychiatric disorders’. These include delayed developments in areas such as language, academic skills and motor skills.

The study has been published in BMJ Peadiatrics Open.

Additional risks for premature girls

In addition, the youngest premature girls were at a significantly greater risk of being diagnosed with emotional disorders, such as anxiety, depression and adaptation disorders, compared with the oldest premature girls in the same year group.

“We know that children and adolescents born prematurely are already more vulnerable to poor mental and social health compared with children and young people born full term. For those born prematurely, the risks associated with being born late in the year comes in addition to this vulnerability.

“We believe that these findings, which show an increase in the number of psychological diagnoses for the youngest class members, can partly be linked to the way in which we organize our education system. The school system is unable to adequately provide for children with normal, but more immature behaviour. Possible solutions include flexible school start dates or additional support.”

In addition to being a researcher at NTNU, Christine Strand Bachmann is also a consultant at the Neonatal Intensive Care Unit, Children and Adolescent Medicine Department, St. Olavs Hospital.

In a large community-based study, researchers at Fatty Acid Research Institute observed weak but statistically significant inverse associations between several types of inflammatory biomarkers with omega-6 fatty acids.

“Chronic inflammation is recognized as an important risk factor for a variety of health disorders,” said Fatty Acid Research Institute’s president William Harris and his colleagues.

“Omega-6 fatty acids, particularly linoleic (LA) and arachidonic acid (AA), have been shown to be either pro- or anti-inflammatory, and researchers have advocated both for and against reducing their dietary intake.”

The authors relied on data from the Framingham Offspring Study, a well-known research cohort from the Boston area.

The Framingham Offspring Study is a landmark longitudinal research initiative that follows the children of participants in the original Framingham Heart Study to investigate genetic and lifestyle factors influencing cardiovascular and metabolic health.

Launched in 1971, it has provided decades of valuable insights into chronic disease risk and prevention.

The cohort’s rigor and continuity make it one of the most trusted sources for understanding long-term health trajectories.

This was a cross-sectional study, meaning that the LA and AA levels were measured in the same blood samples as the 10 inflammation-related biomarkers in 2,700 individuals.

The relationships between the levels of these two omega-6 fatty acids and 10 separate blood/urine biomarkers of inflammation and oxidative stress were statistically evaluated.

After adjusting (controlling statistically) for multiple other potentially confounding factors (age, race, sex, smoking, blood lipid levels, blood pressure, body weight, etc.), the researchers found that higher LA levels were associated with statistically significantly lower levels of five of the 10 biomarkers, and in no case was higher LA related to higher levels of any biomarker.

For AA, higher levels were linked with lower concentrations of four markers, and, like LA, there were no statistically significant associations with higher levels of inflammation/oxidation.

“These new data show clearly that people who have the highest levels of LA (and AA) in their blood are in a less inflammatory state than people with lower levels,” Dr. Harris said.

“This finding is exactly the opposite of what one would expect if omega-6 fatty acids were ‘proinflammatory’ — in fact, they appear to be anti-inflammatory.”

“In the flurry of news stories about the harms of seed oils — the primary sources of LA in the diet — many voices are calling for reducing Americans’ intakes of LA.”

“This is not a science-based recommendation, and this study — in addition to many more — point in precisely the opposite direction: instead of lowering LA intakes, raising intakes appears to be a healthier recommendation.”

“These findings contradict a narrative, not previous research findings.”

“There are many studies in the medical literature that are consistent with our findings here.”

The study was published June 22 in the journal Nutrients.

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Heidi T.M. Lai et al. 2025. Red Blood Cell Omega-6 Fatty Acids and Biomarkers of Inflammation in the Framingham Offspring Study. Nutrients 17 (13): 2076; doi: 10.3390/nu17132076

Epilepsy is among the most common neurological conditions, marked by unpredictable seizures, accidents and injuries, reduced quality of life, stigma and-in the worst case-premature death. 

But a program-developed over several years by a Case Western Reserve University-led research team-that teaches people with epilepsy how to “self-manage” their disorder is showing positive results.

The program has been found to help people with epilepsy reduce related health complications and improve their mood and quality of life, according to a new study recently published in the peer-reviewed journal, Epilepsy & Behavior.

Results of this study provide a model for broad and practical expansion of the program to people with epilepsy.”

Martha Sajatovic, the L. Douglas Lenkoski MD Professor in Psychiatry at the Case Western Reserve University School of Medicine

Sajatovic, who co-led the study funded by the U.S. Centers for Disease Control and Prevention (CDC), is also the Willard Brown Chair in Neurological Outcomes Research and director of the Neurological and Behavioral Outcomes Center at University Hospitals Cleveland Medical Center. The study was also co-led by Gena Ghearing, formerly at the University of Iowa and now a professor of neurology at the Icahn School of Medicine at Mount Sinai in New York. Collaborators also included researchers at the University of Cincinnati.

Self-managing the disorder

Epilepsy is a chronic health condition triggered by abnormal electrical activity in the brain

in which individuals experience recurrent-and usually unpredictable-seizures. According to the CDC:

• 1.2% of the United States population has active epilepsy. That’s about 3 million adults and 470,000 children nationally.
• Epilepsy can last a lifetime and may be triggered by events like stroke and traumatic brain injury.

Given that people with chronic health conditions often have limited contact with their healthcare providers, self-management interventions have gained increasing attention for their potential benefit.

In particular, how well epilepsy patients manage the condition depends on their daily behavior, such as consistently taking medication, proper nutrition, exercise, stress management and avoiding activities or triggers that can make it more likely for seizures to occur, such as being sleep-deprived.

With that in mind, the CDC’s Managing Epilepsy Well (MEW) network has led the development, testing and growth of various successful epilepsy self-management approaches over the last dozen years. 

Among them is a program Sajatovic and the Case Western Reserve team developed, called SMART, to support people with epilepsy who have experienced health complications, including poorly controlled seizures.

How it works

SMART features remote self-management training sessions for groups of six to 10 people with epilepsy. They meet by video conferencing for about an hour weekly for eight to 10 weeks.

The sessions are led by a nurse and “peer educator”-a person with epilepsy trained to deliver the detailed curriculum designed to help people learn to better manage and cope with their epilepsy and improve their overall well-being. Participants also get written resource materials to help them continue to practice refining their epilepsy self-management skills.

“Many people who participate in our SMART program have never been in a group with other people with epilepsy and find this a particularly valuable and rewarding part of the program,” Sajatovic said.

The study

SMART’s effectiveness was measured in two independent research studies. The published report summarizes the results of a clinical research study of 160 people with epilepsy. Half used the SMART program; half did not.

Compared to the control group, people with epilepsy who participated in the SMART program demonstrated reduced complications of the condition as well as improved mood and quality of life and an increase in the ability to manage their epilepsy. 

“This new clinical trial confirms the positive effects of SMART and also demonstrates how effective a simple and relatively inexpensive telehealth delivery can be,” Sajatovic said.

What’s ahead

The study team at Case Western Reserve has made substantial progress to refine, implement and expand the SMART program in community settings by collaborating with the Epilepsy Association in Cleveland, the Epilepsy Alliance of Ohio and the Epilepsy Association of Western and Central Pennsylvania, as well as with epilepsy treatment centers in Ohio and in Iowa.

“I am most excited about the possibility of establishing successful models of delivering SMART that can be used by clinical-care teams and by epilepsy-focused social services agencies,” Sajatovic said. “I am hopeful that we can make the SMART program available to as many people with epilepsy as possible.”

Mayo Clinic researchers have developed an artificial intelligence–based clinical decision support system (CDSS) that could help clinicians identify patterns of brain activity associated with 9 types of dementia, including Alzheimer disease, from a single FDG-PET brain scan.¹ The tool, called StateViewer, was trained and validated on more than 3,600 brain scans and in a new study achieved a sensitivity of 0.89 ± 0.03 and an area under the receiver operating characteristic (ROC) curve of 0.93 ± 0.02 in distinguishing neurodegenerative phenotypes.¹

In the radiologic reader study, which compared the tool’s integration into standard workflow, clinical readers using StateViewer had 3.3 ± 1.1 times greater odds of making a correct diagnosis than those using standard-of-care practices. It also enabled nearly twice the speed of interpretation. The research was published June 27, 2025, in Neurology.¹

StateViewer has the potential to remedy a core challenge in dementia care: identifying the disease early and precisely, even when multiple conditions are present, the Mayo team said in a statement.² “Every patient who walks into my clinic carries a unique story shaped by the brain’s complexity,” lead author David Jones, MD, neurologist and director of the Mayo Clinic Neurology Artificial Intelligence Program, said in the Mayo statement. The intricacy of the brain drew Jones to neuroscience in the first place, he added, and supports his deep “commitment to clearer answers. StateViewer reflects that commitment — a step toward earlier understanding, more precise treatment and, one day, changing the course of these diseases.”²

The system uses a neighbor-matching algorithm to compare an individual patient’s FDG-PET scan with a large reference dataset of confirmed dementia cases. It then produces color-coded brain activity maps highlighting regions that match specific disease patterns. Among the 9 syndrome the tool is designed to detect are Alzheimer disease, Lewy body dementia, posterior cortical atrophy, and frontotemporal dementia.¹

The discovery cohort consisted of 3,671 individuals (mean age 68 years, 49% women), drawn from 3 research studies and clinical patient populations. All patients had FDG-PET imaging within 2.5 years of diagnosis. The system’s classification performance was externally validated in the Alzheimer’s Disease Neuroimaging Initiative dataset. While promising, the authors noted that the discovery cohort may not fully represent broader clinical populations.¹

Mayo Clinic researchers plan further evaluation of StateViewer across a range of clinical environments. The tool’s use of a widely available imaging modality and its visual interpretability could help expand access to specialist-level insights in clinics that lack neurology expertise.² Access to neurologists is extremely limited, particularly in low income and rural areas where financial, time, and travel restrictions put specialist appointments out of reach or where wait times can be extreme. The broader goal for StateViewer is to expand the technology beyond the Mayo Clinic where it could be “transformative on a global scale in the near future and expand access to these data-driven insights.”³

Dr. Jones partnered with Mayo Clinic data scientist Leland Barnard, PhD to build the system. “As we were designing StateViewer, we never lost sight of the fact that behind every data point and brain scan was a person facing a difficult diagnosis and urgent questions,” he said in a statement. “Seeing how this tool could assist physicians with real-time, precise insights and guidance highlights the potential of machine learning for clinical medicine.”²

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References

1. Barnard L, Botha H, Corriveau-Lecavalier N, et al. An FDG-PET-based machine learning framework to support neurologic decision making in Alzheimer disease and related disorders. Neurology. 2025;105(2). doi:10.1212/WNL.0000000000213831

2. Murphy S. Mayo Clinic’s AI tool identifies 9 dementia types, including Alzheimer’s, with one scan. News release. Mayo Clinic. June 27, 2025. Accessed July 1, 2025. https://newsnetwork.mayoclinic.org/discussion/mayo-clinics-ai-tool-identifies-9-dementia-types-including-alzheimers-with-one-scan/

3. Lindquist SB. Mayo Clinic neurology AI program tests platform to detect brain diseases. News release. Mayo Clinic. December 17, 2024. Accessed July 1, 2025. https://newsnetwork.mayoclinic.org/discussion/mayo-clinic-neurology-ai-program-tests-platform-to-detect-brain-diseases/

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