Carrying far too much weight when diagnosed with MS (multiple sclerosis) is linked to higher current and subsequent levels of disability within a relatively short period of time, finds research published online in the Journal of Neurology Neurosurgery & Psychiatry. 

Reverting to a healthy weight may improve clinical outcomes for obese patients with MS, suggest the researchers.

Obesity during childhood and adolescence is associated with a heightened risk of developing MS, irrespective of other potential environmental triggers. But it’s not clear if it might also be linked to faster disability progression after diagnosis. 

To try and find out, the researchers drew on 1066 participants with relapsing-remitting MS from across Germany who were taking part in The German National MS (NationMS) study. More than a quarter (29.5%, 315) of them were men with an average age of 33.

When MS was diagnosed, 159 patients (15%) were obese with a BMI of at least 30. Co-existing conditions associated with obesity (type 2 diabetes, high blood pressure) were reported in 68 patients (just under 6.5%). 

Their levels of disability were monitored every 2 years for a total of 6 years, using the Expanded Disability Status Scale (EDSS). This ranges from 0 to 10 in 0.5 unit increments.

Obesity at diagnosis wasn’t associated with a higher annual relapse rate, or greater build-up of nerve damage, as seen on MRI brain scans, over the 6-year monitoring period.

But levels of disability were higher at the time of diagnosis and at each of the subsequent three time points, after factoring in age, sex, and smoking. And the average time it took obese patients to accumulate greater levels of disability was shorter. They reached EDSS 3 at just under 12 months, on average, compared with nearly 18 months for those who weren’t obese.

Obese patients were also more than twice as likely to reach EDSS 3 within 6 years, irrespective of what type of drug treatment they were getting.

Complete health data were available for 81 (51%) of the obese MS patients and for 430 (just under 47.5%) of the others.

The risk of reaching EDSS 3 within 6 years in this group was again more than twice as high in obese patients as it was in those who weren’t, falling to an 84% heightened risk after factoring in sex, age, and smoking. 

Importantly, overweight (BMI 25–29.9) at diagnosis wasn’t significantly associated with higher disability then or subsequently, or with a heightened risk of reaching an EDSS of 3 after 6 years. 

This is an observational study, and as such, can’t establish cause. And the researchers acknowledge that BMI was assessed only once at the start of the study while co-existing conditions were limited to type 2 diabetes and high blood pressure, with the number of those affected, small.

But previous research has linked a reduction in brain grey matter with obesity, they point out.

“Our finding that obesity, but not overweight in MS patients, is associated with a poorer outcome suggests a threshold effect of body mass on disability accumulation in MS,” they write, adding that obesity is a modifiable risk factor.

“These data suggest that dedicated management of obesity should be explored for its potential merit in improving long-term clinical outcomes of patients diagnosed with MS,” they conclude.

A video about common misconceptions in MS filmed from my hotel room balcony when I was on vacation in Oahu.

A new study from UCLA researchers identified an animal model that could be used to study treatments for improving disabilities in multiple sclerosis patients. 

BACKGROUND 

Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease in which the immune system attacks nerves in the brain and spinal cord. There are numerous treatments aimed at immune mechanisms and reducing MS relapses, but none is designed to protect cells in the brain and spinal cord from damage. Existing treatments have limited effectiveness in slowing disability accumulation and none actually improve disabilities. 

Identifying an animal model of disease progression is a critical step toward finding better treatments since the mechanisms underlying disease progression could be identified and then blocked.  

FINDINGS 

Dr. Rhonda Voskuhl, MD, the Director of the UCLA Multiple Sclerosis Program, and Dr. Allan Mackenzie-Graham, PhD, an associate professor of neurology, have identified an animal model that shares many similarities with progressive MS. 

Previously, acute and relapsing forms of experimental autoimmune encephalomyelitis (EAE), a mouse model characterized by inflammation within blood and spinal cord, played a central role in development of current anti-inflammatory treatments for MS. Here, Voskuhl and MacKenzie-Graham reported brain MRI and neuropathology analyses in a chronic form of EAE, revealing many features of neurodegeneration that are shared with MS. Beyond spinal cord, findings included effects on the cerebral cortex, cerebellum, and optic nerve, among others. 

IMPACT 

In the future, this model can be used by researchers to discover targets for treatments that improve walking, cognitive, coordination and visual disabilities in MS.  

UVA neuroscientist John Lukens, PhD, said the new discovery “provides a potent strategy to eliminate the toxic culprits that cause memory loss and impaired motor control in neurodegenerative disease.” CREDIT Dan Addison | University of Virginia Communications

UVA Health researchers have discovered a molecule in the brain responsible for orchestrating the immune system’s responses to Alzheimer’s disease and multiple sclerosis (MS), potentially allowing doctors to supercharge the body’s ability to fight those and other devastating neurological diseases.

The molecule the researchers identified, called a kinase, is crucial to both removing plaque buildup associated with Alzheimer’s and preventing the debris buildup that causes MS, the researchers found. It does this, the researchers showed, by directing the activity of brain cleaners called microglia. These immune cells were once largely ignored by scientists but have, in recent years, proved vital players in brain health.

UVA’s important new findings could one day let doctors augment the activity of microglia to treat or protect patients from Alzheimer’s, MS and other neurodegenerative diseases, the researchers report.

“Unfortunately, medical doctors do not currently possess effective treatments to target the root causes of most neurodegenerative diseases, such as Alzheimer’s, Parkinson’s or ALS [amyotrophic lateral sclerosis, commonly called Lou Gehrig’s disease]. In our studies, we have discovered a master controller of the cell type and processes that are required to protect the brain from these disorders,” said senior researcher John Lukens, PhD, of the University of Virginia School of Medicine and its Center for Brain Immunology and Glia (BIG), as well as the Carter Immunology Center and the UVA Brain Institute. “Our work further shows that targeting this novel pathway provides a potent strategy to eliminate the toxic culprits that cause memory loss and impaired motor control in neurodegenerative disease.”

CAPTION

“Our work has described a critical element of microglial function during Alzheimer’s disease and MS,” said researcher Hannah Ennerfelt, the first author of a new scientific paper outlining the findings. “Understanding the underlying biology of these cells during neurodegeneration may allow for scientists and doctors to develop increasingly informed and effective therapeutic interventions.”

Toxic Brain Buildup

Many neurodegenerative diseases, including Alzheimer’s and MS, are thought to be caused by the brain’s inability to cleanse itself of toxic buildup. Recent advances in neuroscience research have shed light on the importance of microglia in removing harmful debris from the brain, but UVA’s new discovery offers practical insights into how this cleaning process occurs – and the dire consequences when it doesn’t.

Using a mouse model of Alzheimer’s disease, the UVA researchers found that a lack of the molecule they identified, spleen tyrosine kinase, triggered plaque buildup in the brain and caused the mice to suffer memory loss – like the symptoms seen in humans with Alzheimer’s. Further, the neuroscientists were able to reduce the plaque buildup by activating this molecule and microglia in the brain, suggesting a potential treatment approach for human patients, though that would require significantly more research and testing.

“Our work has described a critical element of microglial function during Alzheimer’s disease and MS,” said researcher Hannah Ennerfelt, the first author of a new scientific paper outlining the findings. “Understanding the underlying biology of these cells during neurodegeneration may allow for scientists and doctors to develop increasingly informed and effective therapeutic interventions.”

A lack of the molecule in a mouse model of MS, meanwhile, led to the buildup of damaged myelin, a protective coating on nerve cells. When myelin is damaged, the cells cannot transmit messages properly, causing MS symptoms such as mobility problems and muscle spasms. The UVA researchers conclude in a new scientific paper that the molecule they identified, abbreviated as SYK, is “critically involved” in the crucial removal of myelin debris.
“If boosting SYK activity in microglia can decrease the amount of myelin debris in MS lesions, developing new drugs to target SYK could stop the progression of MS and help to reverse the damage,” said Elizabeth L. Frost, PhD, a critical researcher on the project. “This is an especially promising option given that most of the currently available drugs for MS treatment dampen adaptive immunity. These immunosuppressive drugs lead to susceptibility to infection and higher risk of potentially fatal side effects like progressive multifocal leukoencephalopathy. Additionally, some forms of MS do not have a strong involvement of the immune system, and therefore there are currently very limited treatment options for those patients.”

“Targeting SYK in microglia,” she noted, “would circumvent multiple limitations of present-day therapeutics for MS.”

Based on their promising results, the researchers report that targeting the molecule to stimulate the brain’s immune activity could offer a way to treat not just Alzheimer’s and MS but a “spectrum” of neurodegenerative diseases.

“These findings are especially exciting because they point to a treatment avenue in which we could alter the behavior of these native brain cells, microglia, to behave in a more neuroprotective way,” said researcher Coco Holliday, a UVA undergraduate working in the Lukens lab. “It could potentially be applied to a variety of different neurological diseases that all share the problem of a buildup of toxic waste in the brain. It’s been a very exciting project to be a part of.” 

From left, Richard Sowers, Rachneet Kaur and Manuel Hernandez led the development of a new approach for identifying people with multiple sclerosis or Parkinson’s disease. Their method involves videotaping the hips and lower extremities of individuals walking on a treadmill and allowing a machine-learning algorithm to differentiate gait abnormalities associated with each of these neurological conditions.
Photo by Fred Zwicky

In an effort to streamline the process of diagnosing patients with multiple sclerosis and Parkinson’s disease, researchers used digital cameras to capture changes in gait – a symptom of these diseases – and developed a machine-learning algorithm that can differentiate those with MS and PD from people without those neurological conditions.

Their findings are reported in the IEEE Journal of Biomedical and Health Informatics.

The goal of the research was to make the process of diagnosing these diseases more accessible, said Manuel Hernandez, a University of Illinois Urbana-Champaign professor of kinesiology and community health who led the work with graduate student Rachneet Kaur and industrial and enterprise systems engineering and mathematics professor Richard Sowers.

Currently, patients must wait – sometimes for years – to get an appointment with a neurologist to make a diagnosis, Hernandez said. And people in rural communities often must travel long distances to a facility where their condition can be assessed. To be able to gather gait information using nothing more than a digital camera and have that data assessed online could allow clinicians to do a quick screening that sends to a specialist only those deemed likely to have a neurological condition.

To conduct the study, the team videotaped adults with and without MS or Parkinson’s disease as they walked on a treadmill, focusing the digital cameras on participants’ hips and lower limbs. Those without the neurological conditions were age-, weight- and gender-matched with participants with MS and PD. The walking exercise also included trials in which participants walked while reciting every-other letter of the alphabet in sequence. This added task was designed to mimic the real-world challenges of walking while engaging in other potentially mentally distracting tasks, Sowers said.

“This is a novel study in that we were trying to address the fact that the lab is different from how people behave in the wild,” he said. “When you’re at home, you’re doing whatever you’re doing, but you’re also thinking, ‘Did I close the garage door? Did I turn the stove off?’ So there’s an added cognitive load.”

The researchers used an open-source tool to analyze the video to extract data about how participants moved during the walking exercises.

“We looked at the body coordinates for hips, knees, ankles, the big and small toes and the heels,” said Kaur, who developed the method for analyzing how these coordinates moved over time to look for differences between adults with and without MS or Parkinson’s disease. She tested the accuracy of her approach using more than a dozen traditional machine-learning and deep-learning algorithms. The team also tested the method on new study subjects to see if it could identify those with MS, those with Parkinson’s disease and those with neither condition.

The study revealed that several of the algorithms were more than 75% accurate at detecting these differences.

“This study suggests the viability of inexpensive vision-based systems for diagnosing certain neurological disorders,” the researchers wrote.

Making the new tools available to the public will likely take several years, the scientists said.