Round up: Engineering smarter care for ALS patients, and more

NR Times explores the latest research developments in the world of neurorehabilitation.

Shingles vaccine could slow dementia

An unusual public health policy in Wales may have produced the strongest evidence yet that a vaccine can reduce the risk of dementia.

In a new study led by Stanford Medicine, researchers analysing the health records of Welsh older adults discovered that those who received the shingles vaccine were 20 per cent less likely to develop dementia over the next seven years than those who did not receive the vaccine.

The remarkable findings support an emerging theory that viruses that affect the nervous system can increase the risk of dementia.

If further confirmed, the new findings suggest that a preventive intervention for dementia is already close at hand.

In a follow-up study, the researchers found that the vaccine may also benefit those already diagnosed with dementia by slowing the progress of the disease.

In a further finding, the study showed that protection against dementia was much more pronounced in women than in men.

This could be due to sex differences in immune response or in the way dementia develops, the researchers said. #

Women on average have higher antibody responses to vaccination, for example, and shingles is more common in women than in men.

Whether the vaccine protects against dementia by revving up the immune system overall, by specifically reducing reactivations of the virus or by some other mechanism is still unknown.

Also unknown is whether a newer version of the vaccine, which contains only certain proteins from the virus and is more effective at preventing shingles, may have a similar or even greater impact on dementia.

The team hope the new findings will inspire more funding for this line of research.

In the past two years, his team has replicated the Wales findings in health records from other countries, including England, Australia, New Zealand and Canada, that had similar rollouts of the vaccine.

New technique maps genetic variants driving neurodegenerative disease risk

A new method that substantially improves the ability to map the genetic variants that drive disease, particularly neurodegenerative diseases has been developed.

Instead of analysing genetic effects by grouping cells into specific categories and determining genetic effects for each type individually, the team modeled the effects shared among seven different brain cell types.

The new approach from Penn State College of Medicine outperforms existing methodologies, identifying approximately 75 per cent more genes of interest.

The researchers also found new genes linked to the risk of Alzheimer’s disease and amyotrophic lateral sclerosis (ALS) and therapeutic targets, some of which have already-existing promising treatments.

The research team’s work focuses on understanding how genes influence disease risk.

They explained that, for example, genes like APOE can increase the risk of developing Alzheimer’s disease between three-fold and nine-fold.

Neuroinflammation may also play a role in the development of neurodegenerative diseases, something that Jiang explained specialised cells in the brain like microglia — the brain’s immune cells — may contribute to.

Scientists often use genome-wide association studies to identify regions of the genome associated with particular diseases.

However, genome-wide association studies often rely on bulk tissue samples where different cell types are mixed together.

More recent studies might instead utilise single-cell data, which allows scientists to investigate cell types individually, but sample sizes are typically small, especially for rare cell types like microglia.

Here, the team developed a new method, dubbed BASIC for Bulk And Single cell eQTL Integration across Cell states, which integrates both bulk tissue samples and single-cell data.

The researchers looked across cell types to identify combinations of genes that, when expressed, produced similar effects across multiple cell types as well as effects that were unique to certain cell types.

The improvement they saw is equivalent to bolstering sample size by nearly 77 per cent.

When they applied this method to analyse 12 different brain-related diseases, like Alzheimer’s disease, ALS and addiction, the team was able to more accurately identify genetic targets linked to disease by over 53 per cent compared to single-cell data alone and by 111 per cent over bulk tissue analysis.

They also identified new genes linked to neurodegenerative disease, including ALS and Alzheimer’s disease, that have been overlooked by conventional approaches.

The researchers then used this information to identify drug compounds that could reverse gene expression associated with disease, such as alfacalcidol — a synthetic version of vitamin D — for schizophrenia and cabergoline for Alzheimer’s disease.

These are existing medications that have already been approved by the Food and Drug Administration as safe and effective for treating other diseases and could potentially be repurposed.

However, the team says that more research is needed to fully understand the implications of their findings.

Engineering smarter care for ALS patients

Licensed occupational therapist and researcher at the University of Missouri, Bill Janes, has seen firsthand how ALS can steal a person’s strength, speech and independence.

To help close gaps in care, Janes is working with experts at Mizzou’s School of Medicine and Institute for Data Science and Informatics to build a smarter way to track ALS progression in real time.

Their solution uses a combination of in-home sensors and AI.

Curators’ Distinguished Professor Emerita Marjorie Skubic at Mizzou’s College of Engineering and Curators’ Distinguished Professor Emerita Marilyn Rantz at Mizzou’s Sinclair School of Nursing originally developed the sensors to monitor the health of older adults living at home.

The devices can detect changes in behavior and physical activity, including walking and sleeping patterns, prompting health care interventions that can delay or prevent serious health events.

Now, Janes and colleagues are adapting the sensors to fit the needs of ALS patients, whose functional decline often mirrors that of older adults but progresses more rapidly and unpredictably.

Right now, the team is focused on verifying that the sensor data accurately reflects real-world changes in how patients function day to day.

Their next phase will make sense of the collected data using predictive modeling.

The data flows wirelessly through two small boxes in the home, then securely transfers to university systems, where researchers can study the results.

Using machine learning, predictive models are built to estimate each patient’s score on the ALS Functional Rating Scale Revised (ALSFRS-R) — a clinical tool that measures how ALS affects a person’s daily abilities over time, including walking, talking, swallowing and breathing.

For the final stage of the project, researchers will integrate the system directly into clinical workflows.

If the model predicts a concerning decline, a clinician could receive an alert to check in with the patient, adjust medication, recommend assistive devices or suggest further treatment.

Early feedback from participating families has been positive as many appreciate the sense of connection and peace of mind the system provides.

While the current project focuses on ALS, this same technology could be adapted to help monitor other chronic conditions, such as Parkinson’s disease or heart failure.

Restless legs syndrome linked to Parkinson’s risk

Restless legs syndrome (RLS) is a common neurological sleep disorder characterised by an uncontrollable urge to move the legs, often worsening at night.

Parkinson’s disease (PD), a progressive neurodegenerative disorder, is marked by tremor, rigidity, and slowed movement. Both conditions are associated with dysfunction in the brain’s dopaminergic system, but their causal relationship has remained unclear.

A joint research team from Korea University Ansan Hospital, Pohang Stroke and Spine Hospital, and National Health Insurance Service Ilsan Hospital, Republic of Korea, has now clarified that untreated RLS may increase the risk of developing PD, while dopamine-agonist (DA) therapy may significantly reduce that risk.

The researchers identified 9,919 individuals with RLS and compared them with an equal number of matched controls without the condition.

Over a median follow-up of 15 years, PD developed in 1.6 per cent of RLS patients compared with 1 per cent of controls, confirming a heightened risk. When analysed by treatment status, the results revealed a striking divergence.

Patients with untreated RLS showed the highest PD incidence and an earlier onset whereas, DA-treated patients showed a markedly lower PD incidence and a delayed onset compared with controls.

To strengthen the validity of their conclusions, the team employed target-trial emulation methods, an advanced analytical approach that reduces bias in observational research.

This methodological rigor reinforces the biological plausibility of a link between RLS and PD rather than a mere overlap in symptoms.

The authors propose that beyond dopamine dysfunction, other factors, such as sleep disruption, iron deficiency, and immune or metabolic pathways, may mediate this association.

The protective trend observed with DA therapy could reflect neuroprotective mechanisms or improved identification of genuine RLS cases that are distinct from early-stage PD.

“This dual pattern underscores the importance of recognizing and managing restless legs syndrome early,” adds Prof. Kim.

“Monitoring and treating RLS may not only improve sleep quality but could also influence long-term neurological health.”