Deep brain stimulation, or DBS, is a neurosurgical technique that aims to regulate neuron activity via internal pulse generators to electrodes in specific target areas within the brain. The development of deep brain stimulation is largely attributed to Alim Benabid, who was utilizing surgical approaches to treat cases of Parkinson’s disease, dystonia, and several psychiatric conditions that had historically failed to respond to drug-based therapies.

Deep brain stimulation has since shown great promise for treating movement disorders associated with neurological diseases, such as Parkinson’s disease and essential tremor, and consequently is widely used in the field of neurological diseases.

More recently, researchers have begun investigating deep brain stimulation and Alzheimer’s disease. Below, we take a closer look at deep brain stimulation and Alzheimer’s disease, address the limitations of existing research, and propose a new gold standard for measuring therapeutic response.

How Is Deep Brain Stimulation Performed?

In general, deep brain stimulations systems have three main components:

• A neurostimulator: A programmable battery-powered, pacemaker-like device that creates electric pulses and is surgically implanted under the skin of the chest
• A lead: A coated wire with electrodes at the tip to deliver the electric pulses to brain tissue that is strategically and precisely placed inside the brain
• An extension: An insulated wire connecting the lead to the neurostimulator device that is placed under the skin, running from the scalp, behind the ear, down the neck, and into the chest

Whether performed using traditional approaches or robotically, deep brain stimulation is typically performed in three distinct stages:

1. Imaging and placement of bone markers/screws 
2. Placement of electrodes
3. Placement of the battery and lead extender

Deep Brain Stimulation and Alzheimer’s Disease: Animal Studies

Over the past decade, deep brain stimulation has shown several positive effects in animal models, demonstrating benefits such as enhanced short- and long-term memory, restoration of spatial memory-related functions, decreased amyloidosis, and decreased neuronal loss in the cortex and hippocampus. Animal studies have incorporated multiple stimulation targets, such as the midline thalamic nuclei (MTN), the intralaminar thalamic nucleus (ILN), the anterior nucleus of thalamus (ANT), the hippocampal CA1 subfield, and the entorhinal cortex (EC).

Deep Brain Stimulation and Alzheimer’s Disease: Human Studies

During this same time, deep brain stimulation has been investigated in several human clinical studies. Here is a look at some of the findings:

• A 2010 phase I trial demonstrated that after deep brain stimulation surgery, Alzheimer’s patients had improved memory, decreased rates of cognitive decline, and increased cerebral glucose metabolism.
• A 2015 phase I trial showed that after one year of deep brain stimulation, Alzheimer’s patients showed decreased rates of hippocampal atrophy as well as stabilization of nutritional status.
• A 2018 phase II trial found that participants under 65 showed similar rates of decline to controls (those without the neurostimulator device turned on), meaning there was no decrease in the rate of cognitive decline. However, participants over 65 showed decreased rates of cognitive decline compared to controls. This suggests that deep brain stimulation may not benefit individuals with early-onset Alzheimer’s disease (diagnosed under age 65) but may benefit those over 65. 

Stimulation targets in human studies involved the fornix, the nucleus basalis of Meynert (NBM), and the ventral capsule/ventral striatum (VC/VS).

The mechanism of action currently remains unclear; however, several potential mechanisms have been proposed, such as those listed below:

• Regulation of neural networks
• Reduction in beta-amyloid levels
• Reduction in tau levels
• Promotion of nerve oscillation
• Reduction of neuroinflammation
• Induction of nerve growth factor (NGF) synthesis
• Regulation of the cholinergic system

Limitations of Research Surrounding Deep Brain Stimulation and Alzheimer’s Disease

Currently, to assess and measure therapeutic response to deep brain stimulation in clinical trials, studies rely on narrow-natured, simple cognitive assessments, such the Mini-Mental State Exam (MMSE) and the Clinical Dementia Rating (CDR).

Many of these traditional assessments are purely cognitive batteries that only assess a small subset of neurocognitive domains. Assessment of Activities of Daily Living (ADLs) is arguably the most relevant and robust measure of neurocognitive function. However, traditional cognitive function assessment tools are not ecologically valid, meaning the design of the evaluation does not match and align with neurocognitive states representative of Activities of Daily Living (ADLs). Because of these limitations, these assessments frequently produce noisy, highly variable results that lack the specificity and granularity to confidently draw conclusions about the efficacy of deep brain stimulation.

To improve our understanding of therapeutic response to deep brain stimulation, it is important to assess a breadth of both cognitive and functional domains at a highly granular level.

By now, you are likely aware of many of the well-established risks associated with smoking cigarettes, such as cancer, asthma, chronic obstructive pulmonary disease (COPD), diabetes, cardiovascular disease, and stroke. But did you know that research has discovered a link between smoking and cognitive decline?

This research emphasizes the importance of identifying and controlling modifiable risk factors for cognitive decline and dementia as early as possible while monitoring brain health to detect changes in brain function as early as possible.

Here is everything you need to know about smoking and cognitive decline, including a breakdown of the research and the best way to monitor brain health while controlling modifiable risk factors for dementia.

Smoking, Cognitive Decline, and Dementia Risk: A Breakdown of the Research

Over the past two and a half decades, researchers have discovered a significant connection between smoking, cognitive decline, and dementia. Research suggests smoking increases the risk of cognitive decline and dementia and may accelerate cognitive decline in individuals with Mild Cognitive Impairment.

Smoking and Cognitive Decline

A 2008 study assessing smoking and cognitive decline among middle-aged men and women found that at baseline, people who smoke scored lower than those who have never smoked in global cognitive function, speed, and flexibility. At the five-year follow-up, decline among smokers was 1.9 times greater for memory function, 2.4 times greater for cognitive flexibility, and 1.7 times greater for global cognitive function compared to those who have never smoked. Additionally, smokers who smoked a greater number of cigarettes (measured in pack-years) showed a greater decline in cognitive function.

A 2012 study assessing the impact of smoking on cognitive decline in early old age found that middle-aged male smokers experienced faster cognitive decline when compared to those who have never smoked. In former smokers (with at least a 10-year cessation), no adverse effects on cognitive decline were observed. They also found that cognitive decline did not vary as a function of smoking status in women, though several other studies have produced contradictory findings. For example, a 2021 study found that smoking was associated with impaired verbal learning and memory performance in women more than men. 

A 2021 study found that among people with Mild Cognitive Impairment, smokers showed a more rapid decline in functional performance compared to non-smokers, where functional performance refers to the ability to complete Activities of Daily Living (normal day-to-day activities).

Together, this research suggests that there is indeed a relationship between smoking and cognitive decline, though it is not yet clear what role sex plays in this relationship.

Smoking and Dementia Risk

Over the years, many studies have assessed the impact of smoking on the risk of developing dementia later in life. A review of 37 research studies assessing the association between smoking, dementia risk, and Alzheimer’s disease risk found that when compared to people who have never smoked, current smokers are 30% more likely to develop dementia and 40% more likely to develop Alzheimer’s disease, the leading cause of dementia. They also concluded that smoking cessation can reduce the risk of developing dementia.

To summarize all of the above research and make this a bit more digestible, here is what research currently suggests:

• Smoking in midlife is associated with a decline in cognitive and functional aspects of brain health, particularly in domains of cognitive function such as learning and memory and executive function.
• Smoking is associated with an increased risk of developing dementia as well as Alzheimer’s disease.
• Heavy smoking is associated with greater cognitive decline.
• Smoking cessation can reduce the risk of developing dementia.

Why is Smoking Associated with Cognitive Decline and Dementia?

While there is a clear connection between smoking and cognitive decline, it is not fully clear why it is that smoking affects brain health. However, there are several theories on how smoking damages our brains and increases the risk of developing dementia, including the following:

• Smoking may accelerate brain aging.
• Smoking may increase the risk of developing Alzheimer’s disease by increasing oxidative stress.
• Vascular conditions, such as stroke and heart disease, as well as risk factors for vascular conditions, such as high blood pressure, high cholesterol, and type 2 diabetes, have all been linked to an increased risk of dementia. As smoking can cause damage to the brain and blood vessels, it can cause vascular conditions and consequently increase dementia risk.
• Smokers are at high risk for insomnia and sleep apnea, conditions which have been linked to an increased risk of developing dementia.

Controlling Modifiable Risk Factors and Monitoring Brain Health

The connection between smoking and cognitive decline has important implications for individuals who smoke. While smoking is a tough habit to quit, it is a modifiable risk factor for dementia. By taking appropriate steps to control risk factors and regularly monitoring brain health, patients can benefit from early intervention and better health outcomes. In the event a decline in brain function is detected, frequent and consistent monitoring of brain health provides early diagnosis and early treatment.

Humans are inherently social beings who thrive on making and maintaining social relationships. Connecting with and supporting one another forms deep bonds that make us feel seen, valued, and like we belong. These social interactions are not only important for our emotional well-being but also for our physical well-being—maybe even more so than originally thought. Loneliness, an increasingly prevalent global public health issue, has been linked to serious health risks, including dementia. 

Below, we take a closer look into the link between loneliness and dementia, how loneliness affects brain health, and loneliness and social isolation as a modifiable risk factor for dementia.

Understanding The Link Between Loneliness and Dementia

In a recent study published in Neurology, a peer-reviewed neurology journal, in February of 2022, researchers revealed a shockingly robust link between loneliness and dementia, bolstering previous studies. Key findings of this study include the following:

• Loneliness (for three or more days in the past week) was associated with an increased 10-year incidence of all-cause dementia.
• This risk was tripled for lonely adults less than 80 years of age without an APOE4 allele (a risk gene for Alzheimer’s disease).
• Among adults less than 80 years of age without an APOE4 allele (APOE4-negative), loneliness was associated with poorer executive function, a cognitive domain that includes processes such as judgment, attention, organization, planning, and decision-making.

Previous research has shown similar (yet slightly different) findings. A 2007 study assessing loneliness and the risk of Alzheimer’s disease, the most common cause of dementia, found that Alzheimer’s risk was more than doubled in lonely individuals compared to those who were not lonely. Results from a 2019 study indicated that loneliness was associated with a 40% increased risk of dementia.

As a whole, this research suggests that loneliness may either be an early symptom of neurodegenerative diseases or an early contributor to neuropathy and cognitive decline. In other words, it is not yet clear if loneliness is a consequence or risk factor/cause of dementia.

How Does Loneliness Affect Brain Health?

Whether loneliness stems from living alone, the loss of a loved one, chronic illness, sensory impairments, or even social isolation due to the COVID-19 pandemic, it has a strong impact on brain health—but what is it about loneliness that affects brain health and causes this increased dementia risk?

Loneliness can result in several circumstances and conditions that can ultimately contribute to cognitive decline and increased dementia risk. These conditions include social isolation, lack of brain stimulation, increased levels of stress, poor sleep, and mental health disorders, all of which have been linked to cognitive decline and an increased risk of developing dementia. Poor social relationships have also been associated with an increased risk of vascular conditions, such as heart disease and stroke, which are known risk factors for dementia.

Loneliness and Social Isolation as a Modifiable Risk Factor for Dementia

This research sheds light on a robust link between loneliness and dementia, emphasizing the importance of understanding our brain health as we age and addressing modifiable risk factors for dementia. Recognizing and addressing signs of loneliness in ourselves as well as our loved ones and prioritizing our brain health can go a long way.

Just as we regularly get checked for things like high blood pressure, heart disease, and cancer, we should be regularly checked for changes in brain health. This is particularly true for individuals with known risk factors for developing Alzheimer’s disease or other causes of dementia, including loneliness and social isolation. Identifying risk factors and detecting changes in brain health as early as possible is key to delaying or even preventing cognitive decline.

Thanks to advancements in medical care, the adoption of new technologies, and overall improved living conditions, global life expectancy has seen a steady increase over the past two centuries. Unfortunately, as aging is the primary risk factor for many diseases and conditions, a longer life means there is a higher probability of developing multiple long-term health conditions, such as dementia, diabetes, cardiovascular disease, and sensory impairments. 

Comorbidity and multimorbidity are typical of the majority of individuals living with Alzheimer’s and other causes of dementia. However, healthcare systems are more or less designed around single-organ diseases, not multimorbidity, which can greatly impact the quality and efficacy of patient treatment and care. Additionally, numerous studies have demonstrated that multimorbidity significantly increases the risk of dementia development.

Below, we take a closer look at multimorbidity and dementia, including research surrounding multimorbidity and dementia risk, how multimorbidity affects the needs of dementia patients, and the need for more precise, personalized treatment and care.

What Is Meant By Multimorbidity?

Multimorbidity is conventionally defined as the presence of two or more long-term health conditions or chronic diseases, regardless of the severity of such conditions. The working definition of multimorbidity has been expanded by the National Institute for Health and Care Excellence to include the following criteria for long-term health conditions:

• Defined physical and mental health conditions (e.g. diabetes and schizophrenia)
• Ongoing conditions (e.g. learning disabilities)
• Symptom complexes (e.g. fragility and chronic pain)
• Sensory impairments (e.g. hearing impairments and vision impairments)
• Alcohol and substance misuse

Multimorbidity and Dementia Risk

It is well-known that individual diseases and health conditions, such as cardiovascular disease, stroke, and hearing loss, can increase the risk of developing dementia later in life. However, newer research aims to assess the impact of multimorbidity on dementia risk.

A 2021 study assessing the impact of multimorbidity and dementia risk found that individuals with neuropsychiatric, cardiovascular, and sensory impairment/cancer patterns are at an increased risk for developing dementia. They also found that APOE4 and inflammation may further increase the risk of dementia.

In 2022, a 30-year follow-up prospective cohort study aimed to investigate the association between age at onset of multimorbidity and incidence of dementia. The study found that multimorbidity, especially when onset occurs in midlife rather than late life, had a strong association with subsequent dementia.

This research emphasizes the importance of taking a preventive approach to medicine and identifying patients at high risk of developing dementia as early as possible to enable tailored interventions for effective dementia prevention measures.

Multimorbidity and Dementia: The Need for Precision Medicine Approaches

As mentioned above, multimorbidity is quite common in individuals living with Alzheimer’s and other causes of dementia. Research suggests that multimorbidity is associated with a poorer quality of life as well as increased risks of polypharmacy, adverse drug reactions, falls, and hospital admissions. 

This suggests that there is an urgent need for providers to take multimorbidity into account at a personalized level when tailoring an approach to care and treatment, rather than focusing on each disease or condition separately, particularly when mental and physical conditions overlap. Taking all conditions into account and creating an individualized management plan can not only improve health outcomes but can improve the quality of life by reducing adverse events and uncoordinated or disjointed care.

Additionally, several studies have found that multimorbidity contributes to the clinical progression of dementia; more specifically, multimorbidity is associated with accelerated decline in individuals with dementia, but not in individuals without dementia. This demonstrates the importance of frequently and consistently assessing neurocognitive function to adequately update care and treatment plans to meet the changing care needs of patients.

The COVID-19 pandemic has catalyzed the implementation of decentralized clinical trials in neurology, bringing the immense benefits of clinical trials to light. This industry-wide push towards trial decentralization has emerged as a key element for improving clinical trial efficiency and improving the experience for patients and physicians. 

By utilizing digital technologies, such as wearables, portables, and other sensor-based technologies, decentralized clinical trials meet patients where they are, offering a more patient-oriented approach that greatly minimizes common barriers to patient participation.

Below, we take a closer look at the benefits of decentralized clinical trials for neurology, current challenges of trial decentralization, and clinically validated end-to-end digital solutions for neurological disease trials.

Benefits of Decentralized Clinical Trials for Neurology

The benefits of decentralized clinical trials can be seen across all branches of medicine, including neurology. From improved patient recruitment and retention to the ability to improve data diversity, decentralized trials are here to stay. Here are some of the top benefits of decentralized clinical trials:

• Improved patient recruitment and retention: The average patient dropout rate across all clinical trials is 30%, with 85% of all clinical trials failing to retain an adequate number of subjects to successfully complete a study. 
• Flexibility and improved data diversity: Typically, clinical trials are designed around the locations of research centers and recruiting subjects from the local population. Travel distance to the clinic often plays a huge part in patients’ decisions on whether or not they will participate in a trial. By decentralizing trials, barriers to participation are greatly decreased while geographical barriers are broken down, enabling improved data diversity—a crucial element of many neurological disease clinical trials.
• Real-time communication with trial subjects: Frequent and effective communication between study site personnel and patients is a key element to ensuring patient retention. By utilizing digital platforms, site personnel can communicate with patients in real-time.
• Use of non-invasive technologies and low-cost solutions: Decentralized trials offer the ability to leverage non-invasive technologies and low-cost solutions without the use of large clinical equipment. By eliminating the need to transfer large equipment to and from the clinic, more frequent measurements can be collected.
• Opportunities for novel digital endpoints: Currently, trial data is often collected and processed through manual paper workflows. Digital endpoints and digital biomarkers provide pharmaceutical companies with granular, supplemental, and contextual information, enabling them to confidently reach a go/no-go decision as early as possible can help achieve proof of concept more rapidly and at lower costs. Collection of high-quality clinical data through decentralized trials can help build even stronger evidence packages to prove drug or therapy efficacy.

Challenges of Decentralized Clinical Trials for Neurology

It is clear the benefits of decentralized clinical trials outweigh the drawbacks; however, there are several challenges for pharmaceutical companies to keep in mind, such as those detailed below:

• Patient adherence to trial protocols: As trials are decentralized, there will likely be challenges regarding patient adherence to trial protocols. However, technologies, such as wearables, mobile applications, smart boxes/caps for medication, and telehealth programs can be utilized to effectively engage patients and allow them to self-monitor.
• High-frequency testing: While the ability to perform high-frequency testing is beneficial in clinical research settings, it can also be a pitfall, particularly in the neurology space. Most solutions utilized to assess neurocognitive function have a learning effect, meaning if the patient completes the assessment too many times, they will get better at it, and the scores will not reflect their true neurocognitive function. 
• Data quality: Decentralized approaches to clinical trials also bring new risks, particularly regarding data quality. Apps, wearable devices, and other digital health technologies require robust technical and clinical validation.

Since the discovery of the beta-amyloid peptide in 1984, the amyloid cascade hypothesis has been the primary focus of research surrounding Alzheimer’s disease treatment and is more or less dominating the Alzheimer’s research space. The hypothesis states that the deposition of beta-amyloid protein, the primary component of the plaques, is the causative agent of Alzheimer’s disease pathology and that hallmarks, such as neurofibrillary tangles, cell loss, vascular damage, and dementia, directly result from this deposition.

However, in the past decade, after countless failed clinical trials targeting beta-amyloid plaques, this school of thought is rapidly changing. While beta-amyloid deposition is certainly still a neuropathological hallmark of Alzheimer’s disease and plays a role in the development and progression of Alzheimer’s, it is not the only factor driving Alzheimer’s disease progression. Effective treatment of Alzheimer’s disease will likely rely on a combination of multiple effective therapies targeting different pathological mechanisms. Consequently, a vast range of new novel targets, including neuroinflammation, have entered the clinical research pipeline.

Below, we take a closer look at Alzheimer’s disease neuropathology, the role of neuroinflammation in Alzheimer’s disease, neuroinflammation as a target for treatment, and the shift towards combination treatments for Alzheimer’s.

Alzheimer’s Disease Neuropathology

Neuropathological hallmarks of Alzheimer’s disease consist of positive and negative lesions. Positive lesions include tau hyperphosphorylation, neurofibrillary tangles, beta-amyloid plaques, cerebral amyloid angiopathy, and glial responses, while negative lesions include neuronal and synaptic loss. However, Alzheimer's is most commonly characterized by two core characteristics: beta-amyloid plaques and neurofibrillary tangles resulting from abnormal tau hyperphosphorylation. 

In the past decade, a third core feature of Alzheimer’s has emerged; recent research suggests that chronic neuroinflammation influences beta-amyloid deposition and tau phosphorylation and may contribute to accelerated Alzheimer’s disease progression. In several other studies, it has also been proposed that the inflammatory response may link the initial beta-amyloid pathology and the later development of neurofibrillary tangles.

Neuroinflammation in Alzheimer’s Disease

Acute inflammation in the brain is a normal defense against toxins, infections, and injury; however, in Alzheimer’s disease, there is a disruption in the equilibrium of anti- and pro-inflammatory signals, which can result in chronic neuroinflammation, the hallmark of dysregulated microglia.

Consequently, chronic neuroinflammation in Alzheimer’s disease is believed to be primarily attributed to activated microglial cells and the release of cytokines. Chronic neuroinflammation was previously thought to be a result of the neuronal loss that occurs in Alzheimer’s. However, a significant amount of research suggests that this sustained immune response in the brain is an early event in the Alzheimer’s disease continuum and neuroinflammation is a central mechanism that facilitates and exacerbates beta-amyloid and tau pathologies in addition to contributing to neurodegeneration. Depending on the state of the disease, activated microglia may have diverse impacts on the progression of Alzheimer’s disease.

It should be noted that neuroinflammation is not unique to Alzheimer’s disease; numerous studies have demonstrated elevated markers of inflammation in the brains of those with Parkinson’s disease, amyotrophic lateral sclerosis, and multiple sclerosis. Additionally, inflammatory pathways for Alzheimer’s are quite similar to those for diabetes. This is why drugs like semaglutide are often repurposed for Alzheimer’s disease.

The Path Towards Precision Medicine in Alzheimer’s Disease Treatment

As chronic neuroinflammation in Alzheimer’s disease may accelerate other core pathologies, inflammatory mechanisms appear to be viable targets for therapeutic development, alongside established targets, such as beta-amyloid and tau, and new targets, such as mitochondria and metabolic dysfunction, vascular disease, synaptic activity and neurotransmitters, and genetics and epigenetics.

The complex pathology of Alzheimer’s disease will likely necessitate combination treatments rather than monotherapy. Because every individual’s neurocognitive domain functions are affected uniquely in the presence of Alzheimer’s, the treatment pathways will also likely be unique. Utilizing multiple effective treatments tailored to an individual’s specific impairments due to their unique pathological manifestations will allow for more effective, well-rounded, and personalized treatment.

After two full years have passed since the COVID-19 pandemic began, we are hearing more about the potential long-term effects of the virus, both mentally and physically. COVID-19 spares no organ system. The short- and long-term symptoms are widespread and seem to vary significantly from patient to patient. While the virus is known for attacking the respiratory and cardiovascular systems, it’s also becoming known for attacking the nervous system. This begs the question of whether or not COVID-19 could cause neurological problems in the long term.

Below, we take a closer look at how COVID-19 could cause neurological problems in patients, including both acute and potential long-term consequences, as well as what this means for patient monitoring and rehabilitation.

Could COVID-19 Cause Neurological Problems?

When examining neurological manifestations in patients admitted with confirmed COVID-19 infections, doctors within an extensive hospital network in Chicago, Illinois, found that 40.2% of patients with COVID-19 presented with neurological problems at the onset, and more than 30% of those patients showed signs of impaired cognitive function. They found that the most frequent neurologic manifestations were myalgias (44.8%), headaches (37.7%), encephalopathy (31.8%), dizziness (29.7%), dysgeusia (15.9%), and anosmia (11.4%), with encephalopathy being independently associated with worse functional outcomes and higher mortality within 30 days of hospitalization.

Many patients are concerned and are asking their doctors if COVID-19 could cause neurological problems. Here is what we know so far about the acute and potential long-term consequences of COVID-19.

Acute Neurological Problems Caused By COVID-19 Infection

Most individuals who are infected with the SARS-CoV-2 virus will experience no or mild to moderate neurological symptoms. However, most patients who are hospitalized as a result of COVID infection will likely present with neurological manifestations. 

Several neurological symptoms have been reported with acute COVID-19, including loss of taste and smell, headaches, muscle aches, delirium, brain inflammation, and stroke. It also has been known to cause seizures or major strokes in rare cases. As the virus does not appear to extensively infect brain cells, these symptoms are currently believed to be caused by immune activation, neuroinflammation, and damage to blood vessels in the brain.

While inflammation typically plays a helpful role in our bodies, acting as a defense system against pathogens, it can also cause immense harm. Some experts believe that the more severe cases of COVID-19 may develop from an overactive inflammatory response to the virus. Coronaviruses directly bind to ACE-2 receptors in respiratory epithelial cells, causing an event known as a “cytokine storm,” leading to widespread inflammation in COVID-19 patients and ultimately leading to multiple organ damage.

Possible Long-Term Neurological Problems Caused By COVID-19 Infection

Our understanding of the long-term neurological consequences of COVID-19 is still very limited, but it is clear that COVID can damage the brain; however, how COVID damages the brain is still up for debate. Current research suggests this damage can occur from direct infection (encephalitis), a lack of oxygen to the brain, and strokes.

One of the most common symptoms reported in long COVID patients is “brain fog,” which is essentially an umbrella term used to describe long-term cognitive symptoms associated with COVID that are similar to symptoms of Mild Cognitive Impairment, including short-term memory loss, poor attention span and difficulty concentrating, slow thinking, and confusion. Currently, researchers believe these cognitive symptoms may be a byproduct of the inflammatory processes within the brain.

Monitoring Neurological Changes in Long COVID Patients

Emerging and ongoing research surrounding neurological problems caused by COVID-19 has important implications for healthcare providers. Providers should incorporate tools to measure and monitor neurological changes in COVID patients, particularly those at high risk of developing neurological manifestations. Cognitive and functional aspects of brain function should be regularly assessed and monitored over time for patients experiencing long COVID symptoms. This will give rise to tailored treatment and rehabilitation, and consequently, better health outcomes.

Lewy body dementia, or dementia with Lewy bodies, is believed to be the third most common cause of dementia after Alzheimer’s disease and vascular dementia, accounting for approximately 5% to 10% of dementia cases. However, the pathology of Lewy body dementia and its risk factors are far less established and understood when compared to other causes of dementia, such as Alzheimer’s disease.

Below, we provide information on established and potential risk factors for Lewy body dementia and how to monitor the brain health of individuals at risk of developing Lewy body dementia.

What Is Lewy Body Dementia?

Lewy body dementia is a cause of progressive dementia that is clinically characterized by a decline in thinking, reasoning, and independent function. Symptoms include visual hallucinations, changes in cognitive abilities (thinking, reasoning, memory, and attention), changes in movement and gait, sleep disturbances, malfunctions of the autonomic nervous system, and depression. 

Neuropathological hallmarks, or key characteristics, of Lewy body dementia include the deposition of Lewy bodies and Lewy neurites. Lewy bodies, protein deposits made of abnormal filaments composed of alpha-synuclein, develop in nerve cells (neurons) within the regions of the brain responsible for memory, thinking, and motor control. Alpha-synuclein is found naturally in the brain; however, its function is not yet fully understood. Lewy neurites are abnormal neurites in diseased neurons and contain granular material and abnormal alpha-synuclein filaments similar to those in Lewy bodies.

Lewy Body Dementia Risk Factors

Although Lewy body dementia risk factors are less established and less understood than risk factors for other neurodegenerative diseases, several potential risk factors have been identified. Established and generally agreed-upon risk factors for Lewy body dementia include age, family history, and sex, described in more detail below.

• Age: Advanced age is the greatest known risk factor for Lewy body dementia. Lewy body dementia typically presents between the ages of 50 and 85, though it has been diagnosed in younger individuals.
• Family history: The hereditary nature of Lewy body dementia is not well established; however, experts believe that individuals with a family history of Lewy body dementia or Parkinson’s disease may be at greater risk.
• Sex: For many diseases, including those of the brain, sex plays a role in disease risk. Lewy body dementia is more prevalent in men than in women.

Conditions linked to vascular problems, such as hypertension, hyperlipidemia, and diabetes mellitus, as well as conditions that may result in social isolation and a lack of brain stimulation, like depression and loneliness, have been linked to many neurodegenerative and neurological diseases and conditions. Research suggests these conditions may also be risk factors for Lewy body dementia.

• Hypertension, diabetes mellitus, and hyperlipidemia: A 2018 population-based study found that hypertension, diabetes mellitus, and hyperlipidemia are both risk factors for Alzheimer’s disease and Lewy body dementia.
• Depression: A 2013 case-control study found that depression increases Lewy body dementia risk more strongly than it does in Alzheimer’s disease and Parkinson’s disease.

While there are no proven strategies for preventing Lewy body dementia, several aspects of healthy living may reduce the risk of developing dementia. In general, what is good for your heart is good for your brain. Experts recommend:

• Quitting smoking.
• Exercising daily (30-60 minutes/day).
• Eating a heart-healthy diet.
• Getting adequate sleep.
• Minimizing stress.
• Controlling alcohol consumption.

Monitoring Brain Health of At-Risk Patients

Monitoring the brain health of patients at risk of developing Lewy body dementia as early as possible is crucial to detect changes in function and enable early diagnosis, early intervention and treatment, and consequently, better health outcomes.

Additionally, individuals with modifiable Lewy body dementia risk factors, such as hypertension, diabetes, and depression, should closely monitor their brain health while modifying risk factors and making lifestyle changes.

Countless failed Alzheimer’s disease clinical trials and a lack of effective therapies have resulted in the development of many novel therapies for Alzheimer’s disease, and more recently, gene therapy.

Gene therapy represents a promising area of research for neurodegenerative diseases, like Alzheimer’s and Parkinson’s disease. One of the biggest challenges of drug delivery for Alzheimer’s is the blood-brain barrier (BBB), as it prevents large molecules from reaching the brain. Gene therapy for Alzheimer’s disease is unique in that it can essentially circumvent the BBB by delivering genes directly via delivery systems, like viral vectors. Additionally, due to the persistent nature of gene expression, only a single administration of the therapy is theoretically required.

Below, we take a closer look at gene therapy for Alzheimer’s disease, including identified targets for genetic therapies for Alzheimer’s, associated clinical research, and insight into what is needed to accelerate and improve clinical research in this space.

Gene Therapy for Alzheimer’s Disease

Over the years, several targets for genetic therapies have been researched and assessed in pre-clinical trials. These targets include but are not limited to the following:

• Amyloid pathway intermediates and enzyme modulation
• Tau protein downregulation
• APOE4 downregulation and APOE2 upregulation
• Neurotrophin expression (nerve growth factor [NGF] and brain-derived neurotrophic factor [BDNF])
• Inflammatory cytokine alteration

Below, we take a closer look into clinical research surrounding BDNF and APOE2.

AAV2-BDNF Treatment

BDNF, also known as abrineurin, is a protein that is encoded by the BDNF gene and is found in the central nervous system. This protein is part of a family of growth factors and is responsible for promoting the survival of neurons via its role in the growth, differentiation, and maintenance of new neurons and synapses.

BDNF is produced in the entorhinal cortex, an important region of the brain for memory that is typically affected by Alzheimer’s early in the disease continuum. In individuals with Alzheimer’s disease, the levels of BDNF are reduced.

Animal studies, including those involving aged rats, aged monkeys, and amyloid mice, found that delivering BDNF to the entorhinal cortex and hippocampus via a modified viral vector, adeno-associated virus (AAV2), was a promising approach. When compared to non-treated animals, the animals treated with this approach showed notable improvement in learning and memory assessments, while the brains of treated animals showed restored BDNF gene expression and activation of function in neurons that would have otherwise degenerated.

Following promising animal studies, in 2021, researchers at the University of California San Diego School of Medicine launched a first-in-human Phase I clinical trial to investigate the safety and potential therapeutic benefits of the AAV2-BDNF gene therapy for Alzheimer’s disease. 

AAVrh.10-APOE2 Treatment

The most common and widely researched gene associated with late-onset Alzheimer’s disease is APOE, which has been identified as a risk gene. APOE is responsible for creating a protein that helps carry cholesterol and other fats in the bloodstream. 

Genetic variants on the APOE gene on chromosome 19 are known to increase the risk of developing Alzheimer’s. APOE comes in several forms, or alleles: APOE2, APOE3, and APOE4. Individuals inherit two APOE alleles—one from each biological parent.

Because of the significant risk associated with carrying two copies of APOE4, researchers began investigating the potential of treating APOE4 homozygotes (with Mild Cognitive Impairment [MCI], mild dementia, and moderate dementia due to Alzheimer’s) via intrathecal administration of AAVrh.10hAPOE2 (serotype rh.10 adeno-associated virus gene transfer vector expressing cDNA coding for human APOE2) directly to the central nervous system/cerebrospinal fluid. The goal of this approach is to increase the expression of APOE2 and overcome the harmful effects of APOE4.

In preclinical research, AAVrh.10hAPOE2 was tested with mice expressing human APP, PS1, and APOE4. Intracerebral delivery resulted in widespread brain expression of APOE2 as well as decreased beta-amyloid levels and amyloid deposition. Widespread expression of APOE2 was also observed in nonhuman primates two months after intraparenchymal, intracisternal, or intraventricular delivery of AAVrh.10hAPOE2.

In 2019, Weill Medical College of Cornell University began a Phase 1 trial, set to end in January 2024, evaluating LX1001 (AAVrh.10hAPOE2) in 15 volunteers who carry two APOE4 alleles, confirmed amyloid deposition, and a clinical diagnosis of MCI to moderate dementia. In March 2022, the FDA granted LX1001 Fast Track designation.

Improving and Accelerating Clinical Trials Assessing Gene Therapy for Alzheimer’s Disease

It is clear that gene therapy for Alzheimer’s disease is a promising area of clinical research, and advancements in neurosurgical techniques now enable reliable delivery of therapeutic vectors with real-time verification—yet several issues, such as the following, are hindering the ability to bring therapies to market quickly and help Alzheimer’s disease patients:  

• Costly and time-consuming subject screening and selection
• Unreliable tools for longitudinal cognitive assessment of trial subjects
• Lack of tools to support decentralized clinical trials and remote subject monitoring

Healthcare is currently undergoing a digital transformation, generating a whole new approach to healthcare. Big data, mobile devices, wearable devices, and innovative artificial intelligence are changing the game, opening up a whole new paradigm in medicine.

This digital transformation will change the way we diagnose, monitor, and even treat symptoms of a breadth of diseases, including neurological diseases. For patients, this means being able to take their health into their own hands using new digital technologies, and for national healthcare systems, this means being able to utilize resources more efficiently while simultaneously improving patient engagement and patient outcomes.

Virtual and augmented reality for dementia are two of the newest additions to this digital revolution and have applications spanning the diagnostic and therapeutic spectrum. 

Let’s take a closer look at how virtual and augmented reality are making their way into the neurological disease space.

Applications of Virtual and Augmented Reality for Dementia

According to Allied Market Research, the market for virtual and augmented reality in healthcare is expected to reach $2.4 billion by 2026. The growing demand for new, innovative diagnostic and therapeutic techniques, alongside increased awareness surrounding applications of virtual and augmented realities technologies, is quickly bringing immersive technologies into the neurological disease space. 

Highly personalized, patient-oriented medicine is now within reach and includes augmented reality for supporting dementia patients with everyday tasks and managing behavioral symptoms of dementia, psychological need-based virtual reality experiences, and artificial intelligence to diagnose Alzheimer’s disease.

Neurocognitive Training Through Augmented Reality 

Neurocognitive deterioration in patients with dementia, particularly those with dementia caused by Alzheimer’s disease, is known to negatively impact patients’ abilities to complete complex Activities of Daily Living (ADLs), such as shopping for groceries, navigating routines, and preparing drinks and meals. The ADL capacity of a dementia patient greatly influences their ability to live and function independently.

In an effort to find an avenue for patients to practice and potentially improve upon these activities to remain independent, researchers have begun investigating using virtual and augmented reality for dementia patients. 

In a 2019 study, researchers aimed to analyze the feasibility and usability of a head-mounted Microsoft HoloLens to support patients with Alzheimer’s disease in executing the ADL of tea making. While executing this task, patients received three-dimensional dynamic holographs of the sub-steps required to complete the task.

Although they did not find that the guidance and support provided by augmented reality reduced errors or improved success rates, the overall acceptability of this application was high. Researchers concluded that the biggest impediment was the bulky hardware, and overall, the paradigm of augmented support is generally working, but the implementation itself needs improvement (e.g. through an improved user interface).

Virtual Reality for Mild Cognitive Impairment and Dementia

Virtual reality-based interventions are also making their mark in research and clinical trials. Over the last few years, researchers have investigated the potential of virtual reality to improve balance and reduce fall risk, reduce aggressive behaviors, and improve overall interactions and behaviors with caregivers.

• Balance, gait, and fall risk: A 2019 pilot study aimed to assess the feasibility, patient experience, and effects of a novel sensor-based balance training program using an interactive virtual user interface for patients with Mild Cognitive Impairment (MCI). The training included weight shifting and virtual obstacle crossing. When measuring post-intervention effects of the patients with MCI, they found that sway and fear of falling were reduced, indicating this method is beneficial for improving postural control.

• Behavioral and psychological symptoms of dementia (BPSD): A 2021 study aimed to develop a virtual reality intervention program for dementia patients in nursing homes to reduce BPSD and assess the program’s feasibility. Surveys and questionnaires were utilized to identify specific activities that alleviated BPSD among patients. Patients used arm motions in their virtual environment to choose the virtual location to visit and interact with. The study demonstrated the feasibility, safety, and patient satisfaction of the program and warrants further research to determine if the program can be utilized to reduce BPSD in dementia patients.