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Psychedelics May Help Treat Neurodegenerative Disorders

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Alzheimer’s disease (AD) is a devastating neurodegenerative disorder that affects millions of people worldwide. The hallmark features of AD include neuroinflammation, dendritic atrophy, and loss of synapse density in cortical regions controlling cognition, memory, and mood. Recent research has pointed to a potentially groundbreaking therapy using psilocybin, a naturally occurring compound found in certain mushrooms known for its hallucinogenic properties. While some current treatments carry significant risk for adverse side effects, psilocybin and other psychedelics are relatively low risk. This blog discusses the emerging evidence suggesting that psilocybin may hold promise as a treatment for AD due to its ability to promote neuronal growth and modulate neuroinflammation.

Recent studies have demonstrated that psychedelics like psilocybin can stimulate 5-HT2A receptors, promoting cortical neuron growth, activation of neuronal survival mechanisms, and modulation of the immune system. Activation of these receptors induces the expression of immediate early genes (IEGs), which are known to be involved in neuroplasticity. Moreover, psychedelics have been shown to activate signaling pathways that promote neurotrophic factor release, particularly brain-derived neurotrophic factor (BDNF), which plays a crucial role in neuronal growth and survival. BDNF is often reduced in AD, contributing to the progressive loss of spines and synapses associated with dementia. In both human and animal studies, psychedelics like psilocybin increased BDNF expression in the cortex, increasing neuronal growth. These structural changes are accompanied by functional changes, such as an increase in spontaneous excitatory postsynaptic currents (sEPSCs), which indicate improved synaptic activity.

Neuroinflammation is increasingly recognized as a critical component of AD pathophysiology. Psychedelics have shown potential in modulating the immune system and reducing inflammation. By promoting cortical neuron growth and modulating neuroinflammation, psilocybin may have the potential to simultaneously address two significant components of AD pathophysiology.

One of the most promising aspects of psychedelic medicine is the long-lasting therapeutic effects observed after a single administration. Clinical trials and preclinical studies have demonstrated that psychedelic-assisted therapy can elicit therapeutic responses lasting for months. In some cases, this effect has been associated with increased neuroplasticity. In addition to promoting neuronal growth and modulating neuroinflammation, using psilocybin to activate 5-HT2A receptors has been shown to improve mitochondrial function. Mitochondrial dysfunction and oxidative stress are common features of neurodegenerative diseases like AD. By enhancing mitochondrial function, psilocybin may further contribute to its therapeutic potential for AD.

 While the evidence supporting the use of psilocybin for treating neurodegenerative disorders like AD is still limited, the emerging research is promising. The unique ability of psychedelics to promote both structural and functional neuroplasticity through the activation of 5-HT2A receptors makes them an intriguing candidate for further exploration as a potential treatment for AD. As we continue to investigate the therapeutic potential of psychedelics, it is crucial to conduct further research to better understand their mechanisms of action and assess their safety and efficacy for treating neurodegenerative diseases. Collaborative efforts between researchers, medical professionals, and therapeutic facilitators will be essential to unlock the full potential of psychedelic medicine and offer hope to those affected by devastating neurological disorders like AD.

Reference: Saeger, H. N., & Olson, D. E. (2022). Psychedelic-inspired approaches for treating neurodegenerative disorders. Journal of Neurochemistry, 162, 109–127. 

Rationale for Amyloid-Beta Targeting Therapies for Early AD Treatment

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Recent translational studies have led to a model of Alzheimer’s disease (AD) pathophysiology that focuses on the accumulation of amyloid-beta (Aβ) plaques between 20-30 years prior to the spread of tau, neuronal loss, and appearance of clinical symptoms. These findings have enabled the current research landscape to evolve to include preclinical stages of AD, when treatment success is predicted to be higher. There are a number of contributing factors that lead to a person developing AD. However, the multifactorial nature of AD largely plays into the reasoning researchers are focusing on Aβ accumulation for potential therapeutic interventions for early AD.

As discussed in previous blogs, Aβ is an enzymatic product of the amyloid precursor protein (APP) gene. An imbalance of Aβ production in the brain and extra-cellular clearance precedes Aβ protein misfolding and aggregation into brain plaques in AD. Mutations in APP can make enzymes involved in processing it bind more tightly to it, causing more of these misfolded Aβ protein fragments to be produced. Additionally, the APP gene can be processed by 3 main proteases: β-secretase and gamma-secretase promote toxic Aβ production, whereas A-secretase produces healthy, soluble Aβ. Dysregulation in these secretases can result in Aβ over production. Although an excess of Aβ proves detrimental, Aβ protein is necessary for normal neurotransmission and synaptic plasticity, so knocking out the APP gene altogether is not a viable solution. Large-scale genome-wide association studies have identified over 50 additional genetic risk factors for AD, and while they do not denote the exact cause of the disease, most are involved in maintaining Aβ homeostasis. For instance, those with early-onset AD often have mutations in at least one of three genes: APP, presenilin 1 (PSEN1), and presenilin 2 (PSEN 2), and have increased Aβ due to genetic driven-dysregulation. This is compared to those with late-onset AD, with Aβ plaques largely attributed to reduced cellular quality control.
Another well-known genetic association with Aβ metabolism and homeostasis is an individual’s apolipoprotein (APOE) genotype. In-vitro and mouse models have shown that APOE moderates the activity of specific enzymes and downstream Aβ production. Those with an APOE E4 genotype were found to have significantly higher Aβ secretion, and those with two copies resulted in a 5-13-fold increase in AD incidence. Although our genes can be important in determining health status, sometimes it’s the downstream events, after protein production, that can initiate dysfunction. These post-translational, or epigenetic, changes further modify gene expression and protein production and degradation, continuing to alter Aβ levels.
In an attempt to protect the brain from Aβ plaques, microglia activate to prevent Aβ plaque spread, help with Aβ clearance, and attempt to limit Aβ accumulation. A dysregulation in these microglia, or a normal regulation under Aβ conditions, can further induce Aβ aggregation in the brain. Transforming growth factor-beta1 (TGFβ-1) is a neuroprotective, anti-inflammatory growth factor that stimulates Aβ clearance. In those with early AD, this growth factor is selectively impaired. The presence of Aβ can induce detrimental microglia activity, causing the release of pro-inflammatory cytokines and interfering with anti-inflammatory cytokine synthesis. For example, the cytokine tumor necrosis factor-alpha (TNF-α) results in increased synthesis of Aβ peptides, and its presence perpetuates more TNF- α in a vicious cycle. Studies have found that TNF-α levels are elevated in both mild cognitive impairment (MCI) and AD. Therefore, Aβ is again a common factor in the culmination of events that can lead to disease progression. Since microglia have both beneficial and detrimental effects on the brain when associated with Aβ, an undiscovered temporal factor may be at play, indicating that only at certain stages can microglia constructively intervene. More research is needed to elucidate this further.

Toxicity within the Aβ pathway is believed to play a crucial role in the progression of AD. Studies have suggested a temporal progression of Aβ pathophysiology from the spread of Aβ aggregation to the formation of plaques in the brain. While the causal effect is not fully established, evidence suggests that Aβ aggregation may facilitate and have a synergistic effect on other pathophysiological pathways, triggering downstream effects such as tau misfolding, tangle formation, and eventual neurodegeneration. Understanding this relationship is crucial for unraveling the pathogenesis of AD.

In summary, the central role of Aβ in AD pathophysiology demonstrates why it is a viable target for early treatment options. Aβ accumulation during preclinical stages presents a critical time period for intervention. Imbalances in Aβ production and clearance contribute to plaque formation, while genetic risk factors can trigger further disruption of Aβ homeostasis. When microglia fail to effectively limit Aβ accumulation, Aβ aggregation is accelerated. The resulting toxicity is thought to start a cascade of events, causing disease progression. Continued research holds potential for the development of effective therapies targeting Aβ in the early stages of AD, potentially improving treatment outcomes for individuals affected by this devastating disease.

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Reference:

The Amyloid-β Pathway in Alzheimer’s Disease

Hampel H; Hardy J; Blennow K; Chen C; Perry G; Kim SH; Villemagne VL; Aisen P; Vendruscolo M; Iwatsubo T; Masters CL; Cho M; Lannfelt L; Cummings JL; Vergallo A

https://pubmed.ncbi.nlm.nih.gov/34456336/

Understanding Why Tangles Spread in Alzheimer’s Disease: Part II

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Part I of this 2-part blog series discussed possibilities why neurofibrillary tangles (NFTs) spread in the brains of people with Alzheimer’s disease (AD). Phosphorylated tau protein (p-Tau) 217, a potential mediator between amyloid plaque accumulation and NFTs, and sTREM2, a microglial activation marker showing correlation to rising p-tau and plaque thresholds due to its instigation of phosphorylating the tau protein are two key factors that may affect the proliferation of NFTs. However, we cannot pinpoint these factors as the sole reason for NFT propagation, as the research is inconsistent. Alzheimer’s is a very complex disease and researchers have difficulty determining how it develops with multiple variables at play (e.g., genes, environment, diet, various strands of p-Tau, etc.). Even with these complexities, probabilities and correlations emerge to point us in a direction of focus.

Next, we’ll discuss the patterns that tangles use to spread throughout the brain. Particularly, how location and higher neuronal firing in areas of the brain could propagate the spread of NFTs and how that correlates to the rate of cognitive decline.

A recent study investigated 3 models predicting tangle spread: one being functional, and the other two being structural. The functional model maintained the highest accuracy (r=0.58), inferring that tau is likely to spread based on which brain networks are most active, rather than how the brain is structured. Previous research has also found tau to be increasingly released during neuronal stimulation.

Where tangles begin accumulating in the brain is theorized to indicate the rate of cognitive decline. There is a large variation in how slowly or quickly people decline when diagnosed with AD, possibly due in part to the differing locations that tangles first begin. It is hypothesized that if tau aggregates in a less active or connected region of the brain, tangles are expected to spread slowly, whereas if tau aggregates in a highly active or densely connected region, tangles will spread quicker, and cognition will decline at a faster rate. A recent study replicated this theory. Interestingly, those who were more likely to have tangles in active neocortical, or hub regions, were younger participants, whereas the older participants had tangles located in less active/connected limbic regions. Those with symptomatic AD were found to have tangles in hub regions with an increased rate of tau aggregation over time, especially in younger people. Evidence suggests that tau accumulation beginning in a hub region leads to a higher likeliness of experiencing AD symptoms at an earlier age. At this time, we don’t know what makes tau aggregate in certain brain regions of some versus differing regions for others, but perhaps genes play a role in steering this variability.

Research has depicted risk alleles linked to AD. Carriers of the E4 variant of the APOE gene tend to accumulate more tangles in various brain regions with the temporal lobe as a particular hot spot, when compared to E3 variant carriers. Those carrying the E2 variant have even less tau burden when compared to E3 carriers. Interestingly, amyloid deposition seems to have little effect on tau burden in the case of E4 carriers, as the allele itself appears to drive the spread of NFTs. Future research remains to identify amyloid deposition as the strongest driver in tau accumulation, whereas involvement of the E4 allele may promote further tau accumulation, and E2 (identified as a protective gene against AD) diminishes tau accumulation, even in amyloid positive people.

There is still much to be determined in understanding why and how NFTs spread in the brain, how location of its aggregation plays a role in the rate of cognitive decline, and how genes and other environmental factors play a role. Identifying potential influences that lessen or increase the burden of tau and amyloid plaque assist in the knowledge of preventative measures and aid in the target of treatment. Nevertheless, more research is needed to confirm results and find successful therapies in halting the onset or spread of AD.

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References

 

Alzforum. (2022, September 08). What drives tangles to spread? answers start rolling in. Alzforum: Networking for a cure. https://www.alzforum.org/news/conference-coverage/what-drives-tangles-spread-answers-start-rolling

Understanding Why Tangles Spread in Alzheimer’s Disease: Part I

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             As discussed in our previous blogs, the study of Alzheimer’s disease (AD) concentrates on its two primary biomarkers: phosphorylated Tau protein (p-tau), that reflects neurofibrillary tangles (NFTs), and amyloid beta (Aβ), that forms amyloid plaques. The give and take between plaques and NFTs complicate the understanding of how AD develops and spreads, as it is hypothesized that Aβ accumulation activates the phosphorylation of tau (i.e., p-tau) therefore instigating NFT formation. Clinically, as NFTs proliferate through the brain, a person’s cognition declines in correspondence with the rate and location where NFTs are spreading. However, it is unclear how this process is controlled and how plaques stimulate it, causing difficulty in finding a successful therapy, or cure, for AD.

             A rise in phosphorylated tau is indicative of plaque formation; p-tau181, p-tau217, and p-tau231 are the most telling isoforms. Research has found that p-tau217 mediates the interplay between plaques and tangles. One study compared regional plaque accumulation and p-tau217 thresholds to understand which has a stronger influence on the spread of tangles. Findings show that p-tau217 was the main predictor for the spread of NFTs. However, the association between p-tau217 and NFTs decreased as the disease progressed. Plaque load and p-tau tend to plateau in those with AD, but tangles continue to spread. With these findings, perhaps p-tau217 is the initial spark that induces tangles, but once the NFTs have made a prominent presence, tangles themselves take over the continuity of spreading. This indicates that p-tau217 could be a therapeutic target for AD, but only in the early stages.

             Taking the focus of AD pathology a step earlier in the process, another study sought out how plaques give rise to p-tau to begin with. Research has labeled sTREM2, a microglial activation marker, as a connection to rising p-tau. Microglia are the immune scavenger cells in the brain. This study compared three groups of people: amyloid-negative controls, early amyloid accumulators, and late amyloid accumulators to dissect the association of plaques and p-tau. Results found that plaques and increased sTREM2 and p-tau181 correlated, but differed between the stages of AD. In early accumulators, plaques were found to instigate microglia in a way to activate the phosphorylation of p-tau181, allowing it to increase. However, in late accumulators, sTREM2 appeared to weaken p-tau181’s effect. Nonetheless, these results have been found reversed in other research, making it difficult to understand the connection of microglia’s role in brain atrophy.

             Phosphorylated tau may have a role in the progression of NFTs as described above, but how can these higher concentrations of p-tau, and its eventual plateau, explain the patterns that tangles spread throughout the brain? Stay tuned for Part II of this blog, where we discuss how location and higher neuronal firing in areas could propagate the spread of NFTs and how this associates with the occurrence and rate of cognitive decline.

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References

Alzforum. (2022, September 08). What drives tangles to spread? answers start rolling in. Alzforum: Networking for a cure. https://www.alzforum.org/news/conference-coverage/what-drives-tangles-spread-answers-start-rolling

The Interplay Between Alzheimer’s Disease Biomarkers and Predicting Cognitive Decline

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      Alzheimer’s disease (AD) biomarkers allow the identification of those at risk of developing AD and will aid in preventing the disease. The two primary biomarkers of AD are phosphorylated Tau protein, which forms neurofibrillary tangles (NFTs), and amyloid beta (Aβ), which forms amyloid plaques. The Amyloid hypothesis posits Aβ buildup activates the misfolding of Tau via hyper-phosphorylation (p-Tau) leading to NFT formation that kills neurons. Two types of p-Tau can be measured through blood tests or cerebrospinal fluid (CSF) and can indicate an accumulation of Aβ presence in the brain prior to symptom onset.

         Cognitively normal older adults who are positive for both plaques and NFTs decline much faster than those without either biomarker as well as older adults who only have plaques. Those with the presence of both pathologies (i.e., plaques and NFTs) have about a 15-20 times higher risk of developing dementia or mild cognitive impairment. Furthermore, brain regions in which NFTs have spread also indicate worsening decline in cognition. For example, those with both plaques and NFTs in the neocortex perform worse on tests of cognition (specifically global cognition, semantic fluency, and executive function) than those with NFTs that are still contained in the medial temporal lobe (MTL) that subserves memory function. As NFTs spread to the neocortex, multiple domains of cognition begin to deteriorate, which is indicative of a much higher risk of progressing quickly to dementia. The presence of both plaques and especially NFTs predict cognitive decline. Once p-Tau levels spike in CSF NFT presence is clearer and cognitive decline begins.

       Biomarker positivity is required in the new diagnostic criteria of preclinical AD under the National Institute on Aging and Alzheimer’s Association (NIA-AA) without any clinical symptoms. Furthermore, these biomarkers provide us an opportunity for preventative treatments in those at risk for AD before symptom onset. Eli Lily is utilizing this tactic in their assessment of Donanemab to slow the progression of cognitive decline in those at risk for AD based on elevated blood p-Tau levels. The investigational drug is a monoclonal antibody that removes Aβ plaques in the brain. Although previous and current clinical trials with Donanemab show great promise, the drug only targets plaques, not NFTs. Although it’s indicated that NFTs develop during ongoing plaque accumulation, there is evidence that people can still form NFTs without the presence of Aβ plaques. The trial mentioned above requires participants to have a positive p-Tau blood test, meeting a certain threshold of tau that is hypothetically indicative of future cognitive decline. However, p-Tau levels can change much earlier in one’s lifetime in response to amyloid deposition and may prove unable to forecast measurable cognitive decline in the typical period of a clinical trial. This makes it difficult to know when cognitively intact adults will decline and how fast they could decline. Perhaps prevention trials should push to enroll people who are deemed cognitively normal but test positive for the presence of plaques and NFTs. In this case, it may be more telling of how we can measure and determine the timeline of cognitive decline in its response to a preventative investigational drug within the length of a 2–3-year clinical trial. 

         Even with the proven removal of deposited Aβ plaques, research is still struggling to show a clinical benefit. Removing Aβ plaques improves elevated biomarker levels associated with AD, but how early should this be done to improve patient’s lives, or at a minimum, slow further decline.

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Destined to Decline: Plaque-Tangle Combo Foretells Impairment. 2022, June 30. Alzforum. Retrieved August, 9, 2022 from https://www.alzforum.org/news/research-news/destined-decline-plaque-tangle-combo-foretells-impairment 
 

Eli Lilly and Company. (2022). Clinical Trial Information. Lilly.  https://trials.lilly.com/en-US/clinical-trial-information#what-to-expect

Could Non-Optimal Sleeping Patterns Predict Cognitive Decline and Change in Brain Structure?

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       Sleep plays a critical role in our cognitive processing, maintenance of psychological health, emotional processing, consolidation of memories, and is when, waste products in the central nervous system are cleared. Previously we discussed correlations between neurodegenerative disorders and sleep problems, specifically about not getting enough sleep and how Alzheimer’s disease (AD) and Parkinson’s disease (PD) share similar sleep abnormalities. Common concerns about sleep in AD and PD include insomnia, excessive daytime sleepiness, or abnormal motor activity while sleeping. Although many factors are involved with sleep difficulties (e.g., medication side effects), AD and PD are diseases that can damage areas of the brain that control sleep, leading to further disruption in one’s well-being. However, a difficult question remains: which problem starts first? Does the pathology of AD or PD lead to an inability to attain sufficient sleep, or does non-optimal sleep aid in the development of cognitive decline, and further, a neurodegenerative disease?

        A recent study showed that sleep problems likely precede cognitive dysfunction and that sleep duration predicts cognitive decline. The study gathered baseline average sleep duration and cognitive test scores from subjects aged 38 to 73 years old. Follow up data (i.e., average sleep duration, cognitive testing, neuroimaging) was collected about 8 years after baseline. An interesting finding emerged from the study, suggesting that not only was less sleep predictive of cognitive decline, but also too much sleep. Those who slept too much or too little than the average sleep duration overall (i.e., 7 hours) scored worse on tests of memory, fluid intelligence, reaction time, and executive function. Similar results emerged at follow-up, while the higher the reported abnormal sleep duration at baseline, the worse the cognitive scores at follow-up. The study indicates a “sweet spot” in consistent sleep duration, being about 7 hours, as test scores and mental well-being remained higher compared to consistent abnormal sleepers overall. Also long-term, consistent, under/oversleeping in middle adulthood is more predictive of worsening cognitive performance and mental health later in life, indicating middle adulthood as a critical period for sleep.

     Another measure of change, MRI results, collected at follow-up showed that those who reported optimal sleep duration at baseline had a significantly higher volume of gray matter compared to non-optimal sleepers. Regions of gray matter loss most pronounced in non-optimal sleepers involved the precentral cortex, lateral orbitofrontal cortex, and the hippocampus.

       Gray matter deterioration is a prominent feature of AD due to neuronal loss, causing progressive cognitive dysfunction. Consistent with previous findings is the reduction of gray matter in the lateral orbitofrontal cortex and hippocampus, both of which are associated with poor or disrupted sleep patterns in older adults. Previous research linked sleep duration and cognitive decline potentially due to the disruption in slow-wave sleep, which is associated with memory consolidation and amyloid deposition, both prominent abnormalities in AD.

       Overall, sleep has an important role in cognitive functioning and there are many factors involved with poor sleeping (e.g., genetic factors, medication side effects) or the development of a neurodegenerative disease. It is nearly impossible to identify a definitive cause, however research is continuously expanding to find potential preventative measures at best. In this discussion, although sleep disturbances may occur before the onset of cognitive decline and perhaps the development of a neurodegenerative disease, there may be hidden underlying factors associated with AD or PD pathology that are setting the course well before sleep disturbances appear.

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References
 
Alzforum. (2022, May 11). Sleep: Too little, or too much, foreshadows brain shrinkage. Alzforum, networking for a cure. https://www.alzforum.org/news/research-news/sleep-too-little-or-too-much-foreshadows-brain-shrinkage
 
Li, Y., Sahakian, B. J., Kang, J., Langley, C., Zhang, W., Xie, C., … & Feng, J. (2022). The brain structure and genetic mechanisms underlying the nonlinear association between sleep duration, cognition and mental health. Nature Aging, 1-13.
 
Wu, Z., Peng, Y., Hong, M., & Zhang, Y. (2021). gray matter deterioration pattern during alzheimer’s disease progression: A regions-of-interest based surface morphometry study. Frontiers in Aging Neuroscience, 13, 23.

Parkinson’s Disease and Dementia with Lewy Bodies: Could Molecule ATH-1017 Show Efficacy for Treatment of Each?

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Dementia with Lewy bodies (DLB), Parkinson’s disease (PD), and Parkinson’s disease dementia (PDD) are all neurodegenerative diseases embodied under Lewy Body disorders and have significant overlap in their pathologies, symptoms, and prognoses. Although closely related, these diseases have unique enough criteria to differentiate between them. Parkinson’s disease and DLB have identical pathologies, but early cognitive symptoms are associated with DLB over PD. Furthermore, if dementia occurs before, concurrently, or within 1 year of motor parkinsonism, DLB is diagnosed. If dementia occurs more than 1 year after an established PD diagnosis, then PDD is diagnosed. 

Both PDD and DLB typically follow the same Alzheimer’s disease (AD) dementia stages and nearly all PD patients experience some degree of cognitive deficit. Pathologically, PD is characterized by neurodegeneration and the formation of Lewy bodies (i.e., made up of misfolded alpha-synuclein) first in brainstem neurons, and then cortical structures as the disease advances. Cognitive deficits in PD are associated with deficits in various neurotransmitters (NT), with a deficiency of dopamine as the principal abnormality. Cognitive deficits are less common in PD when tremor is observed at onset, or in those with tremor predominant syndrome. Most common forms of neuropsychological deficits observed with PD involve executive dysfunction or mild subcortical dementia exemplified by difficulty in word list generation, organizational skills, and multi-tasking. 

Like PD, DLB is associated with Lewy bodies in the brainstem. However, those with DLB tend to have Lewy bodies in the substantia nigra to a lesser severity than patients with PD. Preferentially, with DLB, Lewy bodies are present in the cortex (e.g., limbic and paralimbic regions), with neocortical participation most severe in the temporal lobe. AD-type pathology is also seen, with senile plaque and neurofibrillary tangle deposition, regional neuronal loss, synapse loss, and NT deficits. Common cognitive deficits in DLB include delusions, hallucinations, fluctuating cognition/attention, REM sleep behavior disorder, depression, memory impairment, and disturbances in executive function. Parkinsonism in DLB consists of rigidity, bradykinesia, and dystonia, with rest tremor less frequent. 

Promising treatments for AD, PDD, and DLB tends to focus on therapeutic strategies that target neurotrophic factors to induce protection of existing neurons, promotion of synaptogenesis, neuronal growth, and regenerative mechanisms, which in turn, anticipates improved cognition, decreased inflammation, and improved cerebral blood flow; slowing the progression of neurodegeneration and negative effects that stem from it. Specifically, a small molecule approach that allows passage through the blood brain barrier and reaches all regions of the brain is a superior strategy in comparison to other non-efficient and invasive deliveries to the brain. Due to the stark overlap in these diseases, a medication used for AD may soon prove efficacious for the Lewy Body disorders as well.

A molecule known as ATH-1017 has potential promise for treatment of AD and may have efficacy for PD and DLB as well. ATH-1017 facilitates progress of hepatic growth factor (HGF) function and enables signal transduction through MET phosphorylation. Both HGF and MET activity in the central nervous system incorporate neuroprotective and neurotrophic effects, as well as modulation of neurogenesis and neuronal maturation. Findings suggest that ATH-1017 therapy has potential for pro-cognitive effects in those with AD, and now research is being conducted on the effects it may have on those with PDD or DLB, as there are many shared pathological characteristics between these disorders. Here at the Center for Cognitive Health, we offer clinical trials for PD/DLB and AD assessing the effects of ATH-1017. If interested, give us a call at 503-207-2066 or visit Our Webpage, where you can find a listing of all of the clinical trials being held at the Center.

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References 
 
Cummings, J., Mega, M. (2003). Neuropsychiatry and behavioral neuroscience. Oxford University Press. 
 
Athira Pharma. (2022). Are You or Someone You Know Living with Parkinson’s Disease Dementia or Dementia with Lewy Bodies? Consider Participating in the SHAPE Trial. Shape Trial. https://shapetrial.com/

Diagnostic Testing for Alzheimer’s Disease: Are Blood Tests an Upcoming Promise?

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Previously we have discussed the utilization of blood tests for diagnosing Alzheimer’s Disease (AD). There are few ways AD can be diagnosed with certainty (i.e., PET scan to assess amyloid-β, lumbar puncture to assess cerebrospinal fluid Amyloid and p-tau), these tests can be very expensive or invasive. Blood tests, on the other hand, are much safer, easier, and of lower cost. In this blog, we will continue to discuss the promise of blood testing for AD and its utilization in detecting different stages of the disease through serum levels of p-tau181.  

P-tau181 is a highly specific biomarker of AD and is a sub-type of misfolded tau protein. The occurrence of misfolded proteins can be triggered by genetics, environmental factors, or even head trauma to name a few. When a protein is misfolded it changes shape, leading to a functional change. Misfolded tau protein can also negatively change the shape of other correctly folded tau proteins, like a prion in Mad Cow disease, triggering neurofibrillary tangles (NFTs) to continue to aggregate and propagate down nerve networks interfering with neuronal functioning and causing cognitive decline in AD. 

       Blood levels of p-tau 181 can differentiate AD from other neurodegenerative diseases, as well as predicting disease staging and the rate of cognitive decline. Subjects with AD were compared with cognitively unimpaired age-matched controls, patients with mild cognitive impairment (MCI), those with frontotemporal dementia and other neurodegenerative disorders, as well as healthy young adults. Established cerebrospinal fluid (CSF) and PET biomarkers were collected to compare the capability of blood p-tau181 for identifying AD.

Concentrations of serum p-tau181 significantly increased with cognitive decline across groups. The lowest p-tau181 concentrations were found in healthy young adults and cognitively unimpaired older adults. The next highest levels were found in amyloid β-positive cognitively unimpaired older adults and those with MCI. The highest concentrations were found in amyloid β-positive AD patients. Serum p-tau181 was not only sensitive in correctly identifying AD stages but also specifically ruled out other causes of dementia. 

A simple blood test would be invaluable for identifying and assessing AD in the community and clinical trials, especially since such p-tau181 concentrations correlate to AD risk. Here at the Center for Cognitive Health, we offer an AD prevention trial utilizing the p-tau 217 blood test, developed by Lilly, to assess the risk for developing AD in those with no memory problems–TRAILBLAZER-ALZ3 is using Donanemab (an antibody that targets amyloid-β), hopefully to prevent AD from developing. The days of needing a dose of radioactivity for an Amyloid PET scan or a spinal tap for CSF assessment may soon become obsolete. Hopefully, the results of this study will determine if treatment prevention (e.g., Donanemab) based on p-tau blood levels will be successful. If interested in knowing more about the study mentioned above, please visit our clinical trials page or give us a call at 503-207-2066 to find out more about disease modifying opportunities. 

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Sources
A donanemab prevention study in participants with Alzheimer’s disease (TRAILBLAZER-ALZ 3). (2022, April 7). ClinicalTrials.gov. Retrieved April 11, 2022, from https://clinicaltrials.gov/ct2/show/NCT05026866
Karikari, T. K., Pascoal, T. A., Ashton, N. J., Janelidze, S., Benedet, A. L., Rodriguez, J.L., Chamoun, M., Savard, M., Kang, M. S., Therriault, J., Schöll, M., Massarweh, G., Soucy, J. P., Höglund, K., Brinkmalm, G., Mattsson, N., Palmqvist, S., Gauthier, S., Stomrud, E., Zetterberg, H., … Blennow, K. (2020). Blood phosphorylated tau 181 as a biomarker for Alzheimer’s disease: a diagnostic performance and prediction modelling study using data from four prospective cohorts. The Lancet. Neurology, 19(5), 422–433. https://doi.org/10.1016/S1474-4422(20)30071-5

Exercise Related Neuroinflammatory Factor: Isolated

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Previously, we’ve discussed ways in which we can lower our risk of Alzheimer’s Disease, such as decreasing risk for cardiovascular disease and eating a healthy Mediterranean-like diet. In this blog, we will dive deeper into the benefits of exercise and a particular protein upregulated from exercise, as there appears to be some implications in neurologic benefit regarding two major neurodegenerative disorders, specifically Parkinson’s Disease (PD) and Alzheimer’s disease (AD).

            Parkinson’s Disease is a disorder of the central nervous system that is characterized by impaired motor abilities including tremor, slowed and rigid mobility, unintentional movements, and even cognitive dysfunction (e.g., fluctuations in alertness, mild memory impairment). Regular physical activity is beneficial in slowing the progression of PD. In PD, neurodegeneration of the dopaminergic neurons in the substantia nigra occurs, damaging motor and reward systems.  Researchers compared PD patients who exercised to those who did not, and found that regular exercise slowed patient’s physical and cognitive decline but intermittent activity did not. Furthermore, exercise needed to be task and context specific to target declining functions in PD. For example, activities involved with balance-control, like Tai-Chi, better maintained postural and gait function compared to other activities. PD patients involved in household and work-related activities showed slower decline in activities of daily living (ADLs) and cognition. Additionally, regular physical activity increased corticostriatal plasticity and increased dopamine (DA) release stimulating increased activation of the striatum, possibly contributing to improved PD symptoms in those that habitually exercise. An encouraging takeaway from these findings suggests that something as simple as regularly sustained physical activity may lead to a modification in the typical trajectory of PD, slowing the rate of both the physical and cognitive decline, something that PD medications currently cannot accomplish. Furthermore, low levels of the brain protein clusterin predicts faster cognitive decline and dementia progression; clusterin increases with sustained exercise and may contribute to neurologic benefit.

A recent study compared the effects of physical activity with mice that regularly exercised to sedentary mice. After 28 days of running, the active mice, compared to their sedentary counterparts, showed increased overall cell survival in the memory circuit (called the hippocampus) as well as neural stem cells, progenitor cells, and astrocytes–all of which play important roles in neuronal maintenance, function, and repair. Similar beneficial results in the sedentary mice occurred with injection of serum taken from the exercised mice. When clusterin was removed from the exercised mice serum before injecting into the sedentary mice, the neurological benefits of decreased inflammation went away, supporting the role that clusterin may have in AD or PD when in lower proportions. To further understand these results, the researchers utilized RNA sequencing to analyze changes in gene expression in the active mice compared to their sedentary counterparts.  Physical activity in mice altered their gene expression, upregulating genes associated with hippocampal learning and memory. 

Humans with mild cognitive impairment (MCI) that exercise regularly for six months also show improved verbal and episodic memory, as well as significantly increased levels of clusterin. These results again indicate a role clusterin may play in AD and PD. 

All in all, exercise, and perhaps what is upregulated from exercise organically, like clusterin, may have a more powerful underlying effect on cognition than we knew previously. Such activity slowed decline in physical and cognitive functioning in PD, and may also work for those suffering from AD. Due to the increase in clusterin upon exercise, and the evidence presented above of clusterin’s capacity to improve brain function, one would wonder if providing clusterin may slow or prevent cognitive decline in those at risk. At this time, more research is needed to understand the potential implications of clusterin’s effect on cognition, especially in relation to diseases that affect cognitive functioning. Perhaps one day, for those of us who are too lazy to exercise, a clusterin pill will allow us to stay on the couch binge watching Netflix indefinitely! 

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Resources:

Hurley, D. (2022, February 17). A molecule transfers neurologic benefits of exercise to the sedentary. Neurology Today.

Mak, M.K.Y. & Schwarz, H.B. (2022). Could exercise be the answer? Neurology, 98(8), 303-304. doi:10.1212/WNL000000000001328

Tau: How Different Isoforms Predict Different Stages of AD Progression

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       If you have read our blogs before, you are likely familiar with the two primary biomarkers of Alzheimer’s disease (AD), protein tau which forms neurofibrillary tangles (NFTs) and amyloid beta (Aꞵ) which forms amyloid plaques. Both of these contribute heavily to neuronal dysfunction, degeneration, and eventual memory impairment, but the relationship between them is complicated and has been the subject of research for several years. Evidence suggests that Aꞵ buildup instigates the misfolding of protein tau, eventually inducing NFT formation, however, tau levels better predict cognitive impairment than Aꞵ levels. More recently, researchers have expanded upon this by determining different stages of AD development as predicted by Aꞵ and tau.

       Before explaining the stages, we need to have some prior knowledge. While we frequently refer to tau as a single protein, this is not necessarily the case. Tau’s full name is microtubule associated protein tau (MAPT), and in its normal form it serves as the rigid scaffolding that helps maintain the shape of axons, the communication bridge between neurons. The diagram below depicts both normal, healthy tau as well as the NFTs that form in cases of AD. It is believed that the presence of toxic Aꞵ proteins induce hyperphosphorylation of tau proteins, changing their structure. This decreases their ability to support microtubules and makes them prone to clumping together, inducing dysfunction both through the tangle of proteins blocking normal cellular functions in the brain and through axonal loss due to their lack of stabilization.

       The specific locations on the protein at which tau can be hyperphosphorylated result in multiple different forms of tau, called p-tau isoforms. The most relevant isoforms to AD are p-tau217, 181, and 205. The presence, or lack thereof, of each type of tau predicts something different and generally correlates to a specific stage of disease progression. For example, an increase of p-tau217 and 181 without presence of NFTs predicts amyloidosis, the buildup of Aꞵ plaques in the brain before symptom onset. A rise of p-tau205 as measured by cerebrospinal fluid (CSF) correlates to waning brain metabolism and shrinking gray matter, the initial stages of degeneration but not yet producing dysfunction. Finally, as total tau levels spike in CSF, NFTs begin to form and cognitive decline begins. Interestingly, once NFT formation begins and global cognition starts to decline, the amount p-tau181 and 217 present in CSF plummets, presumably because these isoforms are being sequestered into the NFTs that are now forming. While this explanation for decrease in CSF p-tau levels is hypothetical, it is supported by the fact that the same phenomenon occurs with amyloid. The figure below from Barthélemy et. al. (2020) exemplifies this sudden change in p-tau and amyloid levels around the estimated year of onset (EYO).

       This information is extremely useful because AD therapies being tested in clinical trials utilize many different mechanisms to fight the disease. Using the different p-tau metrics above, it may be possible to more specifically gauge how far progressed a patient may be and what therapies are most likely to be useful. It is also projected that the increased specificity for placement in trials provided by p-tau measurements, as well as tau PET scans using a new and more accurate tracer, could reduce the sample size needed within clinical trials to find (or disprove) efficacy. Specifically, for trials on preclinical (asymptomatic) AD, using p-tau217 with tau PET scans was hypothesized to reduce required sample size by 43% and by 68% for MCI trials. Using either p-tau217 or tau PET alone would theoretically also result in reduced sample requirements, albeit to a lesser degree, with p-tau217 alone for preclinical AD trials reducing sizes by 31%, and PET alone reducing MCI trial sizes by 47%.

       A decreased sample size with more specific subject selection could provide faster clinical trial outcomes with lessened screening times, and a decrease in the likelihood of a successful drug requiring additional data before coming to market. Should these staging procedures become a widespread method of pre-screening, patients are more likely to be placed into a clinical trial that will help them based upon their specific disease staging, whether that be clearing tau tangles, preventing tau aggregation, or clearing amyloid proteins before they even initiate the hyperphosphorylation of tau.

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Sources:
Different CSF Phospho-Taus Match Distinct Changes in Brain Pathology. Alzforum [Internet]. 2020. Available from: https://www.alzforum.org/news/research-news/different-csf-phospho-taus-match-distinct-changes-brain-pathology
In Preclinical Alzheimer’s, p-tau217 in Blood Best Predicts Tangles. Alzforum [Internet]. 2021. Available from: https://www.alzforum.org/news/research-news/preclinical-alzheimers-p-tau217-blood-best-predicts-tangles
Barthélemy et. al. A soluble phosphorylated tau signature links tau, amyloid and the evolution of stages of dominantly inherited Alzheimer’s disease. Nature Medicine [Internet]. 2020. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309367/