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Tag: Dopaminergic

  • Phase 2 trial reveals Lixisenatide may reduce motor disability in Parkinson’s patients

    Phase 2 trial reveals Lixisenatide may reduce motor disability in Parkinson’s patients

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    A recent study published in the New England Journal of Medicine conducted a trial of lixisenatide to assess its effects in early Parkinson’s disease.

    Study: Trial of Lixisenatide in Early Parkinson’s Disease. Image Credit: create jobs 51/Shutterstock.comStudy: Trial of Lixisenatide in Early Parkinson’s Disease. Image Credit: create jobs 51/Shutterstock.com

    Background

    Current treatments for Parkinson’s disease are primarily based on dopaminergic replacement therapy and have not convincingly demonstrated effects on disease progression. Further, epidemiological studies have observed increased Parkinson’s disease risk in individuals with type 2 diabetes.

    Moreover, some studies have shown a lower prevalence of Parkinson’s disease among diabetes patients treated with dipeptidyl peptidase-4 inhibitors or glucagon-like peptide (GLP)-1 receptor agonists compared to recipients of other medications.

    Lixisenatide is a GLP-1 receptor agonist used to treat type 2 diabetes. Its neuroprotective actions have been demonstrated in animal models of Parkinson’s disease and Alzheimer’s disease.

    About the study

    In the present study, researchers evaluated the disease-modifying effect of lixisenatide in individuals with early Parkinson’s disease. This phase 2, double-blind, randomized, multicenter, placebo-controlled trial was performed in France.

    People aged 40–75 diagnosed with Parkinson’s disease within the past three years were recruited. Eligible subjects were treated with a stable, optimized dopaminergic medication regimen for at least a month before starting trial agents.

    Participants were randomized to receive lixisenatide or placebo in addition to their standard treatment for Parkinson’s disease.

    The trial agent was initially administered at 10 μg/day for 14 days and 20 μg/day for the remainder of 12 months. Subjects continued their existing medication for Parkinson’s disease for the first six months at least.

    Clinical assessments were performed at baseline, six-month, and 12-month visits. Subjects were evaluated in an on-medication state based on scores on the Parkinson’s Disease Questionnaire summary index, Movement Disorder Society (MDS)-sponsored revision of the Unified Parkinson’s Disease Rating Scale (UPDRS) parts I–IV, and Montreal Cognitive Assessment.

    Besides, subjects were assessed in an off-medication state after a two-month washout period at 14 months.

    Fasting blood glucose and insulin levels were measured. Vital signs and adverse events were recorded at visits. The primary efficacy endpoint was the MDS-UPDRS part III scores change from baseline to 12 months.

    Secondary efficacy endpoints were the change in scores on MDS-UPDRS part III at six months, change in scores on MDS-UPDRS parts I, II, and IV at six and 12 months, and change in total MDS-UPDRS score at 12 months. Efficacy was assessed using Student’s t-test.

    Linear regression analyses investigated the potential effects of baseline levels of fasting blood glucose and insulin on the primary endpoint.

    Findings

    The study enrolled 156 subjects; seventy-eight were assigned to receive lixisenatide, and the remainder were assigned to the placebo group. In the lixisenatide arm, 28 subjects were switched back to the 10 μg/day dose due to side effects at the 20 μg/day dose.

    Further, dose reduction was required for three placebo recipients. Adherence to the trial agent was over 92% at all visits.

    Participants’ baseline clinical and demographic characteristics were similar between groups. In both groups, the average time from diagnosis was 1.4 years.

    The average baseline MDS-UPDRS motor score was 14.8 in lixisenatide subjects and 15.5 in placebo recipients. At 12 months, these scores were 14.9 and 18.8 in the lixisenatide and placebo groups, respectively.

    Lixisenatide recipients improved their score by 0.04 points from baseline, while placebo subjects had worsened it by 3.04 points. At 14 months, these scores were 17.7 and 20.7 in the lixisenatide and placebo groups, respectively.

    Results for secondary/exploratory measures were similar between groups at six and 12 months. No associations were observed between fasting blood glucose and insulin levels at baseline and MDS-UPDRS part III score at 12 months.

    Most participants had at least one adverse event. Gastrointestinal side effects were more prevalent with lixisenatide.

    The two groups had a similar incidence of serious adverse events. One serious adverse event, syncope in placebo recipients and pancreatitis in the lixisenatide group was deemed treatment-related.

    Conclusions

    In sum, this phase 2 trial showed that lixisenatide, administered in an on-medication state, had a three-point improvement on a motor disability scale over 12 months compared to baseline.

    This difference was driven by an increase in scores in placebo recipients. Further, a three-point between-group difference in the motor score was observed after the two-month washout period, favoring active treatment.

    Notably, the trial involved subjects with early disease; as such, it has to be investigated whether drug effects persist at other stages of the disease.

    Moreover, secondary endpoints did not definitively support primary endpoint results; therefore, longer washout periods may be necessary to test if the drug has long-lasting effects.

    Journal reference:

    • Meissner WG, Remy P, Giordana C, et al. (2024) Trial of Lixisenatide in Early Parkinson’s Disease. N Engl J Med,. doi: 10.1056/NEJMoa2312323.

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  • Ketamine’s rapid impact on depression linked to immune system pathways

    Ketamine’s rapid impact on depression linked to immune system pathways

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    In a recent study published in Molecular Psychiatry, researchers review the anti-inflammatory effects of ketamine in the peripheral and central nervous systems. To this end, all relevant articles were obtained from PubMed and Web of Science databases, with both animal and human studies published until September 2023 considered for the analysis.

    Study: Ketamine’s mechanism of action with an emphasis on neuroimmune regulation: Can the complement system complement ketamine’s antidepressant effects? Image Credit: Jack_the_sparrow / Shutterstock.com

    Treating major depressive disorder

    Major depressive disorder (MDD) is a mood disorder associated with persistent feelings of loss of interest and sadness. Current estimates indicate that over 300 million individuals are affected by MDD globally, about 700,000 of whom commit suicide each year. Altered neurotrophin levels and monoamine dysregulation are both mechanisms that have been attributed to manifestations of MDD.

    Monoamines associated with noradrenergic, serotoninergic, and dopaminergic activities can be regulated through certain pharmaceutical agents to improve the cognition, sleep, and mood of MDD patients. However, conventional monoamine antidepressant therapy has only been shown to be effective in 30-40% of patients with MDD. 

    According to the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, a significant number of MDD patients do not respond to standard treatment. Patients who fail to respond to two antidepressants of suitable dosage are known to suffer treatment-resistant depression (TRD). 

    Racemic (R, S)-ketamine, which is more commonly referred to as ketamine, and (S)-ketamine (esketamine) have shown significant positive effects on MDD. As compared to conventional treatments, ketamine has been shown to exert antidepressant effects within a few hours. Many TRD patients have also responded positively to a single ketamine infusion.

    Mechanism of action of ketamine for MDD treatment

    The mechanisms that underlie the antidepressant effects of ketamine are associated with the N-methyl-D-aspartate (NMDA) receptor, opioid pathway, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor, and mechanistic target of rapamycin (mTOR). 

    Various neuronal cells, including microglia and astrocytes, regulate neuroinflammation. Individuals with MDD often exhibit lower levels of glial fibrillary acidic protein (GFAP) and glutamate transporter-1 (GLT-1). In these patients, an acute administration of ketamine normalized these levels, thus improving their mood. 

    In vivo experimental findings have also shown that ketamine has an inhibitory effect in lipopolysaccharide (LPS)-induced microglial activation, which led to improvements in depressive-like behaviors. Rodent studies have also reported that transforming growth factor β (TGF)-β, an anti-inflammatory molecule inhibiting excessive microglial activation, is associated with the differential antidepressant effects of ketamine enantiomers.

    Mouse models have revealed that (R)-ketamine, and not (S)-ketamine, alleviates stress-induced reduction in the expression of Tgfb1 and its receptors Tgfbr1 and Tgfbr2. Nevertheless, additional research is needed to clarify the microglia-based mechanisms underlying the antidepressant effects of ketamine.

    Patients with MDD exhibit higher interleukin 6 (IL-6) and tumor necrosis factor ⍺ (TNF-⍺) levels than non-depressed individuals. One rodent study revealed ketamine administration normalized these levels and improved MDD symptoms.

    Higher levels of granulocyte-macrophage colony-stimulating factor (GM-CSF) have been observed in patients with MDD. Administration of 0.5 mg/kg ketamine infusions for twelve days led to symptomatic improvement that was associated with significant downregulation of GM-CSF. 

    Ketamine and the immune response

    The antidepressant effects of ketamine have been linked with the complement system, which is a vital component of synaptic plasticity. The complement system comprises 30 proteins that are involved in the classical, alternate, and lectin pathways, all of which converge in C3 cleavage, a major complement component.

    Complement proteins play a crucial role in the regulation of cell proliferation, maturation, and responsiveness. Activation of the complement system results in the release of complement and immune molecules that are linked with inflammatory responses.

    Increased levels of serum complement components C3a and C5a have been observed in bipolar disorder. Similarly, a high concentration of serum C1q levels is found in patients with MDD.

    An in vivo experiment with C5a receptor knockout mice highlighted the neuroprotective role of C5a against glutamate excitotoxicity-induced apoptosis through elevated expression and regulation of glutamate receptor subunit 2 (GluR2). Glutamatergic modulation has been established as a mechanistic commonality between the complement system and ketamine. 

    Ketamine also activates mTORC1 by triggering the brain-derived neurotrophic factor (BDNF), tropomyosin receptor kinase B (TrkB), and NMDA receptors. Additionally, the the C3a ligand-C3a receptor in CD4 + T-cells leads to mTOR activatiwhich is on, essential for cell survival. Complement-mTOR activation also modulates many stress and metabolic pathways, such as cytokine secretion, oxidative phosphorylation, and inflammasome activation.

    Conclusions

    The current study indicated the potential association between the complement system and the antidepressant effects of ketamine. Nevertheless, additional studies are needed to improve treatment outcomes for MDD using ketamine.

    Journal reference:

    • Quintanilla, B., Zarate, C. A., and Pillai, A. (2024) Ketamine’s mechanism of action with an emphasis on neuroimmune regulation: Can the complement system complement ketamine’s antidepressant effects? Molecular Psychiatry; 1-10. doi:10.1038/s41380-024-02507-7

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  • Can psychedelics improve sexual functioning and satisfaction?

    Can psychedelics improve sexual functioning and satisfaction?

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    In a recent study published in the journal Scientific Reports, researchers explored the influence of psychedelics on sexual functioning using a large, naturalistic study and a controlled clinical trial that compared the impacts of psilocybin and selective serotonin reuptake inhibitors (SSRI) on various facets of sexual functioning in patients with major depressive disorders.

    Study: Psychedelics and sexual functioning: a mixed-methods study. Image Credit: Cannabis_Pic/Shutterstock.comStudy: Psychedelics and sexual functioning: a mixed-methods study. Image Credit: Cannabis_Pic/Shutterstock.com

    Background

    Research on psychedelic substances has followed a relatively unsteady trajectory, with various clinical studies through the 1950s and up to the 1970s examining the use of lysergic acid diethylamide (LSD) for treating alcohol dependence and mood disorders.

    Psychedelics also played a major role in the social movements of the 1960s, such as the anti-war protests and hippy culture. The 1971 Act on Controlled Substances passed by the United Nations, however, brought most of the scientific research on psychedelics to a halt.

    Recent studies indicate a revival of research interest in the use of psychedelics as therapeutic avenues for mental health disorders. Studies have examined the effectiveness of psilocybin therapy in alleviating symptoms of depression and anxiety.

    Psilocybin also showed comparable efficacy to the SSRI escitalopram in lowering symptoms of depression, with significantly better performance in secondary outcomes such as anhedonia, general functioning, and well-being.

    Given that sexual dysfunction is a common symptom in patients with major depressive disorder, and it is also the side effect of most SSRIs, it is essential to explore the impact of psychedelics on sexual function.

    About the study

    In the present study, the researchers examined the use of psychedelics in naturalistic settings and ceremonies to understand its effect on various aspects of sexual functioning.

    The association was further investigated in a six-week-long clinical trial comparing psilocybin with escitalopram. Sexual functioning was explored along the domains of sexual satisfaction, pleasure, arousal, body image, importance of sex, and sexual desires.

    The researchers also aimed to understand whether psychedelics influenced sexual openness and desires for sexual exploration using a set of self-constructed questions. Additionally, the study evaluated the differences in this association among male and female patients.

    Although not a core symptom, sexual dysfunction is very common in individuals with major depressive disorders, with the most frequently reported symptoms being difficulty getting aroused, lower libido, and a delay in or absence of orgasms in patients of both sexes.

    Furthermore, sexual dysfunction is also known to be a common side effect of SSRIs such as fluoxetine, citalopram, and escitalopram.

    Impairments in sexual function due to SSRIs are thought to be due to the downstream impact of SSRIs on dopaminergic and serotoninergic. Sexual dysfunction can also significantly lower self-esteem and impact the quality of relationships and life.

    Sexual satisfaction has also been linked to lower depression rates among individuals of both sexes.

    For the first part of the study, the researchers gathered data from individuals who attended a ceremony that involved the consumption of psychedelics such as magic mushrooms, psilocybin, ayahuasca, LSD, N, N-Dimethyltryptamine, etc.

    The second part of the study involved data obtained from a double-blinded, controlled, phase II clinical trial that compared the effectiveness of psilocybin therapy against that of escitalopram therapy against major depressive disorder.

    Results

    The results from the naturalistic study showed that the use of psychedelics brought about improvements in various domains of sexual satisfaction and functioning, including body image, partner satisfaction, and improvements in communication and pleasure during sex.

    The clinical trial included in the study also supported these findings and reported that the post-acute effects of psilocybin therapy with respect to sexual functioning were positive, while those of escitalopram therapy were not.

    The findings suggested that while both psilocybin and escitalopram therapy resulted in comparable reductions in the symptoms of depression, escitalopram had a significant negative impact on sexual functioning.

    However, the researchers also stated that these results on the negative impact of escitalopram must not be generalized to all SSRIs since various SSRIs have been developed that do not cause sexual dysfunction to the same extent as escitalopram.

    The difference in the impacts of escitalopram and psilocybin on sexual functioning could be linked to the different mechanisms by which they alleviate depression.

    SSRIs inhibit serotonin re-intake, increasing serotonin concentrations and promoting serotonin activity in the post-synaptic phase.

    This impacts the downstream serotoninergic and dopaminergic functioning, subsequently impacting acetylcholine, testosterone, and nitric oxide levels that affect libido.

    Conclusions

    Overall, the results showed that the use of psilocybin in treating major depressive disorder might have a positive impact on sexual functioning.

    While this association needs to be explored further through validated measures, the findings do support the fact that psychedelics not only reduce the symptoms of major depressive disorder but could also be potentially important treatment options for other disorders that have reduced sexual functioning.

    Journal reference:

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  • Microfluidic chips advance neurodegenerative disease research

    Microfluidic chips advance neurodegenerative disease research

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    A review article published in the journal Nature Communications provides a detailed overview of recent developments in microfluidic chip models for neurodegenerative diseases.

    Study: Neuropathogenesis-on-chips for neurodegenerative diseases. Image Credit: luchschenF / ShutterstockStudy: Neuropathogenesis-on-chips for neurodegenerative diseases. Image Credit: luchschenF / Shutterstock

    Background

    Recent advancements in medical science have significantly increased human life expectancy, leading to a gradual risNeuropathogenesis-on-chips for neurodegenerative diseasesNeuropathogenesis-on-chips for neurodegenerative diseases in the aging population globally. This is accompanied by a concomitant increase in the prevalence of age-related neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis.

    Neurodegenerative diseases primarily affect the cognitive and behavioral abilities of older adults. With the accumulation of dysfunctional proteins as the primary initiating factor, these diseases share some common pathogenic characteristics, including specific neuronal loss, gliosis, neuroinflammation, oxidative stress, mitochondrial dysfunction, and early vascular damage.

    Despite advancements in medical science, the development of diagnostic and therapeutic interventions for neurodegenerative diseases remains a challenging task because of the complex multifactorial pathogenesis that progresses gradually.

    Microfluidic organs or organoids-on-chips have provided a unique opportunity to experimentally reproduce critical elements of distinct brain regions associated with neurodegenerative diseases. These miniaturized systems can be used for studying disease pathogenesis, drug development, drug screening, and primary biomedical research purposes.

    Microfluidic chip design  

    The ‘Campenot chamber,’ a compartmentalized in vitro system, was the first microfluidic chip application for brain research. With two fluidically separated chambers, this device is used to study the effects of nerve growth factors on axonal growth. Later, scientists invented several miniaturized systems of neuron-glia cells, the blood-brain barrier, and the neurovascular unit.

    Microfluidic chips typically contain two or more fluidically separated chambers that are connected by microchannels, porous membranes, or phase guides. These connections are required to maintain direct or indirect interactions between homogeneous or heterogeneous cell populations kept in these chambers.      

    The earliest microfluidic chip for the brain was designed by separating a neuronal soma from its neurites using microchannels. This design was used to study directional neurite growth. More advanced neural circuit models were developed later by incorporating multiple chambers for neuronal subpopulations.

    AD is characterized by the inclusion of misfolded amyloid-β (Aβ) and neurofibrillary tangles in pyramidal neurons, primarily in the hippocampus and cortex regions of the brain. b PD is characterized by Lewy body aggregates composed of misfolded α-synuclein and degeneration of dopaminergic neurons in the substantia nigra region of the brain. c ALS is characterized by including mutant TAR DNA-binding protein 43 (TDP-43) and other proteins, degeneration of motor neurons in the motor cortex and spinal cord, and muscle atrophy with dysfunctional proteins. d HD is characterized by including mutant Huntingtin protein (mHTT) and degeneration of medium spiny neurons in the basal ganglia, and corpus striatum of the brain. AD Alzheimer’s disease, ALS amyotrophic lateral sclerosis, BDNF brain-derived neurotrophic factor, EAL endosomal-autophagic-lysosomal pathway, GABA gamma-aminobutyric acid, HD Huntington’s disease, PSEN presenilin 1, SNCA synuclein alpha.AD is characterized by the inclusion of misfolded amyloid-β (Aβ) and neurofibrillary tangles in pyramidal neurons, primarily in the hippocampus and cortex regions of the brain. b PD is characterized by Lewy body aggregates composed of misfolded α-synuclein and degeneration of dopaminergic neurons in the substantia nigra region of the brain. c ALS is characterized by including mutant TAR DNA-binding protein 43 (TDP-43) and other proteins, degeneration of motor neurons in the motor cortex and spinal cord, and muscle atrophy with dysfunctional proteins. d HD is characterized by including mutant Huntingtin protein (mHTT) and degeneration of medium spiny neurons in the basal ganglia, and corpus striatum of the brain. AD Alzheimer’s disease, ALS amyotrophic lateral sclerosis, BDNF brain-derived neurotrophic factor, EAL endosomal-autophagic-lysosomal pathway, GABA gamma-aminobutyric acid, HD Huntington’s disease, PSEN presenilin 1, SNCA synuclein alpha.

    Current neuronal chips contain multiple chambers of different diameters positioned in various geometries. These models also include microchannels with patterned shapes and controlled fluid flow. These features allow for indirect and direct, asymmetric, and symmetric neuronal connections.     

    Extra pump systems and passive hydrostatic pressure can be incorporated into chips to control fluid flow. This helps create disease models by allowing a gradient of chemicals with varying concentrations throughout the cell compartments.  

    Porous membranes with different pore sizes, numbers, and positions can be used on chips as an interface between chambers to enable indirect interactions mediated by soluble chemicals and direct physical contact. This design has been used for mimicking the blood-brain barrier on chips.

    Application of microfluidic chips for neurodegenerative disease pathogenesis

    Microfluidic chips can be used for replicating several anatomical and physiological systems, including the neuromuscular junction, corticostriatal pathway, substantia nigra, blood-brain barrier, glymphatic system, neurovascular unit, and gut-brain axis.

    To provide mechanical, structural, and biochemical cues to cells, 3D extracellular matrix gel has been introduced on chips, which allows for studying cell morphology, migration patterns, signal transduction, and gene expression in the context of neurodegenerative diseases.

    Alzheimer’s disease-on-chips

    The application of microfluidic chips in Alzheimer’s disease research has provided valuable insights into distinct pathogenic features, including amyloid-beta and tau protein accumulation, mitochondrial dysfunction, and neuroinflammation.

    Several models of neurons-on-a-chip have been used to study tau propagation and amyloid-beta toxicity. By separating the soma and neurites, neurons-on-a-chip allow real-time visualization of proteinopathy.

    A gradient chip with interstitial flow has been used to study the effect of amyloid-beta oligomers on neurons. Inflammatory cytokine-mediated migration of microglia towards Alzheimer’s disease neurons and astrocytes has been observed using a 3D static neuroinflammation-on-a-chip model.

    Blood-brain barrier-on-a-chip has been developed to fully recapitulate amyloid plaque formation, neurofibrillary tangle formation, and increased permeability of the brain endothelial cells.

    Dynamic neurospheroid-on-a-chip has been developed by incorporating an osmotic pump that creates a flow of exogenous amyloid-beta to study axonal degeneration and cell death.

    Parkinson’s disease-on-chips

    Many studies have been conducted using Parkinson’s disease-on-a-chip to primarily recapitulate alpha-synuclein-related pathogenesis. The propagation of alpha-synuclein has been studied by co-culturing neuroglioma cells that express green fluorescent protein-tagged alpha-synuclein.

    A gradient chip has been developed to manipulate intracellular alpha-synuclein expression in singularly trapped yeasts in the system with a galactose gradient. Dopaminergic neurons-on-a-chip have been developed to recapitulate mitochondrial dysfunction and neural degeneration caused by Parkinson’s disease-related mutations.     

    Substantia nigra and vascular barrier chips have been developed by co-culturing human-induced pluripotent stem cell-derived midbrain dopaminergic neurons, primary glia cells, and brain microvascular endothelial cells in chambers separated by porous membrane. This model has been used to study blood-brain barrier-on-a-chip dysfunction, progressive neuronal loss, neuroinflammation, and astrogliosis.  

    Amyotrophic lateral sclerosis on-chips

    Application of chemotactic and volumetric gradients on amyotrophic lateral sclerosis-on-chips has caused the successful formation of interactions between FUS-mutated motor neurons and mesangioblast-derived myotubes through microchannels.

    Many pathologies of amyotrophic lateral sclerosis have been recapitulated by co-culturing TAR DNA-binding protein 43 (TDP-43)-mutated motor neuron spheroid and muscle fibers in a 3D condition between two separate chambers.  

    A three-chamber-chip has been developed to create metabolic interactions between superoxide dismutase-mutated astrocytes and cortical neurons through microchannels in a glutamate gradient condition. 

    Muscle denervation pathology of amyotrophic lateral sclerosis has been studied using an open compartmentalized neuromuscular junction device that co-cultures optogenetic motor neurons and superoxide dismutase-mutated astrocytes as a spheroid.

    Huntington’s disease on-chips

    Early pathologies of Parkinson’s disease have been studied by forming synaptic connections between cortical axons and striatal dendrites through microchannels of different lengths and a separate synaptic channel.

    Corticostriatal on-a-chip has been developed to study how mutant huntingtin protein reduces the cortical axonal transport of brain-derived neurotrophic factors to trigger striatal neuron degeneration.

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  • How cell types and location influence Parkinson’s disease

    How cell types and location influence Parkinson’s disease

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    In a recent study published in Cell Reports, researchers conducted a single-cell spatial transcriptome analysis on murine brain expression in age and disease using a Parkinson’s disease (PD) transgenic model, focusing on dopaminergic neurons (DA) spanning 29 cell types.

    Study: Single-cell spatial transcriptomic and translatomic profiling of dopaminergic neurons in health, aging, and disease. Image Credit: solarseven/Shutterstock.comStudy: Single-cell spatial transcriptomic and translatomic profiling of dopaminergic neurons in health, aging, and disease. Image Credit: solarseven/Shutterstock.com

    Background

    The spatially structured brain contains various cells, each with a distinct purpose. PD is a neurodegenerative condition characterized by DA loss and alpha-synuclein buildup due to overexpression via locus multiplication.

    Single-cell ribonucleic acid sequencing (RNS-seq) has improved the knowledge of cell-based expression in organs such as the brain, but current methods fail to attain high-throughput resolution. Fluorescent in situ hybridization (FISH) technologies provide higher sensitivity at an individual level.

    About the study

    In the present study, researchers performed single-cell spatial transcriptomic and translatomic profiling of DA to find markers for healthy and aged cells.

    The researchers crossed Rosa26fsTRAP::DATIREScre (DAT-TRAP) mice with SNCA-OVX mice to enable DA messenger RNA (mRNA) capture in a PD model.

    The mice were aged to 18 months to assess the influence of human ⍺-synuclein overexpression and aging on dopaminergic neuron genetic expression and study the effect of healthy and Parkinsonian aging.

    The researchers created a single-cell-level spatial transcriptomic map of gene expression in the adult mouse brain and a high-fidelity translatome-level profile of DA neuron expression.

    They analyzed stereo-seq arrays with special transcript maps. They converted the transcript expression maps to segmented individual cells, identifying 29 types of cells, including astrocytes and inhibitory cortical neurons, in 18 brain slices.

    The team filtered the segmented cells by transcriptome size and complexity and analyzed spatially distinct cortex, hippocampus, and thalamus populations. They also examined the ventral midbrain and striatum to enrich transcripts confined to the cell body and putative axon.

    They used data from gene enrichment and genome-wide association studies (GWAS) to identify potential disease-causing genes.

    They evaluated each cell’s location and compared DA neuronal gene expression in various cells.

    The researchers examined enhanced green fluorescent protein (eGFP)-tagged ribosomes in DAT-expressing cells and confirmed eGFP colocalization with tyrosine hydroxylase (TH), a DA neuronal marker.

    They split cells from stereo-seq brain slices, filtering them based on detected genes, and performed Uniform Manifold Approximation and Projection (UMAP) analysis.

    They also performed short- and long-read RNA sequencing of the translating mRNA collected by TRAP and used stereo-sequencing and TRAP data to rank prospective genes for inquiry into sporadic PD.

    The researchers demonstrated specific enrichment of DA marker genes and depletion of marker genes of other neighboring cell types in DAT-TRAP mRNA.

    They confirmed specific calcium-sensing receptor (CASR) protein expression in mouse ventral midbrain neurons and investigated CASR expression in human-induced pluripotent stem cell-derived DA neurons. They also examined age-related gene variations in cells revealed by stereo-seq.

    Results

    The team studied PD in young and aged brains to identify genes having spatially varying expression in dopaminergic neurons of the ventral tegmental area (VTA) and substantia nigra (SN) and particular markers such as copine-7 (Cpne7) and Solute carrier family 10 member 4 (Slc10a4) genes.

    They also detected splice variants unique to DA. They demonstrated ways of using TRAP and stereo-sequencing expression specificity measurements to identify potentially relevant genes from GWAS areas, indicating that CASR regulates intracellular DA neuronal calcium.

    The findings demonstrated substantia nigra-specific DA neuronal loss and increased microglial activation with age. They highlighted aging- and disease-associated genetic alterations in various cells, including dopaminergic neurons, across many PD-related pathways.

    Stereo-seq detected expression alterations caused by aging and illness across different cell types, loss of nigral DA neurons, and the neuroinflammatory expansion of microglia.

    Pathway enrichment research revealed that various biological processes were altered, including axon ensheathment, synaptic transmission modulation, intracellular calcium ion homeostasis, and catecholamine secretion control.

    The team extracted 355,307 transcriptomes of high quality with spatial coordinate details from 18 murine brains, identifying a total of 14,494 genes.

    They observed synaptosomal-associated protein, 25kDa (Snap25) expression, and structured localization in places like the thalamus or hippocampus differentiated neurons from glia.

    They also examined neuronal cells in the CA1 region, CA3 region, subiculum, and dentate gyrus in the hippocampus region or gamma-aminobutyric acid (GABA)-releasing nuclei in the midbrain.  

    Marker expression enabled oligodendrocyte, astrocyte, microglia, and erythrocyte identification. In DAT-TRAP samples, classical markers of dopaminergic neurons showed significant enrichment, whereas those of other cell types decreased in the ventral midbrain.

    Conclusion

    Overall, the study identified 29 unique brain cell types by examining variations in spatial gene expression linked to aging and illness. The stereo-seq data indicated differences in transcript use across more than a thousand genes.

    There were 817 occurrences of alternative splicing, suggesting that more genes were being translated than gene-level count data showed. The study also discovered an age-dependent drop in SN DA neuron cell number, which supports earlier findings.

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  • Deep learning shines a new light on Parkinson’s detection through the eye

    Deep learning shines a new light on Parkinson’s detection through the eye

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    A recent Scientific Reports study discusses the potential of retinal fundus imaging as a diagnostic screening modality for Parkinson’s disease (PD).

    Study: Deep learning predicts prevalent and incident Parkinson’s disease from UK Biobank fundus imaging. Image Credit: recep art / Shutterstock.com

    Background

    PD is associated with a gradual decline in motor control and several non-motor symptoms due to the progressive loss of dopaminergic neurons in the substantia nigra of the brain.

    PD-related deaths have more than doubled since 2000, mainly because of the lack of good-quality interventions among the elderly. Thus, further research is needed to better understand the pathology of PD and develop early diagnostic systems.

    The retina, often referred to as a window to the brain, provides a viable avenue for assessing neuropathological processes associated with many neurodegenerative diseases. Despite recent progress, clinical findings on retinal degeneration are not always inconclusive, which warrants further research to enhance retinal diagnostic power.

    To this end, artificial intelligence (AI) algorithms, including deep learning models and conventional machine learning algorithms, have emerged as efficient diagnostic tools.

    About the study

    Developing a deep understanding of retinal biomarkers of PD requires a thorough knowledge of the structural degeneration of the retinal vasculature. Although this is often difficult to achieve clinically, AI could aid in elucidating the complex relationships at the local and global spatial levels of the retina. The present study proposes the use of AI algorithms to address the aforementioned challenge and is one of the first extensive AI studies on diagnosing PD from fundus imaging. 

    The study’s primary aim was to systematically profile the classification performance across various phases of PD progression, including incident and prevalent PD. By neglecting any feature selection methods or external quantitative measures, the researchers maximized the diagnostic ability of AI algorithms. Robustness was established through deep learning and conventional machine learning methods. 

    Study findings

    Deep neural networks outperformed conventional machine learning models and exhibited notable performance in the detection of PD in retinal fundus images. The model successfully predicted the incidence of PD before formal diagnosis with a sensitivity level of 80% from zero to 5.07 years.

    Between 5.07 and 5.57 years, sensitivity rose to 93.33% and then reduced to 81.67% between 5.57 and 7.38 years. These results are promising, as they show the potential for early disease intervention.

    Attribution correspondence of retinal features. In the first column, an artery-vein (red and blue, respectively) map is combined with the optic cup (teal) and optic disc (yellow) generated from the AutoMorph deep learning segmentation module. A white dashed line is shown as an estimate for the foveal region. In the third column, a predicted attribution map is generated using the guided backpropagation algorithm on top of the AlexNet model. The intersection of the salient features with the segmentation is shown in the last column. The images represent the left (top) and right (bottom) eyes from the same subject, demonstrating distinct feature distributions for prediction.Attribution correspondence of retinal features. In the first column, an artery-vein (red and blue, respectively) map is combined with the optic cup (teal) and optic disc (yellow) generated from the AutoMorph deep learning segmentation module. A white dashed line is shown as an estimate for the foveal region. In the third column, a predicted attribution map is generated using the guided backpropagation algorithm on top of the AlexNet model. The intersection of the salient features with the segmentation is shown in the last column. The images represent the left (top) and right (bottom) eyes from the same subject, demonstrating distinct feature distributions for prediction.

    Automated deep neural networks can complement ophthalmologists to identify disease biomarkers and perform the high-throughput evaluation. To date, AI-based PD assessment using the retina is rare. Importantly, prior research did not compare deep learning and conventional machine learning methods.

    In contrast, the current study evaluated a wide range of deep learning and conventional machine learning methods to consider the entire fundus image as a diagnostic medium. Moreover, prevalent and incident PD patients were successfully differentiated from appropriately matched healthy controls with an accuracy of 68%.

    Conclusions

    In the current study, conventional machine learning models were outperformed by deep learning models to precisely predict PD from retinal fundus images. This method was robust to image perturbations, which is promising for early treatment.

    This work is expected to provide the foundation for future research and act as an algorithm selection reference for both its interpretability and performance.

    A fundamental limitation of this study is the dataset size, which could be improved to capture a broader range of presentations of PD. Second, the study is based on the United Kingdom population, thereby limiting the generalizability of the findings.

    An additional limitation of the current study is that the researchers did not report how this approach could be applied to different severity levels of PD. Although the current study was focused on PD, it remains unclear whether other neurogenerative diseases like Alzheimer’s disease, as well as certain eye diseases, share similar degeneration patterns or biomarkers.

    Future research should also investigate whether the model predictions can inform ophthalmologists’ grading. However, this could be complicated as the visual biomarkers of common eye diseases are better understood than those of PD.

    Taken together, these limitations necessitate additional research using diverse samples to establish the trustworthiness of AI models in clinical settings.

    Journal reference:

    • Tran, C., Shen, K., Liu, K., et al. (2024). Deep learning predicts prevalent and incident Parkinson’s disease from UK Biobank fundus imaging. Scientific Reports 14(1);1-12. doi:10.1038/s41598-024-54251-1

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  • Researchers introduce a pioneering approach to combat neurodegenerative diseases

    Researchers introduce a pioneering approach to combat neurodegenerative diseases

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    Researchers led by Northwestern University and the University of Wisconsin-Madison have introduced a pioneering approach aimed at combating neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease and Amyotrophic lateral sclerosis (ALS).

    In a new study, researchers discovered a new way to enhance the body’s antioxidant response, which is crucial for cellular protection against the oxidative stress implicated in many neurodegenerative diseases.

    The study published today (Feb. 16) in the journal Advanced Materials. 

    Nathan Gianneschi, the Jacob & Rosaline Cohn Professor of Chemistry at Northwestern’s Weinberg College of Arts and Sciences and member of the International Institute for Nanotechnology, led the work with Jeffrey A. Johnson and Delinda A. Johnson of the University of Wisconsin-Madison School of Pharmacy.

    Targeting neurodegenerative diseases

    Alzheimer’s disease, characterized by the accumulation of beta-amyloid plaques and tau protein tangles; Parkinson’s disease, known for its loss of dopaminergic neurons and presence of Lewy bodies; and ALS, involving the degeneration of motor neurons, all share a common thread of oxidative stress contributing to disease pathology. 

    The study focuses on disrupting the Keap1/Nrf2 protein-protein interaction (PPI), which plays a role in the body’s antioxidant response. By preventing the degradation of Nrf2 through selective inhibition of its interaction with Keap1, the research holds promise for mitigating the cellular damage that underlies these debilitating conditions. 

    “We established Nrf2 as a principal target for the treatment of neurodegenerative diseases over the past two decades, but this novel approach for activating the pathway holds great promise to develop disease-modifying therapies,” Jeffrey Johnson said.

    Limitations of current therapeutics

    The research team embarked on addressing one of the most challenging aspects of neurodegenerative disease treatment: the precise targeting of PPIs within the cell. Traditional methods, including small molecule inhibitors and peptide-based therapies, have fallen short due to lack of specificity, stability and cellular uptake.

    The study introduces an innovative solution: protein-like polymers, or PLPs, are high-density brush macromolecular architectures synthesized via the ring-opening metathesis polymerization (ROMP) of norbornenyl-peptide-based monomers. These globular, proteomimetic structures display bioactive peptide side chains that can penetrate cell membranes, exhibit remarkable stability and resist proteolysis.

    This targeted approach to inhibit the Keap1/Nrf2 PPI represents a significant leap forward. By preventing Keap1 from marking Nrf2 for degradation, Nrf2 accumulates in the nucleus, activating the Antioxidant Response Element (ARE) and driving the expression of detoxifying and antioxidant genes. This mechanism effectively enhances the cellular antioxidant response, providing a potent therapeutic strategy against the oxidative stress implicated in many neurodegenerative diseases.

    The innovation behind protein-like polymers

    PLPs, developed by Gianneschi’s team, could represent a significant breakthrough in halting or reversing damage offering hope for improved treatments and outcomes.

    Focusing on the challenge of activating processes crucial for the body’s antioxidant response, the team’s research offers a novel solution. The team provides a robust, selective method enabling enhanced cellular protection and offering a promising therapeutic strategy for a range of diseases including neurodegenerative conditions. 

    Through modern polymer chemistry, we can begin to think about mimicking complex proteins. The promise lies in the development of a new modality for the design of therapeutics. This could be a way to address diseases like Alzheimer’s and Parkinson’s among others where traditional approaches have struggled.”


    Nathan Gianneschi, the Jacob & Rosaline Cohn Professor of Chemistry at Northwestern’s Weinberg College of Arts and Sciences 

    This approach not only represents a significant advance in targeting transcription factors and disordered proteins, but also showcases the PLP technology’s versatility and potential to revolutionize the development of therapeutics. The technology’s modularity and efficacy in inhibiting the Keap1/Nrf2 interaction underscore its potential for impact as a therapeutic, but also as a tool for studying the biochemistry of these processes. 

    A collaboration of minds 

    Highlighting the study’s collaborative nature, Gianneschi’s team worked closely with experts across disciplines, illustrating the rich potential of combining materials science with cellular biology to tackle complex medical challenges. 

    “We were contacted by Professor Gianneschi and colleagues proposing to use this novel PLP technology in neurodegenerative diseases due to our previous work on Nrf2 in models of Alzheimer’s disease, Parkinson’s disease, ALS and Huntington’s disease,” Jeffrey Johnson said. “We had never heard of this approach for Nrf2 activation and immediately agreed to initiate this collaborative effort that led to the generation of great data and this publication.” 

    This partnership underscores the importance of interdisciplinary research in developing new therapeutic modalities.

    Impact

    With the development of this innovative technology, Gianneschi, his colleagues at the International Institute for Nanotechnology and the Johnson Lab at the University of Wisconsin-Madison, are not just advancing the field of medicinal chemistry, they are opening new pathways to combat some of the most challenging and devastating neurodegenerative diseases faced by society today. As this research progresses towards clinical application, it may soon offer new hope to those suffering from diseases of oxidative stress such as Alzheimer’s and Parkinson’s diseases. 

    “By controlling materials at the scale of single nanometers, we’re opening new possibilities in the fight against diseases that are more prevalent than ever, yet remain untreatable,” Gianneschi said. “This study is just the beginning. We’re excited about the possibilities as we continue to explore and expand the development of macromolecular drugs, capable of mimicking some of the aspects of proteins using our PLP platform.”

    Source:

    Journal reference:

    Carrow, K. P., et al. (2024). Inhibiting the Keap1/Nrf2 Protein‐Protein Interaction with Protein‐Like Polymers. Advanced Materials. doi.org/10.1002/adma.202311467.

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