Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes

One path, two solutions: Network-based analysis identifies targetable pathways for the treatment of comorbid type II diabetes and neuropsychiatric disorders

Comorbid diseases complicate patient outcomes and escalate healthcare costs, necessitating the need for a deeper mechanistic understanding. Neuropsychiatric disorders (NPDs) such as Neurotic Disorder, Major Depression, Bipolar Disorder, Anxiety Disorder, and Schizophrenia significantly exacerbate Type 2 Diabetes Mellitus (DM2), often leading to suboptimal treatment outcomes. The neurobiological mechanisms underlying this comorbidity remain poorly understood. To address this gap, we developed a novel pathway-based network computational framework to identify critical shared disease mechanisms between DM2 and these five prevalent comorbid NPDs. Our approach involves reconstructing an integrated DM2 ∩ NPDs KEGG pathway-pathway network and employs two complementary analytical methods, including the "minimum path to comorbidity" method to identify the shortest path fostering comorbid development. This analysis uncovered shared pathways like the PI3K-Akt signaling pathway and highlighted key nodes such as calcium signaling, MAPK, estrogen signaling, and apoptosis pathways. Dysregulation of these pathways likely contributes to the development of DM2-NPDs comorbidity. These findings have significant clinical implications, as they identify promising therapeutic targets that could lead to more effective treatments addressing both DM2 and NPDs simultaneously. Our model not only elucidates the intricate molecular interactions driving this comorbidity but also identifies promising therapeutic targets, paving the way for innovative treatment strategies. Additionally, the framework developed in this study can be adapted to study other complex comorbid conditions, advancing personalized medicine for comorbidities and improving patient care.

Dexmedetomidine, an alpha-2 adrenoceptors agonist, provides a neuroprotective effect for dopaminergic neurons in the substantia nigra and attenuates glucose imbalance in the 6-hydroxydopamine animal model of Parkinson's disease

INTRODUCTION

Studies have shown that dexmedetomidine (DEX, an a2-adrenoceptors agonist) provides a neuroprotective effect and influences blood glucose levels. Here, we evaluated the effect of prolonged treatment with low doses of DEX on the survival rate of dopaminergic (DAergic) neurons in the substantia nigra and also serum glucose levels in 6-hydroxydopamine (6-OHDA) - induced Parkinson's disease (PD) in the rat.

MATERIAL AND METHODS

The neurotoxin of 6-OHDA was injected into the medial forebrain bundle by stereotaxic surgery. DEX (25 and 50 µg/kg, i.p) and yohimbine, an a2-adrenoceptor antagonist (1 mg/kg, i.p) were administered before the surgery to the 13 weeks afterward. Apomorphine-induced rotational tests and blood sampling were carried out before the surgery and multiple weeks after that. Thirteen weeks after the surgery, the rats' brain was transcardially perfused to assess the survival rate of DAergic neurons using the tyrosine hydroxylase (TH) immunohistochemistry.

RESULTS

DEX remarkably attenuated the severity of rotational behavior and reversed the progress of the PD. It also increased the number of TH-labeled neurons by up to 60%. The serum glucose levels in 6-OHDA-received rats did not change in the third and seventh weeks after the surgery but decreased significantly in the thirteenth week. Treatment with DEX prevented this decrement in glucose levels. On the other hand, Treatment with yohimbine did not affect PD symptoms and glucose levels.

CONCLUSION

Our data indicate that DEX through neuroprotective activity attenuates the severity of 6-OHDA-induced PD in rats. DEX might also prevent hypoglycemia during the progress of the PD.

Antidiabetic drugs in Parkinson's disease

This review explores the intricate connections between type 2 diabetes (T2D) and Parkinson's disease (PD), both prevalent chronic conditions that primarily affect the aging population. These diseases share common early biochemical pathways that contribute to tissue damage. This manuscript also systematically compiles potential shared cellular mechanisms between T2D and PD and discusses the literature on the utilization of antidiabetic drugs as potential therapeutic options for PD. This review encompasses studies investigating the experimental and clinical efficacy of antidiabetic drugs in the treatment of Parkinson's disease, along with the proposed mechanisms of action. The exploration of the benefits of antidiabetic drugs in PD presents a promising avenue for the treatment of this neurodegenerative disorder.

Toxic interactions between dopamine, α-synuclein, monoamine oxidase, and genes in mitochondria of Parkinson's disease

Parkinson's disease is characterized by its distinct pathological features; loss of dopamine neurons in the substantia nigra pars compacta and accumulation of Lewy bodies and Lewy neurites containing modified α-synuclein. Beneficial effects of L-DOPA and dopamine replacement therapy indicate dopamine deficit as one of the main pathogenic factors. Dopamine and its oxidation products are proposed to induce selective vulnerability in dopamine neurons. However, Parkinson's disease is now considered as a generalized disease with dysfunction of several neurotransmitter systems caused by multiple genetic and environmental factors. The pathogenic factors include oxidative stress, mitochondrial dysfunction, α-synuclein accumulation, programmed cell death, impaired proteolytic systems, neuroinflammation, and decline of neurotrophic factors. This paper presents interactions among dopamine, α-synuclein, monoamine oxidase, its inhibitors, and related genes in mitochondria. α-Synuclein inhibits dopamine synthesis and function. Vice versa, dopamine oxidation by monoamine oxidase produces toxic aldehydes, reactive oxygen species, and quinones, which modify α-synuclein, and promote its fibril production and accumulation in mitochondria. Excessive dopamine in experimental models modifies proteins in the mitochondrial electron transport chain and inhibits the function. α-Synuclein and familiar Parkinson's disease-related gene products modify the expression and activity of monoamine oxidase. Type A monoamine oxidase is associated with neuroprotection by an unspecific dose of inhibitors of type B monoamine oxidase, rasagiline and selegiline. Rasagiline and selegiline prevent α-synuclein fibrillization, modulate this toxic collaboration, and exert neuroprotection in experimental studies. Complex interactions between these pathogenic factors play a decisive role in neurodegeneration in PD and should be further defined to develop new therapies for Parkinson's disease.

Mito-metformin protects against mitochondrial dysfunction and dopaminergic neuronal degeneration by activating upstream PKD1 signaling in cell culture and MitoPark animal models of Parkinson's disease

Impaired mitochondrial function and biogenesis have strongly been implicated in the pathogenesis of Parkinson's disease (PD). Thus, identifying the key signaling mechanisms regulating mitochondrial biogenesis is crucial to developing new treatment strategies for PD. We previously reported that protein kinase D1 (PKD1) activation protects against neuronal cell death in PD models by regulating mitochondrial biogenesis. To further harness the translational drug discovery potential of targeting PKD1-mediated neuroprotective signaling, we synthesized mito-metformin (Mito-Met), a mitochondria-targeted analog derived from conjugating the anti-diabetic drug metformin with a triphenylphosphonium functional group, and then evaluated the preclinical efficacy of Mito-Met in cell culture and MitoPark animal models of PD. Mito-Met (100-300 nM) significantly activated PKD1 phosphorylation, as well as downstream Akt and AMPKα phosphorylation, more potently than metformin, in N27 dopaminergic neuronal cells. Furthermore, treatment with Mito-Met upregulated the mRNA and protein expression of mitochondrial transcription factor A (TFAM) implying that Mito-Met can promote mitochondrial biogenesis. Interestingly, Mito-Met significantly increased mitochondrial bioenergetics capacity in N27 dopaminergic cells. Mito-Met also reduced mitochondrial fragmentation induced by the Parkinsonian neurotoxicant MPP+ in N27 cells and protected against MPP+-induced TH-positive neurite loss in primary neurons. More importantly, Mito-Met treatment (10 mg/kg, oral gavage for 8 week) significantly improved motor deficits and reduced striatal dopamine depletion in MitoPark mice. Taken together, our results demonstrate that Mito-Met possesses profound neuroprotective effects in both in vitro and in vivo models of PD, suggesting that pharmacological activation of PKD1 signaling could be a novel neuroprotective translational strategy in PD and other related neurocognitive diseases.

Type 2 Diabetes and Parkinson's Disease: A Focused Review of Current Concepts

Highly reproducible epidemiological evidence shows that type 2 diabetes (T2D) increases the risk and rate of progression of Parkinson's disease (PD), and crucially, the repurposing of certain antidiabetic medications for the treatment of PD has shown early promise in clinical trials, suggesting that the effects of T2D on PD pathogenesis may be modifiable. The high prevalence of T2D means that a significant proportion of patients with PD may benefit from personalized antidiabetic treatment approaches that also confer neuroprotective benefits. Therefore, there is an immediate need to better understand the mechanistic relation between these conditions and the specific molecular pathways affected by T2D in the brain. Although there is considerable evidence that processes such as insulin signaling, mitochondrial function, autophagy, and inflammation are involved in the pathogenesis of both PD and T2D, the primary aim of this review is to highlight the evidence showing that T2D-associated dysregulation of these pathways occurs not only in the periphery but also in the brain and how this may facilitate neurodegeneration in PD. We also discuss the challenges involved in disentangling the complex relationship between T2D, insulin resistance, and PD, as well as important questions for further research. © 2022 International Parkinson and Movement Disorder Society.

Biological and Clinical Implications of Sex-Specific Differences in Alzheimer's Disease

Mounting evidence indicates that the female sex is a risk factor for Alzheimer's disease (AD), the most common cause of dementia worldwide. Decades of research suggest that sex-specific differences in genetics, environmental factors, hormones, comorbidities, and brain structure and function may contribute to AD development. However, although significant progress has been made in uncovering specific genetic factors and biological pathways, the precise mechanisms underlying sex-biased differences are not fully characterized. Here, we review several lines of evidence, including epidemiological, clinical, and molecular studies addressing sex differences in AD. In addition, we discuss the challenges and future directions in advancing personalized treatments for AD.

The Impact of Type 2 Diabetes in Parkinson's Disease

BACKGROUND

Type 2 diabetes (T2DM) is an established risk factor for developing Parkinson's disease (PD), but its effect on disease progression is not well understood.

OBJECTIVE

The aim of this study was to investigate the influence of T2DM on aspects of disease progression in PD.

METHODS

We analyzed data from the Tracking Parkinson's study to examine the effects of comorbid T2DM on PD progression and quality of life by comparing symptom severity scores assessing a range of motor and nonmotor symptoms.

RESULTS

We identified 167 (8.7%) patients with PD and T2DM (PD + T2DM) and 1763 (91.3%) patients with PD without T2DM (PD). After controlling for confounders, patients with T2DM had more severe motor symptoms, as assessed by Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part III (25.8 [0.9] vs. 22.5 [0.3] P = 0.002), and nonmotor symptoms, as assessed by Non-Motor Symptoms Scale total (38.4 [2.5] vs. 31.8 [0.7] P < 0.001), and were significantly more likely to report loss of independence (odds ratio, 2.08; 95% confidence interval [CI]: 1.34-3.25; P = 0.001) and depression (odds ratio, 1.62; CI: 1.10-2.39; P = 0.015). Furthermore, over time, patients with T2DM had significantly faster motor symptom progression (P = 0.012), developed worse mood symptoms (P = 0.041), and were more likely to develop substantial gait impairment (hazard ratio, 1.55; CI: 1.07-2.23; P = 0.020) and mild cognitive impairment (hazard ratio, 1.7; CI: 1.24-2.51; P = 0.002) compared with the PD group.

CONCLUSIONS

In the largest study to date, T2DM is associated with faster disease progression in Parkinson's, highlighting an interaction between these two diseases. Because it is a potentially modifiable metabolic state, with multiple peripheral and central targets for intervention, it may represent a target for alleviating parkinsonian symptoms and slowing progression to disability and dementia. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Modulation of Reactive Oxygen Species Homeostasis as a Pleiotropic Effect of Commonly Used Drugs

Age-associated diseases represent a growing burden for global health systems in our aging society. Consequently, we urgently need innovative strategies to counteract these pathological disturbances. Overwhelming generation of reactive oxygen species (ROS) is associated with age-related damage, leading to cellular dysfunction and, ultimately, diseases. However, low-dose ROS act as crucial signaling molecules and inducers of a vaccination-like response to boost antioxidant defense mechanisms, known as mitohormesis. Consequently, modulation of ROS homeostasis by nutrition, exercise, or pharmacological interventions is critical in aging. Numerous nutrients and approved drugs exhibit pleiotropic effects on ROS homeostasis. In the current review, we provide an overview of drugs affecting ROS generation and ROS detoxification and evaluate the potential of these effects to counteract the development and progression of age-related diseases. In case of inflammation-related dysfunctions, cardiovascular- and neurodegenerative diseases, it might be essential to strengthen antioxidant defense mechanisms in advance by low ROS level rises to boost the individual ROS defense mechanisms. In contrast, induction of overwhelming ROS production might be helpful to fight pathogens and kill cancer cells. While we outline the potential of ROS manipulation to counteract age-related dysfunction and diseases, we also raise the question about the proper intervention time and dosage.

The Effect of the Ketogenic Diet on the Therapy of Neurodegenerative Diseases and Its Impact on Improving Cognitive Functions

The ketogenic diet (KD) is a high-fat and low-carbohydrate diet with controlled amounts of protein. The use of drastic caloric restriction or ultralow-carbohydrate diets increases the production of ketone bodies, which are an alternative energy substrate in situations of insufficient glucose supply. Alzheimer's disease (AD) and Parkinson's disease are the most common neurodegenerative diseases in the world. It is believed that carbohydrate metabolism disorders may affect the progression of these diseases, as confirmed by both animal and human studies. Among patients with AD, the presence of ketone bodies in the body can improve cerebral circulation. Among Parkinson's patients, the presence of ketone bodies can reduce muscle tremor and stiffness, as well as improve cognitive function. The results of the research indicate that using a low-carbohydrate diet, including a KD, may have a beneficial effect on brain function in diseases that cause neuronal damage.

Multiple Criteria Optimization (MCO): A gene selection deterministic tool in RStudio

Identifying genes with the largest expression changes (gene selection) to characterize a given condition is a popular first step to drive exploration into molecular mechanisms and is, therefore, paramount for therapeutic development. Reproducibility in the sciences makes it necessary to emphasize objectivity and systematic repeatability in biological and informatics analyses, including gene selection. With these two characteristics in mind, in previous works our research team has proposed using multiple criteria optimization (MCO) in gene selection to analyze microarray datasets. The result of this effort is the MCO algorithm, which selects genes with the largest expression changes without user manipulation of neither informatics nor statistical parameters. Furthermore, the user is not required to choose either a preference structure among multiple measures or a predetermined quantity of genes to be deemed significant a priori. This implies that using the same datasets and performance measures (PMs), the method will converge to the same set of selected differentially expressed genes (repeatability) despite who carries out the analysis (objectivity). The present work describes the development of an open-source tool in RStudio to enable both: (1) individual analysis of single datasets with two or three PMs and (2) meta-analysis with up to five microarray datasets, using one PM from each dataset. The capabilities afforded by the code include license-free portability and the possibility to carry out analyses via modest computer hardware, such as personal laptops. The code provides affordable, repeatable, and objective detection of differentially expressed genes from microarrays. It can be used to analyze other experiments with similar experimental comparative layouts, such as microRNA arrays and protein arrays, among others. As a demonstration of the capabilities of the code, the analysis of four publicly-available microarray datasets related to Parkinson´s Disease (PD) is presented here, treating each dataset individually or as a four-way meta-analysis. These MCO-supported analyses made it possible to identify MMP9 and TUBB2A as potential PD genetic biomarkers based on their persistent appearance across each of the case studies. A literature search confirmed the importance of these genes in PD and indeed as PD biomarkers, which evidences the code´s potential.

Chronic and progressive dopaminergic neuronal death in substantia nigra associates with a decrease in serum levels of glucose and free fatty acids, the role of interlokin-1 beta

Human studies indicate that Parkinson's disease (PD) associates with disruption in metabolism of glucose and free fatty acids (FFA). Studies have shown that interlukin-1beta (IL-1β) causes hypoglycemia through insulin- independent mechanisms. Here, we investigated association between dopaminergic neuronal death, as the main pathophysiological mechanism underlying PD, and serum levels of glucose, FFA and IL-1β in 6-hydroxydopamine (6-OHDA) animal model of PD. Neurotoxin of 6-OHDA was injected into medial forebrain bundle and multiple behavioral testes were carried out during eight weeks thereafter. Blood was collected before the toxin and in second and eight weeks thereafter. Then, brain of the animals was perfused to assess survival of dopaminergic (DAergic) neurons in substantia nigra by tyrosine hydroxylase (TH) immunohistochemistry. Glucose, FFA and IL-1β levels were determined using calorimetric method and specific ELISA kits. In compare to control, 6-OHDA- treated rats had less glucose and FFA levels in the eight week and higher IL-1β level in the both second and eight weeks. Based on severity of behavioral symptoms, 6-OHDA- treated rats were divided into two subgroups of severe and mild. Number of TH- positive cells in these subgroups was 83 and 45% less than that in control. Also, both subgroups showed less weight gain, lower glucose and FFA and higher IL-1β in eight week. Our data indicate that moderate to severe progressive DAergic neuronal death in substantia nigra associates with a decrease in serum levels of glucose and FFA. Increase in IL-1β production following neuronal death possibly mediated this decrease.

Diabetes, insulin and new therapeutic strategies for Parkinson's disease: Focus on glucagon-like peptide-1 receptor agonists

Parkinson's disease and diabetes mellitus are two chronic disorders associated with aging that are becoming increasingly prevalent worldwide. Parkinson is a multifactorial progressive condition with no available disease modifying treatments at the moment. Over the last few years there is growing interest in the relationship between diabetes (and impaired insulin signaling) and neurodegenerative diseases, as well as the possible benefit of antidiabetic treatments as neuroprotectors, even in non-diabetic patients. Insulin regulates essential functions in the brain such as neuronal survival, autophagy of toxic proteins, synaptic plasticity, neurogenesis, oxidative stress and neuroinflammation. We review the existing epidemiological, experimental and clinical evidence that supports the interplay between insulin and neurodegeneration in Parkinson's disease, as well as the role of antidiabetic treatments in this disease.

Cascading from SARS-CoV-2 to Parkinson's Disease through Protein-Protein Interactions

Extensive extrapulmonary damages in a dozen of organs/systems, including the central nervous system (CNS), are reported in patients of the coronavirus disease 2019 (COVID-19). Three cases of Parkinson's disease (PD) have been reported as a direct consequence of COVID-19. In spite of the scarce data for establishing a definitive link between COVID-19 and PD, some hypotheses have been proposed to explain the cases reported. They, however, do not fit well with the clinical findings reported for COVID-19 patients, in general, and for the PD cases reported, in particular. Given the importance of this potential connection, we present here a molecular-level mechanistic hypothesis that explains well these findings and will serve to explore the potential CNS damage in COVID-19 patients. The model explaining the cascade effects from COVID-19 to CNS is developed by using bioinformatic tools. It includes the post-translational modification of host proteins in the lungs by viral proteins, the transport of modified host proteins via exosomes out the lungs, and the disruption of protein-protein interaction in the CNS by these modified host proteins. Our hypothesis is supported by finding 44 proteins significantly expressed in the CNS which are associated with PD and whose interactions can be perturbed by 24 host proteins significantly expressed in the lungs. These 24 perturbators are found to interact with viral proteins and to form part of the cargoes of exosomes in human tissues. The joint set of perturbators and PD-vulnerable proteins form a tightly connected network with significantly more connections than expected by selecting a random cluster of proteins of similar size from the human proteome. The molecular-level mechanistic hypothesis presented here provides several routes for the cascading of effects from the lungs of COVID-19 patients to PD. In particular, the disruption of autophagy/ubiquitination processes appears as an important mechanism that triggers the generation of large amounts of exosomes containing perturbators in their cargo, which would insult several PD-vulnerable proteins, potentially triggering Parkinsonism in COVID-19 patients.

Diabetes Mellitus is Associated with a Higher Relative Risk for Parkinson’s Disease in Women than in Men

Background: In general, the risk to develop Parkinson’s disease (PD) is higher in men compared to women. Besides male sex and genetics, research suggests diabetes mellitus (DM) is a risk factor for PD as well. Objective: In this population-level study, we aimed at investigating the sex-specific impact of DM on the risk of developing PD. Methods: Medical claims data were analyzed in a cross-sectional study in the Austrian population between 1997 and 2014. In the age group of 40–79 and 80+, 235,268 patients (46.6%females, 53.4%males) with DM were extracted and compared to 1,938,173 non-diabetic controls (51.9%females, 48.1%males) in terms of risk of developing PD. Results: Men with DM had a 1.46 times increased odds ratio (OR) to be diagnosed with PD compared to non-diabetic men (95%CI 1.38–1.54, p < 0.001). The association of DM with newly diagnosed PD was significantly greater in women (OR = 1.71, 95%CI 1.60–1.82, p < 0.001) resulting in a relative risk increase of 1.17 (95%CI 1.11–1.30) in the age group 40 to 79 years. In 80+-year-olds the relative risk increase is 1.09 (95%CI 1.01–1.18). Conclusion: Although men are more prone to develop PD, women see a higher risk increase in PD than men amongst DM patients.

C-reactive protein as a possible marker for severity and mortality of COVID-19 infection

AIM

The present study aimed to introduce a possible biomarker to differentiate between severe and fatal conditions of COVID-19.

BACKGROUND

The COVID-19 pandemic, appearing as a complicated health problem, has changed the lifestyle of people in recent years. Clinical findings indicate mild, severe, and fatal conditions of this disease. Prediction of disease severity is a significant point in managing COVID-19 infection.

METHODS

In this study, 195 differentially expressed genes (DEGs) that discriminate between fatal and severe conditions in patients were extracted from the literature and screened to determine the significant ones. The significant DEGs plus the 90 first neighbors added from the STRING database were included in the interactome using Cytoscape software v 3.7.2. The central nodes of the analyzed network were identified and assessed.

RESULTS

Ten significant DEGs were candidates for assessment, of which 9 were recognized by the STRING database. IL6, ALB, TNF, CRP, INS, MPO, C3, CXCL8, TTR, and TLR4 were determined as central nodes; IL6, CRP, and TTR were highlighted as the critical genes related to the severity of COVID-19 infection.

CONCLUSION

CRP was identified as the best possible biomarker with levels related to the severity and fatality of COVID-19 infection.

Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease

Parkinson's disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.

Diabetes Causes Dysfunctional Dopamine Neurotransmission Favoring Nigrostriatal Degeneration in Mice

BACKGROUND

Numerous studies indicate an association between neurodegenerative and metabolic diseases. Although still a matter of debate, growing evidence from epidemiological and animal studies indicate that preexisting diabetes increases the risk to develop Parkinson's disease. However, the mechanisms of such an association are unknown.

OBJECTIVES

We investigated whether diabetes alters striatal dopamine neurotransmission and assessed the vulnerability of nigrostriatal neurons to neurodegeneration.

METHODS

We used streptozotocin-treated and genetically diabetic db/db mice. Expression of oxidative stress and nigrostriatal neuronal markers and levels of dopamine and its metabolites were monitored. Dopamine release and uptake were assessed using fast-scan cyclic voltammetry. 6-Hydroxydopamine was unilaterally injected into the striatum using stereotaxic surgery. Motor performance was scored using specific tests.

RESULTS

Diabetes resulted in oxidative stress and decreased levels of dopamine and its metabolites in the striatum. Levels of proteins regulating dopamine release and uptake, including the dopamine transporter, the Girk2 potassium channel, the vesicular monoamine transporter 2, and the presynaptic vesicle protein synaptobrevin-2, were decreased in diabetic mice. Electrically evoked levels of extracellular dopamine in the striatum were enhanced, and altered dopamine uptake was observed. Striatal microinjections of a subthreshold dose of the neurotoxin 6-hydroxydopamine in diabetic mice, insufficient to cause motor alterations in nondiabetic animals, resulted in motor impairment, higher loss of striatal dopaminergic axons, and decreased neuronal cell bodies in the substantia nigra.

CONCLUSIONS

Our results indicate that diabetes promotes striatal oxidative stress, alters dopamine neurotransmission, and increases vulnerability to neurodegenerative damage leading to motor impairment. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Association Between Glycemic Status and the Risk of Parkinson Disease: A Nationwide Population-Based Study

OBJECTIVE

Previous studies have suggested that diabetes increases the risk of Parkinson disease (PD); however, this has not been conclusively established. We analyzed the risk of PD based on baseline glucose tolerance status in a large-scale cohort representative of the general Korean population.

RESEARCH DESIGN AND METHODS

This analysis was performed in a cohort of 15,168,021 adults aged ≥40 years who underwent health checkups under the National Health Insurance Service between January 2009 and December 2010. The clinical course of subjects was monitored until December 2016. Subjects were classified into the following groups: no diabetes, impaired fasting glucose (IFG), diabetes duration <5 years, and diabetes duration ≥5 years. We analyzed the adjusted hazard ratio of PD for each group.

RESULTS

During the observation period of 49,076,148.74 person-years, PD occurred in 31,577 patients. Compared with the nondiabetes group, the adjusted hazard ratio was 1.038 (95% CI, 1.009-1.067) in the IFG group, 1.185 (95% CI, 1.143-1.229) in the diabetes duration <5 years group, and 1.618 (95% CI, 1.566-1.672) in the diabetes duration ≥5 years group. These results were consistent with those of the subgroup analysis, and the presence of diabetes further increased the risk of PD regardless of comorbidities such as cardiovascular, cerebrovascular, and chronic kidney diseases.

CONCLUSIONS

This population-based cohort study suggests that diabetes is an independent risk factor for PD.

Antidiabetic drugs for Alzheimer's and Parkinson's diseases: Repurposing insulin, metformin, and thiazolidinediones

Medical and scientific communities have been striving to disentangle the complexity of neurodegenerative diseases, particularly Alzheimer's disease (AD) and Parkinson's disease (PD), in order to develop a cure or effective treatment for these diseases. Along this journey, it has become important to identify the early events occurring in the prodromal phases of these diseases and the disorders that increase the risk of neurodegeneration highlighting common pathological features. This strategy has led to a wealth of evidence identifying diabetes, mainly type 2 diabetes mellitus (T2DM) as a main risk factor for the onset and progression of AD and PD. Impaired glucose metabolism, insulin resistance, and mitochondrial dysfunction are features common to both type 2 diabetes mellitus (T2DM), and AD and PD, and they appear before clinical diagnosis of the two neurodegenerative diseases. These could represent the strategic nodes of therapeutic intervention. Following this line of thought, a conceivable approach is to repurpose antidiabetic drugs as valuable agents that may prevent or reduce the risk of cognitive decline and neurodegeneration. This review summarizes the past and current findings that link AD and PD with T2DM, emphasizing the common pathological mechanisms. The efficacy of antidiabetic drugs, namely intranasal insulin, metformin, and thiazolidinediones, in the prevention and/or treatment of AD and PD is also discussed.

Lipid Metabolism is the common pathologic mechanism between Type 2 Diabetes Mellitus and Parkinson's disease

Although increasing evidence has suggested crosstalk between Parkinson's disease (PD) and type 2 diabetes mellitus (T2DM), the common mechanisms between the two diseases remain unclear. The aim of our study was to characterize the interconnection between T2DM and PD by exploring their shared biological pathways and convergent molecules. The intersections among the differentially expressed genes (DEGs) in the T2DM dataset GSE95849 and PD dataset GSE6613 from the Gene Expression Omnibus (GEO) database were identified as the communal DEGs between the two diseases. Then, an enrichment analysis, protein-protein interaction (PPI) network analysis, correlation analysis, and transcription factor-target regulatory network analysis were performed for the communal DEGs. As a result, 113 communal DEGs were found between PD and T2DM. They were enriched in lipid metabolism, including protein modifications that regulate metabolism, lipid synthesis and decomposition, and the biological effects of lipid products. All these pathways and their biological processes play important roles in both diseases. Fifteen hub genes identified from the PPI network could be core molecules. Their function annotations also focused on lipid metabolism. According to the correlation analysis and the regulatory network analysis based on the 15 hub genes, Sp1 transcription factor (SP1) could be a key molecule since it affected other hub genes that participate in the common mechanisms between PD and T2DM. In conclusion, our analyses reveal that changes in lipid metabolism could be a key intersection between PD and T2DM, and that SP1 could be a key molecule regulating these processes. Our findings provide novel points for the association between PD and T2DM.

Shared (epi)genomic background connecting neurodegenerative diseases and type 2 diabetes

The progressive aging of populations has resulted in an increased prevalence of chronic pathologies, especially of metabolic, neurodegenerative and movement disorders. In particular, type 2 diabetes (T2D), Alzheimer’s disease (AD) and Parkinson’s disease (PD) are among the most prevalent age-related, multifactorial pathologies that deserve particular attention, given their dramatic impact on patient quality of life, their economic and social burden as well the etiopathogenetic mechanisms, which may overlap in some cases. Indeed, the existence of common triggering factors reflects the contribution of mutual genetic, epigenetic and environmental features in the etiopathogenetic mechanisms underlying T2D and AD/PD. On this subject, this review will summarize the shared (epi)genomic features that characterize these complex pathologies. In particular, genetic variants and gene expression profiles associated with T2D and AD/PD will be discussed as possible contributors to determine the susceptibility and progression to these disorders. Moreover, potential shared epigenetic modifications and factors among T2D, AD and PD will also be illustrated. Overall, this review shows that findings from genomic studies still deserves further research to evaluate and identify genetic factors that directly contribute to the shared etiopathogenesis. Moreover, a common epigenetic background still needs to be investigated and characterized. The evidences discussed in this review underline the importance of integrating large-scale (epi)genomic data with additional molecular information and clinical and social background in order to finely dissect the complex etiopathogenic networks that build up the “disease interactome” characterizing T2D, AD and PD.

Diet in Parkinson's Disease: Critical Role for the Microbiome

Background: Parkinson's disease (PD) is the most common movement disorder affecting up to 1% of the population above the age of 60 and 4–5% of those above the age of 85. Little progress has been made on efforts to prevent disease development or halt disease progression. Diet has emerged as a potential factor that may prevent the development or slow the progression of PD. In this review, we discuss evidence for a role for the intestinal microbiome in PD and how diet-associated changes in the microbiome may be a viable approach to prevent or modify disease progression.

Methods: We reviewed studies demonstrating that dietary components/foods were related to risk for PD. We reviewed evidence for the dysregulated intestinal microbiome in PD patients including abnormal shifts in the intestinal microbiota composition (i.e., dysbiosis) characterized by a loss of short chain fatty acid (SCFA) bacteria and increased lipopolysaccharide (LPS) bacteria. We also examined several candidate mechanisms by which the microbiota can influence PD including the NLRP3 inflammasome, insulin resistance, mitochondrial function, vagal nerve signaling.

Results: The PD-associated microbiome is associated with decreased production of SCFA and increased LPS and it is believed that these changes may contribute to the development or exacerbation of PD. Diet robustly impacts the intestinal microbiome and the Western diet is associated with increased risk for PD whereas the Mediterranean diet (including high intake of dietary fiber) decreases PD risk. Mechanistically this may be the consequence of changes in the relative abundance of SCFA-producing or LPS-containing bacteria in the intestinal microbiome with effects on intestinal barrier function, endotoxemia (i.e., systemic LPS), NLRP3 inflammasome activation, insulin resistance, and mitochondrial dysfunction, and the production of factors such as glucagon like peptide 1 (GLP-1) and brain derived neurotrophic factor (BDNF) as well as intestinal gluconeogenesis.

Conclusions: This review summarizes a model of microbiota-gut-brain-axis regulation of neuroinflammation in PD including several new mechanisms. We conclude with the need for clinical trials in PD patients to test this model for beneficial effects of Mediterranean based high fiber diets.

Transcriptomic and Network Analysis Highlight the Association of Diabetes at Different Stages of Alzheimer's Disease

Alzheimer's disease (AD) and type 2 diabetes (T2D) are among the most prevalent chronic diseases affecting the aging population. Extensive research evidence indicates that T2D is a well-established risk factor for AD; however, the molecular mechanisms underlying this association have not been fully elucidated. Furthermore, how T2D may contribute to the progression of AD is a subject of extensive investigation. In this study, we compared the blood transcriptome of patients with mild cognitive impairment (MCI), AD, and advanced AD to those afflicted with T2D to unveil shared and unique pathways and potential therapeutic targets. Blood transcriptomic analyses revealed a positive correlation between gene expression profiles of MCI, AD, and T2D in seven independent microarrays. Interestingly, gene expression profiles from women with advanced AD correlated negatively with T2D, suggesting sex-specific differences in T2D as a risk factor for AD. Network and pathway analysis revealed that shared molecular networks between MCI and T2D were predominantly enriched in inflammation and infectious diseases whereas those networks shared between overt AD and T2D were involved in the phosphatidylinositol 3-kinase and protein kinase B/Akt (PI3K-AKT) signaling pathway, a major mediator of insulin signaling in the body. The PI3K-AKT signaling pathway became more significantly dysregulated in the advanced AD and T2D shared network. Furthermore, endocrine resistance and atherosclerosis pathways emerged as dysregulated pathways in the advanced AD and T2D shared network. Interestingly, network analysis of shared differentially expressed genes between children with T2D and MCI subjects identified forkhead box O3 (FOXO3) as a central transcriptional regulator, suggesting that it may be a potential therapeutic target for early intervention in AD. Collectively, these results suggest that T2D may be implicated at different stages of AD through different molecular pathways disrupted during the preclinical phase of AD and more advanced stages of the disease.

Repurposing anti-diabetic drugs for the treatment of Parkinson's disease: Rationale and clinical experience

The most pressing need in Parkinson's disease (PD) clinical practice is to identify agents that might slow down, stop or reverse the neurodegenerative process of Parkinson's disease and therefore avoid the onset of the most disabling, dopa-refractory symptoms of the disease. These include dementia, speech and swallowing problems, poor balance and falling. To date, there have been no agents which have yet had robust trial data to confirm positive effects at slowing down the neurodegenerative disease process of PD. In this chapter we will review the reasons why there is growing interest in drugs currently licensed for the treatment of diabetes as agents which may slow down disease progression in PD, including a review of the published trials regarding exenatide, a GLP-1 receptor agonist licensed to treat type 2 diabetes, and recently shown to be associated with reduced severity of PD in a randomized, placebo controlled washout design trial of 60 patients treated for 48 weeks. This subject is now a major area of interest for multiple pharmaceutical companies hoping to bring GLP-1 receptor agonists forward as treatment options in PD.

Analysis of the Relationship between Type II Diabetes Mellitus and Parkinson's Disease: A Systematic Review

In the early sixties, a discussion started regarding the association between Parkinson's disease (PD) and type II diabetes mellitus (T2DM). Today, this potential relationship is still a matter of debate. This review aims to analyze both diseases concerning causal relationships and treatments. A total of 104 articles were found, and studies on animal and “in vitro” models showed that T2DM causes neurological alterations that may be associated with PD, such as deregulation of the dopaminergic system, a decrease in the expression of peroxisome proliferator-activated receptor-gamma coactivator-1α (PGC-1α), an increase in the expression of phosphoprotein enriched in diabetes/phosphoprotein enriched in astrocytes 15 (PED/PEA-15), and neuroinflammation, as well as acceleration of the formation of alpha-synuclein amyloid fibrils. In addition, clinical studies described that Parkinson's symptoms were notably worse after the onset of T2DM, and seven deregulated genes were identified in the DNA of T2DM and PD patients. Regarding treatment, the action of antidiabetic drugs, especially incretin mimetic agents, seems to confer certain degree of neuroprotection to PD patients. In conclusion, the available evidence on the interaction between T2DM and PD justifies more robust clinical trials exploring this interaction especially the clinical management of patients with both conditions.

The Relation Between Type 2 Diabetes Mellitus and Parkinson Disease Up to Date

Parkinson’s disease is defined nowadays as a neurodegenerative disease with prominent motor symptoms accompanied by a wide range of comorbidities, some of them, like type 2 diabetes mellitus, probably implicated in the pathogenesis and progression of the disease. In order to achieve this article, which aimed to realize an up to date synthesis of published dedicated papers, a PubMed search was performed; it revealed increasing evidence that these two morbid conditions share many pathogenic pathways and current studies are trying to finally transform the accumulated knowledge into curative therapy or effective prevention for these frequent and complex diseases.

Identification of potential blood biomarkers for Parkinson's disease by gene expression and DNA methylation data integration analysis

BACKGROUND

Blood-based gene expression or epigenetic biomarkers of Parkinson's disease (PD) are highly desirable. However, accuracy and specificity need to be improved, and methods for the integration of gene expression with epigenetic data need to be developed in order to make this feasible.

METHODS

Whole blood gene expression data and DNA methylation data were downloaded from Gene Expression Omnibus (GEO) database. A linear model was used to identify significantly differentially expressed genes (DEGs) and differentially methylated genes (DMGs) according to specific gene regions 5'-C-phosphate-G-3' (CpGs) or all gene regions CpGs in PD. Gene set enrichment analysis was then applied to DEGs and DMGs. Subsequently, data integration analysis was performed to identify robust PD-associated blood biomarkers. Finally, the random forest algorithm and a leave-one-out cross validation method were performed to construct classifiers based on gene expression data integrated with methylation data.

RESULTS

Eighty-five (85) significantly hypo-methylated and upregulated genes in PD patients compared to healthy controls were identified. The dominant hypo-methylated regions of these genes were significantly different. Some genes had a single dominant hypo-methylated region, while others had multiple dominant hypo-methylated regions. One gene expression classifier and two gene methylation classifiers based on all or dominant methylation-altered region CpGs were constructed. All have a good prediction power for PD.

CONCLUSIONS

Gene expression and methylation data integration analysis identified a blood-based 53-gene signature, which could be applied as a biomarker for PD.

Effects of endurance training on hippocampus DJ-1, cannabinoid receptor type 2 and blood glucose concentration in diabetic rats

AIMS/INTRODUCTION

To investigate the effect of endurance training on hippocampus DJ-1 and cannabinoid receptor type 2 (CB2 ) protein and blood glucose concentration in diabetic rats.

MATERIALS AND METHODS

A total of 32 rats were randomly divided into diabetic (D), diabetic and exercise (DE), exercise (E) and control (C) groups. The endurance training was carried out five times per week for 6 weeks. The hippocampus DJ-1 and CB2 were measured using an enzyme-linked immunosorbent assay method.

RESULTS

The level of DJ-1 in the D group was significantly higher than the other groups (P ≤ 0.01). However, the level of DJ-1 was not significantly different between the C, E and DE groups. In addition, the level of CB2 was significantly lower in the D group compared with the other groups (P ≤ 0.01). Blood glucose was significantly higher in the D group compared with the DE group (P ≤ 0.05). Furthermore, a significant positive correlation between the level of DJ-1 and blood glucose was observed (r = 0.67, P ≤ 0.001). There was also a significant inverse correlation between the level of CB2 and blood glucose (r = -0.77, P ≤ 0.001).

CONCLUSIONS

The results of this study suggest that the level of DJ-1 and CB2 might change in response to diabetes, and regular aerobic exercise could mediate the effect of DJ-1 and CB2 on diabetes-induced neurodegenerative diseases.

Novel Treatment Opportunities Against Cognitive Impairment in Parkinson's Disease with an Emphasis on Diabetes-Related Pathways

Cognitive impairment is highly prevalent in patients with Parkinson's disease (PD) and causes adverse health outcomes. Novel procognitive therapies are needed to address this unmet need. It is now established that there is an increased risk of dementia in patients with type 2 diabetes mellitus (T2DM) and, moreover, T2DM and PD may have common underlying biological mechanisms. As such, T2DM medications are emerging as potential therapies in the context of PD dementia (PDD). In this review, we provide an update on pathophysiological mechanisms underlying cognitive impairments and PDD, focusing on diabetes-related pathways. Finally, we have conducted a review of ongoing clinical trials in PD patients with dementia, highlighting the multiple pharmacological mechanisms that are targeted to achieve cognitive enhancement.

Computational systems biology approaches for Parkinson's disease

Parkinson's disease (PD) is a prime example of a complex and heterogeneous disorder, characterized by multifaceted and varied motor- and non-motor symptoms and different possible interplays of genetic and environmental risk factors. While investigations of individual PD-causing mutations and risk factors in isolation are providing important insights to improve our understanding of the molecular mechanisms behind PD, there is a growing consensus that a more complete understanding of these mechanisms will require an integrative modeling of multifactorial disease-associated perturbations in molecular networks. Identifying and interpreting the combinatorial effects of multiple PD-associated molecular changes may pave the way towards an earlier and reliable diagnosis and more effective therapeutic interventions. This review provides an overview of computational systems biology approaches developed in recent years to study multifactorial molecular alterations in complex disorders, with a focus on PD research applications. Strengths and weaknesses of different cellular pathway and network analyses, and multivariate machine learning techniques for investigating PD-related omics data are discussed, and strategies proposed to exploit the synergies of multiple biological knowledge and data sources. A final outlook provides an overview of specific challenges and possible next steps for translating systems biology findings in PD to new omics-based diagnostic tools and targeted, drug-based therapeutic approaches.

Association between diabetes and subsequent Parkinson disease: A record-linkage cohort study

OBJECTIVE

To investigate the association between type 2 diabetes mellitus (T2DM) and subsequent Parkinson disease (PD).

METHODS

Linked English national Hospital Episode Statistics and mortality data (1999-2011) were used to conduct a retrospective cohort study. A cohort of individuals admitted for hospital care with a coded diagnosis of T2DM was constructed, and compared to a reference cohort. Subsequent PD risk was estimated using Cox regression models. Individuals with a coded diagnosis of cerebrovascular disease, vascular parkinsonism, drug-induced parkinsonism, and normal pressure hydrocephalus were excluded from the analysis.

RESULTS

A total of 2,017,115 individuals entered the T2DM cohort and 6,173,208 entered the reference cohort. There were significantly elevated rates of PD following T2DM (hazard ratio [HR] 1.32, 95% confidence interval [CI] 1.29-1.35; p < 0.001). The relative increase was greater in those with complicated T2DM (HR 1.49, 95% CI 1.42-1.56) and when comparing younger individuals (HR 3.81, 95% CI 2.84-5.11 in age group 25-44 years).

CONCLUSIONS

We report an increased rate of subsequent PD following T2DM in this large cohort study. These findings may reflect shared genetic predisposition and/or disrupted shared pathogenic pathways with potential clinical and therapeutic implications.

Evaluation of RNA Blood Biomarkers in the Parkinson's Disease Biomarkers Program

There is a high misdiagnosis rate between Parkinson’s disease (PD) and atypical parkinsonian disorders (APD), such as progressive supranuclear palsy (PSP), the second most common parkinsonian syndrome. In our earlier studies, we identified and replicated RNA blood biomarkers in several independent cohorts, however, replication in a cohort that includes PSP patients has not yet been performed. To this end, we evaluated the diagnostic potential of nine previously identified RNA biomarkers using quantitative PCR assays in 138 blood samples at baseline from PD, PSP and healthy controls (HCs) nested in the PD Biomarkers Program. Linear discriminant analysis showed that COPZ1 and PTPN1 distinguished PD from PSP patients with 62.5% accuracy. Five biomarkers, PTPN1, COPZ1, FAXDC2, SLC14A1s and NAMPT were useful for distinguishing PSP from controls with 69% accuracy. Several biomarkers correlated with clinical features in PD patients. SLC14A1-s correlated with Unified Parkinson’s Disease Rating Scale total and part III scores. In addition, COPZ1, PTPN1 and MLST8, correlated with Montreal Cognitive Assessment (MoCA). Interestingly, COPZ1, EFTUD2 and PTPN1 were downregulated in cognitively impaired (CI) compared to normal subjects. Linear discriminant analysis showed that age, PTPN1, COPZ1, FAXDC2, EFTUD2 and MLST8 distinguished CI from normal subjects with 65.9% accuracy. These results suggest that COPZ1 and PTPN1 are useful for distinguishing PD from PSP patients. In addition, the combination of PTPN1, COPZ1, FAXDC2, EFTUD2 and MLST8 is a useful signature for cognitive impairment. Evaluation of these biomarkers in a larger study will be a key to advancing these biomarkers into the clinic.

NHLRC2 variants identified in patients with fibrosis, neurodegeneration, and cerebral angiomatosis (FINCA): characterisation of a novel cerebropulmonary disease

A novel multi-organ disease that is fatal in early childhood was identified in three patients from two non-consanguineous families. These children were born asymptomatic but at the age of 2 months they manifested progressive multi-organ symptoms resembling no previously known disease. The main clinical features included progressive cerebropulmonary symptoms, malabsorption, progressive growth failure, recurrent infections, chronic haemolytic anaemia and transient liver dysfunction. In the affected children, neuropathology revealed increased angiomatosis-like leptomeningeal, cortical and superficial white matter vascularisation and congestion, vacuolar degeneration and myelin loss in white matter, as well as neuronal degeneration. Interstitial fibrosis and previously undescribed granuloma-like lesions were observed in the lungs. Hepatomegaly, steatosis and collagen accumulation were detected in the liver. A whole-exome sequencing of the two unrelated families with the affected children revealed the transmission of two heterozygous variants in the NHL repeat-containing protein 2 (NHLRC2); an amino acid substitution p.Asp148Tyr and a frameshift 2-bp deletion p.Arg201GlyfsTer6. NHLRC2 is highly conserved and expressed in multiple organs and its function is unknown. It contains a thioredoxin-like domain; however, an insulin turbidity assay on human recombinant NHLRC2 showed no thioredoxin activity. In patient-derived fibroblasts, NHLRC2 levels were low, and only p.Asp148Tyr was expressed. Therefore, the allele with the frameshift deletion is likely non-functional. Development of the Nhlrc2 null mouse strain stalled before the morula stage. Morpholino knockdown of nhlrc2 in zebrafish embryos affected the integrity of cells in the midbrain region. This is the first description of a fatal, early-onset disease; we have named it FINCA disease based on the combination of pathological features that include fibrosis, neurodegeneration, and cerebral angiomatosis.

Mitochondrial pyruvate carrier regulates autophagy, inflammation, and neurodegeneration in experimental models of Parkinson's disease

Mitochondrial and autophagic dysfunction as well as neuroinflammation are involved in the pathophysiology of Parkinson's disease (PD). We hypothesized that targeting the mitochondrial pyruvate carrier (MPC), a key controller of cellular metabolism that influences mTOR (mammalian target of rapamycin) activation, might attenuate neurodegeneration of nigral dopaminergic neurons in animal models of PD. To test this, we used MSDC-0160, a compound that specifically targets MPC, to reduce its activity. MSDC-0160 protected against 1-methyl-4-phenylpyridinium (MPP⁺) insult in murine and cultured human midbrain dopamine neurons and in an α-synuclein-based Caenorhabditis elegans model. In 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mice, MSDC-0160 improved locomotor behavior, increased survival of nigral dopaminergic neurons, boosted striatal dopamine levels, and reduced neuroinflammation. Long-term targeting of MPC preserved motor function, rescued the nigrostriatal pathway, and reduced neuroinflammation in the slowly progressive Engrailed1 (En1^+/-) genetic mouse model of PD. Targeting MPC in multiple models resulted in modulation of mitochondrial function and mTOR signaling, with normalization of autophagy and a reduction in glial cell activation. Our work demonstrates that changes in metabolic signaling resulting from targeting MPC were neuroprotective and anti-inflammatory in several PD models, suggesting that MPC may be a useful therapeutic target in PD.

Biological and Clinical Implications of Comorbidities in Parkinson's Disease

A wide spectrum of comorbidities has been associated with Parkinson's disease (PD), a progressive neurodegenerative disease that affects more than seven million people worldwide. Emerging evidence indicates that chronic diseases including diabetes, depression, anemia and cancer may be implicated in the pathogenesis and progression of PD. Recent epidemiological studies suggest that some of these comorbidities may increase the risk of PD and precede the onset of motor symptoms. Further, drugs to treat diabetes and cancer have elicited neuroprotective effects in PD models. Nonetheless, the mechanisms underlying the occurrence of these comorbidities remain elusive. Herein, we discuss the biological and clinical implications of comorbidities in the pathogenesis, progression, and clinical management, with an emphasis on personalized medicine applications for PD.

Common gene-network signature of different neurological disorders and their potential implications to neuroAIDS

The neurological complications of AIDS (neuroAIDS) during the infection of human immunodeficiency virus (HIV) are symptomized by non-specific, multifaceted neurological conditions and therefore, defining a specific diagnosis/treatment mechanism(s) for this neuro-complexity at the molecular level remains elusive. Using an in silico based integrated gene network analysis we discovered that HIV infection shares convergent gene networks with each of twelve neurological disorders selected in this study. Importantly, a common gene network was identified among HIV infection, Alzheimer's disease, Parkinson's disease, multiple sclerosis, and age macular degeneration. An mRNA microarray analysis in HIV-infected monocytes showed significant changes in the expression of several genes of this in silico derived common pathway which suggests the possible physiological relevance of this gene-circuit in driving neuroAIDS condition. Further, this unique gene network was compared with another in silico derived novel, convergent gene network which is shared by seven major neurological disorders (Alzheimer's disease, Parkinson's disease, Multiple Sclerosis, Age Macular Degeneration, Amyotrophic Lateral Sclerosis, Vascular Dementia, and Restless Leg Syndrome). These networks differed in their gene circuits; however, in large, they involved innate immunity signaling pathways, which suggests commonalities in the immunological basis of different neuropathogenesis. The common gene circuits reported here can provide a prospective platform to understand how gene-circuits belonging to other neuro-disorders may be convoluted during real-time neuroAIDS condition and it may elucidate the underlying-and so far unknown-genetic overlap between HIV infection and neuroAIDS risk. Also, it may lead to a new paradigm in understanding disease progression, identifying biomarkers, and developing therapies.

Dissecting the Molecular Mechanisms of Neurodegenerative Diseases through Network Biology

Neurodegenerative diseases are rarely caused by a mutation in a single gene but rather influenced by a combination of genetic, epigenetic and environmental factors. Emerging high-throughput technologies such as RNA sequencing have been instrumental in deciphering the molecular landscape of neurodegenerative diseases, however, the interpretation of such large amounts of data remains a challenge. Network biology has become a powerful platform to integrate multiple omics data to comprehensively explore the molecular networks in the context of health and disease. In this review article, we highlight recent advances in network biology approaches with an emphasis in brain-networks that have provided insights into the molecular mechanisms leading to the most prevalent neurodegenerative diseases including Alzheimer’s (AD), Parkinson’s (PD) and Huntington’s diseases (HD). We discuss how integrative approaches using multi-omics data from different tissues have been valuable for identifying biomarkers and therapeutic targets. In addition, we discuss the challenges the field of network medicine faces toward the translation of network-based findings into clinically actionable tools for personalized medicine applications.

The vicious circle of hypometabolism in neurodegenerative diseases: Ways and mechanisms of metabolic correction

Hypometabolism, characterized by decreased brain glucose consumption, is a common feature of many neurodegenerative diseases. Initial hypometabolic brain state, created by characteristic risk factors, may predispose the brain to acquired epilepsy and sporadic Alzheimer's and Parkinson's diseases, which are the focus of this review. Analysis of available data suggests that deficient glucose metabolism is likely a primary initiating factor for these diseases, and that resulting neuronal dysfunction further promotes the metabolic imbalance, establishing an effective positive feedback loop and a downward spiral of disease progression. Therefore, metabolic correction leading to the normalization of abnormalities in glucose metabolism may be an efficient tool to treat the neurological disorders by counteracting their primary pathological mechanisms. Published and preliminary experimental results on this approach for treating Alzheimer's disease and epilepsy models support the efficacy of metabolic correction, confirming the highly promising nature of the strategy. © 2017 Wiley Periodicals, Inc.

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.

Blood Transcriptomic Meta-analysis Identifies Dysregulation of Hemoglobin and Iron Metabolism in Parkinson' Disease

Disrupted iron metabolism has been implicated in the pathogenesis of Parkinson’s disease (PD), a progressive neurodegenerative disorder that severely affects movement and coordination, yet the molecular mechanisms underlying this association remain unknown. To this end, we performed a transcriptomic meta-analysis of four blood microarrays in PD. We observed a significant downregulation of genes related to hemoglobin including, hemoglobin delta (HBD), alpha hemoglobin stabilizing protein (ASHP), genes implicated in iron metabolism including, solute carrier family 11 member 2 (SLC11A2), ferrochelatase (FECH), and erythrocyte-specific genes including erythrocyte membrane protein (EPB42), and 5′-aminolevulinate synthase 2 (ALAS2). Pathway and network analysis identified enrichment in processes related to mitochondrial membrane, oxygen transport, oxygen and heme binding, hemoglobin complex, erythrocyte development, tetrapyrrole metabolism and the spliceosome. Collectively, we identified a subnetwork of genes in blood that may provide a molecular explanation for the disrupted hemoglobin and iron metabolism in the pathogenesis of PD.

Evaluation of RNA Blood Biomarkers in Individuals at Risk of Parkinson's Disease

BACKGROUND

Substantial progress has been made in the discovery of blood biomarkers for Parkinson's disease (PD), a progressive neurodegenerative disease that affects more than 4 million worldwide. Olfactory dysfunction and dopamine deficits usually precede motor symptoms years before the onset of PD. A readily accessible biomarker useful for identifying patients at risk of PD is expected to accelerate clinical trials.

OBJECTIVE

To evaluate previously identified PD blood RNA biomarkers in a cohort of asymptomatic individuals at risk of PD.

METHODS

Here we tested 16 previously identified PD RNA biomarkers using quantitative PCR assays in a total of 269 blood samples at baseline from hyposmic and normosmic participants enrolled in the Parkinson's Associated Risk Syndrome study.

RESULTS

Expression levels of four biomarkers, SOD2, PKM2, ZNF134, and ZNF160 were negatively correlated with the total Unified Parkinson's Disease Rating Scale, thus suggesting these biomarkers may be useful to stratify patients prior to the onset of motor symptoms. Levels of SOD2 were upregulated in hyposmic males compared to females, whereas levels of PKM2 were upregulated in hyposmic males compared to normosmic males and hyposmic females. Further, levels of SOD2 were upregulated in males with abnormal dopamine transporter (DAT) scans compared to females with abnormal DAT scans.

CONCLUSIONS

These results suggest that some of these biomarkers may be useful for stratification of individuals at risk for PD and that there may be sex differences in the expression of some biomarkers. Future studies in larger longitudinal studies will be key to assessing the validity of these findings.

Integrative transcriptomic meta-analysis of Parkinson's disease and depression identifies NAMPT as a potential blood biomarker for de novo Parkinson's disease

Emerging research indicates that depression could be one of the earliest prodromal symptoms or risk factors associated with the pathogenesis of Parkinson’s disease (PD), the second most common neurodegenerative disorder worldwide, but the mechanisms underlying the association between both diseases remains unknown. Understanding the molecular networks linking these diseases could facilitate the discovery of novel diagnostic and therapeutics. Transcriptomic meta-analysis and network analysis of blood microarrays from untreated patients with PD and depression identified genes enriched in pathways related to the immune system, metabolism of lipids, glucose, fatty acids, nicotinamide, lysosome, insulin signaling and type 1 diabetes. Nicotinamide phosphoribosyltransferase (NAMPT), an adipokine that plays a role in lipid and glucose metabolism, was identified as the most significant dysregulated gene. Relative abundance of NAMPT was upregulated in blood of 99 early stage and drug-naïve PD patients compared to 101 healthy controls (HC) nested in the cross-sectional Parkinson’s Progression Markers Initiative (PPMI). Thus, here we demonstrate that shared molecular networks between PD and depression provide an additional source of biologically relevant biomarkers. Evaluation of NAMPT in a larger prospective longitudinal study including samples from other neurodegenerative diseases, and patients at risk of PD is warranted.

MOLECULAR GENETIC STUDIES OF COMORBIDITY

This review focuses at the problem of the genetic basis of comorbidity. We discuss the concepts and terms relating to combinations of diseases. The guidelines of the study of comorbidity using modern high throughput methods and approaches of genetics, molecular biology and bioinformatics are designated. In this review we present results of studies showing genetic specificity for the combined phenotypes dif-ferent from the isolated disease, we considergene-gene and gene-environment interactions in comorbidity. We also discuss the role of single nucleotide polymorphisms and structural genome variations in the development of comorbidity. Own results of researching shared genes of inversely comorbid diseases like as bronchial asthma and tuberculosis are presented.

Blood Biomarkers Associated with Cognitive Decline in Early Stage and Drug-Naive Parkinson's Disease Patients

Early diagnosis of Parkinson's disease (PD) continues to be a major challenge in the field. The lack of a robust biomarker to detect early stage PD patients has considerably slowed the progress toward the development of potential therapeutic agents. We have previously evaluated several RNA biomarkers in whole blood from participants enrolled in two independent clinical studies. In these studies, PD patients were medicated, thus, expression of these biomarkers in de novo patients remains unknown. To this end, we tested ten RNA biomarkers in blood samples from 99 untreated PD patients and 101 HC nested in the cross-sectional Parkinson's Progression Markers Initiative by quantitative real-time PCR. One biomarker out of ten, COPZ1 trended toward significance (nominal p = 0.009) when adjusting for age, sex, and educational level. Further, COPZ1, EFTUD2 and PTBP1 mRNAs correlated with clinical features in PD patients including the Hoehn and Yahr scale, Movement Disorder Society revision of Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Montreal Cognitive Assessment (MoCA) score. Levels of EFTUD2 and PTBP1 were significantly higher in cognitively normal PD patients (PD-CN) compared to cognitively impaired PD patients (PD-MCI). Interestingly, blood glucose levels were significantly higher in PD and PD-MCI patients (≥ 100 mg/dL, pre-diabetes) compared to HC. Collectively, we report the association of three RNA biomarkers, COPZ1, EFTUD2 and PTBP1 with clinical features including cognitive decline in early drug-naïve PD patients. Further, our results show that drug-naïve PD and PD-MCI patients have glucose levels characteristic of pre-diabetes patients, suggesting that impaired glucose metabolism is an early event in PD. Evaluation of these potential biomarkers in a larger longitudinal study is warranted.

Network-based metaanalysis identifies HNF4A and PTBP1 as longitudinally dynamic biomarkers for Parkinson's disease

Environmental and genetic factors are likely to be involved in the pathogenesis of Parkinson's disease (PD), the second most prevalent neurodegenerative disease among the elderly. Network-based metaanalysis of four independent microarray studies identified the hepatocyte nuclear factor 4 alpha (HNF4A), a transcription factor associated with gluconeogenesis and diabetes, as a central regulatory hub gene up-regulated in blood of PD patients. In parallel, the polypyrimidine tract binding protein 1 (PTBP1), involved in the stabilization and mRNA translation of insulin, was identified as the most down-regulated gene. Quantitative PCR assays revealed that HNF4A and PTBP1 mRNAs were up- and down-regulated, respectively, in blood of 51 PD patients and 45 controls nested in the Diagnostic and Prognostic Biomarkers for Parkinson's Disease. These results were confirmed in blood of 50 PD patients compared with 46 healthy controls nested in the Harvard Biomarker Study. Relative abundance of HNF4A mRNA correlated with the Hoehn and Yahr stage at baseline, suggesting its clinical utility to monitor disease severity. Using both markers, PD patients were classified with 90% sensitivity and 80% specificity. Longitudinal performance analysis demonstrated that relative abundance of HNF4A and PTBP1 mRNAs significantly decreased and increased, respectively, in PD patients during the 3-y follow-up period. The inverse regulation of HNF4A and PTBP1 provides a molecular rationale for the altered insulin signaling observed in PD patients. The longitudinally dynamic biomarkers identified in this study may be useful for monitoring disease-modifying therapies for PD.

Synopsis on the linkage of Alzheimer's and Parkinson's disease with chronic diseases

Neurodegeneration is the progressive loss of neuronal structure and function, which ultimately leads to neurological disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis, and Huntington's disease. Even after the recent significant advances in neurobiology, the above-mentioned disorders continue to haunt the global population. Several studies have suggested the role of specific environmental and genetic risk factors associated with these disorders. However, the exact mechanism associated with the progression of these disorders still needs to be elucidated. In the recent years, sophisticated research has revealed interesting association of prominent neurodegenerative disorders such as AD and PD with chronic diseases such as cancer, diabetes, and cardiovascular diseases. Several common molecular mechanisms such as generation of free radicals, oxidative DNA damage, aberrations in mitochondrial DNA, and dysregulation of apoptosis have been highlighted as possible points of connection. The present review summarizes the possible mechanism of coexistence of AD and PD with other chronic diseases.