Genomic Association Study for Cognitive Impairment in Parkinson's Disease

Sleep disorders cause Parkinson's disease or the reverse is true: Good GABA good night

BACKGROUND

Parkinson's disease (PD) is a progressive neurodegenerative brain disease due to degeneration of dopaminergic neurons (DNs) presented with motor and non-motor symptoms. PD symptoms are developed in response to the disturbance of diverse neurotransmitters including γ-aminobutyric acid (GABA). GABA has a neuroprotective effect against PD neuropathology by protecting DNs in the substantia nigra pars compacta (SNpc). It has been shown that the degeneration of GABAergic neurons is linked with the degeneration of DNs and the progression of motor and non-motor PD symptoms. GABA neurotransmission is a necessary pathway for normal sleep patterns, thus deregulation of GABAergic neurotransmission in PD could be the potential cause of sleep disorders in PD.

AIM

Sleep disorders affect GABA neurotransmission leading to memory and cognitive dysfunction in PD. For example, insomnia and short sleep duration are associated with a reduction of brain GABA levels. Moreover, PD-related disorders including rigidity and nocturia influence sleep patterns leading to fragmented sleep which may also affect PD neuropathology. However, the mechanistic role of GABA in PD neuropathology regarding motor and non-motor symptoms is not fully elucidated. Therefore, this narrative review aims to clarify the mechanistic role of GABA in PD neuropathology mainly in sleep disorders, and how good GABA improves PD. In addition, this review of published articles tries to elucidate how sleep disorders such as insomnia and REM sleep behavior disorder (RBD) affect PD neuropathology and severity. The present review has many limitations including the paucity of prospective studies and most findings are taken from observational and preclinical studies. GABA involvement in the pathogenesis of PD has been recently discussed by recent studies. Therefore, future prospective studies regarding the use of GABA agonists in the management of PD are suggested to observe their distinct effects on motor and non-motor symptoms.

CONCLUSION

There is a bidirectional relationship between the pathogenesis of PD and sleep disorders which might be due to GABA deregulation.

Proxy-analysis of the genetics of cognitive decline in Parkinson's disease through polygenic scores

Cognitive decline is common in Parkinson's disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e-13), cognitive performance (p = 1.46e-12), educational attainment (p = 8.52e-10), and reasoning (p = 3.58e-5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant's cognitive reserve for cognitive outcome in PD.

Genetics in parkinson's disease: From better disease understanding to machine learning based precision medicine

Parkinson's Disease (PD) is a neurodegenerative disorder with highly heterogeneous phenotypes. Accordingly, it has been challenging to robustly identify genetic factors associated with disease risk, prognosis and therapy response via genome-wide association studies (GWAS). In this review we first provide an overview of existing statistical methods to detect associations between genetic variants and the disease phenotypes in existing PD GWAS. Secondly, we discuss the potential of machine learning approaches to better quantify disease phenotypes and to move beyond disease understanding towards a better-personalized treatment of the disease.

Plasma arylsulfatase A levels are associated with cognitive function in Parkinson’s disease

Background

Arylsulfatase A (ARSA), a lysosomal enzyme, has been shown to inhibit the aggregation and propagation of α-synuclein (α-syn) through its molecular chaperone function. The relationship between ARSA levels and Parkinson’s disease (PD) in the Chinese Han population remains controversial, and few quantitative research studies have investigated the relationship between plasma ARSA levels and PD.

Objectives

The purpose of this study was to investigate the relationships between ARSA levels and cognitive function in PD patients and to evaluate the association of ARSA and α-syn levels with nonmotor symptoms.

Methods

Enzyme-linked immunosorbent assay (ELISA) was used to measure the plasma ARSA and α-syn levels in 50 healthy controls, 120 PD patients (61 PD patients with no cognitive impairment (PD-NCI) and 59 PD patients with cognitive impairment (PD-CI)). Motor symptoms and nonmotor symptoms (cognitive function, Unified Parkinson’s Disease Rating Scale (UPDRS) score, depression, anxiety, constipation, olfactory dysfunction, sleep disruption, and other symptoms) were assessed with the relevant scales. The Kruskal–Wallis H test was used for comparison between groups, and Pearson/Spearman analysis was used for correlation analysis.

Results

The plasma ARSA concentrations were lower in the PD-CI group than in the PD-NCI group. The plasma α-syn levels in the PD-CI group were higher than those in the healthy control group, and the plasma ARSA levels were correlated with the Mini-Mental State Examination (MMSE scores) and Hoehn and Yahr (H-Y) stage.

Conclusion

We used a quantitative assessment method to show that low plasma ARSA levels and high α-syn levels are related to cognitive impairment in PD patients. Plasma ARSA levels gradually decrease with PD progression.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

Microarray Genotyping Identifies New Loci Associated with Dementia in Parkinson's Disease

Dementia is one of the most disabling nonmotor symptoms of Parkinson’s disease (PD). However, the risk factors contributing to its development remain unclear. To investigate genetic variants associated with dementia in PD, we performed microarray genotyping based on a customized platform utilizing variants identified in previous genetic studies. Microarray genotyping was performed in 313 PD patients with dementia, 321 PD patients without dementia, and 635 healthy controls. The primary analysis was performed using a multiple logistic regression model adjusted for age and sex. SNCA single nucleotide polymorphism (SNP) rs11931074 was determined to be most significantly associated with PD (odds ratio = 0.66, 95% confidence interval = 0.56–0.78, p = 7.75 × 10⁻⁷). In the analysis performed for patients with PD only, MUL1 SNP rs3738128 (odds ratio = 2.52, 95% confidence interval = 1.68–3.79, p = 8.75 × 10⁻⁶) was found to be most significantly associated with dementia in PD. SNPs in ZHX2 and ERP29 were also associated with dementia in PD. This microarray genomic study identified new loci of MUL1 associated with dementia in PD, suggesting an essential role of mitochondrial dysfunction in the development of dementia in patients with PD.

Endoplasmic Reticulum-Based Calcium Dysfunctions in Synucleinopathies

Neuronal calcium dyshomeostasis has been associated to Parkinson's disease (PD) development based on epidemiological studies on users of calcium channel antagonists and clinical trials are currently conducted exploring the hypothesis of increased calcium influx into neuronal cytosol as basic premise. We reported in 2018 an opposite hypothesis based on the demonstration that α-synuclein aggregates stimulate the endoplasmic reticulum (ER) calcium pump SERCA and demonstrated in cell models the existence of an α-synuclein-aggregate dependent neuronal state wherein cytosolic calcium is decreased due to an increased pumping of calcium into the ER. Inhibiting the SERCA pump protected both neurons and an α-synuclein transgenic C. elegans model. This models two cellular states that could contribute to development of PD. First the prolonged state with reduced cytosolic calcium that could deregulate multiple signaling pathways. Second the disease ER state with increased calcium concentration. We will discuss our hypothesis in the light of recent papers. First, a mechanistic study describing how variation in the Inositol-1,4,5-triphosphate (IP3) kinase B (ITPKB) may explain GWAS studies identifying the ITPKB gene as a protective factor toward PD. Here it was demonstrated that how increased ITPKB activity reduces influx of ER calcium to mitochondria via contact between IP₃-receptors and the mitochondrial calcium uniporter complex in ER-mitochondria contact, known as mitochondria-associated membranes (MAMs). Secondly, it was demonstrated that astrocytes derived from PD patients contain α-synuclein accumulations. A recent study has demonstrated how human astrocytes derived from a few PD patients carrying the LRRK2-2019S mutation express more α-synuclein than control astrocytes, release more calcium from ER upon ryanodine receptor (RyR) stimulation, show changes in ER calcium channels and exhibit a decreased maximal and spare respiration indicating altered mitochondrial function in PD astrocytes. Here, we summarize the previous findings focusing the effect of α-synuclein to SERCA, RyR, IP₃R, MCU subunits and other MAM-related channels. We also consider how the SOCE-related events could contribute to the development of PD.

The role of APOE in cognitive trajectories and motor decline in Parkinson's disease

We aimed to investigate the role of the APOE genotype in cognitive and motor trajectories in Parkinson's disease (PD). Using PD registry data, we retrospectively investigated a total of 253 patients with PD who underwent the Mini-Mental State Exam (MMSE) two or more times at least 5 years apart, were aged over 40 years, and free of dementia at the time of enrollment. We performed group-based trajectory modeling to identify patterns of cognitive change using the MMSE. Kaplan-Meier survival analysis was used to investigate the role of the APOE genotype in cognitive and motor progression. Trajectory analysis divided patients into four groups: early fast decline, fast decline, gradual decline, and stable groups with annual MMSE scores decline of - 2.8, - 1.8, - 0.6, and - 0.1 points per year, respectively. The frequency of APOE ε4 was higher in patients in the early fast decline and fast decline groups (50.0%) than those in the stable group (20.1%) (p = 0.007). APOE ε4, in addition to older age at onset, depressive mood, and higher H&Y stage, was associated with the cognitive decline rate, but no APOE genotype was associated with motor progression. APOE genotype could be used to predict the cognitive trajectory in PD.