Metabolic modeling links gut microbiota to metabolic markers of Parkinson’s disease

Although it is known that the relative abundance of Akkermansia, a bacterial genus commonly associated with health, increases in the gut microbiota of Parkinson's disease (PD) patients, the exact reason for this increase remains unclear. This study was aimed to identify potential changes in Akkermansia within the gut microbiota of PD patients in Türkiye. For this purpose, shotgun metagenomics and a novel Akkermansia genus-specific amplicon sequencing technique was used to investigate the presence of specific Akkermansia strains associated with cognitive impairment (CI) stages in PD and to examine potential genes within these strains. In this context, four gut microbiota samples from Türkiye -three PD with dementia (PDD) and one healthy control without CI (HC)- were analyzed by shotgun metagenomics and metagenome-assembled genomes assigned to Akkermansia genus were reconstructed. Then, a custom database was created by combining these genomes with the Akkermansia genomes in public databases and next generation sequencing (NGS) compatible primers specific to the genus Akkermansia were designed using this database. After optimization of amplification and library preparation steps for genus-specific next generation sequencing, gut microbiota samples from 64 PD patients [32 PDD and 32 PD with mild CI (PD-MCI)] and 26 HCs were analyzed by genus-specific amplicon sequencing. The results revealed the presence of seven strains assigned to Akkermansia muciniphila in gut microbiota samples, two of which showed significant distribution differences (p< 0.05) between demented (PDD) and non-demented groups (PD-MCI, HC). When gene contents of the detected Akkermansia genomes were examined through comparative genomic analysis, the presence of 12 genes only in Akkermansia genomes specific to non-demented groups were predicted. The annotations of these genes showed that they were not reported before with unknown functions. In this study, for the first time, gut microbiota samples from PD patients in Türkiye were analyzed using shotgun metagenomics, a novel genus-specific amplicon sequencing method was developed specifically for the analysis of Akkermansia genus, and then Akkermansia strains and genes potentially associated with CI stages in PD were identified using this method. The results underscore that investigating the species or strain level differences could help better understanding of the changes associated with PD in the human gut microbiota.

Recent human and animal studies have found associations between gut microbiota composition and serum levels of sex hormones, indicating that they could be an important factor in shaping the microbiota. However, little is known about the effect of regular hormonal fluctuations over the menstrual cycle or CHC-related changes of hormone levels on gut microbiota structure, diversity and dynamics. The aim of this study was to investigate the effect of CHCs on human gut microbiota composition. The effect of CHC pill intake on gut microbiota composition was studied in a group of 7 healthy pre-menopausal women using the CHC pill, compared to the control group of 9 age-matched healthy women that have not used hormonal contraceptives in the six months prior the start of the study. By analyzing the gut microbiota composition in both groups during one menstrual cycle, we found that CHC usage is associated with a minor decrease in gut microbiota diversity and differences in the abundance of several bacterial taxa. These results call for further investigation of the mechanisms underlying hormonal and hormonal contraceptive-related changes of the gut microbiota and the potential implications of these changes for women's health. This article is protected by copyright. All rights reserved.

Over the past two decades, the development of functional imaging methods has greatly promoted our understanding on the changes of neurons following neurodegenerative disorders, such as Parkinson's disease (PD). The application of a spatial covariance analysis on 18F-FDG PET imaging has led to the identification of a distinctive disease-related metabolic pattern. This pattern has proven to be useful in clinical diagnosis, disease progression monitoring as well as assessment of the neuronal changes before and after clinical treatment. It may potentially serve as an objective biomarker on disease progression monitoring, assessment, histological and functional evaluation of related diseases. PD is one of the most common neurodegenerative disorders in the elderly. It is characterized by progressive loss of dopamine neurons in the substantia nigra pars compacta. Throughout the course of disease, the most obvious symptoms are movement-related, such as resting tremor, muscle rigidity, hypokinesia and postural instability (Worth, 2013). Currently, a definite diagnosis of PD is made by clinical evaluation with at least 2 years of follow-up (Hughes et al., 2002; Bhidayasiri and Reichmann, 2013), due to the overlap of motor symptoms between early PD and atypical parkinsonism including multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). However, this classic diagnostic criterion does not benefit the early diagnosis of disease. The prognostic outcome and treatment option are substantially different between PD and atypical parkinsonism. Thus it is critical to develop biomarkers for earlier and more accurate diagnosis of PD. Generally, appropriate diagnostic biomarker for PD ought to cover several key characteristics: (i) minimal invasiveness to detect the biomarker in easily accessible body tissue or fluids, (ii) excellent sensitivity to explore the patients with PD, (iii) high specificity to prevent false-positive results in PD-free individuals, and (iv) robustness against potential affecting factors. A PD-related spatial covariance pattern (PDRP) with quantifiable expression on 18F-FDG PET imaging has been gradually detected using a spatial covariance method during the last two decades and it has been demonstrated to be the right diagnostic biomarker for PD (Eidelberg et al., 1994). PDRP has proven not only to be effective in early discrimination of PD from atypical parkinsonian disorders, but also to be able to assess the disease progression and treatment response. Thus it is considered as a multifunctional biomarker. In this review, we aim to provide an overview of the development in pattern-based biomarker for PD.

Increasing evidence has shown that gut dysbacteriosis may play a crucial role in neuroinflammation in Parkinson's disease (PD). However, the specific mechanisms that link gut microbiota to PD remain unexplored. Given the critical roles of blood-brain barrier (BBB) dysfunction and mitochondrial dysfunction in the development of PD, we aimed to evaluate the interactions among the gut microbiota, BBB, and mitochondrial resistance to oxidation and inflammation in PD. We investigated the effects of fecal microbiota transplantation (FMT) on the physiopathology of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mice. The aim was to explore the role of fecal microbiota from PD patients and healthy human controls in neuroinflammation, BBB components, and mitochondrial antioxidative capacity via the AMPK/SOD2 pathway. Compared to control mice, MPTP-treated mice exhibited elevated levels of Desulfovibrio, whereas mice given FMT from PD patients exhibited enriched levels of Akkermansia and mice given FMT from healthy humans showed no significant alterations in gut microbiota. Strikingly, FMT from PD patients to MPTP-treated mice significantly aggravated motor impairments, dopaminergic neurodegeneration, nigrostriatal glial activation and colonic inflammation, and inhibited the AMPK/SOD2 signaling pathway. However, FMT from healthy human controls greatly improved the aforementioned MPTP-caused effects. Surprisingly, the MPTP-treated mice displayed a significant loss in nigrostriatal pericytes, which was restored by FMT from healthy human controls. Our findings demonstrate that FMT from healthy human controls can correct gut dysbacteriosis and ameliorate neurodegeneration in the MPTP-induced PD mouse model by suppressing microgliosis and astrogliosis, ameliorating mitochondrial impairments via the AMPK/SOD2 pathway, and restoring the loss of nigrostriatal pericytes and BBB integrity. These findings raise the possibility that the alteration in the human gut microbiota may be a risk factor for PD and provide evidence for potential application of FMT in PD preclinical treatment.

IntroductionRecent studies demonstrated that the gut microbiome of Parkinson's Disease (PD) patients differs from that of age-matched healthy controls. Notably less butyrate-producing bacteria and low mucosal and fecal short chain fatty acid (SCFA) concentrations were found in PD patients. SCFA play a role in the interplay of health and disease: SCFA butyrate improves colon motility, protects the colonic epithelium and reduces inflammation. Administration of butyrate in animal models of PD improved motor impairment and dopamine deficiency and reduced early mortality. We hypothesize that certain orally supplemented dietary fibers can stimulate butyrate production in the colon of Parkinson's patients, and consequently can improve the motor impairment and their quality of life. This hypothesis still requires a step-wise approach. Our objective is to investigate the effect of different types of dietary fiber on the gut microbiota and SCFA production in PD patients and healthy elderly.Material and methodsPD patients and healthy controls (HC) were selected based on age (55–70 years old) and BMI (18.5 -25 kg/m2). For PD patients the Hoehn and Yahr score (I – III) was added to this selection. The effect of inulin varying in degree of polymerization (DP) (average DP ~10 vs. average DP ~23) on the SCFA production was evaluated by ex vivo fermentation experiments with fecal samples of PD patients and HC. Inulin (1% w/v) was incubated in small-scale batch fermentations for 24 h at 37°C in anaerobic conditions. SCFA production was analyzed by solid phase micro-extraction capillary gas chromatography-mass spectrometry detection (SPME-cGS-MS). The clostridia clusters IV and XIVa were quantified through 16s qPCR.Results and discussionShort chain (Sc) and long chain(Lc) inulin fermentation resulted in a mean total SCFA increase of respectively 490.3 ± 128.2μmol/ml and 384.3 ± 85.9μmol/ml in HC (n = 7) and 453.9 ± 99.2μmol/ml and 402.9μmol/ml ± 84.1μmol/ml in PD patients (n = 3). Sc inulin fermentation increased butyrate production with 200.0μg/ml ± 46.2μmol/ml in HC and 119.8 ± 94.4μg/ml in PD patients (p = 0.09). Lc inulin fermentation increased butyrate production with 174.9μmol/ml ± 82.2μmol/ml and 113.3μmol/ml ± 21.2μmol/ml in HC and PD patients, respectively (p = 0.25). Large variation between samples was observed in PD patients.ConclusionAlthough sample size is relatively small and data is still collected, we can conclude that both Sc and Lc inulin increase total SCFA and butyrate production in HC and PD patients. This ex vivo study shows that stimulation of the butyrate production is still possible in PD patients and could be beneficial.

2021 Workshop: Neurodegenerative Diseases in the Gut-Brain Axis—Parkinson's Disease

There had been extensive research on the role of the gut microbiota in human health and disease. Increasing evidence suggested that the gut-brain axis played a crucial role in Parkinson's disease, with changes in the gut microbiota speculated to be involved in the pathogenesis of Parkinson's disease or interfere with its treatment. However, studies utilizing deep learning methods to predict Parkinson's disease through the gut microbiota were still limited. Therefore, the goal of this study was to develop an efficient and accurate prediction method based on deep learning by thoroughly analyzing gut microbiota data to achieve the diagnosis of Parkinson's disease. This study proposed a method for predicting Parkinson's disease using differential gut microbiota, named the Parkinson Gut Prediction Method (PGPM). Initially, differential gut microbiota data were extracted from 39 Parkinson's disease (PD) patients and their corresponding 39 healthy spouses. Subsequently, a preprocessing method called CRFS (combined ranking using random forest scores and principal component analysis contributions) was introduced for feature selection. Following this, the proposed LSIM (LSTM-penultimate to SVM Input Method) approach was utilized for classifying Parkinson's patients. Finally, a soft voting mechanism was employed to predict Parkinson's disease patients. The research results demonstrated that the Parkinson gut prediction method (PGPM), which utilized differential gut microbiota, performed excellently. The method achieved a mean accuracy (ACC) of 0.85, an area under the curve (AUC) of 0.92, and a receiver operating characteristic (ROC) score of 0.92. In summary, this method demonstrated excellent performance in predicting Parkinson's disease, allowing for more accurate predictions of Parkinson's disease.

Type 2 diabetes and Parkinson's disease

Background: Transcranial sonography (TCS) is a noninvasive imaging method that practices ultrasound waves to examine the brain structure changes in many neurological pathologies, including Parkinson’s disease (PD) and parkinsonism. It allows for the visualization of the substantia nigra (SN), which is affected in these conditions and other brain parts. This technique has shown promise in aiding the diagnosis, follow-up, and progress of PD, in addition to differentiating it from other movement disorders. Our research explores the reliability of TCS in the diagnosis of PD and its impact on the differential diagnosis of atypical parkinsonism syndromes. Subjects and Methods: This study involved 52 PD patients, nine with other parkinsonism, and 54 healthy people. The same neurosonologist, blind to the patient’s diagnosis, assessed each individual’s SN, and the hyperechogenic area measurement was obtained. These measurements were compared between PD patients, with other forms of PD, and healthy people. In addition, hyperechogenic regions were compared based on the PD subtypes, dominant disease side, severity, and duration of the disease. Results: PD patients were presented with the highest value of SN hyperechogenic regions. TCS had an 87.5% specificity and a 73.3% sensitivity rate for the diagnosis of PD. The akinetic-rigid subtype of PD showed higher hyperechogenicity. In PD patients, there was no correlation between the disease side, length of the disease, Hoehn and Yahr stage, and SN hyperechogenicity. Conclusion: The results of this research demonstrate that the visualizing of SN hyperechogenicity with TCS in PD has diagnostic significance and may be valuable in the differential diagnosis of atypical parkinsonism disorders. However, the evaluation of only the SN may not be sufficient to advantage from TCS in the diagnosis of other parkinsonisms, and it may be essential to investigate the mesencephalon, other basal ganglia, and the third ventricle.

P41. Reoperation, complications and patient reported outcomes in patients with Parkinson's disease undergoing elective spine surgery: a propensity matched analysis

The number of Parkinson's disease (PD) patients increases with aging, which brings heavy burden to families and society. The emergence of patient-derived induced pluripotent stem cells (iPSCs) has brought hope to the current situation of lacking new breakthroughs in diagnosis and treatment of PD. In this article, we reviewed and analyzed the current researches related to PD patient-derived iPSCs, in order to provide solid theoretical basis for future study of PD. In 2008, successful iPSCs derived from PD patients were reported. The current iPSCs research in PD mostly focused on the establishment of specific iPSCs models of PD patients carrying susceptible genes. The main source of PD patient-derived iPSCs is skin fibroblasts and the mainstream reprogramming methodology is the mature "four-factor" method, which introduces four totipotent correlation factors Oct4, Sox2, Klf4 and c-Myc into somatic cells. The main sources of iPSCs are patients with non-pedigrees and there have been no studies involving both PD patients and unaffected carriers within the same family. Most of the existing studies of PD patient-derived iPSCs started with the induction method for obtaining dopaminergic neurons in the first instance, but therapeutic applications are being increased. Although it is not the ultimate panacea, and there are still some unsolved problems (e.g., whether the mutated genes should be corrected or not), a better understanding of iPSCs may be a good gift for both PD patients and doctors due to their advantages in diagnosis and treatment of PD.

The second brain in Parkinson's disease: fact or fantasy?

Objective: Parkinson's disease (PD) patients are known to suffer from pain, anxiety, and depression, but the exact degree of association between the two is unknown. As many PD patients also suffer from physical impairments, this cross-sectional case-control study sets out to compare and determine the case-ness of pain, anxiety and depression in PD patients that suffer with or without symptomatic osteoarthritis (OA). The goal of this study, therefore, was to observe if additional pain associated with comorbid OA in PD patients is correlated with greater depression and anxiety rates. The importance of understanding the burden of pain and increased depression severity of PD and OA patients is so that they may be screened appropriately based on the symptoms, which may increase their overall quality of life.Methods:This cross-sectional case-control study included 3 groups of 34 patients and 78 healthy age and gender-matched control participants. PD patients with symptomatic OA (PD+OA), PD patients without symptomatic OA (PD), patients with symptomatic OA but no PD (OA), and healthy control participants (Control). A PD patient group with Restless Legs Syndrome (PD+RLS) of 27 patients was also included. All participants completed questionnaires to assess for pain, depression, and anxiety.Results:PD+OA and PD patients had worsened depression severity and were more likely to report anxiety and depression case-ness than OA patients. PD+OA patients were more likely to complain about paresthestic and akasthisic pain, but less likely to complain about aching pain compared to PD patients and OA patients. PD+OA patients were more likely to have greater pain severity, and were more likely to report radiating and sharp pain than PD+RLS patients. PD+OA patients were also more likely to report higher depression case-ness than PD+RLS patients.Conclusion:PD with OA seems to be linked with specific pain characteristics (akathisia and paraesthesia) as well as heightened overall pain severity and pain interference in comparison to OA alone, PD alone and PD with RLS. PD is also correlated with depression severity and anxiety case-ness in OA when compared to the OA alone, PD alone and PD with RLS.

This was a retrospective cohort analysis. To identify the impact of Parkinson disease (PD) on 2-year postoperative outcomes following cervical spine surgery (CSS). (PD) patients are prone to spine malalignment and surgical interventions, yet little is known regarding outcomes of CSS among PD patients. All patients from the Statewide Planning and Research Cooperative System with cervical radiculopathy or myelopathy who underwent CSS were included; among these, those with PD were identified. PD and non-PD patients (n=64 each) were 1:1 propensity score-matched by age, sex, race, surgical approach, and Deyo-Charlson Comorbidity Index (DCCI). Demographics, hospital-related parameters, and adverse postoperative outcomes were compared between cohorts. Logistic regression identified predictive factors for outcomes. Overall, patient demographics were comparable between cohorts, except that DCCI was higher in PD patients (1.28 vs. 0.67, P=0.028). PD patients had lengthier mean hospital stays than non-PD patients (6.4 vs. 4.1 d, P=0.046). PD patients also incurred comparable total hospital expenses ($69,565 vs. $57,388, P=0.248). Individual medical complication rates were comparable between cohorts; though PD patients had higher rates of postoperative altered mental status (4.7% vs. 0%, P=0.08) and acute renal failure (10.9% vs. 3.1%, P=0.084), these differences were not significant. Yet, PD patients experienced higher rates of overall medical complications (35.9% vs. 18.8%, P=0.029). PD patients had comparable rates of individual and overall surgical complications. The PD cohort underwent higher reoperation rates (15.6% vs. 7.8%, P=0.169) compared with non-PD patients, though this difference was not significant. Of note, PD was not a significant predictor of overall 2-year complications (odds ratio=1.57, P=0.268) or reoperations (odds ratio=2.03, P=0.251). Overall medical complication rates were higher in patients with PD, while individual medical complications as well as surgical complication and reoperation rates after elective CSS were similar in patients with and without PD, though PD patients required longer hospital stays. Importantly, a baseline diagnosis of PD was not significantly associated with adverse two-year medical and surgical complications. This data may improve counseling and risk-stratification for PD patients before CSS. Level III.

Blood biomarkers associated with cognitive decline in early stage and drug-naive Parkinson's disease patients