NMR Based Metabolomic Study of Serum Biomarkers in Patients With Parkinson's Disease and Atypical Parkinsonian Syndrome

At present, the diagnosis of Parkinsons disease(PD) mainly relies on clinical symptoms and is easily confused with atypical Parkinsonian syndrome(APS) in the early stages. There is an urgent need for reliable biomarkers. This project aims to use metabolomics technology based on proton nuclear magnetic resonance spectroscopy to study the metabolomic characteristics of patients with PD and APS, and preliminarily screen for possible diagnostic biomarkers of PD and APS.

Parkinson,s disease(PD) is the second largest neurodegenerative disease, with a prevalence rate of 1.7% among the population aged 65 and above in China. Approximately 3 million people suffer from this disease. As the disease progresses, the quality of life of patients is seriously affected, causing a significant burden on both families and society. At present, treatment methods cannot reverse or prevent the progression of the disease, which is related to difficulties in early diagnosis and missed opportunities for drug intervention, as well as the lack of developed drugs with disease modifying effects. Research has found that when patients experience clinical motor symptoms such as tremors, it means that at least 50% of dopaminergic neurons are lost, and the dopamine neurotransmitter content in the striatum is reduced by more than 80%. At this time, patients have missed the opportunity for early intervention. Therefore, early diagnosis and intervention of PD have a significant impact on the prognosis of patients. The etiology and pathogenesis of PD are complex and have not yet been fully elucidated. In recent years, research progress in epidemiology, pathophysiology, genomics, proteomics, and other fields has provided important clues for revealing the etiology and pathogenesis of PD. At present, it is believed that PD may be influenced by genes, gut microbiota, diet, lifestyle habits, and different environmental factors. Research on its pathogenesis mainly focuses on oxidative stress, neurotoxicity, central nervous system inflammation and immune response, mitochondrial energy metabolism disorders, and other aspects.

Atypical Parkinsonian syndrome(APS) includes progressive supranuclear palsy (PSP) and multiple system atrophy, MSA, etc, PD and MSA belong to a group of synucleopathies characterized by fibrous aggregation of alpha synuclein in the cytoplasm of selected neuronal and glial cell populations, PSP is a tau protein disease associated with pathological aggregation of microtubule associated tau proteins. The absence of dopaminergic nerves is a common feature of all Parkinsonian syndromes, therefore PD and APS share some common clinical, neuropathological, and genetic features. In the early stages of the disease, due to the overlap of motor and non motor symptoms, The clinical differentiation between PD and APS is difficult. Therefore, searching for biological markers for PD and MSA The clinical diagnosis and differential diagnosis of PSP are of great significance for the research of disease diagnosis and disease modification therapy.

In the past 20 years, The study of biomarkers for PD and APS has always been a hot topic in various fields. Currently, PD biomarkers are divided into three categories: clinical biomarkers, functional neuroimaging biomarkers, and biochemical biomarkers. Clinical biomarkers are divided into non motor symptoms and motor symptom evaluations, but there are fluctuations and overlaps in clinical symptom manifestations, which affect the correct identification and evaluation of diseases and have a certain misdiagnosis rate. Functional neuroimaging includes technologies such as brain PET metabolic imaging, transcranial ultrasound imaging, and magnetic resonance imaging, which are easy to operate but expensive and have low specificity. With the mature application of platforms such as proteomics, genomics, and metabolomics, more and more biochemical markers have emerged. Some scholars believe that the study of biomarkers must be closely related to the etiology and pathogenesis. Therefore, the study of biochemical markers can better reveal the etiology and pathogenesis, becoming an important direction of current research. In recent years, extensive research has been conducted on the pathogenesis of PD through the misfolding aggregation and intercellular transmission of alpha synuclein. The study suggests that the toxicity of alpha synuclein is influenced by its physical and physiological status, genetic mutations, neuroinflammation, and lipid metabolism. The interaction between them may contribute to the pathogenesis of PD. The latest preclinical evidence suggests that the bidirectional communication between gut microbiota dysbiosis and the brain nervous system plays an important role in the metabolism and pathology of PD patients. The metabolome can be considered as the ultimate result of the interaction between gene expression, protein expression, and environment. Metabolomics is considered the omics science that best studies the phenotype and genotype of organisms, as well as the relationship between phenotype and environment. Compared with other omics techniques, metabolomics has become an ideal source for the discovery of biomarkers.

Another important role of metabolomics is to measure a spectrum of metabolic changes caused by disease, drug, and toxin exposure, known as metabolic fingerprints, which can be used to characterize specific categories (health or disease, control or drug treatment, etc.) and determine the overall characteristics that distinguish categories or groups. Therefore, it can be used for diagnosing disease status, prognosis, and monitoring treatment. At present, metabolomics is widely used in molecular and individualized medicine, as well as research based on single-cell and epidemiological populations, metabolic phenotype and metabolomics association studies. Metabolomics techniques are increasingly being applied in the study of central nervous system diseases, such as Alzheimers disease, depression, etc. Currently, PD is considered a multifactorial disease with strong clinical heterogeneity. Some foreign research reports, PD patients experience disturbances in metabolic pathways such as lipid, energy, fatty acid, and amino acid metabolism.The reason for clinical heterogeneity in PD patients may be due to the different pathological and physiological mechanisms among different subtypes of PD. Studies have found that the levels of important molecules (i.e. niacin, cadherin, glucuronic acid) are correlated with the severity of the phenotype, and there may be potential pathological and physiological connections between gut microbiota/metabolites and the subtypes of PD. However, these results still need to be validated in more research. At present, there is relatively little metabolomic research on PD patients in China, especially in the early stage of PD and the metabolomic characteristics of different APS have not been reported. The metabolomics analysis technique to be used in this study is proton nuclear magnetic resonance technology, which is a major metabolomics analysis technique, Compared with other analytical techniques, NMR has the following advantages: 1) Simple pre-treatment of biological samples; 2) Multiple biomarkers can be observed simultaneously, providing complete biological information for disease diagnosis and pathological analysis; 3) Non destructive testing; 4) Can provide both qualitative and semi quantitative information on specific substances in the sample simultaneously; 5) Can achieve high-throughput detection. In metabolomics research, the most widely used method is 1D proton nuclear magnetic resonance spectroscopy with hydrogen nuclei as the detection object.The hydrogen containing compounds in the sample all exhibit nuclear magnetic resonance (NMR) effects, so 1D proton NMR spectroscopy can collect proton signals from each compound in the sample without bias, providing a fingerprint of metabolites.

NMR can analyze various types of biological samples, and cerebrospinal fluid is the preferred choice for PD in vivo studies. However, obtaining cerebrospinal fluid from patients carries associated risks, which reduces the value of cerebrospinal fluid as a routine diagnostic tool. The readily available biological fluids (serum, urine) provide a safer option. Metabolites can cross the blood-brain barrier, therefore serum metabolites are increasingly being used to study potential biomarkers of diseases.

Eligibility Criteria:
Inclusion Criteria:

* 1) MSA and PSP inclusion criteria

  * Age range from 45 to 80 years old;

    1. MSA inclusion criteria
  * Age range from 45 to 80 years old;

    * Meets the Chinese expert consensus on the diagnostic criteria for multiple system atrophy (2017) or the International Society for Parkinson\&#39;s Disease and Movement Disorders (MDS) diagnostic criteria for multiple system atrophy (2022)

      ③ MSA subtype grouping: MSA is divided into MSA-P and MSA-C subtypes based on the severity of initial and/or motor symptoms, with Patients with Parkinson\&#39;s syndrome as the main type are MSA-P, while patients with cerebellar syndrome as the main type are MSA-C.

      (2) PSP inclusion criteria
  * Age range from 45 to 80 years old;

    ② PSP patients who meet the diagnostic criteria for progressive supranuclear palsy in China (2016) or the diagnostic criteria for progressive supranuclear palsy in the International Society for Parkinson\&#39;s Disease and Movement Disorders (MDS) (2017)

    (3) Selection criteria for Parkinson\&#39;s disease case group
  * Age range from 45 to 80 years old;

    * Patients with idiopathic Parkinson\&#39;s disease who meet the diagnostic criteria of the International Committee on Motor Disorders (MDS) for Parkinson\&#39;s disease (2015);

      * Classification criteria for subtypes of Parkinson\&#39;s disease:

        1. Tremor predominant type: According to the MDS-UPDRS score, the ratio of average tremor score to average PIGD score is ≥ 1.15
        2. PIGD type: According to the MDS-UPDRS score, the ratio of average tremor score to average PIGD score is ≤ 0.9

           Exclusion Criteria:
* ① Hereditary Parkinson\&#39;s syndrome, secondary Parkinson\&#39;s syndrome.

  * After deep brain stimulation (DBS) surgery.

    * Have a history of malignant tumors.