We have performed a complete screening of the Parkin gene (PRKN2) and looked for p.Gly2019Ser (G2019S) and p.Arg1441Gly (R1441G) LRRK2/dardarin gene mutations in twenty seven patients with Parkinson’s disease (PD) wi...We have performed a complete screening of the Parkin gene (PRKN2) and looked for p.Gly2019Ser (G2019S) and p.Arg1441Gly (R1441G) LRRK2/dardarin gene mutations in twenty seven patients with Parkinson’s disease (PD) with an age at onset younger than 50 years (EOPD), living in Gipuzkoa (Basque Country, Spain). Thirteen of them (48%) were PRKN2 mutation carriers. The c.255-256DelA mutation was the most frequent, followed by a deletion involving exons 3 and 4. A deletion involving exons 3 and 12 of the PRKN2 gene and R1441G LRRK2 mutation was found together in one PD patient. Four out of fourteen PRKN2 negative patients carried the p.G2019S mutation. Both PRKN2 mutation carriers and non-carriers presented frequently with family history (10 PRKN2 mutation carriers and 8 PRKN2 non-carriers);in fact, five patients without a known gene mutation had a first degree relative affected, suggesting another monogenic disease. PRKN2 carriers presented with a younger age at onset (36.7 vs. 41.7) and more benign disease progression. Indeed, those PD patients younger than forty who initially presented with unilateral tremor became shortly bilateral. Relatively, symmetric parkinsonism and slow disease progression carried more frequently PRKN2 mutations than patients with unilateral akinetic rigid parkinsonism and age at onset later than 40 years. As expected in a recessive disease, PRKN2 patients present more often with affected siblings and unaffected patients. The G2019S LRRK2 mutation, less prevalent than R1441G in our area, may be also a frequent cause of PD in EOPD (4 patients).展开更多
There are many techniques using sensors and wearable devices for detecting and monitoring patients with Parkinson’s disease(PD).A recent development is the utilization of human interaction with computer keyboards for...There are many techniques using sensors and wearable devices for detecting and monitoring patients with Parkinson’s disease(PD).A recent development is the utilization of human interaction with computer keyboards for analyzing and identifying motor signs in the early stages of the disease.Current designs for classification of time series of computer-key hold durations recorded from healthy control and PD subjects require the time series of length to be considerably long.With an attempt to avoid discomfort to participants in performing long physical tasks for data recording,this paper introduces the use of fuzzy recurrence plots of very short time series as input data for the machine training and classification with long short-term memory(LSTM)neural networks.Being an original approach that is able to both significantly increase the feature dimensions and provides the property of deterministic dynamical systems of very short time series for information processing carried out by an LSTM layer architecture,fuzzy recurrence plots provide promising results and outperform the direct input of the time series for the classification of healthy control and early PD subjects.展开更多
Parkinson＇s disease （PD） is a typical degenerative disease, which is characterized by the most obvious symptoms of movement dysfunction, including shaking, rigidity, slowness of movement and difficulty in walking a...Parkinson＇s disease （PD） is a typical degenerative disease, which is characterized by the most obvious symptoms of movement dysfunction, including shaking, rigidity, slowness of movement and difficulty in walking and gait. This disease can not be clearly identified through laboratory tests at present, thus application of high-throughput technique in studying the expression profiles of PD helps to find the genetic markers for its early diagnosis. Studies on expression profiles of neurodegenerative diseases have revealed the novel genes and pathways involved in the progress of illness. In this study, the expression profiles of PD in blood were compared, showing that 181 differentially expressed genes （DEG） exhibit a similar expression trend both in patients and in normal controls.展开更多
Parkinson＇s disease （PD） is a neurodegenerative disorder characterized by selective and progressive degeneration, as well as loss of dopaminergic neurons in the substantia nigra. In PD, approximately 60-70% of nigr...Parkinson＇s disease （PD） is a neurodegenerative disorder characterized by selective and progressive degeneration, as well as loss of dopaminergic neurons in the substantia nigra. In PD, approximately 60-70% of nigrostriatal neurons are degenerated and 80% of content of the striatal dopamine is reduced before the diagnosis can be established according to widely accepted clinical diagnostic criteria. This condition describes a stage of disease called ＂prodromal＂, where non-motor symptoms, such as olfactory dysfunction, constipation, rapid eye movement behaviour disorder, depression, precede motor sign of PD. Detection of prodromal phase of PD is becoming an important goal for determining the prognosis and choosing a suitable treatment strategy. In this review, we present some non-invasive instrumental approaches that could be useful to identify patients in the prodromal phase of PD or in an early clinical phase, when the first motor symptoms begin to be apparent. Conventional magnetic resonance imaging （MRI） and advanced MRI techniques, such as magnetic resonance spectroscopy imaging, diffusion-weighted and diffusion tensor imaging and functional MRI, are useful to differentiate early PD with initial motor symptoms from atypical parkinsonian disorders, thus, making easier early diagnosis. Functional MRI and diffusion tensor imaging techniques can show abnormalities in the olfactory system in prodromal PD.展开更多
Parkinson’s disease(PD),one of whose symptoms is dysphonia,is a prevalent neurodegenerative disease.The use of outdated diagnosis techniques,which yield inaccurate and unreliable results,continues to represent an obs...Parkinson’s disease(PD),one of whose symptoms is dysphonia,is a prevalent neurodegenerative disease.The use of outdated diagnosis techniques,which yield inaccurate and unreliable results,continues to represent an obstacle in early-stage detection and diagnosis for clinical professionals in the medical field.To solve this issue,the study proposes using machine learning and deep learning models to analyze processed speech signals of patients’voice recordings.Datasets of these processed speech signals were obtained and experimented on by random forest and logistic regression classifiers.Results were highly successful,with 90%accuracy produced by the random forest classifier and 81.5%by the logistic regression classifier.Furthermore,a deep neural network was implemented to investigate if such variation in method could add to the findings.It proved to be effective,as the neural network yielded an accuracy of nearly 92%.Such results suggest that it is possible to accurately diagnose early-stage PD through merely testing patients’voices.This research calls for a revolutionary diagnostic approach in decision support systems,and is the first step in a market-wide implementation of healthcare software dedicated to the aid of clinicians in early diagnosis of PD.展开更多
The early diagnosis of Parkinson’s disease(PD)provides opportunities for early intervention to slow the progression of neurological degeneration in patients,particularly as the aging population increases in our socie...The early diagnosis of Parkinson’s disease(PD)provides opportunities for early intervention to slow the progression of neurological degeneration in patients,particularly as the aging population increases in our society.Among a series of pathological features of PD,mitochondria abnormalities have been identified as central event that occurs at the early stage of PD.However,the method for detecting mitochondrial abnormalities-associated early PD has not been fully developed.We herein report a specifically mitochondrial targeting probe(named TPA-BT-SCP)that is able to characterize mitochondria abnormalities for early diagnosis of PD and monitor PD neurodegenerative progress.The probe is an aggregation-induced emission(AIE)probe with a strong positive charge,a 3D distorted molecular structure,and a separated HOMO-LUMO distribution,designed with unique molecular design guidelines.Our research demonstrated that TPA-BT-SCP could emit stable and strong fluorescence,and rapidly accumulate in mitochondria due to the negative charge.After intranasal administration of 1-methy-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)-induced PD mice,TPA-BT-SCP successfully bypassed the blood−brain barrier to light up the brain,allowing the grading of PD severity based on its high sensitivity.Taken together,this work develops a novel AIE probe that exhibits dramatically high sensitivity to mitochondrial changes and enables noninvasive diagnosis of early PD in the brain.展开更多
Background：Sleep disturbance is one of the major non-motor symptoms which cause the disability of Parkinson’s disease （PD） patients. Cystatin C （CysC） is a more sensitive biomarker than serum creatinine or estim...Background：Sleep disturbance is one of the major non-motor symptoms which cause the disability of Parkinson’s disease （PD） patients. Cystatin C （CysC） is a more sensitive biomarker than serum creatinine or estimated glomerular filtration rate. Previous studies have reported altered CysC levels in neurodegenerative disorders and sleep disorders. This study aimed to explore the correlations of serum CysC levels and objective sleep disturbances in early PD.Methods：We recruited 106 early PD patients and 146 age- and sex-matched controls. All participants underwent clinical investigation and video-polysomnography. Sleep parameters and serum levels of CysC were measured. Then, we investigated the relationships between CysC and clinical variables and objective sleep disturbances in early PD patients.Results：The mean serum level of CysC was significantly higher in patients with early PD （1.03 ± 0.19 mg/L） compared to controls （0.96 ± 0.15 mg/L, P = 0.009）. There were significantly positive correlations between serum CysC levels and age （r = 0.334, P 〈 0.001）, gender （r = 0.264, P = 0.013）, and creatinine levels （r = 0.302, P = 0.018） in early PD patients. Increased serum CysC levels in early PD patients were significantly associated with higher apnea and hypopnea index （AHI） （r = 0.231, P = 0.017）, especially hypopnea index （r = 0.333, P 〈 0.001）. In early PD patients, elevated serum CysC levels were positively correlated with oxygen desaturation index （r = 0.223, P = 0.021）, percentage of time spent at oxygen saturation （SaO2） 〈90% （r = 0.644, P 〈 0.001）, arousal with respiratory event during sleep （r = 0.247, P = 0.013）. On the contrary, the elevated serum CysC levels were negatively correlated with mean and minimal SaO2 （r = ？0.323, ？0.315, both P = 0.001） in PD patients.Conclusions：The level of serum CysC was higher in early PD patients. PD patients with elevated serum CysC levels had more respiratory events and more severe oxygen desaturation. Therefore, the serum CysC levels may predict the severities of sleep-disordered breathing problems in early PD patients.展开更多
Parkinson＇s disease （PD） is a complex neurode- generative disease with progressive loss of dopamine neurons. PD patients usually manifest a series of motor and non-motor symptoms. In order to provide better early d...Parkinson＇s disease （PD） is a complex neurode- generative disease with progressive loss of dopamine neurons. PD patients usually manifest a series of motor and non-motor symptoms. In order to provide better early diagnosis and subsequent disease-modifying therapies for PD patients, there is an urgent need to identify sensitive and specific biomarkers. Biomarkers can be divided into four categories： clinical, imaging, biochemical, and genetic. Ideal biomarkers not only improve our under- standing of PD pathogenesis and progression, but also provide benefits for early risk evaluation and clinical diagnosis of PD. Although many efforts have been made and several biomarkers have been extensively investigated, few if any have been found useful for early diagnosis. Here, we summarize recent developments in the discovered biomarkers of PD and discuss their merits and limitations for the early diagnosis of PD.展开更多
文摘We have performed a complete screening of the Parkin gene (PRKN2) and looked for p.Gly2019Ser (G2019S) and p.Arg1441Gly (R1441G) LRRK2/dardarin gene mutations in twenty seven patients with Parkinson’s disease (PD) with an age at onset younger than 50 years (EOPD), living in Gipuzkoa (Basque Country, Spain). Thirteen of them (48%) were PRKN2 mutation carriers. The c.255-256DelA mutation was the most frequent, followed by a deletion involving exons 3 and 4. A deletion involving exons 3 and 12 of the PRKN2 gene and R1441G LRRK2 mutation was found together in one PD patient. Four out of fourteen PRKN2 negative patients carried the p.G2019S mutation. Both PRKN2 mutation carriers and non-carriers presented frequently with family history (10 PRKN2 mutation carriers and 8 PRKN2 non-carriers);in fact, five patients without a known gene mutation had a first degree relative affected, suggesting another monogenic disease. PRKN2 carriers presented with a younger age at onset (36.7 vs. 41.7) and more benign disease progression. Indeed, those PD patients younger than forty who initially presented with unilateral tremor became shortly bilateral. Relatively, symmetric parkinsonism and slow disease progression carried more frequently PRKN2 mutations than patients with unilateral akinetic rigid parkinsonism and age at onset later than 40 years. As expected in a recessive disease, PRKN2 patients present more often with affected siblings and unaffected patients. The G2019S LRRK2 mutation, less prevalent than R1441G in our area, may be also a frequent cause of PD in EOPD (4 patients).
文摘There are many techniques using sensors and wearable devices for detecting and monitoring patients with Parkinson’s disease(PD).A recent development is the utilization of human interaction with computer keyboards for analyzing and identifying motor signs in the early stages of the disease.Current designs for classification of time series of computer-key hold durations recorded from healthy control and PD subjects require the time series of length to be considerably long.With an attempt to avoid discomfort to participants in performing long physical tasks for data recording,this paper introduces the use of fuzzy recurrence plots of very short time series as input data for the machine training and classification with long short-term memory(LSTM)neural networks.Being an original approach that is able to both significantly increase the feature dimensions and provides the property of deterministic dynamical systems of very short time series for information processing carried out by an LSTM layer architecture,fuzzy recurrence plots provide promising results and outperform the direct input of the time series for the classification of healthy control and early PD subjects.
基金supported by the National Natural Science Foundation of China(81101302,31270185)SKLID Development Grant(2014,SKLID201)
文摘Parkinson＇s disease （PD） is a typical degenerative disease, which is characterized by the most obvious symptoms of movement dysfunction, including shaking, rigidity, slowness of movement and difficulty in walking and gait. This disease can not be clearly identified through laboratory tests at present, thus application of high-throughput technique in studying the expression profiles of PD helps to find the genetic markers for its early diagnosis. Studies on expression profiles of neurodegenerative diseases have revealed the novel genes and pathways involved in the progress of illness. In this study, the expression profiles of PD in blood were compared, showing that 181 differentially expressed genes （DEG） exhibit a similar expression trend both in patients and in normal controls.
文摘Parkinson＇s disease （PD） is a neurodegenerative disorder characterized by selective and progressive degeneration, as well as loss of dopaminergic neurons in the substantia nigra. In PD, approximately 60-70% of nigrostriatal neurons are degenerated and 80% of content of the striatal dopamine is reduced before the diagnosis can be established according to widely accepted clinical diagnostic criteria. This condition describes a stage of disease called ＂prodromal＂, where non-motor symptoms, such as olfactory dysfunction, constipation, rapid eye movement behaviour disorder, depression, precede motor sign of PD. Detection of prodromal phase of PD is becoming an important goal for determining the prognosis and choosing a suitable treatment strategy. In this review, we present some non-invasive instrumental approaches that could be useful to identify patients in the prodromal phase of PD or in an early clinical phase, when the first motor symptoms begin to be apparent. Conventional magnetic resonance imaging （MRI） and advanced MRI techniques, such as magnetic resonance spectroscopy imaging, diffusion-weighted and diffusion tensor imaging and functional MRI, are useful to differentiate early PD with initial motor symptoms from atypical parkinsonian disorders, thus, making easier early diagnosis. Functional MRI and diffusion tensor imaging techniques can show abnormalities in the olfactory system in prodromal PD.
文摘Parkinson’s disease(PD),one of whose symptoms is dysphonia,is a prevalent neurodegenerative disease.The use of outdated diagnosis techniques,which yield inaccurate and unreliable results,continues to represent an obstacle in early-stage detection and diagnosis for clinical professionals in the medical field.To solve this issue,the study proposes using machine learning and deep learning models to analyze processed speech signals of patients’voice recordings.Datasets of these processed speech signals were obtained and experimented on by random forest and logistic regression classifiers.Results were highly successful,with 90%accuracy produced by the random forest classifier and 81.5%by the logistic regression classifier.Furthermore,a deep neural network was implemented to investigate if such variation in method could add to the findings.It proved to be effective,as the neural network yielded an accuracy of nearly 92%.Such results suggest that it is possible to accurately diagnose early-stage PD through merely testing patients’voices.This research calls for a revolutionary diagnostic approach in decision support systems,and is the first step in a market-wide implementation of healthcare software dedicated to the aid of clinicians in early diagnosis of PD.
基金National Natural Science Foundation of China,Grant/Award Numbers:82241058,31922045,31771031Natural Science Foundation of Tianjin Province of China,Grant/Award Number:21JCZDJC00290+2 种基金State Key Laboratory of Medicinal Chemical Biology in Nankai University,Grant/Award Number:2020017State Key Laboratory of Biochemical EngineeringOpen Funding Project of State Key Laboratory of Biochemical Engineering,Grant/Award Number:2021KF-01。
文摘The early diagnosis of Parkinson’s disease(PD)provides opportunities for early intervention to slow the progression of neurological degeneration in patients,particularly as the aging population increases in our society.Among a series of pathological features of PD,mitochondria abnormalities have been identified as central event that occurs at the early stage of PD.However,the method for detecting mitochondrial abnormalities-associated early PD has not been fully developed.We herein report a specifically mitochondrial targeting probe(named TPA-BT-SCP)that is able to characterize mitochondria abnormalities for early diagnosis of PD and monitor PD neurodegenerative progress.The probe is an aggregation-induced emission(AIE)probe with a strong positive charge,a 3D distorted molecular structure,and a separated HOMO-LUMO distribution,designed with unique molecular design guidelines.Our research demonstrated that TPA-BT-SCP could emit stable and strong fluorescence,and rapidly accumulate in mitochondria due to the negative charge.After intranasal administration of 1-methy-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)-induced PD mice,TPA-BT-SCP successfully bypassed the blood−brain barrier to light up the brain,allowing the grading of PD severity based on its high sensitivity.Taken together,this work develops a novel AIE probe that exhibits dramatically high sensitivity to mitochondrial changes and enables noninvasive diagnosis of early PD in the brain.
文摘Background：Sleep disturbance is one of the major non-motor symptoms which cause the disability of Parkinson’s disease （PD） patients. Cystatin C （CysC） is a more sensitive biomarker than serum creatinine or estimated glomerular filtration rate. Previous studies have reported altered CysC levels in neurodegenerative disorders and sleep disorders. This study aimed to explore the correlations of serum CysC levels and objective sleep disturbances in early PD.Methods：We recruited 106 early PD patients and 146 age- and sex-matched controls. All participants underwent clinical investigation and video-polysomnography. Sleep parameters and serum levels of CysC were measured. Then, we investigated the relationships between CysC and clinical variables and objective sleep disturbances in early PD patients.Results：The mean serum level of CysC was significantly higher in patients with early PD （1.03 ± 0.19 mg/L） compared to controls （0.96 ± 0.15 mg/L, P = 0.009）. There were significantly positive correlations between serum CysC levels and age （r = 0.334, P 〈 0.001）, gender （r = 0.264, P = 0.013）, and creatinine levels （r = 0.302, P = 0.018） in early PD patients. Increased serum CysC levels in early PD patients were significantly associated with higher apnea and hypopnea index （AHI） （r = 0.231, P = 0.017）, especially hypopnea index （r = 0.333, P 〈 0.001）. In early PD patients, elevated serum CysC levels were positively correlated with oxygen desaturation index （r = 0.223, P = 0.021）, percentage of time spent at oxygen saturation （SaO2） 〈90% （r = 0.644, P 〈 0.001）, arousal with respiratory event during sleep （r = 0.247, P = 0.013）. On the contrary, the elevated serum CysC levels were negatively correlated with mean and minimal SaO2 （r = ？0.323, ？0.315, both P = 0.001） in PD patients.Conclusions：The level of serum CysC was higher in early PD patients. PD patients with elevated serum CysC levels had more respiratory events and more severe oxygen desaturation. Therefore, the serum CysC levels may predict the severities of sleep-disordered breathing problems in early PD patients.
基金supported by grants from the National Natural Science Foundation of China (81430021 and 81370470)the Program for Liaoning Provincial Innovative Research Team in Universities (LT2015009)+1 种基金the Liaoning Provincial Science and Technology Project (2015225008)a Research Project of Dalian Science and Technology (2014E14SF175) of Liaoning Province, China
文摘Parkinson＇s disease （PD） is a complex neurode- generative disease with progressive loss of dopamine neurons. PD patients usually manifest a series of motor and non-motor symptoms. In order to provide better early diagnosis and subsequent disease-modifying therapies for PD patients, there is an urgent need to identify sensitive and specific biomarkers. Biomarkers can be divided into four categories： clinical, imaging, biochemical, and genetic. Ideal biomarkers not only improve our under- standing of PD pathogenesis and progression, but also provide benefits for early risk evaluation and clinical diagnosis of PD. Although many efforts have been made and several biomarkers have been extensively investigated, few if any have been found useful for early diagnosis. Here, we summarize recent developments in the discovered biomarkers of PD and discuss their merits and limitations for the early diagnosis of PD.
