Kun Nie

Dr. Kun Nie


Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 October 2014 in International Journal of Neuroscience
Verified
Journal Article
Closed access
LGLiang Gao
Liang Gao
HTHongmei Tang
Hongmei Tang
KNKun Nie
Kun Nie
LWLimin Wang
Limin Wang
JZJiehao Zhao
Jiehao Zhao
LWLijuan Wang
Lijuan Wang
To date, there are no definitive biomarkers for Parkinson's disease (PD) diagnosis. The detection of cerebrospinal fluid (CSF) alpha (α)-synuclein in PD patients has yielded promising but inconclusive results. To determine the performance of CSF α-synuclein as a diagnostic biomarker of PD and whether CSF α-synuclein can discriminate PD from other neurodegenerative diseases, a systematic search of all relevant studies investigating reproducible CSF α-synuclein quantification methods was conducted in electronic databases. A total of 17 studies that included 3311 patients were included in this systemic review and meta-analysis. The mean CSF α-synuclein concentration was significantly lower in PD patients compared to normal/neurological controls [weighted mean difference (WMD) -0.31; 95% CI, -0.45, -0.16; p < 0.0001] and patients with Alzheimer's disease (AD) [WMD -0.15; 95% CI, -0.26, -0.04; p < 0.0001]. There was no significant difference between PD patients and dementia with Lewy bodies (DLB) patients [WMD -0.03; 95% CI, -0.16, 0.09; p = 0.58] or patients with multiple system atrophy (MSA) [WMD 0.05; 95% CI, -0.04, 0.13; p = 0.25]. Sensitivity and specificity of CSF α-synuclein in the diagnosis of PD was 0.88 (95% CI, 0.84-0.91) and 0.40 (95% CI, 0.35-0.45), respectively. The positive and negative likelihood ratios of CSF α-synuclein in the diagnosis of PD were 1.41 (95% CI, 1.24-1.60), and 0.29 (95% CI, 0.15-0.56), respectively. The corresponding summary receiver operating characteristic (SROC) curve showed an area under the curve (AUC) of 0.73. The concentration of CSF α-synuclein may be a biomarker for the diagnosis of PD. The use of α-synuclein alone however is not sufficient as a single biomarker and it must therefore be used in conjunction with other documented and reliable biomarkers.

25 February 2020 in Frontiers in Neurology
Verified
Journal Article
Open access
PDF file
TRTengzhu Ren
Tengzhu Ren
YGYuyuan Gao
Yuyuan Gao
YQYihui Qiu
Yihui Qiu
SJShuolin Jiang
Shuolin Jiang
QZQingxi Zhang
Qingxi Zhang
KNKun Nie
Kun Nie
Background and Aim: Gut bacteria play an important role in the pathogenesis of Parkinson's disease (PD). However, the alteration of fecal microbiota in PD with cognitive impairment remains unexplored. This study aimed to explore whether the gut microbiota of patients with PD having mild cognitive impairment (PD-MCI) were different from those with PD having normal cognition (PD-NC) and from healthy controls (HC). Also, the study probed the association between altered gut microbiota and cognitive ability in patients with PD. Methods: The fecal bacteria composition and short-chain fatty acids of 13 patients with PD-MCI, 14 patients with PD-NC, and 13 healthy spouses were analyzed using 16S ribosomal RNA sequencing and gas chromatography–mass spectrometry. Results: Compared with HC, the fecal microbial diversities increased in patients with PD-MCI and PD-NC. After adjusting the influence of age, sex, body mass index, education, and constipation using the statistical method, the relative abundances of two families (Rikenellaceae and Ruminococcaceae) and four genera (Alistipes, Barnesiella, Butyricimonas, and Odoribacter) were found to be higher in the feces of the PD-MCI group compared with the other two groups. Moreover, the abundance of genus Blautia and Ruminococcus decreased obviously in the PD-MCI group compared with the PD-NC group. Further, the abundance of genera Butyricimonas, Barnesiella, Alistipes, Odoribacter, and Ruminococcus negatively correlated with cognition ability. Conclusion: Compared with HC and patients with PD-NC, the gut microbiota of patients with PD-MCI was significantly altered, particularly manifesting in enriched genera from Porphyromonadaceae family and decreased the abundance of genera Blautia and Ruminococcus.

18 July 2023 in Annals of Neurology
Verified
Journal Article
Closed access
PHPeikun He
Peikun He
LSLin Shi
Lin Shi
YLYanyi Li
Yanyi Li
QDQingrui Duan
Qingrui Duan
YQYihui Qiu
Yihui Qiu
KNKun Nie
Kun Nie

26 December 2012 in American Journal of Alzheimer's Disease and Other Dementias®
Verified
Journal Article
Closed access
BDBingmei Deng
Bingmei Deng
YZyuhu zhang
yuhu zhang
LWLijuan Wang
Lijuan Wang
KPKairun Peng
Kairun Peng
LHLixin Han
Lixin Han
JWJun Wang
Jun Wang
: Cognitive deficit and white matter alteration relationships in Parkinson’s disease (PD) were investigated. : Comparison of 64 patients with PD (M:F, 34:30; 64.4 ± 10.4 years) classified as cognitively normal (PD-CogNL, n = 24), mild cognitive impairment (PD-MCI, n = 30), and dementia (PD-D, n = 10) with 21 healthy participants (M:F, 10:11; 60.1 ± 13.6 years) was conducted using white matter fractional anisotropy (FA), region-of-interest analysis, and diffusion tensor imaging. : The PD-D and PD-MCI exhibited higher Unified Parkinson’s Disease Rating Scale motor scores (P < .001; P < .01) and Hoehn-Yahr stages (P < .001; P < .05) and FA reductions in left frontal/right temporal white matter and bilateral anterior cingulated bundles. Largest FA reductions occurred in PD-D left anterior cingulated bundle and corpus callosum splenium. Disease durations of PD-D = 6.8 ± 6.86, PD-MCI = 5.1 ± 2.9, and PD-CogNL = 4.7 ± 3.4 years, suggesting progressive deterioration. : Cerebral white matter deterioration may underlie progressive cognitive impairment in PD.

1 September 2017 in Neuroscience Letters
Verified
Journal Article
Closed access
YGYuyuan Gao
Yuyuan Gao
KNKun Nie
Kun Nie
BHBiao Huang
Biao Huang
MMMingjin Mei
Mingjin Mei
MGManli Guo
Manli Guo
LWLijuan Wang
Lijuan Wang

1 March 2013 in Parkinsonism & Related Disorders
Verified
Journal Article
Closed access
KNKun Nie
Kun Nie
YZyuhu zhang
yuhu zhang
BHBiao Huang
Biao Huang
LWLimin Wang
Limin Wang
JZJiehao Zhao
Jiehao Zhao
LWLijuan Wang
Lijuan Wang