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Deng L, Liu T, Liu CA, Zhang Q, Song MM, Lin SQ, Wang YM, Zhang QS, Shi HP. The association of metabolic syndrome score trajectory patterns with risk of all cancer types. Cancer 2024; 130:2150-2159. [PMID: 38462898 DOI: 10.1002/cncr.35235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/05/2024] [Accepted: 01/22/2024] [Indexed: 03/12/2024]
Abstract
BACKGROUND Metabolic syndrome (MetS) elevates cancer risk. However, a single MetS assessment does not fully reveal the long-term association with cancer. Inflammation, alongside MetS, could synergistically expedite both the onset and advancement of cancer. This study aims to investigate MetS score trajectories and cancer risk in a large, prospective cohort study. METHODS The authors prospectively examined the relationship between MetS score trajectory patterns and new-onset cancer in 44,115 participants. Latent mixture modeling was used to identify the MetS score trajectories. Cox proportional hazards regression models were used to evaluate the association between MetS score trajectory patterns and the risk of overall and site-specific cancers. RESULTS Four MetS score trajectory patterns were identified: low-stable (n = 4657), moderate-low (n = 18,018), moderate-high (n = 18,288), and elevated-increasing (n = 3152). Compared to participants with a low-stable trajectory pattern, the elevated-increasing trajectory pattern was associated with an elevated risk of overall (hazard ratio [HR], 1.27; 95% confidence interval [CI], 1.04-1.55), breast (HR, 2.11; 95% CI, 1.04-4.34), endometrial (HR, 3.33; 95% CI, 1.16-6.77), kidney (HR, 4.52; 95% CI, 1.17-10.48), colorectal (HR, 2.54; 95% CI, 1.27-5.09), and liver (HR, 1.61; 95% CI, 1.09-4.57) cancers. Among participants with chronic inflammation (C-reactive protein levels ≥3 mg/L), the elevated-increasing trajectory pattern was significantly associated with subsequent breast, endometrial, colorectal, and liver cancers. CONCLUSIONS Trajectories of MetS scores are associated with the occurrence of cancers, especially breast, endometrial, kidney, colorectal, and liver cancers, emphasizing the importance of long-term monitoring and evaluation of MetS. PLAIN LANGUAGE SUMMARY The association between long-term elevated metabolic syndrome (MetS) scores and a heightened risk of various cancers is a pivotal finding of our study. Our research further indicates that individuals with MetS, particularly when coupled with chronic inflammation, are at an increased risk of cancer. We propose that sustained monitoring and management of MetS could be beneficial in reducing cancer risk.
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Affiliation(s)
- Li Deng
- Department of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
- Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Tong Liu
- Department of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
- Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Chen-An Liu
- Department of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
- Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Qi Zhang
- Department of Genetics, Yale School of Medicine, New Haven, Connecticut, USA
| | - Meng-Meng Song
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA
| | - Shi-Qi Lin
- Department of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
- Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Yi-Ming Wang
- Department of Hepatological Surgery, Kailuan General Hospital, Tangshan, China
| | - Qing-Song Zhang
- Department of General Surgery, Kailuan General Hospital, Tangshan, China
| | - Han-Ping Shi
- Department of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
- Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
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Guo T, Zheng S, Chen T, Chu C, Ren J, Sun Y, Wang Y, He M, Yan Y, Jia H, Liao Y, Cao Y, Du M, Wang D, Yuan Z, Wang D, Mu J. The association of long-term trajectories of BMI, its variability, and metabolic syndrome: a 30-year prospective cohort study. EClinicalMedicine 2024; 69:102486. [PMID: 38370536 PMCID: PMC10874716 DOI: 10.1016/j.eclinm.2024.102486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/21/2024] [Accepted: 01/30/2024] [Indexed: 02/20/2024] Open
Abstract
Background Limited data exists on how early-life weight changes relate to metabolic syndrome (MetS) risk in midlife. This study examines the association between long-term trajectories of body mass index (BMI), its variability, and MetS risk in Chinese individuals. Methods In the Hanzhong Adolescent Hypertension study (March 10, 1987-June 3, 2017), 1824 participants with at least five BMI measurements from 1987 to 2017 were included. Using group-based trajectory modeling, different BMI trajectories were identified. BMI variability was assessed through standard deviation (SD), variability independent of the mean (VIM), and average real variability (ARV). Logistic regression analyzed the relationship between BMI trajectory, BMI variability, and MetS occurrence in midlife (URL: https://www.clinicaltrials.gov; Unique identifier: NCT02734472). Findings BMI trajectories were categorized as low-increasing (34.4%), moderate-increasing (51.8%), and high-increasing (13.8%). Compared to the low-increasing group, the odds ratios (ORs) [95% CIs] for MetS were significantly higher in moderate (4.27 [2.63-6.91]) and high-increasing groups (13.11 [6.30-27.31]) in fully adjusted models. Additionally, higher BMI variabilities were associated with increased MetS odds (ORs for SDBMI, VIMBMI, and ARVBMI: 2.30 [2.02-2.62], 1.22 [1.19-1.26], and 4.29 [3.38-5.45]). Furthermore, BMI trajectories from childhood to adolescence were predictive of midlife MetS, with ORs in moderate (1.49 [1.00-2.23]) and high-increasing groups (2.45 [1.22-4.91]). Lastly, elevated BMI variability in this period was also linked to higher MetS odds (ORs for SDBMI, VIMBMI, and ARVBMI: 1.24 [1.08-1.42], 1.00 [1.00-1.01], and 1.21 [1.05-1.38]). Interpretation Our study suggests that both early-life BMI trajectories and BMI variability could be predictive of incident MetS in midlife. Funding This work was supported by the National Natural Science Foundation of China No. 82070437 (J.-J.M.), the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University of China (No. XJTU1AF-CRF-2022-002, XJTU1AF2021CRF-021, and XJTU1AF-CRF-2023-004), the Key R&D Projects in Shaanxi Province (Grant No. 2023-ZDLSF-50), the Chinese Academy of Medical Sciences & Peking Union Medical College (2017-CXGC03-2), and the International Joint Research Centre for Cardiovascular Precision Medicine of Shaanxi Province (2020GHJD-14).
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Affiliation(s)
- Tongshuai Guo
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Sirui Zheng
- Biostatistics Unit, Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK
| | - Tao Chen
- Centre for Health Economics, University of York, Heslington, York, YO10 5DD, UK
| | - Chao Chu
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Jie Ren
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Yue Sun
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Yang Wang
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Mingjun He
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Yu Yan
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Hao Jia
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Yueyuan Liao
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Yumeng Cao
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Mingfei Du
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Dan Wang
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Zuyi Yuan
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Duolao Wang
- Biostatistics Unit, Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK
| | - Jianjun Mu
- Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China
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Costa SO, Chaves WF, Lopes PKF, Silva IM, Burguer B, Ignácio-Souza LM, Torsoni AS, Milanski M, Rodrigues HG, Desai M, Ross MG, Torsoni MA. Maternal consumption of a high-fat diet modulates the inflammatory response in their offspring, mediated by the M1 muscarinic receptor. Front Immunol 2023; 14:1273556. [PMID: 38193079 PMCID: PMC10773672 DOI: 10.3389/fimmu.2023.1273556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 11/27/2023] [Indexed: 01/10/2024] Open
Abstract
Introduction High-fat diet (HFD) consumption is associated with various metabolic disorders and diseases. Both pre-pregnancy and maternal obesity can have long-term consequences on offspring health. Furthermore, consuming an HFD in adulthood significantly increases the risk of obesity and metabolic disorders. However, an intriguing phenomenon known as the obesity paradox suggests that obesity may confer a protective effect on mortality outcomes in sepsis. In sepsis, activation of the cholinergic anti-inflammatory pathway (CAP) can help mitigate systemic inflammation. We employed a metabolic programming model to explore the relationship between maternal HFD consumption and offspring response to sepsis. Methods We fed female mice either a standard diet (SC) or an HFD during the pre-pregnancy, pregnancy, and lactation periods. Subsequently, we evaluated 28-day-old male offspring. Results Notably, we discovered that offspring from HFD-fed dams (HFD-O) exhibited a higher survival rate compared with offspring from SC-fed dams (SC-O). Importantly, inhibition of the m1 muscarinic acetylcholine receptor (m1mAChR), involved in the CAP, in the hypothalamus abolished this protection. The expression of m1mAChR in the hypothalamus was higher in HFD-O at different ages, peaking on day 28. Treatment with an m1mAChR agonist could modulate the inflammatory response in peripheral tissues. Specifically, CAP activation was greater in the liver of HFD-O following agonist treatment. Interestingly, lipopolysaccharide (LPS) challenge failed to induce a more inflammatory state in HFD-O, in contrast to SC-O, and agonist treatment had no additional effect. Analysis of spleen immune cells revealed a distinct phenotype in HFD-O, characterized by elevated levels of CD4+ lymphocytes rather than CD8+ lymphocytes. Moreover, basal Il17 messenger RNA (mRNA) levels were lower while Il22 mRNA levels were higher in HFD-O, and we observed the same pattern after LPS challenge. Discussion Further examination of myeloid cells isolated from bone marrow and allowed to differentiate showed that HFD-O macrophages displayed an anti-inflammatory phenotype. Additionally, treatment with the m1mAChR agonist contributed to reducing inflammatory marker levels in both groups. In summary, our findings demonstrate that HFD-O are protected against LPS-induced sepsis, and this protection is mediated by the central m1mAChR. Moreover, the inflammatory response in the liver, spleen, and bone marrow-differentiated macrophages is diminished. However, more extensive analysis is necessary to elucidate the specific mechanisms by which m1mAChR modulates the immune response during sepsis.
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Affiliation(s)
- Suleyma Oliveira Costa
- Laboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil
| | - Wenicios Ferreira Chaves
- Laboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil
| | | | - Iracema M. Silva
- Laboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil
| | - Beatriz Burguer
- Laboratory of Nutrients and Tissue Repair, School of Applied Sciences, University of Campinas, Limeira, Brazil
| | - Leticia M. Ignácio-Souza
- Laboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil
- Obesity and Comorbidities Research Center, University of Campinas, Campinas, Brazil
| | - Adriana Souza Torsoni
- Laboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil
- Obesity and Comorbidities Research Center, University of Campinas, Campinas, Brazil
| | - Marciane Milanski
- Laboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil
- Obesity and Comorbidities Research Center, University of Campinas, Campinas, Brazil
| | - Hosana Gomes Rodrigues
- Laboratory of Nutrients and Tissue Repair, School of Applied Sciences, University of Campinas, Limeira, Brazil
| | - Mina Desai
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles at Harbor-UCLA, Torrance, CA, United States
| | - Michael Glenn Ross
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles at Harbor-UCLA, Torrance, CA, United States
| | - Marcio Alberto Torsoni
- Laboratory of Metabolic Disorders, School of Applied Sciences, University of Campinas, Limeira, Brazil
- Obesity and Comorbidities Research Center, University of Campinas, Campinas, Brazil
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Seyedhoseinpour A, Barzin M, Mahdavi M, Valizadeh M, Azizi F, Hosseinpanah F. Association between BMI trajectories from childhood to early adulthood and the carotid intima-media thickness in early adulthood: Tehran lipid and glucose study. BMC Public Health 2023; 23:2233. [PMID: 37957617 PMCID: PMC10641964 DOI: 10.1186/s12889-023-17184-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 11/08/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND AND AIMS Childhood and adolescence overweight/obesity is an important predictor of obesity and increased long-term cardiometabolic abnormalities in adulthood. In this study, we aimed to investigate the association of body mass index (BMI) and waist circumference (WC) trajectories among children and adolescents with adulthood carotid intima-media thickness (cIMT) as a determinant of subclinical atherosclerosis. METHODS In this prospective cohort study, 1265 participants aged 3 to 18 were followed up for 18 years. By using Latent Class Growth Analysis, three groups of BMI and WC trajectory were defined; low stable, moderate-increasing, and high-increasing. Linear and logistic regression analysis were used to investigate the association of each lifetime BMI and WC trajectory group with cIMT. RESULTS Although the high-increasing BMI trajectory group was significantly associated with higher cIMT (ß=0.0464, P < 0.001), moderate-increase was not (ß=0.0096, P = 0.102); in reference to the low-stable BMI trajectory group. Among WC trajectory groups, both moderate- (ß=0.0177, P = 0.006) and high-increasing (ß=0.0533, P < 0.001), in reference to the low-stable group, were significantly associated with higher cIMT. The results did not change after adjustment for baseline BMI. The ORs of high-increasing BMI, moderate-increasing WC, and high-increasing WC trajectories were 3.24, 1.92, and 3.29, respectively for high cIMT. CONCLUSION Our study resulted that a high-increasing trajectory of childhood BMI and moderate- and high-increasing trajectories of childhood WC are associated with higher cIMT and higher risk of high-cIMT. Regular monitoring and screening of BMI and WC trajectory from childhood may improve identifying individuals with high risks of cardiovascular disease, more accurately.
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Affiliation(s)
- Amirhosein Seyedhoseinpour
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Barzin
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Mahdavi
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Majid Valizadeh
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farhad Hosseinpanah
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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He P, Gao Y, Shi L, Li Y, Jiang S, Tie Z, Qiu Y, Ma G, Zhang Y, Nie K, Wang L. Motor progression phenotypes in early-stage Parkinson's Disease: A clinical prediction model and the role of glymphatic system imaging biomarkers. Neurosci Lett 2023; 814:137435. [PMID: 37562710 DOI: 10.1016/j.neulet.2023.137435] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 08/06/2023] [Accepted: 08/07/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Substantial heterogeneity of motor symptoms in Parkinson's disease (PD) poses a challenge to disease prediction. OBJECTIVES The aim of this study was to construct a nomogram model that can distinguish different longitudinal trajectories of motor symptom changes in early-stage PD patients. METHODS Data on 90 patients with 5-years of follow-up were collected from the Parkinson's Progression Marker Initiative (PPMI) cohort. We used a latent class mixed modeling (LCMM) to identify distinct progression patterns of motor symptoms, and backward stepwise logistic regression with baseline information was conducted to identify the potential predictors for motor trajectory and to develop a nomogram. The performance of the nomogram model was then evaluated using the optimism-corrected C-index for internal validation, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for discrimination, the calibration curve for predictive accuracy, and decision curve analysis (DCA) for its clinical value. RESULTS We identified two trajectories for motor progression patterns. The first, Class 1 (Motor deteriorated group), was characterized by sustained, continuously worsening motor symptoms, and the second, Class 2 (Motor stable group), had stable motor symptoms throughout the follow-up period. The best combination of 7 baseline variables was identified and assembled into the nomogram: Scopa-AUT [odds ratio (OR), 1.11; p = 0.091], Letter number sequencing (LNS) (OR, 0.76; p = 0.068), the asymmetry index of putamen (OR, 0.95; p = 0.034), mean caudate uptake (OR, 0.14; p = 0.086), CSF pTau/α-synuclein (OR, 0.00; p = 0.011), CSF tTau/Aβ (OR, 25434806; p = 0.025), and the index for diffusion tensor image analysis along the perivascular space (ALPS-index) (OR, 0.02; p = 0.030). The nomogram achieved good discrimination, with an original AUC of 0.901 (95% CI, 0.813-0.989), and the bias-corrected concordance index (C-index) with 1,000 bootstraps was 0.834. The calibration curve and DCA also suggested both the high accuracy and clinical usefulness of the nomogram, respectively. CONCLUSIONS This study proposes an effective nomogram to predict different motor progression patterns in early-stage PD. Furthermore, the imaging biomarker indicating glymphatic function could be an independent predictive factor for PD motor progression.
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Affiliation(s)
- Peikun He
- School of Medicine, South China University of Technology, Guangzhou 510006, China; Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yuyuan Gao
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China; BrainNow Research Institute, Shenzhen, Guangdong Province, China
| | - Yanyi Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Shuolin Jiang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Zihui Tie
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yihui Qiu
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Guixian Ma
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yuhu Zhang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Kun Nie
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
| | - Lijuan Wang
- School of Medicine, South China University of Technology, Guangzhou 510006, China; Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
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