{"title":"识别具有不同脑萎缩进展的帕金森病亚型及其与临床进展的关系","authors":"Guoqing Pan, Yuchao Jiang, Wei Zhang, Xuejuan Zhang, Linbo Wang, Wei Cheng","doi":"10.1093/psyrad/kkae002","DOIUrl":null,"url":null,"abstract":"\n \n \n Studying of heterogeneity of Parkinson's disease (PD) is crucial for comprehending pathophysiological mechanisms underlying the disease. PD patients suffer from progressive gray matter volume (GMV) loss, but whether distinct patterns of atrophy progression exist within PD are still unclear.\n \n \n \n The objective of this study was to identify PD subtypes with different rates of GMV loss and to explore whether these subtypes were associated with clinical progression.\n \n \n \n Patients with PD (n = 107, mean age 60.06 ± 9.98 years, 70.09% male) who had baseline and at least three years of follow-up structural MRI scans were included in the study. Linear mixed-effects model (LME) was used to evaluate the rate of GMV loss for each patient at the regional level with adjusting for covariates. Hierarchical cluster analysis was applied to individual rate of GMV loss to test whether there exist different subtypes in PD. Longitudinal changes in clinical scores were compared between different subtypes.\n \n \n \n Hierarchical cluster analysis classified patients into two clusters based on their individual atrophy rates. Subtype 1 (n = 63) had moderate levels of atrophy rates in the prefrontal lobe and lateral temporal lobe, while subtype 2 (n = 44) was characterized by faster atrophy in almost the entire brain, particularly in the lateral temporal region. Furthermore, subtype 2 exhibited faster deterioration in non-motor (MDS-UPDRS Part Ⅰ, β=1.26 ± 0.18, P = 0.016) and motor (MDS-UPDRS Part Ⅱ, β=1.34 ± 0.20, P = 0.017) symptoms, autonomic dysfunction (SCOPA-AUT, β=1.15 ± 0.22, P = 0.043), memory (HVLT-Retention, β=-0.02 ± 0.01, P = 0.016) and depression (GDS, β=0.26 ± 0.083, P = 0.019) compared to subtype 1.\n \n \n \n The study has identified two PD subtypes with distinct patterns of atrophy progression and clinical progression, which may have implications for developing personalized treatment strategies.\n","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"3 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of Parkinson's Disease Subtypes with Distinct Brain Atrophy Progression and its Association with Clinical Progression\",\"authors\":\"Guoqing Pan, Yuchao Jiang, Wei Zhang, Xuejuan Zhang, Linbo Wang, Wei Cheng\",\"doi\":\"10.1093/psyrad/kkae002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\n Studying of heterogeneity of Parkinson's disease (PD) is crucial for comprehending pathophysiological mechanisms underlying the disease. PD patients suffer from progressive gray matter volume (GMV) loss, but whether distinct patterns of atrophy progression exist within PD are still unclear.\\n \\n \\n \\n The objective of this study was to identify PD subtypes with different rates of GMV loss and to explore whether these subtypes were associated with clinical progression.\\n \\n \\n \\n Patients with PD (n = 107, mean age 60.06 ± 9.98 years, 70.09% male) who had baseline and at least three years of follow-up structural MRI scans were included in the study. Linear mixed-effects model (LME) was used to evaluate the rate of GMV loss for each patient at the regional level with adjusting for covariates. Hierarchical cluster analysis was applied to individual rate of GMV loss to test whether there exist different subtypes in PD. Longitudinal changes in clinical scores were compared between different subtypes.\\n \\n \\n \\n Hierarchical cluster analysis classified patients into two clusters based on their individual atrophy rates. Subtype 1 (n = 63) had moderate levels of atrophy rates in the prefrontal lobe and lateral temporal lobe, while subtype 2 (n = 44) was characterized by faster atrophy in almost the entire brain, particularly in the lateral temporal region. Furthermore, subtype 2 exhibited faster deterioration in non-motor (MDS-UPDRS Part Ⅰ, β=1.26 ± 0.18, P = 0.016) and motor (MDS-UPDRS Part Ⅱ, β=1.34 ± 0.20, P = 0.017) symptoms, autonomic dysfunction (SCOPA-AUT, β=1.15 ± 0.22, P = 0.043), memory (HVLT-Retention, β=-0.02 ± 0.01, P = 0.016) and depression (GDS, β=0.26 ± 0.083, P = 0.019) compared to subtype 1.\\n \\n \\n \\n The study has identified two PD subtypes with distinct patterns of atrophy progression and clinical progression, which may have implications for developing personalized treatment strategies.\\n\",\"PeriodicalId\":93496,\"journal\":{\"name\":\"Psychoradiology\",\"volume\":\"3 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Psychoradiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/psyrad/kkae002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychoradiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/psyrad/kkae002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of Parkinson's Disease Subtypes with Distinct Brain Atrophy Progression and its Association with Clinical Progression
Studying of heterogeneity of Parkinson's disease (PD) is crucial for comprehending pathophysiological mechanisms underlying the disease. PD patients suffer from progressive gray matter volume (GMV) loss, but whether distinct patterns of atrophy progression exist within PD are still unclear.
The objective of this study was to identify PD subtypes with different rates of GMV loss and to explore whether these subtypes were associated with clinical progression.
Patients with PD (n = 107, mean age 60.06 ± 9.98 years, 70.09% male) who had baseline and at least three years of follow-up structural MRI scans were included in the study. Linear mixed-effects model (LME) was used to evaluate the rate of GMV loss for each patient at the regional level with adjusting for covariates. Hierarchical cluster analysis was applied to individual rate of GMV loss to test whether there exist different subtypes in PD. Longitudinal changes in clinical scores were compared between different subtypes.
Hierarchical cluster analysis classified patients into two clusters based on their individual atrophy rates. Subtype 1 (n = 63) had moderate levels of atrophy rates in the prefrontal lobe and lateral temporal lobe, while subtype 2 (n = 44) was characterized by faster atrophy in almost the entire brain, particularly in the lateral temporal region. Furthermore, subtype 2 exhibited faster deterioration in non-motor (MDS-UPDRS Part Ⅰ, β=1.26 ± 0.18, P = 0.016) and motor (MDS-UPDRS Part Ⅱ, β=1.34 ± 0.20, P = 0.017) symptoms, autonomic dysfunction (SCOPA-AUT, β=1.15 ± 0.22, P = 0.043), memory (HVLT-Retention, β=-0.02 ± 0.01, P = 0.016) and depression (GDS, β=0.26 ± 0.083, P = 0.019) compared to subtype 1.
The study has identified two PD subtypes with distinct patterns of atrophy progression and clinical progression, which may have implications for developing personalized treatment strategies.