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Devigili G, Straccia G, Cereda E, Garavaglia B, Fedeli A, Elia AE, Piacentini SHMJ, Prioni S, Amami P, Invernizzi F, Andreasi NG, Romito LM, Eleopra R, Cilia R. Unraveling Autonomic Dysfunction in GBA-Related Parkinson's Disease. Mov Disord Clin Pract 2023; 10:1620-1638. [PMID: 38026514 PMCID: PMC10654845 DOI: 10.1002/mdc3.13892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 08/13/2023] [Accepted: 09/08/2023] [Indexed: 12/01/2023] Open
Abstract
Background Patients with Parkinson's disease (PD) and GBA gene mutations (GBA-PD) develop nonmotor complications more frequently than noncarriers. However, an objective characterization of both cardiovascular and sudomotor autonomic dysfunction using extensive clinical and instrumental measures has never been provided so far. Survival is reduced in GBA-PD regardless of age and dementia, suggesting that other hitherto unrecognized factors are involved. Objectives To provide instrumental measures of pattern and severity of autonomic dysfunction in GBA-PD and explore their correlation with other non-motor symptoms and implications for clinical practice. Methods In this cross-sectional study, 21 GBA-PD and 24 matched PD noncarriers underwent extensive assessment of motor and non-motor features, including neuropsychological testing. Cardiovascular autonomic function was explored through a comprehensive battery of indexes, including power spectral analysis of the R-R intervals and blood pressure short-term variability during resting state and active maneuvers. Dynamic Sweat Test was used to assess post-ganglionic sudomotor dysfunction. Results Despite minimal or absent clinical correlates, cardiovagal and sympathetic indexes, heart rate variability parameters and sudomotor postganglionic function were more severely impaired in GBA-PD than noncarriers (overcoming relatively preserved compensatory peripheral sympathetic function), suggesting more prominent cardiac sympatho-vagal demodulation, efferent baroreflex failure and peripheral sympathetic dysfunction in GBA-PD. Cardiovascular dysautonomia showed marginal correlations with cognitive impairment. Conclusions Compared to PD noncarriers, GBA-PD display more severe instrumental autonomic abnormalities, which may be underestimated by purely clinical measures, despite their relevance on morbidity and mortality. This supports the necessity of implementing instrumental autonomic assessment in all GBA-PD, regardless of clinically overt symptoms.
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Affiliation(s)
- Grazia Devigili
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Department of Clinical Neurosciences, Parkinson and Movement Disorders UnitMilanItaly
| | - Giulia Straccia
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Department of Clinical Neurosciences, Parkinson and Movement Disorders UnitMilanItaly
- Neurology and Stroke UnitC.T.O. Hospital, A.O.R.N Ospedali dei ColliNaplesItaly
| | - Emanuele Cereda
- Clinical Nutrition and Dietetics UnitFondazione IRCCS Policlinico San MatteoPaviaItaly
| | - Barbara Garavaglia
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Unit of Medical Genetics and NeurogeneticsMilanItaly
| | - Alessandro Fedeli
- Neuropsychology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Antonio Emanuele Elia
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Department of Clinical Neurosciences, Parkinson and Movement Disorders UnitMilanItaly
| | | | - Sara Prioni
- Neuropsychology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Paolo Amami
- Neuropsychology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Federica Invernizzi
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Unit of Medical Genetics and NeurogeneticsMilanItaly
| | - Nico Golfrè Andreasi
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Department of Clinical Neurosciences, Parkinson and Movement Disorders UnitMilanItaly
| | - Luigi Michele Romito
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Department of Clinical Neurosciences, Parkinson and Movement Disorders UnitMilanItaly
| | - Roberto Eleopra
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Department of Clinical Neurosciences, Parkinson and Movement Disorders UnitMilanItaly
| | - Roberto Cilia
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Department of Clinical Neurosciences, Parkinson and Movement Disorders UnitMilanItaly
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Karabayir I, Gunturkun F, Butler L, Goldman SM, Kamaleswaran R, Davis RL, Colletta K, Chinthala L, Jefferies JL, Bobay K, Ross GW, Petrovitch H, Masaki K, Tanner CM, Akbilgic O. Externally validated deep learning model to identify prodromal Parkinson's disease from electrocardiogram. Sci Rep 2023; 13:12290. [PMID: 37516770 PMCID: PMC10387090 DOI: 10.1038/s41598-023-38782-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 07/14/2023] [Indexed: 07/31/2023] Open
Abstract
Little is known about electrocardiogram (ECG) markers of Parkinson's disease (PD) during the prodromal stage. The aim of the study was to build a generalizable ECG-based fully automatic artificial intelligence (AI) model to predict PD risk during the prodromal stage, up to 5 years before disease diagnosis. This case-control study included samples from Loyola University Chicago (LUC) and University of Tennessee-Methodist Le Bonheur Healthcare (MLH). Cases and controls were matched according to specific characteristics (date, age, sex and race). Clinical data were available from May, 2014 onward at LUC and from January, 2015 onward at MLH, while the ECG data were available as early as 1990 in both institutes. PD was denoted by at least two primary diagnostic codes (ICD9 332.0; ICD10 G20) at least 30 days apart. PD incidence date was defined as the earliest of first PD diagnostic code or PD-related medication prescription. ECGs obtained at least 6 months before PD incidence date were modeled to predict a subsequent diagnosis of PD within three time windows: 6 months-1 year, 6 months-3 years, and 6 months-5 years. We applied a novel deep neural network using standard 10-s 12-lead ECGs to predict PD risk at the prodromal phase. This model was compared to multiple feature engineering-based models. Subgroup analyses for sex, race and age were also performed. Our primary prediction model was a one-dimensional convolutional neural network (1D-CNN) that was built using 131 cases and 1058 controls from MLH, and externally validated on 29 cases and 165 controls from LUC. The model was trained on 90% of the MLH data, internally validated on the remaining 10% and externally validated on LUC data. The best performing model resulted in an external validation AUC of 0.67 when predicting future PD at any time between 6 months and 5 years after the ECG. Accuracy increased when restricted to ECGs obtained within 6 months to 3 years before PD diagnosis (AUC 0.69) and was highest when predicting future PD within 6 months to 1 year (AUC 0.74). The 1D-CNN model based on raw ECG data outperformed multiple models built using more standard ECG feature engineering approaches. These results demonstrate that a predictive model developed in one cohort using only raw 10-s ECGs can effectively classify individuals with prodromal PD in an independent cohort, particularly closer to disease diagnosis. Standard ECGs may help identify individuals with prodromal PD for cost-effective population-level early detection and inclusion in disease-modifying therapeutic trials.
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Affiliation(s)
- Ibrahim Karabayir
- Cardiovascular Section, Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
| | - Fatma Gunturkun
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Palo Alto, CA, USA
| | - Liam Butler
- Cardiovascular Section, Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
| | - Samuel M Goldman
- Division of Occupational, Environmental, and Climate Medicine, San Francisco Veterans Affairs Medical Center, University of California-San Francisco, 4150 Clement Street, Box 127, San Francisco, CA, 94121, USA.
| | | | - Robert L Davis
- Center for Biomedical Informatics, University of Tennessee Health Science Center, Memphis, USA
| | - Kalea Colletta
- Department of Neurology, Edward Hines Jr. VA Hospital, Hines, IL, USA
| | - Lokesh Chinthala
- Center for Biomedical Informatics, University of Tennessee Health Science Center, Memphis, USA
| | - John L Jefferies
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Kathleen Bobay
- Parkinson School of Health Sciences and Public Health, Loyola University Chicago, Maywood, IL, USA
| | - G Webster Ross
- Veterans Affairs Pacific Islands Health Care Systems, Honolulu, HI, USA
| | - Helen Petrovitch
- Pacific Health Research and Education Institute, Honolulu, HI, USA
| | - Kamal Masaki
- Kuakini Medical Center, Honolulu, HI, USA
- Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
| | - Caroline M Tanner
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Oguz Akbilgic
- Cardiovascular Section, Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA.
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Abulafia C, Vidal MF, Olivar N, Odzak A, Brusco I, Guinjoan SM, Cardinali DP, Vigo DE. An Exploratory Study of Sleep-Wake Differences of Autonomic Activity in Patients with Mild Cognitive Impairment: The Role of Melatonin as a Modulating Factor. Clin Interv Aging 2023; 18:771-781. [PMID: 37200894 PMCID: PMC10187579 DOI: 10.2147/cia.s394749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 05/08/2023] [Indexed: 05/20/2023] Open
Abstract
Purpose The objective of the present study was to assess sleep-wake differences of autonomic activity in patients with mild cognitive impairment (MCI) compared to control subjects. As a post-hoc objective, we sought to evaluate the mediating effect of melatonin on this association. Patients and Methods A total of 22 MCI patients (13 under melatonin treatment) and 12 control subjects were included in this study. Sleep-wake periods were identified by actigraphy and 24hr-heart rate variability measures were obtained to study sleep-wake autonomic activity. Results MCI patients did not show any significant differences in sleep-wake autonomic activity when compared to control subjects. Post-hoc analyses revealed that MCI patients not taking melatonin displayed lower parasympathetic sleep-wake amplitude than controls not taking melatonin (RMSSD -7 ± 1 vs 4 ± 4, p = 0.004). In addition, we observed that melatonin treatment was associated with greater parasympathetic activity during sleep (VLF 15.5 ± 0.1 vs 15.1 ± 0.1, p = 0.010) and in sleep-wake differences in MCI patients (VLF 0.5 ± 0.1 vs 0.2 ± 0.0, p = 0.004). Conclusion These preliminary findings hint at a possible sleep-related parasympathetic vulnerability in patients at prodromal stages of dementia as well as a potential protective effect of exogenous melatonin in this population.
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Affiliation(s)
- Carolina Abulafia
- Laboratory of Chronophysiology, Institute for Biomedical Research (BIOMED), Pontifical Catholic University of Argentina (UCA) and CONICET, Buenos Aires, Argentina
- Facultad de Psicología, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - María F Vidal
- Servicio de Psiquiatría, Departamento de Neurología, Fleni, Buenos Aires, Argentina
| | - Natividad Olivar
- Hospital de Clínicas “José de San Martín”, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Andrea Odzak
- Servicio de Clínica Médica, Hospital Argerich, Buenos Aires, Argentina
| | - Ignacio Brusco
- Hospital de Clínicas “José de San Martín”, Universidad de Buenos Aires, Buenos Aires, Argentina
- Servicio de Clínica Médica, Hospital Argerich, Buenos Aires, Argentina
- CONICET, Buenos Aires, Argentina
| | | | - Daniel P Cardinali
- Facultad de Ciencias Médicas, Universidad Católica Argentina, Buenos Aires, Argentina
| | - Daniel E Vigo
- Laboratory of Chronophysiology, Institute for Biomedical Research (BIOMED), Pontifical Catholic University of Argentina (UCA) and CONICET, Buenos Aires, Argentina
- Faculty of Psychology and Educational Sciences, Katholieke Universiteit Leuven, Leuven, Belgium
- Correspondence: Daniel E Vigo, Instituto de Investigaciones Biomédicas, Pontificia Universidad Católica Argentina, Alicia Moreau de Justo 1500, 4° piso, Buenos Aires, C1107AAZ, Argentina, Tel +54 0810-2200-822 ext 1152, Email ;
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Association between heart rate variability and striatal dopamine depletion in Parkinson's disease. J Neural Transm (Vienna) 2021; 128:1835-1840. [PMID: 34559319 DOI: 10.1007/s00702-021-02418-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/10/2021] [Indexed: 10/20/2022]
Abstract
Striatal dopamine depletion is associated with not only motor symptom but also non-motor symptoms in patients with Parkinson's disease (PD). The purpose is to elucidate the relation between heart rate variability (HRV) and dopaminergic depletion in specific striatal subregions. The subjects were 84 patients with newly diagnosed untreated PD. All patients underwent striatal 123I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane (123I-FP-CIT) dopamine transporter single-photon emission computed tomography (DAT-SPECT). DaTQUANT software (GE Healthcare) was used as a semi-quantitative tool to analyze DAT-SPECT data. Association of HRV with dopaminergic depletion in specific striatal subregions was examined. HRV was related to dopamine depletion in the caudate and anterior putamen, especially the left side, after controlling for age, hemoglobin A1c level, disease duration, motor severity and global cognition on multiple regression analysis (left caudate p = 0.012). HRV was closely related to striatal dopamine depletion, especially in the left associative striatum, in patients with PD.
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