Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis
Abstract This narrative review examines the utility of gait digital biomarkers in Parkinson’s disease (PD) research and clinical trials across four contexts: disease susceptibility/risk, disease progression, response to exercise, and fall prediction. The review of the literature to date suggests tha...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-03-01
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| Series: | npj Parkinson's Disease |
| Online Access: | https://doi.org/10.1038/s41531-025-00897-1 |
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| author | Martina Mancini Mitra Afshari Quincy Almeida Sommer Amundsen-Huffmaster Katherine Balfany Richard Camicioli Cory Christiansen Marian L. Dale Leland E. Dibble Gammon M. Earhart Terry D. Ellis Garett J. Griffith Madeleine E. Hackney Jammie Hopkins Fay B. Horak Kelvin E. Jones Leah Ling Joan A. O’Keefe Kimberly Kwei Genevieve Olivier Ashwini K. Rao Anjali Sivaramakrishnan Daniel M. Corcos |
| author_facet | Martina Mancini Mitra Afshari Quincy Almeida Sommer Amundsen-Huffmaster Katherine Balfany Richard Camicioli Cory Christiansen Marian L. Dale Leland E. Dibble Gammon M. Earhart Terry D. Ellis Garett J. Griffith Madeleine E. Hackney Jammie Hopkins Fay B. Horak Kelvin E. Jones Leah Ling Joan A. O’Keefe Kimberly Kwei Genevieve Olivier Ashwini K. Rao Anjali Sivaramakrishnan Daniel M. Corcos |
| author_sort | Martina Mancini |
| collection | DOAJ |
| description | Abstract This narrative review examines the utility of gait digital biomarkers in Parkinson’s disease (PD) research and clinical trials across four contexts: disease susceptibility/risk, disease progression, response to exercise, and fall prediction. The review of the literature to date suggests that upper body characteristics of gait (e.g., arm swing, trunk motion) may indicate susceptibility/risk of PD, while pace aspects (e.g., gait speed, stride length) are informative for tracking disease progression, exercise response, and fall likelihood. Dynamic stability aspects (e.g., trunk regularity, double-support time) worsen with disease progression but can improve with exercise. Gait variability emerges as a sensitive biomarker across all 4 contexts but with low specificity. The lack of standardized gait testing protocols and the lack of a minimum set of quantified digital gait biomarkers limit data harmonization across studies. Future studies, using a commonly agreed upon protocol, could be used to demonstrate the utility of specific gait biomarkers for clinical practice. |
| format | Article |
| id | doaj-art-21d2f196287d4383bfbb6d9f39629518 |
| institution | DOAJ |
| issn | 2373-8057 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Parkinson's Disease |
| spelling | doaj-art-21d2f196287d4383bfbb6d9f396295182025-08-20T02:51:24ZengNature Portfolionpj Parkinson's Disease2373-80572025-03-0111111810.1038/s41531-025-00897-1Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosisMartina Mancini0Mitra Afshari1Quincy Almeida2Sommer Amundsen-Huffmaster3Katherine Balfany4Richard Camicioli5Cory Christiansen6Marian L. Dale7Leland E. Dibble8Gammon M. Earhart9Terry D. Ellis10Garett J. Griffith11Madeleine E. Hackney12Jammie Hopkins13Fay B. Horak14Kelvin E. Jones15Leah Ling16Joan A. O’Keefe17Kimberly Kwei18Genevieve Olivier19Ashwini K. Rao20Anjali Sivaramakrishnan21Daniel M. Corcos22Department of Neurology, Oregon Health & Science UniversityDepartment of Neurology and Rehabilitation, University of Illinois at ChicagoCarespace Health & WellnessDepartment of Neurology, University of MinnesotaDepartment of Physical Medicine & Rehabilitation, University of ColoradoDepartment of Medicine (Neurology) and Neuroscience and Mental Health Institute, University of AlbertaDepartment of Physical Medicine & Rehabilitation, University of ColoradoDepartment of Neurology, Oregon Health & Science UniversityDepartment of Physical Therapy & Athletic Training, University of UtahProgram in Physical Therapy, Washington University School of Medicine in St. LouisDepartment of Physical Therapy, Boston UniversityDepartment of Physical Therapy & Human Movement Sciences, Northwestern UniversityEmory University School of Medicine, Department of Medicine, Division of Geriatrics and GerontologyDepartment of Community Health and Preventive Medicine, Morehouse School of MedicineDepartment of Neurology, Oregon Health & Science UniversityDepartment of Medicine, Faculty of Kinesiology, Sport, & Recreation and Neuroscience and Mental Health Institute, University of AlbertaDepartment of Physical Therapy & Athletic Training, University of UtahDepartments of Anatomy & Cell Biology and Neurological Sciences, Rush University Medical CenterDepartment of Rehabilitation & Regenerative Medicine (Programs in Physical Therapy), and GH Sergievsky Center, Columbia UniversityDepartment of Physical Therapy & Athletic Training, University of UtahDepartment of Rehabilitation & Regenerative Medicine (Programs in Physical Therapy), and GH Sergievsky Center, Columbia UniversityDepartment of Physical Therapy at the School of Health Professions at UT Health San AntonioDepartment of Physical Therapy & Human Movement Sciences, Northwestern UniversityAbstract This narrative review examines the utility of gait digital biomarkers in Parkinson’s disease (PD) research and clinical trials across four contexts: disease susceptibility/risk, disease progression, response to exercise, and fall prediction. The review of the literature to date suggests that upper body characteristics of gait (e.g., arm swing, trunk motion) may indicate susceptibility/risk of PD, while pace aspects (e.g., gait speed, stride length) are informative for tracking disease progression, exercise response, and fall likelihood. Dynamic stability aspects (e.g., trunk regularity, double-support time) worsen with disease progression but can improve with exercise. Gait variability emerges as a sensitive biomarker across all 4 contexts but with low specificity. The lack of standardized gait testing protocols and the lack of a minimum set of quantified digital gait biomarkers limit data harmonization across studies. Future studies, using a commonly agreed upon protocol, could be used to demonstrate the utility of specific gait biomarkers for clinical practice.https://doi.org/10.1038/s41531-025-00897-1 |
| spellingShingle | Martina Mancini Mitra Afshari Quincy Almeida Sommer Amundsen-Huffmaster Katherine Balfany Richard Camicioli Cory Christiansen Marian L. Dale Leland E. Dibble Gammon M. Earhart Terry D. Ellis Garett J. Griffith Madeleine E. Hackney Jammie Hopkins Fay B. Horak Kelvin E. Jones Leah Ling Joan A. O’Keefe Kimberly Kwei Genevieve Olivier Ashwini K. Rao Anjali Sivaramakrishnan Daniel M. Corcos Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis npj Parkinson's Disease |
| title | Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis |
| title_full | Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis |
| title_fullStr | Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis |
| title_full_unstemmed | Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis |
| title_short | Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis |
| title_sort | digital gait biomarkers in parkinson s disease susceptibility risk progression response to exercise and prognosis |
| url | https://doi.org/10.1038/s41531-025-00897-1 |
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