Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral Infection
Neurological dysfunction following viral infection varies among individuals, largely due to differences in their genetic backgrounds. Gait patterns, which can be evaluated using measures of coordination, balance, posture, muscle function, step-to-step variability, and other factors, are also influen...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
|
| Series: | International Journal of Molecular Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1422-0067/24/3/2843 |
| _version_ | 1797624232513896448 |
|---|---|
| author | Moumita Karmakar Aracely A. Pérez Gómez Raymond J. Carroll Koedi S. Lawley Katia A. Z. Amstalden C. Jane Welsh David W. Threadgill Candice Brinkmeyer-Langford |
| author_facet | Moumita Karmakar Aracely A. Pérez Gómez Raymond J. Carroll Koedi S. Lawley Katia A. Z. Amstalden C. Jane Welsh David W. Threadgill Candice Brinkmeyer-Langford |
| author_sort | Moumita Karmakar |
| collection | DOAJ |
| description | Neurological dysfunction following viral infection varies among individuals, largely due to differences in their genetic backgrounds. Gait patterns, which can be evaluated using measures of coordination, balance, posture, muscle function, step-to-step variability, and other factors, are also influenced by genetic background. Accordingly, to some extent gait can be characteristic of an individual, even prior to changes in neurological function. Because neuromuscular aspects of gait are under a certain degree of genetic control, the hypothesis tested was that gait parameters could be predictive of neuromuscular dysfunction following viral infection. The Collaborative Cross (CC) mouse resource was utilized to model genetically diverse populations and the DigiGait treadmill system used to provide quantitative and objective measurements of 131 gait parameters in 142 mice from 23 CC and SJL/J strains. DigiGait measurements were taken prior to infection with the neurotropic virus Theiler’s Murine Encephalomyelitis Virus (TMEV). Neurological phenotypes were recorded over 90 days post-infection (d.p.i.), and the cumulative frequency of the observation of these phenotypes was statistically associated with discrete baseline DigiGait measurements. These associations represented spatial and postural aspects of gait influenced by the 90 d.p.i. phenotype score. Furthermore, associations were found between these gait parameters with sex and outcomes considered to show resistance, resilience, or susceptibility to severe neurological symptoms after long-term infection. For example, higher pre-infection measurement values for the Paw Drag parameter corresponded with greater disease severity at 90 d.p.i. Quantitative trait loci significantly associated with these DigiGait parameters revealed potential relationships between 28 differentially expressed genes (DEGs) and different aspects of gait influenced by viral infection. Thus, these potential candidate genes and genetic variations may be predictive of long-term neurological dysfunction. Overall, these findings demonstrate the predictive/prognostic value of quantitative and objective pre-infection DigiGait measurements for viral-induced neuromuscular dysfunction. |
| first_indexed | 2024-03-11T09:40:02Z |
| format | Article |
| id | doaj.art-87a0db1752f24c4eacf41b8f68bed695 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-11T09:40:02Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-87a0db1752f24c4eacf41b8f68bed6952023-11-16T17:03:14ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-02-01243284310.3390/ijms24032843Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral InfectionMoumita Karmakar0Aracely A. Pérez Gómez1Raymond J. Carroll2Koedi S. Lawley3Katia A. Z. Amstalden4C. Jane Welsh5David W. Threadgill6Candice Brinkmeyer-Langford7Department of Statistics, College of Science, Texas A & M University, College Station, TX 77843, USADepartment of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A & M University, College Station, TX 77843, USADepartment of Statistics, College of Science, Texas A & M University, College Station, TX 77843, USADepartment of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A & M University, College Station, TX 77843, USADepartment of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A & M University, College Station, TX 77843, USADepartment of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A & M University, College Station, TX 77843, USADepartment of Molecular and Cellular Medicine, Texas A & M Health Science Center, Texas A & M University, College Station, TX 77843, USADepartment of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A & M University, College Station, TX 77843, USANeurological dysfunction following viral infection varies among individuals, largely due to differences in their genetic backgrounds. Gait patterns, which can be evaluated using measures of coordination, balance, posture, muscle function, step-to-step variability, and other factors, are also influenced by genetic background. Accordingly, to some extent gait can be characteristic of an individual, even prior to changes in neurological function. Because neuromuscular aspects of gait are under a certain degree of genetic control, the hypothesis tested was that gait parameters could be predictive of neuromuscular dysfunction following viral infection. The Collaborative Cross (CC) mouse resource was utilized to model genetically diverse populations and the DigiGait treadmill system used to provide quantitative and objective measurements of 131 gait parameters in 142 mice from 23 CC and SJL/J strains. DigiGait measurements were taken prior to infection with the neurotropic virus Theiler’s Murine Encephalomyelitis Virus (TMEV). Neurological phenotypes were recorded over 90 days post-infection (d.p.i.), and the cumulative frequency of the observation of these phenotypes was statistically associated with discrete baseline DigiGait measurements. These associations represented spatial and postural aspects of gait influenced by the 90 d.p.i. phenotype score. Furthermore, associations were found between these gait parameters with sex and outcomes considered to show resistance, resilience, or susceptibility to severe neurological symptoms after long-term infection. For example, higher pre-infection measurement values for the Paw Drag parameter corresponded with greater disease severity at 90 d.p.i. Quantitative trait loci significantly associated with these DigiGait parameters revealed potential relationships between 28 differentially expressed genes (DEGs) and different aspects of gait influenced by viral infection. Thus, these potential candidate genes and genetic variations may be predictive of long-term neurological dysfunction. Overall, these findings demonstrate the predictive/prognostic value of quantitative and objective pre-infection DigiGait measurements for viral-induced neuromuscular dysfunction.https://www.mdpi.com/1422-0067/24/3/2843Collaborative CrossTMEVgaitDigiGaitQTL |
| spellingShingle | Moumita Karmakar Aracely A. Pérez Gómez Raymond J. Carroll Koedi S. Lawley Katia A. Z. Amstalden C. Jane Welsh David W. Threadgill Candice Brinkmeyer-Langford Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral Infection International Journal of Molecular Sciences Collaborative Cross TMEV gait DigiGait QTL |
| title | Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral Infection |
| title_full | Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral Infection |
| title_fullStr | Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral Infection |
| title_full_unstemmed | Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral Infection |
| title_short | Baseline Gait and Motor Function Predict Long-Term Severity of Neurological Outcomes of Viral Infection |
| title_sort | baseline gait and motor function predict long term severity of neurological outcomes of viral infection |
| topic | Collaborative Cross TMEV gait DigiGait QTL |
| url | https://www.mdpi.com/1422-0067/24/3/2843 |
| work_keys_str_mv | AT moumitakarmakar baselinegaitandmotorfunctionpredictlongtermseverityofneurologicaloutcomesofviralinfection AT aracelyaperezgomez baselinegaitandmotorfunctionpredictlongtermseverityofneurologicaloutcomesofviralinfection AT raymondjcarroll baselinegaitandmotorfunctionpredictlongtermseverityofneurologicaloutcomesofviralinfection AT koedislawley baselinegaitandmotorfunctionpredictlongtermseverityofneurologicaloutcomesofviralinfection AT katiaazamstalden baselinegaitandmotorfunctionpredictlongtermseverityofneurologicaloutcomesofviralinfection AT cjanewelsh baselinegaitandmotorfunctionpredictlongtermseverityofneurologicaloutcomesofviralinfection AT davidwthreadgill baselinegaitandmotorfunctionpredictlongtermseverityofneurologicaloutcomesofviralinfection AT candicebrinkmeyerlangford baselinegaitandmotorfunctionpredictlongtermseverityofneurologicaloutcomesofviralinfection |