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Herpes simplex virus-2 genital tract shedding is not predictable over months or years in infected persons.

Dhankani V, Kutz JN, Schiffer JT - PLoS Comput. Biol. (2014)

Bottom Line: Empirical and model-derived, time-series data gathered over >30 days consists of multiple complex episodes that could not be reduced to a manageable number of descriptive features with PCA and SVD.However, single HSV-2 shedding episodes, even those with prolonged duration and complex morphologies consisting of multiple erratic peaks, were consistently described using a maximum of four dominant features.These findings suggest that HSV-2 shedding patterns within an individual are impossible to predict over weeks or months, and that even highly complex single HSV-2 episodes can only be partially predicted based on spatial distribution of immune cell density.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.

ABSTRACT
Herpes simplex virus-2 (HSV-2) is a chronic reactivating infection that leads to recurrent shedding episodes in the genital tract. A minority of episodes are prolonged, and associated with development of painful ulcers. However, currently, available tools poorly predict viral trajectories and timing of reactivations in infected individuals. We employed principal components analysis (PCA) and singular value decomposition (SVD) to interpret HSV-2 genital tract shedding time series data, as well as simulation output from a stochastic spatial mathematical model. Empirical and model-derived, time-series data gathered over >30 days consists of multiple complex episodes that could not be reduced to a manageable number of descriptive features with PCA and SVD. However, single HSV-2 shedding episodes, even those with prolonged duration and complex morphologies consisting of multiple erratic peaks, were consistently described using a maximum of four dominant features. Modeled and clinical episodes had equivalent distributions of dominant features, implying similar dynamics in real and simulated episodes. We applied linear discriminant analysis (LDA) to simulation output and identified that local immune cell density at the viral reactivation site had a predictive effect on episode duration, though longer term shedding suggested chaotic dynamics and could not be predicted based on spatial patterns of immune cell density. These findings suggest that HSV-2 shedding patterns within an individual are impossible to predict over weeks or months, and that even highly complex single HSV-2 episodes can only be partially predicted based on spatial distribution of immune cell density.

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Results of Singular Value Decomposition on longitudinal data that captured multiple diverse episodes.Left column shows representative shedding curves from single patients: (a) Clinical data (swabs every 24 hours for 60 days), (b) Clinical data (swabs every 6 hours for 60 days), and (c) Modeled data (swabs every 15 minutes for 60 days). Right column (d,e,f) shows plots of singular values for the corresponding datasets (100, 25 and 98 patients, respectively). For all the three datasets, the most dominant features accounted for a very small percentage (13.5, 18.2, and 9.7 respectively) of the total variance of the system, and were closely followed by other features with gradually declining variances, making dimensional reduction infeasible. Red and orange bars indicate number of modes at which a total of 50% and 90% variance is achieved.
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pcbi-1003922-g001: Results of Singular Value Decomposition on longitudinal data that captured multiple diverse episodes.Left column shows representative shedding curves from single patients: (a) Clinical data (swabs every 24 hours for 60 days), (b) Clinical data (swabs every 6 hours for 60 days), and (c) Modeled data (swabs every 15 minutes for 60 days). Right column (d,e,f) shows plots of singular values for the corresponding datasets (100, 25 and 98 patients, respectively). For all the three datasets, the most dominant features accounted for a very small percentage (13.5, 18.2, and 9.7 respectively) of the total variance of the system, and were closely followed by other features with gradually declining variances, making dimensional reduction infeasible. Red and orange bars indicate number of modes at which a total of 50% and 90% variance is achieved.

Mentions: In order to identify fundamental dynamic patterns of HSV-2 infection, we applied Singular Value Decomposition (SVD) on shedding time series data that captured multiple diverse episodes of HSV-2 reactivation. HSV-2 infection is notable for frequent, heterogeneous spikes, or episodes, of shedding. Figure 1 shows representative shedding curves (left column) from two datasets: (1a) Clinical data (100 patients, every 24 hour swabs for 60 days, [7], [13]) and (b) Clinical data (25 patients, every 6 hour swabs for 60 days, [14]). Each episode has a unique morphology, peak viral load and duration, but shares the characteristics of rapid viral expansion and clearance [14]). Prolonged episodes persist due to viral re-expansion following a short clearance phase.


Herpes simplex virus-2 genital tract shedding is not predictable over months or years in infected persons.

Dhankani V, Kutz JN, Schiffer JT - PLoS Comput. Biol. (2014)

Results of Singular Value Decomposition on longitudinal data that captured multiple diverse episodes.Left column shows representative shedding curves from single patients: (a) Clinical data (swabs every 24 hours for 60 days), (b) Clinical data (swabs every 6 hours for 60 days), and (c) Modeled data (swabs every 15 minutes for 60 days). Right column (d,e,f) shows plots of singular values for the corresponding datasets (100, 25 and 98 patients, respectively). For all the three datasets, the most dominant features accounted for a very small percentage (13.5, 18.2, and 9.7 respectively) of the total variance of the system, and were closely followed by other features with gradually declining variances, making dimensional reduction infeasible. Red and orange bars indicate number of modes at which a total of 50% and 90% variance is achieved.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4222642&req=5

pcbi-1003922-g001: Results of Singular Value Decomposition on longitudinal data that captured multiple diverse episodes.Left column shows representative shedding curves from single patients: (a) Clinical data (swabs every 24 hours for 60 days), (b) Clinical data (swabs every 6 hours for 60 days), and (c) Modeled data (swabs every 15 minutes for 60 days). Right column (d,e,f) shows plots of singular values for the corresponding datasets (100, 25 and 98 patients, respectively). For all the three datasets, the most dominant features accounted for a very small percentage (13.5, 18.2, and 9.7 respectively) of the total variance of the system, and were closely followed by other features with gradually declining variances, making dimensional reduction infeasible. Red and orange bars indicate number of modes at which a total of 50% and 90% variance is achieved.
Mentions: In order to identify fundamental dynamic patterns of HSV-2 infection, we applied Singular Value Decomposition (SVD) on shedding time series data that captured multiple diverse episodes of HSV-2 reactivation. HSV-2 infection is notable for frequent, heterogeneous spikes, or episodes, of shedding. Figure 1 shows representative shedding curves (left column) from two datasets: (1a) Clinical data (100 patients, every 24 hour swabs for 60 days, [7], [13]) and (b) Clinical data (25 patients, every 6 hour swabs for 60 days, [14]). Each episode has a unique morphology, peak viral load and duration, but shares the characteristics of rapid viral expansion and clearance [14]). Prolonged episodes persist due to viral re-expansion following a short clearance phase.

Bottom Line: Empirical and model-derived, time-series data gathered over >30 days consists of multiple complex episodes that could not be reduced to a manageable number of descriptive features with PCA and SVD.However, single HSV-2 shedding episodes, even those with prolonged duration and complex morphologies consisting of multiple erratic peaks, were consistently described using a maximum of four dominant features.These findings suggest that HSV-2 shedding patterns within an individual are impossible to predict over weeks or months, and that even highly complex single HSV-2 episodes can only be partially predicted based on spatial distribution of immune cell density.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.

ABSTRACT
Herpes simplex virus-2 (HSV-2) is a chronic reactivating infection that leads to recurrent shedding episodes in the genital tract. A minority of episodes are prolonged, and associated with development of painful ulcers. However, currently, available tools poorly predict viral trajectories and timing of reactivations in infected individuals. We employed principal components analysis (PCA) and singular value decomposition (SVD) to interpret HSV-2 genital tract shedding time series data, as well as simulation output from a stochastic spatial mathematical model. Empirical and model-derived, time-series data gathered over >30 days consists of multiple complex episodes that could not be reduced to a manageable number of descriptive features with PCA and SVD. However, single HSV-2 shedding episodes, even those with prolonged duration and complex morphologies consisting of multiple erratic peaks, were consistently described using a maximum of four dominant features. Modeled and clinical episodes had equivalent distributions of dominant features, implying similar dynamics in real and simulated episodes. We applied linear discriminant analysis (LDA) to simulation output and identified that local immune cell density at the viral reactivation site had a predictive effect on episode duration, though longer term shedding suggested chaotic dynamics and could not be predicted based on spatial patterns of immune cell density. These findings suggest that HSV-2 shedding patterns within an individual are impossible to predict over weeks or months, and that even highly complex single HSV-2 episodes can only be partially predicted based on spatial distribution of immune cell density.

Show MeSH
Related in: MedlinePlus