Limits...
Multidimensional Clusters of CD4+ T Cell Dysfunction Are Primarily Associated with the CD4/CD8 Ratio in Chronic HIV Infection.

Frederiksen J, Buggert M, Noyan K, Nowak P, Sönnerborg A, Lund O, Karlsson AC - PLoS ONE (2015)

Bottom Line: HIV infection provokes a myriad of pathological effects on the immune system where many markers of CD4+ T cell dysfunction have been identified.In order to reduce the subjectivity of FLOCK, we developed an "artificial reference", using 2% of all CD4+ gated T cells from each of the HIV-infected individuals.Principle component analyses demonstrated that using an artificial reference lead to a better separation of the HIV-infected individuals from the healthy controls as compared to using a single HIV-infected subject as a reference or analyzing data manually.

View Article: PubMed Central - PubMed

Affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.

ABSTRACT
HIV infection provokes a myriad of pathological effects on the immune system where many markers of CD4+ T cell dysfunction have been identified. However, most studies to date have focused on single/double measurements of immune dysfunction, while the identification of pathological CD4+ T cell clusters that is highly associated to a specific biomarker for HIV disease remain less studied. Here, multi-parametric flow cytometry was used to investigate immune activation, exhaustion, and senescence of diverse maturation phenotypes of CD4+ T cells. The traditional method of manual data analysis was compared to a multidimensional clustering tool, FLOw Clustering with K (FLOCK) in two cohorts of 47 untreated HIV-infected individuals and 21 age and sex matched healthy controls. In order to reduce the subjectivity of FLOCK, we developed an "artificial reference", using 2% of all CD4+ gated T cells from each of the HIV-infected individuals. Principle component analyses demonstrated that using an artificial reference lead to a better separation of the HIV-infected individuals from the healthy controls as compared to using a single HIV-infected subject as a reference or analyzing data manually. Multiple correlation analyses between laboratory parameters and pathological CD4+ clusters revealed that the CD4/CD8 ratio was the preeminent surrogate marker of CD4+ T cells dysfunction using all three methods. Increased frequencies of an early-differentiated CD4+ T cell cluster with high CD38, HLA-DR and PD-1 expression were best correlated (Rho = -0.80, P value = 1.96×10-11) with HIV disease progression as measured by the CD4/CD8 ratio. The novel approach described here can be used to identify cell clusters that distinguish healthy from HIV infected subjects and is biologically relevant for HIV disease progression. These results further emphasize that a simple measurement of the CD4/CD8 ratio is a useful biomarker for assessment of combined CD4+ T cell dysfunction in chronic HIV disease.

No MeSH data available.


Related in: MedlinePlus

Flow cytometry gating and FLOCK populations.The manual gating strategy used to gate for the CD4+ T cells is shown in the top panel (A). The CD4+ T cell events were uploaded to immPort (immport.niaid.nih.gov) for FLOCK analysis. The unique populations identified by FLOCK using the single HIV reference (bottom left) (B) and artificial reference (top right) (C) is shown. The artificial reference is made-up of 2% of the CD4+ T cells from each subject in the HIV cohort, where as the single HIV reference is made-up of the CD4+ T cells from a single individual from the HIV cohort that appeared to be biologically representative of the cohort.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4581870&req=5

pone.0137635.g001: Flow cytometry gating and FLOCK populations.The manual gating strategy used to gate for the CD4+ T cells is shown in the top panel (A). The CD4+ T cell events were uploaded to immPort (immport.niaid.nih.gov) for FLOCK analysis. The unique populations identified by FLOCK using the single HIV reference (bottom left) (B) and artificial reference (top right) (C) is shown. The artificial reference is made-up of 2% of the CD4+ T cells from each subject in the HIV cohort, where as the single HIV reference is made-up of the CD4+ T cells from a single individual from the HIV cohort that appeared to be biologically representative of the cohort.

Mentions: FLOCK was used for automated population (cluster) identification to analyze an eight-parameter dataset of HIV+ and healthy control subjects. The eight measured parameters were selected to give an overview of the activation (CD38, HLA-DR), exhaustion (PD-1, Tim-3), senescence (CD28, CD57) and memory differentiation (CD45RO, CD27) status of CD4+ T cells. A traditional gating strategy for isolating CD4+ T cells were performed on the multiparametric flow cytometry data set prior to FLOCK data examination (Fig 1A). Thereafter, FLOCK analyses were performed on all of the HIV-infected subjects, where the number of clusters automatically identified by FLOCK differed between the subjects, ranging from 12–23 clusters. In the interest of being able to compare the data, a reference subject that identified the biologically relevant cell clusters was chosen and the centroids of these clusters were then applied to the remaining healthy controls and HIV-infected subjects. The unique clusters identified in the eight-dimensional space for the representative subject is shown in Fig 1B.


Multidimensional Clusters of CD4+ T Cell Dysfunction Are Primarily Associated with the CD4/CD8 Ratio in Chronic HIV Infection.

Frederiksen J, Buggert M, Noyan K, Nowak P, Sönnerborg A, Lund O, Karlsson AC - PLoS ONE (2015)

Flow cytometry gating and FLOCK populations.The manual gating strategy used to gate for the CD4+ T cells is shown in the top panel (A). The CD4+ T cell events were uploaded to immPort (immport.niaid.nih.gov) for FLOCK analysis. The unique populations identified by FLOCK using the single HIV reference (bottom left) (B) and artificial reference (top right) (C) is shown. The artificial reference is made-up of 2% of the CD4+ T cells from each subject in the HIV cohort, where as the single HIV reference is made-up of the CD4+ T cells from a single individual from the HIV cohort that appeared to be biologically representative of the cohort.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4581870&req=5

pone.0137635.g001: Flow cytometry gating and FLOCK populations.The manual gating strategy used to gate for the CD4+ T cells is shown in the top panel (A). The CD4+ T cell events were uploaded to immPort (immport.niaid.nih.gov) for FLOCK analysis. The unique populations identified by FLOCK using the single HIV reference (bottom left) (B) and artificial reference (top right) (C) is shown. The artificial reference is made-up of 2% of the CD4+ T cells from each subject in the HIV cohort, where as the single HIV reference is made-up of the CD4+ T cells from a single individual from the HIV cohort that appeared to be biologically representative of the cohort.
Mentions: FLOCK was used for automated population (cluster) identification to analyze an eight-parameter dataset of HIV+ and healthy control subjects. The eight measured parameters were selected to give an overview of the activation (CD38, HLA-DR), exhaustion (PD-1, Tim-3), senescence (CD28, CD57) and memory differentiation (CD45RO, CD27) status of CD4+ T cells. A traditional gating strategy for isolating CD4+ T cells were performed on the multiparametric flow cytometry data set prior to FLOCK data examination (Fig 1A). Thereafter, FLOCK analyses were performed on all of the HIV-infected subjects, where the number of clusters automatically identified by FLOCK differed between the subjects, ranging from 12–23 clusters. In the interest of being able to compare the data, a reference subject that identified the biologically relevant cell clusters was chosen and the centroids of these clusters were then applied to the remaining healthy controls and HIV-infected subjects. The unique clusters identified in the eight-dimensional space for the representative subject is shown in Fig 1B.

Bottom Line: HIV infection provokes a myriad of pathological effects on the immune system where many markers of CD4+ T cell dysfunction have been identified.In order to reduce the subjectivity of FLOCK, we developed an "artificial reference", using 2% of all CD4+ gated T cells from each of the HIV-infected individuals.Principle component analyses demonstrated that using an artificial reference lead to a better separation of the HIV-infected individuals from the healthy controls as compared to using a single HIV-infected subject as a reference or analyzing data manually.

View Article: PubMed Central - PubMed

Affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.

ABSTRACT
HIV infection provokes a myriad of pathological effects on the immune system where many markers of CD4+ T cell dysfunction have been identified. However, most studies to date have focused on single/double measurements of immune dysfunction, while the identification of pathological CD4+ T cell clusters that is highly associated to a specific biomarker for HIV disease remain less studied. Here, multi-parametric flow cytometry was used to investigate immune activation, exhaustion, and senescence of diverse maturation phenotypes of CD4+ T cells. The traditional method of manual data analysis was compared to a multidimensional clustering tool, FLOw Clustering with K (FLOCK) in two cohorts of 47 untreated HIV-infected individuals and 21 age and sex matched healthy controls. In order to reduce the subjectivity of FLOCK, we developed an "artificial reference", using 2% of all CD4+ gated T cells from each of the HIV-infected individuals. Principle component analyses demonstrated that using an artificial reference lead to a better separation of the HIV-infected individuals from the healthy controls as compared to using a single HIV-infected subject as a reference or analyzing data manually. Multiple correlation analyses between laboratory parameters and pathological CD4+ clusters revealed that the CD4/CD8 ratio was the preeminent surrogate marker of CD4+ T cells dysfunction using all three methods. Increased frequencies of an early-differentiated CD4+ T cell cluster with high CD38, HLA-DR and PD-1 expression were best correlated (Rho = -0.80, P value = 1.96×10-11) with HIV disease progression as measured by the CD4/CD8 ratio. The novel approach described here can be used to identify cell clusters that distinguish healthy from HIV infected subjects and is biologically relevant for HIV disease progression. These results further emphasize that a simple measurement of the CD4/CD8 ratio is a useful biomarker for assessment of combined CD4+ T cell dysfunction in chronic HIV disease.

No MeSH data available.


Related in: MedlinePlus