Table Info

Table 1.

Human immunophenotyping standard panels. This table lists the combination of markers frequently used to analyze different immune cells populations

Parental populations	Parental markers	Subpopulation	Subpopulation markers	Ref.
CD4 T cells	CD3⁺/CD20^–/CD8⁻/CD4⁺	Naive	CCR7⁺/CD45RA⁺	[18, 19]
		Central memory	CCR7⁺/CD45RA⁻
		Terminal effector	CCR7⁻/CD45RA⁺
		Effector memory	CCR7⁻/CD45RA⁻
		Treg	CD127^low/CD25^Hi/CCR4⁺
		Th1	CD25^low/−/CXCR5⁻/CD45RA⁻/CXCR3⁺/CCR6⁻	[19]
		Th2	CD45RA^–/CCR4⁺/CCR6^–/CXCR3⁺	[20]
		Th1Th17	CD45RA^–/CCR4^–/CCR6⁺/CXCR3⁺	[20]
		Th17	CD25^low/−/CXCR5⁻/CD45RA⁻/CXCR3⁻/CCR6⁺	[19]
		Th22	CD194⁺/CD196⁺/CCR10⁺	[21]
CD8 T cells	CD3⁺/CD20^–/CD8⁺/CD4^–	Naive	CCR7⁺/CD45RA⁺	[18, 19, 22]
		Central memory	CCR7⁺/CD45RA⁻
		Terminal effector	CCR7⁻/CD45RA⁺
		Effector memory	CCR7⁻/CD45RA⁻
Unconventional T cells	CD3⁺/CD20^–	NKT cells	TCRVα24JαQ⁺	[19]
		MAIT cells	CD161⁺/TCRVα7.2⁺
		γδ T cells	TCRVαβ⁻/TCRVγδ⁺
NK cells	CD3⁻/CD56⁺	-	-	[19]
Granulocytes	CD45⁺/CD3^–/CD19^–	Neutrophils	CD16⁺	[23]
		Basophils	CD123⁺/HLA-DR^–
		Eosinophils	CD16^–
B cells	CD3^–/CD20⁺	Transitional	CD10⁺/CD27⁻	[19]
		Naive	CD27⁻/CD10⁻
		Memory	CD27⁺/CD10⁻
Monocytes	CD45⁺/CD3^–/CD19^–/CD123^–/HLA-DR⁺/CD11c⁺	Classical	CD14⁺CD16^–	[23]
		Intermediate	CD14⁺CD16⁺
		Non-classical	CD14^–CD16⁺
Dendritic cells	CD45⁺/CD3^–/CD19^–	Myeloid	CD123^–CD11c⁺/CD16^–CD14^–/HLA-DR⁺⁺	[23]
Dendritic cells	CD45⁺/CD3^–/CD19^–	Plasmacytoid	CD123⁺/HLA-DR⁺	[23]

CCR7: C-C chemokine receptor type 7; CXCR5: C-X-C motif chemokine receptor 5; HLA: human leucocyte antigen; MAIT: mucosal-associated invariant T; Th1: T helper 1; Treg: regulatory T cell; -: none

Declarations

Author contributions

ACS: Writing—original draft. DEDZS: Writing—original draft, Writing—review & editing. ASZ, GMC, and ABG: Writing—review & editing. MIL: Conceptualization, Writing—review & editing, Supervision. MVP: Conceptualization, Writing—original draft, Writing—review & editing, Supervision. All authors contributed to the manuscript revision, and read and approved the submitted version.

Conflicts of interest

The authors declare that they have no conflicts of interest.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publication

Not applicable.

Availability of data and materials

Not applicable.

Funding

This work was supported by grants from the Instituto de Salud Carlos III cofounded by Fondo Europeo de Desarrollo Regional (FEDER), contract numbers: [PI21/01248], [PI19-00883], [PT 20/00127], [UMA18-FEDERJA-194], [PY18-3364]; and grants from Consejería de Salud de Andalucía cofounded by FEDER, contract number: [PEMP-0127-2020]. Marina Villanueva-Paz holds a Sara Borrell [CD21/00198] research contract from Instituto de Salud Carlos III (ISCIII) and Consejería de Salud de Andalucía. Alejandro Cueto-Sánchez holds an i-PFIS: Doctorados IIS-empresa en Ciencias y Tecnologías de la Salud [IFI18/00047] research contract from ISCIII. Daniel E. Di Zeo-Sánchez holds an i-PFIS: Doctorados IIS-empresa en Ciencias y Tecnologías de la Salud [IFI21/00034] research contract from ISCIII. Gonzalo Matilla-Cabello holds a Garantía Juvenil [SNGJ5Y6-09] research contract with Junta de Andalucía and the European Social Fund. Antonio Segovia-Zafra holds a Jaume Bosch Training Action 2022 from Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas (CIBEREHD). Ana Bodoque-García holds a Garantía Juvenil [POEJ-00041-IBIMA] research contract from Junta de Andalucía and the European Social Fund. Spanish Clinical Research Network (SCReN) and CIBEREHD are funded by ISCIII. This publication is based on work from COST Action ‘CA17112—Prospective European Drug-Induced Liver Injury Network’ supported by COST (European Cooperation in Science and Technology), www.cost.eu. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright

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