{"doi":"10.1093/infdis/jiae091","title":"Vδ1 Effector and Vδ2 γδ T-Cell Subsets Shift in Frequency and Are Linked to Plasma Inflammatory Markers During Antiretroviral Therapy-Suppressed HIV Infection","abstract":"BACKGROUND: Chronic inflammation is prevalent with antiretroviral therapy (ART)-suppressed human immunodeficiency virus (HIV) infection and one immune cell subset putatively driving this phenomenon is TIGIT+ γδ T cells. METHODS: To elucidate γδ T-cell phenotypic diversity, spectral flow cytometry was performed on blood lymphocytes from individuals of a HIV and aging cohort and data were analyzed using bioinformatic platforms. Plasma inflammatory markers were measured and correlated with γδ T-cell subset frequencies. RESULTS: Thirty-nine distinct γδ T-cell subsets were identified (22 Vδ1+, 14 Vδ2+, and 3 Vδ1-Vδ2-Vγ9+) and TIGIT was nearly exclusively found on the Vδ1+CD45RA+CD27- effector populations. People with ART-suppressed HIV infection (PWH) exhibited high frequencies of distinct clusters of Vδ1+ effectors distinguished via CD8, CD16, and CD38 expression. Among Vδ2+ cells, most Vγ9+ (innate-like) clusters were lower in PWH; however, CD27+ subsets were similar in frequency between participants with and without HIV. Comparisons by age revealed lower 'naive' Vδ1+CD45RA+CD27+ cells in older individuals, regardless of HIV status. Plasma inflammatory markers were selectively linked to subsets of Vδ1+ and Vδ2+ cells. CONCLUSIONS: These results further elucidate γδ T-cell subset complexity and reveal distinct alterations and connections with inflammatory pathways of Vδ1+ effector and Vδ2+ innate-like subsets during ART-suppressed HIV infection.","journal":"The Journal of Infectious Diseases","year":2024,"id":452915,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9265,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1275098,"name":"Erika L. Smith-Mahoney","orcid":"0000-0001-5104-8483","position":1,"is_corresponding":false},{"id":296035,"name":"Alex Olson","orcid":"0000-0002-3371-3213","position":2,"is_corresponding":false},{"id":439450,"name":"Rachel R. Yuen","orcid":"0000-0001-8272-9185","position":3,"is_corresponding":false},{"id":446832,"name":"Archana Asundi","orcid":"0000-0003-3910-909X","position":4,"is_corresponding":false},{"id":312539,"name":"Nina Lin","orcid":"0000-0002-4913-0442","position":5,"is_corresponding":false},{"id":110438,"name":"Anna C. Belkina","orcid":"0000-0001-7967-6254","position":6,"is_corresponding":false},{"id":110434,"name":"Jennifer Snyder‐Cappione","orcid":"0000-0002-0941-5582","position":7,"is_corresponding":false},{"id":110437,"name":"Riley M.F. Pihl","orcid":"0000-0002-6160-5324","position":0,"is_corresponding":true}],"reference_count":51,"raw_metadata":null,"created_at":"2026-07-19T02:02:54.415477Z","pmid":"38390982","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}