Adipose Tissue in Persons With HIV Is Enriched for CD4+ T Effector Memory and T Effector Memory RA+ Cells, Which Show Higher CD69 Expression and CD57, CX3CR1, GPR56 Co-expression With Increasing Glucose Intolerance

Celestine N Wanjalla, Wyatt J McDonnell, Louise Barnett, Joshua D Simmons, Briana D Furch, Morgan C Lima, Beverly O Woodward, Run Fan, Ye Fei, Paxton G Baker, Ramesh Ram, Mark A Pilkinton, Mona Mashayekhi, Nancy J Brown, Simon A Mallal, Spyros A Kalams, John R Koethe, Celestine N Wanjalla, Wyatt J McDonnell, Louise Barnett, Joshua D Simmons, Briana D Furch, Morgan C Lima, Beverly O Woodward, Run Fan, Ye Fei, Paxton G Baker, Ramesh Ram, Mark A Pilkinton, Mona Mashayekhi, Nancy J Brown, Simon A Mallal, Spyros A Kalams, John R Koethe

Abstract

Chronic T cell activation and accelerated immune senescence are hallmarks of HIV infection, which may contribute to the increased risk of cardiometabolic diseases in people living with HIV (PLWH). T lymphocytes play a central role in modulating adipose tissue inflammation and, by extension, adipocyte energy storage and release. Here, we assessed the CD4+ and CD8+ T cell profiles in the subcutaneous adipose tissue (SAT) and blood of non-diabetic (n = 9; fasting blood glucose [FBG] < 100 mg/dL), pre-diabetic (n = 8; FBG = 100-125 mg/dL) and diabetic (n = 9; FBG ≥ 126 mg/dL) PLWH, in addition to non- and pre-diabetic, HIV-negative controls (n = 8). SAT was collected by liposuction and T cells were extracted by collagenase digestion. The proportion of naïve (TNai) CD45RO-CCR7+, effector memory (TEM) CD45RO+CCR7-, central memory (TCM) CD45RO+CCR7+, and effector memory revertant RA+(TEMRA) CD45RO-CCR7- CD4+ and CD8+ T cells were measured by flow cytometry. CD4+ and CD8+ TEM and TEMRA were significantly enriched in SAT of PLWH compared to blood. The proportions of SAT CD4+ and CD8+ memory subsets were similar across metabolic status categories in the PLWH, but CD4+ T cell expression of the CD69 early-activation and tissue residence marker, particularly on TEM cells, increased with progressive glucose intolerance. Use of t-distributed Stochastic Neighbor Embedding (t-SNE) identified a separate group of predominantly CD69lo TEM and TEMRA cells co-expressing CD57, CX3CR1, and GPR56, which were significantly greater in diabetics compared to non-diabetics. Expression of the CX3CR1 and GPR56 markers indicate these TEM and TEMRA cells may have anti-viral specificity. Compared to HIV-negative controls, SAT from PLWH had an increased CD8:CD4 ratio, but the distribution of CD4+ and CD8+ memory subsets was similar irrespective of HIV status. Finally, whole adipose tissue from PLWH had significantly higher expression of TLR2, TLR8, and multiple chemokines potentially relevant to immune cell homing compared to HIV-negative controls with similar glucose tolerance.

Keywords: CX3CR1; GPR56; HIV—human immunodeficiency virus; T effector memory cells; TEMRA; adipose tissue; diabetes mellitus; memory T cells.

Figures

Figure 1
Figure 1
Subcutaneous adipose tissue from PLWH has a higher percentage of CD4+ and CD8+ memory T cells compared to matched blood samples. (A) Frequencies of total CD4+ and CD8+ T cells (percentage of CD3+ cells) in subcutaneous adipose tissue (SAT) and blood (PBMC) from all 26 PLWH. (B) Representative plot showing gating of CD4+ memory T cells (gated on CD3+) in SAT and PBMC depicted by the yellow and red shading, respectively; on the right are individual values and means. (C) Representative plot showing total CD8+ memory T cells in adipose tissue and PBMC. The box and whiskers plot indicate mean ± SD. Wilcoxon matched pair signed test was used to calculate statistics (A-C); ****p < 0.0001.
Figure 2
Figure 2
Subcutaneous adipose tissue has a higher percentage of TEM (CD45RO+ CCR7−) and TEMRA (CD45RO− CCR7−) cells compared to blood in PLWH. (A) The bar graphs show frequencies of CD4+ TNai, TEM, TCM, and TEMRA cells in subcutaneous adipose tissue (SAT) and blood (PBMC) from all twenty-six subjects. (B) Frequencies of CD8+ TNai, TEM, TCM, and TEMRA cells in SAT and PBMC. The numbers in the bar graphs on the left indicate mean and diagonal lines indicate matched pairs of SAT and PBMCs. Wilcoxon matched pair signed test was used to calculate statistics ****p < 0.0001; ***p < 0.001.
Figure 3
Figure 3
Analysis of CD4+ and CD8+ memory subsets by metabolic status in PLWH. (A) The bar graphs on the top row show frequencies of CD4+ TNai, TEM, TCM, and TEMRA cells in subcutaneous adipose tissue (SAT) and blood (PBMC) from all twenty six PLWH. Participants are grouped based on glucose tolerance: non-diabetic (Non-DM): hemoglobin A1c < 5.7% and fasting glucose < 100 mg/dL (n = 9); Pre-DM: hemoglobin A1c 5.7–6.4% or fasting glucose 100–125 mg/dL (n = 8); DM: hemoglobin A1c > 6.5% and/or fasting glucose > 126 mg/dL, and on anti-diabetes medication (n = 9). (B) Frequencies of CD8+ TNai, TEM, TCM, and TEMRA cells in SAT and PBMC. The box and whiskers plot indicate mean ± SD. Wilcoxon matched pair signed test was used to calculate statistics between matched PBMC and SAT T cells, Mann-Whitney test was used to analyze differences in SAT and PBMC T cell subsets between metabolic groups; **p < 0.01, *p < 0.05.
Figure 4
Figure 4
CD69 expression on subcutaneous adipose tissue CD4+ T cells increases with progressive glucose intolerance. (A–E) Frequencies of CD4+ total T cells, TNai, TCM, TEM, and TEMRA cells expressing the CD69 activation and putative tissue-residence marker in subcutaneous adipose tissue (SAT) and blood (PBMC). The box and whiskers plot indicate mean ± SD. Wilcoxon matched-pair rank test was used to calculate differences between PBMC and SAT. Mann-Whitney test used to calculate differences between groups; blue lines and red * depict differences between groups **p < 0.01, *p < 0.05.
Figure 5
Figure 5
CD4+ T cells co-expressing CD57, CX3CR1, GPR56 in subcutaneous adipose tissue increase with progressive glucose intolerance. viSNE plots were generated in cytobank to identify groups of cells that differ between non-diabetic, pre-diabetic and diabetic categories. (A) Clusters of CD4+, TNai, TEM, TCM, and TEMRA cells from subcutaneous adipose tissue (SAT). (B) Concatenated viSNE plots of non-diabetic, pre-diabetic, and diabetic PLWH showing clusters of cells expressing CX3CR1, CD57, GPR56, and CD69. (C) Violin plots showing percentage of total CD4+, TEM, and TEMRA cells co-expressing CD57, CX3CR1, and GPR56. Mann-Whitney test used to analyze differences between metabolic groups; *P < 0.05.
Figure 6
Figure 6
Comparison of CD4+ and CD8+ T cell subsets in subcutaneous adipose tissue of PLWH and matched HIV-negative controls. Cells recovered from subcutaneous adipose tissue (SAT) of PLWH (n = 9) and HIV-negative controls (n = 8) with similar BMI and hemoglobin A1c were compared. (A) CD4+ T cells as a percentage of total live CD3+ T cells. (B) Frequencies of TNai, TEM, TCM, and TEMRA cells in SAT of PLWH and HIV-negative controls. (C) Total CD4+ memory T cells (TCM + TEM + TEMRA). (D) Similar analysis also done on CD8+ T cells, which are displayed as percentage of total live CD3+ T cells. (E) Frequencies of CD8+ TNai, TEM, TCM, and TEMRA cells. (F) Total CD8+ memory T cells. The box and whiskers plot indicate mean ± SD. Mann-Whitney test used to analyze differences between unpaired PLWH and (–) subjects; **p < 0.01, *p < 0.05.
Figure 7
Figure 7
PLWH have a higher CXCR1, CXCR2, CXCR4, CCL5, CXCL5, TLR2, and TLR8 RNA expression within the subcutaneous adipose tissue compared to HIV negative individuals with similar glucose tolerance. RNA was extracted from subcutaneous adipose tissue of PLWH (n = 6) and HIV negative individuals (n = 7). (A) Schematic showing data analysis. (B) Volcano plot showing log2 fold change (PLWH vs. HIV negative) vs. log10p-value. Relevant genes out of 249 genes are labeled. (C) Sub-groups of inflammatory gene panels available through Nanostring were compared and adjusted p-values calculated within these groups. Genes in G-alpha signaling, defensins and Toll-like receptors with significant findings are shown. Red denotes genes that are higher in PLWH and blue denotes higher gene expression in HIV negative.

References

    1. Brown TT, Cole SR, Li X, Kingsley LA, Palella FJ, Riddler SA, et al. . Antiretroviral therapy and the prevalence and incidence of diabetes mellitus in the multicenter AIDS cohort study. Arch Intern Med. (2005) 165:1179–84. 10.1001/archinte.165.10.1179
    1. De Wit S, Sabin CA, Weber R, Worm SW, Reiss P, Cazanave C, et al. . Incidence and risk factors for new-onset diabetes in HIV-infected patients: the data collection on adverse events of anti-HIV drugs (D:A:D) study. Diabetes Care. (2008) 31:1224–9. 10.2337/dc07-2013
    1. Capeau J, Bouteloup V, Katlama C, Bastard JP, Guiyedi V, Salmon-Ceron D, et al. . Ten-year diabetes incidence in 1046 HIV-infected patients started on a combination antiretroviral treatment. AIDS. (2012) 26:303–14. 10.1097/QAD.0b013e32834e8776
    1. Barre-Sinoussi F, Chermann JC, Rey F, Nugeyre MT, Chamaret S, Gruest J, et al. . Isolation of a T-lymphotropic retrovirus from a patient at risk for acquired immune deficiency syndrome (AIDS). Science. (1983) 220:868–71.
    1. Hellerstein MK, Grunfeld C, Wu K, Christiansen M, Kaempfer S, Kletke C, et al. . Increased de novo hepatic lipogenesis in human immunodeficiency virus infection. J Clin Endocrinol Metab. (1993) 76:559–65. 10.1210/jcem.76.3.8445011
    1. Sekhar RV, Jahoor F, White AC, Pownall HJ, Visnegarwala F, Rodriguez-Barradas MC, et al. . Metabolic basis of HIV-lipodystrophy syndrome. Am J Physiol Endocrinol Metab. (2002) 283:E332–7. 10.1152/ajpendo.00058.2002
    1. Reeds DN, Mittendorfer B, Patterson BW, Powderly WG, Yarasheski KE, Klein S. Alterations in lipid kinetics in men with HIV-dyslipidemia. Am J Physiol Endocrinol Metab. (2003) 285:E490–7. 10.1152/ajpendo.00118.2003
    1. McComsey GA, Kitch D, Sax PE, Tebas P, Tierney C, Jahed NC, et al. Peripheral and central fat changes in subjects randomized to abacavir-lamivudine or tenofovir-emtricitabine with atazanavir-ritonavir or efavirenz: ACTG Study A5224s. Clin Infect Dis. (2011) 53:185–96. 10.1093/cid/cir324
    1. Nolan D, Hammond E, Martin A, Taylor L, Herrmann S, McKinnon E, et al. . Mitochondrial DNA depletion and morphologic changes in adipocytes associated with nucleoside reverse transcriptase inhibitor therapy. AIDS. (2003) 17:1329–38. 10.1097/01.aids.0000060385.18106.35
    1. Hammond E, Nolan D, James I, Metcalf C, Mallal S. Reduction of mitochondrial DNA content and respiratory chain activity occurs in adipocytes within 6–12 months of commencing nucleoside reverse transcriptase inhibitor therapy. AIDS. (2004) 18:815–7. 10.1097/00002030-200403260-00015
    1. Nolan D, Hammond E, James I, McKinnon E, Mallal S. Contribution of nucleoside-analogue reverse transcriptase inhibitor therapy to lipoatrophy from the population to the cellular level. Antivir Ther. (2003) 8:617–26.
    1. Mallal SA, John M, Moore CB, James IR, McKinnon EJ. Contribution of nucleoside analogue reverse transcriptase inhibitors to subcutaneous fat wasting in patients with HIV infection. AIDS. (2000) 14:1309–16. 10.1097/00002030-200007070-00002
    1. Carr A, Samaras K, Burton S, Law M, Freund J, Chisholm DJ, et al. . A syndrome of peripheral lipodystrophy, hyperlipidaemia and insulin resistance in patients receiving HIV protease inhibitors. AIDS. (1998) 12:F51–8.
    1. Kim RJ, Wilson CG, Wabitsch M, Lazar MA, Steppan CM. HIV protease inhibitor-specific alterations in human adipocyte differentiation and metabolism. Obesity (Silver Spring). (2006) 14:994–1002. 10.1038/oby.2006.114
    1. Lagathu C, Eustace B, Prot M, Frantz D, Gu Y, Bastard JP, et al. . Some HIV antiretrovirals increase oxidative stress and alter chemokine, cytokine or adiponectin production in human adipocytes and macrophages. Antivir Ther. (2007) 12:489–500.
    1. Kudlow BA, Jameson SA, Kennedy BK. HIV protease inhibitors block adipocyte differentiation independently of lamin A/C. AIDS. (2005) 19:1565–73. 10.1097/01.aids.0000186827.91408.90
    1. Couturier J, Suliburk JW, Brown JM, Luke DJ, Agarwal N, Yu X, et al. . Human adipose tissue as a reservoir for memory CD4+ T cells and HIV. AIDS. (2015) 29:667–74. 10.1097/QAD.0000000000000599
    1. Damouche A, Lazure T, Avettand-Fenoel V, Huot N, Dejucq-Rainsford N, Satie AP, et al. . Adipose tissue is a neglected viral reservoir and an inflammatory site during chronic HIV and SIV infection. PLoS Pathog. (2015) 11:e1005153. 10.1371/journal.ppat.1005153
    1. Damouche A, Pourcher G, Pourcher V, Benoist S, Busson E, Lataillade JJ, et al. . High proportion of PD-1-expressing CD4(+) T cells in adipose tissue constitutes an immunomodulatory microenvironment that may support HIV persistence. Eur J Immunol. (2017) 47:2113–23. 10.1002/eji.201747060
    1. Couturier J, Winchester LC, Suliburk JW, Wilkerson GK, Podany AT, Agarwal N, et al. . Adipocytes impair efficacy of antiretroviral therapy. Antiviral Res. (2018) 154:140–8. 10.1016/j.antiviral.2018.04.002
    1. Koethe JR, McDonnell W, Kennedy A, Abana CO, Pilkinton M, Setliff I, et al. . Adipose tissue is enriched for activated and late-differentiated CD8+ T cells and shows distinct CD8+ receptor usage, compared with blood in HIV-infected persons. J Acquir Immune Defic Syndr. (2018) 77:e14–21. 10.1097/QAI.0000000000001573
    1. Hsu DC, Wegner MD, Sunyakumthorn P, Silsorn D, Tayamun S, Inthawong D, et al. CD4+ cell infiltration into subcutaneous adipose tissue is not indicative of productively infected cells during acute SHIV infection. J Med Primatol. (2017) 46:154–7. 10.1111/jmp.12298
    1. Nishimura S, Manabe I, Nagasaki M, Eto K, Yamashita H, Ohsugi M, et al. . CD8+ effector T cells contribute to macrophage recruitment and adipose tissue inflammation in obesity. Nat Med. (2009) 15:914–20. 10.1038/nm.1964
    1. Feuerer M, Herrero L, Cipolletta D, Naaz A, Wong J, Nayer A, et al. Lean, but not obese, fat is enriched for a unique population of regulatory T cells that affect metabolic parameters. Nat Med. (2009) 15:930–9. 10.1038/nm.2002
    1. McDonnell WJ, Koethe JR, Mallal SA, Pilkinton MA, Kirabo A, Ameka MK, et al. High CD8 T cell receptor clonality and altered CDR3 properties are associated with elevated isolevuglandins in adipose tissue during diet-induced obesity. Diabetes. (2018) 68:db180040 10.2337/db18-0040
    1. Winer S, Chan Y, Paltser G, Truong D, Tsui H, Bahrami J, et al. . Normalization of obesity-associated insulin resistance through immunotherapy. Nat Med. (2009) 15:921–9. 10.1038/nm.2001
    1. Winer DA, Winer S, Shen L, Wadia PP, Yantha J, Paltser G, et al. . B cells promote insulin resistance through modulation of T cells and production of pathogenic IgG antibodies. Nat Med. (2011) 17:610–7. 10.1038/nm.2353
    1. Hotamisligil GS, Peraldi P, Budavari A, Ellis R, White MF, Spiegelman BM. IRS-1-mediated inhibition of insulin receptor tyrosine kinase activity in TNF-alpha- and obesity-induced insulin resistance. Science. (1996) 271:665–8.
    1. Lumeng CN, Bodzin JL, Saltiel AR. Obesity induces a phenotypic switch in adipose tissue macrophage polarization. J Clin Invest. (2007) 117:175–84. 10.1172/JCI29881
    1. Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante AW, Jr. Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest. (2003) 112:1796–808. 10.1172/JCI19246
    1. Gao D, Madi M, Ding C, Fok M, Steele T, Ford C, et al. . Interleukin-1beta mediates macrophage-induced impairment of insulin signaling in human primary adipocytes. Am J Physiol Endocrinol Metab. (2014) 307:E289–304. 10.1152/ajpendo.00430.2013
    1. Lumeng CN, Deyoung SM, Saltiel AR. Macrophages block insulin action in adipocytes by altering expression of signaling and glucose transport proteins. Am J Physiol Endocrinol Metab. (2007) 292:E166–74. 10.1152/ajpendo.00284.2006
    1. Alexander RW, Harrell DB. Autologous fat grafting: use of closed syringe microcannula system for enhanced autologous structural grafting. Clin Cosmet Invest Dermatol. (2013) 6:91–102. 10.2147/CCID.S40575
    1. Kotecha N, Krutzik PO, Irish JM. Web-based analysis and publication of flow cytometry experiments. Curr Protoc Cytom. (2010) Chapter 10:Unit10 7. 10.1002/0471142956.cy1017s53
    1. Diggins KE, Ferrell PB, Jr, Irish JM. Methods for discovery and characterization of cell subsets in high dimensional mass cytometry data. Methods. (2015) 82:55–63. 10.1016/j.ymeth.2015.05.008
    1. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. (2010) 11:R106. 10.1186/gb-2010-11-10-r106
    1. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. (2014) 15:550. 10.1186/s13059-014-0550-8
    1. Sathaliyawala T, Kubota M, Yudanin N, Turner D, Camp P, Thome JJ, et al. . Distribution and compartmentalization of human circulating and tissue-resident memory T cell subsets. Immunity. (2013) 38:187–97. 10.1016/j.immuni.2012.09.020
    1. Han SJ, Glatman Zaretsky A, Andrade-Oliveira V, Collins N, Dzutsev A, Shaik J, et al. . White adipose tissue is a reservoir for memory T cells and promotes protective memory responses to infection. Immunity. (2017) 47:1154–68 e6. 10.1016/j.immuni.2017.11.009
    1. Casey KA, Fraser KA, Schenkel JM, Moran A, Abt MC, Beura LK, et al. . Antigen-independent differentiation and maintenance of effector-like resident memory T cells in tissues. J Immunol. (2012) 188:4866–75. 10.4049/jimmunol.1200402
    1. Farber DL, Yudanin NA, Restifo NP. Human memory T cells: generation, compartmentalization and homeostasis. Nat Rev Immunol. (2014) 14:24–35. 10.1038/nri3567
    1. Focosi D, Bestagno M, Burrone O, Petrini M. CD57+ T lymphocytes and functional immune deficiency. J Leukoc Biol. (2010) 87:107–16. 10.1189/jlb.0809566
    1. Brenchley JM, Karandikar NJ, Betts MR, Ambrozak DR, Hill BJ, Crotty LE, et al. . Expression of CD57 defines replicative senescence and antigen-induced apoptotic death of CD8+ T cells. Blood. (2003) 101:2711–20. 10.1182/blood-2002-07-2103
    1. Palmer BE, Blyveis N, Fontenot AP, Wilson CC. Functional and phenotypic characterization of CD57+CD4+ T cells and their association with HIV-1-induced T cell dysfunction. J Immunol. (2005) 175:8415–23. 10.4049/jimmunol.175.12.8415
    1. Papagno L, Spina CA, Marchant A, Salio M, Rufer N, Little S, et al. . Immune activation and CD8+ T-cell differentiation towards senescence in HIV-1 infection. PLoS Biol. (2004) 2:E20. 10.1371/journal.pbio.0020020
    1. Lieberman J, Trimble LA, Friedman RS, Lisziewicz J, Lori F, Shankar P, et al. . Expansion of CD57 and CD62L−CD45RA+ CD8 T lymphocytes correlates with reduced viral plasma RNA after primary HIV infection. AIDS. (1999) 13:891–9.
    1. Le Priol Y, Puthier D, Lecureuil C, Combadiere C, Debre P, Nguyen C, et al. . High cytotoxic and specific migratory potencies of senescent CD8+ CD57+ cells in HIV-infected and uninfected individuals. J Immunol. (2006) 177:5145–54. 10.4049/jimmunol.177.8.5145
    1. Tae Yu H, Youn JC, Lee J, Park S, Chi HS, Lee J, et al. . Characterization of CD8(+)CD57(+) T cells in patients with acute myocardial infarction. Cell Mol Immunol. (2015) 12:466–73. 10.1038/cmi.2014.74
    1. Maeda T, Yamada H, Nagamine R, Shuto T, Nakashima Y, Hirata G, et al. . Involvement of CD4+, CD57+ T cells in the disease activity of rheumatoid arthritis. Arthritis Rheum. (2002) 46:379–84. 10.1002/art.10133
    1. Palmer BE, Mack DG, Martin AK, Maier LA, Fontenot AP. CD57 expression correlates with alveolitis severity in subjects with beryllium-induced disease. J Allergy Clin Immunol. (2007) 120:184–91. 10.1016/j.jaci.2007.03.009
    1. Shnayder M, Nachshon A, Krishna B, Poole E, Boshkov A, Binyamin A, et al. . Defining the transcriptional landscape during cytomegalovirus latency with single-cell RNA sequencing. MBio. (2018) 9:e00013-18. 10.1128/mBio.00013-18
    1. Tian Y, Babor M, Lane J, Schulten V, Patil VS, Seumois G, et al. . Unique phenotypes and clonal expansions of human CD4 effector memory T cells re-expressing CD45RA. Nat Commun. (2017) 8:1473. 10.1038/s41467-017-01728-5
    1. Truong K, Schlickeiser S, Vogt K, Boes D, Schumann J, Appelt C, et al. Progressive change in killer-like receptor and GPR56 expression defines cytokine production of human CD4+ T memory cells. BioRxiv. (2017). 10.1101/191007
    1. Bottcher JP, Beyer M, Meissner F, Abdullah Z, Sander J, Hochst B, et al. . Functional classification of memory CD8(+) T cells by CX3CR1 expression. Nat Commun. (2015) 6:8306. 10.1038/ncomms9306
    1. Nishimura M, Umehara H, Nakayama T, Yoneda O, Hieshima K, Kakizaki M, et al. . Dual functions of fractalkine/CX3C ligand 1 in trafficking of perforin+/granzyme B+ cytotoxic effector lymphocytes that are defined by CX3CR1 expression. J Immunol. (2002) 168:6173–80. 10.4049/jimmunol.168.12.6173
    1. Abana CO, Pilkinton MA, Gaudieri S, Chopra A, McDonnell WJ, Wanjalla C, et al. . Cytomegalovirus (CMV) epitope-specific CD4(+) T cells are inflated in HIV(+) CMV(+) subjects. J Immunol. (2017) 199:3187–201. 10.4049/jimmunol.1700851
    1. Pachnio A, Ciaurriz M, Begum J, Lal N, Zuo J, Beggs A, et al. . Cytomegalovirus infection leads to development of high frequencies of cytotoxic virus-specific CD4+ T cells targeted to vascular endothelium. PLoS Pathog. (2016) 12:e1005832. 10.1371/journal.ppat.1005832
    1. Gordon CL, Lee LN, Swadling L, Hutchings C, Zinser M, Highton AJ, et al. . Induction and maintenance of CX3CR1-intermediate peripheral memory CD8(+) T cells by persistent viruses and vaccines. Cell Rep. (2018) 23:768–82. 10.1016/j.celrep.2018.03.074
    1. Peng YM, van de Garde MD, Cheng KF, Baars PA, Remmerswaal EB, van Lier RA, et al. . Specific expression of GPR56 by human cytotoxic lymphocytes. J Leukoc Biol. (2011) 90:735–40. 10.1189/jlb.0211092
    1. Travers RL, Motta AC, Betts JA, Bouloumie A, Thompson D. The impact of adiposity on adipose tissue-resident lymphocyte activation in humans. Int J Obes (Lond). (2015) 39:762–9. 10.1038/ijo.2014.195
    1. Couturier J, Agarwal N, Nehete PN, Baze WB, Barry MA, Jagannadha Sastry K, et al. . Infectious SIV resides in adipose tissue and induces metabolic defects in chronically infected rhesus macaques. Retrovirology. (2016) 13:30. 10.1186/s12977-016-0260-2
    1. Robins HS, Campregher PV, Srivastava SK, Wacher A, Turtle CJ, Kahsai O, et al. . Comprehensive assessment of T-cell receptor beta-chain diversity in alphabeta T cells. Blood. (2009) 114:4099–107. 10.1182/blood-2009-04-217604
    1. DeWitt WS, Emerson RO, Lindau P, Vignali M, Snyder TM, Desmarais C, et al. . Dynamics of the cytotoxic T cell response to a model of acute viral infection. J Virol. (2015) 89:4517–26. 10.1128/JVI.03474-14
    1. Vitseva OI, Tanriverdi K, Tchkonia TT, Kirkland JL, McDonnell ME, Apovian CM, et al. . Inducible toll-like receptor and NF-kappaB regulatory pathway expression in human adipose tissue. Obesity (Silver Spring). (2008) 16:932–7. 10.1038/oby.2008.25
    1. Ahmad R, Al-Mass A, Atizado V, Al-Hubail A, Al-Ghimlas F, Al-Arouj M, et al. . Elevated expression of the toll like receptors 2 and 4 in obese individuals: its significance for obesity-induced inflammation. J Inflamm (Lond). (2012) 9:48. 10.1186/1476-9255-9-48
    1. Creely SJ, McTernan PG, Kusminski CM, Fisher fM, Da Silva NF, Khanolkar M, et al. . Lipopolysaccharide activates an innate immune system response in human adipose tissue in obesity and type 2 diabetes. Am J Physiol Endocrinol Metab. (2007) 292:E740–7. 10.1152/ajpendo.00302.2006
    1. Dasu MR, Devaraj S, Park S, Jialal I. Increased toll-like receptor (TLR) activation and TLR ligands in recently diagnosed type 2 diabetic subjects. Diabetes Care. (2010) 33:861–8. 10.2337/dc09-1799
    1. Martinez FO, Gordon S, Locati M, Mantovani A. Transcriptional profiling of the human monocyte-to-macrophage differentiation and polarization: new molecules and patterns of gene expression. J Immunol. (2006) 177:7303–11. 10.4049/jimmunol.177.10.7303
    1. Caccuri F, Giagulli C, Bugatti A, Benetti A, Alessandri G, Ribatti D, et al. . HIV-1 matrix protein p17 promotes angiogenesis via chemokine receptors CXCR1 and CXCR2. Proc Natl Acad Sci USA. (2012) 109:14580–5. 10.1073/pnas.1206605109
    1. Sierra-Honigmann MR, Nath AK, Murakami C, Garcia-Cardena G, Papapetropoulos A, Sessa WC, et al. . Biological action of leptin as an angiogenic factor. Science. (1998) 281:1683–6.

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