Supplementary Material Ann Rheum Dis Doi: 10.1136/Annrheumdis

Total Page:16

File Type:pdf, Size:1020Kb

Supplementary Material Ann Rheum Dis Doi: 10.1136/Annrheumdis Supplementary material Ann Rheum Dis Vanarsa K, et al. Ann Rheum Dis 2020;0:1–13. doi: 10.1136/annrheumdis-2019-216312 Supplementary material Ann Rheum Dis Vanarsa et al, Supplementary Table S2 Supplementary Table S2: Patient cohort used for the ELISA validation of urine biomarker candidates Variable All SLE Inactive Active Non-Renal Active Renal (N=62) (N=17) (N=16) (N=29) Age (years) 32.9±9.5 32.8±7.5 42.1±11.3 27.9±4.5 Gender Female, n(%) 62 (100.0%) 17 (100.0%) 16 (100.0%) 29 (100.0%) Ethnicity African-American 58 (93.5%) 16 (94.1%) 13 (81.3%) 29 (100.0%) Caucasian 4 (6.5%) 1 (5.9%) 3 (18.7%) 0 (0.0%) Clinical Assessment SLEDAI 5.9±4.2 0.4±0.8 7.7±3.0 8.1±3.0 rSLEDAI 2.4±2.9 0±0 0±0 5.1±2.1 PGA 1.3±0.8 0.6±0.7 0.8±0.4 2.0±0.6 Laboratory Metrics WBC (X109/L) 6.9±3.3 7.1±2.7 4.3±1.4 8.3±3.6 HGB (g/dl) 11.0±1.5 11.3±1.5 11.3±1.1 10.7±1.7 Platelets (X109/L) 284.0±95.8 235.9±78.9 263.5±62.1 323.2±106.0 C3 (mg/dl) 95.3±34.7 116.5±31.0 87.8±37.5 88.3±31.1 C4 (mg/dl) 18.7±10.2 22.0±8.7 14.9±8.9 19.1±11.1 ESR (mm/h) 43.9±29.2 34.1±26.3 47.9±22.0 47.2±33.5 UrPrCrRatio (mg/mg) 1.2±1.9 0.2±0.1 0.1±0.1 2.5±2.4 Serum Creatinine (mg/dl) 0.9±0.4 0.9±0.5 0.8±0.2 1.0±0.4 Anti-DNA, n(%) 32 (51.6%) 2 (11.8%) 11 (68.8%) 19 (65.5%) Medications Prednisone, n(%) 38 (61.3%) 9 (52.9%) 7 (43.8%) 22 (75.9%) Plaquenil, n(%) 51 (82.3%) 13 (76.5%) 13 (81.3%) 25 (86.2%) Mycophenolate Mofetil, n(%) 32 (51.6%) 8 (47.1%) 9 (56.3%) 15 (51.7%) Tacrolimus, n(%) 1 (1.6%) 0 (0.0%) 1 (6.3%) 0 (0.0%) Azathioprine, n(%) 7 (11.3%) 1 (5.9%) 2 (12.5%) 4 (13.8%) Cyclophosphamide, n(%) 2 (3.2%) 0 (0.0%) 0 (0.0%) 2 (6.9%) Methotrexate, n (%) 2 (3.2%) 0 (0.0%) 1 (6.3%) 1 (3.4%) Abbreviations used: PGA, physician global assessment; UrPrCr ratio, urine protein to creatinine ratio. Vanarsa K, et al. Ann Rheum Dis 2020;0:1–13. doi: 10.1136/annrheumdis-2019-216312 Supplementary material Ann Rheum Dis Supplementary Table S3: Well documented biomarker proteins rediscovered by the screen Molecule FC SLE/HC p value (t test) Supplementary References Albumin 2.0 0.075 S3, S4 ALCAM 1797.9 0.072 S47, S48 Angiostatin 160.9 0.105 S29 Calreticulin 4.6 0.1 S44 CD163 N/A* 0.08 S10, S11 CD30 20.5 0.008 S51 CXCL16 15.9 0.008 S20, S21 Cystatin S 3.0 0.185 Cystatin SA 1.7 0.529 Cystatin SN 0.4 0.313 E-Selectin 3.9 0.002 S37 Ferritin 187.0 0.001 S49, S50 FOLR1 1.4 0.517 ICAM-1 6.8 0.019 S1, S2 IL-12p40 N/A* 0.3 S35, S36 IL-15 4.1 0.47 S13, S14 IL-6 0.1 0.126 S5, S6 IP-10 43.1 0.013 S22, S23 I-TAC 2.5 0.137 Leptin 3.1 0.024 S12 Lipocalin-1 3.1 0.055 Lipocalin-2 3.2 0.012 S28 L-Selectin 16.7 0.013 MCP-1 7.8 0.089 S7 MCSF 1.5 0.344 S15, S16 MCSF R 51.9 0.008 MIP-3a 49.8 0.13 S27 MIP-3b 8.8 0.04 S45 OPG 52.0 0.002 S33, S34 OPN 7.2 0.004 S18, S19 PF4 43.1 0.109 S40, S41 RAGE 10.7 0.1 S26 RANTES 16.7 0.01 S42, S43 Resistin 8.1 0.015 S46 SDF-1a 9.1 0.249 S32 TFPI 397.8 0.027 S8, S9 TNF RI 3.7 0.038 S17 TNF RII 3.2 0.025 TREM-1 21.7 0.099 S38, S39 TWEAK 4.4 0.105 S30, S31 TWEAK R 1.5 0.743 uPA 3.7 0.004 VCAM-1 49.0 0.068 S24, S25 N/A, not available. * indicates FC was not calculated due to average of healthy control is 0. Vanarsa K, et al. Ann Rheum Dis 2020;0:1–13. doi: 10.1136/annrheumdis-2019-216312 Supplementary material Ann Rheum Dis Supplementary References: S1 Guan J, Wang G, Tam L-S, et al. Urinary sediment ICAM-1 level in lupus nephritis. Lupus 2012;21:1190–5. doi:10.1177/0961203312451334 S2 Sabry A, Sheashaa H, El-Husseini A, et al. Intercellular adhesion molecules in systemic lupus erythematosus patients with lupus nephritis. Clin Rheumatol 2007;26:1819–23. doi:10.1007/s10067-007-0580-7 S3 Ding J, Zheng Z, Li X, et al. Urinary Albumin Levels are Independently Associated with Renal Lesion Severity in Patients with Lupus Nephritis and Little or No Proteinuria. Med Sci Monit 2017;23:631–9. doi:10.12659/MSM.899973 S4 Yip J, Aghdassi E, Su J, et al. Serum albumin as a marker for disease activity in patients with systemic lupus erythematosus. J Rheumatol 2010;37:1667–72. doi:10.3899/jrheum.091028 S5 Jacob N, Stohl W. Cytokine disturbances in systemic lupus erythematosus. Arthritis Research & Therapy 2011;13:228. doi:10.1186/ar3349 S6 Ripley B, Goncalves B, Isenberg D, et al. Raised levels of interleukin 6 in systemic lupus erythematosus correlate with anaemia. Ann Rheum Dis 2005;64:849–53. doi:10.1136/ard.2004.022681 S7 Živković V, Cvetković T, Mitić B, et al. Monocyte chemoattractant protein-1 as a marker of systemic lupus erythematosus: an observational study. Rheumatol Int 2018;38:1003–8. doi:10.1007/s00296- 017-3888-x S8 Qin L, Stanley S, Ding H, et al. Urinary pro-thrombotic, anti-thrombotic, and fibrinolytic molecules as biomarkers of lupus nephritis. Arthritis Res Ther 2019;21:176. doi:10.1186/s13075-019-1959-y S9 Adams MJ, Palatinus AA, Harvey AM, et al. Impaired control of the tissue factor pathway of blood coagulation in systemic lupus erythematosus. Lupus 2011;20:1474–83. doi:10.1177/0961203311418267 S10 Endo N, Tsuboi N, Furuhashi K, et al. Urinary soluble CD163 level reflects glomerular inflammation in human lupus nephritis. Nephrol Dial Transplant 2016;31:2023–33. doi:10.1093/ndt/gfw214 S11 Nakayama W, Jinnin M, Makino K, et al. CD163 expression is increased in the involved skin and sera of patients with systemic lupus erythematosus. Eur J Dermatol 2012;22:512–7. doi:10.1684/ejd.2012.1756 S12 Hutcheson J, Ye Y, Han J, et al. Resistin as a potential marker of renal disease in lupus nephritis. Clin Exp Immunol 2015;179:435–43. doi:10.1111/cei.12473 S13 Stanley S, Mok CC, Vanarsa K, et al. Identification of Low-Abundance Urinary Biomarkers in Lupus Nephritis Using Electrochemiluminescence Immunoassays. Arthritis & Rheumatology (Hoboken, NJ) 2019;71:744–55. doi:10.1002/art.40813 S14 Liu C-C, Kao AH, Manzi S, et al. Biomarkers in systemic lupus erythematosus: challenges and prospects for the future. Ther Adv Musculoskelet Dis 2013;5:210–33. doi:10.1177/1759720X13485503 S15 Tian S, Li J, Wang L, et al. Urinary levels of RANTES and M-CSF are predictors of lupus nephritis flare. Inflamm Res 2007;56:304–10. doi:10.1007/s00011-007-6147-x Vanarsa K, et al. Ann Rheum Dis 2020;0:1–13. doi: 10.1136/annrheumdis-2019-216312 Supplementary material Ann Rheum Dis S16 Ramirez GA, Blasi M, Sciorati C, et al. Plasma levels of M-CSF are increased in ANCA-associated vasculitides with active nephritis. Results Immunol 2015;5:33–6. doi:10.1016/j.rinim.2015.10.002 S17 Adhya Z, El Anbari M, Anwar S, et al. Soluble TNF-R1, VEGF and other cytokines as markers of disease activity in systemic lupus erythematosus and lupus nephritis. Lupus 2019;28:713–21. doi:10.1177/0961203319845487 S18 Kitagori K, Yoshifuji H, Oku T, et al. Cleaved Form of Osteopontin in Urine as a Clinical Marker of Lupus Nephritis. PLoS One 2016;11. doi:10.1371/journal.pone.0167141 S19 Pasha HF, Tantawy EA, Youssef MA. Osteopontin and interleukin-17A genes polymorphisms in Egyptian systemic lupus erythematosus patients: A relation to disease activity and severity. Gene 2019;702:107–13. doi:10.1016/j.gene.2019.02.100 S20 Reyes-Thomas J, Blanco I, Putterman C. Urinary Biomarkers in Lupus Nephritis. Clin Rev Allergy Immunol 2011;40:138–50. doi:10.1007/s12016-010-8197-z S21 Qin M, Guo Y, Jiang L, et al. Elevated levels of serum sCXCL16 in systemic lupus erythematosus; potential involvement in cutaneous and renal manifestations. Clin Rheumatol 2014;33:1595–601. doi:10.1007/s10067-014-2741-9 S22 Zeid MMH, Baddour NM, El-Neily DAE-M, et al. Study of urinary interferon gamma-induced protein 10 (IP-10) and urinary soluble CD 25 (sCD25) as markers of lupus nephritis and their relation to histological class.
Recommended publications
  • Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
    Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only.
    [Show full text]
  • Supplementary Table 1: Adhesion Genes Data Set
    Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,
    [Show full text]
  • Supplementary Table S5. Differentially Expressed Gene Lists of PD-1High CD39+ CD8 Tils According to 4-1BB Expression Compared to PD-1+ CD39- CD8 Tils
    BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Immunother Cancer Supplementary Table S5. Differentially expressed gene lists of PD-1high CD39+ CD8 TILs according to 4-1BB expression compared to PD-1+ CD39- CD8 TILs Up- or down- regulated genes in Up- or down- regulated genes Up- or down- regulated genes only PD-1high CD39+ CD8 TILs only in 4-1BBneg PD-1high CD39+ in 4-1BBpos PD-1high CD39+ CD8 compared to PD-1+ CD39- CD8 CD8 TILs compared to PD-1+ TILs compared to PD-1+ CD39- TILs CD39- CD8 TILs CD8 TILs IL7R KLRG1 TNFSF4 ENTPD1 DHRS3 LEF1 ITGA5 MKI67 PZP KLF3 RYR2 SIK1B ANK3 LYST PPP1R3B ETV1 ADAM28 H2AC13 CCR7 GFOD1 RASGRP2 ITGAX MAST4 RAD51AP1 MYO1E CLCF1 NEBL S1PR5 VCL MPP7 MS4A6A PHLDB1 GFPT2 TNF RPL3 SPRY4 VCAM1 B4GALT5 TIPARP TNS3 PDCD1 POLQ AKAP5 IL6ST LY9 PLXND1 PLEKHA1 NEU1 DGKH SPRY2 PLEKHG3 IKZF4 MTX3 PARK7 ATP8B4 SYT11 PTGER4 SORL1 RAB11FIP5 BRCA1 MAP4K3 NCR1 CCR4 S1PR1 PDE8A IFIT2 EPHA4 ARHGEF12 PAICS PELI2 LAT2 GPRASP1 TTN RPLP0 IL4I1 AUTS2 RPS3 CDCA3 NHS LONRF2 CDC42EP3 SLCO3A1 RRM2 ADAMTSL4 INPP5F ARHGAP31 ESCO2 ADRB2 CSF1 WDHD1 GOLIM4 CDK5RAP1 CD69 GLUL HJURP SHC4 GNLY TTC9 HELLS DPP4 IL23A PITPNC1 TOX ARHGEF9 EXO1 SLC4A4 CKAP4 CARMIL3 NHSL2 DZIP3 GINS1 FUT8 UBASH3B CDCA5 PDE7B SOGA1 CDC45 NR3C2 TRIB1 KIF14 TRAF5 LIMS1 PPP1R2C TNFRSF9 KLRC2 POLA1 CD80 ATP10D CDCA8 SETD7 IER2 PATL2 CCDC141 CD84 HSPA6 CYB561 MPHOSPH9 CLSPN KLRC1 PTMS SCML4 ZBTB10 CCL3 CA5B PIP5K1B WNT9A CCNH GEM IL18RAP GGH SARDH B3GNT7 C13orf46 SBF2 IKZF3 ZMAT1 TCF7 NECTIN1 H3C7 FOS PAG1 HECA SLC4A10 SLC35G2 PER1 P2RY1 NFKBIA WDR76 PLAUR KDM1A H1-5 TSHZ2 FAM102B HMMR GPR132 CCRL2 PARP8 A2M ST8SIA1 NUF2 IL5RA RBPMS UBE2T USP53 EEF1A1 PLAC8 LGR6 TMEM123 NEK2 SNAP47 PTGIS SH2B3 P2RY8 S100PBP PLEKHA7 CLNK CRIM1 MGAT5 YBX3 TP53INP1 DTL CFH FEZ1 MYB FRMD4B TSPAN5 STIL ITGA2 GOLGA6L10 MYBL2 AHI1 CAND2 GZMB RBPJ PELI1 HSPA1B KCNK5 GOLGA6L9 TICRR TPRG1 UBE2C AURKA Leem G, et al.
    [Show full text]
  • Wo 2008/021431 A2
    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date PCT 21 February 2008 (21.02.2008) WO 2008/021431 A2 (51) International Patent Classification: (74) Agents: WARD, Michael, R. et al.; Morrison & Foerster C12Q 1/68 (2006.01) LLP, 425 Market Street, San Francisco, CA 94105-2482 (US). (21) International Application Number: PCT/US2007/018135 (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, (22) International Filing Date: 14 August 2007 (14.08.2007) AT,AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, CA, CH, CN, CO, CR, CU, CZ, DE, DK, DM, DO, DZ, EC, EE, EG, (25) Filing Language: English ES, FT, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, MG, MK, MN, MW, (26) Publication Language: English MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PG, PH, PL, PT, RO, RS, RU, SC, SD, SE, SG, SK, SL, SM, SV, SY, (30) Priority Data: TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, 60/837,698 14 August 2006 (14.08.2006) US ZM, ZW (71) Applicant (for all designated States except US): EXPRES¬ (84) Designated States (unless otherwise indicated, for every SION DIAGNOSTICS, INC. [US/US]; 3260 Bayshore kind of regional protection available): ARIPO (BW, GH, Blvd., Brisbane, CA 94005 (US).
    [Show full text]
  • * Supplementary Table 3B. Complete List of Lymphocytic-Associated Genes
    Supplementary Table 3b. Complete list of lymphocytic-associated genes for the HER2+I subtype based on the SNR score (p-val <= 0.005 and FDR<=0.05). A positive score represents genes up-regulated in HER2+I and a negative score represents genes up-regulated in HER2+NI. The first 9 genes, marked with *, are chemokines near the HER2+ amplicon at chr17q12. The remaining are sorted based by chromosomal location (from chr 1 to chr X) and signal-to-noise ratio (SNR). Gene Name Description SNR Score Feature P value FDR(BH) Q Value * CCL5 chemokine (C-C motif) ligand 5 1.395 0.002 0.036 0.025 * CCR7 chemokine (C-C motif) receptor 7 1.362 0.002 0.036 0.025 * CD79B CD79B antigen (immunoglobulin-associated beta) 1.248 0.002 0.036 0.025 * CCL13 chemokine (C-C motif) ligand 13 1.003 0.002 0.036 0.025 * CCL2 chemokine (C-C motif) ligand 2 0.737 0.004 0.056 0.037 * CCL8 chemokine (C-C motif) ligand 8 0.724 0.002 0.036 0.025 * CCL18 chemokine (C-C motif) ligand 18 (pulmonary and activ 0.703 0.002 0.036 0.025 * CCL23 chemokine (C-C motif) ligand 23 0.701 0.002 0.036 0.025 * CCR6 chemokine (C-C motif) receptor 6 0.715 0.002 0.036 0.025 PTPN7 protein tyrosine phosphatase, non-receptor type 7 1.861 0.002 0.036 0.025 CD3Z CD3Z antigen, zeta polypeptide (TiT3 complex) 1.811 0.002 0.036 0.025 CD48 CD48 antigen (B-cell membrane protein) 1.809 0.002 0.036 0.025 IL10RA interleukin 10 receptor, alpha 1.806 0.002 0.036 0.025 SELL selectin L (lymphocyte adhesion molecule 1) 1.773 0.002 0.036 0.025 LCK lymphocyte-specific protein tyrosine kinase 1.745 0.002 0.036 0.025
    [Show full text]
  • Urinary Proteomics for the Early Diagnosis of Diabetic Nephropathy in Taiwanese Patients Authors
    Urinary Proteomics for the Early Diagnosis of Diabetic Nephropathy in Taiwanese Patients Authors: Wen-Ling Liao1,2, Chiz-Tzung Chang3,4, Ching-Chu Chen5,6, Wen-Jane Lee7,8, Shih-Yi Lin3,4, Hsin-Yi Liao9, Chia-Ming Wu10, Ya-Wen Chang10, Chao-Jung Chen1,9,+,*, Fuu-Jen Tsai6,10,11,+,* 1 Graduate Institute of Integrated Medicine, China Medical University, Taichung, 404, Taiwan 2 Center for Personalized Medicine, China Medical University Hospital, Taichung, 404, Taiwan 3 Division of Nephrology and Kidney Institute, Department of Internal Medicine, China Medical University Hospital, Taichung, 404, Taiwan 4 Institute of Clinical Medical Science, China Medical University College of Medicine, Taichung, 404, Taiwan 5 Division of Endocrinology and Metabolism, Department of Medicine, China Medical University Hospital, Taichung, 404, Taiwan 6 School of Chinese Medicine, China Medical University, Taichung, 404, Taiwan 7 Department of Medical Research, Taichung Veterans General Hospital, Taichung, 404, Taiwan 8 Department of Social Work, Tunghai University, Taichung, 404, Taiwan 9 Proteomics Core Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, 404, Taiwan 10 Human Genetic Center, Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 404, Taiwan 11 Department of Health and Nutrition Biotechnology, Asia University, Taichung, 404, Taiwan + Fuu-Jen Tsai and Chao-Jung Chen contributed equally to this work. Correspondence: Fuu-Jen Tsai, MD, PhD and Chao-Jung Chen, PhD FJ Tsai: Genetic Center, China Medical University Hospital, No.2 Yuh-Der Road, 404 Taichung, Taiwan; Telephone: 886-4-22062121 Ext. 2041; Fax: 886-4-22033295; E-mail: [email protected] CJ Chen: Graduate Institute of Integrated Medicine, China Medical University, No.91, Hsueh-Shih Road, 404, Taichung, Taiwan; Telephone: 886-4-22053366 Ext.
    [Show full text]
  • Molecular Signatures Differentiate Immune States in Type 1 Diabetes Families
    Page 1 of 65 Diabetes Molecular signatures differentiate immune states in Type 1 diabetes families Yi-Guang Chen1, Susanne M. Cabrera1, Shuang Jia1, Mary L. Kaldunski1, Joanna Kramer1, Sami Cheong2, Rhonda Geoffrey1, Mark F. Roethle1, Jeffrey E. Woodliff3, Carla J. Greenbaum4, Xujing Wang5, and Martin J. Hessner1 1The Max McGee National Research Center for Juvenile Diabetes, Children's Research Institute of Children's Hospital of Wisconsin, and Department of Pediatrics at the Medical College of Wisconsin Milwaukee, WI 53226, USA. 2The Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA. 3Flow Cytometry & Cell Separation Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA. 4Diabetes Research Program, Benaroya Research Institute, Seattle, WA, 98101, USA. 5Systems Biology Center, the National Heart, Lung, and Blood Institute, the National Institutes of Health, Bethesda, MD 20824, USA. Corresponding author: Martin J. Hessner, Ph.D., The Department of Pediatrics, The Medical College of Wisconsin, Milwaukee, WI 53226, USA Tel: 011-1-414-955-4496; Fax: 011-1-414-955-6663; E-mail: [email protected]. Running title: Innate Inflammation in T1D Families Word count: 3999 Number of Tables: 1 Number of Figures: 7 1 For Peer Review Only Diabetes Publish Ahead of Print, published online April 23, 2014 Diabetes Page 2 of 65 ABSTRACT Mechanisms associated with Type 1 diabetes (T1D) development remain incompletely defined. Employing a sensitive array-based bioassay where patient plasma is used to induce transcriptional responses in healthy leukocytes, we previously reported disease-specific, partially IL-1 dependent, signatures associated with pre and recent onset (RO) T1D relative to unrelated healthy controls (uHC).
    [Show full text]
  • KRAS Mutations Are Negatively Correlated with Immunity in Colon Cancer
    www.aging-us.com AGING 2021, Vol. 13, No. 1 Research Paper KRAS mutations are negatively correlated with immunity in colon cancer Xiaorui Fu1,2,*, Xinyi Wang1,2,*, Jinzhong Duanmu1, Taiyuan Li1, Qunguang Jiang1 1Department of Gastrointestinal Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People's Republic of China 2Queen Mary College, Medical Department, Nanchang University, Nanchang, Jiangxi, People's Republic of China *Equal contribution Correspondence to: Qunguang Jiang; email: [email protected] Keywords: KRAS mutations, immunity, colon cancer, tumor-infiltrating immune cells, inflammation Received: March 27, 2020 Accepted: October 8, 2020 Published: November 26, 2020 Copyright: © 2020 Fu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT The heterogeneity of colon cancer tumors suggests that therapeutics targeting specific molecules may be effective in only a few patients. It is therefore necessary to explore gene mutations in colon cancer. In this study, we obtained colon cancer samples from The Cancer Genome Atlas, and the International Cancer Genome Consortium. We evaluated the landscape of somatic mutations in colon cancer and found that KRAS mutations, particularly rs121913529, were frequent and had prognostic value. Using ESTIMATE analysis, we observed that the KRAS-mutated group had higher tumor purity, lower immune score, and lower stromal score than the wild- type group. Through single-sample Gene Set Enrichment Analysis and Gene Set Enrichment Analysis, we found that KRAS mutations negatively correlated with enrichment levels of tumor infiltrating lymphocytes, inflammation, and cytolytic activities.
    [Show full text]
  • Effects of Sex and Aging on the Immune Cell Landscape As Assessed by Single-Cell Transcriptomic Analysis
    Effects of sex and aging on the immune cell landscape as assessed by single-cell transcriptomic analysis Zhaohao Huanga,1, Binyao Chena,1, Xiuxing Liua,1,HeLia,1, Lihui Xiea,1, Yuehan Gaoa,1, Runping Duana, Zhaohuai Lia, Jian Zhangb, Yingfeng Zhenga,2, and Wenru Sua,2 aState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou 510060, China; and bDepartment of Clinical Research Center, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou 510060, China Edited by Lawrence Steinman, Stanford University School of Medicine, Stanford, CA, and approved June 22, 2021 (received for review November 19, 2020) Sex and aging influence the human immune system, resulting in the immune system integrates numerous interconnected compo- disparate responses to infection, autoimmunity, and cancer. How- nents, pathways, and cell types in sex and aging. ever, the impact of sex and aging on the immune system is not yet To this end, we profiled the transcriptomes of peripheral im- fully elucidated. Using small conditional RNA sequencing, we mune cells sampled from men and women of two distinct age found that females had a lower percentage of natural killer (NK) groups. Then, we investigated sex- and age-related differences in cells and a higher percentage of plasma cells in peripheral blood PBMC immune cell composition, molecular programs, and com- compared with males. Bioinformatics revealed that young females munication network. Extensive differences in all of these aspects exhibited an overrepresentation of pathways that relate to T and were observed between sexes, particularly in aging. Compared – B cell activation. Moreover, cell cell communication analysis revealed with males, females exhibited a higher expression of T cell (TC)– evidence of increased activity of the BAFF/APRIL systems in females.
    [Show full text]
  • Human CD Marker Chart Reviewed by HLDA1 Bdbiosciences.Com/Cdmarkers
    BD Biosciences Human CD Marker Chart Reviewed by HLDA1 bdbiosciences.com/cdmarkers 23-12399-01 CD Alternative Name Ligands & Associated Molecules T Cell B Cell Dendritic Cell NK Cell Stem Cell/Precursor Macrophage/Monocyte Granulocyte Platelet Erythrocyte Endothelial Cell Epithelial Cell CD Alternative Name Ligands & Associated Molecules T Cell B Cell Dendritic Cell NK Cell Stem Cell/Precursor Macrophage/Monocyte Granulocyte Platelet Erythrocyte Endothelial Cell Epithelial Cell CD Alternative Name Ligands & Associated Molecules T Cell B Cell Dendritic Cell NK Cell Stem Cell/Precursor Macrophage/Monocyte Granulocyte Platelet Erythrocyte Endothelial Cell Epithelial Cell CD1a R4, T6, Leu6, HTA1 b-2-Microglobulin, CD74 + + + – + – – – CD93 C1QR1,C1qRP, MXRA4, C1qR(P), Dj737e23.1, GR11 – – – – – + + – – + – CD220 Insulin receptor (INSR), IR Insulin, IGF-2 + + + + + + + + + Insulin-like growth factor 1 receptor (IGF1R), IGF-1R, type I IGF receptor (IGF-IR), CD1b R1, T6m Leu6 b-2-Microglobulin + + + – + – – – CD94 KLRD1, Kp43 HLA class I, NKG2-A, p39 + – + – – – – – – CD221 Insulin-like growth factor 1 (IGF-I), IGF-II, Insulin JTK13 + + + + + + + + + CD1c M241, R7, T6, Leu6, BDCA1 b-2-Microglobulin + + + – + – – – CD178, FASLG, APO-1, FAS, TNFRSF6, CD95L, APT1LG1, APT1, FAS1, FASTM, CD95 CD178 (Fas ligand) + + + + + – – IGF-II, TGF-b latency-associated peptide (LAP), Proliferin, Prorenin, Plasminogen, ALPS1A, TNFSF6, FASL Cation-independent mannose-6-phosphate receptor (M6P-R, CIM6PR, CIMPR, CI- CD1d R3G1, R3 b-2-Microglobulin, MHC II CD222 Leukemia
    [Show full text]
  • Engineered Type 1 Regulatory T Cells Designed for Clinical Use Kill Primary
    ARTICLE Acute Myeloid Leukemia Engineered type 1 regulatory T cells designed Ferrata Storti Foundation for clinical use kill primary pediatric acute myeloid leukemia cells Brandon Cieniewicz,1* Molly Javier Uyeda,1,2* Ping (Pauline) Chen,1 Ece Canan Sayitoglu,1 Jeffrey Mao-Hwa Liu,1 Grazia Andolfi,3 Katharine Greenthal,1 Alice Bertaina,1,4 Silvia Gregori,3 Rosa Bacchetta,1,4 Norman James Lacayo,1 Alma-Martina Cepika1,4# and Maria Grazia Roncarolo1,2,4# Haematologica 2021 Volume 106(10):2588-2597 1Department of Pediatrics, Division of Stem Cell Transplantation and Regenerative Medicine, Stanford School of Medicine, Stanford, CA, USA; 2Stanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford School of Medicine, Stanford, CA, USA; 3San Raffaele Telethon Institute for Gene Therapy, Milan, Italy and 4Center for Definitive and Curative Medicine, Stanford School of Medicine, Stanford, CA, USA *BC and MJU contributed equally as co-first authors #AMC and MGR contributed equally as co-senior authors ABSTRACT ype 1 regulatory (Tr1) T cells induced by enforced expression of interleukin-10 (LV-10) are being developed as a novel treatment for Tchemotherapy-resistant myeloid leukemias. In vivo, LV-10 cells do not cause graft-versus-host disease while mediating graft-versus-leukemia effect against adult acute myeloid leukemia (AML). Since pediatric AML (pAML) and adult AML are different on a genetic and epigenetic level, we investigate herein whether LV-10 cells also efficiently kill pAML cells. We show that the majority of primary pAML are killed by LV-10 cells, with different levels of sensitivity to killing. Transcriptionally, pAML sensitive to LV-10 killing expressed a myeloid maturation signature.
    [Show full text]
  • Analysis of the Impact of Pufas on Placental Gene Expression V2.28 Uploadx
    TECHNISCHE UNIVERSITÄT MÜNCHEN Lehrstuhl für Ernährungsmedizin Analysis of the Impact of Polyunsaturated Fatty Acids (PUFAs) on Placental Gene Expression Eva-Maria Sedlmeier Vollständiger Abdruck der von der Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr. M. Klingenspor Prüfer der Dissertation: 1. Univ.-Prof. Dr. J. J. Hauner 2. Univ.-Prof. Dr. H. Daniel Die Dissertation wurde am 17.10.2013 bei der Technischen Universität München eingereicht und durch die Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt am 12.12.2013 angenommen. Table of contents Table of contents Table of contents ....................................................................................................... I Summary .................................................................................................................. VI Zusammenfassung ................................................................................................ VIII 1. Introduction ........................................................................................................ 1 1.1. Fetal programming - a strategy to prevent the obesity epidemic? ...........................................1 1.1.1. The obesity epidemic ........................................................................................................1 1.1.2. Fetal programming
    [Show full text]