Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients

Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We use...
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Autor*in:	Brunekreef, Tammo E. [verfasserIn] Reteig, Leon C. [verfasserIn] Limper, Maarten [verfasserIn] Haitjema, Saskia [verfasserIn] Dias, Jorge [verfasserIn] Mathsson-Alm, Linda [verfasserIn] van Laar, Jacob M. [verfasserIn] Otten, Henny G. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Systemic Lupus Erythematosus Early diagnosis Autoantibodies Prediction model

Übergeordnetes Werk:	Enthalten in: Human immunology - Amsterdam [u.a.] : Elsevier Science, 1980, 83, Seite 509-514
Übergeordnetes Werk:	volume:83 ; pages:509-514

DOI / URN:	10.1016/j.humimm.2022.03.010

Katalog-ID:	ELV057631522

Internformat


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024	7		\|a 10.1016/j.humimm.2022.03.010 \|2 doi
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100	1		\|a Brunekreef, Tammo E. \|e verfasserin \|4 aut
245	1	0	\|a Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients
264		1	\|c 2022
336			\|a nicht spezifiziert \|b zzz \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients.
650		4	\|a Systemic Lupus Erythematosus
650		4	\|a Early diagnosis
650		4	\|a Autoantibodies
650		4	\|a Prediction model
700	1		\|a Reteig, Leon C. \|e verfasserin \|4 aut
700	1		\|a Limper, Maarten \|e verfasserin \|4 aut
700	1		\|a Haitjema, Saskia \|e verfasserin \|4 aut
700	1		\|a Dias, Jorge \|e verfasserin \|4 aut
700	1		\|a Mathsson-Alm, Linda \|e verfasserin \|4 aut
700	1		\|a van Laar, Jacob M. \|e verfasserin \|4 aut
700	1		\|a Otten, Henny G. \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Human immunology \|d Amsterdam [u.a.] : Elsevier Science, 1980 \|g 83, Seite 509-514 \|h Online-Ressource \|w (DE-627)320454479 \|w (DE-600)2006465-2 \|w (DE-576)094477019 \|x 1879-1166 \|7 nnns
773	1	8	\|g volume:83 \|g pages:509-514
912			\|a GBV_USEFLAG_U
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912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_32
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_101
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_224
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
936	b	k	\|a 44.45 \|j Immunologie \|q VZ
951			\|a AR
952			\|d 83 \|h 509-514

Indexfelder

author_variant	t e b te teb l c r lc lcr m l ml s h sh j d jd l m a lma l j m v ljm ljmv h g o hg hgo
matchkey_str	article:18791166:2022----::irarynlssfuonioisaietfftrsseilp
hierarchy_sort_str	2022
bklnumber	44.45
publishDate	2022
allfields	10.1016/j.humimm.2022.03.010 doi (DE-627)ELV057631522 (ELSEVIER)S0198-8859(22)00070-2 DE-627 ger DE-627 rda eng 610 VZ 44.45 bkl Brunekreef, Tammo E. verfasserin aut Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients. Systemic Lupus Erythematosus Early diagnosis Autoantibodies Prediction model Reteig, Leon C. verfasserin aut Limper, Maarten verfasserin aut Haitjema, Saskia verfasserin aut Dias, Jorge verfasserin aut Mathsson-Alm, Linda verfasserin aut van Laar, Jacob M. verfasserin aut Otten, Henny G. verfasserin aut Enthalten in Human immunology Amsterdam [u.a.] : Elsevier Science, 1980 83, Seite 509-514 Online-Ressource (DE-627)320454479 (DE-600)2006465-2 (DE-576)094477019 1879-1166 nnns volume:83 pages:509-514 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.45 Immunologie VZ AR 83 509-514
spelling	10.1016/j.humimm.2022.03.010 doi (DE-627)ELV057631522 (ELSEVIER)S0198-8859(22)00070-2 DE-627 ger DE-627 rda eng 610 VZ 44.45 bkl Brunekreef, Tammo E. verfasserin aut Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients. Systemic Lupus Erythematosus Early diagnosis Autoantibodies Prediction model Reteig, Leon C. verfasserin aut Limper, Maarten verfasserin aut Haitjema, Saskia verfasserin aut Dias, Jorge verfasserin aut Mathsson-Alm, Linda verfasserin aut van Laar, Jacob M. verfasserin aut Otten, Henny G. verfasserin aut Enthalten in Human immunology Amsterdam [u.a.] : Elsevier Science, 1980 83, Seite 509-514 Online-Ressource (DE-627)320454479 (DE-600)2006465-2 (DE-576)094477019 1879-1166 nnns volume:83 pages:509-514 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.45 Immunologie VZ AR 83 509-514
allfields_unstemmed	10.1016/j.humimm.2022.03.010 doi (DE-627)ELV057631522 (ELSEVIER)S0198-8859(22)00070-2 DE-627 ger DE-627 rda eng 610 VZ 44.45 bkl Brunekreef, Tammo E. verfasserin aut Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients. Systemic Lupus Erythematosus Early diagnosis Autoantibodies Prediction model Reteig, Leon C. verfasserin aut Limper, Maarten verfasserin aut Haitjema, Saskia verfasserin aut Dias, Jorge verfasserin aut Mathsson-Alm, Linda verfasserin aut van Laar, Jacob M. verfasserin aut Otten, Henny G. verfasserin aut Enthalten in Human immunology Amsterdam [u.a.] : Elsevier Science, 1980 83, Seite 509-514 Online-Ressource (DE-627)320454479 (DE-600)2006465-2 (DE-576)094477019 1879-1166 nnns volume:83 pages:509-514 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.45 Immunologie VZ AR 83 509-514
allfieldsGer	10.1016/j.humimm.2022.03.010 doi (DE-627)ELV057631522 (ELSEVIER)S0198-8859(22)00070-2 DE-627 ger DE-627 rda eng 610 VZ 44.45 bkl Brunekreef, Tammo E. verfasserin aut Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients. Systemic Lupus Erythematosus Early diagnosis Autoantibodies Prediction model Reteig, Leon C. verfasserin aut Limper, Maarten verfasserin aut Haitjema, Saskia verfasserin aut Dias, Jorge verfasserin aut Mathsson-Alm, Linda verfasserin aut van Laar, Jacob M. verfasserin aut Otten, Henny G. verfasserin aut Enthalten in Human immunology Amsterdam [u.a.] : Elsevier Science, 1980 83, Seite 509-514 Online-Ressource (DE-627)320454479 (DE-600)2006465-2 (DE-576)094477019 1879-1166 nnns volume:83 pages:509-514 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.45 Immunologie VZ AR 83 509-514
allfieldsSound	10.1016/j.humimm.2022.03.010 doi (DE-627)ELV057631522 (ELSEVIER)S0198-8859(22)00070-2 DE-627 ger DE-627 rda eng 610 VZ 44.45 bkl Brunekreef, Tammo E. verfasserin aut Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients. Systemic Lupus Erythematosus Early diagnosis Autoantibodies Prediction model Reteig, Leon C. verfasserin aut Limper, Maarten verfasserin aut Haitjema, Saskia verfasserin aut Dias, Jorge verfasserin aut Mathsson-Alm, Linda verfasserin aut van Laar, Jacob M. verfasserin aut Otten, Henny G. verfasserin aut Enthalten in Human immunology Amsterdam [u.a.] : Elsevier Science, 1980 83, Seite 509-514 Online-Ressource (DE-627)320454479 (DE-600)2006465-2 (DE-576)094477019 1879-1166 nnns volume:83 pages:509-514 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.45 Immunologie VZ AR 83 509-514
language	English
source	Enthalten in Human immunology 83, Seite 509-514 volume:83 pages:509-514
sourceStr	Enthalten in Human immunology 83, Seite 509-514 volume:83 pages:509-514
format_phy_str_mv	Article
bklname	Immunologie
institution	findex.gbv.de
topic_facet	Systemic Lupus Erythematosus Early diagnosis Autoantibodies Prediction model
dewey-raw	610
isfreeaccess_bool	false
container_title	Human immunology
authorswithroles_txt_mv	Brunekreef, Tammo E. @@aut@@ Reteig, Leon C. @@aut@@ Limper, Maarten @@aut@@ Haitjema, Saskia @@aut@@ Dias, Jorge @@aut@@ Mathsson-Alm, Linda @@aut@@ van Laar, Jacob M. @@aut@@ Otten, Henny G. @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	320454479
dewey-sort	3610
id	ELV057631522
language_de	englisch
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author	Brunekreef, Tammo E.
spellingShingle	Brunekreef, Tammo E. ddc 610 bkl 44.45 misc Systemic Lupus Erythematosus misc Early diagnosis misc Autoantibodies misc Prediction model Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients
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topic_title	610 VZ 44.45 bkl Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients Systemic Lupus Erythematosus Early diagnosis Autoantibodies Prediction model
topic	ddc 610 bkl 44.45 misc Systemic Lupus Erythematosus misc Early diagnosis misc Autoantibodies misc Prediction model
topic_unstemmed	ddc 610 bkl 44.45 misc Systemic Lupus Erythematosus misc Early diagnosis misc Autoantibodies misc Prediction model
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title	Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients
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title_full	Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients
author_sort	Brunekreef, Tammo E.
journal	Human immunology
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author_browse	Brunekreef, Tammo E. Reteig, Leon C. Limper, Maarten Haitjema, Saskia Dias, Jorge Mathsson-Alm, Linda van Laar, Jacob M. Otten, Henny G.
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author-letter	Brunekreef, Tammo E.
doi_str_mv	10.1016/j.humimm.2022.03.010
dewey-full	610
author2-role	verfasserin
title_sort	microarray analysis of autoantibodies can identify future systemic lupus erythematosus patients
title_auth	Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients
abstract	Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients.
abstractGer	Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients.
abstract_unstemmed	Objective: Reliable early ascertainment in patients with SLE is important to prevent the accumulation of irreversible organ damage. Autoantibodies are often present in the serum of patients before the first symptoms arise, therefore they are of potential use as early diagnostic tools.Methods: We used a custom-made antibody microarray containing 57 autoantigens to analyze serum samples of 1519 patients previously tested for anti-dsDNA and 361 samples of self-reported healthy blood bank donors (BBD). The 1519 patients included 483 patients with SLE, 346 patients with other immune mediated inflammatory diseases (IMID), 218 patient controls without relevant clinical symptoms (Non-IMID), and 472 patients that did not fit in any of the previous groups (Rest). The Non-IMID and BBD groups were used individually to create multivariable prediction models to distinguish samples of patients with SLE from these control groups. We subsequently used these models to predict the outcome for samples of patients who developed SLE while in follow-up (pre-SLE).Results: Out of 1036 patients with no diagnosis of SLE at the moment of sample collection, 17 patients developed SLE while in follow-up (mean time to diagnosis 7.2 months). The best performing model (AUC 0.83) identified 9 out of 17 (53%) pre-SLE samples as SLE, with a specificity of 94%.Conclusion: Serum samples of patients who will develop SLE in the future already show a shift of the autoantibody profile prior to diagnosis. In this study, we show that these autoantibody profiles can be used to identify these future SLE patients.
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title_short	Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients
remote_bool	true
author2	Reteig, Leon C. Limper, Maarten Haitjema, Saskia Dias, Jorge Mathsson-Alm, Linda van Laar, Jacob M. Otten, Henny G.
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doi_str	10.1016/j.humimm.2022.03.010
up_date	2024-07-06T16:42:16.690Z
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Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients

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