BACKGROUND: Insulin-like growth factor 1 (IGF-1)(7) is a key mediator of growth hormone (GH) action and a well-characterized biomarker of GH abuse. Current immunoassays for IGF-1 suffer from poor concordance between platforms, which makes comparison of results between laboratories difficult. Although previous work has demonstrated good interlaboratory imprecision of LC-MS/MS methods when plasma is supplemented with purified proteins, the interlaboratory imprecision of an endogenous protein in the nanogram-per-milliliter concentration range has not been reported. METHODS: We deployed an LC-MS/MS method to quantify serum IGF-1 in 5 laboratories using 5 different instruments and analyzed 130 healthy human samples and 22 samples from patients with acromegaly. We determined measurement imprecision (CV) for differences due to instrumentation, calibration curve construction, method of calibration, and reference material. RESULTS: Instrument-dependent variation, exclusive of digestion, across 5 different instrument platforms was determined to be 5.6%. Interlaboratory variation was strongly dependent on calibration. Calibration materials from a single laboratory resulted in less variation than materials made in individual laboratories (CV 5.2% vs 12.8%, respectively). The mean imprecision for 152 samples between the 5 laboratories was 16.0% when a calibration curve was made in each laboratory and 11.1% when a single-point calibration approach was used. CONCLUSIONS: The interlaboratory imprecision of serum IGF-1 concentrations is acceptable for use of the assay in antidoping laboratories and in standardizing results across clinical laboratories. The primary source of variability is not derived from the sample preparation but from the method of calibration.
BACKGROUND:Insulin-like growth factor 1 (IGF-1)(7) is a key mediator of growth hormone (GH) action and a well-characterized biomarker of GH abuse. Current immunoassays for IGF-1 suffer from poor concordance between platforms, which makes comparison of results between laboratories difficult. Although previous work has demonstrated good interlaboratory imprecision of LC-MS/MS methods when plasma is supplemented with purified proteins, the interlaboratory imprecision of an endogenous protein in the nanogram-per-milliliter concentration range has not been reported. METHODS: We deployed an LC-MS/MS method to quantify serum IGF-1 in 5 laboratories using 5 different instruments and analyzed 130 healthy human samples and 22 samples from patients with acromegaly. We determined measurement imprecision (CV) for differences due to instrumentation, calibration curve construction, method of calibration, and reference material. RESULTS: Instrument-dependent variation, exclusive of digestion, across 5 different instrument platforms was determined to be 5.6%. Interlaboratory variation was strongly dependent on calibration. Calibration materials from a single laboratory resulted in less variation than materials made in individual laboratories (CV 5.2% vs 12.8%, respectively). The mean imprecision for 152 samples between the 5 laboratories was 16.0% when a calibration curve was made in each laboratory and 11.1% when a single-point calibration approach was used. CONCLUSIONS: The interlaboratory imprecision of serum IGF-1 concentrations is acceptable for use of the assay in antidoping laboratories and in standardizing results across clinical laboratories. The primary source of variability is not derived from the sample preparation but from the method of calibration.
Authors: Jeffrey R Whiteaker; Goran N Halusa; Andrew N Hoofnagle; Vagisha Sharma; Brendan MacLean; Ping Yan; John A Wrobel; Jacob Kennedy; D R Mani; Lisa J Zimmerman; Matthew R Meyer; Mehdi Mesri; Henry Rodriguez; Amanda G Paulovich Journal: Nat Methods Date: 2014-07 Impact factor: 28.547
Authors: Andrew N Hoofnagle; Jeffrey R Whiteaker; Steven A Carr; Eric Kuhn; Tao Liu; Sam A Massoni; Stefani N Thomas; R Reid Townsend; Lisa J Zimmerman; Emily Boja; Jing Chen; Daniel L Crimmins; Sherri R Davies; Yuqian Gao; Tara R Hiltke; Karen A Ketchum; Christopher R Kinsinger; Mehdi Mesri; Matthew R Meyer; Wei-Jun Qian; Regine M Schoenherr; Mitchell G Scott; Tujin Shi; Gordon R Whiteley; John A Wrobel; Chaochao Wu; Brad L Ackermann; Ruedi Aebersold; David R Barnidge; David M Bunk; Nigel Clarke; Jordan B Fishman; Russ P Grant; Ulrike Kusebauch; Mark M Kushnir; Mark S Lowenthal; Robert L Moritz; Hendrik Neubert; Scott D Patterson; Alan L Rockwood; John Rogers; Ravinder J Singh; Jennifer E Van Eyk; Steven H Wong; Shucha Zhang; Daniel W Chan; Xian Chen; Matthew J Ellis; Daniel C Liebler; Karin D Rodland; Henry Rodriguez; Richard D Smith; Zhen Zhang; Hui Zhang; Amanda G Paulovich Journal: Clin Chem Date: 2016-01 Impact factor: 8.327
Authors: Vivien Bonert; John Carmichael; Zengru Wu; James Mirocha; Daniel A Perez; Nigel J Clarke; Richard E Reitz; Michael J McPhaul; Adam Mamelak Journal: Pituitary Date: 2018-02 Impact factor: 4.107
Authors: Maximilian Bielohuby; Sayyed Hamid Zarkesh-Esfahani; Jenny Manolopoulou; Elisa Wirthgen; Katja Walpurgis; Mohaddeseh Toghiany Khorasgani; Zahra Sadat Aghili; Ian Robert Wilkinson; Andreas Hoeflich; Mario Thevis; Richard J Ross; Martin Bidlingmaier Journal: Dis Model Mech Date: 2014-09-19 Impact factor: 5.758
Authors: Ehwang Song; Yuqian Gao; Chaochao Wu; Tujin Shi; Song Nie; Thomas L Fillmore; Athena A Schepmoes; Marina A Gritsenko; Wei-Jun Qian; Richard D Smith; Karin D Rodland; Tao Liu Journal: Sci Data Date: 2017-07-19 Impact factor: 6.444