OBJECTIVE: To map the occurrence of amyloid types in a large clinical cohort using mass spectrometry-based shotgun proteomics, an unbiased method that unambiguously identifies all amyloid types in a single assay. METHODS: A mass spectrometry-based shotgun proteomics assay was implemented in a central reference laboratory. We documented our experience of typing 16,175 amyloidosis specimens over an 11-year period from January 1, 2008, to December 31, 2018. RESULTS: We identified 21 established amyloid types, including AL (n=9542; 59.0%), ATTR (n=4600; 28.4%), ALECT2 (n=511; 3.2%), AA (n=463; 2.9%), AH (n=367; 2.3%), AIns (n=182; 1.2%), KRT5-14 (n=94; <1%), AFib (n=71; <1%), AApoAIV (n=57; <1%), AApoA1 (n=56; <1%), AANF (n=47; <1%), Aβ2M (n=38; <1%), ASem1 (n=34; <1%), AGel (n=29; <1%), TGFB1 (n=29; <1%), ALys (n=15; <1%), AIAPP (n=13; <1%), AApoCII (n=11; <1%), APro (n=8; <1%), AEnf (n=6; <1%), and ACal (n=2; <1%). We developed the first comprehensive organ-by-type map showing the relative frequency of 21 amyloid types in 31 different organs, and the first type-by-organ map showing organ tropism of 18 rare types. Using a modified bioinformatics pipeline, we detected amino acid substitutions in cases of hereditary amyloidosis with 100% specificity. CONCLUSION: Amyloid typing by proteomics, which effectively recognizes all amyloid types in a single assay, optimally supports the diagnosis and treatment of amyloidosis patients in routine clinical practice.
OBJECTIVE: To map the occurrence of amyloid types in a large clinical cohort using mass spectrometry-based shotgun proteomics, an unbiased method that unambiguously identifies all amyloid types in a single assay. METHODS: A mass spectrometry-based shotgun proteomics assay was implemented in a central reference laboratory. We documented our experience of typing 16,175 amyloidosis specimens over an 11-year period from January 1, 2008, to December 31, 2018. RESULTS: We identified 21 established amyloid types, including AL (n=9542; 59.0%), ATTR (n=4600; 28.4%), ALECT2 (n=511; 3.2%), AA (n=463; 2.9%), AH (n=367; 2.3%), AIns (n=182; 1.2%), KRT5-14 (n=94; <1%), AFib (n=71; <1%), AApoAIV (n=57; <1%), AApoA1 (n=56; <1%), AANF (n=47; <1%), Aβ2M (n=38; <1%), ASem1 (n=34; <1%), AGel (n=29; <1%), TGFB1 (n=29; <1%), ALys (n=15; <1%), AIAPP (n=13; <1%), AApoCII (n=11; <1%), APro (n=8; <1%), AEnf (n=6; <1%), and ACal (n=2; <1%). We developed the first comprehensive organ-by-type map showing the relative frequency of 21 amyloid types in 31 different organs, and the first type-by-organ map showing organ tropism of 18 rare types. Using a modified bioinformatics pipeline, we detected amino acid substitutions in cases of hereditary amyloidosis with 100% specificity. CONCLUSION: Amyloid typing by proteomics, which effectively recognizes all amyloid types in a single assay, optimally supports the diagnosis and treatment of amyloidosispatients in routine clinical practice.
Authors: Surbhi Sidana; Surendra Dasari; Taxiarchis V Kourelis; Angela Dispenzieri; David L Murray; Rebecca L King; Ellen D McPhail; Marina Ramirez-Alvarado; Shaji K Kumar; Morie A Gertz Journal: Blood Adv Date: 2021-04-27
Authors: Michelle M Hill; Surendra Dasari; Peter Mollee; Giampaolo Merlini; Catherine E Costello; Bouke P C Hazenberg; Martha Grogan; Angela Dispenzieri; Morie A Gertz; Taxiarchis Kourelis; Ellen D McPhail Journal: Mayo Clin Proc Date: 2021-04-09 Impact factor: 11.104
Authors: Surendra Dasari; Angela Dispenzieri; Shareef Mansour; Prasuna Muppa; Paul J Kurtin; Jason D Theis; Julie A Vrana; Martha Grogan; Taxiarchis Kourelis; Morie A Gertz; Ellen D McPhail Journal: ESC Heart Fail Date: 2020-12-05
Authors: Cristina Chimenti; Maria Alfarano; Viviana Maestrini; Nicola Galea; Giuseppe De Vincentis; Romina Verardo; Francesco Fedele; Andrea Frustaci Journal: ESC Heart Fail Date: 2021-05-25