BACKGROUND: Sensitive triplex nucleic acid tests (NATs) are implemented for blood donation screening worldwide. Assays have variable ability to detect low-level hepatitis B virus (HBV) DNA. At borderline DNA detection levels, where Poisson distribution impacts results, distinguishing true-positive from false-positive results is challenging. Algorithms are needed to confirm such low-level HBV DNA-positive samples. STUDY DESIGN AND METHODS: A total of 135 blood donor samples reactive by one or more HBV markers that provided discrepant results were tested undiluted with four commercial NATs: Ultrio, Ultrio Plus, MPX, and a quantitative assay (SuperQuant). To further explore discrepancies, three additional in-house NATs including real-time polymerase chain reaction (PCR) and nested PCR and sequencing were performed. RESULTS: The numbers reactive of these 135 "difficult" samples by four commercial NATs were as follows: 39 of 107 (36%) with SuperQuant, 40 (30%) with Ultrio, 100 (74%) with Ultrio Plus, and 102 (76%) with MPX. Of the seven NATs, 109 (81%) samples were reactive by at least two assays and thus considered confirmed positive of which 67 (50%) generated a sequence. Ultrio Plus and MPX performed similarly as above (80%-85% detected of 109 and 81%-90% of 67, respectively). Older (median, 49 years), HBV core antibody-reactive donors carried predominantly Genotype A (58%) with high-frequency amino acid substitutions in the major hydrophilic region of the S-protein. Younger (median, 24 years) hepatitis B surface antigen-positive donors carried wild-type strains predominantly Genotype B (32%) and E (24%), the latter in an apparent cluster. CONCLUSIONS: Highly sensitive NATs require new confirmatory algorithms as presented optimally using different genomic regions or sequence generation. The introduction of immigration-related HBV genotypes may impact HBV epidemiology in the United States.
BACKGROUND: Sensitive triplex nucleic acid tests (NATs) are implemented for blood donation screening worldwide. Assays have variable ability to detect low-level hepatitis B virus (HBV) DNA. At borderline DNA detection levels, where Poisson distribution impacts results, distinguishing true-positive from false-positive results is challenging. Algorithms are needed to confirm such low-level HBV DNA-positive samples. STUDY DESIGN AND METHODS: A total of 135 blood donor samples reactive by one or more HBV markers that provided discrepant results were tested undiluted with four commercial NATs: Ultrio, Ultrio Plus, MPX, and a quantitative assay (SuperQuant). To further explore discrepancies, three additional in-house NATs including real-time polymerase chain reaction (PCR) and nested PCR and sequencing were performed. RESULTS: The numbers reactive of these 135 "difficult" samples by four commercial NATs were as follows: 39 of 107 (36%) with SuperQuant, 40 (30%) with Ultrio, 100 (74%) with Ultrio Plus, and 102 (76%) with MPX. Of the seven NATs, 109 (81%) samples were reactive by at least two assays and thus considered confirmed positive of which 67 (50%) generated a sequence. Ultrio Plus and MPX performed similarly as above (80%-85% detected of 109 and 81%-90% of 67, respectively). Older (median, 49 years), HBV core antibody-reactive donors carried predominantly Genotype A (58%) with high-frequency amino acid substitutions in the major hydrophilic region of the S-protein. Younger (median, 24 years) hepatitis B surface antigen-positive donors carried wild-type strains predominantly Genotype B (32%) and E (24%), the latter in an apparent cluster. CONCLUSIONS: Highly sensitive NATs require new confirmatory algorithms as presented optimally using different genomic regions or sequence generation. The introduction of immigration-related HBV genotypes may impact HBV epidemiology in the United States.
Authors: Sumathi Ramachandran; Jamel A Groves; Guo-Liang Xia; Paula Saá; Edward P Notari; Jan Drobeniuc; Amanda Poe; Natasha Khudyakov; Sarah F Schillie; Trudy V Murphy; Saleem Kamili; Chong-Gee Teo; Roger Y Dodd; Yury E Khudyakov; Susan L Stramer Journal: Transfusion Date: 2018-11-30 Impact factor: 3.157
Authors: Antonella Esposito; Chiara Sabia; Carmela Iannone; Giovanni F Nicoletti; Linda Sommese; Claudio Napoli Journal: Transfus Med Hemother Date: 2017-05-05 Impact factor: 3.747