Lynn Pique1, Steve Graham2, Michelle Pearl3, Martin Kharrazi4, Iris Schrijver1,5. 1. Department of Pathology, Stanford University Medical Center, Stanford, California, USA. 2. Genetic Disease Screening Program, California Department of Public Health, Richmond, California, USA. 3. Sequoia Foundation, La Jolla, California, USA. 4. Environmental Health Investigations Branch, California Department of Public Health, Richmond, California, USA. 5. Department of Pediatrics, Stanford University Medical Center, Stanford, California, USA.
Abstract
PURPOSE: Cystic fibrosis newborn screening (CFNBS) has been offered across the United States since 2010. However, as compared with white patients with CF, CFTR variant identification in nonwhite populations remains inequitable. Utilizing the recent characterization of the nonwhite CF variant spectrum, we examined the effectiveness of current CFNBS molecular panels in identifying affected nonwhite newborns. METHODS: Based on a cross-sectional evaluation of genotyping data from the CF Foundation Patient Registry that compared 3,496 nonwhite with 22,206 white CF patients, the current CFNBS algorithms used in the 50 states and the District of Columbia were analyzed. We assessed the percentage of CF patients of Hispanic, African, Asian, and Native American heritage who would not be identified by the molecular panels most commonly used. RESULTS: Compared with whites, variant detection was significantly lower in Hispanic, black, and Asian newborns (P ≤ 0.0001 each), as well as in Native American newborns (P values ranged from 0.001 to 0.0003), for the most common CFNBS panels. CONCLUSION: This study provides a perspective on the applicability of current panels to a diverse population and enables CFNBS programs to consider more inclusive test approaches to facilitate diagnosis, timely clinical intervention, and enhanced prognosis for CF patients of nonwhite and mixed ethnicities.Genet Med 19 1, 36-44.
PURPOSE: Cystic fibrosis newborn screening (CFNBS) has been offered across the United States since 2010. However, as compared with white patients with CF, CFTR variant identification in nonwhite populations remains inequitable. Utilizing the recent characterization of the nonwhite CF variant spectrum, we examined the effectiveness of current CFNBS molecular panels in identifying affected nonwhite newborns. METHODS: Based on a cross-sectional evaluation of genotyping data from the CF Foundation Patient Registry that compared 3,496 nonwhite with 22,206 white CF patients, the current CFNBS algorithms used in the 50 states and the District of Columbia were analyzed. We assessed the percentage of CF patients of Hispanic, African, Asian, and Native American heritage who would not be identified by the molecular panels most commonly used. RESULTS: Compared with whites, variant detection was significantly lower in Hispanic, black, and Asian newborns (P ≤ 0.0001 each), as well as in Native American newborns (P values ranged from 0.001 to 0.0003), for the most common CFNBS panels. CONCLUSION: This study provides a perspective on the applicability of current panels to a diverse population and enables CFNBS programs to consider more inclusive test approaches to facilitate diagnosis, timely clinical intervention, and enhanced prognosis for CF patients of nonwhite and mixed ethnicities.Genet Med 19 1, 36-44.
Authors: M Elske van den Akker-van Marle; Hinke M Dankert; Paul H Verkerk; Jeannette E Dankert-Roelse Journal: Pediatrics Date: 2006-09 Impact factor: 7.124
Authors: Daniel S Grosu; Lynda Hague; Manjula Chelliserry; Kristina M Kruglyak; Ross Lenta; Brandy Klotzle; Jonathan San; Wendy M Goldstein; Sharmili Moturi; Patricia Devers; Julie Woolworth; Eric Peters; Barbara Elashoff; Jay Stoerker; Daynna J Wolff; Kenneth J Friedman; W Edward Highsmith; Erick Lin; Frank S Ong Journal: Expert Rev Mol Diagn Date: 2014-06 Impact factor: 5.225
Authors: Scott D Grosse; Coleen A Boyle; Jeffrey R Botkin; Anne Marie Comeau; Martin Kharrazi; Margaret Rosenfeld; Benjamin S Wilfond Journal: MMWR Recomm Rep Date: 2004-10-15
Authors: Ahmad N Abou Tayoun; Christopher D Tunkey; Trevor J Pugh; Tristen Ross; Minita Shah; Clarence C Lee; Timothy T Harkins; Wendy A Wells; Laura J Tafe; Christopher I Amos; Gregory J Tsongalis Journal: Clin Chem Date: 2013-06-17 Impact factor: 8.327
Authors: Lisa Prach; Ruth Koepke; Martin Kharrazi; Steven Keiles; Danieli B Salinas; Maria Carmen Reyes; Mark Pian; Harry Opsimos; Kimberly N Otsuka; Karen Ann Hardy; Carlos E Milla; Jacquelyn M Zirbes; Bradley Chipps; Susan O'Bra; Muhammad M Saeed; Reddivalam Sudhakar; Susan Lehto; Dennis Nielson; Gregory F Shay; Mary Seastrand; Sanjay Jhawar; Bruce Nickerson; Christopher Landon; Ann Thompson; Eliezer Nussbaum; Terry Chin; Henry Wojtczak Journal: J Mol Diagn Date: 2013-06-28 Impact factor: 5.568
Authors: Martina I Lefterova; Peidong Shen; Justin I Odegaard; Eula Fung; Tsoyu Chiang; Gang Peng; Ronald W Davis; Wenyi Wang; Martin Kharrazi; Iris Schrijver; Curt Scharfe Journal: J Mol Diagn Date: 2016-02-01 Impact factor: 5.568
Authors: Mei W Baker; Anne E Atkins; Suzanne K Cordovado; Miyono Hendrix; Marie C Earley; Philip M Farrell Journal: Genet Med Date: 2015-02-12 Impact factor: 8.822
Authors: Doron M Behar; Ori Inbar; Michal Shteinberg; Michal Gur; Huda Mussaffi; David Shoseyov; Moshe Ashkenazi; Soliman Alkrinawi; Concetta Bormans; Fahed Hakim; Meir Mei-Zahav; Malena Cohen-Cymberknoh; Adi Dagan; Dario Prais; Ifat Sarouk; Patrick Stafler; Bat El Bar Aluma; Gidon Akler; Elie Picard; Micha Aviram; Ori Efrati; Galit Livnat; Joseph Rivlin; Lea Bentur; Hannah Blau; Eitan Kerem; Amihood Singer Journal: Mol Genet Genomic Med Date: 2017-02-19 Impact factor: 2.183