Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth

Yu Chung Lin; Katherine Keenan; Jiafen Gong; Naim Panjwani; Julie Avolio; Fan Lin; Damien Adam; Paula Barrett; Stéphanie Bégin; Yves Berthiaume; Lara Bilodeau; Candice Bjornson; Janna Brusky; Caroline Burgess; Mark Chilvers; Raquel Consunji-Araneta; Guillaume Côté-Maurais; Andrea Dale; Christine Donnelly; Lori Fairservice; Katie Griffin; Natalie Henderson; Angela Hillaby; Daniel Hughes; Shaikh Iqbal; Jennifer Itterman; Mary Jackson; Emma Karlsen; Lorna Kosteniuk; Lynda Lazosky; Winnie Leung; Valerie Levesque; Émilie Maille; Dimas Mateos-Corral; Vanessa McMahon; Mays Merjaneh; Nancy Morrison; Michael Parkins; Jennifer Pike; April Price; Bradley S. Quon; Joe Reisman; Clare Smith; Mary Jane Smith; Nathalie Vadeboncoeur; Danny Veniott; Terry Viczko; Pearce Wilcox; Richard van Wylick; Garry Cutting; Elizabeth Tullis; Felix Ratjen; Johanna M. Rommens; Lei Sun; Melinda Solomon; Anne L. Stephenson; Emmanuelle Brochiero; Scott Blackman; Harriet Corvol; Lisa J. Strug

doi:10.1038/s41436-020-01073-x

Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth

Yu Chung Lin, Katherine Keenan, Jiafen Gong, Naim Panjwani, Julie Avolio, Fan Lin, Damien Adam, Paula Barrett, Stéphanie Bégin, Yves Berthiaume, Lara Bilodeau, Candice Bjornson, Janna Brusky, Caroline Burgess, Mark Chilvers, Raquel Consunji-Araneta, Guillaume Côté-Maurais, Andrea Dale, Christine Donnelly, Lori FairserviceKatie Griffin, Natalie Henderson, Angela Hillaby, Daniel Hughes, Shaikh Iqbal, Jennifer Itterman, Mary Jackson, Emma Karlsen, Lorna Kosteniuk, Lynda Lazosky, Winnie Leung, Valerie Levesque, Émilie Maille, Dimas Mateos-Corral, Vanessa McMahon, Mays Merjaneh, Nancy Morrison, Michael Parkins, Jennifer Pike, April Price, Bradley S. Quon, Joe Reisman, Clare Smith, Mary Jane Smith, Nathalie Vadeboncoeur, Danny Veniott, Terry Viczko, Pearce Wilcox, Richard van Wylick, Garry Cutting, Elizabeth Tullis, Felix Ratjen, Johanna M. Rommens, Lei Sun, Melinda Solomon, Anne L. Stephenson, Emmanuelle Brochiero, Scott Blackman, Harriet Corvol, Lisa J. Strug

School of Medicine

Research output: Contribution to journal › Article › peer-review

Abstract

Purpose: Cystic fibrosis (CF), caused by pathogenic variants in the CF transmembrane conductance regulator (CFTR), affects multiple organs including the exocrine pancreas, which is a causal contributor to cystic fibrosis–related diabetes (CFRD). Untreated CFRD causes increased CF-related mortality whereas early detection can improve outcomes. Methods: Using genetic and easily accessible clinical measures available at birth, we constructed a CFRD prediction model using the Canadian CF Gene Modifier Study (CGS; n = 1,958) and validated it in the French CF Gene Modifier Study (FGMS; n = 1,003). We investigated genetic variants shown to associate with CF disease severity across multiple organs in genome-wide association studies. Results: The strongest predictors included sex, CFTR severity score, and several genetic variants including one annotated to PRSS1, which encodes cationic trypsinogen. The final model defined in the CGS shows excellent agreement when validated on the FGMS, and the risk classifier shows slightly better performance at predicting CFRD risk later in life in both studies. Conclusion: We demonstrated clinical utility by comparing CFRD prevalence rates between the top 10% of individuals with the highest risk and the bottom 10% with the lowest risk. A web-based application was developed to provide practitioners with patient-specific CFRD risk to guide CFRD monitoring and treatment.

Original language	English (US)
Pages (from-to)	927-933
Number of pages	7
Journal	Genetics in Medicine
Volume	23
Issue number	5
DOIs	https://doi.org/10.1038/s41436-020-01073-x
State	Published - May 2021

ASJC Scopus subject areas

Genetics(clinical)

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Lin, Y. C., Keenan, K., Gong, J., Panjwani, N., Avolio, J., Lin, F., Adam, D., Barrett, P., Bégin, S., Berthiaume, Y., Bilodeau, L., Bjornson, C., Brusky, J., Burgess, C., Chilvers, M., Consunji-Araneta, R., Côté-Maurais, G., Dale, A., Donnelly, C., ... Strug, L. J. (2021). Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth. Genetics in Medicine, 23(5), 927-933. https://doi.org/10.1038/s41436-020-01073-x

Lin, YC, Keenan, K, Gong, J, Panjwani, N, Avolio, J, Lin, F, Adam, D, Barrett, P, Bégin, S, Berthiaume, Y, Bilodeau, L, Bjornson, C, Brusky, J, Burgess, C, Chilvers, M, Consunji-Araneta, R, Côté-Maurais, G, Dale, A, Donnelly, C, Fairservice, L, Griffin, K, Henderson, N, Hillaby, A, Hughes, D, Iqbal, S, Itterman, J, Jackson, M, Karlsen, E, Kosteniuk, L, Lazosky, L, Leung, W, Levesque, V, Maille, É, Mateos-Corral, D, McMahon, V, Merjaneh, M, Morrison, N, Parkins, M, Pike, J, Price, A, Quon, BS, Reisman, J, Smith, C, Smith, MJ, Vadeboncoeur, N, Veniott, D, Viczko, T, Wilcox, P, van Wylick, R, Cutting, G, Tullis, E, Ratjen, F, Rommens, JM, Sun, L, Solomon, M, Stephenson, AL, Brochiero, E, Blackman, S, Corvol, H & Strug, LJ 2021, 'Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth', Genetics in Medicine, vol. 23, no. 5, pp. 927-933. https://doi.org/10.1038/s41436-020-01073-x

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title = "Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth",

abstract = "Purpose: Cystic fibrosis (CF), caused by pathogenic variants in the CF transmembrane conductance regulator (CFTR), affects multiple organs including the exocrine pancreas, which is a causal contributor to cystic fibrosis–related diabetes (CFRD). Untreated CFRD causes increased CF-related mortality whereas early detection can improve outcomes. Methods: Using genetic and easily accessible clinical measures available at birth, we constructed a CFRD prediction model using the Canadian CF Gene Modifier Study (CGS; n = 1,958) and validated it in the French CF Gene Modifier Study (FGMS; n = 1,003). We investigated genetic variants shown to associate with CF disease severity across multiple organs in genome-wide association studies. Results: The strongest predictors included sex, CFTR severity score, and several genetic variants including one annotated to PRSS1, which encodes cationic trypsinogen. The final model defined in the CGS shows excellent agreement when validated on the FGMS, and the risk classifier shows slightly better performance at predicting CFRD risk later in life in both studies. Conclusion: We demonstrated clinical utility by comparing CFRD prevalence rates between the top 10% of individuals with the highest risk and the bottom 10% with the lowest risk. A web-based application was developed to provide practitioners with patient-specific CFRD risk to guide CFRD monitoring and treatment.",

author = "Lin, {Yu Chung} and Katherine Keenan and Jiafen Gong and Naim Panjwani and Julie Avolio and Fan Lin and Damien Adam and Paula Barrett and St{\'e}phanie B{\'e}gin and Yves Berthiaume and Lara Bilodeau and Candice Bjornson and Janna Brusky and Caroline Burgess and Mark Chilvers and Raquel Consunji-Araneta and Guillaume C{\^o}t{\'e}-Maurais and Andrea Dale and Christine Donnelly and Lori Fairservice and Katie Griffin and Natalie Henderson and Angela Hillaby and Daniel Hughes and Shaikh Iqbal and Jennifer Itterman and Mary Jackson and Emma Karlsen and Lorna Kosteniuk and Lynda Lazosky and Winnie Leung and Valerie Levesque and {\'E}milie Maille and Dimas Mateos-Corral and Vanessa McMahon and Mays Merjaneh and Nancy Morrison and Michael Parkins and Jennifer Pike and April Price and Quon, {Bradley S.} and Joe Reisman and Clare Smith and Smith, {Mary Jane} and Nathalie Vadeboncoeur and Danny Veniott and Terry Viczko and Pearce Wilcox and {van Wylick}, Richard and Garry Cutting and Elizabeth Tullis and Felix Ratjen and Rommens, {Johanna M.} and Lei Sun and Melinda Solomon and Stephenson, {Anne L.} and Emmanuelle Brochiero and Scott Blackman and Harriet Corvol and Strug, {Lisa J.}",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s).",

year = "2021",

month = may,

doi = "10.1038/s41436-020-01073-x",

language = "English (US)",

volume = "23",

pages = "927--933",

journal = "Genetics in Medicine",

issn = "1098-3600",

publisher = "Lippincott Williams and Wilkins",

number = "5",

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TY - JOUR

T1 - Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth

AU - Lin, Yu Chung

AU - Keenan, Katherine

AU - Gong, Jiafen

AU - Panjwani, Naim

AU - Avolio, Julie

AU - Lin, Fan

AU - Adam, Damien

AU - Barrett, Paula

AU - Bégin, Stéphanie

AU - Berthiaume, Yves

AU - Bilodeau, Lara

AU - Bjornson, Candice

AU - Brusky, Janna

AU - Burgess, Caroline

AU - Chilvers, Mark

AU - Consunji-Araneta, Raquel

AU - Côté-Maurais, Guillaume

AU - Dale, Andrea

AU - Donnelly, Christine

AU - Fairservice, Lori

AU - Griffin, Katie

AU - Henderson, Natalie

AU - Hillaby, Angela

AU - Hughes, Daniel

AU - Iqbal, Shaikh

AU - Itterman, Jennifer

AU - Jackson, Mary

AU - Karlsen, Emma

AU - Kosteniuk, Lorna

AU - Lazosky, Lynda

AU - Leung, Winnie

AU - Levesque, Valerie

AU - Maille, Émilie

AU - Mateos-Corral, Dimas

AU - McMahon, Vanessa

AU - Merjaneh, Mays

AU - Morrison, Nancy

AU - Parkins, Michael

AU - Pike, Jennifer

AU - Price, April

AU - Quon, Bradley S.

AU - Reisman, Joe

AU - Smith, Clare

AU - Smith, Mary Jane

AU - Vadeboncoeur, Nathalie

AU - Veniott, Danny

AU - Viczko, Terry

AU - Wilcox, Pearce

AU - van Wylick, Richard

AU - Cutting, Garry

AU - Tullis, Elizabeth

AU - Ratjen, Felix

AU - Rommens, Johanna M.

AU - Sun, Lei

AU - Solomon, Melinda

AU - Stephenson, Anne L.

AU - Brochiero, Emmanuelle

AU - Blackman, Scott

AU - Corvol, Harriet

AU - Strug, Lisa J.

PY - 2021/5

Y1 - 2021/5

N2 - Purpose: Cystic fibrosis (CF), caused by pathogenic variants in the CF transmembrane conductance regulator (CFTR), affects multiple organs including the exocrine pancreas, which is a causal contributor to cystic fibrosis–related diabetes (CFRD). Untreated CFRD causes increased CF-related mortality whereas early detection can improve outcomes. Methods: Using genetic and easily accessible clinical measures available at birth, we constructed a CFRD prediction model using the Canadian CF Gene Modifier Study (CGS; n = 1,958) and validated it in the French CF Gene Modifier Study (FGMS; n = 1,003). We investigated genetic variants shown to associate with CF disease severity across multiple organs in genome-wide association studies. Results: The strongest predictors included sex, CFTR severity score, and several genetic variants including one annotated to PRSS1, which encodes cationic trypsinogen. The final model defined in the CGS shows excellent agreement when validated on the FGMS, and the risk classifier shows slightly better performance at predicting CFRD risk later in life in both studies. Conclusion: We demonstrated clinical utility by comparing CFRD prevalence rates between the top 10% of individuals with the highest risk and the bottom 10% with the lowest risk. A web-based application was developed to provide practitioners with patient-specific CFRD risk to guide CFRD monitoring and treatment.

AB - Purpose: Cystic fibrosis (CF), caused by pathogenic variants in the CF transmembrane conductance regulator (CFTR), affects multiple organs including the exocrine pancreas, which is a causal contributor to cystic fibrosis–related diabetes (CFRD). Untreated CFRD causes increased CF-related mortality whereas early detection can improve outcomes. Methods: Using genetic and easily accessible clinical measures available at birth, we constructed a CFRD prediction model using the Canadian CF Gene Modifier Study (CGS; n = 1,958) and validated it in the French CF Gene Modifier Study (FGMS; n = 1,003). We investigated genetic variants shown to associate with CF disease severity across multiple organs in genome-wide association studies. Results: The strongest predictors included sex, CFTR severity score, and several genetic variants including one annotated to PRSS1, which encodes cationic trypsinogen. The final model defined in the CGS shows excellent agreement when validated on the FGMS, and the risk classifier shows slightly better performance at predicting CFRD risk later in life in both studies. Conclusion: We demonstrated clinical utility by comparing CFRD prevalence rates between the top 10% of individuals with the highest risk and the bottom 10% with the lowest risk. A web-based application was developed to provide practitioners with patient-specific CFRD risk to guide CFRD monitoring and treatment.

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U2 - 10.1038/s41436-020-01073-x

DO - 10.1038/s41436-020-01073-x

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SN - 1098-3600

VL - 23

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EP - 933

JO - Genetics in Medicine

JF - Genetics in Medicine

IS - 5

ER -

Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth

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