Using germline variants to estimate glioma and subtype risks

Jeanette E Eckel-Passow, Paul A. Decker, Matt L. Kosel, Thomas M. Kollmeyer, Annette M. Molinaro, Terri Rice, Alissa A. Caron, Kristen L. Drucker, Corinne E. Praska, Melike Pekmezci, Helen M. Hansen, Lucie S. Mccoy, Paige M. Bracci, Bradley J Erickson, Claudia F Lucchinetti, Joseph L. Wiemels, John K. Wiencke, Melissa L. Bondy, Beatrice Melin, Terence Burns & 4 others Caterina Giannini, Daniel H Lachance, Margaret R. Wrensch, Robert Brian Jenkins

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background. Twenty-five single nucleotide polymorphisms (SNPs) are associated with adult diffuse glioma risk. We hypothesized that the inclusion of these 25 SNPs with age at diagnosis and sex could estimate risk of glioma as well as identify glioma subtypes. Methods. Case-control design and multinomial logistic regression were used to develop models to estimate the risk of glioma development while accounting for histologic and molecular subtypes. Case-case design and logistic regression were used to develop models to predict isocitrate dehydrogenase (IDH) mutation status. A total of 1273 glioma cases and 443 controls from Mayo Clinic were used in the discovery set, and 852 glioma cases and 231 controls from UCSF were used in the validation set. All samples were genotyped using a custom Illumina OncoArray. Results. Patients in the highest 5% of the risk score had more than a 14-fold increase in relative risk of developing an IDH mutant glioma. Large differences in lifetime absolute risk were observed at the extremes of the risk score percentile. For both IDH mutant 1p/19q non-codeleted glioma and IDH mutant 1p/19q codeleted glioma, the lifetime risk increased from almost null to 2.3% and almost null to 1.7%, respectively. The SNP-based model that predicted IDH mutation status had a validation concordance index of 0.85. Conclusions. These results suggest that germline genotyping can provide new tools for the initial management of newly discovered brain lesions. Given the low lifetime risk of glioma, risk scores will not be useful for population screening; however, they may be useful in certain clinically defined high-risk groups.

Original languageEnglish (US)
Pages (from-to)451-461
Number of pages11
JournalNeuro-oncology
Volume21
Issue number4
DOIs
StatePublished - Mar 18 2019

Fingerprint

Glioma
Isocitrate Dehydrogenase
Single Nucleotide Polymorphism
Logistic Models
Mutation
Brain

Keywords

  • classification
  • genotype
  • glioblastoma
  • glioma
  • polygenic

ASJC Scopus subject areas

  • Oncology
  • Clinical Neurology
  • Cancer Research

Cite this

Eckel-Passow, J. E., Decker, P. A., Kosel, M. L., Kollmeyer, T. M., Molinaro, A. M., Rice, T., ... Jenkins, R. B. (2019). Using germline variants to estimate glioma and subtype risks. Neuro-oncology, 21(4), 451-461. https://doi.org/10.1093/neuonc/noz009

Using germline variants to estimate glioma and subtype risks. / Eckel-Passow, Jeanette E; Decker, Paul A.; Kosel, Matt L.; Kollmeyer, Thomas M.; Molinaro, Annette M.; Rice, Terri; Caron, Alissa A.; Drucker, Kristen L.; Praska, Corinne E.; Pekmezci, Melike; Hansen, Helen M.; Mccoy, Lucie S.; Bracci, Paige M.; Erickson, Bradley J; Lucchinetti, Claudia F; Wiemels, Joseph L.; Wiencke, John K.; Bondy, Melissa L.; Melin, Beatrice; Burns, Terence; Giannini, Caterina; Lachance, Daniel H; Wrensch, Margaret R.; Jenkins, Robert Brian.

In: Neuro-oncology, Vol. 21, No. 4, 18.03.2019, p. 451-461.

Research output: Contribution to journalArticle

Eckel-Passow, JE, Decker, PA, Kosel, ML, Kollmeyer, TM, Molinaro, AM, Rice, T, Caron, AA, Drucker, KL, Praska, CE, Pekmezci, M, Hansen, HM, Mccoy, LS, Bracci, PM, Erickson, BJ, Lucchinetti, CF, Wiemels, JL, Wiencke, JK, Bondy, ML, Melin, B, Burns, T, Giannini, C, Lachance, DH, Wrensch, MR & Jenkins, RB 2019, 'Using germline variants to estimate glioma and subtype risks', Neuro-oncology, vol. 21, no. 4, pp. 451-461. https://doi.org/10.1093/neuonc/noz009
Eckel-Passow JE, Decker PA, Kosel ML, Kollmeyer TM, Molinaro AM, Rice T et al. Using germline variants to estimate glioma and subtype risks. Neuro-oncology. 2019 Mar 18;21(4):451-461. https://doi.org/10.1093/neuonc/noz009
Eckel-Passow, Jeanette E ; Decker, Paul A. ; Kosel, Matt L. ; Kollmeyer, Thomas M. ; Molinaro, Annette M. ; Rice, Terri ; Caron, Alissa A. ; Drucker, Kristen L. ; Praska, Corinne E. ; Pekmezci, Melike ; Hansen, Helen M. ; Mccoy, Lucie S. ; Bracci, Paige M. ; Erickson, Bradley J ; Lucchinetti, Claudia F ; Wiemels, Joseph L. ; Wiencke, John K. ; Bondy, Melissa L. ; Melin, Beatrice ; Burns, Terence ; Giannini, Caterina ; Lachance, Daniel H ; Wrensch, Margaret R. ; Jenkins, Robert Brian. / Using germline variants to estimate glioma and subtype risks. In: Neuro-oncology. 2019 ; Vol. 21, No. 4. pp. 451-461.
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T1 - Using germline variants to estimate glioma and subtype risks

AU - Eckel-Passow, Jeanette E

AU - Decker, Paul A.

AU - Kosel, Matt L.

AU - Kollmeyer, Thomas M.

AU - Molinaro, Annette M.

AU - Rice, Terri

AU - Caron, Alissa A.

AU - Drucker, Kristen L.

AU - Praska, Corinne E.

AU - Pekmezci, Melike

AU - Hansen, Helen M.

AU - Mccoy, Lucie S.

AU - Bracci, Paige M.

AU - Erickson, Bradley J

AU - Lucchinetti, Claudia F

AU - Wiemels, Joseph L.

AU - Wiencke, John K.

AU - Bondy, Melissa L.

AU - Melin, Beatrice

AU - Burns, Terence

AU - Giannini, Caterina

AU - Lachance, Daniel H

AU - Wrensch, Margaret R.

AU - Jenkins, Robert Brian

PY - 2019/3/18

Y1 - 2019/3/18

N2 - Background. Twenty-five single nucleotide polymorphisms (SNPs) are associated with adult diffuse glioma risk. We hypothesized that the inclusion of these 25 SNPs with age at diagnosis and sex could estimate risk of glioma as well as identify glioma subtypes. Methods. Case-control design and multinomial logistic regression were used to develop models to estimate the risk of glioma development while accounting for histologic and molecular subtypes. Case-case design and logistic regression were used to develop models to predict isocitrate dehydrogenase (IDH) mutation status. A total of 1273 glioma cases and 443 controls from Mayo Clinic were used in the discovery set, and 852 glioma cases and 231 controls from UCSF were used in the validation set. All samples were genotyped using a custom Illumina OncoArray. Results. Patients in the highest 5% of the risk score had more than a 14-fold increase in relative risk of developing an IDH mutant glioma. Large differences in lifetime absolute risk were observed at the extremes of the risk score percentile. For both IDH mutant 1p/19q non-codeleted glioma and IDH mutant 1p/19q codeleted glioma, the lifetime risk increased from almost null to 2.3% and almost null to 1.7%, respectively. The SNP-based model that predicted IDH mutation status had a validation concordance index of 0.85. Conclusions. These results suggest that germline genotyping can provide new tools for the initial management of newly discovered brain lesions. Given the low lifetime risk of glioma, risk scores will not be useful for population screening; however, they may be useful in certain clinically defined high-risk groups.

AB - Background. Twenty-five single nucleotide polymorphisms (SNPs) are associated with adult diffuse glioma risk. We hypothesized that the inclusion of these 25 SNPs with age at diagnosis and sex could estimate risk of glioma as well as identify glioma subtypes. Methods. Case-control design and multinomial logistic regression were used to develop models to estimate the risk of glioma development while accounting for histologic and molecular subtypes. Case-case design and logistic regression were used to develop models to predict isocitrate dehydrogenase (IDH) mutation status. A total of 1273 glioma cases and 443 controls from Mayo Clinic were used in the discovery set, and 852 glioma cases and 231 controls from UCSF were used in the validation set. All samples were genotyped using a custom Illumina OncoArray. Results. Patients in the highest 5% of the risk score had more than a 14-fold increase in relative risk of developing an IDH mutant glioma. Large differences in lifetime absolute risk were observed at the extremes of the risk score percentile. For both IDH mutant 1p/19q non-codeleted glioma and IDH mutant 1p/19q codeleted glioma, the lifetime risk increased from almost null to 2.3% and almost null to 1.7%, respectively. The SNP-based model that predicted IDH mutation status had a validation concordance index of 0.85. Conclusions. These results suggest that germline genotyping can provide new tools for the initial management of newly discovered brain lesions. Given the low lifetime risk of glioma, risk scores will not be useful for population screening; however, they may be useful in certain clinically defined high-risk groups.

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