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Using germline variants to estimate glioma and subtype risks
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2019 (English)In: Neuro-Oncology, ISSN 1522-8517, E-ISSN 1523-5866, Vol. 21, no 4, p. 451-461Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Oxford University Press, 2019. Vol. 21, no 4, p. 451-461
Keywords [en]
classification, genotype, glioblastoma, glioma, polygenic
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:umu:diva-158081DOI: 10.1093/neuonc/noz009ISI: 000462632100006PubMedID: 30624711OAI: oai:DiVA.org:umu-158081DiVA, id: diva2:1304917
Funder
NIH (National Institute of Health), P50CA108961NIH (National Institute of Health), P30 CA15083NIH (National Institute of Health), RC1NS068222ZNIH (National Institute of Health), R01CA52689NIH (National Institute of Health), P50CA097257NIH (National Institute of Health), R01CA126831NIH (National Institute of Health), R01CA139020NIH (National Institute of Health), R01CA163687NIH (National Institute of Health), R25CA112355Available from: 2019-04-15 Created: 2019-04-15 Last updated: 2019-04-15Bibliographically approved

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Melin, Beatrice S.

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