Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma

F. Gu, T.-H. Chen, R.M. Pfeiffer, M.C. Fargnoli, D. Calista, P. Ghiorzo, K. Peris, S. Puig, C. Menin, A. De Nicolo, M. Rodolfo, C. Pellegrini, L. Pastorino, E. Evangelou, T. Zhang, X. Hua, C.T. DellaValle, D. Timothy Bishop, S. MacGregor, M.I. IlesM.H. Law, A. Cust, K.M. Brown, A.J. Stratigos, E. Nagore, S. Chanock, J. Shi, M.M.-A. Consortium, M. Consortium, M.T. Landi

Research output: Contribution to journalArticle

Abstract

Melanoma heritability is among the highest for cancer and single nucleotide polymorphisms (SNPs) contribute to it. To date, only SNPs that reached statistical significance in genome-wide association studies or few candidate SNPs have been included in melanoma risk prediction models. We compared four approaches for building polygenic risk scores (PRS) using 12 874 melanoma cases and 23 203 controls from Melanoma Meta-Analysis Consortium as a training set, and newly genotyped 3102 cases and 2301 controls from the MelaNostrum consortium for validation. We estimated adjusted odds ratios (ORs) for melanoma risk using traditional melanoma risk factors and the PRS with the largest area under the receiver operator characteristics curve (AUC). We estimated absolute risks combining the PRS and other risk factors, with age- and sex-specific melanoma incidence and competing mortality rates from Italy as an example. The best PRS, including 204 SNPs (AUC = 64.4%; 95% confidence interval (CI) = 63-65.8%), developed using winner's curse estimate corrections, had a per-quintile OR = 1.35 (95% CI = 1.30-1.41), corresponding to a 3.33-fold increase comparing the 5th to the 1st PRS quintile. The AUC improvement by adding the PRS was up to 7%, depending on adjusted factors and country. The 20-year absolute risk estimates based on the PRS, nevus count and pigmentation characteristics for a 60-year-old Italian man ranged from 0.5 to 11.8% (relative risk = 26.34), indicating good separation. © 2018 Lippincott Williams and Wilkins.All Rights Reserved.
Original languageEnglish
Pages (from-to)4145-4156
Number of pages12
JournalHuman Molecular Genetics
Volume27
Issue number3
DOIs
Publication statusPublished - Feb 1 2019

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Melanoma
Skin
Single Nucleotide Polymorphism
Area Under Curve
Odds Ratio
Confidence Intervals
Nevus
Genome-Wide Association Study
Pigmentation
Italy
Meta-Analysis
Mortality
Incidence

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Gu, F., Chen, T-H., Pfeiffer, R. M., Fargnoli, M. C., Calista, D., Ghiorzo, P., ... Landi, M. T. (2019). Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma. Human Molecular Genetics, 27(3), 4145-4156. https://doi.org/10.1093/hmg/ddy282

Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma. / Gu, F.; Chen, T.-H.; Pfeiffer, R.M.; Fargnoli, M.C.; Calista, D.; Ghiorzo, P.; Peris, K.; Puig, S.; Menin, C.; De Nicolo, A.; Rodolfo, M.; Pellegrini, C.; Pastorino, L.; Evangelou, E.; Zhang, T.; Hua, X.; DellaValle, C.T.; Timothy Bishop, D.; MacGregor, S.; Iles, M.I.; Law, M.H.; Cust, A.; Brown, K.M.; Stratigos, A.J.; Nagore, E.; Chanock, S.; Shi, J.; Consortium, M.M.-A.; Consortium, M.; Landi, M.T.

In: Human Molecular Genetics, Vol. 27, No. 3, 01.02.2019, p. 4145-4156.

Research output: Contribution to journalArticle

Gu, F, Chen, T-H, Pfeiffer, RM, Fargnoli, MC, Calista, D, Ghiorzo, P, Peris, K, Puig, S, Menin, C, De Nicolo, A, Rodolfo, M, Pellegrini, C, Pastorino, L, Evangelou, E, Zhang, T, Hua, X, DellaValle, CT, Timothy Bishop, D, MacGregor, S, Iles, MI, Law, MH, Cust, A, Brown, KM, Stratigos, AJ, Nagore, E, Chanock, S, Shi, J, Consortium, MM-A, Consortium, M & Landi, MT 2019, 'Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma', Human Molecular Genetics, vol. 27, no. 3, pp. 4145-4156. https://doi.org/10.1093/hmg/ddy282
Gu, F. ; Chen, T.-H. ; Pfeiffer, R.M. ; Fargnoli, M.C. ; Calista, D. ; Ghiorzo, P. ; Peris, K. ; Puig, S. ; Menin, C. ; De Nicolo, A. ; Rodolfo, M. ; Pellegrini, C. ; Pastorino, L. ; Evangelou, E. ; Zhang, T. ; Hua, X. ; DellaValle, C.T. ; Timothy Bishop, D. ; MacGregor, S. ; Iles, M.I. ; Law, M.H. ; Cust, A. ; Brown, K.M. ; Stratigos, A.J. ; Nagore, E. ; Chanock, S. ; Shi, J. ; Consortium, M.M.-A. ; Consortium, M. ; Landi, M.T. / Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma. In: Human Molecular Genetics. 2019 ; Vol. 27, No. 3. pp. 4145-4156.
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abstract = "Melanoma heritability is among the highest for cancer and single nucleotide polymorphisms (SNPs) contribute to it. To date, only SNPs that reached statistical significance in genome-wide association studies or few candidate SNPs have been included in melanoma risk prediction models. We compared four approaches for building polygenic risk scores (PRS) using 12 874 melanoma cases and 23 203 controls from Melanoma Meta-Analysis Consortium as a training set, and newly genotyped 3102 cases and 2301 controls from the MelaNostrum consortium for validation. We estimated adjusted odds ratios (ORs) for melanoma risk using traditional melanoma risk factors and the PRS with the largest area under the receiver operator characteristics curve (AUC). We estimated absolute risks combining the PRS and other risk factors, with age- and sex-specific melanoma incidence and competing mortality rates from Italy as an example. The best PRS, including 204 SNPs (AUC = 64.4{\%}; 95{\%} confidence interval (CI) = 63-65.8{\%}), developed using winner's curse estimate corrections, had a per-quintile OR = 1.35 (95{\%} CI = 1.30-1.41), corresponding to a 3.33-fold increase comparing the 5th to the 1st PRS quintile. The AUC improvement by adding the PRS was up to 7{\%}, depending on adjusted factors and country. The 20-year absolute risk estimates based on the PRS, nevus count and pigmentation characteristics for a 60-year-old Italian man ranged from 0.5 to 11.8{\%} (relative risk = 26.34), indicating good separation. {\circledC} 2018 Lippincott Williams and Wilkins.All Rights Reserved.",
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T1 - Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma

AU - Gu, F.

AU - Chen, T.-H.

AU - Pfeiffer, R.M.

AU - Fargnoli, M.C.

AU - Calista, D.

AU - Ghiorzo, P.

AU - Peris, K.

AU - Puig, S.

AU - Menin, C.

AU - De Nicolo, A.

AU - Rodolfo, M.

AU - Pellegrini, C.

AU - Pastorino, L.

AU - Evangelou, E.

AU - Zhang, T.

AU - Hua, X.

AU - DellaValle, C.T.

AU - Timothy Bishop, D.

AU - MacGregor, S.

AU - Iles, M.I.

AU - Law, M.H.

AU - Cust, A.

AU - Brown, K.M.

AU - Stratigos, A.J.

AU - Nagore, E.

AU - Chanock, S.

AU - Shi, J.

AU - Consortium, M.M.-A.

AU - Consortium, M.

AU - Landi, M.T.

N1 - cited By 0

PY - 2019/2/1

Y1 - 2019/2/1

N2 - Melanoma heritability is among the highest for cancer and single nucleotide polymorphisms (SNPs) contribute to it. To date, only SNPs that reached statistical significance in genome-wide association studies or few candidate SNPs have been included in melanoma risk prediction models. We compared four approaches for building polygenic risk scores (PRS) using 12 874 melanoma cases and 23 203 controls from Melanoma Meta-Analysis Consortium as a training set, and newly genotyped 3102 cases and 2301 controls from the MelaNostrum consortium for validation. We estimated adjusted odds ratios (ORs) for melanoma risk using traditional melanoma risk factors and the PRS with the largest area under the receiver operator characteristics curve (AUC). We estimated absolute risks combining the PRS and other risk factors, with age- and sex-specific melanoma incidence and competing mortality rates from Italy as an example. The best PRS, including 204 SNPs (AUC = 64.4%; 95% confidence interval (CI) = 63-65.8%), developed using winner's curse estimate corrections, had a per-quintile OR = 1.35 (95% CI = 1.30-1.41), corresponding to a 3.33-fold increase comparing the 5th to the 1st PRS quintile. The AUC improvement by adding the PRS was up to 7%, depending on adjusted factors and country. The 20-year absolute risk estimates based on the PRS, nevus count and pigmentation characteristics for a 60-year-old Italian man ranged from 0.5 to 11.8% (relative risk = 26.34), indicating good separation. © 2018 Lippincott Williams and Wilkins.All Rights Reserved.

AB - Melanoma heritability is among the highest for cancer and single nucleotide polymorphisms (SNPs) contribute to it. To date, only SNPs that reached statistical significance in genome-wide association studies or few candidate SNPs have been included in melanoma risk prediction models. We compared four approaches for building polygenic risk scores (PRS) using 12 874 melanoma cases and 23 203 controls from Melanoma Meta-Analysis Consortium as a training set, and newly genotyped 3102 cases and 2301 controls from the MelaNostrum consortium for validation. We estimated adjusted odds ratios (ORs) for melanoma risk using traditional melanoma risk factors and the PRS with the largest area under the receiver operator characteristics curve (AUC). We estimated absolute risks combining the PRS and other risk factors, with age- and sex-specific melanoma incidence and competing mortality rates from Italy as an example. The best PRS, including 204 SNPs (AUC = 64.4%; 95% confidence interval (CI) = 63-65.8%), developed using winner's curse estimate corrections, had a per-quintile OR = 1.35 (95% CI = 1.30-1.41), corresponding to a 3.33-fold increase comparing the 5th to the 1st PRS quintile. The AUC improvement by adding the PRS was up to 7%, depending on adjusted factors and country. The 20-year absolute risk estimates based on the PRS, nevus count and pigmentation characteristics for a 60-year-old Italian man ranged from 0.5 to 11.8% (relative risk = 26.34), indicating good separation. © 2018 Lippincott Williams and Wilkins.All Rights Reserved.

U2 - 10.1093/hmg/ddy282

DO - 10.1093/hmg/ddy282

M3 - Article

VL - 27

SP - 4145

EP - 4156

JO - Human Molecular Genetics

JF - Human Molecular Genetics

SN - 0964-6906

IS - 3

ER -