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

Fangyi Gu, Ting Huei Chen, Ruth M. Pfeiffer, Maria Concetta Fargnoli, Donato Calista, Paola Ghiorzo, Ketty Peris, Susana Puig, Chiara Menin, Arcangela De Nicolo, Monica Rodolfo, Cristina Pellegrini, Lorenza Pastorino, Evangelos Evangelou, Tongwu Zhang, Xing Hua, Curt T. DellaValle, D. Timothy Bishop, Stuart MacGregor, Mark I. IlesMatthew H. Law, Anne Cust, Kevin M. Brown, Alexander J. Stratigos, Eduardo Nagore, Stephen Chanock, Jianxin Shi, Melanoma Meta Analysis Consortium, Mela Nostrum Consortium, Maria Teresa Landi

Research output: Contribution to journalArticle

6 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)4145-4156
Number of pages12
JournalHuman Molecular Genetics
Volume27
Issue number23
DOIs
Publication statusPublished - Dec 1 2018

Fingerprint

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

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)

Cite this

Gu, F., Chen, T. H., Pfeiffer, R. M., Fargnoli, M. C., Calista, D., Ghiorzo, P., ... Landi, M. T. (2018). Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma. Human Molecular Genetics, 27(23), 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, Fangyi; Chen, Ting Huei; Pfeiffer, Ruth M.; Fargnoli, Maria Concetta; Calista, Donato; Ghiorzo, Paola; Peris, Ketty; Puig, Susana; Menin, Chiara; De Nicolo, Arcangela; Rodolfo, Monica; Pellegrini, Cristina; Pastorino, Lorenza; Evangelou, Evangelos; Zhang, Tongwu; Hua, Xing; DellaValle, Curt T.; Timothy Bishop, D.; MacGregor, Stuart; Iles, Mark I.; Law, Matthew H.; Cust, Anne; Brown, Kevin M.; Stratigos, Alexander J.; Nagore, Eduardo; Chanock, Stephen; Shi, Jianxin; Consortium, Melanoma Meta Analysis; Consortium, Mela Nostrum; Landi, Maria Teresa.

In: Human Molecular Genetics, Vol. 27, No. 23, 01.12.2018, p. 4145-4156.

Research output: Contribution to journalArticle

Gu, F, Chen, TH, 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, MMA, Consortium, MN & Landi, MT 2018, 'Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma', Human Molecular Genetics, vol. 27, no. 23, pp. 4145-4156. https://doi.org/10.1093/hmg/ddy282
Gu, Fangyi ; Chen, Ting Huei ; Pfeiffer, Ruth M. ; Fargnoli, Maria Concetta ; Calista, Donato ; Ghiorzo, Paola ; Peris, Ketty ; Puig, Susana ; Menin, Chiara ; De Nicolo, Arcangela ; Rodolfo, Monica ; Pellegrini, Cristina ; Pastorino, Lorenza ; Evangelou, Evangelos ; Zhang, Tongwu ; Hua, Xing ; DellaValle, Curt T. ; Timothy Bishop, D. ; MacGregor, Stuart ; Iles, Mark I. ; Law, Matthew H. ; Cust, Anne ; Brown, Kevin M. ; Stratigos, Alexander J. ; Nagore, Eduardo ; Chanock, Stephen ; Shi, Jianxin ; Consortium, Melanoma Meta Analysis ; Consortium, Mela Nostrum ; Landi, Maria Teresa. / Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma. In: Human Molecular Genetics. 2018 ; Vol. 27, No. 23. pp. 4145-4156.
@article{6f91b65fe1d24fadaec2e096b50b838f,
title = "Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma",
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.",
author = "Fangyi Gu and Chen, {Ting Huei} and Pfeiffer, {Ruth M.} and Fargnoli, {Maria Concetta} and Donato Calista and Paola Ghiorzo and Ketty Peris and Susana Puig and Chiara Menin and {De Nicolo}, Arcangela and Monica Rodolfo and Cristina Pellegrini and Lorenza Pastorino and Evangelos Evangelou and Tongwu Zhang and Xing Hua and DellaValle, {Curt T.} and {Timothy Bishop}, D. and Stuart MacGregor and Iles, {Mark I.} and Law, {Matthew H.} and Anne Cust and Brown, {Kevin M.} and Stratigos, {Alexander J.} and Eduardo Nagore and Stephen Chanock and Jianxin Shi and Consortium, {Melanoma Meta Analysis} and Consortium, {Mela Nostrum} and Landi, {Maria Teresa}",
year = "2018",
month = "12",
day = "1",
doi = "10.1093/hmg/ddy282",
language = "English",
volume = "27",
pages = "4145--4156",
journal = "Human Molecular Genetics",
issn = "0964-6906",
publisher = "Oxford University Press",
number = "23",

}

TY - JOUR

T1 - Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma

AU - Gu, Fangyi

AU - Chen, Ting Huei

AU - Pfeiffer, Ruth M.

AU - Fargnoli, Maria Concetta

AU - Calista, Donato

AU - Ghiorzo, Paola

AU - Peris, Ketty

AU - Puig, Susana

AU - Menin, Chiara

AU - De Nicolo, Arcangela

AU - Rodolfo, Monica

AU - Pellegrini, Cristina

AU - Pastorino, Lorenza

AU - Evangelou, Evangelos

AU - Zhang, Tongwu

AU - Hua, Xing

AU - DellaValle, Curt T.

AU - Timothy Bishop, D.

AU - MacGregor, Stuart

AU - Iles, Mark I.

AU - Law, Matthew H.

AU - Cust, Anne

AU - Brown, Kevin M.

AU - Stratigos, Alexander J.

AU - Nagore, Eduardo

AU - Chanock, Stephen

AU - Shi, Jianxin

AU - Consortium, Melanoma Meta Analysis

AU - Consortium, Mela Nostrum

AU - Landi, Maria Teresa

PY - 2018/12/1

Y1 - 2018/12/1

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.

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.

UR - http://www.scopus.com/inward/record.url?scp=85056716573&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056716573&partnerID=8YFLogxK

U2 - 10.1093/hmg/ddy282

DO - 10.1093/hmg/ddy282

M3 - Article

C2 - 30060076

AN - SCOPUS:85056716573

VL - 27

SP - 4145

EP - 4156

JO - Human Molecular Genetics

JF - Human Molecular Genetics

SN - 0964-6906

IS - 23

ER -