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. 2020 Oct;22(10):1653-1666.
doi: 10.1038/s41436-020-0862-x. Epub 2020 Jul 15.

Polygenic risk scores and breast and epithelial ovarian cancer risks for carriers of BRCA1 and BRCA2 pathogenic variants

Daniel R Barnes  1 , Matti A Rookus  2 , Lesley McGuffog  3 , Goska Leslie  3 , Thea M Mooij  2 , Joe Dennis  3 , Nasim Mavaddat  3 , Julian Adlard  4 , Munaza Ahmed  5 , Kristiina Aittomäki  6 , Nadine Andrieu  7   8   9   10 , Irene L Andrulis  11   12 , Norbert Arnold  13   14 , Banu K Arun  15 , Jacopo Azzollini  16 , Judith Balmaña  17   18 , Rosa B Barkardottir  19   20 , Daniel Barrowdale  3 , Javier Benitez  21   22 , Pascaline Berthet  23 , Katarzyna Białkowska  24 , Amie M Blanco  25 , Marinus J Blok  26 , Bernardo Bonanni  27 , Susanne E Boonen  28 , Åke Borg  29 , Aniko Bozsik  30 , Angela R Bradbury  31 , Paul Brennan  32 , Carole Brewer  33 , Joan Brunet  34 , Saundra S Buys  35 , Trinidad Caldés  36 , Maria A Caligo  37 , Ian Campbell  38   39 , Lise Lotte Christensen  40 , Wendy K Chung  41 , Kathleen B M Claes  42 , Chrystelle Colas  43 ; GEMO Study Collaborators; EMBRACE Collaborators; Marie-Agnès Collonge-Rame  44 , Jackie Cook  45 , Mary B Daly  46 , Rosemarie Davidson  47 , Miguel de la Hoya  36 , Robin de Putter  42 , Capucine Delnatte  48 , Peter Devilee  49   50 , Orland Diez  51   52 , Yuan Chun Ding  53 , Susan M Domchek  54 , Cecilia M Dorfling  55 , Martine Dumont  56 , Ros Eeles  57 , Bent Ejlertsen  58 , Christoph Engel  59 , D Gareth Evans  60   61 , Laurence Faivre  62   63 , Lenka Foretova  64 , Florentia Fostira  65 , Michael Friedlander  66 , Eitan Friedman  67   68 , Debra Frost  3 , Patricia A Ganz  69 , Judy Garber  70 , Andrea Gehrig  71 , Anne-Marie Gerdes  72 , Paul Gesta  73 , Sophie Giraud  74 , Gord Glendon  11 , Andrew K Godwin  75 , David E Goldgar  76 , Anna González-Neira  22 , Mark H Greene  77 , Daphne Gschwantler-Kaulich  78 , Eric Hahnen  79   80 , Ute Hamann  81 , Helen Hanson  82 , Julia Hentschel  83 , Frans B L Hogervorst  84 , Maartje J Hooning  85 , Judit Horvath  86 , Chunling Hu  87 , Peter J Hulick  88   89 , Evgeny N Imyanitov  90 ; kConFab Investigators; HEBON Investigators; GENEPSO Investigators; Claudine Isaacs  91 , Louise Izatt  92 , Angel Izquierdo  34 , Anna Jakubowska  24   93 , Paul A James  39   94 , Ramunas Janavicius  95   96 , Esther M John  97 , Vijai Joseph  98 , Beth Y Karlan  99   100 , Karin Kast  101 , Marco Koudijs  102 , Torben A Kruse  103 , Ava Kwong  104   105   106 , Yael Laitman  67 , Christine Lasset  107   108 , Conxi Lazaro  34 , Jenny Lester  99   100 , Fabienne Lesueur  7   8   9   10 , Annelie Liljegren  109 , Jennifer T Loud  77 , Jan Lubiński  24 , Phuong L Mai  110 , Siranoush Manoukian  16 , Véronique Mari  111 , Noura Mebirouk  7   8   9   10 , Hanne E J Meijers-Heijboer  112 , Alfons Meindl  113 , Arjen R Mensenkamp  114 , Austin Miller  115 , Marco Montagna  116 , Emmanuelle Mouret-Fourme  43 , Semanti Mukherjee  117 , Anna Marie Mulligan  118   119 , Katherine L Nathanson  54 , Susan L Neuhausen  53 , Heli Nevanlinna  120 , Dieter Niederacher  121 , Finn Cilius Nielsen  122 , Liene Nikitina-Zake  123 , Catherine Noguès  124 , Edith Olah  30 , Olufunmilayo I Olopade  125 , Kai-Ren Ong  126 , Aoife O'Shaughnessy-Kirwan  127 , Ana Osorio  21   22 , Claus-Eric Ott  128 , Laura Papi  129 , Sue K Park  130   131   132 , Michael T Parsons  133 , Inge Sokilde Pedersen  134   135   136 , Bernard Peissel  16 , Ana Peixoto  137 , Paolo Peterlongo  138 , Georg Pfeiler  139 , Kelly-Anne Phillips  38   39   140   141 , Karolina Prajzendanc  24 , Miquel Angel Pujana  142 , Paolo Radice  143 , Juliane Ramser  144 , Susan J Ramus  145   146   147 , Johanna Rantala  148 , Gad Rennert  149 , Harvey A Risch  150 , Mark Robson  117 , Karina Rønlund  151 , Ritu Salani  152 , Hélène Schuster  153   154   155 , Leigha Senter  156 , Payal D Shah  31 , Priyanka Sharma  157 , Lucy E Side  158 , Christian F Singer  139 , Thomas P Slavin  159 , Penny Soucy  56 , Melissa C Southey  160   161   162 , Amanda B Spurdle  133 , Doris Steinemann  163 , Zoe Steinsnyder  117 , Dominique Stoppa-Lyonnet  43   164   165 , Christian Sutter  166 , Yen Yen Tan  78 , Manuel R Teixeira  137   167 , Soo Hwang Teo  168   169 , Darcy L Thull  170 , Marc Tischkowitz  171   172 , Silvia Tognazzo  116 , Amanda E Toland  173 , Alison H Trainer  94   174 , Nadine Tung  175 , Klaartje van Engelen  176 , Elizabeth J van Rensburg  55 , Ana Vega  21   177   178 , Jeroen Vierstraete  42 , Gabriel Wagner  139 , Lisa Walker  179 , Shan Wang-Gohrke  180 , Barbara Wappenschmidt  79   80 , Jeffrey N Weitzel  159 , Siddhartha Yadav  181 , Xin Yang  3 , Drakoulis Yannoukakos  65 , Dario Zimbalatti  16 , Kenneth Offit  98   117 , Mads Thomassen  103 , Fergus J Couch  87 , Rita K Schmutzler  79   80   182 , Jacques Simard  56 , Douglas F Easton  3   183 , Georgia Chenevix-Trench  133 , Antonis C Antoniou  3 ; Consortium of Investigators of Modifiers of BRCA and BRCA2
Collaborators, Affiliations

Polygenic risk scores and breast and epithelial ovarian cancer risks for carriers of BRCA1 and BRCA2 pathogenic variants

Daniel R Barnes et al. Genet Med. 2020 Oct.

Abstract

Purpose: We assessed the associations between population-based polygenic risk scores (PRS) for breast (BC) or epithelial ovarian cancer (EOC) with cancer risks for BRCA1 and BRCA2 pathogenic variant carriers.

Methods: Retrospective cohort data on 18,935 BRCA1 and 12,339 BRCA2 female pathogenic variant carriers of European ancestry were available. Three versions of a 313 single-nucleotide polymorphism (SNP) BC PRS were evaluated based on whether they predict overall, estrogen receptor (ER)-negative, or ER-positive BC, and two PRS for overall or high-grade serous EOC. Associations were validated in a prospective cohort.

Results: The ER-negative PRS showed the strongest association with BC risk for BRCA1 carriers (hazard ratio [HR] per standard deviation = 1.29 [95% CI 1.25-1.33], P = 3×10-72). For BRCA2, the strongest association was with overall BC PRS (HR = 1.31 [95% CI 1.27-1.36], P = 7×10-50). HR estimates decreased significantly with age and there was evidence for differences in associations by predicted variant effects on protein expression. The HR estimates were smaller than general population estimates. The high-grade serous PRS yielded the strongest associations with EOC risk for BRCA1 (HR = 1.32 [95% CI 1.25-1.40], P = 3×10-22) and BRCA2 (HR = 1.44 [95% CI 1.30-1.60], P = 4×10-12) carriers. The associations in the prospective cohort were similar.

Conclusion: Population-based PRS are strongly associated with BC and EOC risks for BRCA1/2 carriers and predict substantial absolute risk differences for women at PRS distribution extremes.

Keywords: BRCA1/2; PRS; breast cancer; genetics; ovarian cancer.

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Conflict of interest statement

G.P. has received honoraria from Novartis, Amgen, Roche, Pfizer, and AstraZeneca. The other authors declare no conflicts of interest.

Figures

Fig. 1
Fig. 1. Associations with specific polygenic risk score (PRS) percentiles.
The PRS percentile thresholds were determined in the sets of unaffected carriers for the disease under assessment. Table 2 shows the estimated hazard ratios (HRs). The black curve represents the expected HRs assuming the per standard deviation HR estimates in BRCA1 and BRCA2 carriers based on the continuous PRS models (Table 1). (a) PRSER- percentile-specific associations with breast cancer risk for BRCA1 carriers. The red curve represents the expected HRs over the PRS percentile distribution, assuming the per SD odds ratio (OR) estimate from the population-based validation studies from Mavaddat et al. (OR = 1.45 per PRSER- standard deviation). (b) PRSBC percentile-specific associations with breast cancer risk for BRCA2 carriers. The red curve represents the expected HRs over the PRS percentile distribution, assuming the per SD OR estimate from the population-based validation studies from Mavaddat et al. (OR = 1.61 per PRSBC standard deviation). (c) PRSHGS percentile-specific associations with ovarian cancer risk for BRCA1 carriers. (d) PRSHGS percentile-specific associations with ovarian cancer risk for BRCA2 carriers. The gray curve (c and d only) represents the theoretical HRs across the PRS distribution, calculated by assuming external single-nucleotide polymorphism (SNP) effect sizes and allele frequencies for SNPs contributing to the PRS. CI confidence interval, ER estrogen receptor, HGS high-grade serous.
Fig. 2
Fig. 2. Predicted absolute risks of developing breast and ovarian cancer by polygenic risk score (PRS) percentile.
Risks were calculated assuming the retrospective cohort hazard ratio (HR) estimates (Tables 1, 2). (a) Predicted absolute risks of developing breast cancer for BRCA1 carriers by percentiles of the PRSER-. (b) Predicted absolute risks of developing breast cancer for BRCA2 carriers by percentiles of the PRSBC. (c) Predicted absolute risks of developing ovarian cancer for BRCA1 carriers by the percentiles of the PRSHGS. (d) Predicted absolute risks of developing ovarian cancer for BRCA2 carriers by percentiles of the PRSHGS. ER estrogen receptor, HGS high-grade serous.
See this image and copyright information in PMC

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