Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes

Lymphoma risk is elevated for relatives with common non-Hodgkin lymphoma (NHL) subtypes, suggesting shared genetic susceptibility across subtypes. To evaluate the extent of mutual heritability among NHL subtypes and discover novel loci shared among subtypes, we analyzed data from eight genome-wide association studies within the InterLymph Consortium, including 10,629 cases and 9505 controls. We utilized Association analysis based on SubSETs (ASSET) to discover loci for subsets of NHL subtypes and evaluated shared heritability across the genome using Genome-wide Complex Trait Analysis (GCTA) and polygenic risk scores. We discovered 17 genome-wide significant loci (P < 5 × 10−8) for subsets of NHL subtypes, including a novel locus at 10q23.33 (HHEX) (P = 3.27 × 10−9). Most subset associations were driven primarily by only one subtype. Genome-wide genetic correlations between pairs of subtypes varied broadly from 0.20 to 0.86, suggesting substantial heterogeneity in the extent of shared heritability among subtypes. Polygenic risk score analyses of established loci for different lymphoid malignancies identified strong associations with some NHL subtypes (P < 5 × 10−8), but weak or null associations with others. Although our analyses suggest partially shared heritability and biological pathways, they reveal substantial heterogeneity among NHL subtypes with each having its own distinct germline genetic architecture

Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32

To identify susceptibility loci for non-Hodgkin lymphoma subtypes, we conducted a three-stage genome-wide association study. We identified two variants associated with follicular lymphoma at 6p21.32 (rs10484561, combined P = 1.12 × 10-29 and rs7755224, combined P = 2.00 × 10-19; r2 = 1.0), supporting the idea that major histocompatibility complex genetic variation influences follicular lymphoma susceptibility. We also found confirmatory evidence of a previously reported association between chronic lymphocytic leukemia/small lymphocytic lymphoma and rs735665 (combined P = 4.24 × 10-9). © 2010 Nature America, Inc. All rights reserved

MC1R gene variants and non-melanoma skin cancer: A pooled-analysis from the M-SKIP project

Background:The melanocortin-1-receptor (MC1R) gene regulates human pigmentation and is highly polymorphic in populations of European origins. The aims of this study were to evaluate the association between MC1R variants and the risk of non-melanoma skin cancer (NMSC), and to investigate whether risk estimates differed by phenotypic characteristics.Methods:Data on 3527 NMSC cases and 9391 controls were gathered through the M-SKIP Project, an international pooled-analysis on MC1R, skin cancer and phenotypic characteristics. We calculated summary odds ratios (SOR) with random-effect models, and performed stratified analyses.Results:Subjects carrying at least one MC1R variant had an increased risk of NMSC overall, basal cell carcinoma (BCC) and squamous cell carcinoma (SCC): SOR (95%CI) were 1.48 (1.24-1.76), 1.39 (1.15-1.69) and 1.61 (1.35-1.91), respectively. All of the investigated variants showed positive associations with NMSC, with consistent significant results obtained for V60L, D84E, V92M, R151C, R160W, R163Q and D294H: SOR (95%CI) ranged from 1.42 (1.19-1.70) for V60L to 2.66 (1.06-6.65) for D84E variant. In stratified analysis, there was no consistent pattern of association between MC1R and NMSC by skin type, but we consistently observed higher SORs for subjects without red hair.Conclusions:Our pooled-analysis highlighted a role of MC1R variants in NMSC development and suggested an effect modification by red hair colour phenotype

Genome-wide association study identifies multiple susceptibility loci for diffuse large B cell lymphoma

Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of 3 new genome-wide association studies (GWAS) and 1 previous scan, totaling 3,857 cases and 7,666 controls of European ancestry, with additional genotyping of 9 promising SNPs in 1,359 cases and 4,557 controls. In our multi-stage analysis, five independent SNPs in four loci achieved genome-wide significance marked by rs116446171 at 6p25.3 (EXOC2; P = 2.33 7 10 '21), rs2523607 at 6p21.33 (HLA-B; P = 2.40 7 10 '10), rs79480871 at 2p23.3 (NCOA1; P = 4.23 7 10 '8) and two independent SNPs, rs13255292 and rs4733601, at 8q24.21 (PVT1; P = 9.98 7 10 '13 and 3.63 7 10 '11, respectively). These data provide substantial new evidence for genetic susceptibility to this B cell malignancy and point to pathways involved in immune recognition and immune function in the pathogenesis of DLBCL. \ua9 2014 Nature America, Inc. All rights reserved

MC1R variants in childhood and adolescent melanoma: a retrospective pooled analysis of a multicentre cohort

149nonenonePellegrini C.; Botta F.; Massi D.; Martorelli C.; Facchetti F.; Gandini S.; Maisonneuve P.; Avril M.-F.; Demenais F.; Bressac-de Paillerets B.; Hoiom V.; Cust A.E.; Anton-Culver H.; Gruber S.B.; Gallagher R.P.; Marrett L.; Zanetti R.; Dwyer T.; Thomas N.E.; Begg C.B.; Berwick M.; Puig S.; Potrony M.; Nagore E.; Ghiorzo P.; Menin C.; Manganoni A.M.; Rodolfo M.; Brugnara S.; Passoni E.; Sekulovic L.K.; Baldini F.; Guida G.; Stratigos A.; Ozdemir F.; Ayala F.; Fernandez-de-Misa R.; Quaglino P.; Ribas G.; Romanini A.; Migliano E.; Stanganelli I.; Kanetsky P.A.; Pizzichetta M.A.; Garcia-Borron J.C.; Nan H.; Landi M.T.; Little J.; Newton-Bishop J.; Sera F.; Fargnoli M.C.; Raimondi S.; Alaibac M.; Ferrari A.; Valeri B.; Sicher M.; Mangiola D.; Nazzaro G.; Tosti G.; Mazzarol G.; Giudice G.; Ribero S.; Astrua C.; Mazzoni L.; Orlow I.; Mujumdar U.; Hummer A.; Busam K.; Roy P.; Canchola R.; Clas B.; Cotignola J.; Monroe Y.; Armstrong B.; Kricker A.; Litchfield M.; Tucker P.; Stephens N.; Switzer T.; Theis B.; From L.; Chowdhury N.; Vanasse L.; Purdue M.; Northrup D.; Rosso S.; Sacerdote C.; Leighton N.; Gildea M.; Bonner J.; Jeter J.; Klotz J.; Wilcox H.; Weiss H.; Millikan R.; Mattingly D.; Player J.; Tse C.-K.; Rebbeck T.; Walker A.; Panossian S.; Setlow R.; Mohrenweiser H.; Autier P.; Han J.; Caini S.; Hofman A.; Kayser M.; Liu F.; Nijsten T.; Uitterlinden A.G.; Kumar R.; Bishop T.; Elliott F.; Lazovich D.; Polsky D.; Hansson J.; Pastorino L.; Gruis N.A.; Bouwes Bavinck J.N.; Aguilera P.; Badenas C.; Carrera C.; Gimenez-Xavier P.; Malvehy J.; Puig-Butille J.A.; Tell-Marti G.; Blizzard L.; Cochrane J.; Branicki W.; Debniak T.; Morling N.; Johansen P.; Mayne S.; Bale A.; Cartmel B.; Ferrucci L.; Pfeiffer R.; Palmieri G.; Kypreou K.; Bowcock A.; Cornelius L.; Council M.L.; Motokawa T.; Anno S.; Helsing P.; Andresen P.A.; Guida S.; Wong T.H.Pellegrini, C.; Botta, F.; Massi, D.; Martorelli, C.; Facchetti, F.; Gandini, S.; Maisonneuve, P.; Avril, M. -F.; Demenais, F.; Bressac-de Paillerets, B.; Hoiom, V.; Cust, A. E.; Anton-Culver, H.; Gruber, S. B.; Gallagher, R. P.; Marrett, L.; Zanetti, R.; Dwyer, T.; Thomas, N. E.; Begg, C. B.; Berwick, M.; Puig, S.; Potrony, M.; Nagore, E.; Ghiorzo, P.; Menin, C.; Manganoni, A. M.; Rodolfo, M.; Brugnara, S.; Passoni, E.; Sekulovic, L. K.; Baldini, F.; Guida, G.; Stratigos, A.; Ozdemir, F.; Ayala, F.; Fernandez-de-Misa, R.; Quaglino, P.; Ribas, G.; Romanini, A.; Migliano, E.; Stanganelli, I.; Kanetsky, P. A.; Pizzichetta, M. A.; Garcia-Borron, J. C.; Nan, H.; Landi, M. T.; Little, J.; Newton-Bishop, J.; Sera, F.; Fargnoli, M. C.; Raimondi, S.; Alaibac, M.; Ferrari, A.; Valeri, B.; Sicher, M.; Mangiola, D.; Nazzaro, G.; Tosti, G.; Mazzarol, G.; Giudice, G.; Ribero, S.; Astrua, C.; Mazzoni, L.; Orlow, I.; Mujumdar, U.; Hummer, A.; Busam, K.; Roy, P.; Canchola, R.; Clas, B.; Cotignola, J.; Monroe, Y.; Armstrong, B.; Kricker, A.; Litchfield, M.; Tucker, P.; Stephens, N.; Switzer, T.; Theis, B.; From, L.; Chowdhury, N.; Vanasse, L.; Purdue, M.; Northrup, D.; Rosso, S.; Sacerdote, C.; Leighton, N.; Gildea, M.; Bonner, J.; Jeter, J.; Klotz, J.; Wilcox, H.; Weiss, H.; Millikan, R.; Mattingly, D.; Player, J.; Tse, C. -K.; Rebbeck, T.; Walker, A.; Panossian, S.; Setlow, R.; Mohrenweiser, H.; Autier, P.; Han, J.; Caini, S.; Hofman, A.; Kayser, M.; Liu, F.; Nijsten, T.; Uitterlinden, A. G.; Kumar, R.; Bishop, T.; Elliott, F.; Lazovich, D.; Polsky, D.; Hansson, J.; Pastorino, L.; Gruis, N. A.; Bouwes Bavinck, J. N.; Aguilera, P.; Badenas, C.; Carrera, C.; Gimenez-Xavier, P.; Malvehy, J.; Puig-Butille, J. A.; Tell-Marti, G.; Blizzard, L.; Cochrane, J.; Branicki, W.; Debniak, T.; Morling, N.; Johansen, P.; Mayne, S.; Bale, A.; Cartmel, B.; Ferrucci, L.; Pfeiffer, R.; Palmieri, G.; Kypreou, K.; Bowcock, A.; Cornelius, L.; Council, M. L.; Motokawa, T.; Anno, S.; Helsing, P.; Andresen, P. A.; Guida, S.; Wong, T. H

MC1R variants in childhood and adolescent melanoma: a retrospective pooled analysis of a multicentre cohort

Background: Germline variants in the melanocortin 1 receptor gene (MC1R) might increase the risk of childhood and adolescent melanoma, but a clear conclusion is challenging because of the low number of studies and cases. We assessed the association of MC1R variants with childhood and adolescent melanoma in a large study comparing the prevalence of MC1R variants in child or adolescent patients with melanoma to that in adult patients with melanoma and in healthy adult controls. Methods: In this retrospective pooled analysis, we used the M-SKIP Project, the Italian Melanoma Intergroup, and other European groups (with participants from Australia, Canada, France, Greece, Italy, the Netherlands, Serbia, Spain, Sweden, Turkey, and the USA) to assemble an international multicentre cohort. We gathered phenotypic and genetic data from children or adolescents diagnosed with sporadic single-primary cutaneous melanoma at age 20 years or younger, adult patients with sporadic single-primary cutaneous melanoma diagnosed at age 35 years or older, and healthy adult individuals as controls. We calculated odds ratios (ORs) for childhood and adolescent melanoma associated with MC1R variants by multivariable logistic regression. Subgroup analysis was done for children aged 18 or younger and 14 years or younger. Findings: We analysed data from 233 young patients, 932 adult patients, and 932 healthy adult controls. Children and adolescents had higher odds of carrying MC1R r variants than did adult patients (OR 1·54, 95% CI 1·02–2·33), including when analysis was restricted to patients aged 18 years or younger (1·80, 1·06–3·07). All investigated variants, except Arg160Trp, tended, to varying degrees, to have higher frequencies in young patients than in adult patients, with significantly higher frequencies found for Val60Leu (OR 1·60, 95% CI 1·05–2·44; p=0·04) and Asp294His (2·15, 1·05–4·40; p=0·04). Compared with those of healthy controls, young patients with melanoma had significantly higher frequencies of any MC1R variants. Interpretation: Our pooled analysis of MC1R genetic data of young patients with melanoma showed that MC1R r variants were more prevalent in childhood and adolescent melanoma than in adult melanoma, especially in patients aged 18 years or younger. Our findings support the role of MC1R in childhood and adolescent melanoma susceptibility, with a potential clinical relevance for developing early melanoma detection and preventive strategies. Funding: SPD-Pilot/Project-Award-2015; AIRC-MFAG-11831. © 2019 Elsevier Lt