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1. IDPlanT: the Italian database of plant translocation

Author: Abeli, T, D'Agostino, M, Orsenigo, S, Bartolucci, F, Accogli, R, Albani Rocchetti, G, Alessandrelli, C, Amadori, A, Amato, F, Angiolini, C, Assini, S, Bacchetta, G, Banfi, E, Bonini, I, Bonito, A, Borettini, M, Brancaleoni, L, Brusa, G, Buldrini, F, Carruggio, F, Carta, A, Castagnini, P, Cerabolini, B, Ceriani, R, Ciaschetti, G, Citterio, S, Clementi, U, Cogoni, D, Congiu, A, Conti, F, Crescente, M, Crosti, R, Cuena, A, D'Antraccoli, M, Dallai, D, De Andreis, R, Deidda, A, Dessi, C, De Vitis, M, Di Cecco, V, Di Cecco, M, Di Giustino, A, Di Martino, L, Di Noto, G, Domina, G, Fabrini, G, Farris, E, Fiorentin, R, Foggi, B, Forte, L, Galasso, G, Garfi, G, Gentile, C, Gentili, R, Geraci, A, Gerdol, R, Gheza, G, Giusso del Galdo, G, Gratani, L, La Placa, G, Landi, M, Loi, T, Luzzaro, A, Alfredo, M, Magnani, C, Magrini, S, Mantino, F, Mariotti, M, Martinelli, V, Mastrullo, S, Medagli, P, Minuto, L, Nonis, D, Palumbo, M, Paoli, L, Pasta, S, Peruzzi, L, Pierce, S, Pinna, M, Rainini, F, Ravera, S, Rossi, G, Sanna, N, Santini, C, Sau, S, Schettino, A, Schicchi, R, Sciandrello, S, Sgarbi, E, Gristina, A, Troia, A, Varone, L, Villa, M, Zappa, E, Fenu, G, Abeli T., D'Agostino M., Orsenigo S., Bartolucci F., Accogli R., Albani Rocchetti G., Alessandrelli C., Amadori A., Amato F., Angiolini C., Assini S., Bacchetta G., Banfi E., Bonini I., Bonito A., Borettini M. L., Brancaleoni L., Brusa G., Buldrini F., Carruggio F., Carta A., Castagnini P., Cerabolini B. E. L., Ceriani R. M., Ciaschetti G., Citterio S., Clementi U., Cogoni D., Congiu A., Conti F., Crescente M. F., Crosti R., Cuena A., D'Antraccoli M., Dallai D., De Andreis R., Deidda A., Dessi C., De Vitis M., Di Cecco V., Di Cecco M., Di Giustino A., Di Martino L., Di Noto G., Domina G., Fabrini G., Farris E., Fiorentin R., Foggi B., Forte L., Galasso G., Garfi G., Gentile C., Gentili R., Geraci A., Gerdol R., Gheza G., Giusso del Galdo G., Gratani L., La Placa G., Landi M., Loi T., Luzzaro A., Alfredo M., Magnani C., Magrini S., Mantino F., Mariotti M. G., Martinelli V., Mastrullo S., Medagli P., Minuto L., Nonis D., Palumbo M. E., Paoli L., Pasta S., Peruzzi L., Pierce S., Pinna M. S., Rainini F., Ravera S., Rossi G., Sanna N., Santini C., Sau S., Schettino A., Schicchi R., Sciandrello S., Sgarbi E., Gristina A. S., Troia A., Varone L., Villa M., Zappa E., Fenu G., Abeli, T, D'Agostino, M, Orsenigo, S, Bartolucci, F, Accogli, R, Albani Rocchetti, G, Alessandrelli, C, Amadori, A, Amato, F, Angiolini, C, Assini, S, Bacchetta, G, Banfi, E, Bonini, I, Bonito, A, Borettini, M, Brancaleoni, L, Brusa, G, Buldrini, F, Carruggio, F, Carta, A, Castagnini, P, Cerabolini, B, Ceriani, R, Ciaschetti, G, Citterio, S, Clementi, U, Cogoni, D, Congiu, A, Conti, F, Crescente, M, Crosti, R, Cuena, A, D'Antraccoli, M, Dallai, D, De Andreis, R, Deidda, A, Dessi, C, De Vitis, M, Di Cecco, V, Di Cecco, M, Di Giustino, A, Di Martino, L, Di Noto, G, Domina, G, Fabrini, G, Farris, E, Fiorentin, R, Foggi, B, Forte, L, Galasso, G, Garfi, G, Gentile, C, Gentili, R, Geraci, A, Gerdol, R, Gheza, G, Giusso del Galdo, G, Gratani, L, La Placa, G, Landi, M, Loi, T, Luzzaro, A, Alfredo, M, Magnani, C, Magrini, S, Mantino, F, Mariotti, M, Martinelli, V, Mastrullo, S, Medagli, P, Minuto, L, Nonis, D, Palumbo, M, Paoli, L, Pasta, S, Peruzzi, L, Pierce, S, Pinna, M, Rainini, F, Ravera, S, Rossi, G, Sanna, N, Santini, C, Sau, S, Schettino, A, Schicchi, R, Sciandrello, S, Sgarbi, E, Gristina, A, Troia, A, Varone, L, Villa, M, Zappa, E, Fenu, G, Abeli T., D'Agostino M., Orsenigo S., Bartolucci F., Accogli R., Albani Rocchetti G., Alessandrelli C., Amadori A., Amato F., Angiolini C., Assini S., Bacchetta G., Banfi E., Bonini I., Bonito A., Borettini M. L., Brancaleoni L., Brusa G., Buldrini F., Carruggio F., Carta A., Castagnini P., Cerabolini B. E. L., Ceriani R. M., Ciaschetti G., Citterio S., Clementi U., Cogoni D., Congiu A., Conti F., Crescente M. F., Crosti R., Cuena A., D'Antraccoli M., Dallai D., De Andreis R., Deidda A., Dessi C., De Vitis M., Di Cecco V., Di Cecco M., Di Giustino A., Di Martino L., Di Noto G., Domina G., Fabrini G., Farris E., Fiorentin R., Foggi B., Forte L., Galasso G., Garfi G., Gentile C., Gentili R., Geraci A., Gerdol R., Gheza G., Giusso del Galdo G., Gratani L., La Placa G., Landi M., Loi T., Luzzaro A., Alfredo M., Magnani C., Magrini S., Mantino F., Mariotti M. G., Martinelli V., Mastrullo S., Medagli P., Minuto L., Nonis D., Palumbo M. E., Paoli L., Pasta S., Peruzzi L., Pierce S., Pinna M. S., Rainini F., Ravera S., Rossi G., Sanna N., Santini C., Sau S., Schettino A., Schicchi R., Sciandrello S., Sgarbi E., Gristina A. S., Troia A., Varone L., Villa M., Zappa E., and Fenu G.
Abstract: IDPlanT is the Italian Database of Plant Translocation, an initiative of the Nature Conservation Working Group of the Italian Botanical Society. IDPlanT currently includes 185 plant translocations. The establishment of a national database on plant translocation is a key step forward in data sharing and techniques improvement in this field of plant conservation. Supplemental data for this article is available online at https://doi.org/10.1080/11263504.2021.1985004.
Published: 2021

2. Novel MAPK/AKT-impairing germline NRAS variant identified in a melanoma-prone family

Author: Brown, K. M., Xu, M., Sargen, M., Jang, H., Zhang, M., Zhang, T., Zhu, B., Jones, K., Kim, J., Mendoza, L., Hayward, N. K., Tucker, M. A., Goldstein, A. M., Yang, X. R., Stewart, D. R., Hicks, B., Consonni, D., Pesatori, A. C., Fargnoli, Maria Concetta, Peris, Ketty, Stratigos, A., Menin, C., Ghiorzo, P., Puig, S., Nagore, E., Andresson, T., Nussinov, R., Calista, D., Landi, M. T., Fargnoli M. C., Peris K. (ORCID:0000-0002-5237-0463), Brown, K. M., Xu, M., Sargen, M., Jang, H., Zhang, M., Zhang, T., Zhu, B., Jones, K., Kim, J., Mendoza, L., Hayward, N. K., Tucker, M. A., Goldstein, A. M., Yang, X. R., Stewart, D. R., Hicks, B., Consonni, D., Pesatori, A. C., Fargnoli, Maria Concetta, Peris, Ketty, Stratigos, A., Menin, C., Ghiorzo, P., Puig, S., Nagore, E., Andresson, T., Nussinov, R., Calista, D., Landi, M. T., Fargnoli M. C., and Peris K. (ORCID:0000-0002-5237-0463)
Abstract: While several high-penetrance melanoma risk genes are known, variation in these genes fail to explain melanoma susceptibility in a large proportion of high-risk families. As part of a melanoma family sequencing study, including 435 families from Mediterranean populations we identified a novel NRAS variant (c.170A > C, p.D57A) in an Italian melanoma-prone family. This variant is absent in exomes in gnomAD, ESP, UKBiobank, and the 1000 Genomes Project, as well as in 11,273 Mediterranean individuals and 109 melanoma-prone families from the US and Australia. This variant occurs in the GTP-binding pocket of NRAS. Differently from other RAS activating alterations, NRAS D57A expression is unable to activate MAPK-pathway both constitutively and after stimulation but enhances EGF-induced PI3K-pathway signaling in serum starved conditions in vitro. Consistent with in vitro data demonstrating that NRAS D57A does not enrich GTP binding, molecular modeling suggests that the D57A substitution would be expected to impair Mg2 + binding and decrease nucleotide-binding and GTPase activity of NRAS. While we cannot firmly establish NRAS c.170A > C (p.D57A) as a melanoma susceptibility variant, further investigation of NRAS as a familial melanoma gene is warranted.
Published: 2021

3. Germline ATM variants predispose to melanoma: a joint analysis across the GenoMEL and MelaNostrum consortia

Author: Dalmasso, B., Pastorino, L., Nathan, V., Shah, N. N., Palmer, J. M., Howlie, M., Johansson, P. A., Freedman, N. D., Carter, B. D., Beane-Freeman, L., Hicks, B., Molven, A., Helgadottir, H., Sankar, A., Tsao, H., Stratigos, A. J., Helsing, P., Van Doorn, R., Gruis, N. A., Visser, M., Wadt, K. A. W., Mann, G., Holland, E. A., Nagore, E., Potrony, M., Puig, S., Menin, C., Peris, Ketty, Fargnoli, Maria Concetta, Calista, D., Soufir, N., Harland, M., Bishop, T., Kanetsky, P. A., Elder, D. E., Andreotti, V., Vanni, I., Bruno, W., Hoiom, V., Tucker, M. A., Yang, X. R., Andresen, P. A., Adams, D. J., Landi, M. T., Hayward, N. K., Goldstein, A. M., Ghiorzo, P., Peris K. (ORCID:0000-0002-5237-0463), Fargnoli M. C., Dalmasso, B., Pastorino, L., Nathan, V., Shah, N. N., Palmer, J. M., Howlie, M., Johansson, P. A., Freedman, N. D., Carter, B. D., Beane-Freeman, L., Hicks, B., Molven, A., Helgadottir, H., Sankar, A., Tsao, H., Stratigos, A. J., Helsing, P., Van Doorn, R., Gruis, N. A., Visser, M., Wadt, K. A. W., Mann, G., Holland, E. A., Nagore, E., Potrony, M., Puig, S., Menin, C., Peris, Ketty, Fargnoli, Maria Concetta, Calista, D., Soufir, N., Harland, M., Bishop, T., Kanetsky, P. A., Elder, D. E., Andreotti, V., Vanni, I., Bruno, W., Hoiom, V., Tucker, M. A., Yang, X. R., Andresen, P. A., Adams, D. J., Landi, M. T., Hayward, N. K., Goldstein, A. M., Ghiorzo, P., Peris K. (ORCID:0000-0002-5237-0463), and Fargnoli M. C.
Abstract: Purpose: Ataxia–Telangiectasia Mutated (ATM) has been implicated in the risk of several cancers, but establishing a causal relationship is often challenging. Although ATM single-nucleotide polymorphisms have been linked to melanoma, few functional alleles have been identified. Therefore, ATM impact on melanoma predisposition is unclear. Methods: From 22 American, Australian, and European sites, we collected 2,104 familial, multiple primary (MPM), and sporadic melanoma cases who underwent ATM genotyping via panel, exome, or genome sequencing, and compared the allele frequency (AF) of selected ATM variants classified as loss-of-function (LOF) and variants of uncertain significance (VUS) between this cohort and the gnomAD non-Finnish European (NFE) data set. Results: LOF variants were more represented in our study cohort than in gnomAD NFE, both in all (AF = 0.005 and 0.002, OR = 2.6, 95% CI = 1.56–4.11, p < 0.01), and familial + MPM cases (AF = 0.0054 and 0.002, OR = 2.97, p < 0.01). Similarly, VUS were enriched in all (AF = 0.046 and 0.033, OR = 1.41, 95% CI = 1.6–5.09, p < 0.01) and familial + MPM cases (AF = 0.053 and 0.033, OR = 1.63, p < 0.01). In a case–control comparison of two centers that provided 1,446 controls, LOF and VUS were enriched in familial + MPM cases (p = 0.027, p = 0.018). Conclusion: This study, describing the largest multicenter melanoma cohort investigated for ATM germline variants, supports the role of ATM as a melanoma predisposition gene, with LOF variants suggesting a moderate-risk.
Published: 2021

4. Genome-wide association meta-analysis identifies pleiotropic risk loci for aerodigestive squamous cell cancers

Author: Lesseur, C., Ferreiro-Iglesias, A., McKay, J. D., Bosse, Y., Johansson, M., Gaborieau, V., Landi, M. T., Christiani, D. C., Caporaso, N. C., Bojesen, S. E., Amos, C. I., Shete, S., Liu, G., Rennert, G., Albanes, D., Aldrich, M. C., Tardon, A., Chen, Chen, Triantafillos, L., Field, J. K., Teare, M. D., Kiemeney, L. A., Diergaarde, B., Ferris, R. L., Zienolddiny, S., Lam, S., Olshan, A. F., Weissler, M. C., Lacko, M., Risch, A., Bickeboller, H., Ness, A. R., Thomas, S., Le Marchand, L., Schabath, M. B., Wunsch-Filho, V., Tajara, E. H., Andrew, A. S., Clifford, G. M., Lazarus, P., Grankvist, K., Arnold, S., Melander, O., Brunnstrom, H., Boccia, S., Cadoni, G., Timens, W., Obeidat, M., Xiao, X., Houlston, R. S., Hung, R. J., Brennan, P., Liu G., Chen C., Boccia S. (ORCID:0000-0002-1864-749X), Cadoni G. (ORCID:0000-0001-8244-784X), Lesseur, C., Ferreiro-Iglesias, A., McKay, J. D., Bosse, Y., Johansson, M., Gaborieau, V., Landi, M. T., Christiani, D. C., Caporaso, N. C., Bojesen, S. E., Amos, C. I., Shete, S., Liu, G., Rennert, G., Albanes, D., Aldrich, M. C., Tardon, A., Chen, Chen, Triantafillos, L., Field, J. K., Teare, M. D., Kiemeney, L. A., Diergaarde, B., Ferris, R. L., Zienolddiny, S., Lam, S., Olshan, A. F., Weissler, M. C., Lacko, M., Risch, A., Bickeboller, H., Ness, A. R., Thomas, S., Le Marchand, L., Schabath, M. B., Wunsch-Filho, V., Tajara, E. H., Andrew, A. S., Clifford, G. M., Lazarus, P., Grankvist, K., Arnold, S., Melander, O., Brunnstrom, H., Boccia, S., Cadoni, G., Timens, W., Obeidat, M., Xiao, X., Houlston, R. S., Hung, R. J., Brennan, P., Liu G., Chen C., Boccia S. (ORCID:0000-0002-1864-749X), and Cadoni G. (ORCID:0000-0001-8244-784X)
Abstract: Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant (Pmeta<5x10-8) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273). Additionally, three previously unknown loci reached suggestive significance (Pmeta<5x10-7): 1q32.1 (rs12133735, near MDM4), 5q31.2 (rs13181561, TMEM173) and 19p13.11 (rs61494113, ABHD8). Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 (ADH1B), 6p21.33 (STK19), 6p21.32 (HLA-DQB1), 9p21.33 (CDKN2B-AS1) and 13q13.1(BRCA2). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.
Published: 2021

5. MC1R variants as melanoma risk factors independent of at-risk phenotypic characteristics: A pooled analysis from the M-SKIP project

Author: Tagliabue, E, Gandini, S, Bellocco, R, Maisonneuve, P, Newton-Bishop, J, Polsky, D, Lazovich, D, Kanetsky, P, Ghiorzo, P, Gruis, N, Landi, M, Menin, C, Fargnoli, M, Garcia-Borron, J, Han, J, Little, J, Sera, F, Raimondi, S, Tagliabue E., Gandini S., Bellocco R., Maisonneuve P., Newton-Bishop J., Polsky D., Lazovich D., Kanetsky P. A., Ghiorzo P., Gruis N. A., Landi M. T., Menin C., Fargnoli M. C., Garcia-Borron J. C., Han J., Little J., Sera F., Raimondi S., Tagliabue, E, Gandini, S, Bellocco, R, Maisonneuve, P, Newton-Bishop, J, Polsky, D, Lazovich, D, Kanetsky, P, Ghiorzo, P, Gruis, N, Landi, M, Menin, C, Fargnoli, M, Garcia-Borron, J, Han, J, Little, J, Sera, F, Raimondi, S, Tagliabue E., Gandini S., Bellocco R., Maisonneuve P., Newton-Bishop J., Polsky D., Lazovich D., Kanetsky P. A., Ghiorzo P., Gruis N. A., Landi M. T., Menin C., Fargnoli M. C., Garcia-Borron J. C., Han J., Little J., Sera F., and Raimondi S.
Abstract: Purpose: Melanoma represents an important public health problem, due to its high case-fatality rate. Identification of individuals at high risk would be of major interest to improve early diagnosis and ultimately survival. The aim of this study was to evaluate whether MC1R variants predicted melanoma risk independently of at-risk phenotypic characteristics. Materials and methods: Data were collected within an international collaboration – the M-SKIP project. The present pooled analysis included data on 3,830 single, primary, sporadic, cutaneous melanoma cases and 2,619 controls from seven previously published case–control studies. All the studies had information on MC1R gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype. Results: The presence of any MC1R variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95% CI 1.36–1.88). Inclusion of MC1R variants in a risk prediction model increased melanoma predictive accuracy (area under the receiver-operating characteristic curve) by 0.7% over a base clinical model (P=0.002), and 24% of participants were better assessed (net reclassification index 95% CI 20%–30%). Subgroup analysis suggested a possibly stronger role of MC1R in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28%) compared to paler skinned participants (15%). Conclusion: The authors suggest that measuring the MC1R genotype might result in a benefit for melanoma prediction. The results could be a valid starting point to guide the development of scientific protocols assessing melanoma risk prediction tools incorporating the MC1R genotype.
Published: 2018

6. MC1R variants as melanoma risk factors independent of at-risk phenotypic characteristics: A pooled analysis from the M-SKIP project

Author: Tagliabue, E, Gandini, S, Bellocco, R, Maisonneuve, P, Newton-Bishop, J, Polsky, D, Lazovich, D, Kanetsky, P, Ghiorzo, P, Gruis, N, Landi, M, Menin, C, Fargnoli, M, Garcia-Borron, J, Han, J, Little, J, Sera, F, Raimondi, S, Tagliabue E., Gandini S., Bellocco R., Maisonneuve P., Newton-Bishop J., Polsky D., Lazovich D., Kanetsky P. A., Ghiorzo P., Gruis N. A., Landi M. T., Menin C., Fargnoli M. C., Garcia-Borron J. C., Han J., Little J., Sera F., Raimondi S., Tagliabue, E, Gandini, S, Bellocco, R, Maisonneuve, P, Newton-Bishop, J, Polsky, D, Lazovich, D, Kanetsky, P, Ghiorzo, P, Gruis, N, Landi, M, Menin, C, Fargnoli, M, Garcia-Borron, J, Han, J, Little, J, Sera, F, Raimondi, S, Tagliabue E., Gandini S., Bellocco R., Maisonneuve P., Newton-Bishop J., Polsky D., Lazovich D., Kanetsky P. A., Ghiorzo P., Gruis N. A., Landi M. T., Menin C., Fargnoli M. C., Garcia-Borron J. C., Han J., Little J., Sera F., and Raimondi S.
Abstract: Purpose: Melanoma represents an important public health problem, due to its high case-fatality rate. Identification of individuals at high risk would be of major interest to improve early diagnosis and ultimately survival. The aim of this study was to evaluate whether MC1R variants predicted melanoma risk independently of at-risk phenotypic characteristics. Materials and methods: Data were collected within an international collaboration – the M-SKIP project. The present pooled analysis included data on 3,830 single, primary, sporadic, cutaneous melanoma cases and 2,619 controls from seven previously published case–control studies. All the studies had information on MC1R gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype. Results: The presence of any MC1R variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95% CI 1.36–1.88). Inclusion of MC1R variants in a risk prediction model increased melanoma predictive accuracy (area under the receiver-operating characteristic curve) by 0.7% over a base clinical model (P=0.002), and 24% of participants were better assessed (net reclassification index 95% CI 20%–30%). Subgroup analysis suggested a possibly stronger role of MC1R in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28%) compared to paler skinned participants (15%). Conclusion: The authors suggest that measuring the MC1R genotype might result in a benefit for melanoma prediction. The results could be a valid starting point to guide the development of scientific protocols assessing melanoma risk prediction tools incorporating the MC1R genotype.
Published: 2018

7. Overlapping genetic architecture between Parkinson disease and melanoma

Author: Dube, Umber, Ibanez, Laura, Budde, John P., Benitez, Bruno A., Davis, Albert A., Harari, Oscar, Iles, M. M., Law, Matthew H., Brown, Kevin M., Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Hinds, David A., Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Sathirapongsasuti, J. Fah, Sazonova, Olga V., Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce Y., Vacic, Vladimir, Wilson, Catherine H., Bishop, D. T., Lee, J. E., Brossard, M., Martin, N. G., Moses, E. K., Song, F., Barrett, J. H., Kumar, R., Easton, D. F., Pharoah, P. D., Swerdlow, A. J., Kypreou, K. P., Taylor, J. C., Harland, M., Randerson-Moor, J., Akslen, L. A., Andresen, P. A., Avril, M. F., Azizi, E., Scarrà, G. B., Brown, K. M., Debniak, T., Duffy, D. L., Elder, D. E., Fang, S., Friedman, E., Galan, P., Ghiorzo, P., Gillanders, E. M., Goldstein, A. M., Gruis, N. A., Hansson, J., Helsing, P., Hočevar, M., Höiom, V., Ingvar, C., Kanetsky, P. A., Chen, W. V., Landi, M. T., Lang, J., Lathrop, G. M., Lubiński, J., Mackie, R. M., Mann, G. J., Molven, A., Montgomery, G. W., Novaković, S., Olsson, H., Puig, S., Puig-Butille, J. A., Wu, W., Qureshi, A. A., Radford-Smith, G. L., van der Stoep, N., van Doorn, R., Whiteman, D. C., Craig, J. E., Schadendorf, E., Simms, L. A., Burdon, K. P., Nyholt, D. R., Pooley, K. A., Orr, N., Stratigos, A. J., Cust, A. E., Ward, S. V., Hayward, N. K., Han, J., Schulze, H. J., Dunning, A. M., Bishop, J. A., Demenais, F., Amos, C. I., MacGregor, S., Cruchaga, Carlos, other, and, Dube, Umber, Ibanez, Laura, Budde, John P., Benitez, Bruno A., Davis, Albert A., Harari, Oscar, Iles, M. M., Law, Matthew H., Brown, Kevin M., Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Hinds, David A., Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Sathirapongsasuti, J. Fah, Sazonova, Olga V., Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce Y., Vacic, Vladimir, Wilson, Catherine H., Bishop, D. T., Lee, J. E., Brossard, M., Martin, N. G., Moses, E. K., Song, F., Barrett, J. H., Kumar, R., Easton, D. F., Pharoah, P. D., Swerdlow, A. J., Kypreou, K. P., Taylor, J. C., Harland, M., Randerson-Moor, J., Akslen, L. A., Andresen, P. A., Avril, M. F., Azizi, E., Scarrà, G. B., Brown, K. M., Debniak, T., Duffy, D. L., Elder, D. E., Fang, S., Friedman, E., Galan, P., Ghiorzo, P., Gillanders, E. M., Goldstein, A. M., Gruis, N. A., Hansson, J., Helsing, P., Hočevar, M., Höiom, V., Ingvar, C., Kanetsky, P. A., Chen, W. V., Landi, M. T., Lang, J., Lathrop, G. M., Lubiński, J., Mackie, R. M., Mann, G. J., Molven, A., Montgomery, G. W., Novaković, S., Olsson, H., Puig, S., Puig-Butille, J. A., Wu, W., Qureshi, A. A., Radford-Smith, G. L., van der Stoep, N., van Doorn, R., Whiteman, D. C., Craig, J. E., Schadendorf, E., Simms, L. A., Burdon, K. P., Nyholt, D. R., Pooley, K. A., Orr, N., Stratigos, A. J., Cust, A. E., Ward, S. V., Hayward, N. K., Han, J., Schulze, H. J., Dunning, A. M., Bishop, J. A., Demenais, F., Amos, C. I., MacGregor, S., Cruchaga, Carlos, and other, and
Abstract: Epidemiologic studies have reported inconsistent results regarding an association between Parkinson disease (PD) and cutaneous melanoma (melanoma). Identifying shared genetic architecture between these diseases can support epidemiologic findings and identify common risk genes and biological pathways. Here, we apply polygenic, linkage disequilibrium-informed methods to the largest available case–control, genome-wide association study summary statistic data for melanoma and PD. We identify positive and significant genetic correlation (correlation: 0.17, 95% CI 0.10–0.24; P = 4.09 × 10−06) between melanoma and PD. We further demonstrate melanoma and PD-inferred gene expression to overlap across tissues (correlation: 0.14, 95% CI 0.06 to 0.22; P = 7.87 × 10−04) and highlight seven genes including PIEZO1, TRAPPC2L, and SOX6 as potential mediators of the genetic correlation between melanoma and PD. These findings demonstrate specific, shared genetic architecture between PD and melanoma that manifests at the level of gene expression.
Published: 2020

8. Consensus statement of the Italian society of pediatric allergy and immunology for the pragmatic management of children and adolescents with allergic or immunological diseases during the COVID-19 pandemic

Author: Cardinale, F, Ciprandi, G, Barberi, S, Bernardini, R, Caffarelli, C, Calvani, M, Cavagni, G, Galli, E, Minasi, D, Del Giudice, M, Moschese, V, Novembre, E, Paravati, F, Peroni, D, Tosca, M, Traina, G, Tripodi, S, Marseglia, G, Amato, D, Anania, C, Anastasio, E, Antignani, R, Arasi, S, Baldassarre, M, Baldo, E, Barbalace, A, Barni, S, Betti, F, Bianchi, A, Bolzacchini, E, Bonini, M, Bottau, P, Bozzetto, S, Brighetti, M, Caimmi, D, Caimmi, S, Calzone, L, Cancrini, C, Caminiti, L, Capata, G, Capra, L, Capristo, C, Carboni, E, Carella, F, Castagnoli, R, Chiappini, E, Chiera, F, Chinellato, I, Chini, L, Cipriani, F, Civitelli, F, Comberiati, P, Contini, D, Corrente, S, Cravidi, C, Crisafulli, G, Cuomo, B, D'Auria, E, D'Elios, S, Decimo, F, Giustina, A, Piane, R, De Filippo, M, De Vittori, V, Diaferio, L, Di Mauro, M, Duse, M, Federici, S, Felice, G, Fenu, G, Ferrante, G, Foti, T, Franceschini, F, Ghiglioni, D, Giardino, G, Giovannini, M, Indirli, G, Indolfi, C, Landi, M, La Torre, F, Leone, L, Licari, A, Liotti, L, Lougaris, V, Maiello, N, Mantecca, P, Manti, S, Mariani, M, Martelli, A, Mastrorilli, C, Mastrorilli, V, Montin, D, Mori, F, Olcese, R, Ottaviano, G, Paglialunga, C, Pajno, G, Parisi, G, Pattini, S, Pecoraro, L, Pelosi, U, Pignata, C, Ricci, G, Ricci, S, Rizzi, S, Rizzo, C, Rosati, S, Rosso, P, Sangerardi, M, Santoro, A, Saretta, F, Sarti, L, Sartorio, M, Sgruletti, M, Soresina, A, Sfika, I, Sgrulletti, M, Tesse, N, Tranchino, V, Travaglini, A, Velia, M, Verduci, E, Vernich, M, Veronelli, E, Volpi, S, Votto, M, Zicari, A, Cardinale, F, Ciprandi, G, Barberi, S, Bernardini, R, Caffarelli, C, Calvani, M, Cavagni, G, Galli, E, Minasi, D, Del Giudice, M, Moschese, V, Novembre, E, Paravati, F, Peroni, D, Tosca, M, Traina, G, Tripodi, S, Marseglia, G, Amato, D, Anania, C, Anastasio, E, Antignani, R, Arasi, S, Baldassarre, M, Baldo, E, Barbalace, A, Barni, S, Betti, F, Bianchi, A, Bolzacchini, E, Bonini, M, Bottau, P, Bozzetto, S, Brighetti, M, Caimmi, D, Caimmi, S, Calzone, L, Cancrini, C, Caminiti, L, Capata, G, Capra, L, Capristo, C, Carboni, E, Carella, F, Castagnoli, R, Chiappini, E, Chiera, F, Chinellato, I, Chini, L, Cipriani, F, Civitelli, F, Comberiati, P, Contini, D, Corrente, S, Cravidi, C, Crisafulli, G, Cuomo, B, D'Auria, E, D'Elios, S, Decimo, F, Giustina, A, Piane, R, De Filippo, M, De Vittori, V, Diaferio, L, Di Mauro, M, Duse, M, Federici, S, Felice, G, Fenu, G, Ferrante, G, Foti, T, Franceschini, F, Ghiglioni, D, Giardino, G, Giovannini, M, Indirli, G, Indolfi, C, Landi, M, La Torre, F, Leone, L, Licari, A, Liotti, L, Lougaris, V, Maiello, N, Mantecca, P, Manti, S, Mariani, M, Martelli, A, Mastrorilli, C, Mastrorilli, V, Montin, D, Mori, F, Olcese, R, Ottaviano, G, Paglialunga, C, Pajno, G, Parisi, G, Pattini, S, Pecoraro, L, Pelosi, U, Pignata, C, Ricci, G, Ricci, S, Rizzi, S, Rizzo, C, Rosati, S, Rosso, P, Sangerardi, M, Santoro, A, Saretta, F, Sarti, L, Sartorio, M, Sgruletti, M, Soresina, A, Sfika, I, Sgrulletti, M, Tesse, N, Tranchino, V, Travaglini, A, Velia, M, Verduci, E, Vernich, M, Veronelli, E, Volpi, S, Votto, M, and Zicari, A
Abstract: The COVID-19 pandemic has surprised the entire population. The world has had to face an unprecedented pandemic. Only, Spanish flu had similar disastrous consequences. As a result, drastic measures (lockdown) have been adopted worldwide. Healthcare service has been overwhelmed by the extraordinary influx of patients, often requiring high intensity of care. Mortality has been associated with severe comorbidities, including chronic diseases. Patients with frailty were, therefore, the victim of the SARS-COV-2 infection. Allergy and asthma are the most prevalent chronic disorders in children and adolescents, so they need careful attention and, if necessary, an adaptation of their regular treatment plans. Fortunately, at present, young people are less suffering from COVID-19, both as incidence and severity. However, any age, including infancy, could be affected by the pandemic. Based on this background, the Italian Society of Pediatric Allergy and Immunology has felt it necessary to provide a Consensus Statement. This expert panel consensus document offers a rationale to help guide decision-making in the management of children and adolescents with allergic or immunologic diseases.
Published: 2020

9. Comparative phytochemical profile of the elephant garlic (Allium ampeloprasum var. holmense) and the common garlic (Allium sativum) from the Val di Chiana area (Tuscany, Italy) before and after in vitro gastrointestinal digestion

Author: Ceccanti, C., Rocchetti, Gabriele, Lucini, Luigi, Giuberti, Gianluca, Landi, M., Biagiotti, S., Guidi, L., Rocchetti G. (ORCID:0000-0003-3488-4513), Lucini L. (ORCID:0000-0002-5133-9464), Giuberti G. (ORCID:0000-0002-0135-1609), Ceccanti, C., Rocchetti, Gabriele, Lucini, Luigi, Giuberti, Gianluca, Landi, M., Biagiotti, S., Guidi, L., Rocchetti G. (ORCID:0000-0003-3488-4513), Lucini L. (ORCID:0000-0002-5133-9464), and Giuberti G. (ORCID:0000-0002-0135-1609)
Abstract: This study is aimed to comparatively investigate the phytochemical profiles, focusing on the nutritional and phytochemical properties of common garlic (Allium sativum L.; CG) and elephant garlic (EG) (Allium ampeloprasum var. holmense) collected from the Val di Chiana area (Tuscany, Italy). The results showed a lower amount of fibers, demonstrating a higher digestibility of the bulb, and sulfur-containing compounds in EG rather than in CG. Untargeted metabolomic profiling followed by supervised and unsupervised statistics allowed understanding the differences in phytochemical composition among the two bulbs, both as raw bulbs, processed following the in vitro gastrointestinal digestion process. Typical sulfur-containing compounds, such as alliin and N-gamma-glutamyl-S-allyl cysteine, could notably be detected in lower amounts in EG. EG maintains a distinct phytochemical signature during in vitro gastrointestinal digestion. Our findings support the distinct sensorial attributes of the bulbs.
Published: 2020

10. Effect of cut on secondary metabolite profile in hydroponically-grown Rumex acetosa L. seedlings: a metabolomic approach

Author: Ceccanti, C., Landi, M., Rocchetti, Gabriele, Miras Moreno, Maria Begona, Lucini, Luigi, Incrocci, L., Pardossi, A., Guidi, L., Rocchetti G. (ORCID:0000-0003-3488-4513), Miras Moreno M. B. (ORCID:0000-0002-5931-355X), Lucini L. (ORCID:0000-0002-5133-9464), Ceccanti, C., Landi, M., Rocchetti, Gabriele, Miras Moreno, Maria Begona, Lucini, Luigi, Incrocci, L., Pardossi, A., Guidi, L., Rocchetti G. (ORCID:0000-0003-3488-4513), Miras Moreno M. B. (ORCID:0000-0002-5931-355X), and Lucini L. (ORCID:0000-0002-5133-9464)
Abstract: Seedlings of Rumex acetosa L. (sorrel) were grown in floating system and two consecutive cuts took place: 15 (C1) and 30 (C2) days after sowing. An untargeted metabolomics approach was utilised to fingerprint phenolics and other health-related compounds in sorrel leaves, as well as to unveil differences between the two cuts. The untargeted approach allowed to putatively identify 458 metabolites considering both the cuts. Three new terpenoids and two new phenylpropanoid glycosides (dihydrosyringin and dihydroconiferin) with antifungal and anti-inflammatory activity were annotated. Overall, leaves from C2 had lower level of secondary metabolites (44 were down-accumulated), especially sesquiterpenes and stilbenes. Conversely, anthocyanins showed a relevant increase in C2 than in C1 leaves. The dataset suggests that sorrel leaves represent a good source of nutraceutical compounds and unveils the pivotal effect of pre-harvest factor in secondary metabolite profile.
Published: 2020

11. Outcomes in children treated for tuberculosis with the new dispersible fixed-dose combinations in Port Moresby

Author: Apis, V, Landi, M, Graham, SM, Islam, T, Amini, J, Sabumi, G, Mandalakas, AM, Meae, T, du Cros, P, Shewade, HD, Welch, H, Apis, V, Landi, M, Graham, SM, Islam, T, Amini, J, Sabumi, G, Mandalakas, AM, Meae, T, du Cros, P, Shewade, HD, and Welch, H
Abstract: SETTING: The new child-friendly fixed dose combinations (FDCs) were introduced at Port Moresby General Hospital, Papua New Guinea, in 2016 for the first-line treatment of children (aged <15 years) with tuberculosis (TB) who weighed <25 kg. OBJECTIVE: To describe the characteristics and outcomes for children treated with the new FDCs, and to identify risk factors for unfavourable treatment outcomes. DESIGN: This was a retrospective cohort study of all children treated for TB with the FDCs from August 2016 to August 2017. RESULTS: Of 713 children included, 488 (68%) were diagnosed with pulmonary TB. Only 6 (0.8%) TB cases were bacteriologically confirmed and human immunodeficiency virus (HIV) status was known in 50%. Treatment outcomes were favourable in 425 (60%) children. Of 288 children with unfavourable outcomes, there were 242 (84%) with loss to follow-up (LTFU) and 25 (8.4%) were known to have died. Children who were severely underweight (weight-for-age Z score <-3) on presentation were at greater risk of LTFU compared to children of normal weight on multivariable analysis (aRR 1.3, 95%CI 1.0-1.6, P < 0.05). CONCLUSION: Alternative models of care to decrease LTFU during treatment are needed, including integration with nutritional support. Improving diagnosis through microbiological confirmation of TB and HIV are major challenges to be addressed.
Published: 2019

12. Shared heritability and functional enrichment across six solid cancers

Author: Jiang, X. (Xia), Finucane, H. K. (Hilary K.), Schumacher, F. R. (Fredrick R.), Schmit, S. L. (Stephanie L.), Tyrer, J. P. (Jonathan P.), Han, Y. (Younghun), Michailidou, K. (Kyriaki), Lesseur, C. (Corina), Kuchenbaecker, K. B. (Karoline B.), Dennis, J. (Joe), Conti, D. V. (David V.), Casey, G. (Graham), Gaudet, M. M. (Mia M.), Huyghe, J. R. (Jeroen R.), Albanes, D. (Demetrius), Aldrich, M. C. (Melinda C.), Andrew, A. S. (Angeline S.), Andrulis, I. L. (Irene L.), Anton-Culver, H. (Hoda), Antoniou, A. C. (Antonis C.), Antonenkova, N. N. (Natalia N.), Arnold, S. M. (Susanne M.), Aronson, K. J. (Kristan J.), Arun, B. K. (Banu K.), Bandera, E. V. (Elisa V.), Barkardottir, R. B. (Rosa B.), Barnes, D. R. (Daniel R.), Batra, J. (Jyotsna), Beckmann, M. W. (Matthias W.), Benitez, J. (Javier), Benlloch, S. (Sara), Berchuck, A. (Andrew), Berndt, S. I. (Sonja I.), Bickeboeller, H. (Heike), Bien, S. A. (Stephanie A.), Blomqvist, C. (Carl), Boccia, S. (Stefania), Bogdanova, N. V. (Natalia V.), Bojesen, S. E. (Stig E.), Bolla, M. K. (Manjeet K.), Brauch, H. (Hiltrud), Brenner, H. (Hermann), Brenton, J. D. (James D.), Brook, M. N. (Mark N.), Brunet, J. (Joan), Brunnstrom, H. (Hans), Buchanan, D. D. (Daniel D.), Burwinkel, B. (Barbara), Butzow, R. (Ralf), Cadoni, G. (Gabriella), Caldes, T. (Trinidad), Caligo, M. A. (Maria A.), Campbell, I. (Ian), Campbell, P. T. (Peter T.), Cancel-Tassin, G. (Geraldine), Cannon-Albright, L. (Lisa), Campa, D. (Daniele), Caporaso, N. (Neil), Carvalho, A. L. (Andre L.), Chan, A. T. (Andrew T.), Chang-Claude, J. (Jenny), Chanock, S. J. (Stephen J.), Chen, C. (Chu), Christiani, D. C. (David C.), Claes, K. B. (Kathleen B. M.), Claessens, F. (Frank), Clements, J. (Judith), Collee, J. M. (J. Margriet), Correa, M. C. (Marcia Cruz), Couch, F. J. (Fergus J.), Cox, A. (Angela), Cunningham, J. M. (Julie M.), Cybulski, C. (Cezary), Czene, K. (Kamila), Daly, M. B. (Mary B.), defazio, A. (Anna), Devilee, P. (Peter), Diez, O. (Orland), Gago-Dominguez, M. (Manuela), Donovan, J. L. (Jenny L.), Doerk, T. (Thilo), Duell, E. J. (Eric J.), Dunning, A. M. (Alison M.), Dwek, M. (Miriam), Eccles, D. M. (Diana M.), Edlund, C. K. (Christopher K.), Edwards, D. R. (Digna R. Velez), Ellberg, C. (Carolina), Evans, D. G. (D. Gareth), Fasching, P. A. (Peter A.), Ferris, R. L. (Robert L.), Liloglou, T. (Triantafillos), Figueiredo, J. C. (Jane C.), Fletcher, O. (Olivia), Fortner, R. T. (Renee T.), Fostira, F. (Florentia), Franceschi, S. (Silvia), Friedman, E. (Eitan), Gallinger, S. J. (Steven J.), Ganz, P. A. (Patricia A.), Garber, J. (Judy), Garcia-Saenz, J. A. (Jose A.), Gayther, S. A. (Simon A.), Giles, G. G. (Graham G.), Godwin, A. K. (Andrew K.), Goldberg, M. S. (Mark S.), Goldgar, D. E. (David E.), Goode, E. L. (Ellen L.), Goodman, M. T. (Marc T.), Goodman, G. (Gary), Grankvist, K. (Kjell), Greene, M. H. (Mark H.), Gronberg, H. (Henrik), Gronwald, J. (Jacek), Guenel, P. (Pascal), Hakansson, N. (Niclas), Hall, P. (Per), Hamann, U. (Ute), Hamdy, F. C. (Freddie C.), Hamilton, R. J. (Robert J.), Hampe, J. (Jochen), Haugen, A. (Aage), Heitz, F. (Florian), Herrero, R. (Rolando), Hillemanns, P. (Peter), Hoffmeister, M. (Michael), Hogdall, E. (Estrid), Hong, Y.-C. (Yun-Chul), Hopper, J. L. (John L.), Houlston, R. (Richard), Hulick, P. J. (Peter J.), Hunter, D. J. (David J.), Huntsman, D. G. (David G.), Idos, G. (Gregory), Imyanitov, E. N. (Evgeny N.), Ingles, S. A. (Sue Ann), Isaacs, C. (Claudine), Jakubowska, A. (Anna), James, P. (Paul), Jenkins, M. A. (Mark A.), Johansson, M. (Mattias), Johansson, M. (Mikael), John, E. M. (Esther M.), Joshi, A. D. (Amit D.), Kaneva, R. (Radka), Karlan, B. Y. (Beth Y.), Kelemen, L. E. (Linda E.), Kuhl, T. (Tabea), Khaw, K.-T. (Kay-Tee), Khusnutdinova, E. (Elza), Kibel, A. S. (Adam S.), Kiemeney, L. A. (Lambertus A.), Kim, J. (Jeri), Kjaer, S. K. (Susanne K.), Knight, J. A. (Julia A.), Kogevinas, M. (Manolis), Kote-Jarai, Z. (Zsofia), Koutros, S. (Stella), Kristensen, V. N. (Vessela N.), Kupryjanczyk, J. (Jolanta), Lacko, M. (Martin), Lam, S. (Stephan), Lambrechts, D. (Diether), Landi, M. T. (Maria Teresa), Lazarus, P. (Philip), Le, N. D. (Nhu D.), Lee, E. (Eunjung), Lejbkowicz, F. (Flavio), Lenz, H.-J. (Heinz-Josef), Leslie, G. (Goska), Lessel, D. (Davor), Lester, J. (Jenny), Levine, D. A. (Douglas A.), Li, L. (Li), Li, C. I. (Christopher I.), Lindblom, A. (Annika), Lindor, N. M. (Noralane M.), Liu, G. (Geoffrey), Loupakis, F. (Fotios), Lubinski, J. (Jan), Maehle, L. (Lovise), Maier, C. (Christiane), Mannermaa, A. (Arto), Le Marchand, L. (Loic), Margolin, S. (Sara), May, T. (Taymaa), McGuffog, L. (Lesley), Meindl, A. (Alfons), Middha, P. (Pooja), Miller, A. (Austin), Milne, R. L. (Roger L.), MacInnis, R. J. (Robert J.), Modugno, F. (Francesmary), Montagna, M. (Marco), Moreno, V. (Victor), Moysich, K. B. (Kirsten B.), Mucci, L. (Lorelei), Muir, K. (Kenneth), Mulligan, A. M. (Anna Marie), Nathanson, K. L. (Katherine L.), Neal, D. E. (David E.), Ness, A. R. (Andrew R.), Neuhausen, S. L. (Susan L.), Nevanlinna, H. (Heli), Newcomb, P. A. (Polly A.), Newcomb, L. F. (Lisa F.), Nielsen, F. C. (Finn Cilius), Nikitina-Zake, L. (Liene), Nordestgaard, B. G. (Borge G.), Nussbaum, R. L. (Robert L.), Offit, K. (Kenneth), Olah, E. (Edith), Al Olama, A. A. (Ali Amin), Olopade, O. I. (Olufunmilayo I.), Olshan, A. F. (Andrew F.), Olsson, H. (Hakan), Osorio, A. (Ana), Pandha, H. (Hardev), Park, J. Y. (Jong Y.), Pashayan, N. (Nora), Parsons, M. T. (Michael T.), Pejovic, T. (Tanja), Penney, K. L. (Kathryn L.), Peters, W. H. (Wilbert H. M.), Phelan, C. M. (Catherine M.), Phipps, A. I. (Amanda I.), Plaseska-Karanfilska, D. (Dijana), Pring, M. (Miranda), Prokofyeva, D. (Darya), Radice, P. (Paolo), Stefansson, K. (Kari), Ramus, S. J. (Susan J.), Raskin, L. (Leon), Rennert, G. (Gad), Rennert, H. S. (Hedy S.), van Rensburg, E. J. (Elizabeth J.), Riggan, M. J. (Marjorie J.), Risch, H. A. (Harvey A.), Risch, A. (Angela), Roobol, M. J. (Monique J.), Rosenstein, B. S. (Barry S.), Rossing, M. A. (Mary Anne), De Ruyck, K. (Kim), Saloustros, E. (Emmanouil), Sandler, D. P. (Dale P.), Sawyer, E. J. (Elinor J.), Schabath, M. B. (Matthew B.), Schleutker, J. (Johanna), Schmidt, M. K. (Marjanka K.), Setiawan, V. W. (V. Wendy), Shen, H. (Hongbing), Siegel, E. M. (Erin M.), Sieh, W. (Weiva), Singer, C. F. (Christian F.), Slattery, M. L. (Martha L.), Sorensen, K. D. (Karina Dalsgaard), Southey, M. C. (Melissa C.), Spurdle, A. B. (Amanda B.), Stanford, J. L. (Janet L.), Stevens, V. L. (Victoria L.), Stintzing, S. (Sebastian), Stone, J. (Jennifer), Sundfeldt, K. (Karin), Sutphen, R. (Rebecca), Swerdlow, A. J. (Anthony J.), Tajara, E. H. (Eloiza H.), Tangen, C. M. (Catherine M.), Tardon, A. (Adonina), Taylor, J. A. (Jack A.), Teare, M. D. (M. Dawn), Teixeira, M. R. (Manuel R.), Terry, M. B. (Mary Beth), Terry, K. L. (Kathryn L.), Thibodeau, S. N. (Stephen N.), Thomassen, M. (Mads), Bjorge, L. (Line), Tischkowitz, M. (Marc), Toland, A. E. (Amanda E.), Torres, D. (Diana), Townsend, P. A. (Paul A.), Travis, R. C. (Ruth C.), Tung, N. (Nadine), Tworoger, S. S. (Shelley S.), Ulrich, C. M. (Cornelia M.), Usmani, N. (Nawaid), Vachon, C. M. (Celine M.), Van Nieuwenhuysen, E. (Els), Vega, A. (Ana), Aguado-Barrera, M. E. (Miguel Elias), Wang, Q. (Qin), Webb, P. M. (Penelope M.), Weinberg, C. R. (Clarice R.), Weinstein, S. (Stephanie), Weissler, M. C. (Mark C.), Weitzel, J. N. (Jeffrey N.), West, C. M. (Catharine M. L.), White, E. (Emily), Whittemore, A. S. (Alice S.), Wichmann, H.-E. (H-Erich), Wiklund, F. (Fredrik), Winqvist, R. (Robert), Wolk, A. (Alicja), Woll, P. (Penella), Woods, M. (Michael), Wu, A. H. (Anna H.), Wu, X. (Xifeng), Yannoukakos, D. (Drakoulis), Zheng, W. (Wei), Zienolddiny, S. (Shanbeh), Ziogas, A. (Argyrios), Zorn, K. K. (Kristin K.), Lane, J. M. (Jacqueline M.), Saxena, R. (Richa), Thomas, D. (Duncan), Hung, R. J. (Rayjean J.), Diergaarde, B. (Brenda), Mckay, J. (James), Peters, U. (Ulrike), Hsu, L. (Li), Garcia-Closas, M. (Montserrat), Eeles, R. A. (Rosalind A.), Chenevix-Trench, G. (Georgia), Brennan, P. J. (Paul J.), Haiman, C. A. (Christopher A.), Simard, J. (Jacques), Easton, D. F. (Douglas F.), Gruber, S. B. (Stephen B.), Pharoah, P. D. (Paul D. P.), Price, A. L. (Alkes L.), Pasaniuc, B. (Bogdan), Amos, C. I. (Christopher I.), Kraft, P. (Peter), Lindstrom, S. (Sara), Jiang, X. (Xia), Finucane, H. K. (Hilary K.), Schumacher, F. R. (Fredrick R.), Schmit, S. L. (Stephanie L.), Tyrer, J. P. (Jonathan P.), Han, Y. (Younghun), Michailidou, K. (Kyriaki), Lesseur, C. (Corina), Kuchenbaecker, K. B. (Karoline B.), Dennis, J. (Joe), Conti, D. V. (David V.), Casey, G. (Graham), Gaudet, M. M. (Mia M.), Huyghe, J. R. (Jeroen R.), Albanes, D. (Demetrius), Aldrich, M. C. (Melinda C.), Andrew, A. S. (Angeline S.), Andrulis, I. L. (Irene L.), Anton-Culver, H. (Hoda), Antoniou, A. C. (Antonis C.), Antonenkova, N. N. (Natalia N.), Arnold, S. M. (Susanne M.), Aronson, K. J. (Kristan J.), Arun, B. K. (Banu K.), Bandera, E. V. (Elisa V.), Barkardottir, R. B. (Rosa B.), Barnes, D. R. (Daniel R.), Batra, J. (Jyotsna), Beckmann, M. W. (Matthias W.), Benitez, J. (Javier), Benlloch, S. (Sara), Berchuck, A. (Andrew), Berndt, S. I. (Sonja I.), Bickeboeller, H. (Heike), Bien, S. A. (Stephanie A.), Blomqvist, C. (Carl), Boccia, S. (Stefania), Bogdanova, N. V. (Natalia V.), Bojesen, S. E. (Stig E.), Bolla, M. K. (Manjeet K.), Brauch, H. (Hiltrud), Brenner, H. (Hermann), Brenton, J. D. (James D.), Brook, M. N. (Mark N.), Brunet, J. (Joan), Brunnstrom, H. (Hans), Buchanan, D. D. (Daniel D.), Burwinkel, B. (Barbara), Butzow, R. (Ralf), Cadoni, G. (Gabriella), Caldes, T. (Trinidad), Caligo, M. A. (Maria A.), Campbell, I. (Ian), Campbell, P. T. (Peter T.), Cancel-Tassin, G. (Geraldine), Cannon-Albright, L. (Lisa), Campa, D. (Daniele), Caporaso, N. (Neil), Carvalho, A. L. (Andre L.), Chan, A. T. (Andrew T.), Chang-Claude, J. (Jenny), Chanock, S. J. (Stephen J.), Chen, C. (Chu), Christiani, D. C. (David C.), Claes, K. B. (Kathleen B. M.), Claessens, F. (Frank), Clements, J. (Judith), Collee, J. M. (J. Margriet), Correa, M. C. (Marcia Cruz), Couch, F. J. (Fergus J.), Cox, A. (Angela), Cunningham, J. M. (Julie M.), Cybulski, C. (Cezary), Czene, K. (Kamila), Daly, M. B. (Mary B.), defazio, A. (Anna), Devilee, P. (Peter), Diez, O. (Orland), Gago-Dominguez, M. (Manuela), Donovan, J. L. (Jenny L.), Doerk, T. (Thilo), Duell, E. J. (Eric J.), Dunning, A. M. (Alison M.), Dwek, M. (Miriam), Eccles, D. M. (Diana M.), Edlund, C. K. (Christopher K.), Edwards, D. R. (Digna R. Velez), Ellberg, C. (Carolina), Evans, D. G. (D. Gareth), Fasching, P. A. (Peter A.), Ferris, R. L. (Robert L.), Liloglou, T. (Triantafillos), Figueiredo, J. C. (Jane C.), Fletcher, O. (Olivia), Fortner, R. T. (Renee T.), Fostira, F. (Florentia), Franceschi, S. (Silvia), Friedman, E. (Eitan), Gallinger, S. J. (Steven J.), Ganz, P. A. (Patricia A.), Garber, J. (Judy), Garcia-Saenz, J. A. (Jose A.), Gayther, S. A. (Simon A.), Giles, G. G. (Graham G.), Godwin, A. K. (Andrew K.), Goldberg, M. S. (Mark S.), Goldgar, D. E. (David E.), Goode, E. L. (Ellen L.), Goodman, M. T. (Marc T.), Goodman, G. (Gary), Grankvist, K. (Kjell), Greene, M. H. (Mark H.), Gronberg, H. (Henrik), Gronwald, J. (Jacek), Guenel, P. (Pascal), Hakansson, N. (Niclas), Hall, P. (Per), Hamann, U. (Ute), Hamdy, F. C. (Freddie C.), Hamilton, R. J. (Robert J.), Hampe, J. (Jochen), Haugen, A. (Aage), Heitz, F. (Florian), Herrero, R. (Rolando), Hillemanns, P. (Peter), Hoffmeister, M. (Michael), Hogdall, E. (Estrid), Hong, Y.-C. (Yun-Chul), Hopper, J. L. (John L.), Houlston, R. (Richard), Hulick, P. J. (Peter J.), Hunter, D. J. (David J.), Huntsman, D. G. (David G.), Idos, G. (Gregory), Imyanitov, E. N. (Evgeny N.), Ingles, S. A. (Sue Ann), Isaacs, C. (Claudine), Jakubowska, A. (Anna), James, P. (Paul), Jenkins, M. A. (Mark A.), Johansson, M. (Mattias), Johansson, M. (Mikael), John, E. M. (Esther M.), Joshi, A. D. (Amit D.), Kaneva, R. (Radka), Karlan, B. Y. (Beth Y.), Kelemen, L. E. (Linda E.), Kuhl, T. (Tabea), Khaw, K.-T. (Kay-Tee), Khusnutdinova, E. (Elza), Kibel, A. S. (Adam S.), Kiemeney, L. A. (Lambertus A.), Kim, J. (Jeri), Kjaer, S. K. (Susanne K.), Knight, J. A. (Julia A.), Kogevinas, M. (Manolis), Kote-Jarai, Z. (Zsofia), Koutros, S. (Stella), Kristensen, V. N. (Vessela N.), Kupryjanczyk, J. (Jolanta), Lacko, M. (Martin), Lam, S. (Stephan), Lambrechts, D. (Diether), Landi, M. T. (Maria Teresa), Lazarus, P. (Philip), Le, N. D. (Nhu D.), Lee, E. (Eunjung), Lejbkowicz, F. (Flavio), Lenz, H.-J. (Heinz-Josef), Leslie, G. (Goska), Lessel, D. (Davor), Lester, J. (Jenny), Levine, D. A. (Douglas A.), Li, L. (Li), Li, C. I. (Christopher I.), Lindblom, A. (Annika), Lindor, N. M. (Noralane M.), Liu, G. (Geoffrey), Loupakis, F. (Fotios), Lubinski, J. (Jan), Maehle, L. (Lovise), Maier, C. (Christiane), Mannermaa, A. (Arto), Le Marchand, L. (Loic), Margolin, S. (Sara), May, T. (Taymaa), McGuffog, L. (Lesley), Meindl, A. (Alfons), Middha, P. (Pooja), Miller, A. (Austin), Milne, R. L. (Roger L.), MacInnis, R. J. (Robert J.), Modugno, F. (Francesmary), Montagna, M. (Marco), Moreno, V. (Victor), Moysich, K. B. (Kirsten B.), Mucci, L. (Lorelei), Muir, K. (Kenneth), Mulligan, A. M. (Anna Marie), Nathanson, K. L. (Katherine L.), Neal, D. E. (David E.), Ness, A. R. (Andrew R.), Neuhausen, S. L. (Susan L.), Nevanlinna, H. (Heli), Newcomb, P. A. (Polly A.), Newcomb, L. F. (Lisa F.), Nielsen, F. C. (Finn Cilius), Nikitina-Zake, L. (Liene), Nordestgaard, B. G. (Borge G.), Nussbaum, R. L. (Robert L.), Offit, K. (Kenneth), Olah, E. (Edith), Al Olama, A. A. (Ali Amin), Olopade, O. I. (Olufunmilayo I.), Olshan, A. F. (Andrew F.), Olsson, H. (Hakan), Osorio, A. (Ana), Pandha, H. (Hardev), Park, J. Y. (Jong Y.), Pashayan, N. (Nora), Parsons, M. T. (Michael T.), Pejovic, T. (Tanja), Penney, K. L. (Kathryn L.), Peters, W. H. (Wilbert H. M.), Phelan, C. M. (Catherine M.), Phipps, A. I. (Amanda I.), Plaseska-Karanfilska, D. (Dijana), Pring, M. (Miranda), Prokofyeva, D. (Darya), Radice, P. (Paolo), Stefansson, K. (Kari), Ramus, S. J. (Susan J.), Raskin, L. (Leon), Rennert, G. (Gad), Rennert, H. S. (Hedy S.), van Rensburg, E. J. (Elizabeth J.), Riggan, M. J. (Marjorie J.), Risch, H. A. (Harvey A.), Risch, A. (Angela), Roobol, M. J. (Monique J.), Rosenstein, B. S. (Barry S.), Rossing, M. A. (Mary Anne), De Ruyck, K. (Kim), Saloustros, E. (Emmanouil), Sandler, D. P. (Dale P.), Sawyer, E. J. (Elinor J.), Schabath, M. B. (Matthew B.), Schleutker, J. (Johanna), Schmidt, M. K. (Marjanka K.), Setiawan, V. W. (V. Wendy), Shen, H. (Hongbing), Siegel, E. M. (Erin M.), Sieh, W. (Weiva), Singer, C. F. (Christian F.), Slattery, M. L. (Martha L.), Sorensen, K. D. (Karina Dalsgaard), Southey, M. C. (Melissa C.), Spurdle, A. B. (Amanda B.), Stanford, J. L. (Janet L.), Stevens, V. L. (Victoria L.), Stintzing, S. (Sebastian), Stone, J. (Jennifer), Sundfeldt, K. (Karin), Sutphen, R. (Rebecca), Swerdlow, A. J. (Anthony J.), Tajara, E. H. (Eloiza H.), Tangen, C. M. (Catherine M.), Tardon, A. (Adonina), Taylor, J. A. (Jack A.), Teare, M. D. (M. Dawn), Teixeira, M. R. (Manuel R.), Terry, M. B. (Mary Beth), Terry, K. L. (Kathryn L.), Thibodeau, S. N. (Stephen N.), Thomassen, M. (Mads), Bjorge, L. (Line), Tischkowitz, M. (Marc), Toland, A. E. (Amanda E.), Torres, D. (Diana), Townsend, P. A. (Paul A.), Travis, R. C. (Ruth C.), Tung, N. (Nadine), Tworoger, S. S. (Shelley S.), Ulrich, C. M. (Cornelia M.), Usmani, N. (Nawaid), Vachon, C. M. (Celine M.), Van Nieuwenhuysen, E. (Els), Vega, A. (Ana), Aguado-Barrera, M. E. (Miguel Elias), Wang, Q. (Qin), Webb, P. M. (Penelope M.), Weinberg, C. R. (Clarice R.), Weinstein, S. (Stephanie), Weissler, M. C. (Mark C.), Weitzel, J. N. (Jeffrey N.), West, C. M. (Catharine M. L.), White, E. (Emily), Whittemore, A. S. (Alice S.), Wichmann, H.-E. (H-Erich), Wiklund, F. (Fredrik), Winqvist, R. (Robert), Wolk, A. (Alicja), Woll, P. (Penella), Woods, M. (Michael), Wu, A. H. (Anna H.), Wu, X. (Xifeng), Yannoukakos, D. (Drakoulis), Zheng, W. (Wei), Zienolddiny, S. (Shanbeh), Ziogas, A. (Argyrios), Zorn, K. K. (Kristin K.), Lane, J. M. (Jacqueline M.), Saxena, R. (Richa), Thomas, D. (Duncan), Hung, R. J. (Rayjean J.), Diergaarde, B. (Brenda), Mckay, J. (James), Peters, U. (Ulrike), Hsu, L. (Li), Garcia-Closas, M. (Montserrat), Eeles, R. A. (Rosalind A.), Chenevix-Trench, G. (Georgia), Brennan, P. J. (Paul J.), Haiman, C. A. (Christopher A.), Simard, J. (Jacques), Easton, D. F. (Douglas F.), Gruber, S. B. (Stephen B.), Pharoah, P. D. (Paul D. P.), Price, A. L. (Alkes L.), Pasaniuc, B. (Bogdan), Amos, C. I. (Christopher I.), Kraft, P. (Peter), and Lindstrom, S. (Sara)
Abstract: Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
Published: 2019

13. Hydroponically grown sanguisorba minor scop.: Effects of cut and storage on fresh-cut produce

Author: Ceccanti, C., Landi, M., Rocchetti, G., Miras-Moreno, M. B., Lucini, L., Incrocci, L., Pardossi, A., Guidi, L., Rocchetti G. (ORCID:0000-0003-3488-4513), Miras-Moreno M. B. (ORCID:0000-0002-5931-355X), Lucini L. (ORCID:0000-0002-5133-9464), Ceccanti, C., Landi, M., Rocchetti, G., Miras-Moreno, M. B., Lucini, L., Incrocci, L., Pardossi, A., Guidi, L., Rocchetti G. (ORCID:0000-0003-3488-4513), Miras-Moreno M. B. (ORCID:0000-0002-5931-355X), and Lucini L. (ORCID:0000-0002-5133-9464)
Abstract: Wild edible plants have been used in cooking since ancient times. Recently, their value has improved as a result of the scientific evidence for their nutraceutical properties. Sanguisorba minor Scop. (salad burnet) plants were hydroponically grown and two consecutive cuts took place at 15 (C1) and 30 (C2) days after sowing. An untargeted metabolomics approach was utilized to fingerprint phenolics and other health-related compounds in this species; this approach revealed the different effects of the two cuts on the plant. S. minor showed a different and complex secondary metabolite profile, which was influenced by the cut. In fact, flavonoids increased in leaves obtained from C2, especially flavones. However, other secondary metabolites were downregulated in leaves from C2 compared to those detected in leaves from C1, as evidenced by the combination of the variable important in projections (VIP score > 1.3) and the fold-change (FC > 2). The storage of S. minor leaves for 15 days as fresh-cut products did not induce significant changes in the phenolic content and antioxidant capacity, which indicates that the nutraceutical value was maintained. The only difference evidenced during storage was that leaves obtained from C2 showed a lower constitutive content of nutraceutical compounds than leaves obtained from C1; except for chlorophylls and carotenoids. In conclusion, the cut was the main influence on the modulation of secondary metabolites in leaves, and the effects were independent of storage.
Published: 2019

14. Publisher Correction: Shared heritability and functional enrichment across six solid cancers (Nature Communications, (2019), 10, 1, (431), 10.1038/s41467-018-08054-4)

Author: Jiang, X., Finucane, H. K., Schumacher, F. R., Schmit, S. L., Tyrer, J. P., Han, Y., Michailidou, K., Lesseur, C., Kuchenbaecker, K. B., Dennis, J., Conti, D. V., Casey, G., Gaudet, M. M., Huyghe, J. R., Albanes, D., Aldrich, M. C., Andrew, A. S., Andrulis, I. L., Anton-Culver, H., Antoniou, A. C., Antonenkova, N. N., Arnold, S. M., Aronson, K. J., Arun, B. K., Bandera, E. V., Barkardottir, R. B., Barnes, D. R., Batra, J., Beckmann, M. W., Benitez, J., Benlloch, S., Berchuck, A., Berndt, S. I., Bickeboller, H., Bien, S. A., Blomqvist, C., Boccia, S., Bogdanova, N. V., Bojesen, S. E., Bolla, M. K., Brauch, H., Brenner, H., Brenton, J. D., Brook, M. N., Brunet, J., Brunnstrom, H., Buchanan, D. D., Burwinkel, B., Butzow, R., Cadoni, G., Caldes, T., Caligo, M. A., Campbell, I., Campbell, P. T., Cancel-Tassin, G., Cannon-Albright, L., Campa, D., Caporaso, N., Carvalho, A. L., Chan, A. T., Chang-Claude, J., Chanock, S. J., Chen, Chen, Christiani, D. C., Claes, K. B. M., Claessens, F., Clements, J., Collee, J. M., Correa, M. C., Couch, F. J., Cox, A., Cunningham, J. M., Cybulski, C., Czene, K., Daly, M. B., deFazio, A., Devilee, P., Diez, O., Gago-Dominguez, M., Donovan, J. L., Dork, T., Duell, E. J., Dunning, A. M., Dwek, M., Eccles, D. M., Edlund, C. K., Edwards, D. R. V., Ellberg, C., Evans, D. G., Fasching, P. A., Ferris, R. L., Liloglou, T., Figueiredo, J. C., Fletcher, O., Fortner, R. T., Fostira, F., Franceschi, S., Friedman, E., Gallinger, S. J., Ganz, P. A., Garber, J., Garcia-Saenz, J. A., Gayther, S. A., Giles, G. G., Godwin, A. K., Goldberg, M. S., Goldgar, D. E., Goode, E. L., Goodman, M. T., Goodman, G., Grankvist, K., Greene, M. H., Gronberg, H., Gronwald, J., Guenel, P., Hakansson, N., Hall, P., Hamann, U., Hamdy, F. C., Hamilton, R. J., Hampe, J., Haugen, A., Heitz, F., Herrero, R., Hillemanns, P., Hoffmeister, M., Hogdall, E., Hong, Y. -C., Hopper, J. L., Houlston, R., Hulick, P. J., Hunter, D. J., Huntsman, D. G., Idos, G., Imyanitov, E. N., Ingles, S. A., Isaacs, C., Jakubowska, A., James, P., Jenkins, M. A., Johansson, M., John, E. M., Joshi, A. D., Kaneva, R., Karlan, B. Y., Kelemen, L. E., Kuhl, T., Khaw, K. -T., Khusnutdinova, E., Kibel, A. S., Kiemeney, L. A., Kim, J., Kjaer, S. K., Knight, J. A., Kogevinas, M., Kote-Jarai, Z., Koutros, S., Kristensen, V. N., Kupryjanczyk, J., Lacko, M., Lam, S., Lambrechts, D., Landi, M. T., Lazarus, P., Le, N. D., Lee, E., Lejbkowicz, F., Lenz, H. -J., Leslie, G., Lessel, D., Lester, J., Levine, D. A., Li, L., Li, C. I., Lindblom, A., Lindor, N. M., Liu, G., Loupakis, F., Lubinski, J., Maehle, L., Maier, C., Mannermaa, A., Marchand, L. L., Margolin, S., May, T., McGuffog, L., Meindl, A., Middha, P., Miller, A., Milne, R. L., MacInnis, R. J., Modugno, F., Montagna, M., Moreno, V., Moysich, K. B., Mucci, L., Muir, K., Mulligan, A. M., Nathanson, K. L., Neal, D. E., Ness, A. R., Neuhausen, S. L., Nevanlinna, H., Newcomb, P. A., Newcomb, L. F., Nielsen, F. C., Nikitina-Zake, L., Nordestgaard, B. G., Nussbaum, R. L., Offit, K., Olah, E., Olama, A. A. A., Olopade, O. I., Olshan, A. F., Olsson, H., Osorio, A., Pandha, H., Park, J. Y., Pashayan, N., Parsons, M. T., Pejovic, T., Penney, K. L., Peters, W. H. M., Phelan, C. M., Phipps, A. I., Plaseska-Karanfilska, D., Pring, M., Prokofyeva, D., Radice, P., Stefansson, K., Ramus, S. J., Raskin, L., Rennert, G., Rennert, H. S., van Rensburg, E. J., Riggan, M. J., Risch, H. A., Risch, A., Roobol, M. J., Rosenstein, B. S., Rossing, M. A., De Ruyck, K., Saloustros, E., Sandler, D. P., Sawyer, E. J., Schabath, M. B., Schleutker, J., Schmidt, M. K., Setiawan, V. W., Shen, H., Siegel, E. M., Sieh, W., Singer, C. F., Slattery, M. L., Sorensen, K. D., Southey, M. C., Spurdle, A. B., Stanford, J. L., Stevens, V. L., Stintzing, S., Stone, J., Sundfeldt, K., Sutphen, R., Swerdlow, A. J., Tajara, E. H., Tangen, C. M., Tardon, A., Taylor, J. A., Teare, M. D., Teixeira, M. R., Terry, M. B., Terry, K. L., Thibodeau, S. N., Thomassen, M., Bjorge, L., Tischkowitz, M., Toland, A. E., Torres, D., Townsend, P. A., Travis, R. C., Tung, N., Tworoger, S. S., Ulrich, C. M., Usmani, N., Vachon, C. M., Van Nieuwenhuysen, E., Vega, A., Aguado-Barrera, M. E., Wang, Q., Webb, P. M., Weinberg, C. R., Weinstein, S., Weissler, M. C., Weitzel, J. N., West, C. M. L., White, E., Whittemore, A. S., Wichmann, H. -E., Wiklund, F., Winqvist, R., Wolk, A., Woll, P., Woods, M., Wu, A. H., Wu, X., Yannoukakos, D., Zheng, W., Zienolddiny, S., Ziogas, A., Zorn, K. K., Lane, J. M., Saxena, R., Thomas, D., Hung, R. J., Diergaarde, B., McKay, J., Peters, U., Hsu, L., Garcia-Closas, M., Eeles, R. A., Chenevix-Trench, G., Brennan, P. J., Haiman, C. A., Simard, J., Easton, D. F., Gruber, S. B., Pharoah, P. D. P., Price, A. L., Pasaniuc, B., Amos, C. I., Kraft, P., Lindstrom, S., Boccia S. (ORCID:0000-0002-1864-749X), Cadoni G. (ORCID:0000-0001-8244-784X), Chen C., Liu G., Wang Q., Jiang, X., Finucane, H. K., Schumacher, F. R., Schmit, S. L., Tyrer, J. P., Han, Y., Michailidou, K., Lesseur, C., Kuchenbaecker, K. B., Dennis, J., Conti, D. V., Casey, G., Gaudet, M. M., Huyghe, J. R., Albanes, D., Aldrich, M. C., Andrew, A. S., Andrulis, I. L., Anton-Culver, H., Antoniou, A. C., Antonenkova, N. N., Arnold, S. M., Aronson, K. J., Arun, B. K., Bandera, E. V., Barkardottir, R. B., Barnes, D. R., Batra, J., Beckmann, M. W., Benitez, J., Benlloch, S., Berchuck, A., Berndt, S. I., Bickeboller, H., Bien, S. A., Blomqvist, C., Boccia, S., Bogdanova, N. V., Bojesen, S. E., Bolla, M. K., Brauch, H., Brenner, H., Brenton, J. D., Brook, M. N., Brunet, J., Brunnstrom, H., Buchanan, D. D., Burwinkel, B., Butzow, R., Cadoni, G., Caldes, T., Caligo, M. A., Campbell, I., Campbell, P. T., Cancel-Tassin, G., Cannon-Albright, L., Campa, D., Caporaso, N., Carvalho, A. L., Chan, A. T., Chang-Claude, J., Chanock, S. J., Chen, Chen, Christiani, D. C., Claes, K. B. M., Claessens, F., Clements, J., Collee, J. M., Correa, M. C., Couch, F. J., Cox, A., Cunningham, J. M., Cybulski, C., Czene, K., Daly, M. B., deFazio, A., Devilee, P., Diez, O., Gago-Dominguez, M., Donovan, J. L., Dork, T., Duell, E. J., Dunning, A. M., Dwek, M., Eccles, D. M., Edlund, C. K., Edwards, D. R. V., Ellberg, C., Evans, D. G., Fasching, P. A., Ferris, R. L., Liloglou, T., Figueiredo, J. C., Fletcher, O., Fortner, R. T., Fostira, F., Franceschi, S., Friedman, E., Gallinger, S. J., Ganz, P. A., Garber, J., Garcia-Saenz, J. A., Gayther, S. A., Giles, G. G., Godwin, A. K., Goldberg, M. S., Goldgar, D. E., Goode, E. L., Goodman, M. T., Goodman, G., Grankvist, K., Greene, M. H., Gronberg, H., Gronwald, J., Guenel, P., Hakansson, N., Hall, P., Hamann, U., Hamdy, F. C., Hamilton, R. J., Hampe, J., Haugen, A., Heitz, F., Herrero, R., Hillemanns, P., Hoffmeister, M., Hogdall, E., Hong, Y. -C., Hopper, J. L., Houlston, R., Hulick, P. J., Hunter, D. J., Huntsman, D. G., Idos, G., Imyanitov, E. N., Ingles, S. A., Isaacs, C., Jakubowska, A., James, P., Jenkins, M. A., Johansson, M., John, E. M., Joshi, A. D., Kaneva, R., Karlan, B. Y., Kelemen, L. E., Kuhl, T., Khaw, K. -T., Khusnutdinova, E., Kibel, A. S., Kiemeney, L. A., Kim, J., Kjaer, S. K., Knight, J. A., Kogevinas, M., Kote-Jarai, Z., Koutros, S., Kristensen, V. N., Kupryjanczyk, J., Lacko, M., Lam, S., Lambrechts, D., Landi, M. T., Lazarus, P., Le, N. D., Lee, E., Lejbkowicz, F., Lenz, H. -J., Leslie, G., Lessel, D., Lester, J., Levine, D. A., Li, L., Li, C. I., Lindblom, A., Lindor, N. M., Liu, G., Loupakis, F., Lubinski, J., Maehle, L., Maier, C., Mannermaa, A., Marchand, L. L., Margolin, S., May, T., McGuffog, L., Meindl, A., Middha, P., Miller, A., Milne, R. L., MacInnis, R. J., Modugno, F., Montagna, M., Moreno, V., Moysich, K. B., Mucci, L., Muir, K., Mulligan, A. M., Nathanson, K. L., Neal, D. E., Ness, A. R., Neuhausen, S. L., Nevanlinna, H., Newcomb, P. A., Newcomb, L. F., Nielsen, F. C., Nikitina-Zake, L., Nordestgaard, B. G., Nussbaum, R. L., Offit, K., Olah, E., Olama, A. A. A., Olopade, O. I., Olshan, A. F., Olsson, H., Osorio, A., Pandha, H., Park, J. Y., Pashayan, N., Parsons, M. T., Pejovic, T., Penney, K. L., Peters, W. H. M., Phelan, C. M., Phipps, A. I., Plaseska-Karanfilska, D., Pring, M., Prokofyeva, D., Radice, P., Stefansson, K., Ramus, S. J., Raskin, L., Rennert, G., Rennert, H. S., van Rensburg, E. J., Riggan, M. J., Risch, H. A., Risch, A., Roobol, M. J., Rosenstein, B. S., Rossing, M. A., De Ruyck, K., Saloustros, E., Sandler, D. P., Sawyer, E. J., Schabath, M. B., Schleutker, J., Schmidt, M. K., Setiawan, V. W., Shen, H., Siegel, E. M., Sieh, W., Singer, C. F., Slattery, M. L., Sorensen, K. D., Southey, M. C., Spurdle, A. B., Stanford, J. L., Stevens, V. L., Stintzing, S., Stone, J., Sundfeldt, K., Sutphen, R., Swerdlow, A. J., Tajara, E. H., Tangen, C. M., Tardon, A., Taylor, J. A., Teare, M. D., Teixeira, M. R., Terry, M. B., Terry, K. L., Thibodeau, S. N., Thomassen, M., Bjorge, L., Tischkowitz, M., Toland, A. E., Torres, D., Townsend, P. A., Travis, R. C., Tung, N., Tworoger, S. S., Ulrich, C. M., Usmani, N., Vachon, C. M., Van Nieuwenhuysen, E., Vega, A., Aguado-Barrera, M. E., Wang, Q., Webb, P. M., Weinberg, C. R., Weinstein, S., Weissler, M. C., Weitzel, J. N., West, C. M. L., White, E., Whittemore, A. S., Wichmann, H. -E., Wiklund, F., Winqvist, R., Wolk, A., Woll, P., Woods, M., Wu, A. H., Wu, X., Yannoukakos, D., Zheng, W., Zienolddiny, S., Ziogas, A., Zorn, K. K., Lane, J. M., Saxena, R., Thomas, D., Hung, R. J., Diergaarde, B., McKay, J., Peters, U., Hsu, L., Garcia-Closas, M., Eeles, R. A., Chenevix-Trench, G., Brennan, P. J., Haiman, C. A., Simard, J., Easton, D. F., Gruber, S. B., Pharoah, P. D. P., Price, A. L., Pasaniuc, B., Amos, C. I., Kraft, P., Lindstrom, S., Boccia S. (ORCID:0000-0002-1864-749X), Cadoni G. (ORCID:0000-0001-8244-784X), Chen C., Liu G., and Wang Q.
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2019

15. Contribution of common genetic variants to familial aggregation of disease and implications for sequencing studies

Author: Schlafly, A., Pfeiffer, R. M., Nagore, E., Puig, S., Calista, D., Ghiorzo, P., Menin, C., Fargnoli, Maria Concetta, Peris, Ketty, Song, L., Zhang, T., Shi, J., Landi, M. T., Sampson, J., Fargnoli M. C., Peris K. (ORCID:0000-0002-5237-0463), Schlafly, A., Pfeiffer, R. M., Nagore, E., Puig, S., Calista, D., Ghiorzo, P., Menin, C., Fargnoli, Maria Concetta, Peris, Ketty, Song, L., Zhang, T., Shi, J., Landi, M. T., Sampson, J., Fargnoli M. C., and Peris K. (ORCID:0000-0002-5237-0463)
Abstract: Despite genetics being accepted as the primary cause of familial aggregation for most diseases, it is still unclear whether afflicted families are likely to share a single highly penetrant rare variant, many minimally penetrant common variants, or a combination of the two types of variants. We therefore use recent estimates of SNP heritability and the liability threshold model to estimate the proportion of afflicted families likely to carry a rare, causal variant. We then show that Polygenic Risk Scores (PRS) may be useful for identifying families likely to carry such a rare variant and therefore for prioritizing families to include in sequencing studies with that aim. Specifically, we introduce a new statistic that estimates the proportion of individuals carrying causal rare variants based on the family structure, disease pattern, and PRS of genotyped individuals. Finally, we consider data from the MelaNostrum consortium and show that, despite an estimated PRS heritability of only 0.05 for melanoma, families carrying putative causal variants had a statistically significantly lower PRS, supporting the idea that PRS prioritization may be a useful future tool. However, it will be important to evaluate whether the presence of rare mendelian variants are generally associated with the proposed test statistic or lower PRS in future and larger studies.
Published: 2019

16. Hydroponically grown sanguisorba minor scop.: Effects of cut and storage on fresh-cut produce

Author: Ceccanti, C., Landi, M., Rocchetti, Gabriele, Moreno, M. B. M., Lucini, Luigi, Incrocci, L., Pardossi, A., Guidi, L., Rocchetti G. (ORCID:0000-0003-3488-4513), Lucini L. (ORCID:0000-0002-5133-9464), Ceccanti, C., Landi, M., Rocchetti, Gabriele, Moreno, M. B. M., Lucini, Luigi, Incrocci, L., Pardossi, A., Guidi, L., Rocchetti G. (ORCID:0000-0003-3488-4513), and Lucini L. (ORCID:0000-0002-5133-9464)
Abstract: Wild edible plants have been used in cooking since ancient times. Recently, their value has improved as a result of the scientific evidence for their nutraceutical properties. Sanguisorba minor Scop. (salad burnet) plants were hydroponically grown and two consecutive cuts took place at 15 (C1) and 30 (C2) days after sowing. An untargeted metabolomics approach was utilized to fingerprint phenolics and other health-related compounds in this species; this approach revealed the different effects of the two cuts on the plant. S. minor showed a different and complex secondary metabolite profile, which was influenced by the cut. In fact, flavonoids increased in leaves obtained from C2, especially flavones. However, other secondary metabolites were downregulated in leaves from C2 compared to those detected in leaves from C1, as evidenced by the combination of the variable important in projections (VIP score > 1.3) and the fold-change (FC > 2). The storage of S. minor leaves for 15 days as fresh-cut products did not induce significant changes in the phenolic content and antioxidant capacity, which indicates that the nutraceutical value was maintained. The only difference evidenced during storage was that leaves obtained from C2 showed a lower constitutive content of nutraceutical compounds than leaves obtained from C1; except for chlorophylls and carotenoids. In conclusion, the cut was the main influence on the modulation of secondary metabolites in leaves, and the effects were independent of storage.
Published: 2019

17. Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence

Author: Hancock, D. B., Guo, Y., Reginsson, G. W., Gaddis, N. C., Lutz, S. M., Sherva, R., Loukola, A., Minica, C. C., Markunas, C. A., Han, Y., Young, K. A., Gudbjartsson, D. F., Gu, F., McNeil, D. W., Qaiser, B., Glasheen, C., Olson, S., Landi, M. T., Madden, P. A.F., Farrer, L. A., Vink, J., Saccone, N. L., Neale, M. C., Kranzler, H. R., McKay, J., Hung, R. J., Amos, C. I., Marazita, M. L., Boomsma, D. I., Baker, T. B., Gelernter, J., Kaprio, J., Caporaso, N. E., Thorgeirsson, T. E., Hokanson, J. E., Bierut, L. J., Stefansson, K., Johnson, E. O., Hancock, D. B., Guo, Y., Reginsson, G. W., Gaddis, N. C., Lutz, S. M., Sherva, R., Loukola, A., Minica, C. C., Markunas, C. A., Han, Y., Young, K. A., Gudbjartsson, D. F., Gu, F., McNeil, D. W., Qaiser, B., Glasheen, C., Olson, S., Landi, M. T., Madden, P. A.F., Farrer, L. A., Vink, J., Saccone, N. L., Neale, M. C., Kranzler, H. R., McKay, J., Hung, R. J., Amos, C. I., Marazita, M. L., Boomsma, D. I., Baker, T. B., Gelernter, J., Kaprio, J., Caporaso, N. E., Thorgeirsson, T. E., Hokanson, J. E., Bierut, L. J., Stefansson, K., and Johnson, E. O.
Abstract: Cigarette smoking is a leading cause of preventable mortality worldwide. Nicotine dependence, which reduces the likelihood of quitting smoking, is a heritable trait with firmly established associations with sequence variants in nicotine acetylcholine receptor genes and at other loci. To search for additional loci, we conducted a genome-wide association study (GWAS) meta-analysis of nicotine dependence, totaling 38,602 smokers (28,677 Europeans/European Americans and 9925 African Americans) across 15 studies. In this largest-ever GWAS meta-analysis for nicotine dependence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfirmed the well-known CHRNA5-CHRNA3-CHRNB4 genes and further yielded a novel association in the DNA methyltransferase gene DNMT3B. The intronic DNMT3B rs910083-C allele (frequency=44–77%) was associated with increased risk of nicotine dependence at P=3.7 × 10−8 (odds ratio (OR)=1.06 and 95% confidence interval (CI)=1.04–1.07 for severe vs mild dependence). The association was independently confirmed in the UK Biobank (N=48,931) using heavy vs never smoking as a proxy phenotype (P=3.6 × 10−4, OR=1.05, and 95% CI=1.02–1.08). Rs910083-C is also associated with increased risk of squamous cell lung carcinoma in the International Lung Cancer Consortium (N=60,586, meta-analysis P=0.0095, OR=1.05, and 95% CI=1.01–1.09). Moreover, rs910083-C was implicated as a cis-methylation quantitative trait locus (QTL) variant associated with higher DNMT3B methylation in fetal brain (N=166, P=2.3 × 10−26) and a cis-expression QTL variant associated with higher DNMT3B expression in adult cerebellum from the Genotype-Tissue Expression project (N=103, P=3.0 × 10−6) and the independent Brain eQTL Almanac (N=134, P=0.028). This novel DNMT3B cis-acting QTL variant highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and co
Published: 2018
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18. Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence

Author: Hancock, D. B., Guo, Y., Reginsson, G. W., Gaddis, N. C., Lutz, S. M., Sherva, R., Loukola, A., Minica, C. C., Markunas, C. A., Han, Y., Young, K. A., Gudbjartsson, D. F., Gu, F., McNeil, D. W., Qaiser, B., Glasheen, C., Olson, S., Landi, M. T., Madden, P. A.F., Farrer, L. A., Vink, J., Saccone, N. L., Neale, M. C., Kranzler, H. R., McKay, J., Hung, R. J., Amos, C. I., Marazita, M. L., Boomsma, D. I., Baker, T. B., Gelernter, J., Kaprio, J., Caporaso, N. E., Thorgeirsson, T. E., Hokanson, J. E., Bierut, L. J., Stefansson, K., Johnson, E. O., Hancock, D. B., Guo, Y., Reginsson, G. W., Gaddis, N. C., Lutz, S. M., Sherva, R., Loukola, A., Minica, C. C., Markunas, C. A., Han, Y., Young, K. A., Gudbjartsson, D. F., Gu, F., McNeil, D. W., Qaiser, B., Glasheen, C., Olson, S., Landi, M. T., Madden, P. A.F., Farrer, L. A., Vink, J., Saccone, N. L., Neale, M. C., Kranzler, H. R., McKay, J., Hung, R. J., Amos, C. I., Marazita, M. L., Boomsma, D. I., Baker, T. B., Gelernter, J., Kaprio, J., Caporaso, N. E., Thorgeirsson, T. E., Hokanson, J. E., Bierut, L. J., Stefansson, K., and Johnson, E. O.
Abstract: Cigarette smoking is a leading cause of preventable mortality worldwide. Nicotine dependence, which reduces the likelihood of quitting smoking, is a heritable trait with firmly established associations with sequence variants in nicotine acetylcholine receptor genes and at other loci. To search for additional loci, we conducted a genome-wide association study (GWAS) meta-analysis of nicotine dependence, totaling 38,602 smokers (28,677 Europeans/European Americans and 9925 African Americans) across 15 studies. In this largest-ever GWAS meta-analysis for nicotine dependence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfirmed the well-known CHRNA5-CHRNA3-CHRNB4 genes and further yielded a novel association in the DNA methyltransferase gene DNMT3B. The intronic DNMT3B rs910083-C allele (frequency=44–77%) was associated with increased risk of nicotine dependence at P=3.7 × 10−8 (odds ratio (OR)=1.06 and 95% confidence interval (CI)=1.04–1.07 for severe vs mild dependence). The association was independently confirmed in the UK Biobank (N=48,931) using heavy vs never smoking as a proxy phenotype (P=3.6 × 10−4, OR=1.05, and 95% CI=1.02–1.08). Rs910083-C is also associated with increased risk of squamous cell lung carcinoma in the International Lung Cancer Consortium (N=60,586, meta-analysis P=0.0095, OR=1.05, and 95% CI=1.01–1.09). Moreover, rs910083-C was implicated as a cis-methylation quantitative trait locus (QTL) variant associated with higher DNMT3B methylation in fetal brain (N=166, P=2.3 × 10−26) and a cis-expression QTL variant associated with higher DNMT3B expression in adult cerebellum from the Genotype-Tissue Expression project (N=103, P=3.0 × 10−6) and the independent Brain eQTL Almanac (N=134, P=0.028). This novel DNMT3B cis-acting QTL variant highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and co
Published: 2018
Full Text: View/download PDF

19. Prevalence of pathogenic/likely pathogenic variants in the 24 cancer genes of the ACMG Secondary Findings v2.0 list in a large cancer cohort and ethnicity-matched controls

Author: Kim, J., Luo, W., Wang, M., Wegman-Ostrosky, T., Frone, M. N., Johnston, J. J., Nickerson, M. L., Rotunno, M., Li, S. A., Achatz, M. I., Brodie, S. A., Dean, M., De Andrade, K. C., Fortes, F. P., Gianferante, M., Khincha, P., Mcmaster, M. L., Mcreynolds, L. J., Pemov, A., Pinheiro, M., Santiago, K. M., Alter, B. P., Caporaso, N. E., Gadalla, S. M., Goldin, L. R., Greene, M. H., Loud, J., Yang, X. R., Freedman, N. D., Gapstur, S. M., Gaudet, M. M., Calista, D., Ghiorzo, P., Fargnoli, Maria Concetta, Nagore, E., Peris, Ketty, Puig, S., Landi, M. T., Hicks, B., Zhu, B., Liu, J., Sampson, J. N., Chanock, S. J., Mirabello, L. J., Morton, L. M., Biesecker, L. G., Tucker, M. A., Savage, S. A., Goldstein, A. M., Stewart, D. R., Fargnoli M. C., Peris K. (ORCID:0000-0002-5237-0463), Kim, J., Luo, W., Wang, M., Wegman-Ostrosky, T., Frone, M. N., Johnston, J. J., Nickerson, M. L., Rotunno, M., Li, S. A., Achatz, M. I., Brodie, S. A., Dean, M., De Andrade, K. C., Fortes, F. P., Gianferante, M., Khincha, P., Mcmaster, M. L., Mcreynolds, L. J., Pemov, A., Pinheiro, M., Santiago, K. M., Alter, B. P., Caporaso, N. E., Gadalla, S. M., Goldin, L. R., Greene, M. H., Loud, J., Yang, X. R., Freedman, N. D., Gapstur, S. M., Gaudet, M. M., Calista, D., Ghiorzo, P., Fargnoli, Maria Concetta, Nagore, E., Peris, Ketty, Puig, S., Landi, M. T., Hicks, B., Zhu, B., Liu, J., Sampson, J. N., Chanock, S. J., Mirabello, L. J., Morton, L. M., Biesecker, L. G., Tucker, M. A., Savage, S. A., Goldstein, A. M., Stewart, D. R., Fargnoli M. C., and Peris K. (ORCID:0000-0002-5237-0463)
Abstract: Background: Prior research has established that the prevalence of pathogenic/likely pathogenic (P/LP) variants across all of the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes is approximately 0.8-5%. We investigated the prevalence of P/LP variants in the 24 ACMG SF v2.0 cancer genes in a family-based cancer research cohort (n = 1173) and in cancer-free ethnicity-matched controls (n = 982). Methods: We used InterVar to classify variants and subsequently conducted a manual review to further examine variants of unknown significance (VUS). Results: In the 24 genes on the ACMG SF v2.0 list associated with a cancer phenotype, we observed 8 P/LP unique variants (8 individuals; 0.8%) in controls and 11 P/LP unique variants (14 individuals; 1.2%) in cases, a non-significant difference. We reviewed 115 VUS. The median estimated per-variant review time required was 30 min; the first variant within a gene took significantly (p = 0.0009) longer to review (median = 60 min) compared with subsequent variants (median = 30 min). The concordance rate was 83.3% for the variants examined by two reviewers. Conclusion: The 115 VUS required database and literature review, a time- and labor-intensive process hampered by the difficulty in interpreting conflicting P/LP determinations. By rigorously investigating the 24 ACMG SF v2.0 cancer genes, our work establishes a benchmark P/LP variant prevalence rate in a familial cancer cohort and controls.
Published: 2018

20. The role of mobile apps in allergic respiratory diseases: An italian multicentre survey report

Author: Lombardi, Carlo, Bonini, Matteo, Passalacqua, G., Caminati, M., Padrini Peroni, Deni, Favero, E., Patella, V., Landi, M., Gani, F., Meriggi, Fausto Angelo, Corsico, A. G., Costantino, M. T., Senna, G., Cassottana Rossi, Olga, Rolla, G., Bonini, M. (ORCID:0000-0002-3042-0765), Rossi, O., Lombardi, Carlo, Bonini, Matteo, Passalacqua, G., Caminati, M., Padrini Peroni, Deni, Favero, E., Patella, V., Landi, M., Gani, F., Meriggi, Fausto Angelo, Corsico, A. G., Costantino, M. T., Senna, G., Cassottana Rossi, Olga, Rolla, G., Bonini, M. (ORCID:0000-0002-3042-0765), and Rossi, O.
Abstract: We performed a multicentre survey about the role of mobile apps in allergic respiratory diseases. The main objective was to investigate the current use and usefulness of mobile phone apps in the management of allergic respiratory disease. An original questionnaire including 12 multiple-choice questions was administered to 360 participants (153 male and 207 female subjects). Of notice, 290 subjects owned a smartphone, 120 a personal computer and 68 a tablet (multiple answers were possible). 123 subjects reported to be regular mobile-apps users, 209 were occasional users and 76 has never downloaded an app. Indeed, 259 subjects have never dealt with a medical or healthcare app, with only 8 subjects answering to often take advantage of such supportive tools. Data were even more discouraging when asking whether subjects had ever downloaded an app directly related to their own medical condition (allergy, asthma and rhinitis). 87.2% provided a negative answer. Among the few individuals who reported a previous experience with allergy/asthma apps only 2 subjects reported to regularly use the apps they had downloaded, even after months. The majority of subjects believed the apps would provide a relevant support, but only 25/360 participants found that the apps are “truly helpful”, while 44 considered them of “help but not essential”. Our data seem to show that the apps in the medical field, especially for allergic respiratory diseases, are welcome by patients, but their continued use and utility wane with the passage of time from the date of the download. In the future it will therefore be important to focus on the quality of the apps themselves and on the careful selection of the most suitable patients to use them. Finally, it will be important to make use of the fundamental contribution of healthcare professionals for the development of the apps.
Published: 2018

21. Selección de parcelas control para estudios de la dinámica post-incendio: desempeño de rutinas no paramétricas y autorregresivas

Author: Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., Bellis, L. M., Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., and Bellis, L. M.
Abstract: Revista oficial de la Asociación Española de Teledetección, [EN] Natural fire regimes have been modified; therefore robust post-fire monitoring tools are needed to understand the post-fire recovery process. Satellites with high temporal resolution allow us to build time series of vegetation indices for monitoring post-fire vegetation recovery. One of the techniques used is to compare the time series of a burned plot with that of an unburned control plot. However, for its implementation it is necessary to select control plots in which the vegetation has the same structure and functioning than the plot burned before the fire. Previous study defined biological criteria to detect burned and unburned control plots with identical pre-fire vegetation functioning. Moreover, a non-parametric test routine of low statistical power was proposed to test them, this was based on the analysis of the QVI (Quotient Vegetation Index), calculated between NDVI (Normalized Difference Vegetation Index) time series of the burned and control site. However, currently there are autoregressive analysis techniques with greater statistical power. Therefore the aims were to propose six new statistical routines based on autoregressive test, and compare the performance of these with the non-parametric routine. We selected 13,700 forest plots and extracted the NDVI MODIS time series between 2002 and 2005. We randomly selected 43 reference plots, and through each routine, we compared each reference time series with the other 13,657 time series. We estimated the performance of the routines measuring the euclidian distance between the time series of the reference plot and the time series of the plots accepted for each routine. We also measured the quality and the amount of the QVI time series selected by each routine. Autoregressive routines showed better performance than the non-parametric routine, since they selected control plots with NDVI time series with greatest similarity with respect to the reference plots and QVI series with highest quality., [ES] Los regímenes naturales de incendios han sufrido modificaciones; consecuentemente, es indispensable disponer de herramientas robustas para el seguimiento post-fuego de la vegetación. Los satélites de alta resolución temporal permiten construir series temporales de índices de vegetación para monitorear la recuperación post-fuego. Una de las técnicas utilizadas consiste en comparar la serie temporal de una parcela quemada con la de una parcela control no quemada. Sin embargo, para su implementación es necesario seleccionar parcelas control que antes del incendio tengan una vegetación con igual estructura y funcionamiento que la parcela quemada. Un estudio previo definió criterios biológicos para localizar parcelas quemadas y control con idéntico funcionamiento pre-incendio. Para testearlos se propuso una rutina de test no paramétricos de baja potencia estadística, analizando el cociente QVI (Quotient Vegetation Index) de las series temporales de NDVI (Normalized Difference Vegetation Index) de parcelas control y quemadas. Sin embargo, actualmente existen técnicas de análisis autorregresivas con mayor potencia estadística. Los objetivos del presente trabajo fueron proponer seis nuevas rutinas basadas en test autorregresivos y comparar el desempeño de éstas contra la rutina no paramétrica. Seleccionamos 13.700 parcelas de bosque y extrajimos las series temporales NDVI MODIS entre 2002 y 2005. Aleatoriamente seleccionamos 43 parcelas de referencia. A través de las rutinas planteadas comparamos la serie temporal de referencia con cada una de las 13.657 series restantes. Estimamos el desempeño midiendo la distancia euclidiana entre la serie de temporal de la parcela de referencia y las series temporales de las parcelas aceptadas por cada rutina. También, medimos la calidad y contabilizamos la cantidad de las series temporales QVI seleccionadas por cada rutina. Las rutinas autorregresivas tuvieron mejor desempeño, ya que seleccionaron parcelas control con series tempor
Published: 2017

22. Selección de parcelas control para estudios de la dinámica post-incendio: desempeño de rutinas no paramétricas y autorregresivas

Author: Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., Bellis, L. M., Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., and Bellis, L. M.
Abstract: Revista oficial de la Asociación Española de Teledetección, [EN] Natural fire regimes have been modified; therefore robust post-fire monitoring tools are needed to understand the post-fire recovery process. Satellites with high temporal resolution allow us to build time series of vegetation indices for monitoring post-fire vegetation recovery. One of the techniques used is to compare the time series of a burned plot with that of an unburned control plot. However, for its implementation it is necessary to select control plots in which the vegetation has the same structure and functioning than the plot burned before the fire. Previous study defined biological criteria to detect burned and unburned control plots with identical pre-fire vegetation functioning. Moreover, a non-parametric test routine of low statistical power was proposed to test them, this was based on the analysis of the QVI (Quotient Vegetation Index), calculated between NDVI (Normalized Difference Vegetation Index) time series of the burned and control site. However, currently there are autoregressive analysis techniques with greater statistical power. Therefore the aims were to propose six new statistical routines based on autoregressive test, and compare the performance of these with the non-parametric routine. We selected 13,700 forest plots and extracted the NDVI MODIS time series between 2002 and 2005. We randomly selected 43 reference plots, and through each routine, we compared each reference time series with the other 13,657 time series. We estimated the performance of the routines measuring the euclidian distance between the time series of the reference plot and the time series of the plots accepted for each routine. We also measured the quality and the amount of the QVI time series selected by each routine. Autoregressive routines showed better performance than the non-parametric routine, since they selected control plots with NDVI time series with greatest similarity with respect to the reference plots and QVI series with highest quality., [ES] Los regímenes naturales de incendios han sufrido modificaciones; consecuentemente, es indispensable disponer de herramientas robustas para el seguimiento post-fuego de la vegetación. Los satélites de alta resolución temporal permiten construir series temporales de índices de vegetación para monitorear la recuperación post-fuego. Una de las técnicas utilizadas consiste en comparar la serie temporal de una parcela quemada con la de una parcela control no quemada. Sin embargo, para su implementación es necesario seleccionar parcelas control que antes del incendio tengan una vegetación con igual estructura y funcionamiento que la parcela quemada. Un estudio previo definió criterios biológicos para localizar parcelas quemadas y control con idéntico funcionamiento pre-incendio. Para testearlos se propuso una rutina de test no paramétricos de baja potencia estadística, analizando el cociente QVI (Quotient Vegetation Index) de las series temporales de NDVI (Normalized Difference Vegetation Index) de parcelas control y quemadas. Sin embargo, actualmente existen técnicas de análisis autorregresivas con mayor potencia estadística. Los objetivos del presente trabajo fueron proponer seis nuevas rutinas basadas en test autorregresivos y comparar el desempeño de éstas contra la rutina no paramétrica. Seleccionamos 13.700 parcelas de bosque y extrajimos las series temporales NDVI MODIS entre 2002 y 2005. Aleatoriamente seleccionamos 43 parcelas de referencia. A través de las rutinas planteadas comparamos la serie temporal de referencia con cada una de las 13.657 series restantes. Estimamos el desempeño midiendo la distancia euclidiana entre la serie de temporal de la parcela de referencia y las series temporales de las parcelas aceptadas por cada rutina. También, medimos la calidad y contabilizamos la cantidad de las series temporales QVI seleccionadas por cada rutina. Las rutinas autorregresivas tuvieron mejor desempeño, ya que seleccionaron parcelas control con series tempor
Published: 2017

23. Bromodomain protein 4 discriminates tissue-specific super-enhancers containing disease-specific susceptibility loci in prostate and breast cancer

Author: Zuber, Verena, Bettella, Francesco, Witoelar, Aree, Andreassen, Ole A., Mills, Ian G., Urbanucci, Alfonso, Eeles, Rosalind, Easton, Doug, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Benlloch, Sara, Muir, Kenneth, Giles, Graham G., Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher A., Schleutker, Johanna, Weischer, Maren, Travis, Ruth C., Neal, David, Pharoah, Paul, Khaw, Kay Tee, Stanford, Janet L., Blot, William J., Thibodeau, Stephen, Maier, Christiane, Kibel, Adam S., Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Park, Jong, Kaneva, Radka, Batra, Jyotsna, Teixeira, Manuel R., Pandha, Hardev, Chenevix-Trench, Georgia, Humphreys, Manjeet, Hung, R. J., Han, Y., Brennan, P., Bickeböller, H., Rosenberger, A., Houlston, R. S., Caporaso, N., Landi, M. T., Wu, X., Wang, Qin, Bojesen, Stig E., Nielsen, Sune F., Nordestgaard, Borge G., Zuber, Verena, Bettella, Francesco, Witoelar, Aree, Andreassen, Ole A., Mills, Ian G., Urbanucci, Alfonso, Eeles, Rosalind, Easton, Doug, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Benlloch, Sara, Muir, Kenneth, Giles, Graham G., Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher A., Schleutker, Johanna, Weischer, Maren, Travis, Ruth C., Neal, David, Pharoah, Paul, Khaw, Kay Tee, Stanford, Janet L., Blot, William J., Thibodeau, Stephen, Maier, Christiane, Kibel, Adam S., Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Park, Jong, Kaneva, Radka, Batra, Jyotsna, Teixeira, Manuel R., Pandha, Hardev, Chenevix-Trench, Georgia, Humphreys, Manjeet, Hung, R. J., Han, Y., Brennan, P., Bickeböller, H., Rosenberger, A., Houlston, R. S., Caporaso, N., Landi, M. T., Wu, X., Wang, Qin, Bojesen, Stig E., Nielsen, Sune F., and Nordestgaard, Borge G.
Abstract: Background: Epigenetic information can be used to identify clinically relevant genomic variants single nucleotide polymorphisms (SNPs) of functional importance in cancer development. Super-enhancers are cell-specific DNA elements, acting to determine tissue or cell identity and driving tumor progression. Although previous approaches have been tried to explain risk associated with SNPs in regulatory DNA elements, so far epigenetic readers such as bromodomain containing protein 4 (BRD4) and super-enhancers have not been used to annotate SNPs. In prostate cancer (PC), androgen receptor (AR) binding sites to chromatin have been used to inform functional annotations of SNPs. Results: Here we establish criteria for enhancer mapping which are applicable to other diseases and traits to achieve the optimal tissue-specific enrichment of PC risk SNPs. We used stratified Q-Q plots and Fisher test to assess the differential enrichment of SNPs mapping to specific categories of enhancers. We find that BRD4 is the key discriminant of tissue-specific enhancers, showing that it is more powerful than AR binding information to capture PC specific risk loci, and can be used with similar effect in breast cancer (BC) and applied to other diseases such as schizophrenia. Conclusions: This is the first study to evaluate the enrichment of epigenetic readers in genome-wide associations studies for SNPs within enhancers, and provides a powerful tool for enriching and prioritizing PC and BC genetic risk loci. Our study represents a proof of principle applicable to other diseases and traits that can be used to redefine molecular mechanisms of human phenotypic variation.
Published: 2017

24. Selección de parcelas control para estudios de la dinámica post-incendio: desempeño de rutinas no paramétricas y autorregresivas

Author: Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., Bellis, L. M., Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., and Bellis, L. M.
Abstract: Revista oficial de la Asociación Española de Teledetección, [EN] Natural fire regimes have been modified; therefore robust post-fire monitoring tools are needed to understand the post-fire recovery process. Satellites with high temporal resolution allow us to build time series of vegetation indices for monitoring post-fire vegetation recovery. One of the techniques used is to compare the time series of a burned plot with that of an unburned control plot. However, for its implementation it is necessary to select control plots in which the vegetation has the same structure and functioning than the plot burned before the fire. Previous study defined biological criteria to detect burned and unburned control plots with identical pre-fire vegetation functioning. Moreover, a non-parametric test routine of low statistical power was proposed to test them, this was based on the analysis of the QVI (Quotient Vegetation Index), calculated between NDVI (Normalized Difference Vegetation Index) time series of the burned and control site. However, currently there are autoregressive analysis techniques with greater statistical power. Therefore the aims were to propose six new statistical routines based on autoregressive test, and compare the performance of these with the non-parametric routine. We selected 13,700 forest plots and extracted the NDVI MODIS time series between 2002 and 2005. We randomly selected 43 reference plots, and through each routine, we compared each reference time series with the other 13,657 time series. We estimated the performance of the routines measuring the euclidian distance between the time series of the reference plot and the time series of the plots accepted for each routine. We also measured the quality and the amount of the QVI time series selected by each routine. Autoregressive routines showed better performance than the non-parametric routine, since they selected control plots with NDVI time series with greatest similarity with respect to the reference plots and QVI series with highest quality., [ES] Los regímenes naturales de incendios han sufrido modificaciones; consecuentemente, es indispensable disponer de herramientas robustas para el seguimiento post-fuego de la vegetación. Los satélites de alta resolución temporal permiten construir series temporales de índices de vegetación para monitorear la recuperación post-fuego. Una de las técnicas utilizadas consiste en comparar la serie temporal de una parcela quemada con la de una parcela control no quemada. Sin embargo, para su implementación es necesario seleccionar parcelas control que antes del incendio tengan una vegetación con igual estructura y funcionamiento que la parcela quemada. Un estudio previo definió criterios biológicos para localizar parcelas quemadas y control con idéntico funcionamiento pre-incendio. Para testearlos se propuso una rutina de test no paramétricos de baja potencia estadística, analizando el cociente QVI (Quotient Vegetation Index) de las series temporales de NDVI (Normalized Difference Vegetation Index) de parcelas control y quemadas. Sin embargo, actualmente existen técnicas de análisis autorregresivas con mayor potencia estadística. Los objetivos del presente trabajo fueron proponer seis nuevas rutinas basadas en test autorregresivos y comparar el desempeño de éstas contra la rutina no paramétrica. Seleccionamos 13.700 parcelas de bosque y extrajimos las series temporales NDVI MODIS entre 2002 y 2005. Aleatoriamente seleccionamos 43 parcelas de referencia. A través de las rutinas planteadas comparamos la serie temporal de referencia con cada una de las 13.657 series restantes. Estimamos el desempeño midiendo la distancia euclidiana entre la serie de temporal de la parcela de referencia y las series temporales de las parcelas aceptadas por cada rutina. También, medimos la calidad y contabilizamos la cantidad de las series temporales QVI seleccionadas por cada rutina. Las rutinas autorregresivas tuvieron mejor desempeño, ya que seleccionaron parcelas control con series tempor
Published: 2017

25. Selección de parcelas control para estudios de la dinámica post-incendio: desempeño de rutinas no paramétricas y autorregresivas

Author: Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., Bellis, L. M., Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., and Bellis, L. M.
Abstract: Revista oficial de la Asociación Española de Teledetección, [EN] Natural fire regimes have been modified; therefore robust post-fire monitoring tools are needed to understand the post-fire recovery process. Satellites with high temporal resolution allow us to build time series of vegetation indices for monitoring post-fire vegetation recovery. One of the techniques used is to compare the time series of a burned plot with that of an unburned control plot. However, for its implementation it is necessary to select control plots in which the vegetation has the same structure and functioning than the plot burned before the fire. Previous study defined biological criteria to detect burned and unburned control plots with identical pre-fire vegetation functioning. Moreover, a non-parametric test routine of low statistical power was proposed to test them, this was based on the analysis of the QVI (Quotient Vegetation Index), calculated between NDVI (Normalized Difference Vegetation Index) time series of the burned and control site. However, currently there are autoregressive analysis techniques with greater statistical power. Therefore the aims were to propose six new statistical routines based on autoregressive test, and compare the performance of these with the non-parametric routine. We selected 13,700 forest plots and extracted the NDVI MODIS time series between 2002 and 2005. We randomly selected 43 reference plots, and through each routine, we compared each reference time series with the other 13,657 time series. We estimated the performance of the routines measuring the euclidian distance between the time series of the reference plot and the time series of the plots accepted for each routine. We also measured the quality and the amount of the QVI time series selected by each routine. Autoregressive routines showed better performance than the non-parametric routine, since they selected control plots with NDVI time series with greatest similarity with respect to the reference plots and QVI series with highest quality., [ES] Los regímenes naturales de incendios han sufrido modificaciones; consecuentemente, es indispensable disponer de herramientas robustas para el seguimiento post-fuego de la vegetación. Los satélites de alta resolución temporal permiten construir series temporales de índices de vegetación para monitorear la recuperación post-fuego. Una de las técnicas utilizadas consiste en comparar la serie temporal de una parcela quemada con la de una parcela control no quemada. Sin embargo, para su implementación es necesario seleccionar parcelas control que antes del incendio tengan una vegetación con igual estructura y funcionamiento que la parcela quemada. Un estudio previo definió criterios biológicos para localizar parcelas quemadas y control con idéntico funcionamiento pre-incendio. Para testearlos se propuso una rutina de test no paramétricos de baja potencia estadística, analizando el cociente QVI (Quotient Vegetation Index) de las series temporales de NDVI (Normalized Difference Vegetation Index) de parcelas control y quemadas. Sin embargo, actualmente existen técnicas de análisis autorregresivas con mayor potencia estadística. Los objetivos del presente trabajo fueron proponer seis nuevas rutinas basadas en test autorregresivos y comparar el desempeño de éstas contra la rutina no paramétrica. Seleccionamos 13.700 parcelas de bosque y extrajimos las series temporales NDVI MODIS entre 2002 y 2005. Aleatoriamente seleccionamos 43 parcelas de referencia. A través de las rutinas planteadas comparamos la serie temporal de referencia con cada una de las 13.657 series restantes. Estimamos el desempeño midiendo la distancia euclidiana entre la serie de temporal de la parcela de referencia y las series temporales de las parcelas aceptadas por cada rutina. También, medimos la calidad y contabilizamos la cantidad de las series temporales QVI seleccionadas por cada rutina. Las rutinas autorregresivas tuvieron mejor desempeño, ya que seleccionaron parcelas control con series tempor
Published: 2017

26. Selección de parcelas control para estudios de la dinámica post-incendio: desempeño de rutinas no paramétricas y autorregresivas

Author: Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., Bellis, L. M., Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., and Bellis, L. M.
Abstract: Revista oficial de la Asociación Española de Teledetección, [EN] Natural fire regimes have been modified; therefore robust post-fire monitoring tools are needed to understand the post-fire recovery process. Satellites with high temporal resolution allow us to build time series of vegetation indices for monitoring post-fire vegetation recovery. One of the techniques used is to compare the time series of a burned plot with that of an unburned control plot. However, for its implementation it is necessary to select control plots in which the vegetation has the same structure and functioning than the plot burned before the fire. Previous study defined biological criteria to detect burned and unburned control plots with identical pre-fire vegetation functioning. Moreover, a non-parametric test routine of low statistical power was proposed to test them, this was based on the analysis of the QVI (Quotient Vegetation Index), calculated between NDVI (Normalized Difference Vegetation Index) time series of the burned and control site. However, currently there are autoregressive analysis techniques with greater statistical power. Therefore the aims were to propose six new statistical routines based on autoregressive test, and compare the performance of these with the non-parametric routine. We selected 13,700 forest plots and extracted the NDVI MODIS time series between 2002 and 2005. We randomly selected 43 reference plots, and through each routine, we compared each reference time series with the other 13,657 time series. We estimated the performance of the routines measuring the euclidian distance between the time series of the reference plot and the time series of the plots accepted for each routine. We also measured the quality and the amount of the QVI time series selected by each routine. Autoregressive routines showed better performance than the non-parametric routine, since they selected control plots with NDVI time series with greatest similarity with respect to the reference plots and QVI series with highest quality., [ES] Los regímenes naturales de incendios han sufrido modificaciones; consecuentemente, es indispensable disponer de herramientas robustas para el seguimiento post-fuego de la vegetación. Los satélites de alta resolución temporal permiten construir series temporales de índices de vegetación para monitorear la recuperación post-fuego. Una de las técnicas utilizadas consiste en comparar la serie temporal de una parcela quemada con la de una parcela control no quemada. Sin embargo, para su implementación es necesario seleccionar parcelas control que antes del incendio tengan una vegetación con igual estructura y funcionamiento que la parcela quemada. Un estudio previo definió criterios biológicos para localizar parcelas quemadas y control con idéntico funcionamiento pre-incendio. Para testearlos se propuso una rutina de test no paramétricos de baja potencia estadística, analizando el cociente QVI (Quotient Vegetation Index) de las series temporales de NDVI (Normalized Difference Vegetation Index) de parcelas control y quemadas. Sin embargo, actualmente existen técnicas de análisis autorregresivas con mayor potencia estadística. Los objetivos del presente trabajo fueron proponer seis nuevas rutinas basadas en test autorregresivos y comparar el desempeño de éstas contra la rutina no paramétrica. Seleccionamos 13.700 parcelas de bosque y extrajimos las series temporales NDVI MODIS entre 2002 y 2005. Aleatoriamente seleccionamos 43 parcelas de referencia. A través de las rutinas planteadas comparamos la serie temporal de referencia con cada una de las 13.657 series restantes. Estimamos el desempeño midiendo la distancia euclidiana entre la serie de temporal de la parcela de referencia y las series temporales de las parcelas aceptadas por cada rutina. También, medimos la calidad y contabilizamos la cantidad de las series temporales QVI seleccionadas por cada rutina. Las rutinas autorregresivas tuvieron mejor desempeño, ya que seleccionaron parcelas control con series tempor
Published: 2017

27. Selección de parcelas control para estudios de la dinámica post-incendio: desempeño de rutinas no paramétricas y autorregresivas

Author: Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., Bellis, L. M., Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Landi, M. A., Ojeda, S., Di Bella, C. M., Salvatierra, P., Argañaraz, J. P., and Bellis, L. M.
Abstract: Revista oficial de la Asociación Española de Teledetección, [EN] Natural fire regimes have been modified; therefore robust post-fire monitoring tools are needed to understand the post-fire recovery process. Satellites with high temporal resolution allow us to build time series of vegetation indices for monitoring post-fire vegetation recovery. One of the techniques used is to compare the time series of a burned plot with that of an unburned control plot. However, for its implementation it is necessary to select control plots in which the vegetation has the same structure and functioning than the plot burned before the fire. Previous study defined biological criteria to detect burned and unburned control plots with identical pre-fire vegetation functioning. Moreover, a non-parametric test routine of low statistical power was proposed to test them, this was based on the analysis of the QVI (Quotient Vegetation Index), calculated between NDVI (Normalized Difference Vegetation Index) time series of the burned and control site. However, currently there are autoregressive analysis techniques with greater statistical power. Therefore the aims were to propose six new statistical routines based on autoregressive test, and compare the performance of these with the non-parametric routine. We selected 13,700 forest plots and extracted the NDVI MODIS time series between 2002 and 2005. We randomly selected 43 reference plots, and through each routine, we compared each reference time series with the other 13,657 time series. We estimated the performance of the routines measuring the euclidian distance between the time series of the reference plot and the time series of the plots accepted for each routine. We also measured the quality and the amount of the QVI time series selected by each routine. Autoregressive routines showed better performance than the non-parametric routine, since they selected control plots with NDVI time series with greatest similarity with respect to the reference plots and QVI series with highest quality., [ES] Los regímenes naturales de incendios han sufrido modificaciones; consecuentemente, es indispensable disponer de herramientas robustas para el seguimiento post-fuego de la vegetación. Los satélites de alta resolución temporal permiten construir series temporales de índices de vegetación para monitorear la recuperación post-fuego. Una de las técnicas utilizadas consiste en comparar la serie temporal de una parcela quemada con la de una parcela control no quemada. Sin embargo, para su implementación es necesario seleccionar parcelas control que antes del incendio tengan una vegetación con igual estructura y funcionamiento que la parcela quemada. Un estudio previo definió criterios biológicos para localizar parcelas quemadas y control con idéntico funcionamiento pre-incendio. Para testearlos se propuso una rutina de test no paramétricos de baja potencia estadística, analizando el cociente QVI (Quotient Vegetation Index) de las series temporales de NDVI (Normalized Difference Vegetation Index) de parcelas control y quemadas. Sin embargo, actualmente existen técnicas de análisis autorregresivas con mayor potencia estadística. Los objetivos del presente trabajo fueron proponer seis nuevas rutinas basadas en test autorregresivos y comparar el desempeño de éstas contra la rutina no paramétrica. Seleccionamos 13.700 parcelas de bosque y extrajimos las series temporales NDVI MODIS entre 2002 y 2005. Aleatoriamente seleccionamos 43 parcelas de referencia. A través de las rutinas planteadas comparamos la serie temporal de referencia con cada una de las 13.657 series restantes. Estimamos el desempeño midiendo la distancia euclidiana entre la serie de temporal de la parcela de referencia y las series temporales de las parcelas aceptadas por cada rutina. También, medimos la calidad y contabilizamos la cantidad de las series temporales QVI seleccionadas por cada rutina. Las rutinas autorregresivas tuvieron mejor desempeño, ya que seleccionaron parcelas control con series tempor
Published: 2017

28. Bromodomain protein 4 discriminates tissue-specific super-enhancers containing disease-specific susceptibility loci in prostate and breast cancer

Author: Zuber, Verena, Bettella, Francesco, Witoelar, Aree, Andreassen, Ole A., Mills, Ian G., Urbanucci, Alfonso, Eeles, Rosalind, Easton, Doug, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Benlloch, Sara, Muir, Kenneth, Giles, Graham G., Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher A., Schleutker, Johanna, Weischer, Maren, Travis, Ruth C., Neal, David, Pharoah, Paul, Khaw, Kay Tee, Stanford, Janet L., Blot, William J., Thibodeau, Stephen, Maier, Christiane, Kibel, Adam S., Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Park, Jong, Kaneva, Radka, Batra, Jyotsna, Teixeira, Manuel R., Pandha, Hardev, Chenevix-Trench, Georgia, Humphreys, Manjeet, Hung, R. J., Han, Y., Brennan, P., Bickeböller, H., Rosenberger, A., Houlston, R. S., Caporaso, N., Landi, M. T., Wu, X., Wang, Qin, Bojesen, Stig E., Nielsen, Sune F., Nordestgaard, Borge G., Zuber, Verena, Bettella, Francesco, Witoelar, Aree, Andreassen, Ole A., Mills, Ian G., Urbanucci, Alfonso, Eeles, Rosalind, Easton, Doug, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Benlloch, Sara, Muir, Kenneth, Giles, Graham G., Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher A., Schleutker, Johanna, Weischer, Maren, Travis, Ruth C., Neal, David, Pharoah, Paul, Khaw, Kay Tee, Stanford, Janet L., Blot, William J., Thibodeau, Stephen, Maier, Christiane, Kibel, Adam S., Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Park, Jong, Kaneva, Radka, Batra, Jyotsna, Teixeira, Manuel R., Pandha, Hardev, Chenevix-Trench, Georgia, Humphreys, Manjeet, Hung, R. J., Han, Y., Brennan, P., Bickeböller, H., Rosenberger, A., Houlston, R. S., Caporaso, N., Landi, M. T., Wu, X., Wang, Qin, Bojesen, Stig E., Nielsen, Sune F., and Nordestgaard, Borge G.
Abstract: Background: Epigenetic information can be used to identify clinically relevant genomic variants single nucleotide polymorphisms (SNPs) of functional importance in cancer development. Super-enhancers are cell-specific DNA elements, acting to determine tissue or cell identity and driving tumor progression. Although previous approaches have been tried to explain risk associated with SNPs in regulatory DNA elements, so far epigenetic readers such as bromodomain containing protein 4 (BRD4) and super-enhancers have not been used to annotate SNPs. In prostate cancer (PC), androgen receptor (AR) binding sites to chromatin have been used to inform functional annotations of SNPs. Results: Here we establish criteria for enhancer mapping which are applicable to other diseases and traits to achieve the optimal tissue-specific enrichment of PC risk SNPs. We used stratified Q-Q plots and Fisher test to assess the differential enrichment of SNPs mapping to specific categories of enhancers. We find that BRD4 is the key discriminant of tissue-specific enhancers, showing that it is more powerful than AR binding information to capture PC specific risk loci, and can be used with similar effect in breast cancer (BC) and applied to other diseases such as schizophrenia. Conclusions: This is the first study to evaluate the enrichment of epigenetic readers in genome-wide associations studies for SNPs within enhancers, and provides a powerful tool for enriching and prioritizing PC and BC genetic risk loci. Our study represents a proof of principle applicable to other diseases and traits that can be used to redefine molecular mechanisms of human phenotypic variation.
Published: 2017

29. Lung Cancer Among Firefighters: Smoking-Adjusted Risk Estimates in a Pooled Analysis of Case-Control Studies

Author: Bigert, C, Gustavsson, P, Straif, K, Taeger, D, Pesch, B, Kendzia, B, Schuz, J, Stucker, I, Guida, F, Bruske, I, Wichmann, H E, Pesatori, A C, Landi, M T, Caporaso, N, Tse, L A, Yu, I T, Siemiatycki, J, Lavoue, J, Richiardi, L, Mirabelli, D, Simonato, L, Jockel, K H, Ahrens, W, Pohlabeln, H, Tardon, A, Zaridze, D, Field, J K, t Mannetje, A, Pearce, N, McLaughlin, J, Demers, P, Szeszenia-Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Stanescu Dumitru, R, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Peters, S, Vermeulen, R, Kromhout, H, Bruning, T, Olsson, A C, Bigert, C, Gustavsson, P, Straif, K, Taeger, D, Pesch, B, Kendzia, B, Schuz, J, Stucker, I, Guida, F, Bruske, I, Wichmann, H E, Pesatori, A C, Landi, M T, Caporaso, N, Tse, L A, Yu, I T, Siemiatycki, J, Lavoue, J, Richiardi, L, Mirabelli, D, Simonato, L, Jockel, K H, Ahrens, W, Pohlabeln, H, Tardon, A, Zaridze, D, Field, J K, t Mannetje, A, Pearce, N, McLaughlin, J, Demers, P, Szeszenia-Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Stanescu Dumitru, R, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Peters, S, Vermeulen, R, Kromhout, H, Bruning, T, and Olsson, A C
Abstract: OBJECTIVES: The aim of this study was to explore lung cancer risk among firefighters, with adjustment for smoking. METHODS: We used pooled information from the SYNERGY project including 14 case-control studies conducted in Europe, Canada, New Zealand, and China, with lifetime work histories and smoking habits for 14,748 cases of lung cancer and 17,543 controls. We estimated odds ratios by unconditional logistic regression with adjustment for smoking and having ever been employed in a job known to present an excess risk of lung cancer. RESULTS: There was no increased lung cancer risk overall or by specific cell type among firefighters (n = 190), neither before nor after smoking adjustment. We observed no significant exposure-response relationship in terms of work duration. CONCLUSIONS: We found no evidence of an excess lung cancer risk related to occupational exposure as a firefighter.
Published: 2016

30. Lung Cancer Among Firefighters: Smoking-Adjusted Risk Estimates in a Pooled Analysis of Case-Control Studies

Author: LS IRAS EEPI EXAS (Arb.hyg+bl.st.kar.), LS IRAS EEPI GRA (Gezh.risico-analyse), dIRAS RA-2, dIRAS RA-I&I RA, Bigert, C, Gustavsson, P, Straif, K, Taeger, D, Pesch, B, Kendzia, B, Schuz, J, Stucker, I, Guida, F, Bruske, I, Wichmann, H E, Pesatori, A C, Landi, M T, Caporaso, N, Tse, L A, Yu, I T, Siemiatycki, J, Lavoue, J, Richiardi, L, Mirabelli, D, Simonato, L, Jockel, K H, Ahrens, W, Pohlabeln, H, Tardon, A, Zaridze, D, Field, J K, t Mannetje, A, Pearce, N, McLaughlin, J, Demers, P, Szeszenia-Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Stanescu Dumitru, R, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Peters, S, Vermeulen, R, Kromhout, H, Bruning, T, Olsson, A C, LS IRAS EEPI EXAS (Arb.hyg+bl.st.kar.), LS IRAS EEPI GRA (Gezh.risico-analyse), dIRAS RA-2, dIRAS RA-I&I RA, Bigert, C, Gustavsson, P, Straif, K, Taeger, D, Pesch, B, Kendzia, B, Schuz, J, Stucker, I, Guida, F, Bruske, I, Wichmann, H E, Pesatori, A C, Landi, M T, Caporaso, N, Tse, L A, Yu, I T, Siemiatycki, J, Lavoue, J, Richiardi, L, Mirabelli, D, Simonato, L, Jockel, K H, Ahrens, W, Pohlabeln, H, Tardon, A, Zaridze, D, Field, J K, t Mannetje, A, Pearce, N, McLaughlin, J, Demers, P, Szeszenia-Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Stanescu Dumitru, R, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Peters, S, Vermeulen, R, Kromhout, H, Bruning, T, and Olsson, A C
Published: 2016

31. Lung Cancer Among Firefighters: Smoking-Adjusted Risk Estimates in a Pooled Analysis of Case-Control Studies

Author: LS IRAS EEPI EXAS (Arb.hyg+bl.st.kar.), LS IRAS EEPI GRA (Gezh.risico-analyse), dIRAS RA-2, dIRAS RA-I&I RA, Bigert, C, Gustavsson, P, Straif, K, Taeger, D, Pesch, B, Kendzia, B, Schuz, J, Stucker, I, Guida, F, Bruske, I, Wichmann, H E, Pesatori, A C, Landi, M T, Caporaso, N, Tse, L A, Yu, I T, Siemiatycki, J, Lavoue, J, Richiardi, L, Mirabelli, D, Simonato, L, Jockel, K H, Ahrens, W, Pohlabeln, H, Tardon, A, Zaridze, D, Field, J K, t Mannetje, A, Pearce, N, McLaughlin, J, Demers, P, Szeszenia-Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Stanescu Dumitru, R, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Peters, S, Vermeulen, R, Kromhout, H, Bruning, T, Olsson, A C, LS IRAS EEPI EXAS (Arb.hyg+bl.st.kar.), LS IRAS EEPI GRA (Gezh.risico-analyse), dIRAS RA-2, dIRAS RA-I&I RA, Bigert, C, Gustavsson, P, Straif, K, Taeger, D, Pesch, B, Kendzia, B, Schuz, J, Stucker, I, Guida, F, Bruske, I, Wichmann, H E, Pesatori, A C, Landi, M T, Caporaso, N, Tse, L A, Yu, I T, Siemiatycki, J, Lavoue, J, Richiardi, L, Mirabelli, D, Simonato, L, Jockel, K H, Ahrens, W, Pohlabeln, H, Tardon, A, Zaridze, D, Field, J K, t Mannetje, A, Pearce, N, McLaughlin, J, Demers, P, Szeszenia-Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Stanescu Dumitru, R, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Peters, S, Vermeulen, R, Kromhout, H, Bruning, T, and Olsson, A C
Published: 2016

32. Lung Cancer Among Firefighters: Smoking-Adjusted Risk Estimates in a Pooled Analysis of Case-Control Studies

Author: LS IRAS EEPI EXAS (Arb.hyg+bl.st.kar.), LS IRAS EEPI GRA (Gezh.risico-analyse), dIRAS RA-2, dIRAS RA-I&I RA, Bigert, C, Gustavsson, P, Straif, K, Taeger, D, Pesch, B, Kendzia, B, Schuz, J, Stucker, I, Guida, F, Bruske, I, Wichmann, H E, Pesatori, A C, Landi, M T, Caporaso, N, Tse, L A, Yu, I T, Siemiatycki, J, Lavoue, J, Richiardi, L, Mirabelli, D, Simonato, L, Jockel, K H, Ahrens, W, Pohlabeln, H, Tardon, A, Zaridze, D, Field, J K, t Mannetje, A, Pearce, N, McLaughlin, J, Demers, P, Szeszenia-Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Stanescu Dumitru, R, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Peters, S, Vermeulen, R, Kromhout, H, Bruning, T, Olsson, A C, LS IRAS EEPI EXAS (Arb.hyg+bl.st.kar.), LS IRAS EEPI GRA (Gezh.risico-analyse), dIRAS RA-2, dIRAS RA-I&I RA, Bigert, C, Gustavsson, P, Straif, K, Taeger, D, Pesch, B, Kendzia, B, Schuz, J, Stucker, I, Guida, F, Bruske, I, Wichmann, H E, Pesatori, A C, Landi, M T, Caporaso, N, Tse, L A, Yu, I T, Siemiatycki, J, Lavoue, J, Richiardi, L, Mirabelli, D, Simonato, L, Jockel, K H, Ahrens, W, Pohlabeln, H, Tardon, A, Zaridze, D, Field, J K, t Mannetje, A, Pearce, N, McLaughlin, J, Demers, P, Szeszenia-Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Stanescu Dumitru, R, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Peters, S, Vermeulen, R, Kromhout, H, Bruning, T, and Olsson, A C
Published: 2016

33. Genome-wide meta-analysis reveals common splice site acceptor variant in CHRNA4 associated with nicotine dependence

Author: University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Clinicum, Hancock, D. B., Reginsson, G. W., Gaddis, N. C., Chen, X., Saccone, N. L., Lutz, S. M., Qaiser, Beenish, Sherva, R., Steinberg, S., Zink, F., Stacey, S. N., Glasheen, C., Chen, J., Gu, F., Frederiksen, B. N., Loukola, A., Gudbjartsson, D. F., Brueske, I., Landi, M. T., Bickeboeller, H., Madden, P., Farrer, L., Kaprio, J., Kranzler, H. R., Gelernter, J., Baker, T. B., Kraft, P., Amos, C. I., Caporaso, N. E., Hokanson, J. E., Bierut, L. J., Thorgeirsson, T. E., Johnson, E. O., Stefansson, K., University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Clinicum, Hancock, D. B., Reginsson, G. W., Gaddis, N. C., Chen, X., Saccone, N. L., Lutz, S. M., Qaiser, Beenish, Sherva, R., Steinberg, S., Zink, F., Stacey, S. N., Glasheen, C., Chen, J., Gu, F., Frederiksen, B. N., Loukola, A., Gudbjartsson, D. F., Brueske, I., Landi, M. T., Bickeboeller, H., Madden, P., Farrer, L., Kaprio, J., Kranzler, H. R., Gelernter, J., Baker, T. B., Kraft, P., Amos, C. I., Caporaso, N. E., Hokanson, J. E., Bierut, L. J., Thorgeirsson, T. E., Johnson, E. O., and Stefansson, K.
Abstract: We conducted a 1000 Genomes-imputed genome-wide association study (GWAS) meta-analysis for nicotine dependence, defined by the Fagerstrom Test for Nicotine Dependence in 17 074 ever smokers from five European-ancestry samples. We followed up novel variants in 7469 ever smokers from five independent European-ancestry samples. We identified genome-wide significant association in the alpha-4 nicotinic receptor subunit (CHRNA4) gene on chromosome 20q13: lowest P = 8.0 x 10(-9) across all the samples for rs2273500-C (frequency = 0.15; odds ratio = 1.12 and 95% confidence interval = 1.08-1.17 for severe vs mild dependence). rs2273500-C, a splice site acceptor variant resulting in an alternate CHRNA4 transcript predicted to be targeted for nonsense-mediated decay, was associated with decreased CHRNA4 expression in physiologically normal human brains (lowest P = 7.3 x 10(-4)). Importantly, rs2273500-C was associated with increased lung cancer risk (N = 28 998, odds ratio = 1.06 and 95% confidence interval = 1.00-1.12), likely through its effect on smoking, as rs2273500-C was no longer associated with lung cancer after adjustment for smoking. Using criteria for smoking behavior that encompass more than the single 'cigarettes per day' item, we identified a common CHRNA4 variant with important regulatory properties that contributes to nicotine dependence and smoking-related consequences.
Published: 2015

34. Development of an algorithm for the management of cervical lymphadenopathy in children: Consensus of the Italian Society of Preventive and Social Pediatrics, jointly with the Italian Society of Pediatric Infectious Diseases and the Italian Society of Pediatric Otorhinolaryngology

Author: Chiappini, E, Camaioni, A, Benazzo, M, Biondi, A, Bottero, S, De Masi, S, Di Mauro, G, Doria, M, Esposito, S, Felisati, G, Felisati, D, Festini, F, Gaini, R, Galli, L, Gambini, C, Gianelli, U, Landi, M, Lucioni, M, Mansi, N, Mazzantini, R, Marchisio, P, Marseglia, G, Miniello, V, Nicola, M, Novelli, A, Paulli, M, Picca, M, Pillon, M, Pisani, P, Pipolo, C, Principi, N, Sardi, I, Succo, G, Tomà, P, Tortoli, E, Tucci, F, Varricchio, A, de Martino, M, Chiappini, E, Camaioni, A, Benazzo, M, Biondi, A, Bottero, S, De Masi, S, Di Mauro, G, Doria, M, Esposito, S, Felisati, G, Felisati, D, Festini, F, Gaini, R, Galli, L, Gambini, C, Gianelli, U, Landi, M, Lucioni, M, Mansi, N, Mazzantini, R, Marchisio, P, Marseglia, G, Miniello, V, Nicola, M, Novelli, A, Paulli, M, Picca, M, Pillon, M, Pisani, P, Pipolo, C, Principi, N, Sardi, I, Succo, G, Tomà, P, Tortoli, E, Tucci, F, Varricchio, A, and de Martino, M
Abstract: Cervical lymphadenopathy is a common disorder in children due to a wide spectrum of disorders. On the basis of a complete history and physical examination, paediatricians have to select, among the vast majority of children with a benign self-limiting condition, those at risk for other, more complex, diseases requiring laboratory tests, imaging and, finally, tissue sampling. At the same time, they should avoid expensive and invasive examinations when unnecessary. The Italian Society of Preventive and Social Pediatrics, jointly with the Italian Society of Pediatric Infectious Diseases, the Italian Society of Pediatric Otorhinolaryngology, and other Scientific Societies, issued a National Consensus document, based on the most recent literature findings, including an algorithm for the management of cervical lymphadenopathy in children. Methods: The Consensus Conference method was used, following the Italian National Plan Guidelines. Relevant publications in English were identified through a systematic review of MEDLINE and the Cochrane Database of Systematic Reviews from their inception through March 21, 2014. Results: Basing on literature results, an algorithm was developed, including several possible clinical scenarios. Situations requiring a watchful waiting strategy, those requiring an empiric antibiotic therapy, and those necessitating a prompt diagnostic workup, considering the risk for a severe underling disease, have been identified. Conclusion: The present algorithm is a practice tool for the management of pediatric cervical lymphadenopathy in the hospital and the ambulatory settings. A multidisciplinary approach is paramount. Further studies are required for its validation in the clinical field.
Published: 2015

35. MC1R variants increased the risk of sporadic cutaneous melanoma in darker-pigmented Caucasians: A pooled-analysis from the M-SKIP project

Author: Pasquali, E, García Borrón, J, Fargnoli, M, Gandini, S, Maisonneuve, P, Bagnardi, V, Specchia, C, Liu, F, Kayser, M, Nijsten, T, Nagore, E, Kumar, R, Hansson, J, Kanetsky, P, Ghiorzo, P, Debniak, T, Branicki, W, Gruis, N, Han, J, Dwyer, T, Blizzard, L, Landi, M, Palmieri, G, Ribas, G, Stratigos, A, Council, M, Autier, P, Little, J, Newton Bishop, J, Sera, F, Raimondi, S, Caini, S, Hofman, A, Uitterlinden, A, Scherer, D, Hoiom, V, Pastorino, L, Cochrane, J, Fernandez De Misa, R, Morling, N, Johansen, P, Pfeiffer, R, Kypreou, K, Bowcock, A, Cornelius, L, Motokawa, T, Anno, S, Helsing, P, Andresen, P, Wong, T, Wong, T., BAGNARDI, VINCENZO, Pasquali, E, García Borrón, J, Fargnoli, M, Gandini, S, Maisonneuve, P, Bagnardi, V, Specchia, C, Liu, F, Kayser, M, Nijsten, T, Nagore, E, Kumar, R, Hansson, J, Kanetsky, P, Ghiorzo, P, Debniak, T, Branicki, W, Gruis, N, Han, J, Dwyer, T, Blizzard, L, Landi, M, Palmieri, G, Ribas, G, Stratigos, A, Council, M, Autier, P, Little, J, Newton Bishop, J, Sera, F, Raimondi, S, Caini, S, Hofman, A, Uitterlinden, A, Scherer, D, Hoiom, V, Pastorino, L, Cochrane, J, Fernandez De Misa, R, Morling, N, Johansen, P, Pfeiffer, R, Kypreou, K, Bowcock, A, Cornelius, L, Motokawa, T, Anno, S, Helsing, P, Andresen, P, Wong, T, Wong, T., and BAGNARDI, VINCENZO
Abstract: The MC1R gene is a key regulator of skin pigmentation. We aimed to evaluate the association between MC1R variants and the risk of sporadic cutaneous melanoma (CM) within the M-SKIP project, an international pooled-analysis on MC1R, skin cancer and phenotypic characteristics. Data included 5,160 cases and 12,119 controls from 17 studies. We calculated a summary odds ratio (SOR) for the association of each of the nine most studied MC1R variants and of variants combined with CM by using random-effects models. Stratified analysis by phenotypic characteristics were also performed. Melanoma risk increased with presence of any of the main MC1R variants: the SOR for each variant ranged from 1.47 (95%CI: 1.17-1.84) for V60L to 2.74 (1.53-4.89) for D84E. Carriers of any MC1R variant had a 66% higher risk of developing melanoma compared with wildtype subjects (SOR; 95%CI: 1.66; 1.41-1.96) and the risk attributable to MC1R variants was 28%. When taking into account phenotypic characteristics, we found that MC1R-associated melanoma risk increased only for darker-pigmented Caucasians: SOR (95%CI) was 3.14 (2.06-4.80) for subjects with no freckles, no red hair and skin Type III/IV. Our study documents the important role of all the main MC1R variants in sporadic CM and suggests that they have a direct effect on melanoma risk, independently on the phenotypic characteristics of carriers. This is of particular importance for assessing preventive strategies, which may be directed to darker-pigmented Caucasians with MC1R variants as well as to lightly pigmented, fairskinned subjects.
Published: 2015

36. Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma

Author: Law, M., Bishop, D., Lee, J., Brossard, M., Martin, N., Moses, Eric, Song, F., Barrett, J., Kumar, R., Easton, D., Pharoah, P., Swerdlow, A., Kypreou, K., Taylor, J., Harland, M., Randerson-Moor, J., Akslen, L., Andresen, P., Avril, M., Azizi, E., Scarrà, G., Brown, K., Debniak, T., Duffy, D., Elder, D., Fang, S., Friedman, E., Galan, P., Ghiorzo, P., Gillanders, E., Goldstein, A., Gruis, N., Hansson, J., Helsing, P., Hocevar, M., Höiom, V., Ingvar, C., Kanetsky, P., Chen, W., Landi, M., Lang, J., Lathrop, G., Lubinski, J., MacKie, R., Mann, G., Molven, A., Montgomery, G., Novakovic, S., Olsson, H., Puig, S., Puig-Butille, J., Qureshi, A., Radford-Smith, G., Van Der Stoep, N., Van Doorn, R., Whiteman, D., Craig, J., Schadendorf, D., Simms, L., Burdon, K., Nyholt, D., Pooley, K., Orr, N., Stratigos, A., Cust, A., Ward, S., Hayward, N., Han, J., Schulze, H., Dunning, A., Bishop, J., Demenais, F., Amos, C., MacGregor, S., Iles, M., Law, M., Bishop, D., Lee, J., Brossard, M., Martin, N., Moses, Eric, Song, F., Barrett, J., Kumar, R., Easton, D., Pharoah, P., Swerdlow, A., Kypreou, K., Taylor, J., Harland, M., Randerson-Moor, J., Akslen, L., Andresen, P., Avril, M., Azizi, E., Scarrà, G., Brown, K., Debniak, T., Duffy, D., Elder, D., Fang, S., Friedman, E., Galan, P., Ghiorzo, P., Gillanders, E., Goldstein, A., Gruis, N., Hansson, J., Helsing, P., Hocevar, M., Höiom, V., Ingvar, C., Kanetsky, P., Chen, W., Landi, M., Lang, J., Lathrop, G., Lubinski, J., MacKie, R., Mann, G., Molven, A., Montgomery, G., Novakovic, S., Olsson, H., Puig, S., Puig-Butille, J., Qureshi, A., Radford-Smith, G., Van Der Stoep, N., Van Doorn, R., Whiteman, D., Craig, J., Schadendorf, D., Simms, L., Burdon, K., Nyholt, D., Pooley, K., Orr, N., Stratigos, A., Cust, A., Ward, S., Hayward, N., Han, J., Schulze, H., Dunning, A., Bishop, J., Demenais, F., Amos, C., MacGregor, S., and Iles, M.
Abstract: Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5 × 10−8), as did 2 previously reported but unreplicated loci and all 13 established loci. Newly associated SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes in the associated regions, including one involved in telomere biology.
Published: 2015

37. The effect on melanoma risk of genes previously associated with telomere length

Author: Iles, M., Bishop, D., Taylor, J., Hayward, N., Brossard, M., Cust, A., Dunning, A., Lee, J., Moses, Eric, Akslen, L., Andresen, P., Avril, M., Azizi, E., Scarra, G., Brown, K., Debniak, T., Elder, D., Friedman, E., Ghiorzo, P., Gillanders, E., Goldstein, A., Gruis, N., Hansson, J., Harland, M., Helsing, P., Hoçevar, M., Hoiom, V., Ingvar, C., Kanetsky, P., Landi, M., Lang, J., Lathrop, G., Lubinski, J., Mackie, R., Martin, N., Molven, A., Montgomery, G., Novakovi, S., Olsson, H., Puig, S., Puig-Butille, J., Radford-Smith, G., Randerson-Moor, J., Van Der Stoep, N., Van Doorn, R., Whiteman, D., Macgregor, S., Pooley, K., Ward, S., Mann, G., Amos, C., Pharoah, P., Demenais, F., Law, M., Bishop, J., Barrett, J., Iles, M., Bishop, D., Taylor, J., Hayward, N., Brossard, M., Cust, A., Dunning, A., Lee, J., Moses, Eric, Akslen, L., Andresen, P., Avril, M., Azizi, E., Scarra, G., Brown, K., Debniak, T., Elder, D., Friedman, E., Ghiorzo, P., Gillanders, E., Goldstein, A., Gruis, N., Hansson, J., Harland, M., Helsing, P., Hoçevar, M., Hoiom, V., Ingvar, C., Kanetsky, P., Landi, M., Lang, J., Lathrop, G., Lubinski, J., Mackie, R., Martin, N., Molven, A., Montgomery, G., Novakovi, S., Olsson, H., Puig, S., Puig-Butille, J., Radford-Smith, G., Randerson-Moor, J., Van Der Stoep, N., Van Doorn, R., Whiteman, D., Macgregor, S., Pooley, K., Ward, S., Mann, G., Amos, C., Pharoah, P., Demenais, F., Law, M., Bishop, J., and Barrett, J.
Abstract: Telomere length has been associated with risk of many cancers, but results are inconsistent. Seven single nucleotide polymorphisms (SNPs) previously associated with mean leukocyte telomere length were either genotyped or well-imputed in 11108 case patients and 13933 control patients from Europe, Israel, the United States and Australia, four of the seven SNPs reached a P value under .05 (two-sided). A genetic score that predicts telomere length, derived from these seven SNPs, is strongly associated (P = 8.92x10-9, two-sided) with melanoma risk. This demonstrates that the previously observed association between longer telomere length and increased melanoma risk is not attributable to confounding via shared environmental effects (such as ultraviolet exposure) or reverse causality. We provide the first proof that multiple germline genetic determinants of telomere length influence cancer risk.
Published: 2014

38. Melanocortin-1 receptor, skin cancer and phenotypic characteristics (M-SKIP) project: study design and methods for pooling results of genetic epidemiological studies

Author: Raimondi, S, Gandini, S, Fargnoli, M, Bagnardi, V, Maisonneuve, P, Specchia, C, Kumar, R, Nagore, E, Han, J, Hansson, J, Kanetsky, P, Ghiorzo, P, Gruis, N, Dwyer, T, Blizzard, L, Fernandez de Misa, R, Branicki, W, Debniak, T, Morling, N, Landi, M, Palmieri, G, Ribas, G, Stratigos, A, Cornelius, L, Motokawa, T, Anno, S, Helsing, P, Wong, T, Autier, P, García Borrón, J, Little, J, Newton Bishop, J, Sera, F, Liu, F, Kayser, M, Nijsten, T, Study Group, G, BAGNARDI, VINCENZO, Study Group, G., Raimondi, S, Gandini, S, Fargnoli, M, Bagnardi, V, Maisonneuve, P, Specchia, C, Kumar, R, Nagore, E, Han, J, Hansson, J, Kanetsky, P, Ghiorzo, P, Gruis, N, Dwyer, T, Blizzard, L, Fernandez de Misa, R, Branicki, W, Debniak, T, Morling, N, Landi, M, Palmieri, G, Ribas, G, Stratigos, A, Cornelius, L, Motokawa, T, Anno, S, Helsing, P, Wong, T, Autier, P, García Borrón, J, Little, J, Newton Bishop, J, Sera, F, Liu, F, Kayser, M, Nijsten, T, Study Group, G, BAGNARDI, VINCENZO, and Study Group, G.
Abstract: BACKGROUND: For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia. Design and methods Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with randomeffects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling. DISCUSSION: Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields.
Published: 2012

39. Alcohol consumption and lung cancer risk in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study

Author: Bagnardi, V, Randi, G, Lubin, J, Consonni, D, Lam, T, Subar, A, Goldstein, A, Wacholder, S, Bergen, A, Tucker, M, Decarli, A, Caporaso, N, Bertazzi, P, Landi, M, BAGNARDI, VINCENZO, Lam, TK, Subar, AF, Goldstein, AM, Bergen, AW, Tucker, MA, Caporaso, NE, Bertazzi, PA, Landi, MT, Bagnardi, V, Randi, G, Lubin, J, Consonni, D, Lam, T, Subar, A, Goldstein, A, Wacholder, S, Bergen, A, Tucker, M, Decarli, A, Caporaso, N, Bertazzi, P, Landi, M, BAGNARDI, VINCENZO, Lam, TK, Subar, AF, Goldstein, AM, Bergen, AW, Tucker, MA, Caporaso, NE, Bertazzi, PA, and Landi, MT
Abstract: The authors investigated the relation between alcohol consumption and lung cancer risk in the Environment and Genetics in Lung Cancer Etiology (EAGLE) Study, a population-based case-control study. Between 2002 and 2005, 2,100 patients with primary lung cancer were recruited from 13 hospitals within the Lombardy region of Italy and were frequency-matched on sex, area of residence, and age to 2,120 randomly selected controls. Alcohol consumption during adulthood was assessed in 1,855 cases and 2,065 controls. Data on lifetime tobacco smoking, diet, education, and anthropometric measures were collected. Adjusted odds ratios and 95% confidence intervals for categories of mean daily ethanol intake were calculated using unconditional logistic regression. Overall, both nondrinkers (odds ratio = 1.42, 95% confidence interval: 1.03, 2.01) and very heavy drinkers (>/=60 g/day; odds ratio = 1.44, 95% confidence interval: 1.01, 2.07) were at significantly greater risk than very light drinkers (0.1-4.9 g/day). The alcohol effect was modified by smoking behavior, with no excess risk being observed in never smokers. In summary, heavy alcohol consumption was a risk factor for lung cancer among smokers in this study. Although residual confounding by tobacco smoking cannot be ruled out, this finding may reflect interplay between alcohol and smoking, emphasizing the need for preventive measures.
Published: 2010

40. Intakes of red meat, processed meat, and meat mutagens increase lung cancer risk

Author: Lam, T, Cross, A, Consonni, D, Randi, G, Bagnardi, V, Bertazzi, P, Caporaso, N, Sinha, R, Subar, A, Landi, M, Lam, TK, Cross, AJ, Bertazzi, PA, Caporaso, NE, Subar, AF, Landi, MT, BAGNARDI, VINCENZO, Lam, T, Cross, A, Consonni, D, Randi, G, Bagnardi, V, Bertazzi, P, Caporaso, N, Sinha, R, Subar, A, Landi, M, Lam, TK, Cross, AJ, Bertazzi, PA, Caporaso, NE, Subar, AF, Landi, MT, and BAGNARDI, VINCENZO
Abstract: Red and processed meat intake may increase lung cancer risk. However, the epidemiologic evidence is inconsistent and few studies have evaluated the role of meat mutagens formed during high cooking temperatures. We investigated the association of red meat, processed meat, and meat mutagen intake with lung cancer risk in Environment And Genetics in Lung cancer Etiology, a population-based case-control study. Primary lung cancer cases (n = 2,101) were recruited from 13 hospitals within the Lombardy region of Italy examining approximately 80% of the cases from the area. Noncancer population controls (n = 2,120), matched to cases on gender, residence, and age, were randomly selected from the same catchment area. Diet was assessed in 1,903 cases and 2,073 controls and used in conjunction with a meat mutagen database to estimate intake of heterocyclic amines (HCA) and benzo(a)pyrene (BaP). Multivariable odds ratios (OR) and 95% confidence intervals (95% CI) for sex-specific tertiles of intake were calculated using unconditional logistic regression. Red and processed meat were positively associated with lung cancer risk (highest-versus-lowest tertile: OR, 1.8; 95% CI, 1.5-2.2; P trend < 0.001 and OR, 1.7; 95% CI, 1.4-2.1; P trend < 0.001, respectively); the risks were strongest among never smokers (OR, 2.4; 95% CI, 1.4-4.0; P trend = 0.001 and OR, 2.5; 95% CI, 1.5-4.2; P trend = 0.001, respectively). HCAs and BaP were significantly associated with increased risk of lung cancer. When separated by histology, significant positive associations for both meat groups were restricted to adenocarcinoma and squamous cell carcinoma but not small cell carcinoma of the lung. In summary, red meat, processed meat, and meat mutagens were independently associated with increased risk of lung cancer.
Published: 2009

41. The 'Fish & Chips' project: Microarrays as a tool for the identification of marine organisms in biodiversity and ecosystem research

Author: Kochzius, M., Kappel, K., Döbitz, L., Silkenbäumer, N., Nölte, M., Weber, Harald, Hjörleifsdottir, S., Marteinsson, V., Hreggvidsson, G., Planes, S., Tinti, F., Magoulas, A., Vazquez, E., Turan, C., Medlin, Linda, Metfies, Katja, Gescher, Christine, Cariani, A., Landi, M., Hervet, C., Falgueras, D., Antoniou, A., Bertasi, F., Srujana, C., Blohm, D., Kochzius, M., Kappel, K., Döbitz, L., Silkenbäumer, N., Nölte, M., Weber, Harald, Hjörleifsdottir, S., Marteinsson, V., Hreggvidsson, G., Planes, S., Tinti, F., Magoulas, A., Vazquez, E., Turan, C., Medlin, Linda, Metfies, Katja, Gescher, Christine, Cariani, A., Landi, M., Hervet, C., Falgueras, D., Antoniou, A., Bertasi, F., Srujana, C., and Blohm, D.
Published: 2007

42. The 'Fish & Chips' project: Microarrays as a tool for the identification of marine organisms in biodiversity and ecosystem research

Author: Kochzius, M., Kappel, K., Döbitz, L., Silkenbäumer, N., Nölte, M., Weber, Harald, Hjörleifsdottir, S., Marteinsson, V., Hreggvidsson, G., Planes, S., Tinti, F., Magoulas, A., Vazquez, E., Turan, C., Medlin, Linda, Metfies, Katja, Gescher, Christine, Cariani, A., Landi, M., Hervet, C., Falgueras, D., Antoniou, A., Bertasi, F., Srujana, C., Blohm, D., Kochzius, M., Kappel, K., Döbitz, L., Silkenbäumer, N., Nölte, M., Weber, Harald, Hjörleifsdottir, S., Marteinsson, V., Hreggvidsson, G., Planes, S., Tinti, F., Magoulas, A., Vazquez, E., Turan, C., Medlin, Linda, Metfies, Katja, Gescher, Christine, Cariani, A., Landi, M., Hervet, C., Falgueras, D., Antoniou, A., Bertasi, F., Srujana, C., and Blohm, D.
Published: 2007

43. Fish & Chips: Towards DNA chip technology as a standard analytical tool for the identification of marine organisms in biodiversity and ecosystem research

Author: Kochzius, M., Kappel, K., Silkenbäumer, N., Nölte, M., Weber, Harald, Hjörleifsdottir, S., Marteinsson, V. P., Planes, S., Tinti, F., Magoulas, A., Garcia Vazquez, E., Turan, C., Medlin, Linda, Metfies, Katja, Gescher, Christine, Cariani, A., Landi, M., Hervet, C., Campo Falgueras, D., Antoniou, A., Bertasi, F., Blohm, D., Kochzius, M., Kappel, K., Silkenbäumer, N., Nölte, M., Weber, Harald, Hjörleifsdottir, S., Marteinsson, V. P., Planes, S., Tinti, F., Magoulas, A., Garcia Vazquez, E., Turan, C., Medlin, Linda, Metfies, Katja, Gescher, Christine, Cariani, A., Landi, M., Hervet, C., Campo Falgueras, D., Antoniou, A., Bertasi, F., and Blohm, D.
Published: 2006

44. Fish & Chips: Towards DNA chip technology as a standard analytical tool for the identification of marine organisms in biodiversity and ecosystem research

Author: Kochzius, M., Kappel, K., Silkenbäumer, N., Nölte, M., Weber, Harald, Hjörleifsdottir, S., Marteinsson, V. P., Planes, S., Tinti, F., Magoulas, A., Garcia Vazquez, E., Turan, C., Medlin, Linda, Metfies, Katja, Gescher, Christine, Cariani, A., Landi, M., Hervet, C., Campo Falgueras, D., Antoniou, A., Bertasi, F., Blohm, D., Kochzius, M., Kappel, K., Silkenbäumer, N., Nölte, M., Weber, Harald, Hjörleifsdottir, S., Marteinsson, V. P., Planes, S., Tinti, F., Magoulas, A., Garcia Vazquez, E., Turan, C., Medlin, Linda, Metfies, Katja, Gescher, Christine, Cariani, A., Landi, M., Hervet, C., Campo Falgueras, D., Antoniou, A., Bertasi, F., and Blohm, D.
Published: 2006

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