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38 results on '"Cannon-Albright Lisa A"'

1. A likely HOXC4 predisposition variant for Chiari malformations

Author: Brockmeyer, Douglas L., Cheshier, Samuel H., Stevens, Jeff, Facelli, Julio C., Rowe, Kerry, Heiss, John D., Musolf, Anthony, Viskochil, David H., Allen-Brady, Kristina L., and Cannon-Albright, Lisa A.
Subjects: Clinical Article, General Medicine
Abstract: OBJECTIVE Inherited variants predisposing patients to type 1 or 1.5 Chiari malformation (CM) have been hypothesized but have proven difficult to confirm. The authors used a unique high-risk pedigree population resource and approach to identify rare candidate variants that likely predispose individuals to CM and protein structure prediction tools to identify pathogenicity mechanisms. METHODS By using the Utah Population Database, the authors identified pedigrees with significantly increased numbers of members with CM diagnosis. From a separate DNA biorepository of 451 samples from CM patients and families, 32 CM patients belonging to 1 or more of 24 high-risk Chiari pedigrees were identified. Two high-risk pedigrees had 3 CM-affected relatives, and 22 pedigrees had 2 CM-affected relatives. To identify rare candidate predisposition gene variants, whole-exome sequence data from these 32 CM patients belonging to 24 CM-affected related pairs from high-risk pedigrees were analyzed. The I-TASSER package for protein structure prediction was used to predict the structures of both the wild-type and mutant proteins found here. RESULTS Sequence analysis of the 24 affected relative pairs identified 38 rare candidate Chiari predisposition gene variants that were shared by at least 1 CM-affected pair from a high-risk pedigree. The authors found a candidate variant in HOXC4 that was shared by 2 CM-affected patients in 2 independent pedigrees. All 4 of these CM cases, 2 in each pedigree, exhibited a specific craniocervical bony phenotype defined by a clivoaxial angle less than 125°. The protein structure prediction results suggested that the mutation considered here may reduce the binding affinity of HOXC4 to DNA. CONCLUSIONS Analysis of unique and powerful Utah genetic resources allowed identification of 38 strong candidate CM predisposition gene variants. These variants should be pursued in independent populations. One of the candidates, a rare HOXC4 variant, was identified in 2 high-risk CM pedigrees, with this variant possibly predisposing patients to a Chiari phenotype with craniocervical kyphosis.
Published: 2022

2. KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness

Author: Lin, Hui-Yi, Huang, Po-Yu, Cheng, Chia-Ho, Tung, Heng-Yuan, Fang, Zhide, Berglund, Anders E, Chen, Ann, French-Kwawu, Jennifer, Harris, Darian, Pow-Sang, Julio, Yamoah, Kosj, Cleveland, John L, Awasthi, Shivanshu, Rounbehler, Robert J, Gerke, Travis, Dhillon, Jasreman, Eeles, Rosalind, Kote-Jarai, Zsofia, Muir, Kenneth, UKGPCS Collaborators, Schleutker, Johanna, Pashayan, Nora, APCB (Australian Prostate Cancer BioResource), Neal, David E, Nielsen, Sune F, Nordestgaard, Børge G, Gronberg, Henrik, Wiklund, Fredrik, Giles, Graham G, Haiman, Christopher A, Travis, Ruth C, Stanford, Janet L, Kibel, Adam S, Cybulski, Cezary, Khaw, Kay-Tee, Maier, Christiane, Thibodeau, Stephen N, Teixeira, Manuel R, Cannon-Albright, Lisa, Brenner, Hermann, Kaneva, Radka, Pandha, Hardev, PRACTICAL Consortium, Srinivasan, Srilakshmi, Clements, Judith, Batra, Jyotsna, Park, Jong Y, and Apollo - University of Cambridge Repository
Subjects: Male, Genotype, Biomarkers, Tumor, Humans, Prostatic Neoplasms, Epistasis, Genetic, Genetic Predisposition to Disease, Kallikreins, Prostate-Specific Antigen, urologic and male genital diseases, Polymorphism, Single Nucleotide
Abstract: Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP-SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10-9) and 3145 (P < 1 × 10-5) SNP-SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene-gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP-SNP interactions were supported by gene expression and protein-protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.
Published: 2021

3. The effect of sample size on polygenic hazard models for prostate cancer

Author: Karunamuni, Roshan A, Huynh-Le, Minh-Phuong, Fan, Chun C, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, ZSofia, Amin Al Olama, Ali, Benlloch Garcia, Sara, Muir, Kenneth, Gronberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo LJ, Nordestgaard, Børge G, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Brenner, Hermann, Schöttker, Ben, Holleczek, Bernd, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda, Australian Prostate Cancer BioResource (APCB), Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, and PRACTICAL Consortium
Subjects: Male, Urologic Diseases, Genetics & Heredity, Multifactorial Inheritance, Clinical Trials as Topic, Aging, Prostate Cancer, Clinical Sciences, Australian Prostate Cancer BioResource, Prostatic Neoplasms, Single Nucleotide, Genetic, Models, Sample Size, Genetics, PRACTICAL Consortium, Humans, Polymorphism, Proportional Hazards Models, Genome-Wide Association Study, Cancer
Abstract: We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.
Published: 2020

4. Identification and genomic analysis of pedigrees with exceptional longevity identifies candidate rare variants

Author: Miller, Justin B, Ward, Elizabeth, Staley, Lyndsay A, Stevens, Jeffrey, Teerlink, Craig C, Tavana, Justina P, Cloward, Matthew, Page, Madeline, Dayton, Louisa, Alzheimer's Disease Genetics Consortium, Cannon-Albright, Lisa A, and Kauwe, John SK
Subjects: Male, Aging, Neurology & Neurosurgery, Genotype, Utah population database, Prevention, Longevity, Rare variant sharing, Human Genome, Clinical Sciences, Neurosciences, Genetic Variation, Genomics, Pedigree, Clinical Research, Alzheimer's Disease Genetics Consortium, CCAAT-Enhancer-Binding Proteins, Genetics, Humans, 2.1 Biological and endogenous factors, Female, Generic health relevance, Aetiology, Separase, Aged
Abstract: BackgroundLongevity as a phenotype entails living longer than average and typically includes living without chronic age-related diseases. Recently, several common genetic components to longevity have been identified. This study aims to identify additional genetic variants associated with longevity using unique and powerful analyses of pedigrees with a statistical excess of healthy elderly individuals identified in the Utah Population Database (UPDB).MethodsFrom an existing biorepository of Utah pedigrees, six independent cousin pairs were selected from four extended pedigrees that exhibited an excess of healthy elderly individuals; whole exome sequencing (WES) was performed on two elderly individuals from each pedigree who were either first cousins or first cousins once removed. Rare (
Published: 2020

5. A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data

Author: Huynh-Le, Minh-Phuong, Fan, Chun Chieh, Karunamuni, Roshan, Walsh, Eleanor I, Turner, Emma L, Lane, J Athene, Martin, Richard M, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Parsons, J Kellogg, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, Zsofia, Amin Al Olama, Ali, Benlloch Garcia, Sara, Muir, Kenneth, Grönberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo Lj, Nordestgaard, Børge Grønne, Key, Timothy J, Travis, Ruth C, Pharoah, Paul DP, Pashayan, Nora, Khaw, Kay-Tee, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa A, Brenner, Hermann, Schöttker, Ben, Holleczek, Bernd, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar Kroumov, Kaneva, Radka P, Mitev, Vanio I, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda B, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, Australian Prostate Cancer BioResource (APCB), and PRACTICAL Consortium
Subjects: Urologic Diseases, Aging, Clinical Research, Epidemiology, Prostate Cancer, Prevention, Clinical Trials and Supportive Activities, Australian Prostate Cancer BioResource, PRACTICAL Consortium, equipment and supplies, Medical and Health Sciences, Cancer
Abstract: BackgroundA polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.MethodsUnited Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.ResultsThe expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.ConclusionsPHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.ImpactPersonalized genetic risk assessments could inform prostate cancer screening decisions.
Published: 2020

6. A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data

Author: Huynh-Le, Minh-Phuong, Fan, Chun Chieh, Karunamuni, Roshan, Walsh, Eleanor I, Turner, Emma L, Lane, J Athene, Martin, Richard M, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Parsons, J Kellogg, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, Zsofia, Amin Al Olama, Ali, Benlloch Garcia, Sara, Muir, Kenneth, Grönberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo Lj, Nordestgaard, Børge Grønne, Key, Timothy J, Travis, Ruth C, Pharoah, Paul DP, Pashayan, Nora, Khaw, Kay-Tee, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa A, Brenner, Hermann, Schöttker, Ben, Holleczek, Bernd, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar Kroumov, Kaneva, Radka P, Mitev, Vanio I, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda B, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, Australian Prostate Cancer BioResource (APCB), and PRACTICAL Consortium
Subjects: Male, Urologic Diseases, Aging, Epidemiology, Prostate Cancer, Prevention, Clinical Trials and Supportive Activities, Australian Prostate Cancer BioResource, Prostatic Neoplasms, Middle Aged, equipment and supplies, Medical and Health Sciences, Good Health and Well Being, Clinical Research, PRACTICAL Consortium, Humans, Population Control, Neoplasm Grading, Early Detection of Cancer, Aged, Cancer
Abstract: BackgroundA polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.MethodsUnited Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.ResultsThe expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.ConclusionsPHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.ImpactPersonalized genetic risk assessments could inform prostate cancer screening decisions.
Published: 2020

7. An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

Author: Wu, Lang, Yang, Yaohua, Guo, Xingyi, Shu, Xiao-Ou, Cai, Qiuyin, Shu, Xiang, Li, Bingshan, Tao, Ran, Wu, Chong, Nikas, Jason B., Sun, Yanfa, Zhu, Jingjing, Brenner, Hermann, John, Esther M., Clements, Judith, Grindedal, Eli Marie, Stanford, Janet L., Kote-Jarai, Zsofia, Haiman, Christopher A., Zheng, Wei, Long, Jirong, Eeles, Rosalind A., Henderson, Brian E., Schumacher, Fredrick R., Easton, Douglas, Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth, Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Chanock, Stephen, Gapstur, Susan M., Stevens, Victoria L., Tangen, Catherine M., Batra, Jyotsna, Gronberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie, Wolk, Alicja, West, Catharine, Mucci, Lorelei, Cancel-Tassin, Géraldine, Koutros, Stella, Sorensen, Karina Dalsgaard, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong-Jie, Giles, Graham G., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Cybulski, Cezary, Nordestgaard, Børge G., Maier, Christiane, Kim, Jeri, Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Gamulin, Marija, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Dominguez, Manuela Gago, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Blot, William J., Riboli, Elio, Li, Bingshan [0000-0003-2129-168X], Wu, Chong [0000-0002-8400-1785], Nikas, Jason B. [0000-0001-9703-0422], Roobol, Monique J. [0000-0001-6967-1708], Giles, Graham G. [0000-0003-4946-9099], Park, Jong Y. [0000-0002-6384-6447], Eeles, Rosalind A. [0000-0002-3698-6241], Zheng, Wei [0000-0003-1226-070X], and Apollo - University of Cambridge Repository
Subjects: 631/208, 631/67/68, article, 631/67/2324, urologic and male genital diseases
Abstract: It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.
Published: 2020
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8. Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan

Author: Hollis, Ben, Day, Felix R., Busch, Alexander S., Thompson, Deborah J., Soares, Ana Luiza G., Timmers, Paul R. H. J., Kwong, Alex, Easton, Doug F., Joshi, Peter K., Timpson, Nicholas J., Ong, Ken K., Perry, John R. B., Eeles, Rosalind A., Henderson, Brian E., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Olama, Ali Amin Al, Benlloch, Sara, Muir, Kenneth, Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Chanock, Stephen, Gapstur, Susan, Stevens, Victoria L., Tangen, Catherine M., Batra, Jyotsna, Clements, Judith, Gronberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Wolk, Alicja, West, Catharine, Mucci, Lorelei, Cancel-Tassin, Géraldine, Koutros, Stella, Sorensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong-Jie, Giles, Graham G., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Brenner, Hermann, Maier, Christiane, Kim, Jeri, John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Gago-Dominguez, Manuela, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Tilley, Wayne, Risbridger, Gail P., Horvath, Lisa, Taylor, Renea, Hayes, Vanessa, Butler, Lisa, Yeadon, Trina, Eckert, Allison, Saunders, Pamela, Haynes, Anne-Maree, Papargiris, Melissa, Srinivasan, Srilakshmi, Kedda, Mary-Anne, Moya, Leire, 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., 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., Day, Felix R. [0000-0003-3789-7651], Busch, Alexander S. [0000-0003-4417-569X], Thompson, Deborah J. [0000-0003-1465-5799], Soares, Ana Luiza G. [0000-0003-2763-4647], Timmers, Paul R. H. J. [0000-0002-5197-1267], Kwong, Alex [0000-0003-1953-2771], Easton, Doug F. [0000-0003-2444-3247], Joshi, Peter K. [0000-0002-6361-5059], Timpson, Nicholas J. [0000-0002-7141-9189], Ong, Ken K. [0000-0003-4689-7530], and Apollo - University of Cambridge Repository
Subjects: 631/443/494, 631/208/205/2138, 692/308/2056, 45/43, article, 692/163
Abstract: The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective sample size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes.
Published: 2020

9. Association of Rare Coding Mutations With Alzheimer Disease and Other Dementias Among Adults of European Ancestry

Author: Patel, Devanshi, Mez, Jesse, Vardarajan, Badri N., Staley, Lyndsay, Chung, Jaeyoon, Zhang, Xiaoling, Farrell, John J., Rynkiewicz, Michael J., Cannon-Albright, Lisa A., Teerlink, Craig C., Stevens, Jeffery, Corcoran, Chris, and American Medical Association
Subjects: Introduction, Discussion, Methods, Results, Key Points, References, Abstract, Article Information, Mathematics
Abstract: IMPORTANCE Some of the unexplained heritability of Alzheimer disease (AD) may be due to rare variants whose effects are not captured in genome-wide association studies because very large samples are needed to observe statistically significant associations. OBJECTIVE To identify genetic variants associated with AD risk using a nonstatistical approach. DESIGN, SETTING, AND PARTICIPANTS Genetic association study in which rare variants were identified by whole-exome sequencing in unrelated individuals of European ancestry from the Alzheimer’s Disease Sequencing Project (ADSP). Data were analyzed between March 2017 and September 2018. MAIN OUTCOMES AND MEASURES Minor alleles genome-wide and in 95 genes previously associated with AD, AD-related traits, or other dementias were tabulated and filtered for predicted functional impact and occurrence in participants with AD but not controls. Support for several findings was sought in a whole-exome sequencing data set comprising 19 affected relative pairs from Utah high-risk pedigrees and whole-genome sequencing data sets from the ADSP and Alzheimer’s Disease Neuroimaging Initiative. RESULTS Among 5617 participants with AD (3202 [57.0%] women; mean [SD] age, 76.4 [9.3] years) and 4594 controls (2719 [59.0%] women; mean [SD] age, 86.5 [4.5] years), a total of 24 variants with moderate or high functional impact from 19 genes were observed in 10 or more participants with AD but not in controls. These variants included a missense mutation (rs149307620 [p.A284T], n = 10) in NOTCH3, a gene in which coding mutations are associated with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), that was also identified in 1 participant with AD and 1 participant with mild cognitive impairment in the whole genome sequencing data sets. Four participants with AD carried the TREM2 rs104894002 (p.Q33X) high-impact mutation that, in homozygous form, causes Nasu-Hakola disease, a rare disorder characterized by early-onset dementia and multifocal bone cysts, suggesting an intermediate inheritance model for the mutation. Compared with controls, participants with AD had a significantly higher burden of deleterious rare coding variants in dementia-associated genes (2314 vs 3354 cumulative variants, respectively; P = .006). CONCLUSIONS AND RELEVANCE Different mutations in the same gene or variable dose of a mutation may be associated with result in distinct dementias. These findings suggest that minor differences in the structure or amount of protein may be associated with in different clinical outcomes. Understanding these genotype-phenotype associations may provide further insight into the pathogenic nature of the mutations, as well as offer clues for developing new therapeutic targets.
Published: 2019

10. Shared heritability and functional enrichment across six solid cancers

Author: Jiang, Xia, Finucane, Hilary K, Schumacher, Fredrick R, Schmit, Stephanie L, Tyrer, Jonathan P, Han, Younghun, Michailidou, Kyriaki, Lesseur, Corina, Kuchenbaecker, Karoline B, Dennis, Joe, Conti, David V, Casey, Graham, Gaudet, Mia M, Huyghe, Jeroen R, Albanes, Demetrius, Aldrich, Melinda C, Andrew, Angeline S, Andrulis, Irene L, Anton-Culver, Hoda, Antoniou, Antonis C, Antonenkova, Natalia N, Arnold, Susanne M, Aronson, Kristan J, Arun, Banu K, Bandera, Elisa V, Barkardottir, Rosa B, Barnes, Daniel R, Batra, Jyotsna, Beckmann, Matthias W, Benitez, Javier, Benlloch, Sara, Berchuck, Andrew, Berndt, Sonja I, Bickeböller, Heike, Bien, Stephanie A, Blomqvist, Carl, Boccia, Stefania, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Brauch, Hiltrud, Brenner, Hermann, Brenton, James D, Brook, Mark N, Brunet, Joan, Brunnström, Hans, Buchanan, Daniel D, Burwinkel, Barbara, Butzow, Ralf, Cadoni, Gabriella, Caldés, Trinidad, Caligo, Maria A, Campbell, Ian, Campbell, Peter T, Cancel-Tassin, Géraldine, Cannon-Albright, Lisa, Campa, Daniele, Caporaso, Neil, Carvalho, André L, Chan, Andrew T, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Chu, Christiani, David C, Claes, Kathleen BM, Claessens, Frank, Clements, Judith, Collée, J Margriet, Correa, Marcia Cruz, Couch, Fergus J, Cox, Angela, Cunningham, Julie M, Cybulski, Cezary, Czene, Kamila, Daly, Mary B, deFazio, Anna, Devilee, Peter, Diez, Orland, Gago-Dominguez, Manuela, Donovan, Jenny L, Dörk, Thilo, Duell, Eric J, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Edlund, Christopher K, Edwards, Digna R Velez, Ellberg, Carolina, Evans, D Gareth, Fasching, Peter A, Ferris, Robert L, Liloglou, Triantafillos, Figueiredo, Jane C, Fletcher, Olivia, Fortner, Renée T, Fostira, Florentia, Franceschi, Silvia, Friedman, Eitan, Gallinger, Steven J, and Ganz, Patricia A
Subjects: Male, Lung Neoplasms, European Continental Ancestry Group, Inheritance Patterns, Breast Neoplasms, White People, Rare Diseases, Breast Cancer, MD Multidisciplinary, Genetics, Humans, Genetic Predisposition to Disease, Polymorphism, Lung, Cancer, Ovarian Neoplasms, Mental Disorders, Prevention, Smoking, Lung Cancer, Human Genome, Prostatic Neoplasms, Single Nucleotide, Ovarian Cancer, Neoplasm Proteins, Colo-Rectal Cancer, Phenotype, Head and Neck Neoplasms, Case-Control Studies, Female, Colorectal Neoplasms, Digestive Diseases, Genome-Wide Association Study
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

11. AA9int: SNP interaction pattern search using non-hierarchical additive model set

Author: Lin, Hui-Yi, Huang, Po-Yu, Chen, Dung-Tsa, Tung, Heng-Yuan, Sellers, Thomas A, Pow-Sang, Julio M, Eeles, Rosalind, Easton, Doug, Kote-Jarai, Zsofia, Amin Al Olama, Ali, Benlloch, Sara, Muir, Kenneth, Giles, Graham G, Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher A, Schleutker, Johanna, Nordestgaard, Børge G, Travis, Ruth C, Hamdy, Freddie, Neal, David E, Pashayan, Nora, Khaw, Kay-Tee, Stanford, Janet L, Blot, William J, Thibodeau, Stephen N, Maier, Christiane, Kibel, Adam S, Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Kaneva, Radka, Batra, Jyotsna, Teixeira, Manuel R, Pandha, Hardev, Lu, Yong-Jie, PRACTICAL Consortium, Park, Jong Y, Easton, Douglas [0000-0003-2444-3247], Khaw, Kay-Tee [0000-0002-8802-2903], and Apollo - University of Cambridge Repository
Subjects: Statistics as Topic, Computational Biology, Computer Simulation, Polymorphism, Single Nucleotide, Algorithms, Software
Abstract: MOTIVATION: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. RESULTS: We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. AVAILABILITY AND IMPLEMENTATION: The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Published: 2018

12. Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts

Author: Seibert, Tyler M, Fan, Chun Chieh, Wang, Yunpeng, Zuber, Verena, Karunamuni, Roshan, Parsons, J Kellogg, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, ZSofia, Al Olama, Ali Amin, Garcia, Sara Benlloch, Muir, Kenneth, Grönberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo Lj, Nordestgaard, Børge G, Nielsen, Sune F, Weischer, Maren, Bisbjerg, Rasmus, Røder, M Andreas, Iversen, Peter, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Brenner, Hermann, Cuk, Katarina, Saum, Kai-Uwe, Park, Jong Y, Sellers, Thomas A, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Kierzek, Andrzej, Karow, David S, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, PRACTICAL Consortium, Zuber, Verena [0000-0001-9827-1877], Easton, Douglas [0000-0003-2444-3247], Pharoah, Paul [0000-0001-8494-732X], Khaw, Kay-Tee [0000-0002-8802-2903], and Apollo - University of Cambridge Repository
Subjects: Male, Urologic Diseases, Aging, Genotype, Outcome Assessment, European Continental Ancestry Group, Clinical Sciences, Polymorphism, Single Nucleotide, Risk Assessment, White People, Disease-Free Survival, Cohort Studies, Predictive Value of Tests, General & Internal Medicine, Outcome Assessment, Health Care, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Testing, Age of Onset, Polymorphism, Early Detection of Cancer, Aged, Cancer, Whites, Prostate Cancer, Prevention, Prostatic Neoplasms, Single Nucleotide, Prostate-Specific Antigen, Middle Aged, PRACTICAL Consortium, Survival Analysis, Health Care, Public Health and Health Services, Kallikreins
Abstract: OBJECTIVES: To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. DESIGN: Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. SETTING: Multiple institutions that were members of international PRACTICAL consortium. PARTICIPANTS: All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men. MAIN OUTCOME MEASURES: Prediction with hazard score of age of onset of aggressive cancer in validation set. RESULTS: In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score. CONCLUSIONS: Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.
Published: 2018

13. Additional file 1: of Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimerâ s disease resilience

Author: Ridge, Perry, Karch, Celeste, Hsu, Simon, Arano, Ivan, Teerlink, Craig, Ebbert, Mark, Murcia, Josue Gonzalez, Farnham, James, Damato, Anna, Allen, Mariet, Wang, Xue, Harari, Oscar, Fernandez, Victoria, Guerreiro, Rita, Bras, Jose, Hardy, John, Munger, Ronald, Norton, Maria, Sassi, Celeste, Singleton, Andrew, Younkin, Steven, Dickson, Dennis, Golde, Todd, Price, Nathan, NilĂźfer Ertekin-Taner, Cruchaga, Carlos, Goate, Alison, Corcoran, Christopher, Tschanz, JoAnn, Cannon-Albright, Lisa, and Kauwe, John
Abstract: Supplementary Note 1. Variant filtration process. Figures S1 and S2 The pedigrees for RAB10 and SAR1A. (PDF 815 kb)
Published: 2017
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14. A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci

Author: Rand, Kristin A, Song, Chi, Dean, Eric, Serie, Daniel J, Curtin, Karen, Sheng, Xin, Hu, Donglei, Huff, Carol Ann, Bernal-Mizrachi, Leon, Tomasson, Michael H, Ailawadhi, Sikander, Singhal, Seema, Pawlish, Karen, Peters, Edward S, Bock, Cathryn H, Stram, Alex, Van Den Berg, David J, Edlund, Christopher K, Conti, David V, Zimmerman, Todd, Hwang, Amie E, Huntsman, Scott, Graff, John, Nooka, Ajay, Kong, Yinfei, Pregja, Silvana L, Berndt, Sonja I, Blot, William J, Carpten, John, Casey, Graham, Chu, Lisa, Diver, W Ryan, Stevens, Victoria L, Lieber, Michael R, Goodman, Phyllis J, Hennis, Anselm JM, Hsing, Ann W, Mehta, Jayesh, Kittles, Rick A, Kolb, Suzanne, Klein, Eric A, Leske, Cristina, Murphy, Adam B, Nemesure, Barbara, Neslund-Dudas, Christine, Strom, Sara S, Vij, Ravi, Rybicki, Benjamin A, Stanford, Janet L, Signorello, Lisa B, Witte, John S, Ambrosone, Christine B, Bhatti, Parveen, John, Esther M, Bernstein, Leslie, Zheng, Wei, Olshan, Andrew F, Hu, Jennifer J, Ziegler, Regina G, Nyante, Sarah J, Bandera, Elisa V, Birmann, Brenda M, Ingles, Sue A, Press, Michael F, Atanackovic, Djordje, Glenn, Martha J, Cannon-Albright, Lisa A, Jones, Brandt, Tricot, Guido, Martin, Thomas G, Kumar, Shaji K, Wolf, Jeffrey L, Deming Halverson, Sandra L, Rothman, Nathaniel, Brooks-Wilson, Angela R, Rajkumar, S Vincent, Kolonel, Laurence N, Chanock, Stephen J, Slager, Susan L, Severson, Richard K, Janakiraman, Nalini, Terebelo, Howard R, Brown, Elizabeth E, De Roos, Anneclaire J, Mohrbacher, Ann F, Colditz, Graham A, Giles, Graham G, Spinelli, John J, Chiu, Brian C, Munshi, Nikhil C, Anderson, Kenneth C, Levy, Joan, Zonder, Jeffrey A, Orlowski, Robert Z, Lonial, Sagar, Camp, Nicola J, Vachon, Celine M, Ziv, Elad, Stram, Daniel O, and Hazelett, Dennis J
Subjects: Adult, Male, Epidemiology, Transmembrane Activator and CAML Interactor Protein, Black People, Protein Serine-Threonine Kinases, Medical and Health Sciences, White People, Rare Diseases, Clinical Research, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Polymorphism, Aetiology, Aged, Cancer, Polycomb Repressive Complex 1, Human Genome, Single Nucleotide, Hematology, Middle Aged, Repressor Proteins, Genetic Loci, Female, Multiple Myeloma, Genome-Wide Association Study
Abstract: BackgroundGenome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma.MethodsWe performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality.ResultsWe found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10-7) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles.ImpactA subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR.
Published: 2016

15. Polyunsaturated fatty acids and prostate cancer risk: a Mendelian randomisation analysis from the PRACTICAL consortium

Author: Khankari, Nikhil K, Murff, Harvey J, Zeng, Chenjie, Wen, Wanqing, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Benlloch, Sara, Muir, Kenneth, Giles, Graham G, Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher A, Schleutker, Johanna, Nordestgaard, Børge G, Travis, Ruth C, Donovan, Jenny L, Pashayan, Nora, Khaw, Kay-Tee, Stanford, Janet L, Blot, William J, Thibodeau, Stephen N, Maier, Christiane, Kibel, Adam S, Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Park, Jong, Kaneva, Radka, Batra, Jyotsna, Teixeira, Manuel R, Pandha, Hardev, Zheng, Wei, PRACTICAL Consortium, Easton, Douglas [0000-0003-2444-3247], Khaw, Kay-Tee [0000-0002-8802-2903], and Apollo - University of Cambridge Repository
Subjects: Male, Risk Factors, Fatty Acids, Unsaturated, Humans, Prostatic Neoplasms, Genome-Wide Association Study
Abstract: BACKGROUND: Prostate cancer is a common cancer worldwide with no established modifiable lifestyle factors to guide prevention. The associations between polyunsaturated fatty acids (PUFAs) and prostate cancer risk have been inconsistent. Using Mendelian randomisation, we evaluated associations between PUFAs and prostate cancer risk. METHODS: We used individual-level data from a consortium of 22 721 cases and 23 034 controls of European ancestry. Externally-weighted PUFA-specific polygenic risk scores (wPRSs), with explanatory variation ranging from 0.65 to 33.07%, were constructed and used to evaluate associations with prostate cancer risk per one standard deviation (s.d.) increase in genetically-predicted plasma PUFA levels using multivariable-adjusted unconditional logistic regression. RESULTS: No overall association was observed between the genetically-predicted PUFAs evaluated in this study and prostate cancer risk. However, risk reductions were observed for short-chain PUFAs, linoleic (ORLA=0.95, 95%CI=0.92, 0.98) and α-linolenic acids (ORALA=0.96, 95%CI=0.93, 0.98), among men
Published: 2016

16. Investigating the possible causal role of coffee consumption with prostate cancer risk and progression using Mendelian randomization analysis

Author: Taylor, Amy E., Martin, Richard M., Geybels, Milan S., Stanford, Janet L., Shui, Irene, Eeles, Rosalind, Easton, Doug, Kote-Jarai, Zsofia, Amin Al Olama, Ali, Benlloch, Sara, Muir, Kenneth, Giles, Graham G., Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher A., Schleutker, Johanna, Nordestgaard, Børge G., Travis, Ruth C., Neal, David, Pashayan, Nora, Khaw, Kay Tee, Blot, William, 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, Donovan, Jenny, and Munafò, Marcus R.
Subjects: Male, coffee, Short Report, Genetic Variation, Prostatic Neoplasms, Mendelian Randomization Analysis/methods, Mendelian Randomization Analysis, Middle Aged, prostate cancer, Prostatic Neoplasms/etiology, Genetic Variation/genetics, Risk Factors, Coffee/adverse effects, Disease Progression, Mendelian randomization, Humans, Alleles, Cancer Epidemiology, Aged
Abstract: Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all‐cause and prostate cancer‐specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated with prostate cancer risk (OR per additional coffee increasing allele: 1.01, 95% CI: 0.98,1.03) or having high‐grade compared to low‐grade disease (OR: 1.01, 95% CI: 0.97,1.04). There was some evidence that the genetic risk score was associated with higher odds of having nonlocalised compared to localised stage disease (OR: 1.03, 95% CI: 1.01, 1.06). Amongst men with prostate cancer, there was no clear association between the genetic risk score and all‐cause mortality (HR: 1.00, 95% CI: 0.97,1.04) or prostate cancer‐specific mortality (HR: 1.03, 95% CI: 0.98,1.08). These results, which should have less bias from confounding than observational estimates, are not consistent with a substantial effect of coffee consumption on reducing prostate cancer incidence or progression., What's new? Does coffee consumption reduce prostate cancer risk? It's biologically plausible that it could, but studies showing a link have relied on observational evidence, which could be affected by confounding factors. These authors set out to isolate coffee's contribution. They focused on two genetic variants that correspond with caffeine intake, and used them as proxies for coffee drinking. Alleles are not affected by behavior or demographic factors, nor can behavior changes after diagnosis change whether a person carries an allele. The authors found no correlation between either of the alleles and prostate cancer risk, suggesting drinking coffee may not protect against prostate cancer.
Published: 2016

17. Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation

Author: Gusev, Alexander, Shi, Huwenbo, Kichaev, Gleb, Pomerantz, Mark, Li, Fugen, Long, Henry W, Ingles, Sue A, Kittles, Rick A, Strom, Sara S, Rybicki, Benjamin A, Nemesure, Barbara, Isaacs, William B, Zheng, Wei, Pettaway, Curtis A, Yeboah, Edward D, Tettey, Yao, Biritwum, Richard B, Adjei, Andrew A, Tay, Evelyn, Truelove, Ann, Niwa, Shelley, Chokkalingam, Anand P, John, Esther M, Murphy, Adam B, Signorello, Lisa B, Carpten, John, Leske, M Cristina, Wu, Suh-Yuh, Hennis, Anslem JM, Neslund-Dudas, Christine, Hsing, Ann W, Chu, Lisa, Goodman, Phyllis J, Klein, Eric A, Witte, John S, Casey, Graham, Kaggwa, Sam, Cook, Michael B, Stram, Daniel O, Blot, William J, Eeles, Rosalind A, Easton, Douglas, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Benlloch, Sara, Muir, Kenneth, Giles, Graham G, Southey, Melissa C, Fitzgerald, Liesel M, Gronberg, Henrik, Wiklund, Fredrik, Aly, Markus, Henderson, Brian E, Schleutker, Johanna, Wahlfors, Tiina, Tammela, Teuvo LJ, Nordestgaard, Børge G, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Stanford, Janet L, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Teerlink, Craig, Brenner, Hermann, Dieffenbach, Aida K, Arndt, Volker, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Spurdle, Amanda, Clements, Judith A, Teixeira, Manuel R, Pandha, Hardev, Michael, Agnieszka, Paulo, Paula, Maia, Sofia, Kierzek, Andrzej, PRACTICAL consortium, Conti, David V, and Albanes, Demetrius
Subjects: Urologic Diseases, Male, Aging, European Continental Ancestry Group, Inheritance Patterns, urologic and male genital diseases, White People, PRACTICAL consortium, Linkage Disequilibrium, Cell Line, Histones, Atlases as Topic, Genetic, Genetics, 2.1 Biological and endogenous factors, Humans, Genetic Predisposition to Disease, Aetiology, Polymorphism, Cancer, African Americans, Tumor, Prostate Cancer, Human Genome, Prostatic Neoplasms, Acetylation, Single Nucleotide, Black or African American, Genetic Loci, Epigenesis, Genome-Wide Association Study
Abstract: Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.
Published: 2016

18. Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

Author: Berndt, Sonja I, Skibola, Christine F, Joseph, Vijai, Camp, Nicola J, Nieters, Alexandra, Wang, Zhaoming, Cozen, Wendy, Monnereau, Alain, Wang, Sophia S, Kelly, Rachel S, Lan, Qing, Teras, Lauren R, Chatterjee, Nilanjan, Chung, Charles C, Yeager, Meredith, Brooks-Wilson, Angela R, Hartge, Patricia, Purdue, Mark P, Birmann, Brenda M, Armstrong, Bruce K, Cocco, Pierluigi, Zhang, Yawei, Severi, Gianluca, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Burdette, Laurie, Yuenger, Jeffrey, Hutchinson, Amy, Jacobs, Kevin B, Call, Timothy G, Shanafelt, Tait D, Novak, Anne J, Kay, Neil E, Liebow, Mark, Wang, Alice H, Smedby, Karin E, Adami, Hans-Olov, Melbye, Mads, Glimelius, Bengt, Chang, Ellen T, Glenn, Martha, Curtin, Karen, Cannon-Albright, Lisa A, Jones, Brandt, Diver, W Ryan, Link, Brian K, Weiner, George J, Conde, Lucia, Bracci, Paige M, Riby, Jacques, Holly, Elizabeth A, Smith, Martyn T, Jackson, Rebecca D, Tinker, Lesley F, Benavente, Yolanda, Becker, Nikolaus, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, McKay, James, Staines, Anthony, Rabe, Kari G, Achenbach, Sara J, Vachon, Celine M, Goldin, Lynn R, Strom, Sara S, Lanasa, Mark C, Spector, Logan G, Leis, Jose F, Cunningham, Julie M, Weinberg, J Brice, Morrison, Vicki A, Caporaso, Neil E, Norman, Aaron D, Linet, Martha S, De Roos, Anneclaire J, Morton, Lindsay M, Severson, Richard K, Riboli, Elio, Vineis, Paolo, Kaaks, Rudolph, Trichopoulos, Dimitrios, Masala, Giovanna, Weiderpass, Elisabete, Chirlaque, María-Dolores, Vermeulen, Roel CH, Travis, Ruth C, Giles, Graham G, Albanes, Demetrius, Virtamo, Jarmo, Weinstein, Stephanie, Clavel, Jacqueline, Zheng, Tongzhang, Holford, Theodore R, Offit, Kenneth, Zelenetz, Andrew, Klein, Robert J, Spinelli, John J, and Bertrand, Kimberly A
Subjects: Risk, Leukemia, B-Cell, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Chromosomes, Recombination, Linkage Disequilibrium, Lymphocytic, Genetic, Genetic Loci, Case-Control Studies, Pair 2, Humans, Genetic Predisposition to Disease, Polymorphism, Chronic, Human, Genome-Wide Association Study, Developmental Biology
Abstract: Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P=1.22×10(-14)), 18q21.33 (BCL2, P=7.76×10(-11)), 11p15.5 (C11orf21, P=2.15×10(-10)), 4q25 (LEF1, P=4.24×10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P=2.50×10(-9)), 9p21.3 (CDKN2B-AS1, P=1.27×10(-8)), 18q21.32 (PMAIP1, P=2.51×10(-8)), 15q15.1 (BMF, P=2.71×10(-10)) and 2p22.2 (QPCT, P=1.68×10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P=2.08×10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P=5.40×10(-8)) and 5p15.33 (TERT, P=1.92×10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.
Published: 2013

19. Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

Author: Berndt, Sonja I, Skibola, Christine F, Joseph, Vijai, Camp, Nicola J, Nieters, Alexandra, Wang, Zhaoming, Cozen, Wendy, Monnereau, Alain, Wang, Sophia S, Kelly, Rachel S, Lan, Qing, Teras, Lauren R, Chatterjee, Nilanjan, Chung, Charles C, Yeager, Meredith, Brooks-Wilson, Angela R, Hartge, Patricia, Purdue, Mark P, Birmann, Brenda M, Armstrong, Bruce K, Cocco, Pierluigi, Zhang, Yawei, Severi, Gianluca, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Burdette, Laurie, Yuenger, Jeffrey, Hutchinson, Amy, Jacobs, Kevin B, Call, Timothy G, Shanafelt, Tait D, Novak, Anne J, Kay, Neil E, Liebow, Mark, Wang, Alice H, Smedby, Karin E, Adami, Hans-Olov, Melbye, Mads, Glimelius, Bengt, Chang, Ellen T, Glenn, Martha, Curtin, Karen, Cannon-Albright, Lisa A, Jones, Brandt, Diver, W Ryan, Link, Brian K, Weiner, George J, Conde, Lucia, Bracci, Paige M, Riby, Jacques, Holly, Elizabeth A, Smith, Martyn T, Jackson, Rebecca D, Tinker, Lesley F, Benavente, Yolanda, Becker, Nikolaus, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, McKay, James, Staines, Anthony, Rabe, Kari G, Achenbach, Sara J, Vachon, Celine M, Goldin, Lynn R, Strom, Sara S, Lanasa, Mark C, Spector, Logan G, Leis, Jose F, Cunningham, Julie M, Weinberg, J Brice, Morrison, Vicki A, Caporaso, Neil E, Norman, Aaron D, Linet, Martha S, De Roos, Anneclaire J, Morton, Lindsay M, Severson, Richard K, Riboli, Elio, Vineis, Paolo, Kaaks, Rudolph, Trichopoulos, Dimitrios, Masala, Giovanna, Weiderpass, Elisabete, Chirlaque, María-Dolores, Vermeulen, Roel CH, Travis, Ruth C, Giles, Graham G, Albanes, Demetrius, Virtamo, Jarmo, Weinstein, Stephanie, Clavel, Jacqueline, Zheng, Tongzhang, Holford, Theodore R, Offit, Kenneth, Zelenetz, Andrew, Klein, Robert J, Spinelli, John J, and Bertrand, Kimberly A
Subjects: Risk, Leukemia, B-Cell, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Chromosomes, Recombination, Linkage Disequilibrium, Lymphocytic, Genetic, Genetic Loci, Case-Control Studies, Pair 2, Humans, Genetic Predisposition to Disease, Polymorphism, Chronic, Human, Genome-Wide Association Study, Cancer, Developmental Biology
Abstract: Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P=1.22×10(-14)), 18q21.33 (BCL2, P=7.76×10(-11)), 11p15.5 (C11orf21, P=2.15×10(-10)), 4q25 (LEF1, P=4.24×10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P=2.50×10(-9)), 9p21.3 (CDKN2B-AS1, P=1.27×10(-8)), 18q21.32 (PMAIP1, P=2.51×10(-8)), 15q15.1 (BMF, P=2.71×10(-10)) and 2p22.2 (QPCT, P=1.68×10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P=2.08×10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P=5.40×10(-8)) and 5p15.33 (TERT, P=1.92×10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.
Published: 2013

20. At-risk populations for osteosarcoma: the syndromes and beyond

Author: Calvert, George, Randall, Robert, Jones, Kevin, Cannon-Albright, Lisa, Lessnick, Stephen, and Schiffman, Joshua
Subjects: musculoskeletal diseases, neoplasms
Abstract: Osteosarcoma is the most common primary malignancy of bone. Most cases are sporadic without a known genetic or environmental cause. Heritable genetic predisposition syndromes are associated with a small percentage of osteosarcomas. Study of these rare disorders has provided insight into the molecular pathogenesis of osteosarcoma. Screening of at-risk families and surveillance of affected individuals for these syndromes may permit earlier diagnosis and more effective treatment of osteosarcoma in these populations. This paper reviews the genetic and clinical features of the known osteosarcoma predisposition syndromes.
Published: 2012

21. Additional file 1: of The contribution of the rs55705857 G allele to familial cancer risk as estimated in the Utah population database

Author: Hummel, Sarah, Kohlmann, Wendy, Kollmeyer, Thomas, Jenkins, Robert, Sonnen, Joshua, Palmer, Cheryl, Colman, Howard, Abbott, Diana, Cannon-Albright, Lisa, and Cohen, Adam
Subjects: 3. Good health
Abstract: Table S1: DNA sample characteristics of glioma patients harboring IDH1/2 mutant or 1p/19q co-deletion. Legend: Shown are the genotype results of 102 unique individuals. Samples were submitted in 96-well plates. Fifteen water blanks and replicate samples were plated at random. Cells highlighted in blue were called G Allele positive for rs55705857. Cells highlighted in orange have discrepancy between G allele status at rs55705857 in blood and tumor samples. Blood is germline and thus was held to be the true representation of an individualâ s G allele status at rs55705857. (PDF 315 kb)

22. Additional file 1: Tables S1 â S6. of Pubertal development and prostate cancer risk: Mendelian randomization study in a population-based cohort

Author: Bonilla, Carolina, Lewis, Sarah, Martin, Richard, Donovan, Jenny, Hamdy, Freddie, Neal, David, Eeles, Rosalind, Easton, Doug, Zsofia Kote-Jarai, Olama, Ali Al, Benlloch, Sara, Muir, Kenneth, Giles, Graham, Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher, Schleutker, Johanna, BĂ¸Rge Nordestgaard, Travis, Ruth, Pashayan, Nora, Kay-Tee Khaw, Stanford, Janet, Blot, William, Thibodeau, Stephen, Maier, Christiane, Kibel, Adam, Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Park, Jong, Kaneva, Radka, Batra, Jyotsna, Teixeira, Manuel, Pandha, Hardev, Lathrop, Mark, and Smith, George Davey
Subjects: 3. Good health
Abstract: Figures S1â S4. Supplementary Methods. Definitions. Supplementary References. (DOCX 214 kb)

23. Polygenic hazard score is associated with prostate cancer in multi-ethnic populations

Author: Huynh-Le, Minh-Phuong, Fan, Chun Chieh, Karunamuni, Roshan, Thompson, Wesley K, Martinez, Maria Elena, Eeles, Rosalind A, Kote-Jarai, Zsofia, Muir, Kenneth, Schleutker, Johanna, Pashayan, Nora, Batra, Jyotsna, Grönberg, Henrik, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Nielsen, Sune F, Nordestgaard, Børge G, Wiklund, Fredrik, Tangen, Catherine M, Giles, Graham G, Wolk, Alicja, Albanes, Demetrius, Travis, Ruth C, Blot, William J, Zheng, Wei, Sanderson, Maureen, Stanford, Janet L, Mucci, Lorelei A, West, Catharine ML, Kibel, Adam S, Cussenot, Olivier, Berndt, Sonja I, Koutros, Stella, Sørensen, Karina Dalsgaard, Cybulski, Cezary, Grindedal, Eli Marie, Menegaux, Florence, Khaw, Kay-Tee, Park, Jong Y, Ingles, Sue A, Maier, Christiane, Hamilton, Robert J, Thibodeau, Stephen N, Rosenstein, Barry S, Lu, Yong-Jie, Watya, Stephen, Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L, Huff, Chad, Teixeira, Manuel R, Multigner, Luc, Leach, Robin J, Cannon-Albright, Lisa, Brenner, Hermann, John, Esther M, Kaneva, Radka, Logothetis, Christopher J, Neuhausen, Susan L, De Ruyck, Kim, Pandha, Hardev, Razack, Azad, Newcomb, Lisa F, Fowke, Jay H, Gamulin, Marija, Usmani, Nawaid, Claessens, Frank, Gago-Dominguez, Manuela, Townsend, Paul A, Bush, William S, Roobol, Monique J, Parent, Marie-Élise, Hu, Jennifer J, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, UKGPCS Collaborators, APCB (Australian Prostate Cancer BioResource), NC-LA PCaP Investigators, IMPACT Study Steering Committee And Collaborators, Canary PASS Investigators, Profile Study Steering Committee, and PRACTICAL Consortium
Subjects: Male, Multifactorial Inheritance, Multivariate Analysis, Ethnicity, Humans, Prostatic Neoplasms, Neoplasm Invasiveness, Self Report, Middle Aged, 3. Good health, Aged
Abstract: Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS1) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS2 (PHS1, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p < 10-180). Comparing the 80th/20th PHS2 percentiles, hazard ratios for prostate cancer, aggressive cancer, and prostate-cancer-specific death are 5.32, 5.88, and 5.68, respectively. Within European, Asian, and African ancestries, hazard ratios for prostate cancer are: 5.54, 4.49, and 2.54, respectively. PHS2 risk-stratifies men for any, aggressive, and fatal prostate cancer in a multi-ethnic dataset.

24. Genome-wide association study identifies three new melanoma susceptibility loci

Author: Barrett, Jennifer H., Iles, Mark M., Harland, Mark, Taylor, John C., Aitken, Joanne F., Andresen, Per Arne, Akslen, Lars A., Armstrong, Bruce K., Avril, Marie F., Azizi, Esther, Bakker, Bert, Bergman, Wilma, Bianchi-Scarrà, Giovanna, Bressac-de Paillerets, Brigitte, Calista, Donato, Cannon-Albright, Lisa A., Corda, Eve, Cust, Anne E., Dębniak, Tadeusz, Duffy, David, Dunning, Alison M., Easton, Douglas F., Friedman, Eitan, Galan, Pilar, Ghiorzo, Paola, Giles, Graham G., Hansson, Johan, Hocevar, Marko, Höiom, Veronica, Hopper, John L., Ingvar, Christian, Janssen, Bart, Jenkins, Mark A., Jönsson, Göran, Kefford, Richard F., Landi, Giorgio, Landi, Maria Teresa, Lang, Julie, Lubinski, Jan, Mackie, Rona, Malvehy, J. (Josep), Martin, Nicholas G., Molven, Anders, Montgomery, Grant W., Nieuwpoort, Frans A. van, Novakovic, Srdjan, Olsson, Håkan, Pastorino, Lorenza, Puig i Sardà, Susana, Puig Butillé, Joan Anton, Randerson-Moor, Juliette, Snowden, Helen, Tuominen, Raider, Belle, Patricia van, Stoep, Nienke van der, Whiteman, David C., Zelenika, Diana, Han, Jiali, Fang, Shenying, Lee, Jeffrey E., Wei, Qingyi, Lathrop, Mark, Gillanders, Elizabeth M., Brown, Kevin M., Goldstein, Alisa M., Kanetsky, Peter A., Mann, Graham J., MacGregor, Stuart, Elder, David E., Amos, Christopher I., Hayward, Nicholas K., Gruis, Nelleke A., Demenais, Florence, Newton-Bishop, Julia A., Bishop, D. Timothy, and GenoMEL Consortium
Subjects: Genètica mèdica, Medical genetics, Skin cancer, Melanoma, Càncer de pell

25. Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

Author: Berndt, Sonja I., Skibola, Christine F., Joseph, Vijai, Camp, Nicola J., Nieters, Alexandra, Wang, Zhaoming, Cozen, Wendy, Monnereau, Alain, Wang, Sophia S., Kelly, Rachel S., Lan, Qing, Teras, Lauren R., Chatterjee, Nilanjan, Chung, Charles C., Yeager, Meredith, Brooks-Wilson, Angela R., Hartge, Patricia, Purdue, Mark P., Birmann, Brenda M., Armstrong, Bruce K., Cocco, Pierluigi, Zhang, Yawei, Severi, Gianluca, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Burdette, Laurie, Yuenger, Jeffrey, Hutchinson, Amy, Jacobs, Kevin B., Call, Timothy G., Shanafelt, Tait D., Novak, Anne J., Kay, Neil E., Liebow, Mark, Wang, Alice H., Smedby, Karin E., Adami, Hans-Olov, Melbye, Mads, Glimelius, Bengt, Chang, Ellen T., Glenn, Martha, Curtin, Karen, Cannon-Albright, Lisa A., Jones, Brandt, Diver, W. Ryan, Link, Brian K., Weiner, George J., Conde, Lucia, Bracci, Paige M., Riby, Jacques, Holly, Elizabeth A., Smith, Martyn T., Jackson, Rebecca D. J., Tinker, Lesley F., Benavente, Yolanda, Becker, Nikolaus, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadié, Marc, McKay, James D., and Staines, Anthony
Subjects: Genòmica, Leucèmia limfocítica crònica, Chronic lymphocytic leukemia, Genomics

26. Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction

Author: Conti, David V, Darst, Burcu F, Moss, Lilit C, Saunders, Edward J, Sheng, Xin, Chou, Alisha, Schumacher, Fredrick R, Olama, Ali Amin Al, Benlloch, Sara, Dadaev, Tokhir, Brook, Mark N, Sahimi, Ali, Hoffmann, Thomas J, Takahashi, Atushi, Matsuda, Koichi, Momozawa, Yukihide, Fujita, Masashi, Muir, Kenneth, Lophatananon, Artitaya, Wan, Peggy, Le Marchand, Loic, Wilkens, Lynne R, Stevens, Victoria L, Gapstur, Susan M, Carter, Brian D, Schleutker, Johanna, Tammela, Teuvo LJ, Sipeky, Csilla, Auvinen, Anssi, Giles, Graham G, Southey, Melissa C, MacInnis, Robert J, Cybulski, Cezary, Wokołorczyk, Dominika, Lubiński, Jan, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Nordestgaard, Børge G, Nielsen, Sune F, Weischer, Maren, Bojesen, Stig E, Røder, Martin Andreas, Iversen, Peter, Batra, Jyotsna, Chambers, Suzanne, Moya, Leire, Horvath, Lisa, Clements, Judith A, Tilley, Wayne, Risbridger, Gail P, Gronberg, Henrik, Aly, Markus, Szulkin, Robert, Eklund, Martin, Nordström, Tobias, Pashayan, Nora, Dunning, Alison M, Ghoussaini, Maya, Travis, Ruth C, Key, Tim J, Riboli, Elio, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Albanes, Demetrius, Weinstein, Stephanie J, Mucci, Lorelei A, Giovannucci, Edward, Lindstrom, Sara, Kraft, Peter, Hunter, David J, Penney, Kathryn L, Turman, Constance, Tangen, Catherine M, Goodman, Phyllis J, Thompson, Ian M, Hamilton, Robert J, Fleshner, Neil E, Finelli, Antonio, Parent, Marie-Élise, Stanford, Janet L, Ostrander, Elaine A, Geybels, Milan S, Koutros, Stella, Freeman, Laura E Beane, Stampfer, Meir, Wolk, Alicja, Håkansson, Niclas, Andriole, Gerald L, Hoover, Robert N, Machiela, Mitchell J, Sørensen, Karina Dalsgaard, Borre, Michael, Blot, William J, Zheng, Wei, Yeboah, Edward D, Mensah, James E, Lu, Yong-Jie, Zhang, Hong-Wei, Feng, Ninghan, Mao, Xueying, Wu, Yudong, Zhao, Shan-Chao, Sun, Zan, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, West, Catharine ML, Burnet, Neil, Barnett, Gill, Maier, Christiane, Schnoeller, Thomas, Luedeke, Manuel, Kibel, Adam S, Drake, Bettina F, Cussenot, Olivier, Cancel-Tassin, Géraldine, Menegaux, Florence, Truong, Thérèse, Koudou, Yves Akoli, John, Esther M, Grindedal, Eli Marie, Maehle, Lovise, Khaw, Kay-Tee, Ingles, Sue A, Stern, Mariana C, Vega, Ana, Gómez-Caamaño, Antonio, Fachal, Laura, Rosenstein, Barry S, Kerns, Sarah L, Ostrer, Harry, Teixeira, Manuel R, Paulo, Paula, Brandão, Andreia, Watya, Stephen, Lubwama, Alexander, Bensen, Jeannette T, Fontham, Elizabeth TH, Mohler, James, Taylor, Jack A, Kogevinas, Manolis, Llorca, Javier, Castaño-Vinyals, Gemma, Cannon-Albright, Lisa, Teerlink, Craig C, Huff, Chad D, Strom, Sara S, Multigner, Luc, Blanchet, Pascal, Brureau, Laurent, Kaneva, Radka, Slavov, Chavdar, Mitev, Vanio, Leach, Robin J, Weaver, Brandi, Brenner, Hermann, Cuk, Katarina, Holleczek, Bernd, Saum, Kai-Uwe, Klein, Eric A, Hsing, Ann W, Kittles, Rick A, Murphy, Adam B, Logothetis, Christopher J, Kim, Jeri, Neuhausen, Susan L, Steele, Linda, Ding, Yuan Chun, Isaacs, William B, Nemesure, Barbara, Hennis, Anselm JM, Carpten, John, Pandha, Hardev, Michael, Agnieszka, De Ruyck, Kim, De Meerleer, Gert, Ost, Piet, Xu, Jianfeng, Razack, Azad, Lim, Jasmine, Teo, Soo-Hwang, Newcomb, Lisa F, Lin, Daniel W, Fowke, Jay H, Neslund-Dudas, Christine, Rybicki, Benjamin A, Gamulin, Marija, Lessel, Davor, Kulis, Tomislav, Usmani, Nawaid, Singhal, Sandeep, Parliament, Matthew, Claessens, Frank, Joniau, Steven, Van Den Broeck, Thomas, Gago-Dominguez, Manuela, Castelao, Jose Esteban, Martinez, Maria Elena, Larkin, Samantha, Townsend, Paul A, Aukim-Hastie, Claire, Bush, William S, Aldrich, Melinda C, Crawford, Dana C, Srivastava, Shiv, Cullen, Jennifer C, Petrovics, Gyorgy, Casey, Graham, Roobol, Monique J, Jenster, Guido, Van Schaik, Ron HN, Hu, Jennifer J, Sanderson, Maureen, Varma, Rohit, McKean-Cowdin, Roberta, Torres, Mina, Mancuso, Nicholas, Berndt, Sonja I, Van Den Eeden, Stephen K, Easton, Douglas F, Chanock, Stephen J, Cook, Michael B, Wiklund, Fredrik, Nakagawa, Hidewaki, Witte, John S, Eeles, Rosalind A, Kote-Jarai, Zsofia, and Haiman, Christopher A
Subjects: Male, Genetic Loci, Risk Factors, Racial Groups, Odds Ratio, Humans, Prostatic Neoplasms, Genetic Predisposition to Disease, Molecular Sequence Annotation, Neoplasm Invasiveness, Middle Aged, 3. Good health, Genome-Wide Association Study
Abstract: Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

27. Additional file 3: of Pancreatic cancer as a sentinel for hereditary cancer predisposition

Author: Young, Erin, Thompson, Bryony, Neklason, Deborah, Firpo, Matthew, Werner, Theresa, Bell, Russell, Berger, Justin, Fraser, Alison, Gammon, Amanda, Koptiuch, Cathryn, Kohlmann, Wendy, Neumayer, Leigh, Goldgar, David, Mulvihill, Sean, Cannon-Albright, Lisa, and Tavtigian, Sean
Subjects: 3. Good health
Abstract: Table S4. Is a list of reports/genes used for meta-analysis. Table S5. is the values that were used to create Fig. 3. (DOCX 34 kb)

28. Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Author: Matejcic, Marco, Saunders, Edward J, Dadaev, Tokhir, Brook, Mark N, Wang, Kan, Sheng, Xin, Olama, Ali Amin Al, Schumacher, Fredrick R, Ingles, Sue A, Govindasami, Koveela, Benlloch, Sara, Berndt, Sonja I, Albanes, Demetrius, Koutros, Stella, Muir, Kenneth, Stevens, Victoria L, Gapstur, Susan M, Tangen, Catherine M, Batra, Jyotsna, Clements, Judith, Gronberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Wolk, Alicja, West, Catharine, Mucci, Lorelei, Kraft, Peter, Cancel-Tassin, Géraldine, Sorensen, Karina D, Maehle, Lovise, Grindedal, Eli M, Strom, Sara S, Neal, David E, Hamdy, Freddie C, Donovan, Jenny L, Travis, Ruth C, Hamilton, Robert J, Rosenstein, Barry, Lu, Yong-Jie, Giles, Graham G, Kibel, Adam S, Vega, Ana, Bensen, Jeanette T, Kogevinas, Manolis, Penney, Kathryn L, Park, Jong Y, Stanford, Janet L, Cybulski, Cezary, Nordestgaard, Børge G, Brenner, Hermann, Maier, Christiane, Kim, Jeri, Teixeira, Manuel R, Neuhausen, Susan L, De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F, Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A, Gago-Dominguez, Manuela, Roobol, Monique J, Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa A, Pandha, Hardev, Thibodeau, Stephen N, Schaid, Daniel J, PRACTICAL (Prostate Cancer Association Group To Investigate Cancer-Associated Alterations In The Genome) Consortium, Wiklund, Fredrik, Chanock, Stephen J, Easton, Douglas F, Eeles, Rosalind A, Kote-Jarai, Zsofia, Conti, David V, and Haiman, Christopher A
Subjects: Genetic Markers, Male, Genotype, Chromosome Mapping, Prostatic Neoplasms, Risk Assessment, White People, 3. Good health, Haplotypes, Risk Factors, Case-Control Studies, Humans, Genetic Predisposition to Disease, Disease Susceptibility, Chromosomes, Human, Pair 8
Abstract: Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10-15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.

29. Additional file 1: of The contribution of the rs55705857 G allele to familial cancer risk as estimated in the Utah population database

Author: Hummel, Sarah, Kohlmann, Wendy, Kollmeyer, Thomas, Jenkins, Robert, Sonnen, Joshua, Palmer, Cheryl, Colman, Howard, Abbott, Diana, Cannon-Albright, Lisa, and Cohen, Adam
Subjects: 3. Good health
Abstract: Table S1: DNA sample characteristics of glioma patients harboring IDH1/2 mutant or 1p/19q co-deletion. Legend: Shown are the genotype results of 102 unique individuals. Samples were submitted in 96-well plates. Fifteen water blanks and replicate samples were plated at random. Cells highlighted in blue were called G Allele positive for rs55705857. Cells highlighted in orange have discrepancy between G allele status at rs55705857 in blood and tumor samples. Blood is germline and thus was held to be the true representation of an individualâ s G allele status at rs55705857. (PDF 315 kb)

30. Genome-wide association study identifies three new melanoma susceptibility loci

Author: Barrett, Jennifer H., Iles, Mark M., Harland, Mark, Taylor, John C., Aitken, Joanne F., Andresen, Per Arne, Akslen, Lars A., Armstrong, Bruce K., Avril, Marie F., Azizi, Esther, Bakker, Bert, Bergman, Wilma, Bianchi-Scarrà, Giovanna, Bressac-de Paillerets, Brigitte, Calista, Donato, Cannon-Albright, Lisa A., Corda, Eve, Cust, Anne E., Debniak, Tadeusz, Duffy, David, Dunning, Alison M., Easton, Douglas F., Friedman, Eitan, Galan, Pilar, Ghiorzo, Paola, Giles, Graham G., Hansson, Johan, Hocevar, Marko, Höiom, Veronica, Hopper, John L., Ingvar, Christian, Janssen, Bart, Jenkins, Mark A., Jönsson, Göran, Kefford, Richard F., Landi, Giorgio, Landi, Maria Teresa, Lang, Julie, Lubinski, Jan, Mackie, Rona, Malvehy, J. (Josep), Martin, Nicholas G., Molven, Anders, Montgomery, Grant W., Nieuwpoort, Frans A. van, Novakovic, Srdjan, Olsson, Hakan, Pastorino, Lorenza, Puig i Sardà, Susana, Puig Butillé, Joan Anton, Randerson-Moor, Juliette, Snowden, Helen, Tuominen, Raider, Belle, Patricia van, Stoep, Nienke van der, Whiteman, David C., Zelenika, Diana, Han, Jiali, Fang, Shenying, Lee, Jeffrey E., Wei, Qingyi, Lathrop, G. Mark, Gillanders, Elizabeth M., Brown, Kevin M., Goldstein, Alisa M., Kanetsky, Peter A., Mann, Graham J., MacGregor, Stuart, Elder, David E., Amos, Christopher I., Hayward, Nicholas K., Gruis, Nelleke A., Demenais, Florence, Newton-Bishop, Julia, Bishop, D. Timothy, GenoMEL Consortium, and Universitat de Barcelona
Subjects: Genètica mèdica, Medical genetics, Skin cancer, Melanoma, Càncer de pell
Abstract: We report a genome-wide association study for melanoma that was conducted by the GenoMEL Consortium. Our discovery phase included 2,981 individuals with melanoma and 1,982 study-specific control individuals of European ancestry, as well as an additional 6,426 control subjects from French or British populations, all of whom were genotyped for 317,000 or 610,000 single-nucleotide polymorphisms (SNPs). Our analysis replicated previously known melanoma susceptibility loci. Seven new regions with at least one SNP with P < 10−5 and further local imputed or genotyped support were selected for replication using two other genome-wide studies (from Australia and Texas, USA). Additional replication came from case-control series from the UK and The Netherlands. Variants at three of the seven loci replicated at P < 10−3: an SNP in ATM (rs1801516, overall P = 3.4 × 10−9), an SNP in MX2 (rs45430, P = 2.9 × 10−9) and an SNP adjacent to CASP8 (rs13016963, P = 8.6 × 10−10). A fourth locus near CCND1 remains of potential interest, showing suggestive but inconclusive evidence of replication (rs1485993, overall P = 4.6 × 10−7 under a fixed-effects model and P = 1.2 × 10−3 under a random-effects model). These newly associated variants showed no association with nevus or pigmentation phenotypes in a large British case-control series.

31. Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

Author: Berndt, Sonja I., Skibola, Christine F., Joseph, Vijai, Camp, Nicola J., Nieters, Alexandra, Wang, Zhaoming, Cozen, Wendy, Monnereau, Alain, Wang, Sophia S., Kelly, Rachel S., Lan, Qing, Teras, Lauren R., Chatterjee, Nilanjan, Chung, Charles C., Yeager, Meredith, Brooks-Wilson, Angela R., Hartge, Patricia, Purdue, Mark P., Birmann, Brenda M., Armstrong, Bruce K., Cocco, Pierluigi, Zhang, Yawei, Severi, Gianluca, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Burdette, Laurie, Yuenger, Jeffrey, Hutchinson, Amy, Jacobs, Kevin B., Call, Timothy G., Shanafelt, Tait D., Novak, Anne J., Kay, Neil E., Liebow, Mark, Wang, Alice H., Smedby, Karin E., Adami, Hans-Olov, Melbye, Mads, Glimelius, Bengt, Chang, Ellen T., Glenn, Martha, Curtin, Karen, Cannon-Albright, Lisa A., Jones, Brandt, Diver, W. Ryan, Link, Brian K., Weiner, George J., Conde, Lucia, Bracci, Paige M., Riby, Jacques, Holly, Elizabeth A., Smith, Martyn T., Jackson, Rebecca D., Tinker, Lesley F., Benavente, Yolanda, Becker, Nikolaus, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, McKay, James, and Staines, Anthony
Subjects: Genòmica, Leucèmia limfocítica crònica, Chronic lymphocytic leukemia, Genomics
Abstract: Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P = 1.22 x 10(-14)), 18q21.33 (BCL2, P = 7.76 x 10(-11)), 11p15.5 (C11orf21, P = 2.15 x 10(-10)), 4q25 (LEF1, P = 4.24 x 10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P = 2.50 x 10(-9)), 9p21.3 (CDKN2B-AS1, P = 1.27 x 10(-8)), 18q21.32 (PMAIP1, P = 2.51 x 10(-8)), 15q15.1 (BMF, P = 2.71 x 10(-10)) and 2p22.2 (QPCT, P = 1.68 x 10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P = 2.08 x 10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P = 5.40 x 10(-8)) and 5p15.33 (TERT, P = 1.92 x 10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.

32. Fine-mapping the HOXB region detects common variants tagging a rare coding allele: evidence for synthetic association in prostate cancer

Author: Saunders, Edward J, Dadaev, Tokhir, Leongamornlert, Daniel A, Jugurnauth-Little, Sarah, Tymrakiewicz, Malgorzata, Wiklund, Fredrik, Al Olama, Ali Amin, Benlloch, Sara, Neal, David E, Hamdy, Freddie C, Donovan, Jenny L, Giles, Graham G, Severi, Gianluca, Gronberg, Henrik, Aly, Markus, Haiman, Christopher A, Schumacher, Fredrick, Henderson, Brian E, Lindstrom, Sara, Kraft, Peter, Hunter, David J, Gapstur, Susan, Chanock, Stephen, Berndt, Sonja I, Albanes, Demetrius, Andriole, Gerald, Schleutker, Johanna, Weischer, Maren, Nordestgaard, Børge G, Canzian, Federico, Campa, Daniele, Riboli, Elio, Key, Tim J, Travis, Ruth C, Ingles, Sue A, John, Esther M, Hayes, Richard B, Pharoah, Paul, Khaw, Kay-Tee, Stanford, Janet L, Ostrander, Elaine A, Signorello, Lisa B, Thibodeau, Stephen N, Schaid, Daniel, Maier, Christiane, Kibel, Adam S, Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Park, Jong Y, Kaneva, Radka, Batra, Jyotsna, Clements, Judith A, Teixeira, Manuel R, Xu, Jianfeng, Mikropoulos, Christos, Goh, Chee, Govindasami, Koveela, Guy, Michelle, Wilkinson, Rosemary A, Sawyer, Emma J, Morgan, Angela, COGS-CRUK GWAS-ELLIPSE (Part Of GAME-ON) Initiative, UK Genetic Prostate Cancer Study Collaborators, UK ProtecT Study Collaborators, PRACTICAL Consortium, Easton, Douglas F, Muir, Ken, Eeles, Rosalind A, and Kote-Jarai, Zsofia
Subjects: Homeodomain Proteins, Male, Genotype, Risk Factors, Genetic Variation, Humans, Prostatic Neoplasms, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Alleles, 3. Good health, Chromosomes, Human, Pair 17, Genome-Wide Association Study
Abstract: The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.

33. Additional file 1: Tables S1 â S6. of Pubertal development and prostate cancer risk: Mendelian randomization study in a population-based cohort

Author: Bonilla, Carolina, Lewis, Sarah, Martin, Richard, Donovan, Jenny, Hamdy, Freddie, Neal, David, Eeles, Rosalind, Easton, Doug, Zsofia Kote-Jarai, Olama, Ali Al, Benlloch, Sara, Muir, Kenneth, Giles, Graham, Wiklund, Fredrik, Gronberg, Henrik, Haiman, Christopher, Schleutker, Johanna, BĂ¸Rge Nordestgaard, Travis, Ruth, Pashayan, Nora, Kay-Tee Khaw, Stanford, Janet, Blot, William, Thibodeau, Stephen, Maier, Christiane, Kibel, Adam, Cybulski, Cezary, Cannon-Albright, Lisa, Brenner, Hermann, Park, Jong, Kaneva, Radka, Batra, Jyotsna, Teixeira, Manuel, Pandha, Hardev, Lathrop, Mark, and Smith, George Davey
Subjects: 3. Good health
Abstract: Figures S1â S4. Supplementary Methods. Definitions. Supplementary References. (DOCX 214 kb)

34. Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

Author: Berndt, Sonja I., Skibola, Christine F., Joseph, Vijai, Camp, Nicola J., Nieters, Alexandra, Wang, Zhaoming, Cozen, Wendy, Monnereau, Alain, Wang, Sophia S., Kelly, Rachel S., Lan, Qing, Teras, Lauren R., Chatterjee, Nilanjan, Chung, Charles C., Yeager, Meredith, Brooks-Wilson, Angela R., Hartge, Patricia, Purdue, Mark P., Birmann, Brenda M., Armstrong, Bruce K., Cocco, Pierluigi, Zhang, Yawei, Severi, Gianluca, Zeleniuch-Jacquotte, Anne, Lawrence, Charles, Burdette, Laurie, Yuenger, Jeffrey, Hutchinson, Amy, Jacobs, Kevin B., Call, Timothy G., Shanafelt, Tait D., Novak, Anne J., Kay, Neil E., Liebow, Mark, Wang, Alice H., Smedby, Karin E., Adami, Hans-Olov, Melbye, Mads, Glimelius, Bengt, Chang, Ellen T., Glenn, Martha, Curtin, Karen, Cannon-Albright, Lisa A., Jones, Brandt, Diver, W. Ryan, Link, Brian K., Weiner, George J., Conde, Lucia, Bracci, Paige M., Riby, Jacques, Holly, Elizabeth A., Smith, Martyn T., Jackson, Rebecca D., Tinker, Lesley F., Benavente, Yolanda, Becker, Nikolaus, Boffetta, Paolo, Brennan, Paul, Foretova, Lenka, Maynadie, Marc, McKay, James, Staines, Anthony, and Universitat de Barcelona
Subjects: Genòmica, Leucèmia limfocítica crònica, Chronic lymphocytic leukemia, Genomics
Abstract: Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P = 1.22 x 10(-14)), 18q21.33 (BCL2, P = 7.76 x 10(-11)), 11p15.5 (C11orf21, P = 2.15 x 10(-10)), 4q25 (LEF1, P = 4.24 x 10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P = 2.50 x 10(-9)), 9p21.3 (CDKN2B-AS1, P = 1.27 x 10(-8)), 18q21.32 (PMAIP1, P = 2.51 x 10(-8)), 15q15.1 (BMF, P = 2.71 x 10(-10)) and 2p22.2 (QPCT, P = 1.68 x 10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P = 2.08 x 10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P = 5.40 x 10(-8)) and 5p15.33 (TERT, P = 1.92 x 10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.

35. Shared heritability and functional enrichment across six solid cancers

Author: Jiang, Xia, Finucane, Hilary K, Schumacher, Fredrick R, Schmit, Stephanie L, Tyrer, Jonathan P, Han, Younghun, Michailidou, Kyriaki, Lesseur, Corina, Kuchenbaecker, Karoline B, Dennis, Joe, Conti, David V, Casey, Graham, Gaudet, Mia M, Huyghe, Jeroen R, Albanes, Demetrius, Aldrich, Melinda C, Andrew, Angeline S, Andrulis, Irene L, Anton-Culver, Hoda, Antoniou, Antonis C, Antonenkova, Natalia N, Arnold, Susanne M, Aronson, Kristan J, Arun, Banu K, Bandera, Elisa V, Barkardottir, Rosa B, Barnes, Daniel R, Batra, Jyotsna, Beckmann, Matthias W, Benitez, Javier, Benlloch, Sara, Berchuck, Andrew, Berndt, Sonja I, Bickeböller, Heike, Bien, Stephanie A, Blomqvist, Carl, Boccia, Stefania, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Brauch, Hiltrud, Brenner, Hermann, Brenton, James D, Brook, Mark N, Brunet, Joan, Brunnström, Hans, Buchanan, Daniel D, Burwinkel, Barbara, Butzow, Ralf, Cadoni, Gabriella, Caldés, Trinidad, Caligo, Maria A, Campbell, Ian, Campbell, Peter T, Cancel-Tassin, Géraldine, Cannon-Albright, Lisa, Campa, Daniele, Caporaso, Neil, Carvalho, André L, Chan, Andrew T, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Chu, Christiani, David C, Claes, Kathleen BM, Claessens, Frank, Clements, Judith, Collée, J Margriet, Correa, Marcia Cruz, Couch, Fergus J, Cox, Angela, Cunningham, Julie M, Cybulski, Cezary, Czene, Kamila, Daly, Mary B, DeFazio, Anna, Devilee, Peter, Diez, Orland, Gago-Dominguez, Manuela, Donovan, Jenny L, Dörk, Thilo, Duell, Eric J, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Edlund, Christopher K, Edwards, Digna R Velez, Ellberg, Carolina, Evans, D Gareth, Fasching, Peter A, Ferris, Robert L, Liloglou, Triantafillos, Figueiredo, Jane C, Fletcher, Olivia, Fortner, Renée T, Fostira, Florentia, Franceschi, Silvia, Friedman, Eitan, Gallinger, Steven J, Ganz, Patricia A, Garber, Judy, García-Sáenz, José A, Gayther, Simon A, Giles, Graham G, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, Goode, Ellen L, Goodman, Marc T, Goodman, Gary, Grankvist, Kjell, Greene, Mark H, Gronberg, Henrik, Gronwald, Jacek, Guénel, Pascal, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hamdy, Freddie C, Hamilton, Robert J, Hampe, Jochen, Haugen, Aage, Heitz, Florian, Herrero, Rolando, Hillemanns, Peter, Hoffmeister, Michael, Høgdall, Estrid, Hong, Yun-Chul, Hopper, John L, Houlston, Richard, Hulick, Peter J, Hunter, David J, Huntsman, David G, Idos, Gregory, Imyanitov, Evgeny N, Ingles, Sue Ann, Isaacs, Claudine, Jakubowska, Anna, James, Paul, Jenkins, Mark A, Johansson, Mattias, Johansson, Mikael, John, Esther M, Joshi, Amit D, Kaneva, Radka, Karlan, Beth Y, Kelemen, Linda E, Kühl, Tabea, Khaw, Kay-Tee, Khusnutdinova, Elza, Kibel, Adam S, Kiemeney, Lambertus A, Kim, Jeri, Kjaer, Susanne K, Knight, Julia A, Kogevinas, Manolis, Kote-Jarai, Zsofia, Koutros, Stella, Kristensen, Vessela N, Kupryjanczyk, Jolanta, Lacko, Martin, Lam, Stephan, Lambrechts, Diether, Landi, Maria Teresa, Lazarus, Philip, Le, Nhu D, Lee, Eunjung, Lejbkowicz, Flavio, Lenz, Heinz-Josef, Leslie, Goska, Lessel, Davor, Lester, Jenny, Levine, Douglas A, Li, Li, Li, Christopher I, Lindblom, Annika, Lindor, Noralane M, Liu, Geoffrey, Loupakis, Fotios, Lubiński, Jan, Maehle, Lovise, Maier, Christiane, Mannermaa, Arto, Marchand, Loic Le, Margolin, Sara, May, Taymaa, McGuffog, Lesley, Meindl, Alfons, Middha, Pooja, Miller, Austin, Milne, Roger L, MacInnis, Robert J, Modugno, Francesmary, Montagna, Marco, Moreno, Victor, Moysich, Kirsten B, Mucci, Lorelei, Muir, Kenneth, Mulligan, Anna Marie, Nathanson, Katherine L, Neal, David E, Ness, Andrew R, Neuhausen, Susan L, Nevanlinna, Heli, Newcomb, Polly A, Newcomb, Lisa F, Nielsen, Finn Cilius, Nikitina-Zake, Liene, Nordestgaard, Børge G, Nussbaum, Robert L, Offit, Kenneth, Olah, Edith, Olama, Ali Amin Al, Olopade, Olufunmilayo I, Olshan, Andrew F, Olsson, Håkan, Osorio, Ana, Pandha, Hardev, Park, Jong Y, Pashayan, Nora, Parsons, Michael T, Pejovic, Tanja, Penney, Kathryn L, Peters, Wilbert HM, Phelan, Catherine M, Phipps, Amanda I, Plaseska-Karanfilska, Dijana, Pring, Miranda, Prokofyeva, Darya, Radice, Paolo, Stefansson, Kari, Ramus, Susan J, Raskin, Leon, Rennert, Gad, Rennert, Hedy S, Van Rensburg, Elizabeth J, Riggan, Marjorie J, Risch, Harvey A, Risch, Angela, Roobol, Monique J, Rosenstein, Barry S, Rossing, Mary Anne, De Ruyck, Kim, Saloustros, Emmanouil, Sandler, Dale P, Sawyer, Elinor J, Schabath, Matthew B, Schleutker, Johanna, Schmidt, Marjanka K, Setiawan, V Wendy, Shen, Hongbing, Siegel, Erin M, Sieh, Weiva, Singer, Christian F, Slattery, Martha L, Sorensen, Karina Dalsgaard, Southey, Melissa C, Spurdle, Amanda B, Stanford, Janet L, Stevens, Victoria L, Stintzing, Sebastian, Stone, Jennifer, Sundfeldt, Karin, Sutphen, Rebecca, Swerdlow, Anthony J, Tajara, Eloiza H, Tangen, Catherine M, Tardon, Adonina, Taylor, Jack A, Teare, M Dawn, Teixeira, Manuel R, Terry, Mary Beth, Terry, Kathryn L, Thibodeau, Stephen N, Thomassen, Mads, Bjørge, Line, Tischkowitz, Marc, Toland, Amanda E, Torres, Diana, Townsend, Paul A, Travis, Ruth C, Tung, Nadine, Tworoger, Shelley S, Ulrich, Cornelia M, Usmani, Nawaid, Vachon, Celine M, Van Nieuwenhuysen, Els, Vega, Ana, Aguado-Barrera, Miguel Elías, Wang, Qin, Webb, Penelope M, Weinberg, Clarice R, Weinstein, Stephanie, Weissler, Mark C, Weitzel, Jeffrey N, West, Catharine ML, White, Emily, Whittemore, Alice S, Wichmann, H-Erich, Wiklund, Fredrik, Winqvist, Robert, Wolk, Alicja, Woll, Penella, Woods, Michael, Wu, Anna H, Wu, Xifeng, Yannoukakos, Drakoulis, Zheng, Wei, Zienolddiny, Shanbeh, Ziogas, Argyrios, Zorn, Kristin K, Lane, Jacqueline M, Saxena, Richa, Thomas, Duncan, Hung, Rayjean J, Diergaarde, Brenda, McKay, James, Peters, Ulrike, Hsu, Li, García-Closas, Montserrat, Eeles, Rosalind A, Chenevix-Trench, Georgia, Brennan, Paul J, Haiman, Christopher A, Simard, Jacques, Easton, Douglas F, Gruber, Stephen B, Pharoah, Paul DP, Price, Alkes L, Pasaniuc, Bogdan, Amos, Christopher I, Kraft, Peter, and Lindström, Sara
Subjects: Male, Ovarian Neoplasms, Lung Neoplasms, Mental Disorders, Smoking, Inheritance Patterns, Prostatic Neoplasms, Breast Neoplasms, Polymorphism, Single Nucleotide, White People, 3. Good health, Neoplasm Proteins, Phenotype, Head and Neck Neoplasms, Case-Control Studies, Humans, Female, Genetic Predisposition to Disease, Colorectal Neoplasms, Genome-Wide Association Study
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.

36. Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Author: Dadaev, Tokhir, Saunders, Edward J, Newcombe, Paul J, Anokian, Ezequiel, Leongamornlert, Daniel A, Brook, Mark N, Cieza-Borrella, Clara, Mijuskovic, Martina, Wakerell, Sarah, Olama, Ali Amin Al, Schumacher, Fredrick R, Berndt, Sonja I, Benlloch, Sara, Ahmed, Mahbubl, Goh, Chee, Sheng, Xin, Zhang, Zhuo, Muir, Kenneth, Govindasami, Koveela, Lophatananon, Artitaya, Stevens, Victoria L, Gapstur, Susan M, Carter, Brian D, Tangen, Catherine M, Goodman, Phyllis, Thompson, Ian M, Batra, Jyotsna, Chambers, Suzanne, Moya, Leire, Clements, Judith, Horvath, Lisa, Tilley, Wayne, Risbridger, Gail, Gronberg, Henrik, Aly, Markus, Nordström, Tobias, Pharoah, Paul, Pashayan, Nora, Schleutker, Johanna, Tammela, Teuvo LJ, Sipeky, Csilla, Auvinen, Anssi, Albanes, Demetrius, Weinstein, Stephanie, Wolk, Alicja, Hakansson, Niclas, West, Catharine, Dunning, Alison M, Burnet, Neil, Mucci, Lorelei, Giovannucci, Edward, Andriole, Gerald, Cussenot, Olivier, Cancel-Tassin, Géraldine, Koutros, Stella, Freeman, Laura E Beane, Sorensen, Karina Dalsgaard, Orntoft, Torben Falck, Borre, Michael, Maehle, Lovise, Grindedal, Eli Marie, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Travis, Ruth C, Key, Tim J, Hamilton, Robert J, Fleshner, Neil E, Finelli, Antonio, Ingles, Sue Ann, Stern, Mariana C, Rosenstein, Barry, Kerns, Sarah, Ostrer, Harry, Lu, Yong-Jie, Zhang, Hong-Wei, Feng, Ninghan, Mao, Xueying, Guo, Xin, Wang, Guomin, Sun, Zan, Giles, Graham G, Southey, Melissa C, MacInnis, Robert J, FitzGerald, Liesel M, Kibel, Adam S, Drake, Bettina F, Vega, Ana, Gómez-Caamaño, Antonio, Fachal, Laura, Szulkin, Robert, Eklund, Martin, Kogevinas, Manolis, Llorca, Javier, Castaño-Vinyals, Gemma, Penney, Kathryn L, Stampfer, Meir, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Stanford, Janet L, Cybulski, Cezary, Wokolorczyk, Dominika, Lubinski, Jan, Ostrander, Elaine A, Geybels, Milan S, Nordestgaard, Børge G, Nielsen, Sune F, Weisher, Maren, Bisbjerg, Rasmus, Røder, Martin Andreas, Iversen, Peter, Brenner, Hermann, Cuk, Katarina, Holleczek, Bernd, Maier, Christiane, Luedeke, Manuel, Schnoeller, Thomas, Kim, Jeri, Logothetis, Christopher J, John, Esther M, Teixeira, Manuel R, Paulo, Paula, Cardoso, Marta, Neuhausen, Susan L, Steele, Linda, Ding, Yuan Chun, De Ruyck, Kim, De Meerleer, Gert, Ost, Piet, Razack, Azad, Lim, Jasmine, Teo, Soo-Hwang, Lin, Daniel W, Newcomb, Lisa F, Lessel, Davor, Gamulin, Marija, Kulis, Tomislav, Kaneva, Radka, Usmani, Nawaid, Slavov, Chavdar, Mitev, Vanio, Parliament, Matthew, Singhal, Sandeep, Claessens, Frank, Joniau, Steven, Van Den Broeck, Thomas, Larkin, Samantha, Townsend, Paul A, Aukim-Hastie, Claire, Gago-Dominguez, Manuela, Castelao, Jose Esteban, Martinez, Maria Elena, Roobol, Monique J, Jenster, Guido, Van Schaik, Ron HN, Menegaux, Florence, Truong, Thérèse, Koudou, Yves Akoli, Xu, Jianfeng, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Michael, Agnieszka, Kierzek, Andrzej, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Lindstrom, Sara, Turman, Constance, Ma, Jing, Hunter, David J, Riboli, Elio, Siddiq, Afshan, Canzian, Federico, Kolonel, Laurence N, Le Marchand, Loic, Hoover, Robert N, Machiela, Mitchell J, Kraft, Peter, PRACTICAL (Prostate Cancer Association Group To Investigate Cancer-Associated Alterations In The Genome) Consortium, Freedman, Matthew, Wiklund, Fredrik, Chanock, Stephen, Henderson, Brian E, Easton, Douglas F, Haiman, Christopher A, Eeles, Rosalind A, Conti, David V, and Kote-Jarai, Zsofia
Subjects: Male, Risk, Quantitative Trait Loci, Black People, Chromosome Mapping, Prostatic Neoplasms, Bayes Theorem, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, White People, 3. Good health, Multivariate Analysis, Humans, Genetic Predisposition to Disease, Algorithms, Genome-Wide Association Study
Abstract: Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

37. Genome-wide association study identifies three new melanoma susceptibility loci

Author: Barrett, Jennifer H., Iles, Mark M., Harland, Mark, Taylor, John C., Aitken, Joanne F., Andresen, Per Arne, Akslen, Lars A., Armstrong, Bruce K., Avril, Marie F., Azizi, Esther, Bakker, Bert, Bergman, Wilma, Bianchi-Scarrà, Giovanna, Bressac-de Paillerets, Brigitte, Calista, Donato, Cannon-Albright, Lisa A., Corda, Eve, Cust, Anne E., Debniak, Tadeusz, Duffy, David, Dunning, Alison M., Easton, Douglas F., Friedman, Eitan, Galan, Pilar, Ghiorzo, Paola, Giles, Graham G., Hansson, Johan, Hocevar, Marko, Höiom, Veronica, Hopper, John L., Ingvar, Christian, Janssen, Bart, Jenkins, Mark A., Jönsson, Göran, Kefford, Richard F., Landi, Giorgio, Landi, Maria Teresa, Lang, Julie, Lubinski, Jan, Mackie, Rona, Malvehy, J. (Josep), Martin, Nicholas G., Molven, Anders, Montgomery, Grant W., Nieuwpoort, Frans A. van, Novakovic, Srdjan, Olsson, Hakan, Pastorino, Lorenza, Puig i Sardà, Susana, Puig Butillé, Joan Anton, Randerson-Moor, Juliette, Snowden, Helen, Tuominen, Raider, Belle, Patricia van, Stoep, Nienke van der, Whiteman, David C., Zelenika, Diana, Han, Jiali, Fang, Shenying, Lee, Jeffrey E., Wei, Qingyi, Lathrop, G. Mark, Gillanders, Elizabeth M., Brown, Kevin M., Goldstein, Alisa M., Kanetsky, Peter A., Mann, Graham J., MacGregor, Stuart, Elder, David E., Amos, Christopher I., Hayward, Nicholas K., Gruis, Nelleke A., Demenais, Florence, Newton-Bishop, Julia, Bishop, D. Timothy, GenoMEL Consortium, and Universitat de Barcelona
Subjects: Genètica mèdica, Medical genetics, Skin cancer, Melanoma, Càncer de pell
Abstract: We report a genome-wide association study for melanoma that was conducted by the GenoMEL Consortium. Our discovery phase included 2,981 individuals with melanoma and 1,982 study-specific control individuals of European ancestry, as well as an additional 6,426 control subjects from French or British populations, all of whom were genotyped for 317,000 or 610,000 single-nucleotide polymorphisms (SNPs). Our analysis replicated previously known melanoma susceptibility loci. Seven new regions with at least one SNP with P < 10−5 and further local imputed or genotyped support were selected for replication using two other genome-wide studies (from Australia and Texas, USA). Additional replication came from case-control series from the UK and The Netherlands. Variants at three of the seven loci replicated at P < 10−3: an SNP in ATM (rs1801516, overall P = 3.4 × 10−9), an SNP in MX2 (rs45430, P = 2.9 × 10−9) and an SNP adjacent to CASP8 (rs13016963, P = 8.6 × 10−10). A fourth locus near CCND1 remains of potential interest, showing suggestive but inconclusive evidence of replication (rs1485993, overall P = 4.6 × 10−7 under a fixed-effects model and P = 1.2 × 10−3 under a random-effects model). These newly associated variants showed no association with nevus or pigmentation phenotypes in a large British case-control series.

38. Polygenic hazard score is associated with prostate cancer in multi-ethnic populations

Author: Florence Menegaux, William J. Blot, Henrik Grönberg, Luc Multigner, Sune F. Nielsen, Stella Koutros, Frank Claessens, Manuela Gago-Dominguez, Kathryn L. Penney, Tyler M. Seibert, Cezary Cybulski, Jennifer J. Hu, Hermann Brenner, Radka Kaneva, Sue A. Ingles, Catherine M. Tangen, Ian G. Mills, Janet L. Stanford, Karina Dalsgaard Sørensen, Ruth C. Travis, Marie-Élise Parent, Monique J. Roobol, Nora Pashayan, Jyotsna Batra, Maria Elena Martinez, Anders M. Dale, Wei Zheng, Kay-Tee Khaw, Chad D. Huff, Chun Chieh Fan, Paul A. Townsend, Kim De Ruyck, Yong-Jie Lu, Eli Marie Grindedal, Hardev Pandha, Sonja I. Berndt, Susan L. Neuhausen, Alicja Wolk, Apcb, Wesley K. Thompson, Maureen Sanderson, Demetrius Albanes, Stephen N. Thibodeau, Christiane Maier, Kenneth Muir, Robin J. Leach, Børge G. Nordestgaard, Ole A. Andreassen, Fredrik Wiklund, Graham G. Giles, Zsofia Kote-Jarai, Catharine M L West, Minh-Phuong Huynh-Le, Manolis Kogevinas, Manuel R. Teixeira, Jong Y. Park, Johanna Schleutker, Marija Gamulin, Freddie C. Hamdy, William S. Bush, Barry S. Rosenstein, Stephen Watya, Roshan Karunamuni, Richard M. Martin, Nc-La PCaP Investigators, Ana Vega, Adam S. Kibel, Lisa A. Cannon-Albright, Azad Hassan Abdul Razack, Esther M. John, Christopher J. Logothetis, Jay H. Fowke, Nawaid Usmani, David E. Neal, Canary Pass Investigators, Rosalind A. Eeles, Robert J. Hamilton, Lisa F. Newcomb, Jenny L Donovan, Olivier Cussenot, Lorelei A. Mucci, University of California [San Diego] (UC San Diego), University of California, The institute of cancer research [London], University of Manchester [Manchester], University of Turku, Centre for Cancer Genetic Epidemiology [Cambridge], Department of Oncology-University of Cambridge [UK] (CAM), University College of London [London] (UCL), Centre de Recherche pour les Pathologies Prostatiques [Paris] (CeRePP), Sorbonne Université (SU), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Institut de recherche en santé, environnement et travail (Irset), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Santé et de la Recherche Médicale (INSERM)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université d'Angers (UA), This study was funded in part by a grant from the United States National Institute of Health/National Institute of Biomedical Imaging and Bioengineering (#K08EB026503), United States Department of Defense (#W81XWH-13-1-0391), University of California CRCC C21CR2060, the Research Council of Norway (#223273), K.G. Jebsen Stiftelsen, and South East Norway Health Authority. RM Martin is supported in part by the National Institute for Health Research Bristol Biomedical Research Centre. The CAP trial is funded by Cancer Research UK and the UK Department of Health (C11043/A4286, C18281/A8145, C18281/A11326, C18281/A15064, and C18281/A24432). R.M. Martin was supported by a Cancer Research UK (C18281/A19169) program grant (the Integrative Cancer Epidemiology Programme). Funding for the PRACTICAL consortium member studies is detailed in the Supplementary Information., University of California (UC), University of Cambridge [UK] (CAM)-Department of Oncology, Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Huynh-Le, Minh-Phuong [0000-0002-5025-4709], Fan, Chun Chieh [0000-0001-9437-2128], Eeles, Rosalind A [0000-0002-3698-6241], Muir, Kenneth [0000-0001-6429-988X], Schleutker, Johanna [0000-0002-1863-0305], Pashayan, Nora [0000-0003-0843-2468], Batra, Jyotsna [0000-0003-4646-6247], Grönberg, Henrik [0000-0002-1073-2753], Martin, Richard M [0000-0002-7992-7719], Nordestgaard, Børge G [0000-0002-1954-7220], Wiklund, Fredrik [0000-0002-4623-0544], Giles, Graham G [0000-0003-4946-9099], Wolk, Alicja [0000-0001-7387-6845], Travis, Ruth C [0000-0002-9571-0763], Zheng, Wei [0000-0003-1226-070X], West, Catharine ML [0000-0002-0839-3449], Sørensen, Karina Dalsgaard [0000-0002-4902-5490], Park, Jong Y [0000-0002-6384-6447], Vega, Ana [0000-0002-7416-5137], Teixeira, Manuel R [0000-0002-4896-5982], Multigner, Luc [0000-0003-3205-8568], Cannon-Albright, Lisa [0000-0003-2602-3668], Gamulin, Marija [0000-0003-2431-7910], Bush, William S [0000-0002-9729-6519], Roobol, Monique J [0000-0001-6967-1708], Andreassen, Ole A [0000-0002-4461-3568], Seibert, Tyler M [0000-0002-4089-7399], Apollo - University of Cambridge Repository, and Clinical Chemistry
Subjects: 0301 basic medicine, Oncology, Male, Multifactorial Inheritance, Aging, Multivariate analysis, Ethnic Groups/genetics, General Physics and Astronomy, UKGPCS collaborators, Prostate cancer, 0302 clinical medicine, Urologi och njurmedicin, Ethnicity, risk factors, PRACTICAL Consortium, genetics, Stage (cooking), AgedEthnic Groups / genetics, Cancer, Multidisciplinary, Manchester Cancer Research Centre, Prostatic Neoplasms/genetics, Prostate Cancer, Hazard ratio, APCB, Middle Aged, Hazard, Health equity, 3. Good health, Multidisciplinary Sciences, 030220 oncology & carcinogenesis, Science & Technology - Other Topics, polygenic hazard score (PHS1), prostate cancer, ICEP, Medical Genetics, Urologic Diseases, medicine.medical_specialty, hazard, precision medicine, Science, Prostatic Neoplasms / genetics, [SDV.CAN]Life Sciences [q-bio]/Cancer, Ethnic Groups, survival, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Medical research, SDG 3 - Good Health and Well-being, Internal medicine, NC-LA PCaP Investigators, Genetic model, medicine, Urology and Nephrology, Humans, Neoplasm Invasiveness, Multifactorial Inheritance/genetics, Medicinsk genetik, Aged, Canary PASS Investigators, Science & Technology, IMPACT Study Steering Committee and Collaborators, business.industry, Profile Study Steering Committee, ResearchInstitutes_Networks_Beacons/mcrc, Prostatic Neoplasms, General Chemistry, medicine.disease, Multifactorial Inheritance / genetics, 030104 developmental biology, Multivariate Analysis, Self Report, business, Biomarkers
Abstract: Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS1) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS2 (PHS1, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p, A polygenic hazard score (PHS1) improves prostate cancer screening accuracy in European patients. Here, the authors test the performance of a version compatible with OncoArray genotypes (PHS2) in a multi-ethnic dataset and find that it risk-stratifies men for any, aggressive, and fatal prostate cancer.
Published: 2021

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