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1. A methylation risk score for chronic kidney disease: a HyperGEN study

Author

Jones, Alana C, Patki, Amit, Srinivasasainagendra, Vinodh, Hidalgo, Bertha A, Tiwari, Hemant K, Limdi, Nita A, Armstrong, Nicole D, Chaudhary, Ninad S, Minniefield, Bré, Absher, Devin, Arnett, Donna K, Lange, Leslie A, Lange, Ethan M, Young, Bessie A, Diamantidis, Clarissa J, Rich, Stephen S, Mychaleckyj, Josyf C, Rotter, Jerome I, Taylor, Kent D, Kramer, Holly J, Tracy, Russell P, Durda, Peter, Kasela, Silva, Lappalinen, Tuuli, Liu, Yongmei, Johnson, W Craig, Van Den Berg, David J, Franceschini, Nora, Liu, Simin, Mouton, Charles P, Bhatti, Parveen, Horvath, Steve, Whitsel, Eric A, and Irvin, Marguerite R

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Prevention, Clinical Research, Human Genome, Health Disparities, Kidney Disease, Minority Health, Women's Health, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Renal and urogenital, Humans, Renal Insufficiency, Chronic, DNA Methylation, Male, Female, Middle Aged, Glomerular Filtration Rate, CpG Islands, Risk Factors, Black or African American, Aged, Genome-Wide Association Study, Epigenesis, Genetic, Adult, Genetic Predisposition to Disease, Chronic kidney disease, eGFR, Methylation risk score, Epigenetics
Abstract

Chronic kidney disease (CKD) impacts about 1 in 7 adults in the United States, but African Americans (AAs) carry a disproportionately higher burden of disease. Epigenetic modifications, such as DNA methylation at cytosine-phosphate-guanine (CpG) sites, have been linked to kidney function and may have clinical utility in predicting the risk of CKD. Given the dynamic relationship between the epigenome, environment, and disease, AAs may be especially sensitive to environment-driven methylation alterations. Moreover, risk models incorporating CpG methylation have been shown to predict disease across multiple racial groups. In this study, we developed a methylation risk score (MRS) for CKD in cohorts of AAs. We selected nine CpG sites that were previously reported to be associated with estimated glomerular filtration rate (eGFR) in epigenome-wide association studies to construct a MRS in the Hypertension Genetic Epidemiology Network (HyperGEN). In logistic mixed models, the MRS was significantly associated with prevalent CKD and was robust to multiple sensitivity analyses, including CKD risk factors. There was modest replication in validation cohorts. In summary, we demonstrated that an eGFR-based CpG score is an independent predictor of prevalent CKD, suggesting that MRS should be further investigated for clinical utility in evaluating CKD risk and progression.

Published
2024

3. Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI.

Author

Do, Whitney, Sun, Dianjianyi, Meeks, Karlijn, Dugué, Pierre-Antoine, Demerath, Ellen, Guan, Weihua, Li, Shengxu, Chen, Wei, Milne, Roger, Adeyemo, Abedowale, Agyemang, Charles, Nassir, Rami, Manson, JoAnn, Hou, Lifang, Horvath, Steve, Assimes, Themistocles, Bhatti, Parveen, Jordahl, Kristina, Baccarelli, Andrea, Smith, Alicia, Staimez, Lisa, Stein, Aryeh, Whitsel, Eric, Narayan, K, Conneely, Karen, and Shadyab, Aladdin

Subjects
BMI, DNA methylation, adiposity, epigenome-wide association study, epigenomics, metabolic disease, obesity, prediction, Humans, Female, Body Mass Index, Epigenome, Epigenesis, Genetic, Obesity, Cholesterol, HDL, Genome-Wide Association Study, DNA Methylation, Epigenomics, Triglycerides, CpG Islands
Abstract

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Womens Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p

Published
2023

4. DNA methylation in peripheral blood leukocytes for the association with glucose metabolism and invasive breast cancer

Author

Jung, Su Yon, Bhatti, Parveen, and Pellegrini, Matteo

Subjects
Biological Sciences, Genetics, Human Genome, Breast Cancer, Prevention, Cancer, Nutrition, Diabetes, Aging, Aetiology, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, 2.1 Biological and endogenous factors, Good Health and Well Being, Female, Humans, DNA Methylation, Glucose, Insulin, Insulin Resistance, Leukocytes, Risk Factors, Breast Neoplasms, Epigenetic signatures, DNA methylation, Glucose homeostasis, Obesity, Invasive breast cancer, Postmenopausal women, Clinical Sciences, Paediatrics and Reproductive Medicine
Abstract

BackgroundInsulin resistance (IR) is a well-established factor for breast cancer (BC) risk in postmenopausal women, but the interrelated molecular pathways on the methylome are not explicitly described. We conducted a population-level epigenome-wide association (EWA) study for DNA methylation (DNAm) probes that are associated with IR and prospectively correlated with BC development, both overall and in BC subtypes among postmenopausal women.MethodsWe used data from Women's Health Initiative (WHI) ancillary studies for our EWA analyses and evaluated the associations of site-specific DNAm across the genome with IR phenotypes by multiple regressions adjusting for age and leukocyte heterogeneities. For our analysis of the top 20 IR-CpGs with BC risk, we used the WHI and the Cancer Genomic Atlas (TCGA), using multiple Cox proportional hazards and logit regressions, respectively, accounting for age, diabetes, obesity, leukocyte heterogeneities, and tumor purity (for TCGA). We further conducted a Gene Set Enrichment Analysis.ResultsWe detected several EWA-CpGs in TXNIP, CPT1A, PHGDH, and ABCG1. In particular, cg19693031 in TXNIP was replicated in all IR phenotypes, measured by fasting levels of glucose, insulin, and homeostatic model assessment-IR. Of those replicated IR-genes, 3 genes (CPT1A, PHGDH, and ABCG1) were further correlated with BC risk; and 1 individual CpG (cg01676795 in POR) was commonly detected across the 2 cohorts.ConclusionsOur study contributes to better understanding of the interconnected molecular pathways on the methylome between IR and BC carcinogenesis and suggests potential use of DNAm markers in the peripheral blood cells as preventive targets to detect an at-risk group for IR and BC in postmenopausal women.

Published
2023

5. Does a Multiple Myeloma Polygenic Risk Score Predict Overall Survival of Patients with Myeloma?

Author

Macauda, Angelica, Clay-Gilmour, Alyssa, Hielscher, Thomas, Hildebrandt, Michelle, Kruszewski, Marcin, Orlowski, Robert, Kumar, Shaji, Ziv, Elad, Orciuolo, Enrico, Brown, Elizabeth, Försti, Asta, Waller, Rosalie, Machiela, Mitchell, Chanock, Stephen, Camp, Nicola, Rymko, Marcin, Raźny, Małgorzata, Cozen, Wendy, Várkonyi, Judit, Piredda, Chiara, Pelosini, Matteo, Belachew, Alem, Subocz, Edyta, Hemminki, Kari, Rybicka-Ramos, Malwina, Giles, Graham, Milne, Roger, Hofmann, Jonathan, Zaucha, Jan, Vangsted, Annette, Goldschmidt, Hartmut, Rajkumar, S, Tomczak, Waldemar, Sainz, Juan, Butrym, Aleksandra, Watek, Marzena, Iskierka-Jazdzewska, Elżbieta, Buda, Gabriele, Robinson, Dennis, Jurczyszyn, Artur, Dudziński, Marek, Martinez-Lopez, Joaquin, Sinnwell, Jason, Slager, Susan, Jamroziak, Krzysztof, Reis, Rui, Weinhold, Niels, Bhatti, Parveen, Carvajal-Carmona, Luis, Zawirska, Daria, Norman, Aaron, Mazur, Grzegorz, Berndt, Sonja, Campa, Daniele, Vachon, Celine, and Canzian, Federico

Subjects
Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multiple Myeloma, Polymorphism, Single Nucleotide, Risk Factors
Abstract

BACKGROUND: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival. METHODS: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. RESULTS: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P < 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09-1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01-1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. CONCLUSIONS: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. IMPACT: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma.

Published
2022

8. Identification of novel genetic loci for risk of multiple myeloma by functional annotation

Author

Macauda, Angelica, Briem, Klara, Clay-Gilmour, Alyssa, Cozen, Wendy, Försti, Asta, Giaccherini, Matteo, Corradi, Chiara, Sainz, Juan, Niazi, Yasmeen, ter Horst, Rob, Li, Yang, Netea, Mihai G., Vogel, Ulla, Hemminki, Kari, Slager, Susan L., Varkonyi, Judit, Andersen, Vibeke, Iskierka-Jazdzewska, Elzbieta, Mártinez-Lopez, Joaquin, Zaucha, Jan, Camp, Nicola J., Rajkumar, S. Vincent, Druzd-Sitek, Agnieszka, Bhatti, Parveen, Chanock, Stephen J., Kumar, Shaji K., Subocz, Edyta, Mazur, Grzegorz, Landi, Stefano, Machiela, Mitchell J., Jerez, Andrés, Norman, Aaron D., Hildebrandt, Michelle A. T., Kadar, Katalin, Berndt, Sonja I., Ziv, Elad, Buda, Gabriele, Nagler, Arnon, Dumontet, Charles, Raźny, Malgorzata, Watek, Marzena, Butrym, Aleksandra, Grzasko, Norbert, Dudzinski, Marek, Rybicka-Ramos, Malwina, Matera, Eva-Laure, García-Sanz, Ramón, Goldschmidt, Hartmut, Jamroziak, Krzysztof, Jurczyszyn, Artur, Clavero, Esther, Giles, Graham G., Pelosini, Matteo, Zawirska, Daria, Kruszewski, Marcin, Marques, Herlander, Haastrup, Eva, Sánchez-Maldonado, José Manuel, Bertsch, Uta, Rymko, Marcin, Raab, Marc-Steffen, Brown, Elizabeth E., Hofmann, Jonathan N., Vachon, Celine, Campa, Daniele, and Canzian, Federico

Published
2023
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10. Associations between DNA methylation and BMI vary by metabolic health status: a potential link to disparate cardiovascular outcomes

Author

Do, Whitney L, Nguyen, Steve, Yao, Jie, Guo, Xiuqing, Whitsel, Eric A, Demerath, Ellen, Rotter, Jerome I, Rich, Stephen S, Lange, Leslie, Ding, Jingzhong, Van Den Berg, David, Liu, Yongmei, Justice, Anne E, Guan, Weihua, Horvath, Steve, Assimes, Themistocles L, Bhatti, Parveen, Jordahl, Kristina, Shadyab, Aladdin, Valencia, Celina I, Stein, Aryeh D, Smith, Alicia, Staimez, Lisa R, Conneely, Karen, and Narayan, KM Venkat

Subjects
Biological Sciences, Genetics, Heart Disease - Coronary Heart Disease, Nutrition, Obesity, Cardiovascular, Aging, Clinical Research, Heart Disease, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Aged, Body Mass Index, Cardiovascular Diseases, Cohort Studies, DNA Methylation, Female, Humans, Male, Metabolic Diseases, Middle Aged, DNA methylation, Metabolically healthy, Epigenetics, Clinical Sciences, Paediatrics and Reproductive Medicine
Abstract

BackgroundBody mass index (BMI), a well-known risk factor for poor cardiovascular outcomes, is associated with differential DNA methylation (DNAm). Similarly, metabolic health has also been associated with changes in DNAm. It is unclear how overall metabolic health outside of BMI may modify the relationship between BMI and methylation profiles, and what consequences this may have on downstream cardiovascular disease. The purpose of this study was to identify cytosine-phosphate-guanine (CpG) sites at which the association between BMI and DNAm could be modified by overall metabolic health.ResultsThe discovery study population was derived from three Women's Health Initiative (WHI) ancillary studies (n = 3977) and two Atherosclerosis Risk in Communities (ARIC) ancillary studies (n = 3520). Findings were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort (n = 1200). Generalized linear models regressed methylation β values on the interaction between BMI and metabolic health Z score (BMI × MHZ) adjusted for BMI, MHZ, cell composition, chip number and location, study characteristics, top three ancestry principal components, smoking, age, ethnicity (WHI), and sex (ARIC). Among the 429,566 sites examined, differential associations between BMI × MHZ and DNAm were identified at 22 CpG sites (FDR q

Published
2021

11. Epigenome-wide association study of diet quality in the Women's Health Initiative and TwinsUK cohort.

Author

Do, Whitney L, Whitsel, Eric A, Costeira, Ricardo, Masachs, Olatz M, Le Roy, Caroline I, Bell, Jordana T, Staimez, Lisa R, Stein, Aryeh D, Smith, Alicia K, Horvath, Steve, Assimes, Themistocles L, Liu, Simin, Manson, JoAnn E, Shadyab, Aladdin H, Li, Yun, Hou, Lifang, Bhatti, Parveen, Jordahl, Kristina, Narayan, KM Venkat, and Conneely, Karen N

Subjects
Human Genome, Obesity, Prevention, Nutrition, Genetics, 2.2 Factors relating to the physical environment, Aetiology, Cancer, Cardiovascular, CpG Islands, DNA Methylation, Diet, Epigenesis, Genetic, Epigenome, Female, Genome-Wide Association Study, Humans, Proteins, Women's Health, diet quality, dietary epigenetics, EWAS, Women's Health Initiative, Women’s Health Initiative, Statistics, Public Health and Health Services, Epidemiology
Abstract

BackgroundDiet quality is a risk factor for chronic disease and mortality. Differential DNA methylation across the epigenome has been associated with chronic disease risk. Whether diet quality is associated with differential methylation is unknown. This study assessed whether diet quality was associated with differential DNA methylation measured across 445 548 loci in the Women's Health Initiative (WHI) and the TwinsUK cohort.DesignThe discovery cohort consisted of 4355 women from the WHI. The replication cohort consisted of 571 mono- and dizygotic twins from the TwinsUK cohort. DNA methylation was measured in whole blood using the Illumina Infinium HumanMethylation450 Beadchip. Diet quality was assessed using the Alternative Healthy Eating Index 2010 (AHEI-2010). A meta-analysis, stratified by study cohort, was performed using generalized linear models that regressed methylation on AHEI-2010, adjusting for cell composition, chip number and location, study characteristics, principal components of genetic relatedness, age, smoking status, race/ethnicity and body mass index (BMI). Statistical significance was defined as a false discovery rate < 0.05. Significant sites were tested for replication in the TwinsUK cohort, with significant replication defined by P

Published
2021

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

Author

Berndt, Sonja I., Vijai, Joseph, Benavente, Yolanda, Camp, Nicola J., Nieters, Alexandra, Wang, Zhaoming, Smedby, Karin E., Kleinstern, Geffen, Hjalgrim, Henrik, Besson, Caroline, Skibola, Christine F., Morton, Lindsay M., Brooks-Wilson, Angela R., Teras, Lauren R., Breeze, Charles, Arias, Joshua, Adami, Hans-Olov, Albanes, Demetrius, Anderson, Kenneth C., Ansell, Stephen M., Bassig, Bryan, Becker, Nikolaus, Bhatti, Parveen, Birmann, Brenda M., Boffetta, Paolo, Bracci, Paige M., Brennan, Paul, Brown, Elizabeth E., Burdett, Laurie, Cannon-Albright, Lisa A., Chang, Ellen T., Chiu, Brian C. H., Chung, Charles C., Clavel, Jacqueline, Cocco, Pierluigi, Colditz, Graham, Conde, Lucia, Conti, David V., Cox, David G., Curtin, Karen, Casabonne, Delphine, De Vivo, Immaculata, Diepstra, Arjan, Diver, W. Ryan, Dogan, Ahmet, Edlund, Christopher K., Foretova, Lenka, Fraumeni, Jr, Joseph F., Gabbas, Attilio, Ghesquières, Hervé, Giles, Graham G., Glaser, Sally, Glenn, Martha, Glimelius, Bengt, Gu, Jian, Habermann, Thomas M., Haiman, Christopher A., Haioun, Corinne, Hofmann, Jonathan N., Holford, Theodore R., Holly, Elizabeth A., Hutchinson, Amy, Izhar, Aalin, Jackson, Rebecca D., Jarrett, Ruth F., Kaaks, Rudolph, Kane, Eleanor, Kolonel, Laurence N., Kong, Yinfei, Kraft, Peter, Kricker, Anne, Lake, Annette, Lan, Qing, Lawrence, Charles, Li, Dalin, Liebow, Mark, Link, Brian K., Magnani, Corrado, Maynadie, Marc, McKay, James, Melbye, Mads, Miligi, Lucia, Milne, Roger L., Molina, Thierry J., Monnereau, Alain, Montalvan, Rebecca, North, Kari E., Novak, Anne J., Onel, Kenan, Purdue, Mark P., Rand, Kristin A., Riboli, Elio, Riby, Jacques, Roman, Eve, Salles, Gilles, Sborov, Douglas W., Severson, Richard K., Shanafelt, Tait D., Smith, Martyn T., Smith, Alexandra, Song, Kevin W., Song, Lei, Southey, Melissa C., Spinelli, John J., Staines, Anthony, Stephens, Deborah, Sutherland, Heather J., Tkachuk, Kaitlyn, Thompson, Carrie A., Tilly, Hervé, Tinker, Lesley F., Travis, Ruth C., Turner, Jenny, Vachon, Celine M., Vajdic, Claire M., Van Den Berg, Anke, Van Den Berg, David J., Vermeulen, Roel C. H., Vineis, Paolo, Wang, Sophia S., Weiderpass, Elisabete, Weiner, George J., Weinstein, Stephanie, Doo, Nicole Wong, Ye, Yuanqing, Yeager, Meredith, Yu, Kai, Zeleniuch-Jacquotte, Anne, Zhang, Yawei, Zheng, Tongzhang, Ziv, Elad, Sampson, Joshua, Chatterjee, Nilanjan, Offit, Kenneth, Cozen, Wendy, Wu, Xifeng, Cerhan, James R., Chanock, Stephen J., Slager, Susan L., and Rothman, Nathaniel

Published
2022
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13. Correction: Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes

Author

Berndt, Sonja I., Vijai, Joseph, Benavente, Yolanda, Camp, Nicola J., Nieters, Alexandra, Wang, Zhaoming, Smedby, Karin E., Kleinstern, Geffen, Hjalgrim, Henrik, Besson, Caroline, Skibola, Christine F., Morton, Lindsay M., Brooks-Wilson, Angela R., Teras, Lauren R., Breeze, Charles, Arias, Joshua, Adami, Hans-Olov, Albanes, Demetrius, Anderson, Kenneth C., Ansell, Stephen M., Bassig, Bryan, Becker, Nikolaus, Bhatti, Parveen, Birmann, Brenda M., Boffetta, Paolo, Bracci, Paige M., Brennan, Paul, Brown, Elizabeth E., Burdett, Laurie, Cannon-Albright, Lisa A., Chang, Ellen T., Chiu, Brian C. H., Chung, Charles C., Clavel, Jacqueline, Cocco, Pierluigi, Colditz, Graham, Conde, Lucia, Conti, David V., Cox, David G., Curtin, Karen, Casabonne, Delphine, De Vivo, Immaculata, Diepstra, Arjan, Diver, W. Ryan, Dogan, Ahmet, Edlund, Christopher K., Foretova, Lenka, Fraumeni, Jr, Joseph F., Gabbas, Attilio, Ghesquières, Hervé, Giles, Graham G., Glaser, Sally, Glenn, Martha, Glimelius, Bengt, Gu, Jian, Habermann, Thomas M., Haiman, Christopher A., Haioun, Corinne, Hofmann, Jonathan N., Holford, Theodore R., Holly, Elizabeth A., Hutchinson, Amy, Izhar, Aalin, Jackson, Rebecca D., Jarrett, Ruth F., Kaaks, Rudolph, Kane, Eleanor, Kolonel, Laurence N., Kong, Yinfei, Kraft, Peter, Kricker, Anne, Lake, Annette, Lan, Qing, Lawrence, Charles, Li, Dalin, Liebow, Mark, Link, Brian K., Magnani, Corrado, Maynadie, Marc, McKay, James, Melbye, Mads, Miligi, Lucia, Milne, Roger L., Molina, Thierry J., Monnereau, Alain, Montalvan, Rebecca, North, Kari E., Novak, Anne J., Onel, Kenan, Purdue, Mark P., Rand, Kristin A., Riboli, Elio, Riby, Jacques, Roman, Eve, Salles, Gilles, Sborov, Douglas W., Severson, Richard K., Shanafelt, Tait D., Smith, Martyn T., Smith, Alexandra, Song, Kevin W., Song, Lei, Southey, Melissa C., Spinelli, John J., Staines, Anthony, Stephens, Deborah, Sutherland, Heather J., Tkachuk, Kaitlyn, Thompson, Carrie A., Tilly, Hervé, Tinker, Lesley F., Travis, Ruth C., Turner, Jenny, Vachon, Celine M., Vajdic, Claire M., Van Den Berg, Anke, Van Den Berg, David J., Vermeulen, Roel C. H., Vineis, Paolo, Wang, Sophia S., Weiderpass, Elisabete, Weiner, George J., Weinstein, Stephanie, Doo, Nicole Wong, Ye, Yuanqing, Yeager, Meredith, Yu, Kai, Zeleniuch-Jacquotte, Anne, Zhang, Yawei, Zheng, Tongzhang, Ziv, Elad, Sampson, Joshua, Chatterjee, Nilanjan, Offit, Kenneth, Cozen, Wendy, Wu, Xifeng, Cerhan, James R., Chanock, Stephen J., Slager, Susan L., and Rothman, Nathaniel

Published
2023
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18. Advisory Group recommendations on priorities for the IARC Monographs

Author

Berrington de González, Amy, primary, Masten, Scott A, additional, Bhatti, Parveen, additional, Fortner, Renée Turzanski, additional, Peters, Susan, additional, Santonen, Tiina, additional, Yakubovskaya, Marianna G, additional, Barouki, Robert, additional, Barros, Silvia B M, additional, Barupal, Dinesh, additional, Beane Freeman, Laura E, additional, Calaf, Gloria M, additional, Dillner, Joakim, additional, El Rhazi, Karima, additional, Fritschi, Lin, additional, Fukushima, Shoji, additional, Godderis, Lode, additional, Kogevinas, Manolis, additional, Lachenmeier, Dirk W, additional, Mandrioli, Daniele, additional, Muchengeti, Mazvita M, additional, Niemeier, Richard T, additional, Pappas, Jane J, additional, Pi, Jingbo, additional, Purdue, Mark P, additional, Riboli, Elio, additional, Rodríguez, Teresa, additional, Schlünssen, Vivi, additional, Benbrahim-Tallaa, Lamia, additional, de Conti, Aline, additional, Facchin, Caterina, additional, Pasqual, Elisa, additional, Wedekind, Roland, additional, Ahmadi, Ayat, additional, Chittiboyina, Shirisha, additional, Herceg, Zdenko, additional, Kulasingam, Shalini, additional, Lauby-Secretan, Béatrice, additional, MacLehose, Richard, additional, Sanaa, Moez, additional, Schüz, Joachim, additional, Suonio, Eero, additional, Zavadil, Jiri, additional, Mattock, Heidi, additional, Madia, Federica, additional, and Schubauer-Berigan, Mary K, additional

Published
2024
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20. 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
Biomedical and Clinical Sciences, Cancer, Clinical Research, Genetics, Rare Diseases, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Adult, Aged, Black People, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Multiple Myeloma, Polycomb Repressive Complex 1, Polymorphism, Single Nucleotide, Protein Serine-Threonine Kinases, Repressor Proteins, Transmembrane Activator and CAML Interactor Protein, White People, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
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

21. Stressful life events, social support, and epigenetic aging in the Women's Health Initiative

Author

Skinner, Harlyn G., primary, Palma‐Gudiel, Helena, additional, Stewart, James D., additional, Love, Shelly‐Ann, additional, Bhatti, Parveen, additional, Shadyab, Aladdin H., additional, Wallace, Robert B., additional, Salmoirago‐Blotcher, Elena, additional, Manson, JoAnn E., additional, Kroenke, Candyce H., additional, Belsky, Daniel W., additional, Li, Yun, additional, Whitsel, Eric A., additional, and Zannas, Anthony S., additional

Published
2023
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25. Pooled study of occupational exposure to aromatic hydrocarbon solvents and risk of multiple myeloma

Author

De Roos, Anneclaire J, Spinelli, John, Brown, Elizabeth B, Atanackovic, Djordje, Baris, Dalsu, Bernstein, Leslie, Bhatti, Parveen, Camp, Nicola J, Chiu, Brian C, Clavel, Jacqueline, Cozen, Wendy, De Sanjosé, Silvia, Dosman, James A, Hofmann, Jonathan N, McLaughlin, John R, Miligi, Lucia, Monnereau, Alain, Orsi, Laurent, Purdue, Mark P, Schinasi, Leah H, Tricot, Guido J, Wang, Sophia S, Zhang, Yawei, Birmann, Brenda M, and Cocco, Pierluigi

Published
2018

29. Systems Age: A single blood methylation test to quantify aging heterogeneity across 11 physiological systems

Author

Sehgal, Raghav, primary, Meer, Margarita, additional, Shadyab, Aladdin H., additional, Casanova, Ramon, additional, Manson, JoAnn E., additional, Bhatti, Parveen, additional, Crimmins, Eileen M., additional, Assimes, Themistocles L., additional, Whitsel, Eric A., additional, Higgins-Chen, Albert T., additional, and Levine, Morgan, additional

Published
2023
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31. PTFS07-06-23 Dietary Patterns and Epigenetic Aging in the Women's Health Initiative

Author

Reynolds, Lindsay, primary, Houston, Denise, additional, Skiba, Meghan, additional, Whitsel, Eric, additional, Stewart, James, additional, Li, Yun, additional, Zannas, Anthony, additional, Assimes, Themistocles, additional, Horvath, Steve, additional, Bhatti, Parveen, additional, Baccarelli, Andrea, additional, Tooze, Janet, additional, and Vitolins, Mara, additional

Published
2023
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32. Provincial variation in colorectal cancer screening adherence in Canada; evidence from the Canadian Partnership for Tomorrow’s Health

Author

Darvishian, Maryam, primary, Moustaqim-Barrette, Amina, additional, Awadalla, Philip, additional, Bhatti, Parveen, additional, Broet, Philippe, additional, McDonald, Kelly, additional, Murphy, Rachel A., additional, Skead, Kimberly, additional, Urquhart, Robin, additional, Vena, Jennifer, additional, and Dummer, Trevor J. B., additional

Published
2023
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34. Stressful life events, social support, and epigenetic aging in the Women's Health Initiative.

Author

Skinner, Harlyn G., Palma‐Gudiel, Helena, Stewart, James D., Love, Shelly‐Ann, Bhatti, Parveen, Shadyab, Aladdin H., Wallace, Robert B., Salmoirago‐Blotcher, Elena, Manson, JoAnn E., Kroenke, Candyce H., Belsky, Daniel W., Li, Yun, Whitsel, Eric A., and Zannas, Anthony S.

Subjects
LIFE change events, SOCIAL support, AGING, PSYCHOLOGICAL stress, EPIGENOMICS, WOMEN'S health
Abstract

Background: Elevated psychosocial stress has been linked with accelerated biological aging, including composite DNA methylation (DNAm) markers that predict aging‐related outcomes ("epigenetic age"). However, no study has examined whether stressful life events (SLEs) are associated with epigenetic age acceleration in postmenopausal women, an aging population characterized by increased stress burden and disease risk. Methods: We leveraged the Women's Health Initiative, a large muti‐ancestry cohort of postmenopausal women with available psychosocial stress measures over the past year and epigenomic data. SLEs and social support were ascertained via self‐report questionnaires. Whole blood DNAm array (450 K) data were used to calculate five DNAm‐based predictors of chronological age, health span and life span, and telomere length (HorvathAge, HannumAge, PhenoAge, GrimAge, DNAmTL). Results: After controlling for potential confounders, higher SLE burden was significantly associated with accelerated epigenetic aging, as measured by GrimAge (β: 0.34, 95% CI: 0.08, 0.59) and DNAmTL (β: −0.016, 95% CI: −0.028, −0.004). Exploratory analyses showed that SLEs‐GrimAge associations were stronger in Black women as compared to other races/ethnicities and in those with lower social support levels. In women with lower social support, SLEs‐DNAmTL associations showed opposite association in Hispanic women as compared to other race/ethnicity groups. Conclusions: Our findings suggest that elevated stress burden is associated with accelerated epigenetic aging in postmenopausal women. Lower social support and/or self‐reported race/ethnicity may modify the association of stress with epigenetic age acceleration. These findings advance understanding of how stress may contribute to aging‐related outcomes and have important implications for disease prevention and treatment in aging women. [ABSTRACT FROM AUTHOR]

Published
2024
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35. The Association of Epigenetic Age Acceleration and Multimorbidity at Age 90 in the Women's Health Initiative.

Author

Jain, Purva, Binder, Alexandra, Chen, Brian, Parada, Humberto, Gallo, Linda C, Alcaraz, John, Horvath, Steve, Bhatti, Parveen, Whitsel, Eric A, Jordahl, Kristina, Baccarelli, Andrea A, Hou, Lifang, Stewart, James D, Li, Yun, LaMonte, Michael J, Manson, JoAnn E, and LaCroix, Andrea Z

Subjects
COMORBIDITY, WOMEN'S health, OLDER women, POISSON regression, EPIGENETICS
Abstract

Background Epigenetic age acceleration (EAA), a measure of accelerated biological aging, has been associated with an increased risk of several age-related chronic conditions. This is the first study to prospectively examine the relationship between EAA and both multimorbidity count and a weighted multimorbidity score among long-lived postmenopausal women. Methods We included 1 951 women from the Women's Health Initiative who could have survived to age 90. EAA was estimated using the Horvath pan-tissue, Hannum, PhenoAge, and GrimAge "clocks." Twelve chronic conditions were included in the multimorbidity count. The multimorbidity score was weighted for each morbidity's relationship with mortality in the study population. Using mixed-effects Poisson and linear regression models that included baseline covariates associated with both EAA and multimorbidity, we estimated relative risks (RRs) and 95% confidence intervals (CIs) for the relationships between each EAA measure at the study baseline with both multimorbidity count and weighted multimorbidity score at age 90, respectively. Results For every one standard deviation increase in AgeAccelPheno, the rate of multimorbidity accumulation increased 6% (RR = 1.06; 95% CI = 1.01–1.12; p  = .025) and the multimorbidity score by 7% (RR = 1.07; 95% CI = 1.01–1.13; p  = .014) for women who survived to age 90. The results for a one standard deviation increase in AgeAccelHorvath, AgeAccelHannum, and AgeAccelGrim with multimorbidity accumulation and score were weaker compared to AgeAccelPheno, and the latter 2 did not reach statistical significance. Conclusion AgeAccelPheno and AgeAccelHannum may predict multimorbidity count and score at age 90 in older women and, thus, may be useful as a biomarker predictor of multimorbidity burden in the last decades of life. [ABSTRACT FROM AUTHOR]

Published
2023
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37. Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization

Author

Clavero, Esther, primary, Sanchez-Maldonado, José Manuel, additional, Macauda, Angelica, additional, Ter Horst, Rob, additional, Sampaio-Marques, Belém, additional, Jurczyszyn, Artur, additional, Clay-Gilmour, Alyssa, additional, Stein, Angelika, additional, Hildebrandt, Michelle A. T., additional, Weinhold, Niels, additional, Buda, Gabriele, additional, García-Sanz, Ramón, additional, Tomczak, Waldemar, additional, Vogel, Ulla, additional, Jerez, Andrés, additional, Zawirska, Daria, additional, Wątek, Marzena, additional, Hofmann, Jonathan N., additional, Landi, Stefano, additional, Spinelli, John J., additional, Butrym, Aleksandra, additional, Kumar, Abhishek, additional, Martínez-López, Joaquín, additional, Galimberti, Sara, additional, Sarasquete, María Eugenia, additional, Subocz, Edyta, additional, Iskierka-Jażdżewska, Elzbieta, additional, Giles, Graham G., additional, Rybicka-Ramos, Malwina, additional, Kruszewski, Marcin, additional, Abildgaard, Niels, additional, Verdejo, Francisco García, additional, Sánchez Rovira, Pedro, additional, da Silva Filho, Miguel Inacio, additional, Kadar, Katalin, additional, Razny, Małgorzata, additional, Cozen, Wendy, additional, Pelosini, Matteo, additional, Jurado, Manuel, additional, Bhatti, Parveen, additional, Dudzinski, Marek, additional, Druzd-Sitek, Agnieszka, additional, Orciuolo, Enrico, additional, Li, Yang, additional, Norman, Aaron D., additional, Zaucha, Jan Maciej, additional, Reis, Rui Manuel, additional, Markiewicz, Miroslaw, additional, Rodríguez Sevilla, Juan José, additional, Andersen, Vibeke, additional, Jamroziak, Krzysztof, additional, Hemminki, Kari, additional, Berndt, Sonja I., additional, Rajkumar, Vicent, additional, Mazur, Grzegorz, additional, Kumar, Shaji K., additional, Ludovico, Paula, additional, Nagler, Arnon, additional, Chanock, Stephen J., additional, Dumontet, Charles, additional, Machiela, Mitchell J., additional, Varkonyi, Judit, additional, Camp, Nicola J., additional, Ziv, Elad, additional, Vangsted, Annette Juul, additional, Brown, Elizabeth E., additional, Campa, Daniele, additional, Vachon, Celine M., additional, Netea, Mihai G., additional, Canzian, Federico, additional, Försti, Asta, additional, and Sainz, Juan, additional

Published
2023
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38. Data from Chemotherapy and Thyroid Cancer Risk: A Report from the Childhood Cancer Survivor Study

Author

Veiga, Lene H.S., primary, Bhatti, Parveen, primary, Ronckers, Cécile M., primary, Sigurdson, Alice J., primary, Stovall, Marilyn, primary, Smith, Susan A., primary, Weathers, Rita, primary, Leisenring, Wendy, primary, Mertens, Ann C., primary, Hammond, Sue, primary, Neglia, Joseph P., primary, Meadows, Anna T., primary, Donaldson, Sarah S., primary, Sklar, Charles A., primary, Friedman, Debra L., primary, Robison, Leslie L., primary, and Inskip, Peter D., primary

Published
2023
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39. Supplementary data from Young Adult and Usual Adult Body Mass Index and Multiple Myeloma Risk: A Pooled Analysis in the International Multiple Myeloma Consortium (IMMC)

Author

Birmann, Brenda M., primary, Andreotti, Gabriella, primary, De Roos, Anneclaire J., primary, Camp, Nicola J., primary, Chiu, Brian C.H., primary, Spinelli, John J., primary, Becker, Nikolaus, primary, Benhaim-Luzon, Véronique, primary, Bhatti, Parveen, primary, Boffetta, Paolo, primary, Brennan, Paul, primary, Brown, Elizabeth E., primary, Cocco, Pierluigi, primary, Costas, Laura, primary, Cozen, Wendy, primary, de Sanjosé, Silvia, primary, Foretová, Lenka, primary, Giles, Graham G., primary, Maynadié, Marc, primary, Moysich, Kirsten, primary, Nieters, Alexandra, primary, Staines, Anthony, primary, Tricot, Guido, primary, Weisenburger, Dennis, primary, Zhang, Yawei, primary, Baris, Dalsu, primary, and Purdue, Mark P., primary

Published
2023
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40. Supplementary Tables 1-2 from Chemotherapy and Thyroid Cancer Risk: A Report from the Childhood Cancer Survivor Study

Author

Veiga, Lene H.S., primary, Bhatti, Parveen, primary, Ronckers, Cécile M., primary, Sigurdson, Alice J., primary, Stovall, Marilyn, primary, Smith, Susan A., primary, Weathers, Rita, primary, Leisenring, Wendy, primary, Mertens, Ann C., primary, Hammond, Sue, primary, Neglia, Joseph P., primary, Meadows, Anna T., primary, Donaldson, Sarah S., primary, Sklar, Charles A., primary, Friedman, Debra L., primary, Robison, Leslie L., primary, and Inskip, Peter D., primary

Published
2023
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41. Correction: Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes

Author

IRAS OH Epidemiology Chemical Agents, IRAS – One Health Chemical, Berndt, Sonja I, Vijai, Joseph, Benavente, Yolanda, Camp, Nicola J, Nieters, Alexandra, Wang, Zhaoming, Smedby, Karin E, Kleinstern, Geffen, Hjalgrim, Henrik, Besson, Caroline, Skibola, Christine F, Morton, Lindsay M, Brooks-Wilson, Angela R, Teras, Lauren R, Breeze, Charles, Arias, Joshua, Adami, Hans-Olov, Albanes, Demetrius, Anderson, Kenneth C, Ansell, Stephen M, Bassig, Bryan, Becker, Nikolaus, Bhatti, Parveen, Birmann, Brenda M, Boffetta, Paolo, Bracci, Paige M, Brennan, Paul, Brown, Elizabeth E, Burdett, Laurie, Cannon-Albright, Lisa A, Chang, Ellen T, Chiu, Brian C H, Chung, Charles C, Clavel, Jacqueline, Cocco, Pierluigi, Colditz, Graham, Conde, Lucia, Conti, David V, Cox, David G, Curtin, Karen, Casabonne, Delphine, De Vivo, Immaculata, Diepstra, Arjan, Diver, W Ryan, Dogan, Ahmet, Edlund, Christopher K, Foretova, Lenka, Fraumeni, Joseph F, Gabbas, Attilio, Ghesquières, Hervé, Giles, Graham G, Glaser, Sally, Glenn, Martha, Glimelius, Bengt, Gu, Jian, Habermann, Thomas M, Haiman, Christopher A, Haioun, Corinne, Hofmann, Jonathan N, Holford, Theodore R, Holly, Elizabeth A, Hutchinson, Amy, Izhar, Aalin, Jackson, Rebecca D, Jarrett, Ruth F, Kaaks, Rudolph, Kane, Eleanor, Kolonel, Laurence N, Kong, Yinfei, Kraft, Peter, Kricker, Anne, Lake, Annette, Lan, Qing, Lawrence, Charles, Li, Dalin, Liebow, Mark, Link, Brian K, Magnani, Corrado, Maynadie, Marc, McKay, James, Melbye, Mads, Miligi, Lucia, Milne, Roger L, Molina, Thierry J, Monnereau, Alain, Montalvan, Rebecca, North, Kari E, Novak, Anne J, Onel, Kenan, Purdue, Mark P, Rand, Kristin A, Riboli, Elio, Riby, Jacques, Roman, Eve, Salles, Gilles, Sborov, Douglas W, Severson, Richard K, Shanafelt, Tait D, Smith, Martyn T, Smith, Alexandra, Song, Kevin W, Song, Lei, Southey, Melissa C, Spinelli, John J, Staines, Anthony, Stephens, Deborah, Sutherland, Heather J, Tkachuk, Kaitlyn, Thompson, Carrie A, Tilly, Hervé, Tinker, Lesley F, Travis, Ruth C, Turner, Jenny, Vachon, Celine M, Vajdic, Claire M, Van Den Berg, Anke, Van Den Berg, David J, Vermeulen, Roel C H, Vineis, Paolo, Wang, Sophia S, Weiderpass, Elisabete, Weiner, George J, Weinstein, Stephanie, Doo, Nicole Wong, Ye, Yuanqing, Yeager, Meredith, Yu, Kai, Zeleniuch-Jacquotte, Anne, Zhang, Yawei, Zheng, Tongzhang, Ziv, Elad, Sampson, Joshua, Chatterjee, Nilanjan, Offit, Kenneth, Cozen, Wendy, Wu, Xifeng, Cerhan, James R, Chanock, Stephen J, Slager, Susan L, Rothman, Nathaniel, IRAS OH Epidemiology Chemical Agents, IRAS – One Health Chemical, Berndt, Sonja I, Vijai, Joseph, Benavente, Yolanda, Camp, Nicola J, Nieters, Alexandra, Wang, Zhaoming, Smedby, Karin E, Kleinstern, Geffen, Hjalgrim, Henrik, Besson, Caroline, Skibola, Christine F, Morton, Lindsay M, Brooks-Wilson, Angela R, Teras, Lauren R, Breeze, Charles, Arias, Joshua, Adami, Hans-Olov, Albanes, Demetrius, Anderson, Kenneth C, Ansell, Stephen M, Bassig, Bryan, Becker, Nikolaus, Bhatti, Parveen, Birmann, Brenda M, Boffetta, Paolo, Bracci, Paige M, Brennan, Paul, Brown, Elizabeth E, Burdett, Laurie, Cannon-Albright, Lisa A, Chang, Ellen T, Chiu, Brian C H, Chung, Charles C, Clavel, Jacqueline, Cocco, Pierluigi, Colditz, Graham, Conde, Lucia, Conti, David V, Cox, David G, Curtin, Karen, Casabonne, Delphine, De Vivo, Immaculata, Diepstra, Arjan, Diver, W Ryan, Dogan, Ahmet, Edlund, Christopher K, Foretova, Lenka, Fraumeni, Joseph F, Gabbas, Attilio, Ghesquières, Hervé, Giles, Graham G, Glaser, Sally, Glenn, Martha, Glimelius, Bengt, Gu, Jian, Habermann, Thomas M, Haiman, Christopher A, Haioun, Corinne, Hofmann, Jonathan N, Holford, Theodore R, Holly, Elizabeth A, Hutchinson, Amy, Izhar, Aalin, Jackson, Rebecca D, Jarrett, Ruth F, Kaaks, Rudolph, Kane, Eleanor, Kolonel, Laurence N, Kong, Yinfei, Kraft, Peter, Kricker, Anne, Lake, Annette, Lan, Qing, Lawrence, Charles, Li, Dalin, Liebow, Mark, Link, Brian K, Magnani, Corrado, Maynadie, Marc, McKay, James, Melbye, Mads, Miligi, Lucia, Milne, Roger L, Molina, Thierry J, Monnereau, Alain, Montalvan, Rebecca, North, Kari E, Novak, Anne J, Onel, Kenan, Purdue, Mark P, Rand, Kristin A, Riboli, Elio, Riby, Jacques, Roman, Eve, Salles, Gilles, Sborov, Douglas W, Severson, Richard K, Shanafelt, Tait D, Smith, Martyn T, Smith, Alexandra, Song, Kevin W, Song, Lei, Southey, Melissa C, Spinelli, John J, Staines, Anthony, Stephens, Deborah, Sutherland, Heather J, Tkachuk, Kaitlyn, Thompson, Carrie A, Tilly, Hervé, Tinker, Lesley F, Travis, Ruth C, Turner, Jenny, Vachon, Celine M, Vajdic, Claire M, Van Den Berg, Anke, Van Den Berg, David J, Vermeulen, Roel C H, Vineis, Paolo, Wang, Sophia S, Weiderpass, Elisabete, Weiner, George J, Weinstein, Stephanie, Doo, Nicole Wong, Ye, Yuanqing, Yeager, Meredith, Yu, Kai, Zeleniuch-Jacquotte, Anne, Zhang, Yawei, Zheng, Tongzhang, Ziv, Elad, Sampson, Joshua, Chatterjee, Nilanjan, Offit, Kenneth, Cozen, Wendy, Wu, Xifeng, Cerhan, James R, Chanock, Stephen J, Slager, Susan L, and Rothman, Nathaniel

Published
2023

42. Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma:A Meta-Analysis of Three Large Cohorts and Functional Characterization

Author

Clavero, Esther, Sanchez-Maldonado, José Manuel, Macauda, Angelica, Ter Horst, Rob, Sampaio-Marques, Belém, Jurczyszyn, Artur, Clay-Gilmour, Alyssa, Stein, Angelika, Hildebrandt, Michelle A.T., Weinhold, Niels, Buda, Gabriele, García-Sanz, Ramón, Tomczak, Waldemar, Vogel, Ulla, Jerez, Andrés, Zawirska, Daria, Wątek, Marzena, Hofmann, Jonathan N., Landi, Stefano, Spinelli, John J., Butrym, Aleksandra, Kumar, Abhishek, Martínez-López, Joaquín, Galimberti, Sara, Sarasquete, María Eugenia, Subocz, Edyta, Iskierka-Jażdżewska, Elzbieta, Giles, Graham G., Rybicka-Ramos, Malwina, Kruszewski, Marcin, Abildgaard, Niels, Verdejo, Francisco García, Sánchez Rovira, Pedro, da Silva Filho, Miguel Inacio, Kadar, Katalin, Razny, Małgorzata, Cozen, Wendy, Pelosini, Matteo, Jurado, Manuel, Bhatti, Parveen, Dudzinski, Marek, Druzd-Sitek, Agnieszka, Orciuolo, Enrico, Li, Yang, Norman, Aaron D., Zaucha, Jan Maciej, Reis, Rui Manuel, Markiewicz, Miroslaw, Rodríguez Sevilla, Juan José, Andersen, Vibeke, Jamroziak, Krzysztof, Hemminki, Kari, Berndt, Sonja I., Rajkumar, Vicent, Mazur, Grzegorz, Kumar, Shaji K., Ludovico, Paula, Nagler, Arnon, Chanock, Stephen J., Dumontet, Charles, Machiela, Mitchell J., Varkonyi, Judit, Camp, Nicola J., Ziv, Elad, Vangsted, Annette Juul, Brown, Elizabeth E., Campa, Daniele, Vachon, Celine M., Netea, Mihai G., Canzian, Federico, Försti, Asta, Sainz, Juan, Clavero, Esther, Sanchez-Maldonado, José Manuel, Macauda, Angelica, Ter Horst, Rob, Sampaio-Marques, Belém, Jurczyszyn, Artur, Clay-Gilmour, Alyssa, Stein, Angelika, Hildebrandt, Michelle A.T., Weinhold, Niels, Buda, Gabriele, García-Sanz, Ramón, Tomczak, Waldemar, Vogel, Ulla, Jerez, Andrés, Zawirska, Daria, Wątek, Marzena, Hofmann, Jonathan N., Landi, Stefano, Spinelli, John J., Butrym, Aleksandra, Kumar, Abhishek, Martínez-López, Joaquín, Galimberti, Sara, Sarasquete, María Eugenia, Subocz, Edyta, Iskierka-Jażdżewska, Elzbieta, Giles, Graham G., Rybicka-Ramos, Malwina, Kruszewski, Marcin, Abildgaard, Niels, Verdejo, Francisco García, Sánchez Rovira, Pedro, da Silva Filho, Miguel Inacio, Kadar, Katalin, Razny, Małgorzata, Cozen, Wendy, Pelosini, Matteo, Jurado, Manuel, Bhatti, Parveen, Dudzinski, Marek, Druzd-Sitek, Agnieszka, Orciuolo, Enrico, Li, Yang, Norman, Aaron D., Zaucha, Jan Maciej, Reis, Rui Manuel, Markiewicz, Miroslaw, Rodríguez Sevilla, Juan José, Andersen, Vibeke, Jamroziak, Krzysztof, Hemminki, Kari, Berndt, Sonja I., Rajkumar, Vicent, Mazur, Grzegorz, Kumar, Shaji K., Ludovico, Paula, Nagler, Arnon, Chanock, Stephen J., Dumontet, Charles, Machiela, Mitchell J., Varkonyi, Judit, Camp, Nicola J., Ziv, Elad, Vangsted, Annette Juul, Brown, Elizabeth E., Campa, Daniele, Vachon, Celine M., Netea, Mihai G., Canzian, Federico, Försti, Asta, and Sainz, Juan

Abstract

Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10−9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10−4−5.79 × 10−14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10−4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10−4) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 SNP correlated with numbers of CD19+ B cells, CD19+CD3− B cells, CD5+IgD− cells, IgM− cells, IgD−IgM− cells, and CD4−CD8− PBMCs (p = 4.9 × 10−4−8.6 × 10−4)

Published
2023

43. A pleiotropic variant in DNAJB4 is associated with multiple myeloma risk

Author

Dicanio, Marco, Giaccherini, Matteo, Clay-Gilmour, Alyssa, Macauda, Angelica, Sainz, Juan, Machiela, Mitchell J., Rybicka-Ramos, Malwina, Norman, Aaron D., Tyczyńska, Agata, Chanock, Stephen J., Barington, Torben, Kumar, Shaji K., Bhatti, Parveen, Cozen, Wendy, Brown, Elizabeth E., Suska, Anna, Haastrup, Eva K., Orlowski, Robert Z., Dudziński, Marek, Garcia-Sanz, Ramon, Kruszewski, Marcin, Martinez-Lopez, Joaquin, Beider, Katia, Iskierka-Jazdzewska, Elżbieta, Pelosini, Matteo, Berndt, Sonja I., Raźny, Małgorzata, Jamroziak, Krzysztof, Rajkumar, S. Vincent, Jurczyszyn, Artur, Vangsted, Annette Juul, Collado, Pilar Garrido, Vogel, Ulla, Hofmann, Jonathan N., Petrini, Mario, Butrym, Aleksandra, Slager, Susan L., Ziv, Elad, Subocz, Edyta, Giles, Graham G., Andersen, Niels Frost, Mazur, Grzegorz, Watek, Marzena, Lesueur, Fabienne, Hildebrandt, Michelle A.T., Zawirska, Daria, Ebbesen, Lene Hyldahl, Marques, Herlander, Gemignani, Federica, Dumontet, Charles, Várkonyi, Judit, Buda, Gabriele, Nagler, Arnon, Druzd-Sitek, Agnieszka, Wu, Xifeng, Kadar, Katalin, Camp, Nicola J., Grzasko, Norbert, Waller, Rosalie G., Vachon, Celine, Canzian, Federico, Campa, Daniele, Dicanio, Marco, Giaccherini, Matteo, Clay-Gilmour, Alyssa, Macauda, Angelica, Sainz, Juan, Machiela, Mitchell J., Rybicka-Ramos, Malwina, Norman, Aaron D., Tyczyńska, Agata, Chanock, Stephen J., Barington, Torben, Kumar, Shaji K., Bhatti, Parveen, Cozen, Wendy, Brown, Elizabeth E., Suska, Anna, Haastrup, Eva K., Orlowski, Robert Z., Dudziński, Marek, Garcia-Sanz, Ramon, Kruszewski, Marcin, Martinez-Lopez, Joaquin, Beider, Katia, Iskierka-Jazdzewska, Elżbieta, Pelosini, Matteo, Berndt, Sonja I., Raźny, Małgorzata, Jamroziak, Krzysztof, Rajkumar, S. Vincent, Jurczyszyn, Artur, Vangsted, Annette Juul, Collado, Pilar Garrido, Vogel, Ulla, Hofmann, Jonathan N., Petrini, Mario, Butrym, Aleksandra, Slager, Susan L., Ziv, Elad, Subocz, Edyta, Giles, Graham G., Andersen, Niels Frost, Mazur, Grzegorz, Watek, Marzena, Lesueur, Fabienne, Hildebrandt, Michelle A.T., Zawirska, Daria, Ebbesen, Lene Hyldahl, Marques, Herlander, Gemignani, Federica, Dumontet, Charles, Várkonyi, Judit, Buda, Gabriele, Nagler, Arnon, Druzd-Sitek, Agnieszka, Wu, Xifeng, Kadar, Katalin, Camp, Nicola J., Grzasko, Norbert, Waller, Rosalie G., Vachon, Celine, Canzian, Federico, and Campa, Daniele

Abstract

Pleiotropy, which consists of a single gene or allelic variant affecting multiple unrelated traits, is common across cancers, with evidence for genome-wide significant loci shared across cancer and noncancer traits. This feature is particularly relevant in multiple myeloma (MM) because several susceptibility loci that have been identified to date are pleiotropic. Therefore, the aim of this study was to identify novel pleiotropic variants involved in MM risk using 28 684 independent single nucleotide polymorphisms (SNPs) from GWAS Catalog that reached a significant association (P < 5 × 10−8) with their respective trait. The selected SNPs were analyzed in 2434 MM cases and 3446 controls from the International Lymphoma Epidemiology Consortium (InterLymph). The 10 SNPs showing the strongest associations with MM risk in InterLymph were selected for replication in an independent set of 1955 MM cases and 1549 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and 418 MM cases and 147 282 controls from the FinnGen project. The combined analysis of the three studies identified an association between DNAJB4-rs34517439-A and an increased risk of developing MM (OR = 1.22, 95%CI 1.13-1.32, P = 4.81 × 10−7). rs34517439-A is associated with a modified expression of the FUBP1 gene, which encodes a multifunctional DNA and RNA-binding protein that it was observed to influence the regulation of various genes involved in cell cycle regulation, among which various oncogenes and oncosuppressors. In conclusion, with a pleiotropic scan approach we identified DNAJB4-rs34517439 as a potentially novel MM risk locus.

Published
2023

44. Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization

Author

European Commission, Instituto de Salud Carlos III, Fundación CRIS contra el Cáncer, Dietmar Hopp Foundation, Federal Ministry of Education and Research (Germany), Fundação para a Ciência e a Tecnologia (Portugal), Clavero, Esther, Sanchez-Maldonado, José Manuel, Macauda, Angélica, Ter Horst, Rob, Sampaio-Marques, Belém, Jurczyszyn, Artur, Clay-Gilmour, Alyssa, Stein, Angelika, Hildebrandt, Michelle A. T., Weinhold, Niels, Buda, Gabriele, García-Sanz, Ramón, Tomczak, Waldemar, Vogel, Ulla, Jerez, Andrés, Zawirska, Daria, Wątek, Marzena, Hofmann, Jonathan N., Landi, Stefano, Spinelli, John J., Butrym, Aleksandra, Kumar, Abhishek, Martínez-López, Joaquín, Galimberti, Sara, Sarasquete, María Eugenia, Subocz, Edyta, Iskierka-Jażdżewska, Elzbieta, Giles, Graham G., Rybicka-Ramos, Malwina, Kruszewski, Marcin, Abildgaard, Niels, Verdejo, Francisco García, Sánchez Rovira, Pedro, da Silva Filho, Miguel Inacio, Kadar, Katalin, Razny, Małgorzata, Cozen, Wendy, Pelosini, Matteo, Jurado, Manuel, Bhatti, Parveen, Dudzinski, Marek, Druzd-Sitek, Agnieszka, Orciuolo, Enrico, Li, Yang, Norman, Aaron D, Zaucha, Jan Maciej, Reis, Rui Manuel, Markiewicz, Miroslaw, Rodríguez Sevilla, Juan José, Andersen, Vibeke, Jamroziak, Krzysztof, Hemminki, Kari, Berndt, Sonja I., Rajkumar, Vicent, Mazur, Grzegorz, Kumar, Shaji K., Ludovico, Paula, Nagler, Arnon, Chanock, Stephen J., Dumontet, Charles, Machiela, Mitchell J., Varkonyi, Judit, Camp, Nicola J., Ziv, Elad, Vangsted, Annette Juul, Brown, Elizabeth E., Campa, Daniele, Vachon, Celine M., Netea, Mihai G., Canzian, Federico, Försti, Asta, Sainz, Juan, European Commission, Instituto de Salud Carlos III, Fundación CRIS contra el Cáncer, Dietmar Hopp Foundation, Federal Ministry of Education and Research (Germany), Fundação para a Ciência e a Tecnologia (Portugal), Clavero, Esther, Sanchez-Maldonado, José Manuel, Macauda, Angélica, Ter Horst, Rob, Sampaio-Marques, Belém, Jurczyszyn, Artur, Clay-Gilmour, Alyssa, Stein, Angelika, Hildebrandt, Michelle A. T., Weinhold, Niels, Buda, Gabriele, García-Sanz, Ramón, Tomczak, Waldemar, Vogel, Ulla, Jerez, Andrés, Zawirska, Daria, Wątek, Marzena, Hofmann, Jonathan N., Landi, Stefano, Spinelli, John J., Butrym, Aleksandra, Kumar, Abhishek, Martínez-López, Joaquín, Galimberti, Sara, Sarasquete, María Eugenia, Subocz, Edyta, Iskierka-Jażdżewska, Elzbieta, Giles, Graham G., Rybicka-Ramos, Malwina, Kruszewski, Marcin, Abildgaard, Niels, Verdejo, Francisco García, Sánchez Rovira, Pedro, da Silva Filho, Miguel Inacio, Kadar, Katalin, Razny, Małgorzata, Cozen, Wendy, Pelosini, Matteo, Jurado, Manuel, Bhatti, Parveen, Dudzinski, Marek, Druzd-Sitek, Agnieszka, Orciuolo, Enrico, Li, Yang, Norman, Aaron D, Zaucha, Jan Maciej, Reis, Rui Manuel, Markiewicz, Miroslaw, Rodríguez Sevilla, Juan José, Andersen, Vibeke, Jamroziak, Krzysztof, Hemminki, Kari, Berndt, Sonja I., Rajkumar, Vicent, Mazur, Grzegorz, Kumar, Shaji K., Ludovico, Paula, Nagler, Arnon, Chanock, Stephen J., Dumontet, Charles, Machiela, Mitchell J., Varkonyi, Judit, Camp, Nicola J., Ziv, Elad, Vangsted, Annette Juul, Brown, Elizabeth E., Campa, Daniele, Vachon, Celine M., Netea, Mihai G., Canzian, Federico, Försti, Asta, and Sainz, Juan

Abstract

Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10−9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10−4−5.79 × 10−14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10−4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10−4) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 SNP correlated with numbers of CD19+ B cells, CD19+CD3− B cells, CD5+IgD− cells, IgM− cells, IgD−IgM− cells, and CD4−CD8− PBMCs (p = 4.9 × 10−4−8.6 × 10−4) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+EMCD45RO+CD27− cells (p = 9.3 × 10−4). These results suggest that genetic variants within these six loci influ

Published
2023

45. Identification of novel genetic loci for risk of multiple myeloma by functional annotation

Author

European Commission, National Cancer Institute (US), National Institutes of Health (US), Projekt DEAL, Macauda, Angelica, Briem, Klara, Clay-Gilmour, Alyssa, Cozen, Wendy, Försti, Asta, Giaccherini, Matteo, Corradi, Chiara, Sainz, Juan, Niazi, Yasmeen, Ter Horst, Rob, Li, Yang, Netea, Mihai G., Vogel, Ulla, Hemminki, Kari, Slager, Susan L., Varkonyi, Judit, Andersen, Vibeke, Iskierka-Jazdzewska, Elżbieta, Martínez-López, Joaquín, Zaucha, Jan, Camp, Nicola J., Rajkumar, S. Vincent, Druzd-Sitek, Agnieszka, Bhatti, Parveen, Chanock, Stephen J., Kumar, Shaji K., Subocz, Edyta, Mazur, Grzegorz, Landi, Stefano, Machiela, Mitchell J., Jerez, Andrés, Norman, Aaron D., Hildebrandt, Michelle A. T., Kadar, Katalin, Berndt, Sonja I., Ziv, Elad, Buda, Gabriele, Nagler, Arnon, Dumontet, Charles, Raźny, Malgorzata, Watek, Marzena, Butrym, Aleksandra, Grzasko, Norbert, Dudzinski, Marek, Rybicka-Ramos, Malwina, Matera, Eva-Laure, García-Sanz, Ramón, Goldschmidt, Hartmut, Jamroziak, Krzysztof, Jurczyszyn, Artur, Clavero, Esther, Giles, Graham G., Pelosini, Matteo, Zawirska, Daria, Kruszewski, Marcin, Marques, Herlander, Haastrup, Eva, Sánchez Maldonado, José Manuel, Bertsch, Uta, Rymko, Marcin, Raab, Marc-Steffen, Brown, Elizabeth E., Hofmann, Jonathan N., Vachon, Celine, Campa, Daniele, Canzian, Federico, European Commission, National Cancer Institute (US), National Institutes of Health (US), Projekt DEAL, Macauda, Angelica, Briem, Klara, Clay-Gilmour, Alyssa, Cozen, Wendy, Försti, Asta, Giaccherini, Matteo, Corradi, Chiara, Sainz, Juan, Niazi, Yasmeen, Ter Horst, Rob, Li, Yang, Netea, Mihai G., Vogel, Ulla, Hemminki, Kari, Slager, Susan L., Varkonyi, Judit, Andersen, Vibeke, Iskierka-Jazdzewska, Elżbieta, Martínez-López, Joaquín, Zaucha, Jan, Camp, Nicola J., Rajkumar, S. Vincent, Druzd-Sitek, Agnieszka, Bhatti, Parveen, Chanock, Stephen J., Kumar, Shaji K., Subocz, Edyta, Mazur, Grzegorz, Landi, Stefano, Machiela, Mitchell J., Jerez, Andrés, Norman, Aaron D., Hildebrandt, Michelle A. T., Kadar, Katalin, Berndt, Sonja I., Ziv, Elad, Buda, Gabriele, Nagler, Arnon, Dumontet, Charles, Raźny, Malgorzata, Watek, Marzena, Butrym, Aleksandra, Grzasko, Norbert, Dudzinski, Marek, Rybicka-Ramos, Malwina, Matera, Eva-Laure, García-Sanz, Ramón, Goldschmidt, Hartmut, Jamroziak, Krzysztof, Jurczyszyn, Artur, Clavero, Esther, Giles, Graham G., Pelosini, Matteo, Zawirska, Daria, Kruszewski, Marcin, Marques, Herlander, Haastrup, Eva, Sánchez Maldonado, José Manuel, Bertsch, Uta, Rymko, Marcin, Raab, Marc-Steffen, Brown, Elizabeth E., Hofmann, Jonathan N., Vachon, Celine, Campa, Daniele, and Canzian, Federico

Abstract

Multiple myeloma (MM) is one of the most common hematological malignancies, accounting for 20% of all newly diagnosed hematological cancers [1]. The most recent data from Cancer Today show that in 2020 the number of new MM cases was 176,404 worldwide

Published
2023

46. A pleiotropic variant in DNAJB4 is associated with multiple myeloma risk

Author

Università di Pisa, German Cancer Research Center, Dicanio, Marco, Giaccherini, Matteo, Clay-Gilmour, Alyssa, Macauda, Angelica, Sainz, Juan, Machiela, Mitchell J., Rybicka-Ramos, Malwina, Norman, Aaron D., Tyczyńska, Agata, Chanock, Stephen J., Barington, Torben, Kumar, Shaji K., Bhatti, Parveen, Cozen, Wendy, Brown, Elizabeth E., Suska, Anna, Haastrup, Eva K., Orlowski, R. Z., Dudziński, Marek, García-Sanz, Ramón, Kruszewski, Marcin, Martínez-López, Joaquín, Beider, Katia, Iskierka-Jazdzewska, Elżbieta, Pelosini, Matteo, Berndt, Sonja, Raźny, Małgorzata, Jamroziak, Krzysztof, Rajkumar, S. Vincent, Jurczyszyn, Artur, Vangsted, Annette Juul, Garrido, Pilar, Vogel, Ulla, Hofmann, Jonathan N., Petrini, Mario, Butrym, Aleksandra, Slager, Susan L., Ziv, Elad, Subocz, Edyta, Giles, Graham G., Frost Andersen, Niels, Mazur, Grzegorz, Watek, Marzena, Lesueur, Fabienne, Hildebrandt, Michelle A. T., Zawirska, Daria, Hyldahl Ebbesen, Lene, Marques, Herlander, Gemignani, Federica, Dumontet, Charles, Várkonyi, Judit, Buda, Gabriele, Nagler, Arnon, Druzd-Sitek, Agnieszka, Wu, Xifeng, Kadar, Katalin, Camp, Nicola J., Grzasko, Norbert, Waller, Rosalie G., Vachon, Celine, Canzian, Federico, Campa, Daniele, Università di Pisa, German Cancer Research Center, Dicanio, Marco, Giaccherini, Matteo, Clay-Gilmour, Alyssa, Macauda, Angelica, Sainz, Juan, Machiela, Mitchell J., Rybicka-Ramos, Malwina, Norman, Aaron D., Tyczyńska, Agata, Chanock, Stephen J., Barington, Torben, Kumar, Shaji K., Bhatti, Parveen, Cozen, Wendy, Brown, Elizabeth E., Suska, Anna, Haastrup, Eva K., Orlowski, R. Z., Dudziński, Marek, García-Sanz, Ramón, Kruszewski, Marcin, Martínez-López, Joaquín, Beider, Katia, Iskierka-Jazdzewska, Elżbieta, Pelosini, Matteo, Berndt, Sonja, Raźny, Małgorzata, Jamroziak, Krzysztof, Rajkumar, S. Vincent, Jurczyszyn, Artur, Vangsted, Annette Juul, Garrido, Pilar, Vogel, Ulla, Hofmann, Jonathan N., Petrini, Mario, Butrym, Aleksandra, Slager, Susan L., Ziv, Elad, Subocz, Edyta, Giles, Graham G., Frost Andersen, Niels, Mazur, Grzegorz, Watek, Marzena, Lesueur, Fabienne, Hildebrandt, Michelle A. T., Zawirska, Daria, Hyldahl Ebbesen, Lene, Marques, Herlander, Gemignani, Federica, Dumontet, Charles, Várkonyi, Judit, Buda, Gabriele, Nagler, Arnon, Druzd-Sitek, Agnieszka, Wu, Xifeng, Kadar, Katalin, Camp, Nicola J., Grzasko, Norbert, Waller, Rosalie G., Vachon, Celine, Canzian, Federico, and Campa, Daniele

Abstract

Pleiotropy, which consists of a single gene or allelic variant affecting multiple unrelated traits, is common across cancers, with evidence for genome-wide significant loci shared across cancer and noncancer traits. This feature is particularly relevant in multiple myeloma (MM) because several susceptibility loci that have been identified to date are pleiotropic. Therefore, the aim of this study was to identify novel pleiotropic variants involved in MM risk using 28 684 independent single nucleotide polymorphisms (SNPs) from GWAS Catalog that reached a significant association (P < 5 × 10−8) with their respective trait. The selected SNPs were analyzed in 2434 MM cases and 3446 controls from the International Lymphoma Epidemiology Consortium (InterLymph). The 10 SNPs showing the strongest associations with MM risk in InterLymph were selected for replication in an independent set of 1955 MM cases and 1549 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and 418 MM cases and 147 282 controls from the FinnGen project. The combined analysis of the three studies identified an association between DNAJB4-rs34517439-A and an increased risk of developing MM (OR = 1.22, 95%CI 1.13-1.32, P = 4.81 × 10−7). rs34517439-A is associated with a modified expression of the FUBP1 gene, which encodes a multifunctional DNA and RNA-binding protein that it was observed to influence the regulation of various genes involved in cell cycle regulation, among which various oncogenes and oncosuppressors. In conclusion, with a pleiotropic scan approach we identified DNAJB4-rs34517439 as a potentially novel MM risk locus.

Published
2023

47. Radiation-Related New Primary Solid Cancers in the Childhood Cancer Survivor Study: Comparative Radiation Dose Response and Modification of Treatment Effects

Author

Inskip, Peter D., Sigurdson, Alice J., Veiga, Lene, Bhatti, Parveen, Ronckers, Cécile, Rajaraman, Preetha, Boukheris, Houda, Stovall, Marilyn, Smith, Susan, Hammond, Sue, Henderson, Tara O., Watt, Tanya C., Mertens, Ann C., Leisenring, Wendy, Stratton, Kayla, Whitton, John, Donaldson, Sarah S., Armstrong, Gregory T., Robison, Leslie L., and Neglia, Joseph P.

Published
2016
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