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1. Optical bounds on many-electron localization

Author

Souza, Ivo, Martin, Richard M., and Stengel, Massimiliano

Subjects
Condensed Matter - Materials Science
Abstract

We establish rigorous inequalities between different electronic properties linked to optical sum rules, and organize them into weak and strong bounds on three characteristic properties of insulators: electron localization length $\ell$ (the quantum fluctuations in polarization), electric susceptibility $\chi$, and optical gap $E_{\rm G}$. All-electron and valence-only versions of the bounds are given, and the latter are found to be more informative. The bounds on $\ell$ are particularly interesting, as they provide reasonably tight estimates for an ellusive ground-state property -- the average localization length of valence electrons -- from tabulated experimental data: electron density, high-frequency dielectric constant, and optical gap. The localization lengths estimated in this way for several materials follow simple chemical trends, especially for the alkali halides. We also illustrate our findings via analytically solvable harmonic oscillator models, which reveal an intriguing connection to the physics of long-ranged van der Waals forces.

Published
2024

2. Spin-resolved electronic structure of ferromagnetic triple-layered ruthenate Sr$_4$Ru$_3$O$_{10}$

Author

Ngabonziza, Prosper, Denlinger, Jonathan D., Fedorov, Alexei V., Cao, Gang, Allen, J. W., Gebreyesus, G., and Martin, Richard M.

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Other Condensed Matter
Abstract

High-resolution angle- and spin-resolved photoemission spectroscopy reveals new features of the electronic structure of the ferromagnetic triple-layered ruthenate Sr$_4$Ru$_3$O$_{10}$. There are narrow spectral peaks $\sim$30 meV below the Fermi-level in two regions of the Brillouin zone: a hole-like band at the zone-center and a saddle-point van Hove singularity at the zone edge. Below T$_c$ each feature is almost completely spin-polarized, with opposite sign polarization and with strong Kondo-coherence-like temperature-dependent spectral weight variation suggestive of strong Hund's metal correlations. In addition, there are distinct Fermi surfaces for wide electron-like minority spin bands around the zone center and narrow hole-like majority spin Fermi surface contours around the zone corners. The origin of these features is in general agreement with density functional calculations, if they are shifted to reduce the exchange splitting, and scaled to take into account effects of correlation. Furthermore, the deduced narrow band origins from the tri-layer splitting of $d_{xz/yz}$ orbitals implies a layer-specific spin-polarization contribution from the narrow bands. Over a larger energy range, net spin-majority polarization of incoherent Ru $d$-bands is observed to extend down to the top of the oxygen bands, where additional narrow oxygen bands contribute to the magnetism with spin-minority polarization., Comment: 11 pages, 5 figures plus supplement 8 pages, 4 figures

Published
2023

3. Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers

Author

Smith-Byrne, Karl, Hedman, Åsa, Dimitriou, Marios, Desai, Trishna, Sokolov, Alexandr V., Schioth, Helgi B., Koprulu, Mine, Pietzner, Maik, Langenberg, Claudia, Atkins, Joshua, Penha, Ricardo Cortez, McKay, James, Brennan, Paul, Zhou, Sirui, Richards, Brent J., Yarmolinsky, James, Martin, Richard M., Borlido, Joana, Mu, Xinmeng J., Butterworth, Adam, Shen, Xia, Wilson, Jim, Assimes, Themistocles L., Hung, Rayjean J., Amos, Christopher, Purdue, Mark, Rothman, Nathaniel, Chanock, Stephen, Travis, Ruth C., Johansson, Mattias, and Mälarstig, Anders

Published
2024
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5. Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study

Author

Dixon-Suen, Suzanne C, Lewis, Sarah J, Martin, Richard M, English, Dallas R, Boyle, Terry, Giles, Graham G, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Lush, Michael, Investigators, ABCTB, Ahearn, Thomas U, Ambrosone, Christine B, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Auvinen, Päivi, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Brenner, Hermann, Brüning, Thomas, Buys, Saundra S, Camp, Nicola J, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Cessna, Melissa H, Chang-Claude, Jenny, Chanock, Stephen J, Clarke, Christine L, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Fletcher, Olivia, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Goldberg, Mark S, Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Häberle, Lothar, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hart, Steven N, Harvie, Michelle, Hillemanns, Peter, Hollestelle, Antoinette, Hooning, Maartje J, Hoppe, Reiner, Hopper, John, Howell, Anthony, Hunter, David J, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Le Marchand, Loic, Lindblom, Annika, Loibl, Sibylle, Lubiński, Jan, Mannermaa, Arto, and Manoochehri, Mehdi

Subjects
Aging, Genetics, Breast Cancer, Clinical Research, Cancer, Prevention, Female, Humans, Breast Neoplasms, Exercise, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Risk Factors, Sedentary Behavior, Breast Cancer Association Consortium, Breast, Physical activity, Sedentary Behaviour, Engineering, Medical and Health Sciences, Education, Sport Sciences
Abstract

ObjectivesPhysical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.MethodsWe performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity.ResultsGreater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger).ConclusionOur study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.

Published
2022

6. The effect of SGLT2 inhibition on prostate cancer: Mendelian randomization and observational analysis using electronic healthcare and cohort data

Author

Zheng, Jie, Lu, Jieli, Qi, Jiying, Yang, Qian, Zhao, Huiling, Liu, Haoyu, Chen, Zhihe, Huang, Lanhui, Ye, Youqiong, Xu, Min, Xu, Yu, Wang, Tiange, Li, Mian, Zhao, Zhiyun, Zheng, Ruizhi, Wang, Shuangyuan, Lin, Hong, Hu, Chunyan, Ling Chui, Celine Sze, Au Yeung, Shiu Lun, Luo, Shan, Dimopoulou, Olympia, Dixon, Padraig, Harrison, Sean, Liu, Yi, Robinson, Jamie, Yarmolinsky, James, Haycock, Philip, Yuan, Jinqiu, Lewis, Sarah, Yuan, Zhongshang, Gaunt, Tom R., Smith, George Davey, Ning, Guang, Martin, Richard M., Cui, Bin, Wang, Weiqing, and Bi, Yufang

Published
2024
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7. Genetically proxied glucose-lowering drug target perturbation and risk of cancer: a Mendelian randomisation analysis

Author

Yarmolinsky, James, Bouras, Emmanouil, Constantinescu, Andrei, Burrows, Kimberley, Bull, Caroline J., Vincent, Emma E., Martin, Richard M., Dimopoulou, Olympia, Lewis, Sarah J., Moreno, Victor, Vujkovic, Marijana, Chang, Kyong-Mi, Voight, Benjamin F., Tsao, Philip S., Gunter, Marc J., Hampe, Jochen, Pellatt, Andrew J., Pharoah, Paul D. P., Schoen, Robert E., Gallinger, Steven, Jenkins, Mark A., Pai, Rish K., Gill, Dipender, and Tsilidis, Kostas K.

Published
2023
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8. Electronic Structure and Magnetism of the Triple-layered Ruthenate Sr$_{4}$Ru$_{3}$O$_{10}$

Author

Gebreyesus, G., Ngabonziza, Prosper, Nagura, Jonah, Seriani, Nicola, Akin-Ojo, Omololu, and Martin, Richard M.

Subjects
Condensed Matter - Strongly Correlated Electrons
Abstract

We report electronic band structure calculations for Sr$_{4}$Ru$_{3}$O$_{10}$ that displays both ferromagnetic and metamagnetic behavior. The density functional calculations find the ground state to be ferromagnetic in agreement with the experiment and we find that the inclusion of Coulomb Hubbard interaction U applied to the Ru 4d states has dramatic effects on the Fermi surface, which reveal the role of Coulomb interactions and correlated many-body physics. The minority spin bands are mainly empty with Fermi surfaces in the outer areas of the Brillouin zone away from the $\Gamma$ point with bands that disperse steeply upward. The majority spin bands are full or nearly fully occupied and form narrow bands near the Fermi energy around the $\Gamma$ point, which could be the electronic origin of the metamagnetism. The results are in qualitative agreement with recent angle resolved photoemission spectroscopy (ARPES) experiments and show the need for a combined theoretical study and experimental ARPES investigation with better energy resolution to reveal the nature of the narrow bands close to the Fermi-level, which is critical for understanding the exotic magnetic properties observed in this material.

Published
2021
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9. Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics

Author

Desai, Trishna A., Hedman, Åsa K., Dimitriou, Marios, Koprulu, Mine, Figiel, Sandy, Yin, Wencheng, Johansson, Mattias, Watts, Eleanor L., Atkins, Joshua R., Sokolov, Aleksandr V., Schiöth, Helgi B., Gunter, Marc J., Tsilidis, Konstantinos K., Martin, Richard M., Pietzner, Maik, Langenberg, Claudia, Mills, Ian G., Lamb, Alastair D., Mälarstig, Anders, Key, Tim J., Travis, Ruth C., and Smith-Byrne, Karl

Published
2024
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11. Body size and risk of colorectal cancer molecular defined subtypes and pathways: Mendelian randomization analyses

Author

Papadimitriou, Nikos, Qu, Conghui, Harrison, Tabitha A., Bever, Alaina M., Martin, Richard M., Tsilidis, Konstantinos K., Newcomb, Polly A., Thibodeau, Stephen N., Newton, Christina C., Um, Caroline Y., Obón-Santacana, Mireia, Moreno, Victor, Brenner, Hermann, Mandic, Marko, Chang-Claude, Jenny, Hoffmeister, Michael, Pellatt, Andrew J., Schoen, Robert E., Harlid, Sophia, Ogino, Shuji, Ugai, Tomotaka, Buchanan, Daniel D., Lynch, Brigid M., Gruber, Stephen B., Cao, Yin, Hsu, Li, Huyghe, Jeroen R., Lin, Yi, Steinfelder, Robert S., Sun, Wei, Van Guelpen, Bethany, Zaidi, Syed H., Toland, Amanda E., Berndt, Sonja I., Huang, Wen-Yi, Aglago, Elom K., Drew, David A., French, Amy J., Georgeson, Peter, Giannakis, Marios, Hullar, Meredith, Nowak, Johnathan A., Thomas, Claire E., Le Marchand, Loic, Cheng, Iona, Gallinger, Steven, Jenkins, Mark A., Gunter, Marc J., Campbell, Peter T., Peters, Ulrike, Song, Mingyang, Phipps, Amanda I., and Murphy, Neil

Published
2024
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12. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Landi, Maria Teresa, Stevens, Victoria, Wang, Ying, Albanes, Demetrios, Caporaso, Neil, Brennan, Paul, Amos, Christopher I., Shete, Sanjay, Hung, Rayjean J., Bickeböller, Heike, Risch, Angela, Houlston, Richard, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Johansson, Mattias, Wichmann, H-Erich, Christiani, David, Rennert, Gadi, Arnold, Susanne, Field, John K., Le Marchand, Loic, Melander, Olle, Brunnström, Hans, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A., Shen, Hongbing, Zienolddiny, Shan, Grankvist, Kjell, Johansson, Mikael, Teare, M. Dawn, Hong, Yun-Chul, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Al Olama, Ali Amin, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Chanock, Stephen, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M.L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, 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., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanfrod, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Logothetis, Christopher J., 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., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Yarmolinsky, James, Robinson, Jamie W., Mariosa, Daniela, Karhunen, Ville, Huang, Jian, Dimou, Niki, Murphy, Neil, Burrows, Kimberley, Bouras, Emmanouil, Smith-Byrne, Karl, Lewis, Sarah J., Galesloot, Tessel E., Vermeulen, Sita, Martin, Paul, Hou, Lifang, Newcomb, Polly A., White, Emily, Wu, Anna H., Le Marchand, Loïc, Phipps, Amanda I., Buchanan, Daniel D., Zhao, Sizheng Steven, Gill, Dipender, Chanock, Stephen J., Purdue, Mark P., Davey Smith, George, Herzig, Karl-Heinz, Järvelin, Marjo-Riitta, Amos, Chris I., Dehghan, Abbas, Gunter, Marc J., Tsilidis, Kostas K., and Martin, Richard M.

Published
2024
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13. Genetically predicted circulating concentrations of micronutrients and risk of colorectal cancer among individuals of European descent: a Mendelian randomization study

Author

Tsilidis, Konstantinos K, Papadimitriou, Nikos, Dimou, Niki, Gill, Dipender, Lewis, Sarah J, Martin, Richard M, Murphy, Neil, Markozannes, Georgios, Zuber, Verena, Cross, Amanda J, Burrows, Kimberley, Lopez, David S, Key, Timothy J, Travis, Ruth C, Perez-Cornago, Aurora, Hunter, David J, van Duijnhoven, Fränzel JB, Albanes, Demetrius, Arndt, Volker, Berndt, Sonja I, Bézieau, Stéphane, Bishop, D Timothy, Boehm, Juergen, Brenner, Hermann, Burnett-Hartman, Andrea, Campbell, Peter T, Casey, Graham, Castellví-Bel, Sergi, Chan, Andrew T, Chang-Claude, Jenny, de la Chapelle, Albert, Figueiredo, Jane C, Gallinger, Steven J, Giles, Graham G, Goodman, Phyllis J, Gsur, Andrea, Hampe, Jochen, Hampel, Heather, Hoffmeister, Michael, Jenkins, Mark A, Keku, Temitope O, Kweon, Sun-Seog, Larsson, Susanna C, Le Marchand, Loic, Li, Christopher I, Li, Li, Lindblom, Annika, Martín, Vicente, Milne, Roger L, Moreno, Victor, Nan, Hongmei, Nassir, Rami, Newcomb, Polly A, Offit, Kenneth, Pharoah, Paul DP, Platz, Elizabeth A, Potter, John D, Qi, Lihong, Rennert, Gad, Sakoda, Lori C, Schafmayer, Clemens, Slattery, Martha L, Snetselaar, Linda, Schenk, Jeanette, Thibodeau, Stephen N, Ulrich, Cornelia M, Van Guelpen, Bethany, Harlid, Sophia, Visvanathan, Kala, Vodickova, Ludmila, Wang, Hansong, White, Emily, Wolk, Alicja, Woods, Michael O, Wu, Anna H, Zheng, Wei, Bueno-de-Mesquita, Bas, Boutron-Ruault, Marie-Christine, Hughes, David J, Jakszyn, Paula, Kühn, Tilman, Palli, Domenico, Riboli, Elio, Giovannucci, Edward L, Banbury, Barbara L, Gruber, Stephen B, Peters, Ulrike, Gunter, Marc J, and on behalf of GECCO, CORECT

Subjects
Complementary and Integrative Health, Digestive Diseases, Clinical Research, Clinical Trials and Supportive Activities, Cancer, Colo-Rectal Cancer, Prevention, Nutrition, Prevention of disease and conditions, and promotion of well-being, 3.3 Nutrition and chemoprevention, Case-Control Studies, Colorectal Neoplasms, Dietary Supplements, Genetic Predisposition to Disease, Humans, Mendelian Randomization Analysis, Micronutrients, Risk Factors, Selenium, Vitamin B 12, White People, Mendelian randomization, genes, nutrition, supplements, colorectal cancer, Engineering, Medical and Health Sciences, Nutrition & Dietetics
Abstract

BackgroundThe literature on associations of circulating concentrations of minerals and vitamins with risk of colorectal cancer is limited and inconsistent. Evidence from randomized controlled trials (RCTs) to support the efficacy of dietary modification or nutrient supplementation for colorectal cancer prevention is also limited.ObjectivesTo complement observational and RCT findings, we investigated associations of genetically predicted concentrations of 11 micronutrients (β-carotene, calcium, copper, folate, iron, magnesium, phosphorus, selenium, vitamin B-6, vitamin B-12, and zinc) with colorectal cancer risk using Mendelian randomization (MR).MethodsTwo-sample MR was conducted using 58,221 individuals with colorectal cancer and 67,694 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry. Inverse variance-weighted MR analyses were performed with sensitivity analyses to assess the impact of potential violations of MR assumptions.ResultsNominally significant associations were noted for genetically predicted iron concentration and higher risk of colon cancer [ORs per SD (ORSD): 1.08; 95% CI: 1.00, 1.17; P value = 0.05] and similarly for proximal colon cancer, and for vitamin B-12 concentration and higher risk of colorectal cancer (ORSD: 1.12; 95% CI: 1.03, 1.21; P value = 0.01) and similarly for colon cancer. A nominally significant association was also noted for genetically predicted selenium concentration and lower risk of colon cancer (ORSD: 0.98; 95% CI: 0.96, 1.00; P value = 0.05) and similarly for distal colon cancer. These associations were robust to sensitivity analyses. Nominally significant inverse associations were observed for zinc and risk of colorectal and distal colon cancers, but sensitivity analyses could not be performed. None of these findings survived correction for multiple testing. Genetically predicted concentrations of β-carotene, calcium, copper, folate, magnesium, phosphorus, and vitamin B-6 were not associated with disease risk.ConclusionsThese results suggest possible causal associations of circulating iron and vitamin B-12 (positively) and selenium (inversely) with risk of colon cancer.

Published
2021

14. Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.

Author

Karunamuni, Roshan A, Huynh-Le, Minh-Phuong, Fan, Chun C, Thompson, Wesley, Eeles, Rosalind A, Kote-Jarai, Zsofia, Muir, Kenneth, Lophatananon, Artitaya, UKGPCS collaborators, Schleutker, Johanna, Pashayan, Nora, Batra, Jyotsna, APCB BioResource (Australian Prostate Cancer BioResource), Grönberg, Henrik, Walsh, Eleanor I, Turner, Emma L, Lane, Athene, Martin, Richard M, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Nordestgaard, Børge G, Tangen, Catherine M, MacInnis, Robert J, Wolk, Alicja, Albanes, Demetrius, Haiman, Christopher A, Travis, Ruth C, Stanford, Janet L, Mucci, Lorelei A, West, Catharine ML, Nielsen, Sune F, Kibel, Adam S, Wiklund, Fredrik, Cussenot, Olivier, Berndt, Sonja I, Koutros, Stella, Sørensen, Karina Dalsgaard, Cybulski, Cezary, Grindedal, Eli Marie, Park, Jong Y, Ingles, Sue A, Maier, Christiane, Hamilton, Robert J, Rosenstein, Barry S, Vega, Ana, IMPACT Study Steering Committee and Collaborators, Kogevinas, Manolis, Penney, Kathryn L, Teixeira, Manuel R, Brenner, Hermann, John, Esther M, Kaneva, Radka, Logothetis, Christopher J, Neuhausen, Susan L, Razack, Azad, Newcomb, Lisa F, Canary PASS Investigators, Gamulin, Marija, Usmani, Nawaid, Claessens, Frank, Gago-Dominguez, Manuela, Townsend, Paul A, Roobol, Monique J, Zheng, Wei, Profile Study Steering Committee, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, and PRACTICAL Consortium

Subjects
UKGPCS collaborators, APCB BioResource, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, PRACTICAL Consortium, Prevention, Urologic Diseases, Cancer, Prostate Cancer, Aging, Urology & Nephrology, Oncology and Carcinogenesis
Abstract

BackgroundPolygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).Materials and method180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.Results166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.ConclusionsIncorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

Published
2021

15. 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
UKGPCS collaborators, APCB, NC-LA PCaP Investigators, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, PRACTICAL Consortium, Humans, Prostatic Neoplasms, Neoplasm Invasiveness, Multivariate Analysis, Multifactorial Inheritance, Aged, Middle Aged, Ethnic Groups, Male, Self Report, Aging, Urologic Diseases, Cancer, Prostate Cancer
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

Published
2021

17. The association between genetically elevated polyunsaturated fatty acids and risk of cancer

Author

Tintle, Nathan, Rice, Terri, Cheng, Iona, Jenkins, Mark, Gallinger, Steve, Cornish, Alex J., Sud, Amit, Vijayakrishnan, Jayaram, Wrensch, Margaret, Johansson, Mattias, Norman, Aaron D., Klein, Alison, Clay-Gilmour, Alyssa, Franke, Andre, Ardisson Korat, Andres V., Wheeler, Bill, Nilsson, Björn, Smith, Caren, Heng, Chew-Kiat, Song, Ci, Riadi, David, Claus, Elizabeth B., Ellinghaus, Eva, Ostroumova, Evgenia, Hosnijeh, de Vathaire, Florent, Cugliari, Giovanni, Matullo, Giuseppe, Oi-Lin Ng, Irene, Passow, Jeanette E., Foo, Jia Nee, Han, Jiali, Liu, Jianjun, Barnholtz-Sloan, Jill, Schildkraut, Joellen M., Maris, John, Wiemels, Joseph L., Hemminki, Kari, Yang, Keming, Kiemeney, Lambertus A., Wu, Lang, Amundadottir, Laufey, Stern, Marc-Henri, Boutron, Marie-Christine, Iles, Mark Martin, Purdue, Mark P., Stanulla, Martin, Bondy, Melissa, Gaudet, Mia, Mobuchon, Lenha, Camp, Nicola J., Sham, Pak Chung, Guénel, Pascal, Brennan, Paul, Taylor, Philip R., Ostrom, Quinn, Stolzenberg-Solomon, Rachael, Dorajoo, Rajkumar, Houlston, Richard, Jenkins, Robert B., Diskin, Sharon, Berndt, Sonja I., Tsavachidis, Spiridon, Channock, Stephen J., Harrison, Tabitha, Galesloot, Tessel, Gyllensten, Ulf, Joseph, Vijai, Shi, Y., Yang, Wenjian, Lin, Yi, Van Den Eeden, Stephen K., Haycock, Philip C., Borges, Maria Carolina, Burrows, Kimberley, Lemaitre, Rozenn N., Burgess, Stephen, Khankari, Nikhil K., Tsilidis, Konstantinos K., Gaunt, Tom R., Hemani, Gibran, Zheng, Jie, Truong, Therese, Birmann, Brenda M., OMara, Tracy, Spurdle, Amanda B., Iles, Mark M., Law, Matthew H., Slager, Susan L., Saberi Hosnijeh, Fatemeh, Mariosa, Daniela, Cotterchio, Michelle, Cerhan, James R., Peters, Ulrike, Enroth, Stefan, Gharahkhani, Puya, Le Marchand, Loic, Williams, Ann C., Block, Robert C., Amos, Christopher I., Hung, Rayjean J., Zheng, Wei, Gunter, Marc J., Smith, George Davey, Relton, Caroline, and Martin, Richard M.

Published
2023
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18. 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, Al Olama, Ali Amin, Garcia, Sara Benlloch, 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, BioResource, for the Australian Prostate Cancer, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, and Consortium, for the PRACTICAL

Subjects
Biomedical and Clinical Sciences, Health Sciences, Clinical Sciences, Oncology and Carcinogenesis, Aging, Prostate Cancer, Cancer, Prevention, Urologic Diseases, Good Health and Well Being, Aged, Early Detection of Cancer, Humans, Male, Middle Aged, Neoplasm Grading, Population Control, Prostatic Neoplasms, Australian Prostate Cancer BioResource, PRACTICAL Consortium, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
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

19. A national initiative in data science for health: an evaluation of the UK Farr Institute

Author

Hemingway, H, Lyons, R, Li, Q, Buchan, I, Ainsworth, J, Pell, J, Morris, A, Barnes, Michael R, Bedford, Helen, Bennie, Marion, Blandford, Ann, Briggs, Andy, Brocklehurst, Peter, Brophy, Sinead, Brown, Gavin, Burton, Paul, Butler, Christopher, Capewell, Simon, Carpenter, James, Carroll, John, Cassell, Jackie A, Castillo, Fortunato, Catchpole, Mike, Caulfield, Mark, Colhoun, Helen, Coveney, Peter, Cunningham-Burley, Sarah, Custovic, Adnan, Deanfield, John, Denaxas, Spiros, Dennis, Michael, Dezateux, Carol, Dibben, Chris, Diggle, Peter, Dixon, Will, Dunn, Graham, Emam, Khaled El, Fone, David, Ford, David, Ford, Ian, Frank, John, Freemantle, Nick, Gabbe, Belinda, Gallacher, John, Gibson, Martin, Gilbert, Ruth, Gissler, Mika, Goble, Carol, Goldberg, Andy, Gravenor, Mike, Gunnell, David, Hannaford, Phil, Hayward, Andrew, Hickman, Matthew, Hingorani, Aroon, Holm, Soren, Holman, Cashel, John, Gareth, John, Ann, Jones, Kerina, Kalra, Dipak, Laurie, Graeme, Lewis, Shon, Lloyd, Keith, Lowe, Sarah, McCowan, Colin, Macleod, John, Martin, Richard M, Moore, Anthony, Moore, Laurence, Nazareth, Irwin, Nenadic, Goran, Paranjothy, Shantini, Parmar, Max, Pebody, Richard, Petersen, Steffen, Petersen, Irene, Pillay, Deenan, Preen, David, Pickett, Kate, Pritchard-Jones, Kathy, Przulj, Natasa, Renehan, Andrew, Roberts, Stephen, Robson, John, Rodgers, Sarah, Rossor, Martin, Russell, Ian, Shawe-Taylor, John, Sheikh, Aziz, Siebert, Stefan, Snooks, Helen, Sperrin, Matthew, Stephenson, Judith, Sullivan, Frank, Taylor, Chris, Taylor, Paul, Timmis, Adam, and Ward, Hester JT

Subjects
Information and Computing Sciences, Library and Information Studies, Health Sciences, Generic health relevance, Health sciences, Human society, Information and computing sciences
Abstract

ObjectiveTo evaluate the extent to which the inter-institutional, inter-disciplinary mobilisation of data and skills in the Farr Institute contributed to establishing the emerging field of data science for health in the UK.Design and outcome measuresWe evaluated evidence of six domains characterising a new field of science:defining central scientific challenges,demonstrating how the central challenges might be solved,creating novel interactions among groups of scientists,training new types of experts,re-organising universities,demonstrating impacts in society.We carried out citation, network and time trend analyses of publications, and a narrative review of infrastructure, methods and tools.SettingFour UK centres in London, North England, Scotland and Wales (23 university partners), 2013-2018.Results1. The Farr Institute helped define a central scientific challenge publishing a research corpus, demonstrating insights from electronic health record (EHR) and administrative data at each stage of the translational cycle in 593 papers with at least one Farr Institute author affiliation on PubMed. 2. The Farr Institute offered some demonstrations of how these scientific challenges might be solved: it established the first four ISO27001 certified trusted research environments in the UK, and approved more than 1000 research users, published on 102 unique EHR and administrative data sources, although there was no clear evidence of an increase in novel, sustained record linkages. The Farr Institute established open platforms for the EHR phenotyping algorithms and validations (>70 diseases, CALIBER). Sample sizes showed some evidence of increase but remained less than 10% of the UK population in primary care-hospital care linked studies. 3.The Farr Institute created novel interactions among researchers: the co-author publication network expanded from 944 unique co-authors (based on 67 publications in the first 30 months) to 3839 unique co-authors (545 papers in the final 30 months). 4. Training expanded substantially with 3 new masters courses, training >400 people at masters, short-course and leadership level and 48 PhD students. 5. Universities reorganised with 4/5 Centres established 27 new faculty (tenured) positions, 3 new university institutes. 6. Emerging evidence of impacts included: > 3200 citations for the 10 most cited papers and Farr research informed eight practice-changing clinical guidelines and policies relevant to the health of millions of UK citizens.ConclusionThe Farr Institute played a major role in establishing and growing the field of data science for health in the UK, with some initial evidence of benefits for health and healthcare. The Farr Institute has now expanded into Health Data Research (HDR) UK but key challenges remain including, how to network such activities internationally.

Published
2020

20. Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility.

Author

Kachuri, Linda, Johansson, Mattias, Rashkin, Sara R, Graff, Rebecca E, Bossé, Yohan, Manem, Venkata, Caporaso, Neil E, Landi, Maria Teresa, Christiani, David C, Vineis, Paolo, Liu, Geoffrey, Scelo, Ghislaine, Zaridze, David, Shete, Sanjay S, Albanes, Demetrius, Aldrich, Melinda C, Tardón, Adonina, Rennert, Gad, Chen, Chu, Goodman, Gary E, Doherty, Jennifer A, Bickeböller, Heike, Field, John K, Davies, Michael P, Dawn Teare, M, Kiemeney, Lambertus A, Bojesen, Stig E, Haugen, Aage, Zienolddiny, Shanbeh, Lam, Stephen, Le Marchand, Loïc, Cheng, Iona, Schabath, Matthew B, Duell, Eric J, Andrew, Angeline S, Manjer, Jonas, Lazarus, Philip, Arnold, Susanne, McKay, James D, Emami, Nima C, Warkentin, Matthew T, Brhane, Yonathan, Obeidat, Ma'en, Martin, Richard M, Relton, Caroline, Davey Smith, George, Haycock, Philip C, Amos, Christopher I, Brennan, Paul, Witte, John S, and Hung, Rayjean J

Subjects
Lung, Humans, Lung Neoplasms, Genetic Predisposition to Disease, Respiratory Function Tests, Vital Capacity, Forced Expiratory Volume, Prospective Studies, Phenotype, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, Female, Male, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide
Abstract

Impaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1: rg = 0.098, p = 2.3 × 10-8) and the ratio of FEV1 to forced vital capacity (FEV1/FVC: rg = 0.137, p = 2.0 × 10-12). Mendelian randomization analyses demonstrate that reduced FEV1 increases squamous cell carcinoma risk (odds ratio (OR) = 1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR = 1.17, 1.01-1.35) and lung cancer in never smokers (OR = 1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis.

Published
2020

21. The associations of anthropometric, behavioural and sociodemographic factors with circulating concentrations of IGF‐I, IGF‐II, IGFBP‐1, IGFBP‐2 and IGFBP‐3 in a pooled analysis of 16,024 men from 22 studies

Author

Watts, Eleanor L, Perez‐Cornago, Aurora, Appleby, Paul N, Albanes, Demetrius, Ardanaz, Eva, Black, Amanda, Bueno‐de‐Mesquita, H Bas, Chan, June M, Chen, Chu, Chubb, SA Paul, Cook, Michael B, Deschasaux, Mélanie, Donovan, Jenny L, English, Dallas R, Flicker, Leon, Freedman, Neal D, Galan, Pilar, Giles, Graham G, Giovannucci, Edward L, Gunter, Marc J, Habel, Laurel A, Häggström, Christel, Haiman, Christopher, Hamdy, Freddie C, Hercberg, Serge, Holly, Jeff M, Huang, Jiaqi, Huang, Wen‐Yi, Johansson, Mattias, Kaaks, Rudolf, Kubo, Tatsuhiko, Lane, J Athene, Layne, Tracy M, Le Marchand, Loic, Martin, Richard M, Metter, E Jeffrey, Mikami, Kazuya, Milne, Roger L, Morris, Howard A, Mucci, Lorelei A, Neal, David E, Neuhouser, Marian L, Oliver, Steven E, Overvad, Kim, Ozasa, Kotaro, Pala, Valeria, Pernar, Claire H, Pollak, Michael, Rowlands, Mari‐Anne, Schaefer, Catherine A, Schenk, Jeannette M, Stattin, Pär, Tamakoshi, Akiko, Thysell, Elin, Touvier, Mathilde, Trichopoulou, Antonia, Tsilidis, Konstantinos K, Van Den Eeden, Stephen K, Weinstein, Stephanie J, Wilkens, Lynne, Yeap, Bu B, Key, Timothy J, Allen, Naomi E, and Travis, Ruth C

Subjects
Cancer, Aging, Urologic Diseases, Adult, Aged, Aged, 80 and over, Anthropometry, Biomarkers, Tumor, Cross-Sectional Studies, Humans, Insulin-Like Growth Factor Binding Proteins, Insulin-Like Growth Factor I, Insulin-Like Growth Factor II, Male, Middle Aged, Neoplasms, Prospective Studies, Young Adult, IGFs, IGFBPs, pooled analysis, correlates, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Insulin-like growth factors (IGFs) and insulin-like growth factor binding proteins (IGFBPs) have been implicated in the aetiology of several cancers. To better understand whether anthropometric, behavioural and sociodemographic factors may play a role in cancer risk via IGF signalling, we examined the cross-sectional associations of these exposures with circulating concentrations of IGFs (IGF-I and IGF-II) and IGFBPs (IGFBP-1, IGFBP-2 and IGFBP-3). The Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group dataset includes individual participant data from 16,024 male controls (i.e. without prostate cancer) aged 22-89 years from 22 prospective studies. Geometric means of protein concentrations were estimated using analysis of variance, adjusted for relevant covariates. Older age was associated with higher concentrations of IGFBP-1 and IGFBP-2 and lower concentrations of IGF-I, IGF-II and IGFBP-3. Higher body mass index was associated with lower concentrations of IGFBP-1 and IGFBP-2. Taller height was associated with higher concentrations of IGF-I and IGFBP-3 and lower concentrations of IGFBP-1. Smokers had higher concentrations of IGFBP-1 and IGFBP-2 and lower concentrations of IGFBP-3 than nonsmokers. Higher alcohol consumption was associated with higher concentrations of IGF-II and lower concentrations of IGF-I and IGFBP-2. African Americans had lower concentrations of IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 and Hispanics had lower IGF-I, IGF-II and IGFBP-3 than non-Hispanic whites. These findings indicate that a range of anthropometric, behavioural and sociodemographic factors are associated with circulating concentrations of IGFs and IGFBPs in men, which will lead to a greater understanding of the mechanisms through which these factors influence cancer risk.

Published
2019

22. Associating Growth in Infancy and Cognitive Performance in Early Childhood: A functional data analysis approach

Author

Hadjipantelis, Pantelis Z., Han, Kyunghee, Wang, Jane-Ling, Yang, Seungmi, Martin, Richard M., Kramer, Michael S., Oken, Emily, and Müller, Hans-Georg

Subjects
Statistics - Applications
Abstract

Physical growth traits can be naturally represented by continuous functions. In a large dataset of infancy growth patterns, we develop a practical approach to infer statistical associations between growth-trajectories and IQ performance in early childhood. The main objective of this study is to show how to assess physical growth curves and detect if particular infancy growth patterns are associated with differences in IQ (Full-scale WASI scores) in later ages using a semi-parametric functional response model. Additionally, we investigate the association between different growth measurements in terms of their cross-correlation with each other, their correlation with later IQ, as well as their time-varying dynamics. This analysis framework can easily incorporate or learn population information in a non-parametric way, rendering the existence of prior population charts partially redundant.

Published
2018

23. QMCPACK : An open source ab initio Quantum Monte Carlo package for the electronic structure of atoms, molecules, and solids

Author

Kim, Jeongnim, Baczewski, Andrew, Beaudet, Todd D., Benali, Anouar, Bennett, M. Chandler, Berrill, Mark A., Blunt, Nick S., Borda, Edgar Josue Landinez, Casula, Michele, Ceperley, David M., Chiesa, Simone, Clark, Bryan K., Clay III, Raymond C., Delaney, Kris T., Dewing, Mark, Esler, Kenneth P., Hao, Hongxia, Heinonen, Olle, Kent, Paul R. C., Krogel, Jaron T., Kylanpaa, Ilkka, Li, Ying Wai, Lopez, M. Graham, Luo, Ye, Malone, Fionn D., Martin, Richard M., Mathuriya, Amrita, McMinis, Jeremy, Melton, Cody A., Mitas, Lubos, Morales, Miguel A., Neuscamman, Eric, Parker, William D., Flores, Sergio D. Pineda, Romero, Nichols A., Rubenstein, Brenda M., Shea, Jacqueline A. R., Shin, Hyeondeok, Shulenburger, Luke, Tillack, Andreas, Townsend, Joshua P., Tubman, Norm M., Van Der Goetz, Brett, Vincent, Jordan E., Yang, D. ChangMo, Yang, Yubo, Zhang, Shuai, and Zhao, Luning

Subjects
Physics - Computational Physics, Physics - Chemical Physics
Abstract

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program's capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org .

Published
2018
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24. A collaborative analysis of individual participant data from 19 prospective studies assesses circulating vitamin D and prostate cancer risk

Author

Travis, Ruth C, Perez-Cornago, Aurora, Appleby, Paul N, Albanes, Demetrius, Joshu, Corinne E, Lutsey, Pamela L, Mondul, Alison M, Platz, Elizabeth A, Weinstein, Stephanie J, Layne, Tracy M, Helzlsouer, Kathy J, Visvanathan, Kala, Palli, Domenico, Peeters, Petra H, Bueno-de-Mesquita, Bas, Trichopoulou, Antonia, Gunter, Marc J, Tsilidis, Konstantinos K, Sánchez, Maria-Jose, Olsen, Anja, Brenner, Hermann, Schöttker, Ben, Perna, Laura, Holleczek, Bernd, Knekt, Paul, Rissanen, Harri, Yeap, Bu B, Flicker, Leon, Almeida, Osvaldo P, Wong, Yuen Yee Elizabeth, Chan, June M, Giovannucci, Edward L, Stampfer, Meir J, Ursin, Giske, Gislefoss, Randi E, Bjørge, Tone, Meyer, Haakon E, Blomhoff, Rune, Tsugane, Shoichiro, Sawada, Norie, English, Dallas R, Eyles, Darryl W, Heath, Alicia K, Williamson, Elizabeth J, Manjer, Jonas, Malm, Johan, Almquist, Martin, Marchand, Loic Le, Haiman, Christopher A, Wilkens, Lynne R, Schenk, Jeannette M, Tangen, Cathy M, Black, Amanda, Cook, Michael B, Huang, Wen-Yi, Ziegler, Regina G, Martin, Richard M, Hamdy, Freddie C, Donovan, Jenny L, Neal, David E, Touvier, Mathilde, Hercberg, Serge, Galan, Pilar, Deschasaux, Mélanie, Key, Timothy J, and Allen, Naomi E

Subjects
Clinical Trials and Supportive Activities, Nutrition, Cancer, Prostate Cancer, Urologic Diseases, Prevention, Aging, Clinical Research, Aged, Case-Control Studies, Cross-Sectional Studies, Humans, Male, Middle Aged, Odds Ratio, Prospective Studies, Prostatic Neoplasms, Risk Assessment, Risk Factors, Vitamin D, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Previous prospective studies assessing the relationship between circulating concentrations of vitamin D and prostate cancer risk have shown inconclusive results, particularly for risk of aggressive disease. In this study, we examine the association between prediagnostic concentrations of 25-hydroxyvitamin D [25(OH)D] and 1,25-dihydroxyvitamin D [1,25(OH)2D] and the risk of prostate cancer overall and by tumor characteristics. Principal investigators of 19 prospective studies provided individual participant data on circulating 25(OH)D and 1,25(OH)2D for up to 13,462 men with incident prostate cancer and 20,261 control participants. ORs for prostate cancer by study-specific fifths of season-standardized vitamin D concentration were estimated using multivariable-adjusted conditional logistic regression. 25(OH)D concentration was positively associated with risk for total prostate cancer (multivariable-adjusted OR comparing highest vs. lowest study-specific fifth was 1.22; 95% confidence interval, 1.13-1.31; P trend < 0.001). However, this association varied by disease aggressiveness (P heterogeneity = 0.014); higher circulating 25(OH)D was associated with a higher risk of nonaggressive disease (OR per 80 percentile increase = 1.24, 1.13-1.36) but not with aggressive disease (defined as stage 4, metastases, or prostate cancer death, 0.95, 0.78-1.15). 1,25(OH)2D concentration was not associated with risk for prostate cancer overall or by tumor characteristics. The absence of an association of vitamin D with aggressive disease does not support the hypothesis that vitamin D deficiency increases prostate cancer risk. Rather, the association of high circulating 25(OH)D concentration with a higher risk of nonaggressive prostate cancer may be influenced by detection bias. SIGNIFICANCE: This international collaboration comprises the largest prospective study on blood vitamin D and prostate cancer risk and shows no association with aggressive disease but some evidence of a higher risk of nonaggressive disease.

Published
2019

26. Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis

Author

Bouras, Emmanouil, Karhunen, Ville, Gill, Dipender, Huang, Jian, Haycock, Philip C., Gunter, Marc J., Johansson, Mattias, Brennan, Paul, Key, Tim, Lewis, Sarah J., Martin, Richard M., Murphy, Neil, Platz, Elizabeth A., Travis, Ruth, Yarmolinsky, James, Zuber, Verena, Martin, Paul, Katsoulis, Michail, Freisling, Heinz, Nøst, Therese Haugdahl, Schulze, Matthias B., Dossus, Laure, Hung, Rayjean J., Amos, Christopher I., Ahola-Olli, Ari, Palaniswamy, Saranya, Männikkö, Minna, Auvinen, Juha, Herzig, Karl-Heinz, Keinänen-Kiukaanniemi, Sirkka, Lehtimäki, Terho, Salomaa, Veikko, Raitakari, Olli, Salmi, Marko, Jalkanen, Sirpa, Jarvelin, Marjo-Riitta, Dehghan, Abbas, and Tsilidis, Konstantinos K.

Published
2022
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28. Investigating the effect of sexual behaviour on oropharyngeal cancer risk: a methodological assessment of Mendelian randomization

Author

Gormley, Mark, Dudding, Tom, Kachuri, Linda, Burrows, Kimberley, Chong, Amanda H. W., Martin, Richard M., Thomas, Steven J., Tyrrell, Jessica, Ness, Andrew R., Brennan, Paul, Munafò, Marcus R., Pring, Miranda, Boccia, Stefania, Olshan, Andrew F., Diergaarde, Brenda, Hung, Rayjean J., Liu, Geoffrey, Tajara, Eloiza H., Severino, Patricia, Toporcov, Tatiana N., Lacko, Martin, Waterboer, Tim, Brenner, Nicole, Smith, George Davey, Vincent, Emma E., and Richmond, Rebecca C.

Published
2022
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29. Prostate cancer–Exercise and Metformin Trial (Pre-EMpT): study protocol for a feasibility factorial randomized controlled trial in men with localised or locally advanced prostate cancer

Author

McGeagh, Lucy, Robles, Luke A., Persad, Raj, Rowe, Edward, Bahl, Amit, Aning, Jonathan, Koupparis, Anthony, Abrams, Paul, Perks, Claire, Holly, Jeffrey, Johnson, Lyndsey, Shiridzinomwa, Constance, Challapalli, Amarnath, Shingler, Ellie, Taylor, Hilary, Oxley, Jon, Sandu, Meda, Martin, Richard M., and Lane, J. Athene

Published
2022
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33. Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Author

Schumacher, Fredrick R, Al Olama, Ali Amin, Berndt, Sonja I, Benlloch, Sara, Ahmed, Mahbubl, Saunders, Edward J, Dadaev, Tokhir, Leongamornlert, Daniel, Anokian, Ezequiel, Cieza-Borrella, Clara, Goh, Chee, Brook, Mark N, Sheng, Xin, Fachal, Laura, Dennis, Joe, Tyrer, Jonathan, Muir, Kenneth, Lophatananon, Artitaya, Stevens, Victoria L, Gapstur, Susan M, Carter, Brian D, Tangen, Catherine M, Goodman, Phyllis J, Thompson, Ian M, Batra, Jyotsna, Chambers, Suzanne, Moya, Leire, Clements, Judith, Horvath, Lisa, Tilley, Wayne, Risbridger, Gail P, 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, Håkansson, Niclas, West, Catharine ML, Dunning, Alison M, Burnet, Neil, Mucci, Lorelei A, Giovannucci, Edward, Andriole, Gerald L, Cussenot, Olivier, Cancel-Tassin, Géraldine, Koutros, Stella, Beane Freeman, Laura E, 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 S, Kerns, Sarah L, 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, 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, and Cybulski, Cezary

Subjects
Cancer, Aging, Prostate Cancer, Genetics, Urologic Diseases, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Case-Control Studies, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Risk, Profile Study, Australian Prostate Cancer BioResource, IMPACT Study, Canary PASS Investigators, Breast and Prostate Cancer Cohort Consortium, PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium, Cancer of the Prostate in Sweden, Prostate Cancer Genome-wide Association Study of Uncommon Susceptibility Loci, Genetic Associations and Mechanisms in Oncology (GAME-ON)/Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE) Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Published
2018

34. 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, and Sellers, Thomas A

Subjects
Genetics, Aging, Urologic Diseases, Prostate Cancer, Prevention, Human Genome, Cancer, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Algorithms, Bayes Theorem, Black People, Chromosome Mapping, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Molecular Sequence Annotation, Multivariate Analysis, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Quantitative Trait Loci, Risk, White People, PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium
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.

Published
2018

35. Functional principal component analysis for identifying multivariate patterns and archetypes of growth, and their association with long-term cognitive development.

Author

Han, Kyunghee, Hadjipantelis, Pantelis Z, Wang, Jane-Ling, Kramer, Michael S, Yang, Seungmi, Martin, Richard M, and Müller, Hans-Georg

Subjects
Multivariate Analysis, Models, Statistical, Risk, Longitudinal Studies, Intelligence, Cognition, Growth and Development, Principal Component Analysis, Time Factors, Models, Statistical, General Science & Technology
Abstract

For longitudinal studies with multivariate observations, we propose statistical methods to identify clusters of archetypal subjects by using techniques from functional data analysis and to relate longitudinal patterns to outcomes. We demonstrate how this approach can be applied to examine associations between multiple time-varying exposures and subsequent health outcomes, where the former are recorded sparsely and irregularly in time, with emphasis on the utility of multiple longitudinal observations in the framework of dimension reduction techniques. In applications to children's growth data, we investigate archetypes of infant growth patterns and identify subgroups that are related to cognitive development in childhood. Specifically, "Stunting" and "Faltering" time-dynamic patterns of head circumference, body length and weight in the first 12 months are associated with lower levels of long-term cognitive development in comparison to "Generally Large" and "Catch-up" growth. Our findings provide evidence for the statistical association between multivariate growth patterns in infancy and long-term cognitive development.

Published
2018

37. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Yarmolinsky, James, primary, Robinson, Jamie W., additional, Mariosa, Daniela, additional, Karhunen, Ville, additional, Huang, Jian, additional, Dimou, Niki, additional, Murphy, Neil, additional, Burrows, Kimberley, additional, Bouras, Emmanouil, additional, Smith-Byrne, Karl, additional, Lewis, Sarah J., additional, Galesloot, Tessel E., additional, Kiemeney, Lambertus A., additional, Vermeulen, Sita, additional, Martin, Paul, additional, Albanes, Demetrius, additional, Hou, Lifang, additional, Newcomb, Polly A., additional, White, Emily, additional, Wolk, Alicja, additional, Wu, Anna H., additional, Le Marchand, Loïc, additional, Phipps, Amanda I., additional, Buchanan, Daniel D., additional, Zhao, Sizheng Steven, additional, Gill, Dipender, additional, Chanock, Stephen J., additional, Purdue, Mark P., additional, Davey Smith, George, additional, Brennan, Paul, additional, Herzig, Karl-Heinz, additional, Järvelin, Marjo-Riitta, additional, Amos, Chris I., additional, Hung, Rayjean J., additional, Dehghan, Abbas, additional, Johansson, Mattias, additional, Gunter, Marc J., additional, Tsilidis, Kostas K., additional, Martin, Richard M., additional, Landi, Maria Teresa, additional, Stevens, Victoria, additional, Wang, Ying, additional, Albanes, Demetrios, additional, Caporaso, Neil, additional, Amos, Christopher I., additional, Shete, Sanjay, additional, Bickeböller, Heike, additional, Risch, Angela, additional, Houlston, Richard, additional, Lam, Stephen, additional, Tardon, Adonina, additional, Chen, Chu, additional, Bojesen, Stig E., additional, Wichmann, H-Erich, additional, Christiani, David, additional, Rennert, Gadi, additional, Arnold, Susanne, additional, Field, John K., additional, Le Marchand, Loic, additional, Melander, Olle, additional, Brunnström, Hans, additional, Liu, Geoffrey, additional, Andrew, Angeline, additional, Shen, Hongbing, additional, Zienolddiny, Shan, additional, Grankvist, Kjell, additional, Johansson, Mikael, additional, Teare, M. Dawn, additional, Hong, Yun-Chul, additional, Yuan, Jian-Min, additional, Lazarus, Philip, additional, Schabath, Matthew B., additional, Aldrich, Melinda C., additional, Eeles, Rosalind A., additional, Haiman, Christopher A., additional, Kote-Jarai, Zsofia, additional, Schumacher, Fredrick R., additional, Benlloch, Sara, additional, Al Olama, Ali Amin, additional, Muir, Kenneth R., additional, Berndt, Sonja I., additional, Conti, David V., additional, Wiklund, Fredrik, additional, Chanock, Stephen, additional, Tangen, Catherine M., additional, Batra, Jyotsna, additional, Clements, Judith A., additional, Grönberg, Henrik, additional, Pashayan, Nora, additional, Schleutker, Johanna, additional, Weinstein, Stephanie J., additional, West, Catharine M.L., additional, Mucci, Lorelei A., additional, Cancel-Tassin, Géraldine, additional, Koutros, Stella, additional, Sørensen, Karina Dalsgaard, additional, Grindedal, Eli Marie, additional, Neal, David E., additional, Hamdy, Freddie C., additional, Donovan, Jenny L., additional, Travis, Ruth C., additional, Hamilton, Robert J., additional, Ingles, Sue Ann, additional, Rosenstein, Barry S., additional, Lu, Yong-Jie, additional, Giles, Graham G., additional, MacInnis, Robert J., additional, Kibel, Adam S., additional, Vega, Ana, additional, Kogevinas, Manolis, additional, Penney, Kathryn L., additional, Park, Jong Y., additional, Stanfrod, Janet L., additional, Cybulski, Cezary, additional, Nordestgaard, Børge G., additional, Nielsen, Sune F., additional, Brenner, Hermann, additional, Maier, Christiane, additional, Logothetis, Christopher J., additional, John, Esther M., additional, Teixeira, Manuel R., additional, Neuhausen, Susan L., additional, De Ruyck, Kim, additional, Razack, Azad, additional, Newcomb, Lisa F., additional, Lessel, Davor, additional, Kaneva, Radka, additional, Usmani, Nawaid, additional, Claessens, Frank, additional, Townsend, Paul A., additional, Castelao, Jose Esteban, additional, Roobol, Monique J., additional, Menegaux, Florence, additional, Khaw, Kay-Tee, additional, Cannon-Albright, Lisa, additional, Pandha, Hardev, additional, Thibodeau, Stephen N., additional, Hunter, David J., additional, Kraft, Peter, additional, Blot, William J., additional, and Riboli, Elio, additional

Published
2024
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38. Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study

Author

Carreras-Torres, Robert, Johansson, Mattias, Haycock, Philip C, Wade, Kaitlin H, Relton, Caroline L, Martin, Richard M, Smith, George Davey, Albanes, Demetrius, Aldrich, Melinda C, Andrew, Angeline, Arnold, Susanne M, Bickeböller, Heike, Bojesen, Stig E, Brunnström, Hans, Manjer, Jonas, Brüske, Irene, Caporaso, Neil E, Chen, Chu, Christiani, David C, Christian, W Jay, Doherty, Jennifer A, Duell, Eric J, Field, John K, Davies, Michael PA, Marcus, Michael W, Goodman, Gary E, Grankvist, Kjell, Haugen, Aage, Hong, Yun-Chul, Kiemeney, Lambertus A, van der Heijden, Erik HFM, Kraft, Peter, Johansson, Mikael B, Lam, Stephen, Landi, Maria Teresa, Lazarus, Philip, Le Marchand, Loïc, Liu, Geoffrey, Melander, Olle, Park, Sungshim L, Rennert, Gad, Risch, Angela, Haura, Eric B, Scelo, Ghislaine, Zaridze, David, Mukeriya, Anush, Savić, Milan, Lissowska, Jolanta, Swiatkowska, Beata, Janout, Vladimir, Holcatova, Ivana, Mates, Dana, Schabath, Matthew B, Shen, Hongbing, Tardon, Adonina, Teare, M Dawn, Woll, Penella, Tsao, Ming-Sound, Wu, Xifeng, Yuan, Jian-Min, Hung, Rayjean J, Amos, Christopher I, McKay, James, and Brennan, Paul

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Genetics, Lung, Nutrition, Tobacco Smoke and Health, Prevention, Cancer, Tobacco, Obesity, Clinical Research, Lung Cancer, Aetiology, 2.1 Biological and endogenous factors, Body Mass Index, Fasting, Humans, Insulin, Insulin Resistance, Likelihood Functions, Lipids, Lung Neoplasms, Mendelian Randomization Analysis, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, General Science & Technology
Abstract

BackgroundAssessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer.Methods and findingsWe identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results.ConclusionsOur results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.

Published
2017

39. Identification of potential mediators of the relationship between body mass index and colorectal cancer : a Mendelian randomization analysis

Author

Bouras, Emmanouil, Gill, Dipender, Zuber, Verena, Murphy, Neil, Dimou, Niki, Aleksandrova, Krasimira, Lewis, Sarah J., Martin, Richard M., Yarmolinsky, James, Albanes, Demetrius, Brenner, Hermann, Castellví-Bel, Sergi, Chan, Andrew T., Cheng, Iona, Gruber, Stephen, van Guelpen, Bethany, Li, Christopher I., Le Marchand, Loic, Newcomb, Polly A., Ogino, Shuji, Pellatt, Andrew, Schmit, Stephanie L., Wolk, Alicja, Wu, Anna H., Peters, Ulrike, Gunter, Marc J., Tsilidis, Konstantinos K., Bouras, Emmanouil, Gill, Dipender, Zuber, Verena, Murphy, Neil, Dimou, Niki, Aleksandrova, Krasimira, Lewis, Sarah J., Martin, Richard M., Yarmolinsky, James, Albanes, Demetrius, Brenner, Hermann, Castellví-Bel, Sergi, Chan, Andrew T., Cheng, Iona, Gruber, Stephen, van Guelpen, Bethany, Li, Christopher I., Le Marchand, Loic, Newcomb, Polly A., Ogino, Shuji, Pellatt, Andrew, Schmit, Stephanie L., Wolk, Alicja, Wu, Anna H., Peters, Ulrike, Gunter, Marc J., and Tsilidis, Konstantinos K.

Abstract

Background: Colorectal cancer (CRC) is the third-most-common cancer worldwide and its rates are increasing. Elevated body mass index (BMI) is an established risk factor for CRC, although the molecular mechanisms behind this association remain unclear. Using the Mendelian randomization (MR) framework, we aimed to investigate the mediating effects of putative biomarkers and other CRC risk factors in the association between BMI and CRC. Methods: We selected as mediators biomarkers of established cancer-related mechanisms and other CRC risk factors for which a plausible association with obesity exists, such as inflammatory biomarkers, glucose homeostasis traits, lipids, adipokines, insulin-like growth factor 1 (IGF1), sex hormones, 25-hydroxy-vitamin D, smoking, physical activity (PA) and alcohol consumption. We used inverse-variance weighted MR in the main univariable analyses and performed sensitivity analyses (weighted-median, MR–Egger, Contamination Mixture). We used multivariable MR for the mediation analyses. Results: Genetically predicted BMI was positively associated with CRC risk [odds ratio per SD (5 kg/m2) ¼ 1.17, 95% CI: 1.08–1.24, P-value ¼ 1.4 × 10−5] and robustly associated with nearly all potential mediators. Genetically predicted IGF1, fasting insulin, low-density lipoprotein cholesterol, smoking, PA and alcohol were associated with CRC risk. Evidence for attenuation was found for IGF1 [explained 7% (95% CI: 2–13%) of the association], smoking (31%, 4–57%) and PA (7%, 2–11%). There was little evidence for pleiotropy, although smoking was bidirectionally associated with BMI and instruments were weak for PA. Conclusions: The effect of BMI on CRC risk is possibly partly mediated through plasma IGF1, whereas the attenuation of the BMI–CRC association by smoking and PA may reflect confounding and shared underlying mechanisms rather than mediation.

Published
2024
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40. The Use of Primary Care Big Data in Understanding the Pharmacoepidemiology of COVID-19: A Consensus Statement From the COVID-19 Primary Care Database Consortium

Author

Dambha-Miller, Hajira, Griffin, Simon J., Young, Duncan, Watkinson, Peter, Tan, Pui San, Clift, Ashley K., Payne, Rupert A., Coupland, Carol, Hopewell, Jemma C., Mant, Jonathan, Martin, Richard M., and Hippisley-Cox, Julia

Subjects
Medical research -- Methods, Medicine, Experimental -- Methods, Big data -- Usage -- Health aspects, Medical records -- Usage, Primary health care, Health, Science and technology
Abstract

The use of big data containing millions of primary care medical records provides an opportunity for rapid research to help inform patient care and policy decisions during the first and subsequent waves of the coronavirus disease 2019 (COVID-19) pandemic. Routinely collected primary care data have previously been used for national pandemic surveillance, quantifying associations between exposures and outcomes, identifying high risk populations, and examining the effects of interventions at scale, but there is no consensus on how to effectively conduct or report these data for COVID-19 research. A COVID-19 primary care database consortium was established in April 2020 and its researchers have ongoing COVID-19 projects in overlapping data sets with over 40 million primary care records in the United Kingdom that are variously linked to public health, secondary care, and vital status records. This consensus agreement is aimed at facilitating transparency and rigor in methodological approaches, and consistency in defining and reporting cases, exposures, confounders, stratification variables, and outcomes in relation to the pharmacoepidemiology of COVID-19. This will facilitate comparison, validation, and meta-analyses of research during and after the pandemic. Key words: big data; coronavirus; epidemiology; primary health care, INTRODUCTION Primary care big data refers to routinely collected anonymized general practitioner (GP) electronic health records that form large and complex longitudinal databases, often with hundreds of variables at an [...]

Published
2021
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41. The causal relevance of body mass index in different histological types of lung cancer: A Mendelian randomization study.

Author

Carreras-Torres, Robert, Haycock, Philip C, Relton, Caroline L, Martin, Richard M, Smith, George Davey, Kraft, Peter, Gao, Chi, Tworoger, Shelley, Le Marchand, Loïc, Wilkens, Lynne R, Park, Sungshim L, Haiman, Christopher, Field, John K, Davies, Michael, Marcus, Michael, Liu, Geoffrey, Caporaso, Neil E, Christiani, David C, Wei, Yongyue, Chen, Chu, Doherty, Jennifer A, Severi, Gianluca, Goodman, Gary E, Hung, Rayjean J, Amos, Christopher I, McKay, James, Johansson, Mattias, and Brennan, Paul

Subjects
Humans, Lung Neoplasms, Body Mass Index, Risk Factors, Case-Control Studies, Smoking, Female, Male, Mendelian Randomization Analysis
Abstract

Body mass index (BMI) is inversely associated with lung cancer risk in observational studies, even though it increases the risk of several other cancers, which could indicate confounding by tobacco smoking or reverse causality. We used the two-sample Mendelian randomization (MR) approach to circumvent these limitations of observational epidemiology by constructing a genetic instrument for BMI, based on results from the GIANT consortium, which was evaluated in relation to lung cancer risk using GWAS results on 16,572 lung cancer cases and 21,480 controls. Results were stratified by histological subtype, smoking status and sex. An increase of one standard deviation (SD) in BMI (4.65 Kg/m(2)) raised the risk for lung cancer overall (OR = 1.13; P = 0.10). This was driven by associations with squamous cell (SQ) carcinoma (OR = 1.45; P = 1.2 × 10(-3)) and small cell (SC) carcinoma (OR = 1.81; P = 0.01). An inverse trend was seen for adenocarcinoma (AD) (OR = 0.82; P = 0.06). In stratified analyses, a 1 SD increase in BMI was inversely associated with overall lung cancer in never smokers (OR = 0.50; P = 0.02). These results indicate that higher BMI may increase the risk of certain types of lung cancer, in particular SQ and SC carcinoma.

Published
2016

42. A Meta-analysis of Individual Participant Data Reveals an Association between Circulating Levels of IGF-I and Prostate Cancer Risk

Author

Travis, Ruth C, Appleby, Paul N, Martin, Richard M, Holly, Jeff MP, Albanes, Demetrius, Black, Amanda, Bueno-de-Mesquita, HB As, Chan, June M, Chen, Chu, Chirlaque, Maria-Dolores, Cook, Michael B, Deschasaux, Mélanie, Donovan, Jenny L, Ferrucci, Luigi, Galan, Pilar, Giles, Graham G, Giovannucci, Edward L, Gunter, Marc J, Habel, Laurel A, Hamdy, Freddie C, Helzlsouer, Kathy J, Hercberg, Serge, Hoover, Robert N, Janssen, Joseph AMJL, Kaaks, Rudolf, Kubo, Tatsuhiko, Le Marchand, Loic, Metter, E Jeffrey, Mikami, Kazuya, Morris, Joan K, Neal, David E, Neuhouser, Marian L, Ozasa, Kotaro, Palli, Domenico, Platz, Elizabeth A, Pollak, Michael, Price, Alison J, Roobol, Monique J, Schaefer, Catherine, Schenk, Jeannette M, Severi, Gianluca, Stampfer, Meir J, Stattin, Pär, Tamakoshi, Akiko, Tangen, Catherine M, Touvier, Mathilde, Wald, Nicholas J, Weiss, Noel S, Ziegler, Regina G, Key, Timothy J, and Allen, Naomi E

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Aging, Prostate Cancer, Cancer, Urologic Diseases, Aged, Humans, Insulin-Like Growth Factor I, Male, Middle Aged, Prostatic Neoplasms, Risk Factors, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

The role of insulin-like growth factors (IGF) in prostate cancer development is not fully understood. To investigate the association between circulating concentrations of IGFs (IGF-I, IGF-II, IGFBP-1, IGFBP-2, and IGFBP-3) and prostate cancer risk, we pooled individual participant data from 17 prospective and two cross-sectional studies, including up to 10,554 prostate cancer cases and 13,618 control participants. Conditional logistic regression was used to estimate the ORs for prostate cancer based on the study-specific fifth of each analyte. Overall, IGF-I, IGF-II, IGFBP-2, and IGFBP-3 concentrations were positively associated with prostate cancer risk (Ptrend all ≤ 0.005), and IGFBP-1 was inversely associated weakly with risk (Ptrend = 0.05). However, heterogeneity between the prospective and cross-sectional studies was evident (Pheterogeneity = 0.03), unless the analyses were restricted to prospective studies (with the exception of IGF-II, Pheterogeneity = 0.02). For prospective studies, the OR for men in the highest versus the lowest fifth of each analyte was 1.29 (95% confidence interval, 1.16-1.43) for IGF-I, 0.81 (0.68-0.96) for IGFBP-1, and 1.25 (1.12-1.40) for IGFBP-3. These associations did not differ significantly by time-to-diagnosis or tumor stage or grade. After mutual adjustment for each of the other analytes, only IGF-I remained associated with risk. Our collaborative study represents the largest pooled analysis of the relationship between prostate cancer risk and circulating concentrations of IGF-I, providing strong evidence that IGF-I is highly likely to be involved in prostate cancer development. Cancer Res; 76(8); 2288-300. ©2016 AACR.

Published
2016

44. Carotenoids, retinol, tocopherols, and prostate cancer risk: pooled analysis of 15 studies 1–3

Author

Key, Timothy J, Appleby, Paul N, Travis, Ruth C, Albanes, Demetrius, Alberg, Anthony J, Barricarte, Aurelio, Black, Amanda, Boeing, Heiner, Bueno-de-Mesquita, H Bas, Chan, June M, Chen, Chu, Cook, Michael B, Donovan, Jenny L, Galan, Pilar, Gilbert, Rebecca, Giles, Graham G, Giovannucci, Edward, Goodman, Gary E, Goodman, Phyllis J, Gunter, Marc J, Hamdy, Freddie C, Heliövaara, Markku, Helzlsouer, Kathy J, Henderson, Brian E, Hercberg, Serge, Hoffman-Bolton, Judy, Hoover, Robert N, Johansson, Mattias, Khaw, Kay-Tee, King, Irena B, Knekt, Paul, Kolonel, Laurence N, Le Marchand, Loic, Männistö, Satu, Martin, Richard M, Meyer, Haakon E, Mondul, Alison M, Moy, Kristin A, Neal, David E, Neuhouser, Marian L, Palli, Domenico, Platz, Elizabeth A, Pouchieu, Camille, Rissanen, Harri, Schenk, Jeannette M, Severi, Gianluca, Stampfer, Meir J, Tjønneland, Anne, Touvier, Mathilde, Trichopoulou, Antonia, Weinstein, Stephanie J, Ziegler, Regina G, Zhou, Cindy Ke, Allen, Naomi E, Biomarkers, Endogenous Hormones Nutritional, and Group, Prostate Cancer Collaborative

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Prevention, Urologic Diseases, Nutrition, Prostate Cancer, Cancer, Aging, Clinical Research, Adult, Biomarkers, Carotenoids, Case-Control Studies, Cohort Studies, Cross-Sectional Studies, Humans, Lycopene, Male, Meta-Analysis as Topic, Middle Aged, Neoplasm Grading, Neoplasm Staging, Observational Studies as Topic, Prospective Studies, Prostate, Prostatic Neoplasms, Risk Factors, Vitamin A, alpha-Tocopherol, prostate cancer, carotenoids, retinol, tocopherols, vitamin E, vitamin A, pooled analysis, nested case-control study, biomarkers, Endogenous Hormones Nutritional Biomarkers Prostate Cancer Collaborative Group, Engineering, Medical and Health Sciences, Nutrition & Dietetics, Clinical sciences, Nutrition and dietetics
Abstract

BackgroundIndividual studies have suggested that circulating carotenoids, retinol, or tocopherols may be associated with prostate cancer risk, but the studies have not been large enough to provide precise estimates of associations, particularly by stage and grade of disease.ObjectiveThe objective of this study was to conduct a pooled analysis of the associations of the concentrations of 7 carotenoids, retinol, α-tocopherol, and γ-tocopherol with risk of prostate cancer and to describe whether any associations differ by stage or grade of the disease or other factors.DesignPrincipal investigators of prospective studies provided individual participant data for prostate cancer cases and controls. Risk by study-specific fifths of each biomarker was estimated by using multivariable-adjusted conditional logistic regression in matched case-control sets.ResultsData were available for up to 11,239 cases (including 1654 advanced stage and 1741 aggressive) and 18,541 controls from 15 studies. Lycopene was not associated with overall risk of prostate cancer, but there was statistically significant heterogeneity by stage of disease, and the OR for aggressive disease for the highest compared with the lowest fifth of lycopene was 0.65 (95% CI: 0.46, 0.91; P-trend = 0.032). No other carotenoid was significantly associated with overall risk of prostate cancer or with risk of advanced-stage or aggressive disease. For retinol, the OR for the highest compared with the lowest fifth was 1.13 (95% CI: 1.04, 1.22; P-trend = 0.015). For α-tocopherol, the OR for the highest compared with the lowest fifth was 0.86 (95% CI: 0.78, 0.94; P-trend < 0.001), with significant heterogeneity by stage of disease; the OR for aggressive prostate cancer was 0.74 (95% CI: 0.59, 0.92; P-trend = 0.001). γ-Tocopherol was not associated with risk.ConclusionsOverall prostate cancer risk was positively associated with retinol and inversely associated with α-tocopherol, and risk of aggressive prostate cancer was inversely associated with lycopene and α-tocopherol. Whether these associations reflect causal relations is unclear.

Published
2015

48. Energy density in density functional theory: Application to crystalline defects and surfaces

Author

Yu, Min, Trinkle, Dallas R., and Martin, Richard M.

Subjects
Condensed Matter - Materials Science, Physics - Computational Physics
Abstract

We propose a method to decompose the total energy of a supercell containing defects into contributions of individual atoms, using the energy density formalism within density functional theory. The spatial energy density is unique up to a gauge transformation, and we show that unique atomic energies can be calculated by integrating over Bader and charge-neutral volumes for each atom. Numerically, we implement the energy density method in the framework of the Vienna ab initio simulation package (VASP) for both norm-conserving and ultrasoft pseudopotentials and the projector augmented wave method, and use a weighted integration algorithm to integrate the volumes. The surface energies and point defect energies can be calculated by integrating the energy density over the surface region and the defect region, respectively. We compute energies for several surfaces and defects: the (110) surface energy of GaAs, the mono-vacancy formation energies of Si, the (100) surface energy of Au, and the interstitial formation energy of O in the hexagonal close-packed Ti crystal. The surface and defect energies calculated using our method agree with size-converged calculations of the difference between the total energies of the system with and without the defect. Moreover, the convergence of the defect energies with size can be found from a single calculation., Comment: 25 pages, 6 figures

Published
2010
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49. Electrical conductivity of high-pressure liquid hydrogen by quantum Monte Carlo methods

Author

Lin, Fei, Morales, Miguel A., Delaney, Kris T., Pierleoni, Carlo, Martin, Richard M., and Ceperley, D. M.

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Materials Science
Abstract

We compute the electrical conductivity for liquid hydrogen at high pressure using quantum Monte Carlo. The method uses Coupled Electron-Ion Monte Carlo to generate configurations of liquid hydrogen. For each configuration correlated sampling of electrons is performed in order to calculate a set of lowest many-body eigenstates and current-current correlation functions of the system, which are summed over in the many-body Kubo formula to give AC electrical conductivity directly. The extrapolated DC conductivity at 3000 K for several densities shows a liquid semiconductor to liquid-metal transition at high pressure. Our results are in good agreement with shock-wave data., Comment: 4 pages, 5 figures

Published
2009
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50. Kidney Function and Risk of Renal Cell Carcinoma

Author

Alcala, Karine, primary, Zahed, Hana, additional, Cortez Cardoso Penha, Ricardo, additional, Alcala, Nicolas, additional, Robbins, Hilary A., additional, Smith-Byrne, Karl, additional, Martin, Richard M., additional, Muller, David C., additional, Brennan, Paul, additional, and Johansson, Mattias, additional

Published
2023
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