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3. Doublethink: simultaneous Bayesian-frequentist model-averaged hypothesis testing

Author

Fryer, Helen R., Arning, Nicolas, and Wilson, Daniel J.

Subjects
Statistics - Methodology, Mathematics - Statistics Theory
Abstract

Establishing the frequentist properties of Bayesian approaches widens their appeal and offers new understanding. In hypothesis testing, Bayesian model averaging addresses the problem that conclusions are sensitive to variable selection. But Bayesian false discovery rate (FDR) guarantees are contingent on prior assumptions that may be disputed. Here we show that Bayesian model-averaged hypothesis testing is a closed testing procedure that controls the frequentist familywise error rate (FWER) in the strong sense. The rate converges pointwise as the sample size grows and, under some conditions, uniformly. The `Doublethink' method computes simultaneous posterior odds and asymptotic p-values for model-averaged hypothesis testing. We explore its benefits, including post-hoc variable selection, and limitations, including finite-sample inflation, through a Mendelian randomization study and simulations comparing approaches like LASSO, stepwise regression, the Benjamini-Hochberg procedure and e-values., Comment: First full draft. 25 pages main text, 47 pages total. 9 figures, 2 tables

Published
2023

4. Contributors

Author

Brune, Jeffrey A and Wilson, Daniel J

Published
2013

5. Index

Author

Brune, Jeffrey A and Wilson, Daniel J

Published
2013

12. 1. Introduction

Author

Brune, Jeffrey A and Wilson, Daniel J

Published
2013

13. Acknowledgments

Author

Brune, Jeffrey A and Wilson, Daniel J

Published
2013

25. Machine learning to attribute the source of Campylobacter infections in the United States: A retrospective analysis of national surveillance data

Author

Pascoe, Ben, Futcher, Georgina, Pensar, Johan, Bayliss, Sion C., Mourkas, Evangelos, Calland, Jessica K., Hitchings, Matthew D., Joseph, Lavin A., Lane, Charlotte G., Greenlee, Tiffany, Arning, Nicolas, Wilson, Daniel J., Jolley, Keith A., Corander, Jukka, Maiden, Martin C.J., Parker, Craig T., Cooper, Kerry K., Rose, Erica B., Hiett, Kelli, Bruce, Beau B., and Sheppard, Samuel K.

Published
2024
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27. The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: a genotypic analysis

Author

Walker, Timothy M, Miotto, Paolo, Köser, Claudio U, Fowler, Philip W, Knaggs, Jeff, Iqbal, Zamin, Hunt, Martin, Chindelevitch, Leonid, Farhat, Maha R, Cirillo, Daniela Maria, Comas, Iñaki, Posey, James, Omar, Shaheed V, Peto, Timothy EA, Suresh, Anita, Uplekar, Swapna, Laurent, Sacha, Colman, Rebecca E, Nathanson, Carl-Michael, Zignol, Matteo, Walker, Ann Sarah, Crook, Derrick W, Ismail, Nazir, Rodwell, Timothy C, Consortium, the SeqTreat Consortium CRyPTIC, Walker, A Sarah, Steyn, Adrie JC, Lalvani, Ajit, Baulard, Alain, Christoffels, Alan, Mendoza-Ticona, Alberto, Trovato, Alberto, Skrahina, Alena, Lachapelle, Alexander S, Brankin, Alice, Piatek, Amy, Cruz, Ana Gibertoni, Koch, Anastasia, Cabibbe, Andrea Maurizio, Spitaleri, Andrea, Brandao, Angela P, Chaiprasert, Angkana, Barbova, Anna, Van Rie, Annelies, Ghodousi, Arash, Bainomugisa, Arnold, Mandal, Ayan, Roohi, Aysha, Javid, Babak, Zhu, Baoli, Letcher, Brice, Rodrigues, Camilla, Nimmo, Camus, NATHANSON, Carl-Michael, Duncan, Carla, Coulter, Christopher, Utpatel, Christian, Liu, Chunfa, Grazian, Clara, Kong, Clare, Wilson, Daniel J, Matias, Daniela, Jorgensen, Danielle, Zimenkov, Danila, Chetty, Darren, Moore, David AJ, Clifton, David A, van Soolingen, Dick, Liu, Dongxin, Kohlerschmidt, Donna, Barreira, Draurio, Ngcamu, Dumisani, Lazaro, Elias David Santos, Kelly, Ellis, Borroni, Emanuele, Roycroft, Emma, Andre, Emmanuel, Böttger, Erik C, Robinson, Esther, Menardo, Fabrizio, Mendes, Flavia F, Jamieson, Frances B, Coll, Francesc, Gao, George Fu, Kasule, George W, Rossolini, Gian Maria, Rodger, Gillian, Smith, E Grace, Meintjes, Graeme, Thwaites, Guy, Hoffmann, Harald, Albert, Heidi, Cox, Helen, Laurenson, Ian F, and Arandjelovic, Irena

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Microbiology, Clinical Sciences, Tuberculosis, Infectious Diseases, Rare Diseases, Antimicrobial Resistance, Orphan Drug, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Infection, Good Health and Well Being, Antitubercular Agents, Drug Resistance, Ethambutol, Microbial Sensitivity Tests, Mutation, Mycobacterium tuberculosis, World Health Organization, CRyPTIC Consortium, Seq&Treat Consortium, Immunology, Medical microbiology
Abstract

BackgroundMolecular diagnostics are considered the most promising route to achieving rapid, universal drug susceptibility testing for Mycobacterium tuberculosiscomplex (MTBC). We aimed to generate a WHO endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction.MethodsA candidate gene approach was used to identify mutations as associated with resistance, or consistent with susceptibility, for 13 WHO endorsed anti-tuberculosis drugs. 38,215 MTBC isolates with paired whole-genome sequencing and phenotypic drug susceptibility testing data were amassed from 45 countries. For each mutation, a contingency table of binary phenotypes and presence or absence of the mutation computed positive predictive value, and Fisher's exact tests generated odds ratios and Benjamini-Hochberg corrected p-values. Mutations were graded as Associated with Resistance if present in at least 5 isolates, if the odds ratio was >1 with a statistically significant corrected p-value, and if the lower bound of the 95% confidence interval on the positive predictive value for phenotypic resistance was >25%. A series of expert rules were applied for final confidence grading of each mutation.Findings15,667 associations were computed for 13,211 unique mutations linked to one or more drugs. 1,149/15,667 (7·3%) mutations were classified as associated with phenotypic resistance and 107/15,667 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was >80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were classified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs.InterpretationThis first WHO endorsed catalogue of molecular targets for MTBC drug susceptibility testing provides a global standard for resistance interpretation. Its existence should encourage the implementation of molecular diagnostics by National Tuberculosis Programmes.FundingUNITAID, Wellcome, MRC, BMGF.

Published
2022

28. The L\'evy combination test

Author

Wilson, Daniel J.

Subjects
Statistics - Methodology
Abstract

A novel class of methods for combining $p$-values to perform aggregate hypothesis tests has emerged that exploit the properties of heavy-tailed Stable distributions. These methods offer important practical advantages including robustness to dependence and better-than-Bonferroni scaleability, and they reveal theoretical connections between Bayesian and classical hypothesis tests. The harmonic mean $p$-value (HMP) procedure is based on the convergence of summed inverse $p$-values to the Landau distribution, while the Cauchy combination test (CCT) is based on the self-similarity of summed Cauchy-transformed $p$-values. The CCT has the advantage that it is analytic and exact. The HMP has the advantage that it emulates a model-averaged Bayes factor, is insensitive to $p$-values near 1, and offers multilevel testing via a closed testing procedure. Here I investigate whether other Stable combination tests can combine these benefits, and identify a new method, the L\'evy combination test (LCT). The LCT exploits the self-similarity of sums of L\'evy random variables transformed from $p$-values. Under arbitrary dependence, the LCT possesses better robustness than the CCT and HMP, with two-fold worst-case inflation at small significance thresholds. It controls the strong-sense familywise error rate through a multilevel test uniformly more powerful than Bonferroni. Simulations show that the LCT behaves like Simes' test in some respects, with power intermediate between the HMP and Bonferroni. The LCT represents an interesting and attractive addition to combined testing methods based on heavy-tailed distributions.

Published
2021

33. Bedaquiline and clofazimine resistance in Mycobacterium tuberculosis: an in-vitro and in-silico data analysis

Author

Barilar, Ivan, Battaglia, Simone, Borroni, Emanuele, Brandao, Angela Pires, Brankin, Alice, Cabibbe, Andrea Maurizio, Carter, Joshua, Cirillo, Daniela Maria, Claxton, Pauline, Clifton, David A, Cohen, Ted, Coronel, Jorge, Crook, Derrick W, Dreyer, Viola, Earle, Sarah G, Escuyer, Vincent, Ferrazoli, Lucilaine, Fowler, Philip W, Fu Gao, George, Gardy, Jennifer, Gharbia, Saheer, Ghisi, Kelen Teixeira, Ghodousi, Arash, Gibertoni Cruz, Ana Luíza, Grandjean, Louis, Grazian, Clara, Groenheit, Ramona, Guthrie, Jennifer L, He, Wencong, Hoffmann, Harald, Hoosdally, Sarah J, Hunt, Martin, Iqbal, Zamin, Ismail, Nazir Ahmed, Jarrett, Lisa, Joseph, Lavania, Jou, Ruwen, Kambli, Priti, Khot, Rukhsar, Knaggs, Jeff, Koch, Anastasia, Kohlerschmidt, Donna, Kouchaki, Samaneh, Lachapelle, Alexander S, Lalvani, Ajit, Grandjean Lapierre, Simon, Laurenson, Ian F, Letcher, Brice, Lin, Wan-Hsuan, Liu, Chunfa, Liu, Dongxin, Malone, Kerri M, Mandal, Ayan, Mansjö, Mikael, Matias, Daniela, Meintjes, Graeme, de Freitas Mendes, Flávia, Merker, Matthias, Mihalic, Marina, Millard, James, Miotto, Paolo, Mistry, Nerges, Moore, David, Musser, Kimberlee A, Ngcamu, Dumisani, Hoang, Ngoc Nhung, Niemann, Stefan, Nilgiriwala, Kayzad Soli, Nimmo, Camus, Okozi, Nana, Oliveira, Rosangela Siqueira, Omar, Shaheed Vally, Paton, Nicholas, Peto, Timothy EA, Watanabe Pinhata, Juliana Maira, Plesnik, Sara, Puyen, Zully M, Rabodoarivelo, Marie Sylvianne, Rakotosamimanana, Niaina, Rancoita, Paola MV, Rathod, Priti, Rodger, Gillian, Rodrigues, Camilla, Rodwell, Timothy C, Roohi, Eaysha, Santos-Lazaro, David, Shah, Sanchi, Kohl, Thomas Andreas, Smith, Grace, Solano, Walter, Spitaleri, Andrea, Supply, Philip, Surve, Utkarsha, Tahseen, Sabira, Thuong, Nguyen Thuy Thuong, Thwaites, Guy, Todt, Katharina, Trovato, Alberto, Utpatel, Christian, Van Rie, Annelies, Vijay, Srinivasan, Walker, Timothy M, Walker, Sarah A, Warren, Robin, Werngren, Jim, Wijkander, Maria, Wilkinson, Robert J, Wilson, Daniel J, Wintringer, Penelope, Yu, Xin Xiao, Yang, Yang, Zhao, Yanlin, Yao, Shen-Yuan, Zhu, Baoli, Sonnenkalb, Lindsay, Carter, Joshua James, Malone, Kerri Marie, and Fowler, Philip William

Published
2023
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35. p97 Inhibitors Possessing Antiviral Activity Against SARS-CoV-2 and Low Cytotoxicity.

Author

Ding, Rui, Edwards, Tiffany C., Goswami, Prithwish, Wilson, Daniel J., Dreis, Christine D., Ye, Yihong, Geraghty, Robert J., and Chen, Liqiang

Subjects
CYTOTOXINS, MOLECULAR docking, CORONAVIRUSES, SARS-CoV-2, ADENOSINE triphosphatase, ANTIVIRAL agents
Abstract

Background: p97 (also known as valosin-containing protein, VCP) is a member of the AAA+ ATPase family and is intimately associated with protein quality control and homeostasis regulation. Therefore, pharmaceutical inhibition of p97 has been actively pursued as an anticancer strategy. Recently, p97 has emerged as an important pro-viral host factor and p97 inhibitors are being evaluated as potential antiviral agents. Methods: We designed and synthesized novel p97 inhibitors based on the rearrangement of the central fused ring of our previously reported p97 inhibitors. These compounds were tested for inhibition of p97, cytotoxicity, and antiviral activity against SARS-CoV-2. Molecular docking was also performed on selected inhibitors to shed light on their binding modes. Results: Among these new p97 inhibitors, two compounds possess enhanced anti-p97 activity over their parent compounds. More significantly, these two inhibitors exhibit strong antiviral activity against SARS-CoV-2 at doses with no significant cytotoxicity. Molecular docking reveals no major change of the binding mode relative to that of their parent compounds, further supporting our design strategy. Conclusions: These compounds are structurally novel p97 inhibitors that display low toxicity and possess promising antiviral activity against SARS-CoV-2 and potentially other viruses. Further structural exploration is therefore justified and improved analogs will serve as useful tools for studying p97 as a promising host antiviral target. [ABSTRACT FROM AUTHOR]

Published
2025
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36. Population genomics of Escherichia coli in livestock-keeping households across a rapidly developing urban landscape

Author

Muloi, Dishon M., Wee, Bryan A., McClean, Deirdre M. H., Ward, Melissa J., Pankhurst, Louise, Phan, Hang, Ivens, Alasdair C., Kivali, Velma, Kiyong’a, Alice, Ndinda, Christine, Gitahi, Nduhiu, Ouko, Tom, Hassell, James M., Imboma, Titus, Akoko, James, Murungi, Maurice K., Njoroge, Samuel M., Muinde, Patrick, Nakamura, Yukiko, Alumasa, Lorren, Furmaga, Erin, Kaitho, Titus, Öhgren, Elin M., Amanya, Fredrick, Ogendo, Allan, Wilson, Daniel J., Bettridge, Judy M., Kiiru, John, Kyobutungi, Catherine, Tacoli, Cecila, Kang’ethe, Erastus K., Davila, Julio D., Kariuki, Samuel, Robinson, Timothy P., Rushton, Jonathan, Woolhouse, Mark E. J., and Fèvre, Eric M.

Published
2022
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37. Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing

Author

Allix-Béguec, Caroline, Arandjelovic, Irena, Bi, Lijun, Beckert, Patrick, Bonnet, Maryline, Bradley, Phelim, Cabibbe, Andrea M, Cancino-Muñoz, Irving, Caulfield, Mark J, Chaiprasert, Angkana, Cirillo, Daniela, Clifton, David, Comas, Iñaki, Crook, Derrick W, De Filippo, Maria Rosaria, de Neeling, Han, Diel, Roland, Drobniewski, Francis A, Faksri, Kiatichai, Farhat, Maha R, Fleming, Joy, Fowler, Philip, Fowler, Tom A, Gao, Qian, Gardy, Jennifer, Gascoyne-Binzi, Deborah, Cruz, Ana Gibertoni, Gil-Brusola, Ana, Golubchik, Tanya, Gonzalo, Ximena, Grandjean, Louis, He, Guangxue, Guthrie, Jennifer L, Hoosdally, Sarah, Hunt, Martin, Iqbal, Zamin, Ismail, Nazir, Johnston, James, Khanzada, Faisal Masood, Khor, Chiea Chuen, Kohl, Thomas A, Kong, Clare, Lipworth, Sam, Liu, Qingyun, Maphalala, Gugu, Martinez, Elena, Mathys, Vanessa, Merker, Matthias, Miotto, Paolo, Mistry, Nerges, Moore, David, Murray, Megan, Niemann, Stefan, Ong, Rick Twee-Hee, Peto, Tim EA, Posey, James E, Prammananan, Therdsak, Pym, Alexander, Rodrigues, Camilla, Rodrigues, Mabel, Rodwell, Timothy, Rossolini, Gian Maria, Padilla, Elisabeth Sánchez, Schito, Marco, Shen, Xin, Shendure, Jay, Sintchenko, Vitali, Sloutsky, Alex, Smith, E Grace, Snyder, Matthew, Soetaert, Karine, Starks, Angela M, Supply, Philip, Suriyapol, Prapat, Tahseen, Sabira, Tang, Patrick, Teo, Yik-Ying, Thuong, Thuong Nguyen Thuy, Thwaites, Guy, Tortoli, Enrico, Omar, Shaheed Vally, van Soolingen, Dick, Walker, A Sarah, Walker, Timothy M, Wilcox, Mark, Wilson, Daniel J, Wyllie, David, Yang, Yang, Zhang, Hongtai, Zhao, Yanlin, and Zhu, Baoli

Subjects
Genetics, Human Genome, Tuberculosis, Clinical Research, Patient Safety, Prevention, Rare Diseases, Infectious Diseases, Antimicrobial Resistance, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Infection, Good Health and Well Being, Antitubercular Agents, Drug Resistance, Bacterial, Ethambutol, Genome, Bacterial, Genotype, Humans, Isoniazid, Microbial Sensitivity Tests, Mutation, Mycobacterium tuberculosis, Phenotype, Pyrazinamide, Rifampin, Whole Genome Sequencing, CRyPTIC Consortium and the 100, 000 Genomes Project, Medical and Health Sciences, General & Internal Medicine
Abstract

BackgroundThe World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear.MethodsWe obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance.ResultsA total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted.ConclusionsGenotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.).

Published
2018

38. Sequential Monte Carlo with transformations

Author

Everitt, Richard G, Culliford, Richard, Medina-Aguayo, Felipe, and Wilson, Daniel J

Subjects
Statistics - Computation, Statistics - Applications, Statistics - Methodology
Abstract

This paper introduces methodology for performing Bayesian inference sequentially on a sequence of posteriors on spaces of different dimensions. We show how this may be achieved through the use of sequential Monte Carlo (SMC) samplers (Del Moral et al., 2006, 2007), making use of the full flexibility of this framework in order that the method is computationally efficient. In particular, we introduce the innovation of using deterministic transformations to move particles effectively between target distributions with different dimensions. This approach, combined with adaptive methods, yields an extremely flexible and general algorithm for Bayesian model comparison that is suitable for use in applications where the acceptance rate in reversible jump Markov chain Monte Carlo (RJMCMC) is low. We demonstrate this approach on the well-studied problem of model comparison for mixture models, and for the novel application of inferring coalescent trees sequentially, as data arrives.

Published
2016
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39. SCOTTI: Efficient Reconstruction of Transmission within Outbreaks with the Structured Coalescent

Author

De Maio, Nicola, Wu, Chieh-Hsi, and Wilson, Daniel J

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Exploiting pathogen genomes to reconstruct transmission represents a powerful tool in the fight against infectious disease. However, their interpretation rests on a number of simplifying assumptions that regularly ignore important complexities of real data, in particular within-host evolution and non-sampled patients. Here we propose a new approach to transmission inference called SCOTTI (Structured COalescent Transmission Tree Inference). This method is based on a statistical framework that models each host as a distinct population, and transmissions between hosts as migration events. Our computationally efficient implementation of this model enables the inference of host-to-host transmission while accommodating within-host evolution and non-sampled hosts. SCOTTI is distributed as an open source package for the phylogenetic software BEAST2. We show that SCOTTI can generally infer transmission events even in the presence of considerable within-host variation, can account for the uncertainty associated with the possible presence of non-sampled hosts, and can efficiently use data from multiple samples of the same host, although there is some reduction in accuracy when samples are collected very close to the infection time. We illustrate the features of our approach by investigating transmission from genetic and epidemiological data in a Foot and Mouth Disease Virus (FMDV) veterinary outbreak in England and a Klebsiella pneumoniae outbreak in a Nepali neonatal unit. Transmission histories inferred with SCOTTI will be important in devising effective measures to prevent and halt transmission.

Published
2016
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40. SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Author

Neale, Benjamin M., Daly, Mark, Ganna, Andrea, Stevens, Christine, Pathak, Gita A., Andrews, Shea J., Kanai, Masahiro, Cordioli, Mattia, Karjalainen, Juha, Polimanti, Renato, Pirinen, Matti, Harerimana, Nadia, Veerapen, Kumar, Wolford, Brooke, Nguyen, Huy, Solomonson, Matthew, Liao, Rachel G., Chwialkowska, Karolina, Trankiem, Amy, Balaconis, Mary K., Hayward, Caroline, Richmond, Anne, Campbell, Archie, Morris, Marcela, Fawns-Ritchie, Chloe, Glessner, Joseph T., Shaw, Douglas M., Chang, Xiao, Polikowski, Hannah, Lauren, Petty E., Chen, Hung-Hsin, Wanying, Zhu, Hakonarson, Hakon, Porteous, David J., Below, Jennifer, North, Kari, McCormick, Joseph B., Timmers, Paul R.H.J., Wilson, James F., Tenesa, Albert, D’Mellow, Kenton, Kerr, Shona M., Niemi, Mari E.K., Nkambul, Lindokuhle, Aprile von Hohenstaufen, Kathrin, Sobh, Ali, Eltoukhy, Madonna M., Yassen, Amr M., Hegazy, Mohamed A.F., Okasha, Kamal, Eid, Mohammed A., Moahmed, Hanteera S., Shahin, Doaa, El-Sherbiny, Yasser M., Elhadidy, Tamer A., Abd Elghafar, Mohamed S., El-Jawhari, Jehan J., Mohamed, Attia A.S., Elnagdy, Marwa H., Samir, Amr, Abdel-Aziz, Mahmoud, Khafaga, Walid T., El-Lawaty, Walaa M., Torky, Mohamed S., El-shanshory, Mohamed R., Batini, Chiara, Lee, Paul H., Shrine, Nick, Williams, Alexander T., Tobin, Martin D., Guyatt, Anna L., John, Catherine, Packer, Richard J., Ali, Altaf, Free, Robert C., Wang, Xueyang, Wain, Louise V., Hollox, Edward J., Venn, Laura D., Bee, Catherine E., Adams, Emma L., Niavarani, Ahmadreza, Sharififard, Bahareh, Aliannejad, Rasoul, Amirsavadkouhi, Ali, Naderpour, Zeinab, Tadi, Hengameh Ansari, Aleagha, Afshar Etemadi, Ahmadi, Saeideh, Mohseni Moghaddam, Seyed Behrooz, Adamsara, Alireza, Saeedi, Morteza, Abdollahi, Hamed, Hosseini, Abdolmajid, Chariyavilaskul, Pajaree, Chamnanphon, Monpat, Suttichet, Thitima B., Shotelersuk, Vorasuk, Pongpanich, Monnat, Phokaew, Chureerat, Chetruengchai, Wanna, Jantarabenjakul, Watsamon, Putchareon, Opass, Torvorapanit, Pattama, Puthanakit, Thanyawee, Suchartlikitwong, Pintip, Hirankarn, Nattiya, Nilaratanakul, Voraphoj, Sodsai, Pimpayao, Brumpton, Ben M., Hveem, Kristian, Willer, Cristen, Zhou, Wei, Rogne, Tormod, Solligard, Erik, Åsvold, Bjørn Olav, Abedalthagafi, Malak, Alaamery, Manal, Alqahtani, Saleh, Baraka, Dona, Al Harthi, Fawz, Alsolm, Ebtehal, Safieh, Leen Abu, Alowayn, Albandary M., Alqubaishi, Fatimah, Al Mutairi, Amal, Mangul, Serghei, Alshareef, Abdulraheem, Sawaji, Mona, Almutairi, Mansour, Aljawini, Nora, Albesher, Nour, Arabi, Yaseen M., Mahmoud, Ebrahim S., Khattab, Amin K., Halawani, Roaa T., Alahmadey, Ziab Z., Albakri, Jehad K., Felemban, Walaa A., Suliman, Bandar A., Hasanato, Rana, Al-Awdah, Laila, Alghamdi, Jahad, AlZahrani, Deema, AlJohani, Sameera, Al-Afghani, Hani, Alrashed, May, AlDhawi, Nouf, AlBardis, Hadeel, Alkwai, Sarah, Alswailm, Moneera, Almalki, Faisal, Albeladi, Maha, Almohammed, Iman, Barhoush, Eman, Albader, Anoud, Massadeh, Salam, AlMalik, Abdulaziz, Alotaibi, Sara, Alghamdi, Bader, Jung, Junghyun, Fawzy, Mohammad S., Lee, Yunsung, Magnus, Per, Trogstad, Lill-Iren S., Helgeland, Øyvind, Harris, Jennifer R., Mangino, Massimo, Spector, Tim D., Emma, Duncan, Smieszek, Sandra P., Przychodzen, Bartlomiej P., Polymeropoulos, Christos, Polymeropoulos, Vasilios, Polymeropoulos, Mihael H., Fernandez-Cadenas, Israel, Perez-Tur, Jordi, Llucià-Carol, Laia, Cullell, Natalia, Muiño, Elena, Cárcel-Márquez, Jara, DeDiego, Marta L., Iglesias, Lara Lloret, Planas, Anna M., Soriano, Alex, Rico, Veronica, Agüero, Daiana, Bedini, Josep L., Lozano, Francisco, Domingo, Carlos, Robles, Veronica, Ruiz-Jaén, Francisca, Márquez, Leonardo, Gomez, Juan, Coto, Eliecer, Albaiceta, Guillermo M., García-Clemente, Marta, Dalmau, David, Arranz, Maria J., Dietl, Beatriz, Serra-Llovich, Alex, Soler, Pere, Colobrán, Roger, Martín-Nalda, Andrea, Martínez, Alba Parra, Bernardo, David, Rojo, Silvia, Fiz-López, Aida, Arribas, Elisa, Cal-Sabater, Paloma de la, Segura, Tomás, González-Villa, Esther, Serrano-Heras, Gemma, Martí-Fàbregas, Joan, Jiménez-Xarrié, Elena, de Felipe Mimbrera, Alicia, Masjuan, Jaime, García-Madrona, Sebastian, Domínguez-Mayoral, Anna, Villalonga, Joan Montaner, Menéndez-Valladares, Paloma, Chasman, Daniel I., Buring, Julie E., Ridker, Paul M., Franco, Giulianini, Sesso, Howard D., Manson, JoAnn E., Glessner, Joseph R., Medina-Gomez, Carolina, Uitterlinden, Andre G., Ikram, M. Arfan, Kristiansson, Kati, Koskelainen, Sami, Perola, Markus, Donner, Kati, Kivinen, Katja, Palotie, Aarno, Ripatti, Samuli, Ruotsalainen, Sanni, Kaunisto, Mari, FinnGen, Nakanishi, Tomoko, Butler-Laporte, Guillaume, Forgetta, Vincenzo, Morrison, David R., Ghosh, Biswarup, Laurent, Laetitia, Belisle, Alexandre, Henry, Danielle, Abdullah, Tala, Adeleye, Olumide, Mamlouk, Noor, Kimchi, Nofar, Afrasiabi, Zaman, Branka Vulesevic, Nardin Rezk, Bouab, Meriem, Guzman, Charlotte, Petitjean, Louis, Tselios, Chris, Xue, Xiaoqing, Schurr, Erwin, Afilalo, Jonathan, Afilalo, Marc, Oliveira, Maureen, Brenner, Bluma, Lepage, Pierre, Ragoussis, Jiannis, Auld, Daniel, Brassard, Nathalie, Durand, Madeleine, Chassé, Michaël, Kaufmann, Daniel E., Lathrop, G. Mark, Mooser, Vincent, Richards, J. Brent, Li, Rui, Adra, Darin, Rahmouni, Souad, Georges, Michel, Moutschen, Michel, Misset, Benoit, Darcis, Gilles, Guiot, Julien, Guntz, Julien, Azarzar, Samira, Gofflot, Stéphanie, Beguin, Yves, Claassen, Sabine, Malaise, Olivier, Huynen, Pascale, Meuris, Christelle, Thys, Marie, Jacques, Jessica, Léonard, Philippe, Frippiat, Frederic, Giot, Jean-Baptiste, Sauvage, Anne-Sophie, Von Frenckell, Christian, Belhaj, Yasmine, Lambermont, Bernard, Pigazzini, Sara, Nkambule, Lindokuhle, Daya, Michelle, Shortt, Jonathan, Rafaels, Nicholas, Wicks, Stephen J., Crooks, Kristy, Barnes, Kathleen C., Gignoux, Christopher R., Chavan, Sameer, Laisk, Triin, Läll, Kristi, Lepamets, Maarja, Mägi, Reedik, Esko, Tõnu, Reimann, Ene, Milani, Lili, Alavere, Helene, Metsalu, Kristjan, Puusepp, Mairo, Metspalu, Andres, Naaber, Paul, Laane, Edward, Pesukova, Jaana, Peterson, Pärt, Kisand, Kai, Tabri, Jekaterina, Allos, Raili, Hensen, Kati, Starkopf, Joel, Ringmets, Inge, Tamm, Anu, Kallaste, Anne, Bochud, 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Kyle, Wilson, Daniel J., Armstrong, Jacob, Rudkin, Justine K., Band, Gavin, Earle, Sarah G., Lin, Shang-Kuan, Arning, Nicolas, Crook, Derrick W., Wyllie, David H., O’Connell, Anne Marie, Spencer, Chris C.A., Koelling, Nils, Caulfield, Mark J., Scott, Richard H., Fowler, Tom, Moutsianas, Loukas, Kousathanas, Athanasios, Pasko, Dorota, Walker, Susan, Rendon, Augusto, Stuckey, Alex, Odhams, Christopher A., Rhodes, Daniel, Chan, Georgia, Arumugam, Prabhu, Ball, Catherine A., Hong, Eurie L., Rand, Kristin, Girshick, Ahna, Guturu, Harendra, Baltzell, Asher Haug, Roberts, Genevieve, Park, Danny, Coignet, Marie, McCurdy, Shannon, Knight, Spencer, Partha, Raghavendran, Rhead, Brooke, Zhang, Miao, Berkowitz, Nathan, Gaddis, Michael, Noto, Keith, Ruiz, Luong, Pavlovic, Milos, Sloofman, Laura G., Charney, Alexander W., Beckmann, Noam D., Schadt, Eric E., Jordan, Daniel M., Thompson, Ryan C., Gettler, Kyle, Abul-Husn, Noura S., Ascolillo, Steven, Buxbaum, Joseph D., Chaudhary, Kumardeep, Cho, Judy H., Itan, Yuval, Kenny, Eimear E., Belbin, Gillian M., Sealfon, Stuart C., Sebra, Robert P., Salib, Irene, Collins, Brett L., Levy, Tess, Britvan, Bari, Keller, Katherine, Tang, Lara, Peruggia, Michael, Hiester, Liam L., Niblo, Kristi, Aksentijevich, Alexandra, Labkowsky, Alexander, Karp, Avromie, Zlatopolsky, Menachem, Preuss, Michael, Loos, Ruth J.F., Nadkarni, Girish N., Do, Ron, Hoggart, Clive, Choi, Sam, Underwood, Slayton J., O’Reilly, Paul, Huckins, Laura M., Zyndorf, Marissa, D’Antonio, Matteo, Nguyen, Jennifer P., Arthur, Timothy D., Matsui, Hiroko, D’Antonio-Chronowska, Agnieszka, and Frazer, Kelly A.

Published
2021
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42. Identifying lineage effects when controlling for population structure improves power in bacterial association studies

Author

Earle, Sarah G, Wu, Chieh-Hsi, Charlesworth, Jane, Stoesser, Nicole, Gordon, N Claire, Walker, Timothy M, Spencer, Chris C A, Iqbal, Zamin, Clifton, David A, Hopkins, Katie L, Woodford, Neil, Smith, E Grace, Ismail, Nazir, Llewelyn, Martin J, Peto, Tim E, Crook, Derrick W, McVean, Gil, Walker, A Sarah, and Wilson, Daniel J

Subjects
Quantitative Biology - Genomics
Abstract

Bacteria pose unique challenges for genome-wide association studies (GWAS) because of strong structuring into distinct strains and substantial linkage disequilibrium across the genome. While methods developed for human studies can correct for strain structure, this risks considerable loss- of-power because genetic differences between strains often contribute substantial phenotypic variability. Here we propose a new method that captures lineage-level associations even when locus-specific associations cannot be fine-mapped. We demonstrate its ability to detect genes and genetic variants underlying resistance to 17 antimicrobials in 3144 isolates from four taxonomically diverse clonal and recombining bacteria: Mycobacterium tuberculosis, Staphylococcus aureus, Escherichia coli and Klebsiella pneumoniae. Strong selection, recombination and penetrance confer high power to recover known antimicrobial resistance mechanisms, and reveal a candidate association between the outer membrane porin nmpC and cefazolin resistance in E. coli. Hence our method pinpoints locus-specific effects where possible, and boosts power by detecting lineage-level differences when fine-mapping is intractable.

Published
2015

43. Rapid host switching in generalist Campylobacter strains erodes the signal for tracing human infections

Author

Dearlove, Bethany L., Cody, Alison J., Pascoe, Ben, Méric, Guillaume, Wilson, Daniel J., and Sheppard, Samuel K.

Subjects
Quantitative Biology - Populations and Evolution, Quantitative Biology - Genomics
Abstract

Campylobacter jejuni and Campylobacter coli are the biggest causes of bacterial gastroenteritis in the developed world, with human infections typically arising from zoonotic transmission associated with infected meat, especially poultry. Because this organism is not thought to survive well outside of the gut, host associated populations are genetically isolated to varying degrees. Therefore the likely origin of most Campylobacter strains can be determined by host-associated variation in the genome. This is instructive for characterizing the source of human infection at the population level. However, some common strains appear to have broad host ranges, hindering source attribution. Whole genome sequencing has the potential to reveal fine-scale genetic structure associated with host specificity within each of these strains. We found that rates of zoonotic transmission among animal host species in ST-21, ST-45 and ST-828 clonal complexes were so high that the signal of host association is all but obliterated. We attributed 89% of clinical cases to a chicken source, 10% to cattle and 1% to pig. Our results reveal that common strains of C. jejuni and C. coli infectious to humans are adapted to a generalist lifestyle, permitting rapid transmission between different hosts. Furthermore, they show that the weak signal of host association within these complexes presents a challenge for pinpointing the source of clinical infections, underlining the view that whole genome sequencing, powerful though it is, cannot substitute for intensive sampling of suspected transmission reservoirs.

Published
2015

50. Improvement in Renal Function and Reduction in Serum Uric Acid with Intensive Statin Therapy in Older Patients: A Post Hoc Analysis of the SAGE Trial

Author

Deedwania, Prakash C, Stone, Peter H, Fayyad, Rana S, Laskey, Rachel E, and Wilson, Daniel J

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Cardiovascular, Kidney Disease, Atherosclerosis, Clinical Trials and Supportive Activities, Clinical Research, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Renal and urogenital, Aged, Aged, 80 and over, Atorvastatin, Cholesterol, LDL, Coronary Disease, Double-Blind Method, Dyslipidemias, Female, Glomerular Filtration Rate, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Kidney, Male, Pravastatin, Renal Insufficiency, Chronic, Uric Acid, Pharmacology and Pharmaceutical Sciences, Geriatrics, Clinical sciences, Pharmacology and pharmaceutical sciences
Abstract

BackgroundImprovement in renal function and decreases in serum uric acid (SUA) have been reported following prolonged high-intensity statin (HMG-CoA reductase inhibitor) therapy. This post hoc analysis of the SAGE trial examined the effect of intensive versus less intensive statin therapy on renal function, safety, and laboratory parameters, including SUA, in elderly coronary artery disease (CAD) patients (65-85 years) with or without chronic kidney disease (CKD).MethodsPatients were randomized to atorvastatin 80 mg/day or pravastatin 40 mg/day and treated for 12 months. Patients were stratified using Modification of Diet in Renal Disease (MDRD) estimated glomerular filtration rates (eGFRs) in CKD (eGFR 3 times the upper limit of normal occurred in 4.4% of atorvastatin- and 0.2% of pravastatin-treated patients.ConclusionIntensive management of dyslipidemia in older patients with stable coronary heart disease may have beneficial effects on renal function and SUA.

Published
2015

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