Bias in the reporting of sex and age in biomedical research on mouse models

eLife

Volumn 5, Issue MARCH2016, 2016, Pages

  Flórez Vargas, Oscar ^a   Brass, Andy ^a   Karystianis, George ^a   Bramhall, Michael ^a   Stevens, Robert ^a   Cruickshank, Sheena ^a   Nenadic, Goran ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AGE; ANIMAL EXPERIMENT; ANIMAL MODEL; ARTICLE; CARDIOVASCULAR DISEASE; CHRONIC OBSTRUCTIVE LUNG DISEASE; COMMUNICABLE DISEASE; DIABETES MELLITUS; EMBRYO; FEMALE; GENDER IDENTITY; INFORMATION PROCESSING; MALE; MEDICAL RESEARCH; MOUSE; NEUROLOGIC DISEASE; NONHUMAN; PHENOTYPE; AGE DISTRIBUTION; ANIMAL; DATA MINING; DISEASE MODEL; PROCEDURES; SELECTION BIAS; SEX RATIO;

AGE DISTRIBUTION; ANIMALS; BIOMEDICAL RESEARCH; DATA MINING; DISEASE MODELS, ANIMAL; MICE; SELECTION BIAS; SEX DISTRIBUTION;

EID: 84964293342     PISSN: None     EISSN: 2050084X     Source Type: Journal    
DOI: 10.7554/eLife.13615     Document Type: Article

References (50)

1. Ananiadou S, Kell DB, Tsujii J. 2006. Text mining and its potential applications in systems biology. Trends in Biotechnology 24:571–579. doi: 10.1016/j.tibtech.2006.10.002
2. Arbogast P, Glösmann M, Peichl L. 2013. Retinal cone photoreceptors of the deer mouse peromyscus maniculatus: development, topography, opsin expression and spectral tuning. PLoS ONE 8:e80910. doi: 10.1371/journal.pone.0080910
3. Arnold AP. 2010. Promoting the understanding of sex differences to enhance equity and excellence in biomedical science. Biology of Sex Differences 1:1. doi: 10.1186/2042-6410-1-1
4. Baker D, Lidster K, Sottomayor A, Amor S. 2014. Two years later: journals are not yet enforcing the ARRIVE guidelines on reporting standards for pre-clinical animal studies. PLoS Biology 12:e1001756. doi: 10.1371/journal.pbio.1001756
5. Bale TL, Epperson CN. 2015. Sex differences and stress across the lifespan. Nature Neuroscience 18: 1413–1420. doi: 10.1038/nn.4112
6. Beery AK, Zucker I. 2011. Sex bias in neuroscience and biomedical research. Neuroscience and Biobehavioral Reviews 35:565–572. doi: 10.1016/j.neubiorev.2010.07.002
7. Begley CG, Ellis LM. 2012. Drug development: Raise standards for preclinical cancer research. Nature 483:531–533. doi: 10.1038/483531a
8. Bramhall M, Flórez-Vargas O, Stevens R, Brass A, Cruickshank S. 2015. Quality of methods reporting in animal models of colitis. Inflammatory Bowel Diseases 21:1248–1259. doi: 10.1097/MIB.0000000000000369
9. Burden N, Chapman K, Sewell F, Robinson V. 2015. Pioneering better science through the 3Rs: an introduction to the national centre for the replacement, refinement, and reduction of animals in research (NC3Rs). Journal of the American Association for Laboratory Animal Science: JAALAS 54:198–208.
10. Case LK, Wall EH, Dragon JA, Saligrama N, Krementsov DN, Moussawi M, Zachary JF, Huber SA, Blankenhorn EP, Teuscher C. 2013. The Y chromosome as a regulatory element shaping immune cell transcriptomes and susceptibility to autoimmune disease. Genome Research 23:1474–1485. doi: 10.1101/gr.156703.113
11. Clayton JA, Collins FS. 2014. Policy: NIH to balance sex in cell and animal studies. Nature 509:282–283. doi: 10.1038/509282a
12. Clutton-Brock TH, Isvaran K. 2007. Sex differences in ageing in natural populations of vertebrates. Proceedings of the Royal Society B: Biological Sciences 274:3097–3104. doi: 10.1098/rspb.2007.1138
13. Cohen AM, Hersh WR. 2005. A survey of current work in biomedical text mining. Briefings in Bioinformatics 6:57–71. doi: 10.1093/bib/6.1.57
14. Collins FS, Tabak LA. 2014. Policy: NIH plans to enhance reproducibility. Nature 505:612–613. doi:10.1038/505612a
15. Cunningham H, Tablan V, Roberts A, Bontcheva K. 2013. Getting more out of biomedical documents with GATE’s full lifecycle open source text analytics. PLoS Computational Biology 9:e1002854. doi: 10.1371/journal.pcbi.1002854
16. Dehlendorff C, Andersen KK, Olsen TS. 2015. Sex disparities in stroke: women have more severe strokes but better survival than men. Journal of the American Heart Association 4. doi: 10.1161/JAHA.115.001967
17. Diedrich M, Tadic J, Mao L, Wacker MA, Nebrich G, Hetzer R, Regitz-Zagrosek V, Klose J. 2007. Heart protein expression related to age and sex in mice and humans. International Journal of Molecular Medicine 20:865–874. doi: 10.3892/ijmm.20.6.865
18. Fleuren WW, Alkema W. 2015. Application of text mining in the biomedical domain. Methods 74:97–106. doi: 10.1016/j.ymeth.2015.01.015
19. Flórez-Vargas O, Bramhall M, Noyes H, Cruickshank S, Stevens R, Brass A. 2014. The quality of methods reporting in parasitology experiments. PloS One 9: e101131. doi: 10.1371/journal.pone.0101131
20. Freedman LP, Cockburn IM, Simcoe TS. 2015. The Economics of Reproducibility in Preclinical Research. PLoS Biology 13:e1002165. doi: 10.1371/journal.pbio.1002165
21. Gemmell NJ, Metcalf VJ, Allendorf FW. 2004. Mother’s curse: the effect of mtDNA on individual fitness and population viability. Trends in Ecology & Evolution 19:238–244. doi: 10.1016/j.tree.2004.02.002
22. Gilks WP, Abbott JK, Morrow EH. 2014. Sex differences in disease genetics: evidence, evolution, and detection. Trends in Genetics 30:453–463. doi:10.1016/j.tig.2014.08.006
23. Herlyn M, Fukunaga-Kalabis M. 2010. What is a good model for melanoma? Journal of Investigative Dermatology 130:911–912. doi: 10.1038/jid.2009.441
24. Hotho A, Numberger A, Paab G. 2005. A brief survey of text mining. LDV Forum–GLDV Journal for Computational Linguistics and Language Technology 20:19–62.
25. ICMJE. 2013. Uniform Requirements for Manuscripts Submitted to Biomedical Journals: Writing and Editing for Biomedical Publications. http://www.icmje.org/icmje-recommendations.pdf.
26. Ji H, Zheng W, Wu X, Liu J, Ecelbarger CM, Watkins R, Arnold AP, Sandberg K. 2010. Sex chromosome effects unmasked in angiotensin II-induced hypertension. Hypertension 55:1275–1282. doi: 10.1161/HYPERTENSIONAHA.109.144949
27. Kilkenny C, Browne WJ, Cuthill IC, Emerson M, Altman DG. 2010. Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. PLoS Biology 8:e1000412. doi: 10.1371/journal.pbio.1000412
28. Kilkenny C, Parsons N, Kadyszewski E, Festing MF, Cuthill IC, Fry D, Hutton J, Altman DG. 2009. Survey of the quality of experimental design, statistical analysis and reporting of research using animals. PloS One 4:e7824. doi: 10.1371/journal.pone.0007824
29. Landis SC, Amara SG, Asadullah K, Austin CP, Blumenstein R, Bradley EW, Crystal RG, Darnell RB, Ferrante RJ, Fillit H, et al. 2012. A call for transparent reporting to optimize the predictive value of preclinical research. Nature 490:187–191. doi: 10.1038/nature11556
30. Li J, Kannan M, Trivett AL, Liao H, Wu X, Akagi K, Symer DE. 2014. An antisense promoter in mouse L1 retrotransposon open reading frame-1 initiates expression of diverse fusion transcripts and limits retrotransposition. Nucleic Acids Research 42:4546–4562. doi: 10.1093/nar/gku091
31. Lin CQ, Dempsey PJ, Coffey RJ, Bissell MJ. 1995. Extracellular matrix regulates whey acidic protein gene expression by suppression of TGF-alpha in mouse mammary epithelial cells: studies in culture and in transgenic mice. Journal of Cell Biology 129: 1115–1126.
32. Maklakov AA, Lummaa V. 2013. Evolution of sex differences in lifespan and aging: causes and constraints. BioEssays 35:717–724. doi: 10.1002/bies.201300021
33. McCullough LD, de Vries GJ, Miller VM, Becker JB, Sandberg K, McCarthy MM. 2014. NIH initiative to balance sex of animals in preclinical studies: generative questions to guide policy, implementation, and metrics. Biology of Sex Differences 5:15. doi: 10.1186/s13293-014-0015-5
34. Meystre MS, Savova KG, Kipper-Schuler CK, Hurdle FJ. 2008. Extracting information from textual documents in the electronic health record: a review of recent research. Methods of Information in Medicine 47:128–144.
35. Moher D, Simera I, Schulz KF, Hoey J, Altman DG. 2008. Helping editors, peer reviewers and authors improve the clarity, completeness and transparency of reporting health research. BMC Medicine 6:13. doi: 10.1186/1741-7015-6-13
36. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, de Ferranti S, Després JP, Fullerton HJ, Howard VJ, et al.American Heart Association Statistics Committee and Stroke Statistics Subcommittee2015. Heart disease and stroke statistics–2015 update: a report from the American Heart Association. Circulation 131:e29–322. doi: 10.1161/CIR.0000000000000152
37. Nature. 2013. Reporting Checklist for Life Sciences Articles. http://www.nature.com/authors/policies/checklist.pdf.
38. Nguyen DK, Disteche CM. 2006. Dosage compensation of the active X chromosome in mammals. Nature Genetics 38:47–53. doi: 10.1038/ng1705
39. Ober C, Loisel DA, Gilad Y. 2008. Sex-specific genetic architecture of human disease. Nature Reviews Genetics 9:911–922. doi: 10.1038/nrg2415
40. Pennell LM, Galligan CL, Fish EN. 2012. Sex affects immunity. Journal of Autoimmunity 38:J282–291. doi: 10.1016/j.jaut.2011.11.013
41. Perrin S. 2014. Preclinical research: Make mouse studies work. Nature 507:423–425. doi: 10.1038/507423a
42. Prinz F, Schlange T, Asadullah K. 2011. Believe it or not: how much can we rely on published data on potential drug targets? Nature Reviews Drug Discovery 10:712–713. doi: 10.1038/nrd3439-c1
43. Ross AP, Mansilla MA, Choe Y, Helminski S, Sturm R, Maute RL, May SR, Wójcicki P, Mostowska A, Davidson B, et al. 2013. A mutation in mouse Pak1ip1 causes orofacial clefting while human PAK1IP1 maps to 6p24 translocation breaking points associated with orofacial clefting. PLoS ONE 8:e69333. doi: 10.1371/journal.pone.0069333
44. Settles B. 2005. ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text. Bioinformatics 21:3191–3192. doi: 10.1093/bioinformatics/bti475
45. Taylor K, Vallejo-Giraldo C, Schaible NS, Zakeri R, Miller VM. 2011. Reporting of sex as a variable in cardiovascular studies using cultured cells. Biology of Sex Differences 2:11. doi: 10.1186/2042-6410-2-11
46. van der Worp HB, Howells DW, Sena ES, Porritt MJ, Rewell S, O’Collins V, Macleod MR. 2010. Can animal models of disease reliably inform human studies? PLoS Medicine 7:e1000245. doi: 10.1371/journal.pmed.1000245
47. van der Worp HB, Macleod MR. 2011. Preclinical studies of human disease: time to take methodological quality seriously. Journal of Molecular and Cellular Cardiology 51:449–450. doi:10.1016/j.yjmcc.2011.04.008
48. WHO. 2014. The top 10 causes of death. Accessed on 15 Jun 2015 available from: http://www.who.int/mediacentre/factsheets/fs310/en/.
49. Wizemann TM, Pardue ML. 2001. Exploring the Biological Contributions to Human Health: Does Sex Matter?. Washington DC: National Academy Press.
50. Yue F, Cheng Y, Breschi A, Vierstra J, Wu W, Ryba T, Sandstrom R, Ma Z, Davis C, Pope BD, et al.Mouse ENCODE Consortium2014. A comparative encyclopedia of DNA elements in the mouse genome. Nature 515:355–364. doi: 10.1038/nature13992