Practitioners, teamwork, and new information on animal diseases

In 2012 the Morris Animal Foundation launched a $ 32-million longitudinal study on over 3000 golden retriever dogs to collect data on various areas of animal health and disease including behavior, disease, dental issues, diet, reproduction, and physical examinations (1). The recruitment of dog owners for this Golden Retriever Lifetime Study is complete but veterinarians are still being recruited. Veterinarians perform routine annual examinations for each enrolled dog, collect samples and send them to a designated laboratory for analysis, and provide care during health events. The plan is to continue the study for 14 years to determine how nutrition, environment, lifestyle and genes act as risk factors for canine diseases. The Morris Animal Foundation is partnering with the V Foundation for Cancer Research in order to add genomic sequencing data next year. The database, called Data Commons, and biological samples are available to veterinary and human medical researchers. Michael Cinkosky, vice president of Information Systems noted that “Many large datasets and biological sample collections exist for human medicine and have aided in the discovery of new diagnostics, treatments, and even cures for a myriad of diseases. …. Morris Animal Foundation, the Golden Retriever Lifetime Study, and now the Data Commons, are here to improve the discovery process for animals, too.”

Other organizations, such as Banfield Pet Hospital, are also analyzing large data sets of animal diseases to advance knowledge in animal health. In releasing its 2019 State of Pet Health Report, which explores trends in osteoarthritis in pets, the company noted that the report was based on medical data from over 2.5 million dogs and 500 000 cats in its hospitals in 2018.

Many researchers who lack access to large databases needed to address a specific problem establish collaborations, which have several advantages in addition to database access. Djukanović et al (2) recently discussed the reasons scientists collaborate among themselves and with various partners. They concluded that the primary reason was that “scientists come together to undertake better science.” They note that studies have shown that research projects in biomedical sciences that are conducted through interdisciplinary and international collaborative groups are of significantly higher quality and more impactful than research carried out by a single discipline or center. A second reason is that pooling of expertise, facilities, patients, and financial resources allows larger and more complex projects to be carried out. A good example is in the field of cancer research. Several veterinary schools have set up cancer research centers that involve faculty from several departments in the university, faculty from medical schools, and faculty from several countries. Other complex problems are addressed by collaboration among personnel from universities, government, and industry, often involving researchers from different disciplines, who bring different perspectives, experience, and expertise to bear on the problem at the design and interpretation stages.

Having too few patients for sound conclusions to be drawn is one of the most frequent shortcomings we recognize in articles that are submitted to our journal. Establishing teams of researchers from several institutions can sometimes solve this problem, although heterogeneity in protocols and animal populations can be a complication in such studies.

One of the consequences of more collaboration in scientific research is that the average number of authors per paper keeps on increasing. Nature Index (3) recently reported that the number of papers with more than 1000 authors has soared from 0 to 100 over the past 5 years. These papers are mostly in the physical sciences where the average number of authors on a paper increased from 9 to 39 between 2012 and 2016. In 2016 there was 1 paper with 5000 authors. The average number in the biomedical sciences is around 6. Current difficulties in obtaining reviewers will increase as more of the experts in a field come together to do research, leaving few to evaluate the research.

Team projects can be challenging to manage: who to include; ensuring clear responsibility and acknowledging contributions; supervision of the team; presentation and interpretation of study findings; authorships — who and in what order. However, the benefits are enormous and the returns in efficiency are usually worth the effort. The prospects of new and important information from analyses of large data sets are exciting.