Genetics and Genomics of Eye Disease, 1st Edition – Advancing to Precision Medicine (Elsevier)
Editors: Xiaoyi Gao Paperback ISBN: 9780128162224 eBook ISBN: 9780128167274; Pages 383, Academic Press, Published Date: 13th September 2019
Medicine has made enormous strides in the 33 years since Tom Roderick, Victor McKusick and Frank Ruddle coined the term “genomics”, outlined in the inaugural editorial of a then new journal, entitled Genome, founded in 1987. Genomics is the scientific study of a genome, or genomes, and a genome “is the complete DNA sequence containing the entire genetic information of a gamete, an individual, a population or a species” (Huntington F. Willard). In this new book, Genetics and Genomics of Eye Disease: Advancing to Precision Medicine, several contributors here examine the latest genomics methods “for studying eye disease, including complex eye disorders associated with multiple genes. GWAS (genome-wide association study), WES (whole exome sequencing), WGS (whole genome sequencing), RNA-sequencing, and transcriptome analysis as employed in ocular genomics”.
In the current literature, there are an understanding of ~1,500 ocular diseases, underpinned by genetics and genomics, opening up an exciting new field which accelerate many developments in improving diagnosis, counselling and treatment. The current book covers 8 broad sections across 19 chapters, outlining the beginnings of early linkage analysis to whole genome sequencing with significant sections focusing on Mendelian and complex disorders. Genetic testing and “Big data” provide an important contribution as set out in a final chapter, entitled “Advancing to precision medicine through big data and artificial intelligence”. In it, the author explores the connections from genetics to artificial intelligence and machine learning expanding a rapidly new field. The chapter highlights the launch of the Precision Medicine Initiative (PMI), developed in the United States and announced in the speech in the State of the Union in January in 2015 by President Barack Obama. The initiative, among other goals, includes the use of improved healthcare outcomes, big data and artificial intelligence in order to use significant computing power and innovative tools to bring about new benefits for patient healthcare. The combination of genomics, electronic healthcare records (EHR) and imaging is now poised to propel “a new wave of novel discoveries” and this is due to revolutionise medicine over the coming years.
Interestingly in the penultimate chapter, the investment to develop many novel research tools currently wages an “arms race”, among national, international, public and private consortia to out-do technological outcomes: in 2013, the Genomics England initiative aimed to collect 100,000 genomes in the UK; in 2015, in the US, the PMI launched with a budget of $215M to recruit 1 million participants, while finally; in 2016, the Chinese government has launched a 15-year project to collect 100 million genomes by 2030, now with a staggering budget of $9.2BN. Considering that the first human genome project cost $3BN, the current project sponsored by the Chinese government may now suggests that each participant’s genome will cost just below $10, significantly lower than the cost of a McDonald’s meal. More importantly, how will all this play out for patients? What will be the exact benefit for patients? What are the politics relevant to genomic research, and how does “ethical, legal and social issues” will protect participants without a voice? It was recalled by the scientific community in the original human genome project that there had hoped to establish an “ELSI” (Ethical, Legal, and Social Implications) initiative with a 5% budget to protect ethical requirements however, only 0.6% ($18M) of the actual budget was allocated to it. With the world moving apace on mobile devices, social media and GDPR regulation, there needs to be thoughtful deliberation to ensure that research maintains a focus on the patient-centric goal. Regardless, the book summarises a significant combination of digital inputs – genomic data, fundus images, optical coherence tomography and others – aimed to synthesize enormous information over the coming decade, likely useful to both clinicians and researchers in the field of ocular medicine.