The genomes of the rhesus macaque of China (Macaca mulatta lasiota) (CR) and the cynomolgus macaque (Macaca fascicularis) (CE) were recently published in Nature Biotechnology. The genomes were compared with the Indian rhesus macaque (IR). The scientists: “found there were over 20 million single-nucleotide differences and 740,827 indel events in the three macaque species, which will provide abundant genetic heterogeneity for use in future biomedical analysis and application. It is important to note that a large number of genetic differences were shared between at least two macaques. The divergence rate of CE/IR (40%) was higher than that of CR/IR (31%) and CR/CE (34%). . . . “We are excited about all the findings in the study, especially those with great biomedical interests. For instance, macaques have protective immunity against human retrovirus, HIV-1 virus, but are easily infected by SIV virus. TRIM5α protein in macaques can lead to anti-infection of HIV-1, whereas TRIM5α in human does not have the same effect. Variations of TRIM5, a gene encoding TRIM5α were observed at different frequency in the macaque population, and this may be the key hereditary factor for the ability to protect against HIV-1 infection among individual macaques.” added Dr. Zhang.”1 The article is published in Nature Biotechnology.2
What the above is saying is that by studying the genetic makeup of monkeys and then comparing it to humans, we can find the differences that are responsible for disease resistance and apply this to humans. On the face of it, that all sounds reasonable. But that is not how evolution works. The same gene may perform different functions in various species so assigning a function to that gene based on studies in another species can be misleading. There are many more reasons why the same genome may react differently in terms of disease susceptibility. We see this when monozygotic twins respond differently in terms of one contracting schizophrenia while the other does not. When one compares species, the differences increase exponentially and extrapolating the genetic cause for a specific effect becomes almost impossible. Especially for diseases that are multifactorial—a lot of genes are involved and a lot of environmental factors can contribute to the disease.
Sequencing the genomes of other species does provide data for comparative science, which is interesting science, but this is not likely to lead to treatments for humans for all the reasons I routinely explain in this blog.
Comparing human genetic makeups, on the other hand, does provide data that can be used. Researchers have found that the increased risk of kidney disease in African-Americans can be almost entirely explained by the presence of two copies of the APOL1 gene. According to a press release from NIH: “ ‘These findings explain nearly all of the excess risk of non-diabetic kidney failure in African-Americans. African-Americans with no variant or one variant have about the same risk of end-stage kidney disease as their white counterparts,’ Winkler [of the National Cancer Institute] said. ‘People with two APOL1 variants have greatly increased risk of particular kidney diseases – by 17- to 30-fold.’ ”
The press release continues by stating: “These [genetic] variants appear to have evolved about 5,000 years ago in some regions of sub-Saharan Africa to protect against trypanosomal infection, also called African sleeping sickness, a degenerative and potentially fatal disease affecting tens of thousands of people in those regions. People from other continents do not have the APOL1 variants.”
The article can be found in the Journal of the American Society of Nephrology.3
Human-based research has also allowed scientists to link variants of the dopamine transporter (DAT) and dopamine receptor D4 (DRD4) genes to response to the medication methylphenidate, used for ADHD. The article can be found in theJournal of the American Academy of Child and Adolescent Psychiatry.4
The use of animal models is one reason the pipeline is almost dry in the pharmaceutical industry. For example, Decision Resources, an advisory firm for pharmaceutical issues, released a statement saying “no novel drug therapies are forecasted to launch for the treatment of acute ischemic stroke (AIS) through 2020.” Drugs for stroke have historically been developed using animal models and have essentially a 100% fail rate in humans. Numerous science writers and scientists have commented the dearth of new drugs in the pipeline and all have agreed that the lack of predictive ability of animal models is a big reason for this. For example, according to Nature News, Patrick Vallance, head of medicines discovery and development for GlaxoSmithKline attributed the difficulty developing new drugs for diseases of the brain to: “unrealistic animal models, unpredictable results from early trials and difficulties in diagnosing and allocating patients to trials.”5
Surgical procedures are also subject to the same problems associated with interspecies dissimilarities. Extracranial-intracranial bypass was successful in animals but continues to be unsuccessful in humans. It actually causes more harm than good.6-9
Moreover, the animal studies themselves are being performed in way that can best be described a shoddy. Malcolm Macleod: "This is the golden age of medical research. Around the world, scientists are spending more money, writing more papers and building more shiny institutes. . . . Take experiments that use animals to model human diseases. Empirical study of the quality of these experiments is an emerging field, but it does suggest that all is not well. The most reliable animal studies are those that: use randomization to eliminate systematic differences between treatment groups; induce the condition under investigation without knowledge of whether or not the animal will get the drug of interest; and assess the outcome in a blinded fashion. Studies that do not report these measures are much more likely to overstate the efficacy of interventions. Unfortunately, at best one in three publications follows these basic protections against bias."10
The only ethical solution to this problem (ethical for the humans that are patients) is to fund research that results in treatments for disease as opposed to research that does not.
Finally, just FYI, an interview I did with Animal Voices of Toronto is available here.
1. BGI Europe. Genomic Sequence and Comparison of Two Macaques Species Reveal New Insights into Biomedical Research. 2011; http://www.bgisequence.com/eu/newsandevents/news/genomic-sequence-and-comparison-of-two-macaques-species-reveal-n. Accessed October 18, 2011.
2. Yan G, Zhang G, Fang X, et al. Genome sequencing and comparison of two nonhuman primate animal models, the cynomolgus and Chinese rhesus macaques. Nat Biotech. 2011;advance online publication.
3. Kopp JB, Nelson GW, Sampath K, et al. APOL1 Genetic Variants in Focal Segmental Glomerulosclerosis and HIV-Associated Nephropathy. Journal of the American Society of Nephrology. October 13, 2011 2011.
4. Froehlich TE, Epstein JN, Nick TG, et al. Pharmacogenetic Predictors of Methylphenidate Dose-Response in Attention-Deficit/Hyperactivity Disorder. Journal of the American Academy of Child and Adolescent Psychiatry. 2011;50(11):1129-1139.e1122.
5. Smith K. Trillion-dollar brain drain. Nature. Oct 6 2011;478(7367):15.
6. Broderick JP. The Challenges of Intracranial Revascularization for Stroke Prevention. New England Journal of Medicine. 2011;365(11):1054-1055.
7. Chimowitz MI, Lynn MJ, Derdeyn CP, et al. Stenting versus aggressive medical therapy for intracranial arterial stenosis. The New England journal of medicine. Sep 15 2011;365(11):993-1003.
8. The EC/IC Bypass Study Group. Failure of extracranial-intracranial arterial bypass to reduce the risk of ischemic stroke. Results of an international randomized trial. The EC/IC Bypass Study Group. N Engl J Med. Nov 7 1985;313(19):1191-1200.
9. Powers W, Clarke W, Grubb R, Videen T, Adams H, Derdeyn C. Results of the Carotid Occlusion Surgery Study (COSS). International Stroke Conference. Los Angeles2011.
10. Macleod M. Why animal research needs to improve. Nature. Sep 29 2011;477(7366):511.