Medicine and Evolution
Robert C. Brunham MD, University of British Columbia, Vancouver, Canada
Robert C. Brunham MD, University of British Columbia, Vancouver, Canada
Introduction
In 2022 the Nobel Prize in Physiology or Medicine was awarded to Svante Paabo for his discoveries regarding human evolution. By sequencing the ancient genomes of Neanderthals and related archaic hominids and comparing those sequences to modern humans, Paabo and co-workers defined the recent evolutionary history of humanity. Their data illustrated how hominid species interbred and retained gene variants that facilitated modern human adaptations to novel environments throughout Eurasia. This work provided yet another line of evidence of the importance of evolution in shaping human biology. Genomics is the enabling technology that has moved evolution to the forefront of medicine.
Despite these achievements, medicine has yet to fully embrace evolution. In essence, medicine today is much like biology before Darwin, a field rich in observation and data without a unified conceptual foundation. However, all human diseases, whether caused by the physical, biological or social environment, through defects in physiology or by mental events, operate through biological processes. These biological processes have their origin in evolution through natural selection so evolution must be the foundation on which medicine rests. We propose that medicine, like biology, can make sense through the explicit adoption of evolutionary thinking and that the synergistic thinking of medicine and evolution will improve the quality of medical care.
Why has medicine been slow to adopt evolutionary thinking?
Both medicine and biology had their origins 2500 years ago in ancient Greece, with Hippocrates shaping medicine and Aristotle shaping biology. However, over the subsequent millennia, the two fields developed as separate schools of thought. For example, after Darwin established the unifying principle of biology as evolution by natural selection, this idea did not immediately transfer to medicine. Humans were often considered as exceptional examples of life to which biological processes do not apply.
There were attempts to introduce evolutionary thinking into medicine but the early movements of social Darwinism and eugenics were unacceptable to many physicians. This changed somewhat when JBS Haldane argued that infectious diseases were likely a major cause of genetic variation among humans and Allison established that malaria was the selective factor for the high prevalence of sickle cell trait in African and descendent populations. The rise of antimicrobial resistance is another example of how the action of evolution in medicine was made apparent, but which also failed to transform thinking because many thought the evolutionary phenomena of drug resistance was limited to microbes. Medicine has thus remained estranged from evolution.
A major factor for this estrangement is that medical theory and evolutionary theory, despite being biologically based, have had distinct areas of focus (Table 1), which may have kept the two fields apart. Major differences include medicine’s focus on the individual, with variability in individual phenotype limited to a normal range and where mechanism as the proximate cause of disease is important as the target for therapeutic intervention. Evolution, on the other hand, focuses on ultimate causes, where variations within populations are targeted by selective forces and lead to processes of adaptation. In addition, medicine focuses on overcoming disease to achieve health while evolution focuses on maximizing reproductive fitness where less adapted forms are eliminated. Other less important differences include medicine’s focus on development during embryogenesis (ontogeny) and the life cycle and use of randomized clinical trials for experimentation. Evolution’s focus, however, is on evolutionary descent (phylogeny), which is explored by mathematical models or through long-term observation of microbial reproduction in defined environments. Despite these differences, we assert that there is a strong basis for synergy between medical and evolutionary thinking. A modern synthesis uniting these two lines of thinking is already underpinning the thinking and action of the modern physician.
In this essay we provide examples from amongst many, in which evolutionary thinking is advancing medical practice. We consider the advantages that accrue by explicitly incorporating evolutionary thinking into medical practice and argue that it is time for a modern synthesis of medicine and evolution to begin in undergraduate medical education.
Table 1: Differences in Core Concepts of Medicine and Evolution
Category Medicine Evolution
Unit of analysis Individual Population
Constancy of type Normality Variation
Time-scale of change Ontogeny Phylogeny
Process of change Mechanism Adaptation
Result of change Disease Phenotypic change
Optimization of change Health Reproductive fitness
Mathematical methods Randomized clinical trials Mathematical models
Evolutionary Thinking in Medicine
Emerging and Pandemic Diseases
Emerging and pandemic diseases have been a constant feature of human history since the origins of agriculture and civilization because they concentrated the density of human populations to critical thresholds that allowed the propagation of pathogen spread. Movements of people facilitated the spread of disease. Rapid global movement of people, faster than the incubation period of an infectious disease, fuels pandemics. COVID-19 is the first pandemic of the genomic era, the era in which the genome sequences of a pathogen and the host population are routinely available. With intense focus and the use of a wide variety of state-of-the-art genomic tools, the evolution of COVID-19 is rapidly being characterized. No disease has been better understood at an evolutionary level than COVID-19.
In today’s world, RNA viruses like SARS-CoV-2, the causative agent of COVID-19, which spread via the respiratory route, appear to have the highest propensity for community-wide spread. Air travel facilitates the globalization of pathogen spread to produce pandemics in weeks to months, as was witnessed with COVID-19.
Pandemics automatically cause physicians to shift their thinking from the individual to the population. Physicians became adept at using the concepts of evolutionary population biology to limit the spread of COVID-19 and this likely contributed to success in curbing the pandemic. These concepts include consideration of both asymptomatic and symptomatic spread, physical distancing, avoiding poorly ventilated indoor airspaces and herd immunity, among others. Mathematical models of transmission guided the thinking of physicians about the local and global behavior of the pandemic and where to target their efforts.
Evolution provides explanations for how ‘new’ infectious diseases emerge. Most new infections of humans that have pandemic potential that emerge from nature share common traits. They often exist in social host species where horizontal spread readily occurs with or without symptomatic disease. The host species is biochemically similar to humans. Bats and nonhuman primates are two examples of hosts that frequently give rise to emerging infectious diseases. In human history the domesticated animals with which humans closely lived were once the common source for new emerging diseases. Now most emerging infectious are spill-over events from nature. There are often ecological changes at work that bring the reservoir species and human populations together to enable cross-species transfer, such as batching and eating “wild meat” and wet animal markets. The pathogen is often an RNA virus because their higher mutation rates allow rapid genetic adaptation to the human host. The effective reproductive number of the emerging pathogen in the human population at the time of spill-over is often slightly below one. Multiple cross-over events occur before one lineage of the pathogen establishes productive transmission chains [original reproduction number >1] allowing for sustained spread. For instance, it has been estimated that HIV had >8 cross-over jumps and SARS had >5 before these pathogens became established in human populations. Because the host reservoir for SARS-CoV-2 is unknown, the number of cross-over events is unknown but early genomic analysis of SARS-CoV-2 RNA from the Wuhan market suggested that at least two distinct lineages were circulating, one of which seeded the global pandemic. Natural selection acts continuously on the pathogen to optimize transmission within the human population ecology, even as that ecology changes often as a result of medical interventions. SARS-CoV-2 is an excellent example early genomic variants appearing to represent variation that enhances transmissions whereas later variants appear as antigenic variants that allow escape from immunity.
Detailed epidemiological analysis of SARS-CoV-2 showed the initial origin in southeast China with recognized global spread within weeks to months. Genomic sequencing showed serial acquisition of point mutations in the gene for the attachment spike protein that had been selected and enabled better transmission across multiple populations with serial waves of alpha, beta, delta and other variants of concern. Coincident with these waves of point mutation variants, the omicron variant appeared in Africa approximately one year after the onset of the pandemic. Its origin is obscure but may have resulted from chronic infection of an immunocompromised host that lasted many months. Serial mutations accumulated in that strain that enhanced within host cell attachment and ultimately resulted in a multi-mutated strain that outcompeted all other SARS-CoV-2 variants for person-to-person transmission across multiple populations around the world. The transmission fitness of omicron is substantially greater than all previous variants in partially and fully immune populations. This virus and its point mutation descendants currently dominate all SARS-CoV-2 variants seen globally.
Emerging pandemic infectious diseases continue to be a risk for our contemporary global world. From a medical point of view, physicians have an ongoing need to understand the evolutionary biology of emerging infectious diseases in order to best respond. Specifically, physicians need to understand the molecular biology of genomics, the use of DNA sequence variation in tracking pathogen spread, natural selection forces operating in non-immune and immune populations that drive genomic sequence changes and concepts that derive from mathematical models of infectious disease transmission, such as the reproduction number, herd immunity and density-dependent disease spread.
Gene Variants and Disease Susceptibility
The search for gene variants associated with disease is a powerful method for discovering the molecular basis for disease and guides the development of novel treatments. APOL1 nephropathy provides a compelling recent example. APOL1 encodes apolipoprotein L1 (ApoL1), which is a component of serum high-density lipoprotein (HDL) and encodes a membrane pore forming domain that creates an anion channel. African Americans are at much higher risk for end stage renal disease (ESRD) than other Americans, and until recently only a small fraction of the added risk was well-defined. In 2010 a large fraction of this health disparity was linked with allelic variants in the APOL1 gene. In particular, individuals affected with ESRD were homozygous for two high risk alleles coding for amino acid substitutions or deletions in the C terminus of ApoL1. These allelic variants had their origin in West Africa several thousand years ago, much later than the out-of-Africa origin (~70,000 years ago) for most of humanity not presently living in Africa. Thus the selected alleles are restricted to descendants of West Africans found not only in West Africa but also in the Americas as a legacy of slavery. In Africa, these alleles are part of an enhanced innate immune system that lyses pathogenic human trypanosomes (such as Trypanosoma brucei brucei)that cause sleeping sickness. The high mortality rate from sleeping sickness in West Africa and Central Africa presumably selected for these allelic variants; the degree of protection must be striking since their gene frequency is ~50% in areas in which sleeping sickness is holoendemic. For comparison, consider the 20% gene frequency of hemoglobin S in malarial holoendemic areas in West Africa. Outside of areas where sleeping sickness is common, these alleles do not appear to be beneficial and individuals without the evolved APOL1 alleles appear entirely healthy. Over 15% of African Americans who are homozygous for the high-risk alleles develop ESRD. Surprisingly, multiple forms of kidney disease are associated with the high-risk alleles, including focal segmental glomerulosclerosis, HIV associated nephropathy and lupus associated nephropathy. ApoL1 is synthesized in the liver but kidney transplant studies show that ApoL1 expression in the kidney determines the risk of ESRD. Expression of ApoL1 in the kidney podocyte in particular is believed to cause lysis of the podocyte and progressive renal disease. Interferon appears to drive APOL1 nephropathy and this may explain its association with HIV and lupus and why unidentified environmental triggers are necessary for expression of disease in those who are homozygous for the high-risk alleles.
The recognition of APOL1 risk variants with ESKD among African Americans was discovered unexpectedly during genome-wide association studies (GWAS) of genomic correlates of ESRD. Understanding of APOL1’s evolutionary origin and function directly enabled the development of effective treatment. Inaxaplin is a small molecule inhibitor of the ApoL1 channel function. In a phase 2 study of 16 patients with focal segmental glomerulosclerosis due to APOL1 nephropathy who were treated for 13 weeks, there was a clinically significant reduction in proteinuria and improvement in renal function.
It is likely that comparative genomics will continue to be a common route by which disease mechanisms are uncovered and new treatments developed. The notion that gene variants that evolved for advantage in one environment become detrimental in another environment is a common theme in evolution and will increasingly be important to medicine. This is a fertile field for exploration through GWAS of disease associations. Many Mendelian diseases such as cystic fibrosis may have similar explanations.
Mendelian Randomization and Genetic Epidemiology
Observational epidemiology has been a major method for advancing medical understanding of disease causation, treatment and prevention. Because of confounding and reverse causation, observational studies are only able to determine disease association. To advance causal interference, Mendelian randomization was developed as a modification of observational epidemiology. Following sequencing of the human genome together with the development of genome-wide association studies, it became possible to identify genetic markers for environmental exposure variables that are correlated with disease outcome. Because of Mendel’s Laws of segregation and independent assortment, genetic variants associated with a modifiable exposure are allocated from parent to offspring independently of other environmental or genetic factors. They thus avoid confounding and reverse causation that plagues all observational epidemiological studies. Many examples of misleading observational studies exist, with the clearest examples being observational studies that indicated apparent causal effect that failed to be validated in randomized clinical trials, such as vitamins and antioxidants in the prevention of cardiovascular disease, beta carotene in the prevention of lung cancer and selenium in the prevention of prostate cancer.
Mendelian randomization is based on the underlying assumption of gene-environment equivalence. That is to say that environmental causes of disease act through biological pathways. For a given environmental risk factor there must exist a genetic variant that mimics the disruption in the implicated biological causal pathway. The art of Mendelian randomization is to identify a genetic marker that links with the modifiable environmental exposure that associates with a disease outcome.
An elegant study of the power of the Mendelian randomization is the demonstration that alcohol is linked to an increased risk of stroke and hypertension at all levels of exposure. In this study over 500,000 men and women in China were followed for approximately 10 years for medically reported ischemic stroke, intracerebral hemorrhagic stroke, myocardial infarction and hypertension. A subset of subjects was genotyped for two variants that altered alcohol metabolism. Genotype strongly predicted alcohol consumption. Subjects qualitatively and quantitatively self-reported their intake of alcohol. In China women rarely report alcohol consumption and in this study 33% of men and 2% of women reported alcohol consumption. As was true for many other observational studies, observational epidemiology within this cohort suggested that low doses of alcohol reduced the risk of stroke and hypertension. However, Mendelian randomization of genetic variants showed a long linear relationship between alcohol intake and risk of stroke or hypertension for all levels of alcohol exposure. No relationship was observed between alcohol intake and risk of myocardial infarction. Among women, very few of whom drank alcohol, genetic variants in alcohol metabolism did not affect the risk of cardiovascular disease. These data demonstrate that the possible role of low-dose alcohol in protecting against stroke or hypertension in observational studies is spurious.
Though a powerful new method in epidemiology, Mendelian randomization does have limits in its ability to make causal inference. These limitations include the fact that gene variants act throughout a lifetime and in many tissues during human development. Environmental exposures may not. Thus Mendelian randomization studies must be critically evaluated before concluding causal inference. But short of a randomized clinical trial, Mendelian randomization offers the best method to infer disease causation. Furthermore, it is likely that the predictive value for finding a positive outcome from a randomized clinical trial will be improved if a supportive Mendelian randomized trial is performed prior to the trial.
CRISPR Cas9 and siRNA Therapeutics
We are living in a golden age of medical therapeutics as treatment options expand beyond small molecules to include protein and nucleic acid medicines. Advances in macromolecular therapeutics have had their origin in an evolutionary and molecular understanding of medicine. RNA in particular is opening therapeutic doors to previously untreatable conditions. mRNA vaccines for the prevention of COVID-19 are but one example of the many uses of RNA in medicine. We describe two other examples of RNA medicines, including short interfering RNA (siRNA) to treat elevated lipoprotein(a) levels and clustered regularly interspaced palindromic repeats (CRISPR Cas9) to treat sickle cell disease and beta thalassemia.
In 2006 Andrew Fine and Craig Mello won the Nobel Prize in Physiology or Medicine for their discovery of siRNA in the nematode worm. siRNA are double stranded RNA molecules 20 to 24 base pairs in length that induce degradation of mRNA. They are an ancestral type of RNA-based gene regulation system found exclusively in eukaryotes. They can be used to reduce the production of proteins that mediate disease. Observational and Mendelian randomization studies demonstrated that elevated levels of lipoprotein (a) are associated with major cardiovascular disease events. Statins do not reduce lipoprotein (a) levels. In a phase 2 dose escalating clinical trial, Nissen and colleagues used a siRNA drug covalently linked to N- acetyl galactosamine to target the asialoglycoprotein receptor on hepatocytes where mRNA that encodes for apolipoprotein (a) is produced. Among 48 subjects with elevated lipoprotein (a) levels, the highest doses of the drug (304 to 608 mg) reduced lipoprotein (a) levels over 96%. A single intravenous dose reduced lipoprotein (a) levels for longer than six months. The drug was well tolerated. siRNA as a drug has great therapeutic potential for long-term benefit for elevated lipoprotein(a) and likely many other diseases.
CRISPR Cas9 has the potential for curing gene-based diseases. In 2006 Eugene Koonin proposed that the CRISPR Cas9 system discovered in prokaryotes was an adaptive immune system for resisting attack by viral phages. The system is based on acquiring a library of DNA sequences that are complementary to sequences of pathogenic phages prevalent in the prokaryote environment. mRNA transcription from the genomic library is able to recognize incoming phage sequence and target the viral genome for degradation. Among prokaryotes the system is billions of years old. In 2012 Jennifer Doudna and Emmanuelle Charpentier engineered a CRISPR Cas9 molecule that could be used to precisely edit both prokaryotic and eukaryotic DNA. In 2020 they received the Nobel prize in Chemistry for their discovery. The use of CRISPR Cas9 in human disease is less than a decade old.
CRISPR was recently used to successfully treat sickle cell disease and beta thalessemia and is now licensed to treat these two conditions. CD34 positive hematopoietic stem cells were isolated and the CRISPR Cas9 system was used to create an inactivating mutation in the gamma globin gene promotors that enable red blood cell expression of fetal hemoglobin. These transformed stem cells were infused back into the patient after myeloablation of their bone marrow, effectively as a bone marrow transplant. The procedure required hospitalization and a month for recovery. Both the US Federal Drug Administration and UK medicines regulator have approved clinical use of this treatment. Published announcements reported that 45 subjects with sickle cell disease received the treatment and 29 have been followed for over one year. Twenty-eight (97%) of 29 subjects were completely relieved of pain episodes typical of sickle cell disease. Of the 54 subjects with beta thalassemia who received the treatment, 42 have been followed for over one year. Thirty-nine (93%) of 42 treated subjects have not required any blood transfusions during follow up and blood transfusion requirements among the remainder were reduced by over 70%. These results are truly spectacular and usher in a new age of curative therapeutics for gene-based diseases.
Implications for a New Synthesis of Medicine and Evolution
These examples demonstrate the impact of evolutionary thinking on the practice of medicine. We note that many other examples can be identified, demonstrating that evolutionary thinking is more widespread in medicine than appreciated. Evolution has and can make contributions to medicine in three areas, including understanding, research and practice. We note that while evolutionary thinking is increasingly shaping medical research, its impact on clinical practice will depend on changes to the medical curriculum.
The power of evolutionary thinking to biology has been as a conceptual foundation for understanding. The same advantage applies to medicine. With evolutionary thinking it becomes possible to understand disease origin above the level of mechanism and to develop therapeutic drugs based on the evolutionary and molecular biology of the cell. An evolutionary understanding of the human body and the origin of disease provides a foundation for launching new research areas, improving the teaching of medicine to students and providing lifelong learning among practicing physicians. The synergistic thinking of medicine and evolution also unites clinical medicine with public health.
Stephen Stearns and Ruslan Medzhitov in their textbook Evolutionary Medicine have formulated an evolutionary classification of disease into six categories. These include extrinsic causes of disease, of which infectious disease is a major group, and intrinsic causes, which include immunologically mediated diseases, gene-environment mismatch disorders, diseases of aging, genetic and chromosomal diseases and genomic conflict disorders. They note that extrinsic causes of mortality have shaped the evolution of the genome with genetic solutions that are imperfect due to trade-offs, constraints and changing environments, which in turn have given rise to the intrinsic causes of disease. Traditional medical classification of disease is based on mechanisms and there are likely as many mechanisms as there are genes in the genome. The evolutionary classification of disease thus simplifies learning about disease origin and allows for the elaboration of molecular mechanisms within that framework. The evolutionary classification also suggests new categories of disease causation that are understudied. One such category includes genomic conflict disorders that may underpin diseases such as pre-eclampsia, gestational diabetes and major neuropsychiatric disorders.
The molecular mechanisms of disease are the targets for drug treatments and the evolutionary history of the cell allows for a simplified classification of drugs into small molecules that modify those proteins implicated in the disease process, therapeutic proteins that are often derived from monoclonal antibodies, therapeutic RNA as mRNA or siRNA and genome editing using CRISPR systems. Macromolecular therapeutics appear to be under development much faster than small molecule therapeutics and are likely to continue to be the main source of new therapeutics for medicine.
Conclusion
We are living in an age of medicine where the ultimate and proximate causes of disease are rapidly becoming understood and where new highly precise and effective molecules are being developed to prevent or treat disease. The scientific evidence compellingly demonstrates that medicine emerges out of biology and that evolutionary thinking guides many of the advancements in therapeutics. Physicians whose medical knowledge is based on an evolutionary foundation are best positioned to deliver these advanced therapeutics. We envision that the 21st century physician will increasingly use the tools of molecular medicine to treat or prevent diseases that are understood both mechanistically and evolutionarily. Such physicians need to possess a new synthesis of medicine and evolution to enhance their practice of medicine. To accelerate the synthesis of medical and evolutionary thinking, we urge changes to the early years of medical education to explicitly incorporate evolution into teaching anatomy, physiology, biochemistry and cell biology. Because change in medicine is best driven by evidence, we urge that a randomized clinical trial be undertaken to show that students and physicians who learn medicine on an evolutionary foundation score higher on examinations, acquire and retain knowledge longer and practice higher-quality health care.
Acknowledgement
I would like to thank Dr Martin Blaser for his critical review of this manuscript.
In 2022 the Nobel Prize in Physiology or Medicine was awarded to Svante Paabo for his discoveries regarding human evolution. By sequencing the ancient genomes of Neanderthals and related archaic hominids and comparing those sequences to modern humans, Paabo and co-workers defined the recent evolutionary history of humanity. Their data illustrated how hominid species interbred and retained gene variants that facilitated modern human adaptations to novel environments throughout Eurasia. This work provided yet another line of evidence of the importance of evolution in shaping human biology. Genomics is the enabling technology that has moved evolution to the forefront of medicine.
Despite these achievements, medicine has yet to fully embrace evolution. In essence, medicine today is much like biology before Darwin, a field rich in observation and data without a unified conceptual foundation. However, all human diseases, whether caused by the physical, biological or social environment, through defects in physiology or by mental events, operate through biological processes. These biological processes have their origin in evolution through natural selection so evolution must be the foundation on which medicine rests. We propose that medicine, like biology, can make sense through the explicit adoption of evolutionary thinking and that the synergistic thinking of medicine and evolution will improve the quality of medical care.
Why has medicine been slow to adopt evolutionary thinking?
Both medicine and biology had their origins 2500 years ago in ancient Greece, with Hippocrates shaping medicine and Aristotle shaping biology. However, over the subsequent millennia, the two fields developed as separate schools of thought. For example, after Darwin established the unifying principle of biology as evolution by natural selection, this idea did not immediately transfer to medicine. Humans were often considered as exceptional examples of life to which biological processes do not apply.
There were attempts to introduce evolutionary thinking into medicine but the early movements of social Darwinism and eugenics were unacceptable to many physicians. This changed somewhat when JBS Haldane argued that infectious diseases were likely a major cause of genetic variation among humans and Allison established that malaria was the selective factor for the high prevalence of sickle cell trait in African and descendent populations. The rise of antimicrobial resistance is another example of how the action of evolution in medicine was made apparent, but which also failed to transform thinking because many thought the evolutionary phenomena of drug resistance was limited to microbes. Medicine has thus remained estranged from evolution.
A major factor for this estrangement is that medical theory and evolutionary theory, despite being biologically based, have had distinct areas of focus (Table 1), which may have kept the two fields apart. Major differences include medicine’s focus on the individual, with variability in individual phenotype limited to a normal range and where mechanism as the proximate cause of disease is important as the target for therapeutic intervention. Evolution, on the other hand, focuses on ultimate causes, where variations within populations are targeted by selective forces and lead to processes of adaptation. In addition, medicine focuses on overcoming disease to achieve health while evolution focuses on maximizing reproductive fitness where less adapted forms are eliminated. Other less important differences include medicine’s focus on development during embryogenesis (ontogeny) and the life cycle and use of randomized clinical trials for experimentation. Evolution’s focus, however, is on evolutionary descent (phylogeny), which is explored by mathematical models or through long-term observation of microbial reproduction in defined environments. Despite these differences, we assert that there is a strong basis for synergy between medical and evolutionary thinking. A modern synthesis uniting these two lines of thinking is already underpinning the thinking and action of the modern physician.
In this essay we provide examples from amongst many, in which evolutionary thinking is advancing medical practice. We consider the advantages that accrue by explicitly incorporating evolutionary thinking into medical practice and argue that it is time for a modern synthesis of medicine and evolution to begin in undergraduate medical education.
Table 1: Differences in Core Concepts of Medicine and Evolution
Category Medicine Evolution
Unit of analysis Individual Population
Constancy of type Normality Variation
Time-scale of change Ontogeny Phylogeny
Process of change Mechanism Adaptation
Result of change Disease Phenotypic change
Optimization of change Health Reproductive fitness
Mathematical methods Randomized clinical trials Mathematical models
Evolutionary Thinking in Medicine
Emerging and Pandemic Diseases
Emerging and pandemic diseases have been a constant feature of human history since the origins of agriculture and civilization because they concentrated the density of human populations to critical thresholds that allowed the propagation of pathogen spread. Movements of people facilitated the spread of disease. Rapid global movement of people, faster than the incubation period of an infectious disease, fuels pandemics. COVID-19 is the first pandemic of the genomic era, the era in which the genome sequences of a pathogen and the host population are routinely available. With intense focus and the use of a wide variety of state-of-the-art genomic tools, the evolution of COVID-19 is rapidly being characterized. No disease has been better understood at an evolutionary level than COVID-19.
In today’s world, RNA viruses like SARS-CoV-2, the causative agent of COVID-19, which spread via the respiratory route, appear to have the highest propensity for community-wide spread. Air travel facilitates the globalization of pathogen spread to produce pandemics in weeks to months, as was witnessed with COVID-19.
Pandemics automatically cause physicians to shift their thinking from the individual to the population. Physicians became adept at using the concepts of evolutionary population biology to limit the spread of COVID-19 and this likely contributed to success in curbing the pandemic. These concepts include consideration of both asymptomatic and symptomatic spread, physical distancing, avoiding poorly ventilated indoor airspaces and herd immunity, among others. Mathematical models of transmission guided the thinking of physicians about the local and global behavior of the pandemic and where to target their efforts.
Evolution provides explanations for how ‘new’ infectious diseases emerge. Most new infections of humans that have pandemic potential that emerge from nature share common traits. They often exist in social host species where horizontal spread readily occurs with or without symptomatic disease. The host species is biochemically similar to humans. Bats and nonhuman primates are two examples of hosts that frequently give rise to emerging infectious diseases. In human history the domesticated animals with which humans closely lived were once the common source for new emerging diseases. Now most emerging infectious are spill-over events from nature. There are often ecological changes at work that bring the reservoir species and human populations together to enable cross-species transfer, such as batching and eating “wild meat” and wet animal markets. The pathogen is often an RNA virus because their higher mutation rates allow rapid genetic adaptation to the human host. The effective reproductive number of the emerging pathogen in the human population at the time of spill-over is often slightly below one. Multiple cross-over events occur before one lineage of the pathogen establishes productive transmission chains [original reproduction number >1] allowing for sustained spread. For instance, it has been estimated that HIV had >8 cross-over jumps and SARS had >5 before these pathogens became established in human populations. Because the host reservoir for SARS-CoV-2 is unknown, the number of cross-over events is unknown but early genomic analysis of SARS-CoV-2 RNA from the Wuhan market suggested that at least two distinct lineages were circulating, one of which seeded the global pandemic. Natural selection acts continuously on the pathogen to optimize transmission within the human population ecology, even as that ecology changes often as a result of medical interventions. SARS-CoV-2 is an excellent example early genomic variants appearing to represent variation that enhances transmissions whereas later variants appear as antigenic variants that allow escape from immunity.
Detailed epidemiological analysis of SARS-CoV-2 showed the initial origin in southeast China with recognized global spread within weeks to months. Genomic sequencing showed serial acquisition of point mutations in the gene for the attachment spike protein that had been selected and enabled better transmission across multiple populations with serial waves of alpha, beta, delta and other variants of concern. Coincident with these waves of point mutation variants, the omicron variant appeared in Africa approximately one year after the onset of the pandemic. Its origin is obscure but may have resulted from chronic infection of an immunocompromised host that lasted many months. Serial mutations accumulated in that strain that enhanced within host cell attachment and ultimately resulted in a multi-mutated strain that outcompeted all other SARS-CoV-2 variants for person-to-person transmission across multiple populations around the world. The transmission fitness of omicron is substantially greater than all previous variants in partially and fully immune populations. This virus and its point mutation descendants currently dominate all SARS-CoV-2 variants seen globally.
Emerging pandemic infectious diseases continue to be a risk for our contemporary global world. From a medical point of view, physicians have an ongoing need to understand the evolutionary biology of emerging infectious diseases in order to best respond. Specifically, physicians need to understand the molecular biology of genomics, the use of DNA sequence variation in tracking pathogen spread, natural selection forces operating in non-immune and immune populations that drive genomic sequence changes and concepts that derive from mathematical models of infectious disease transmission, such as the reproduction number, herd immunity and density-dependent disease spread.
Gene Variants and Disease Susceptibility
The search for gene variants associated with disease is a powerful method for discovering the molecular basis for disease and guides the development of novel treatments. APOL1 nephropathy provides a compelling recent example. APOL1 encodes apolipoprotein L1 (ApoL1), which is a component of serum high-density lipoprotein (HDL) and encodes a membrane pore forming domain that creates an anion channel. African Americans are at much higher risk for end stage renal disease (ESRD) than other Americans, and until recently only a small fraction of the added risk was well-defined. In 2010 a large fraction of this health disparity was linked with allelic variants in the APOL1 gene. In particular, individuals affected with ESRD were homozygous for two high risk alleles coding for amino acid substitutions or deletions in the C terminus of ApoL1. These allelic variants had their origin in West Africa several thousand years ago, much later than the out-of-Africa origin (~70,000 years ago) for most of humanity not presently living in Africa. Thus the selected alleles are restricted to descendants of West Africans found not only in West Africa but also in the Americas as a legacy of slavery. In Africa, these alleles are part of an enhanced innate immune system that lyses pathogenic human trypanosomes (such as Trypanosoma brucei brucei)that cause sleeping sickness. The high mortality rate from sleeping sickness in West Africa and Central Africa presumably selected for these allelic variants; the degree of protection must be striking since their gene frequency is ~50% in areas in which sleeping sickness is holoendemic. For comparison, consider the 20% gene frequency of hemoglobin S in malarial holoendemic areas in West Africa. Outside of areas where sleeping sickness is common, these alleles do not appear to be beneficial and individuals without the evolved APOL1 alleles appear entirely healthy. Over 15% of African Americans who are homozygous for the high-risk alleles develop ESRD. Surprisingly, multiple forms of kidney disease are associated with the high-risk alleles, including focal segmental glomerulosclerosis, HIV associated nephropathy and lupus associated nephropathy. ApoL1 is synthesized in the liver but kidney transplant studies show that ApoL1 expression in the kidney determines the risk of ESRD. Expression of ApoL1 in the kidney podocyte in particular is believed to cause lysis of the podocyte and progressive renal disease. Interferon appears to drive APOL1 nephropathy and this may explain its association with HIV and lupus and why unidentified environmental triggers are necessary for expression of disease in those who are homozygous for the high-risk alleles.
The recognition of APOL1 risk variants with ESKD among African Americans was discovered unexpectedly during genome-wide association studies (GWAS) of genomic correlates of ESRD. Understanding of APOL1’s evolutionary origin and function directly enabled the development of effective treatment. Inaxaplin is a small molecule inhibitor of the ApoL1 channel function. In a phase 2 study of 16 patients with focal segmental glomerulosclerosis due to APOL1 nephropathy who were treated for 13 weeks, there was a clinically significant reduction in proteinuria and improvement in renal function.
It is likely that comparative genomics will continue to be a common route by which disease mechanisms are uncovered and new treatments developed. The notion that gene variants that evolved for advantage in one environment become detrimental in another environment is a common theme in evolution and will increasingly be important to medicine. This is a fertile field for exploration through GWAS of disease associations. Many Mendelian diseases such as cystic fibrosis may have similar explanations.
Mendelian Randomization and Genetic Epidemiology
Observational epidemiology has been a major method for advancing medical understanding of disease causation, treatment and prevention. Because of confounding and reverse causation, observational studies are only able to determine disease association. To advance causal interference, Mendelian randomization was developed as a modification of observational epidemiology. Following sequencing of the human genome together with the development of genome-wide association studies, it became possible to identify genetic markers for environmental exposure variables that are correlated with disease outcome. Because of Mendel’s Laws of segregation and independent assortment, genetic variants associated with a modifiable exposure are allocated from parent to offspring independently of other environmental or genetic factors. They thus avoid confounding and reverse causation that plagues all observational epidemiological studies. Many examples of misleading observational studies exist, with the clearest examples being observational studies that indicated apparent causal effect that failed to be validated in randomized clinical trials, such as vitamins and antioxidants in the prevention of cardiovascular disease, beta carotene in the prevention of lung cancer and selenium in the prevention of prostate cancer.
Mendelian randomization is based on the underlying assumption of gene-environment equivalence. That is to say that environmental causes of disease act through biological pathways. For a given environmental risk factor there must exist a genetic variant that mimics the disruption in the implicated biological causal pathway. The art of Mendelian randomization is to identify a genetic marker that links with the modifiable environmental exposure that associates with a disease outcome.
An elegant study of the power of the Mendelian randomization is the demonstration that alcohol is linked to an increased risk of stroke and hypertension at all levels of exposure. In this study over 500,000 men and women in China were followed for approximately 10 years for medically reported ischemic stroke, intracerebral hemorrhagic stroke, myocardial infarction and hypertension. A subset of subjects was genotyped for two variants that altered alcohol metabolism. Genotype strongly predicted alcohol consumption. Subjects qualitatively and quantitatively self-reported their intake of alcohol. In China women rarely report alcohol consumption and in this study 33% of men and 2% of women reported alcohol consumption. As was true for many other observational studies, observational epidemiology within this cohort suggested that low doses of alcohol reduced the risk of stroke and hypertension. However, Mendelian randomization of genetic variants showed a long linear relationship between alcohol intake and risk of stroke or hypertension for all levels of alcohol exposure. No relationship was observed between alcohol intake and risk of myocardial infarction. Among women, very few of whom drank alcohol, genetic variants in alcohol metabolism did not affect the risk of cardiovascular disease. These data demonstrate that the possible role of low-dose alcohol in protecting against stroke or hypertension in observational studies is spurious.
Though a powerful new method in epidemiology, Mendelian randomization does have limits in its ability to make causal inference. These limitations include the fact that gene variants act throughout a lifetime and in many tissues during human development. Environmental exposures may not. Thus Mendelian randomization studies must be critically evaluated before concluding causal inference. But short of a randomized clinical trial, Mendelian randomization offers the best method to infer disease causation. Furthermore, it is likely that the predictive value for finding a positive outcome from a randomized clinical trial will be improved if a supportive Mendelian randomized trial is performed prior to the trial.
CRISPR Cas9 and siRNA Therapeutics
We are living in a golden age of medical therapeutics as treatment options expand beyond small molecules to include protein and nucleic acid medicines. Advances in macromolecular therapeutics have had their origin in an evolutionary and molecular understanding of medicine. RNA in particular is opening therapeutic doors to previously untreatable conditions. mRNA vaccines for the prevention of COVID-19 are but one example of the many uses of RNA in medicine. We describe two other examples of RNA medicines, including short interfering RNA (siRNA) to treat elevated lipoprotein(a) levels and clustered regularly interspaced palindromic repeats (CRISPR Cas9) to treat sickle cell disease and beta thalassemia.
In 2006 Andrew Fine and Craig Mello won the Nobel Prize in Physiology or Medicine for their discovery of siRNA in the nematode worm. siRNA are double stranded RNA molecules 20 to 24 base pairs in length that induce degradation of mRNA. They are an ancestral type of RNA-based gene regulation system found exclusively in eukaryotes. They can be used to reduce the production of proteins that mediate disease. Observational and Mendelian randomization studies demonstrated that elevated levels of lipoprotein (a) are associated with major cardiovascular disease events. Statins do not reduce lipoprotein (a) levels. In a phase 2 dose escalating clinical trial, Nissen and colleagues used a siRNA drug covalently linked to N- acetyl galactosamine to target the asialoglycoprotein receptor on hepatocytes where mRNA that encodes for apolipoprotein (a) is produced. Among 48 subjects with elevated lipoprotein (a) levels, the highest doses of the drug (304 to 608 mg) reduced lipoprotein (a) levels over 96%. A single intravenous dose reduced lipoprotein (a) levels for longer than six months. The drug was well tolerated. siRNA as a drug has great therapeutic potential for long-term benefit for elevated lipoprotein(a) and likely many other diseases.
CRISPR Cas9 has the potential for curing gene-based diseases. In 2006 Eugene Koonin proposed that the CRISPR Cas9 system discovered in prokaryotes was an adaptive immune system for resisting attack by viral phages. The system is based on acquiring a library of DNA sequences that are complementary to sequences of pathogenic phages prevalent in the prokaryote environment. mRNA transcription from the genomic library is able to recognize incoming phage sequence and target the viral genome for degradation. Among prokaryotes the system is billions of years old. In 2012 Jennifer Doudna and Emmanuelle Charpentier engineered a CRISPR Cas9 molecule that could be used to precisely edit both prokaryotic and eukaryotic DNA. In 2020 they received the Nobel prize in Chemistry for their discovery. The use of CRISPR Cas9 in human disease is less than a decade old.
CRISPR was recently used to successfully treat sickle cell disease and beta thalessemia and is now licensed to treat these two conditions. CD34 positive hematopoietic stem cells were isolated and the CRISPR Cas9 system was used to create an inactivating mutation in the gamma globin gene promotors that enable red blood cell expression of fetal hemoglobin. These transformed stem cells were infused back into the patient after myeloablation of their bone marrow, effectively as a bone marrow transplant. The procedure required hospitalization and a month for recovery. Both the US Federal Drug Administration and UK medicines regulator have approved clinical use of this treatment. Published announcements reported that 45 subjects with sickle cell disease received the treatment and 29 have been followed for over one year. Twenty-eight (97%) of 29 subjects were completely relieved of pain episodes typical of sickle cell disease. Of the 54 subjects with beta thalassemia who received the treatment, 42 have been followed for over one year. Thirty-nine (93%) of 42 treated subjects have not required any blood transfusions during follow up and blood transfusion requirements among the remainder were reduced by over 70%. These results are truly spectacular and usher in a new age of curative therapeutics for gene-based diseases.
Implications for a New Synthesis of Medicine and Evolution
These examples demonstrate the impact of evolutionary thinking on the practice of medicine. We note that many other examples can be identified, demonstrating that evolutionary thinking is more widespread in medicine than appreciated. Evolution has and can make contributions to medicine in three areas, including understanding, research and practice. We note that while evolutionary thinking is increasingly shaping medical research, its impact on clinical practice will depend on changes to the medical curriculum.
The power of evolutionary thinking to biology has been as a conceptual foundation for understanding. The same advantage applies to medicine. With evolutionary thinking it becomes possible to understand disease origin above the level of mechanism and to develop therapeutic drugs based on the evolutionary and molecular biology of the cell. An evolutionary understanding of the human body and the origin of disease provides a foundation for launching new research areas, improving the teaching of medicine to students and providing lifelong learning among practicing physicians. The synergistic thinking of medicine and evolution also unites clinical medicine with public health.
Stephen Stearns and Ruslan Medzhitov in their textbook Evolutionary Medicine have formulated an evolutionary classification of disease into six categories. These include extrinsic causes of disease, of which infectious disease is a major group, and intrinsic causes, which include immunologically mediated diseases, gene-environment mismatch disorders, diseases of aging, genetic and chromosomal diseases and genomic conflict disorders. They note that extrinsic causes of mortality have shaped the evolution of the genome with genetic solutions that are imperfect due to trade-offs, constraints and changing environments, which in turn have given rise to the intrinsic causes of disease. Traditional medical classification of disease is based on mechanisms and there are likely as many mechanisms as there are genes in the genome. The evolutionary classification of disease thus simplifies learning about disease origin and allows for the elaboration of molecular mechanisms within that framework. The evolutionary classification also suggests new categories of disease causation that are understudied. One such category includes genomic conflict disorders that may underpin diseases such as pre-eclampsia, gestational diabetes and major neuropsychiatric disorders.
The molecular mechanisms of disease are the targets for drug treatments and the evolutionary history of the cell allows for a simplified classification of drugs into small molecules that modify those proteins implicated in the disease process, therapeutic proteins that are often derived from monoclonal antibodies, therapeutic RNA as mRNA or siRNA and genome editing using CRISPR systems. Macromolecular therapeutics appear to be under development much faster than small molecule therapeutics and are likely to continue to be the main source of new therapeutics for medicine.
Conclusion
We are living in an age of medicine where the ultimate and proximate causes of disease are rapidly becoming understood and where new highly precise and effective molecules are being developed to prevent or treat disease. The scientific evidence compellingly demonstrates that medicine emerges out of biology and that evolutionary thinking guides many of the advancements in therapeutics. Physicians whose medical knowledge is based on an evolutionary foundation are best positioned to deliver these advanced therapeutics. We envision that the 21st century physician will increasingly use the tools of molecular medicine to treat or prevent diseases that are understood both mechanistically and evolutionarily. Such physicians need to possess a new synthesis of medicine and evolution to enhance their practice of medicine. To accelerate the synthesis of medical and evolutionary thinking, we urge changes to the early years of medical education to explicitly incorporate evolution into teaching anatomy, physiology, biochemistry and cell biology. Because change in medicine is best driven by evidence, we urge that a randomized clinical trial be undertaken to show that students and physicians who learn medicine on an evolutionary foundation score higher on examinations, acquire and retain knowledge longer and practice higher-quality health care.
Acknowledgement
I would like to thank Dr Martin Blaser for his critical review of this manuscript.