The emergence of human-evolutionary medical genomics

Onco-Breastomics: An Eco-Evo-Devo Holistic Approach

Known as a diverse collection of neoplastic diseases, breast cancer (BC) can be hyperbolically characterized as a dynamic pseudo-organ, a living organism able to build a complex, open, hierarchically organized, self-sustainable, and self-renewable tumor system, a population, a species, a local community, a biocenosis, or an evolving dynamical ecosystem (i.e., immune or metabolic ecosystem) that emphasizes both developmental continuity and spatio-temporal change. Moreover, a cancer cell community, also known as an oncobiota, has been described as non-sexually reproducing species, as well as a migratory or invasive species that expresses intelligent behavior, or an endangered or parasite species that fights to survive, to optimize its features inside the host's ecosystem, or that is able to exploit or to disrupt its host circadian cycle for improving the own proliferation and spreading. BC tumorigenesis has also been compared with the early embryo and placenta development that may suggest new strategies for research and therapy. Furthermore, BC has also been characterized as an environmental disease or as an ecological disorder. Many mechanisms of cancer progression have been explained by principles of ecology, developmental biology, and evolutionary paradigms. Many authors have discussed ecological, developmental, and evolutionary strategies for more successful anti-cancer therapies, or for understanding the ecological, developmental, and evolutionary bases of BC exploitable vulnerabilities. Herein, we used the integrated framework of three well known ecological theories: the Bronfenbrenner's theory of human development, the Vannote's River Continuum Concept (RCC), and the Ecological Evolutionary Developmental Biology (Eco-Evo-Devo) theory, to explain and understand several eco-evo-devo-based principles that govern BC progression. Multi-omics fields, taken together as onco-breastomics, offer better opportunities to integrate, analyze, and interpret large amounts of complex heterogeneous data, such as various and big-omics data obtained by multiple investigative modalities, for understanding the eco-evo-devo-based principles that drive BC progression and treatment. These integrative eco-evo-devo theories can help clinicians better diagnose and treat BC, for example, by using non-invasive biomarkers in liquid-biopsies that have emerged from integrated omics-based data that accurately reflect the biomolecular landscape of the primary tumor in order to avoid mutilating preventive surgery, like bilateral mastectomy. From the perspective of preventive, personalized, and participatory medicine, these hypotheses may help patients to think about this disease as a process governed by natural rules, to understand the possible causes of the disease, and to gain control on their own health.

Antagonistic Pleiotropy in Human Disease

Between the 1930s and 1950s, scientists developed key principles of population genetics to try and explain the aging process. Almost a century later, these aging theories, including antagonistic pleiotropy and mutation accumulation, have been experimentally validated in animals. Although the theories have been much harder to test in humans despite research dating back to the 1970s, recent research is closing this evidence gap. Here we examine the strength of evidence for antagonistic pleiotropy in humans, one of the leading evolutionary explanations for the retention of genetic risk variation for non-communicable diseases. We discuss the analytical tools and types of data that are used to test for patterns of antagonistic pleiotropy and provide a primer of evolutionary theory on types of selection as a guide for understanding this mechanism and how it may manifest in other diseases. We find an abundance of non-experimental evidence for antagonistic pleiotropy in many diseases. In some cases, several studies have independently found corroborating evidence for this mechanism in the same or related sets of diseases including cancer and neurodegenerative diseases. Recent studies also suggest antagonistic pleiotropy may be involved in cardiovascular disease and diabetes. There are also compelling examples of disease risk variants that confer fitness benefits ranging from resistance to other diseases or survival in extreme environments. This provides increasingly strong support for the theory that antagonistic pleiotropic variants have enabled improved fitness but have been traded for higher burden of disease later in life. Future research in this field is required to better understand how this mechanism influences contemporary disease and possible consequences for their treatment.

Impact of demography and population dynamics on the genetic architecture of human longevity

The study of the genetics of longevity has been mainly addressed by GWASs that considered subjects from different populations to reach higher statistical power. The "price to pay" is that population-specific evolutionary histories and trade-offs were neglected in the investigation of gene-environment interactions. We propose a new “diachronic” approach that considers processes occurred at both evolutionary and lifespan timescales. We focused on a well-characterized population in terms of evolutionary history (i.e. Italians) and we generated genome-wide data for 333 centenarians from the peninsula and 773 geographically-matched healthy individuals. Obtained results showed that: (i) centenarian genomes are enriched for an ancestral component likely shaped by pre-Neolithic migrations; (ii) centenarians born in Northern Italy unexpectedly clustered with controls from Central/Southern Italy suggesting that Neolithic and Bronze Age gene flow did not favor longevity in this population; (iii) local past adaptive events in response to pathogens and targeting arachidonic acid metabolism became favorable for longevity; (iv) lifelong changes in the frequency of several alleles revealed pleiotropy and trade-off mechanisms crucial for longevity. Therefore, we propose that demographic history and ancient/recent population dynamics need to be properly considered to identify genes involved in longevity, which can differ in different temporal/spatial settings.

Genetic disease risks can be misestimated across global populations

BACKGROUND

Accurate assessment of health disparities requires unbiased knowledge of genetic risks in different populations. Unfortunately, most genome-wide association studies use genotyping arrays and European samples. Here, we integrate whole genome sequence data from global populations, results from thousands of genome-wide association studies (GWAS), and extensive computer simulations to identify how genetic disease risks can be misestimated.

RESULTS

In contrast to null expectations, we find that risk allele frequencies at known disease loci are significantly different for African populations compared to other continents. Strikingly, ancestral risk alleles are found at 9.51% higher frequency in Africa, and derived risk alleles are found at 5.40% lower frequency in Africa. By simulating GWAS with different study populations, we find that non-African cohorts yield disease associations that have biased allele frequencies and that African cohorts yield disease associations that are relatively free of bias. We also find empirical evidence that genotyping arrays and SNP ascertainment bias contribute to continental differences in risk allele frequencies. Because of these causes, polygenic risk scores can be grossly misestimated for individuals of African descent. Importantly, continental differences in risk allele frequencies are only moderately reduced if GWAS use whole genome sequences and hundreds of thousands of cases and controls. Finally, comparisons between uncorrected and corrected genetic risk scores reveal the benefits of considering whether risk alleles are ancestral or derived.

CONCLUSIONS

Our results imply that caution must be taken when extrapolating GWAS results from one population to predict disease risks in another population.

Understanding rare and common diseases in the context of human evolution

The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.

Recent Positive Selection Drives the Expansion of a Schizophrenia Risk Nonsynonymous Variant at SLC39A8 in Europeans

Natural selection has played important roles in optimizing complex human adaptations. However, schizophrenia poses an evolutionary paradox during human evolution, as the illness has strongly negative effects on fitness, but persists with a prevalence of ~0.5% across global populations. Recent studies have identified numerous risk variations in diverse populations, which might be able to explain the stable and high rate of schizophrenia morbidity in different cultures and regions, but the questions about why the risk alleles derived and maintained in human gene pool still remain unsolved. Here, we studied the evolutionary pattern of a schizophrenia risk variant rs13107325 (P < 5.0 × 10(-8) in Europeans) in the SLC39A8 gene. We found the SNP is monomorphic in Asians and Africans with risk (derived) T-allele totally absent, and further evolutionary analyses showed the T-allele has experienced recent positive selection in Europeans. Subsequent exploratory analyses implicated that the colder environment in Europe was the likely selective pressures, ie, when modern humans migrated "out of Africa" and moved to Europe mainland (a colder and cooler continent than Africa), new alleles derived due to positive selection and protected humans from risk of hypertension and also helped them adapt to the cold environment. The hypothesis was supported by our pleiotropic analyses with hypertension and energy intake as well as obesity in Europeans. Our data thus provides an intriguing example to illustrate a possible mechanism for maintaining schizophrenia risk alleles in the human gene pool, and further supported that schizophrenia is likely a product caused by pleiotropic effect during human evolution.

How evolutionary principles improve the understanding of human health and disease

An appreciation of the fundamental principles of evolutionary biology provides new insights into major diseases and enables an integrated understanding of human biology and medicine. However, there is a lack of awareness of their importance amongst physicians, medical researchers, and educators, all of whom tend to focus on the mechanistic (proximate) basis for disease, excluding consideration of evolutionary (ultimate) reasons. The key principles of evolutionary medicine are that selection acts on fitness, not health or longevity; that our evolutionary history does not cause disease, but rather impacts on our risk of disease in particular environments; and that we are now living in novel environments compared to those in which we evolved. We consider these evolutionary principles in conjunction with population genetics and describe several pathways by which evolutionary processes can affect disease risk. These perspectives provide a more cohesive framework for gaining insights into the determinants of health and disease. Coupled with complementary insights offered by advances in genomic, epigenetic, and developmental biology research, evolutionary perspectives offer an important addition to understanding disease. Further, there are a number of aspects of evolutionary medicine that can add considerably to studies in other domains of contemporary evolutionary studies.

Integrating genomics into evolutionary medicine

The application of the principles of evolutionary biology into medicine was suggested long ago and is already providing insight into the ultimate causes of disease. However, a full systematic integration of medical genomics and evolutionary medicine is still missing. Here, we briefly review some cases where the combination of the two fields has proven profitable and highlight two of the main issues hindering the development of evolutionary genomic medicine as a mature field, namely the dissociation between fitness and health and the still considerable difficulties in predicting phenotypes from genotypes. We use publicly available data to illustrate both problems and conclude that new approaches are needed for evolutionary genomic medicine to overcome these obstacles.

Diabetic embryopathy: a developmental perspective from fertilization to adulthood

Maternal diabetes mellitus is one of the strongest human teratogens. Despite recent advances in the fields of clinical embryology, experimental teratology and preventive medicine, diabetes-related perturbations of the maternofetal unit maintain a considerable impact on the Healthcare System. Classic consequences of prenatal exposure to hyperglycemia encompass (early) spontaneous abortions, perinatal death and malformations. The spectrum of related malformations comprises some recurrent blastogenic monotopic patterns, i.e. holoprosencephaly, caudal dysgenesis and oculoauriculovertebral spectrum, as well as pleiotropic syndromes, i.e. femoral hypoplasia-unusual face syndrome. Despite this, most malformed fetuses display multiple blastogenic defects of the VACTERL type, whose (apparently) casual combination preclude recognizing recurrent patterns, but accurately testifies to their developmental stage at onset. With the application of developmental biology in modern medicine, the effects of diabetes on the unborn patient are expanded to include the predisposition to develop insulin resistance in adulthood. The mechanisms underlying the transgenerational correlation between maternal diabetes and proneness to adult disorders in the offspring remain unclear, and the epigenetic plasticity may represent the missing link. In this scenario, a development-driven summary of the multifaced consequences of maternal diabetes on fertility and child health may add a practical resource to the repertoire of available information on early stages of embryogenesis.

Evolutionary molecular medicine

Evolution has long provided a foundation for population genetics, but some major advances in evolutionary biology from the twentieth century that provide foundations for evolutionary medicine are only now being applied in molecular medicine. They include the need for both proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, competition between alleles, co-evolution, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are transforming evolutionary biology in ways that create even more opportunities for progress at its interfaces with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and related principles to speed the development of evolutionary molecular medicine.

The evolutionary biology of child health

I apply evolutionary perspectives and conceptual tools to analyse central issues underlying child health, with emphases on the roles of human-specific adaptations and genomic conflicts in physical growth and development. Evidence from comparative primatology, anthropology, physiology and human disorders indicates that child health risks have evolved in the context of evolutionary changes, along the human lineage, affecting the timing, growth-differentiation phenotypes and adaptive significance of prenatal stages, infancy, childhood, juvenility and adolescence. The most striking evolutionary changes in humans are earlier weaning and prolonged subsequent pre-adult stages, which have structured and potentiated maladaptations related to growth and development. Data from human genetic and epigenetic studies, and mouse models, indicate that growth, development and behaviour during pre-adult stages are mediated to a notable degree by effects from genomic conflicts and imprinted genes. The incidence of cancer, the primary cause of non-infectious childhood mortality, mirrors child growth rates from birth to adolescence, with paediatric cancer development impacted by imprinted genes that control aspects of growth. Understanding the adaptive significance of child growth and development phenotypes, in the context of human-evolutionary changes and genomic conflicts, provides novel insights into the causes of disease in childhood.

Evolutionary principles and their practical application

Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently in these different fields, even though the underlying fundamental concepts are the same. We explore these fundamental concepts under four main themes: variation, selection, connectivity, and eco-evolutionary dynamics. Within each theme, we present several key evolutionary principles and illustrate their use in addressing applied problems. We hope that the resulting primer of evolutionary concepts and their practical utility helps to advance a unified multidisciplinary field of applied evolutionary biology.