The contribution of natural selection to present-day susceptibility to chronic inflammatory and autoimmune disease

Integrating the Thrifty Genotype and Evolutionary Mismatch Hypotheses to understand variation in cardiometabolic disease risk

More than 60 years ago, James Neel proposed the Thrifty Genotype Hypothesis to explain the widespread prevalence of type 2 diabetes in Western, industrial contexts. This hypothesis posits that variants linked to conservative energy usage and increased fat deposition would have been favored throughout human evolution due to the advantages they could provide during periods of resource limitation. However, in industrial environments, these variants instead produce an increased risk of obesity, metabolic syndrome, type 2 diabetes, and related health issues. This hypothesis has been popular and impactful, with thousands of citations, many ongoing debates, and several spin-off theories in biomedicine, evolutionary biology, and anthropology. However, despite great attention, the applicability and utility of the Thrifty Genotype Hypothesis (TGH) to modern human health remains, in our opinion, unresolved. To move research in this area forward, we first discuss the original formulation of the TGH and its critiques. Second, we trace the TGH to updated hypotheses that are currently at the forefront of the evolutionary medicine literature-namely, the Evolutionary Mismatch Hypothesis. Third, we lay out empirical predictions for updated hypotheses and evaluate them against the current literature. Finally, we discuss study designs that could be fruitful for filling current knowledge gaps; here, we focus on partnerships with subsistence-level groups undergoing lifestyle transitions, and we present data from an ongoing study with the Orang Asli of Malaysia to illustrate this point. Overall, we hope this synthesis will guide new empirical research aimed at understanding how the human evolutionary past interacts with our modern environments to influence cardiometabolic health.

Shaping immunity: The influence of natural selection on population immune diversity

Humans exhibit considerable variability in their immune responses to the same immune challenges. Such variation is widespread and affects individual and population-level susceptibility to infectious diseases and immune disorders. Although the factors influencing immune response diversity are partially understood, what mechanisms lead to the wide range of immune traits in healthy individuals remain largely unexplained. Here, we discuss the role that natural selection has played in driving phenotypic differences in immune responses across populations and present-day susceptibility to immune-related disorders. Further, we touch on future directions in the field of immunogenomics, highlighting the value of expanding this work to human populations globally, the utility of modeling the immune response as a dynamic process, and the importance of considering the potential polygenic nature of natural selection. Identifying loci acted upon by evolution may further pinpoint variants critically involved in disease etiology, and designing studies to capture these effects will enrich our understanding of the genetic contributions to immunity and immune dysregulation.

Epigenetic variation impacts individual differences in the transcriptional response to influenza infection

Humans display remarkable interindividual variation in their immune response to identical challenges. Yet, our understanding of the genetic and epigenetic factors contributing to such variation remains limited. Here we performed in-depth genetic, epigenetic and transcriptional profiling on primary macrophages derived from individuals of European and African ancestry before and after infection with influenza A virus. We show that baseline epigenetic profiles are strongly predictive of the transcriptional response to influenza A virus across individuals. Quantitative trait locus (QTL) mapping revealed highly coordinated genetic effects on gene regulation, with many cis-acting genetic variants impacting concomitantly gene expression and multiple epigenetic marks. These data reveal that ancestry-associated differences in the epigenetic landscape can be genetically controlled, even more than gene expression. Lastly, among QTL variants that colocalized with immune-disease loci, only 7% were gene expression QTL, while the remaining genetic variants impact epigenetic marks, stressing the importance of considering molecular phenotypes beyond gene expression in disease-focused studies.

The selection landscape and genetic legacy of ancient Eurasians

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

Applying an evolutionary mismatch framework to understand disease susceptibility

Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease, and type 2 diabetes are among a long list of "lifestyle" diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be "mismatched" and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions, with different health effects in "ancestral" versus "modern" environments. To identify such loci, we advocate for combining genomic tools in partnership with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the "matched" to "mismatched" spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures.

Mapping interindividual dynamics of innate immune response at single-cell resolution

Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells. This approach identified 1,275 expression quantitative trait loci (local false discovery rate 10%) that manifested during the responses, many of which were colocalized with susceptibility loci identified by genome-wide association studies of infectious and autoimmune diseases, including the OAS1 splicing quantitative trait locus in a COVID-19 susceptibility locus. In summary, our analytical approach provides a unique framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.

Evolutionary mismatch and the role of GxE interactions in human disease

Globally, we are witnessing the rise of complex, non-communicable diseases (NCDs) related to changes in our daily environments. Obesity, asthma, cardiovascular disease, and type 2 diabetes are part of a long list of "lifestyle" diseases that were rare throughout human history but are now common. A key idea from anthropology and evolutionary biology-the evolutionary mismatch hypothesis-seeks to explain this phenomenon. It posits that humans evolved in environments that radically differ from the ones experienced by most people today, and thus traits that were advantageous in past environments may now be "mismatched" and disease-causing. This hypothesis is, at its core, a genetic one: it predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions and have differential health effects in ancestral versus modern environments. Here, we discuss how this concept could be leveraged to uncover the genetic architecture of NCDs in a principled way. Specifically, we advocate for partnering with small-scale, subsistence-level groups that are currently transitioning from environments that are arguably more "matched" with their recent evolutionary history to those that are more "mismatched". These populations provide diverse genetic backgrounds as well as the needed levels and types of environmental variation necessary for mapping GxE interactions in an explicit mismatch framework. Such work would make important contributions to our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and sociocultural contexts.

Prioritizing autoimmunity risk variants for functional analyses by fine-mapping mutations under natural selection

Pathogen-driven selection shaped adaptive mutations in immunity genes, including those contributing to inflammatory disorders. Functional characterization of such adaptive variants can shed light on disease biology and past adaptations. This popular idea, however, was difficult to test due to challenges in pinpointing adaptive mutations in selection footprints. In this study, using a local-tree-based approach, we show that 28% of risk loci (153/535) in 21 inflammatory disorders bear footprints of moderate and weak selection, and part of them are population specific. Weak selection footprints allow partial fine-mapping, and we show that in 19% (29/153) of the risk loci under selection, candidate disease variants are hitchhikers, and only in 39% of cases they are likely selection targets. We predict function for a subset of these selected SNPs and highlight examples of antagonistic pleiotropy. We conclude by offering disease variants under selection that can be tested functionally using infectious agents and other stressors to decipher the poorly understood link between environmental stressors and genetic risk in inflammatory conditions.

Genomic Assessment of Cancer Susceptibility in the Threatened Catalina Island Fox (Urocyon littoralis catalinae)

Small effective population sizes raise the probability of extinction by increasing the frequency of potentially deleterious alleles and reducing fitness. However, the extent to which cancers play a role in the fitness reduction of genetically depauperate wildlife populations is unknown. Santa Catalina island foxes (Urocyon littoralis catalinae) sampled in 2007-2008 have a high prevalence of ceruminous gland tumors, which was not detected in the population prior to a recent bottleneck caused by a canine distemper epidemic. The disease appears to be associated with inflammation from chronic ear mite (Otodectes) infections and secondary elevated levels of Staphyloccus pseudointermedius bacterial infections. However, no other environmental factors to date have been found to be associated with elevated cancer risk in this population. Here, we used whole genome sequencing of the case and control individuals from two islands to identify candidate loci associated with cancer based on genetic divergence, nucleotide diversity, allele frequency spectrum, and runs of homozygosity. We identified several candidate loci based on genomic signatures and putative gene functions, suggesting that cancer susceptibility in this population may be polygenic. Due to the efforts of a recovery program and weak fitness effects of late-onset disease, the population size has increased, which may allow selection to be more effective in removing these presumably slightly deleterious alleles. Long-term monitoring of the disease alleles, as well as overall genetic diversity, will provide crucial information for the long-term persistence of this threatened population.

Inflammation, microbiome and colorectal cancer disparity in African-Americans: Are there bugs in the genetics?

Dysregulated interactions between host inflammation and gut microbiota over the course of life increase the risk of colorectal cancer (CRC). While environmental factors and socio-economic realities of race remain predominant contributors to CRC disparities in African-Americans (AAs), this review focuses on the biological mediators of CRC disparity, namely the under-appreciated influence of inherited ancestral genetic regulation on mucosal innate immunity and its interaction with the microbiome. There remains a poor understanding of mechanisms linking immune-related genetic polymorphisms and microbiome diversity that could influence chronic inflammation and exacerbate CRC disparities in AAs. A better understanding of the relationship between host genetics, bacteria, and CRC pathogenesis will improve the prediction of cancer risk across race/ethnicity groups overall.

The evolution of powerful yet perilous immune systems

The mammalian immune system packs serious punch against infection but can also cause harm: for example, coronavirus disease 2019 (COVID-19) made headline news of the simultaneous power and peril of human immune responses. In principle, natural selection leads to exquisite adaptation and therefore cytokine responsiveness that optimally balances the benefits of defense against its costs (e.g., immunopathology suffered and resources expended). Here, we illustrate how evolutionary biology can predict such optima and also help to explain when/why individuals exhibit apparently maladaptive immunopathological responses. Ultimately, we argue that the evolutionary legacies of multicellularity and life-history strategy, in addition to our coevolution with symbionts and our demographic history, together explain human susceptibility to overzealous, pathology-inducing cytokine responses. Evolutionary insight thereby complements molecular/cellular mechanistic insights into immunopathology.

New insights into human immunity from ancient genomics

Population genetic studies have clearly indicated that immunity and host defense are among the functions most frequently subject to natural selection, and increased our understanding of the biological relevance of the corresponding genes and their contribution to variable immune traits and diseases. Herein, we will focus on some recently studied forms of human adaptation to infectious agents, including hybridization with now-extinct hominins, such as Neanderthals and Denisovans, and admixture between modern human populations. These studies, which are partly enabled by the technological advances in the sequencing of DNA from ancient remains, provide new insight into the sources of immune response variation in contemporary humans, such as the recently reported link between Neanderthal heritage and susceptibility to severe COVID-19 disease. Furthermore, ancient DNA analyses, in both humans and pathogens, allow to measure the action of natural selection on immune genes across time and to reconstruct the impact of past epidemics on the evolution of human immunity.

Cancer as a prospective sequela of long COVID-19

As the spread of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) continues to surge worldwide, our knowledge of coronavirus disease 2019 (COVID‐19) is rapidly expanding. Although most COVID‐19 patients recover within weeks of symptom onset, some experience lingering symptoms that last for months (“long COVID‐19”). Early reports of COVID‐19 sequelae, including cardiovascular, pulmonary, and neurological conditions, have raised concerns about the long‐term effects of COVID‐19, especially in hard‐hit communities. It is becoming increasingly evident that cancer patients are more susceptible to SARS‐CoV‐2 infection and are at a higher risk of severe COVID‐19 than the general population. Nevertheless, whether long COVID‐19 increases the risk of cancer in those with no prior malignancies, remains unclear. Given, the disproportionate impact of the disease on the African American community, yet another unanswered question is whether racial disparities are to be expected in COVID‐19 sequelae. Herein, we propose that long COVID‐19 may predispose recovered patients to cancer development and accelerate cancer progression. This hypothesis is based on growing evidence of the ability of SARS‐CoV‐2 to modulate oncogenic pathways, promote chronic low‐grade inflammation, and cause tissue damage. Comprehensive studies are urgently required to elucidate the effects of long COVID‐19 on cancer susceptibility.

Polygenic Adaptation: Integrating Population Genetics and Gene Regulatory Networks

The adaptation of populations to local environments often relies on the selection of optimal values for polygenic traits. Here, we first summarize the results obtained from different quantitative genetics and population genetics models, about the genetic architecture of polygenic traits and their response to directional selection. We then highlight the contribution of systems biology to the understanding of the molecular bases of polygenic traits and the evolution of gene regulatory networks involved in these traits. Finally, we discuss the need for a unifying framework merging the fields of population genetics, quantitative genetics and systems biology to better understand the molecular bases of polygenic traits adaptation.

Disentangling the Coronavirus Disease 2019 Health Disparities in African Americans: Biological, Environmental, and Social Factors

The stark racial disparities related to the coronavirus disease 2019 (COVID-19) pandemic in the United States, wherein minority populations are disproportionately getting infected and succumbing to the disease, is of grave concern. It is critical to understand and address the underlying causes of these disparities that are complex and driven by interacting environmental, social and biological factors. In this article we focus on the African American community and examine how social and environmental determinants of health intersect with biological factors (comorbidities, underlying genetics, host immunity, vitamin D levels, epigenetics) to exacerbate risk for morbidity and mortality.

Revisiting the Hygiene Hypothesis in the Context of Autoimmunity

Initially described for allergic diseases, the hygiene hypothesis was extended to autoimmune diseases in the early 2000s. A historical overview allows appreciation of the development of this concept over the last two decades and its discussion in the context of evolution. While the epidemiological data are convergent, with a few exceptions, the underlying mechanisms are multiple and complex. A major question is to determine what is the respective role of pathogens, bacteria, viruses, and parasites, versus commensals. The role of the intestinal microbiota has elicited much interest, but is it a cause or a consequence of autoimmune-mediated inflammation? Our hypothesis is that both pathogens and commensals intervene. Another question is to dissect what are the underlying cellular and molecular mechanisms. The role of immunoregulatory cytokines, in particular interleukin-10 and TGF beta is probably essential. An important place should also be given to ligands of innate immunity receptors present in bacteria, viruses or parasites acting independently of their immunogenicity. The role of Toll-Like Receptor (TLR) ligands is well documented including via TLR ligand desensitization.

Sub-Saharan African information potential to unveil adaptations to infectious disease

Sub-Saharan Africa is the most promising region of the world to conduct high-throughput studies to unveil adaptations to infectious diseases due to several reasons, namely, the longest evolving time-depth in the Homo sapiens phylogenetic tree (at least two-third older than any other worldwide region); the continuous burden of infectious diseases (still number one in health/life threat); and the coexistence of populations practising diverse subsistence modes (nomadic or seminomadic hunter-gatherers and agropastoralists, and sedentary agriculturalists, small urban and megacity groups). In this review, we will present the most up-to-date results that shed light on three main hypotheses related with this adaptation. One is the hypothesis of coevolution between host and pathogen, given enough time for the establishment of this highly dynamic relationship. The second hypothesis enunciates that the agricultural transition was responsible for the increase of the infectious disease burden, due to the huge expansion of the sedentary human population and the cohabitation with domesticates as main reservoirs of pathogens. The third hypothesis states that the boosting of our immune system against pathogens by past selection may have resulted in maladaptation of the developed hygienic societies, leading to an increase of allergic, inflammatory and autoimmune disorders. Further work will enlighten the biological mechanisms behind these main adaptations, which can be insightful for translation into diagnosis, prognosis and treatment interventions.

Racial Disparities in Necrotizing Enterocolitis

Necrotizing enterocolitis (NEC) is a serious disease of the intestinal tract affecting 5-10% of pre-term infants with up to 50% mortality in those that require surgery. There is wide variation in the rates and outcomes of NEC by race and ethnicity, and the reasons for this disparity are poorly understood. In this article, we review the epidemiology and discuss possible explanations for racial and ethnic differences in NEC. Most of the current evidence investigating the role of race in NEC comes from North America and suggests that Hispanic ethnicity and non-Hispanic Black race are associated with higher risk of NEC compared to non-Hispanic White populations. Differences in pre-term births, breastfeeding rates, and various sociodemographic factors does not fully account for the observed disparities in NEC incidence and outcomes. While genetic studies are beginning to identify candidate genes that may increase or decrease risk for NEC among racial populations, current data remain limited by small sample sizes and lack of validation. Complex interactions between social and biological determinants likely underly the differences in NEC outcomes among racial groups. Larger datasets with detailed social, phenotypic, and genotypic information, coupled with advanced bioinformatics techniques are needed to comprehensively understand racial disparities in NEC.

Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus

Gene expression signatures can stratify patients with heterogeneous diseases, such as systemic lupus erythematosus (SLE), yet understanding the contributions of ancestral background to this heterogeneity is not well understood. We hypothesized that ancestry would significantly influence gene expression signatures and measured 34 gene modules in 1566 SLE patients of African ancestry (AA), European ancestry (EA), or Native American ancestry (NAA). Healthy subject ancestry-specific gene expression provided the transcriptomic background upon which the SLE patient signatures were built. Although standard therapy affected every gene signature and significantly increased myeloid cell signatures, logistic regression analysis determined that ancestral background significantly changed 23 of 34 gene signatures. Additionally, the strongest association to gene expression changes was found with autoantibodies, and this also had etiology in ancestry: the AA predisposition to have both RNP and dsDNA autoantibodies compared with EA predisposition to have only anti-dsDNA. A machine learning approach was used to determine a gene signature characteristic to distinguish AA SLE and was most influenced by genes characteristic of the perturbed B cell axis in AA SLE patients.

Transcriptional profiling of lupus patients and healthy controls reveals ancestry-related differences and transcriptional heterogeneity among lupus patients.

Precision medicine in atopic diseases

PURPOSE OF REVIEW

To analyze the status of precision medicine in atopic diseases.

RECENT FINDINGS

Atopic diseases are increasingly recognized as heterogeneous in nature and they can be quite different in severity, response to therapy, triggers, genetic back ground, ancestral risk and type of inflammation. This significant variability in the landscape of atopic diseases is not reflected in the common treatment guidelines that follow 'one fits all' approach for their management. Such an approach is largely based on minimal 'phenotype' elements, such as severity of disease and response to therapy and does not reflect the information accumulate in the last 20 years about particular pathogenic pathways (endotypes) leading to disease (phenotypes) based on biomolecular analysis of the single individuals. Accumulating data have defined asthma allergic rhinitis, food allergy based on their endotypes and clinically relevant phenotypes. In general, atopic diseases can be largely classified as high or low Th2 inflammatory status, which may explain the severity and response to therapy.

SUMMARY

Precision medicine is aiming to use known endotype phenotype to guide specific individualized treatment. The work aimed in deep characterization of diseases to guide the disease management is crucial in light of the availability of ever more precise treatment able to target specific pathways.

Detecting fitness epistasis in recently admixed populations with genome-wide data

BACKGROUND

Fitness epistasis, the interaction effect of genes at different loci on fitness, makes an important contribution to adaptive evolution. Although fitness interaction evidence has been observed in model organisms, it is more difficult to detect and remains poorly understood in human populations as a result of limited statistical power and experimental constraints. Fitness epistasis is inferred from non-independence between unlinked loci. We previously observed ancestral block correlation between chromosomes 4 and 6 in African Americans. The same approach fails when examining ancestral blocks on the same chromosome due to the strong confounding effect observed in a recently admixed population.

RESULTS

We developed a novel approach to eliminate the bias caused by admixture linkage disequilibrium when searching for fitness epistasis on the same chromosome. We applied this approach in 16,252 unrelated African Americans and identified significant ancestral correlations in two pairs of genomic regions (P-value< 8.11 × 10- 7) on chromosomes 1 and 10. The ancestral correlations were not explained by population admixture. Historical African-European crossover events are reduced between pairs of epistatic regions. We observed multiple pairs of co-expressed genes shared by the two regions on each chromosome, including ADAR being co-expressed with IFI44 in almost all tissues and DARC being co-expressed with VCAM1, S1PR1 and ELTD1 in multiple tissues in the Genotype-Tissue Expression (GTEx) data. Moreover, the co-expressed gene pairs are associated with the same diseases/traits in the GWAS Catalog, such as white blood cell count, blood pressure, lung function, inflammatory bowel disease and educational attainment.

CONCLUSIONS

Our analyses revealed two instances of fitness epistasis on chromosomes 1 and 10, and the findings suggest a potential approach to improving our understanding of adaptive evolution.

Evolutionary and population (epi)genetics of immunity to infection

Immune response is one of the functions that have been more strongly targeted by natural selection during human evolution. The evolutionary genetic dissection of the immune system has greatly helped to distinguish genes and functions that are essential, redundant or advantageous for human survival. It is also becoming increasingly clear that admixture between early Eurasians with now-extinct hominins such as Neanderthals or Denisovans, or admixture between modern human populations, can be beneficial for human adaptation to pathogen pressures. In this review, we discuss how the integration of population genetics with functional genomics in diverse human populations can inform about the changes in immune functions related to major lifestyle transitions (e.g., from hunting and gathering to farming), the action of natural selection to the evolution of the immune system, and the history of past epidemics. We also highlight the need of expanding the characterization of the immune system to a larger array of human populations-particularly neglected human groups historically exposed to different pathogen pressures-to fully capture the relative contribution of genetic, epigenetic, and environmental factors to immune response variation in humans.

WEIRD bodies: mismatch, medicine and missing diversity

Despite recent rapid advances in medical knowledge that have improved survival, conventional medical science's understanding of human health and disease relies heavily on people of European descent living in contemporary urban industrialized environments. Given that modern conditions in high-income countries differ widely in terms of lifestyle and exposures compared to those experienced by billions of people and all our ancestors over several hundred thousand years, this narrow approach to the human body and health is very limiting. We argue that preventing and treating chronic diseases of aging and other mismatch diseases will require both expanding study design to sample diverse populations and contexts, and fully incorporating evolutionary perspectives. In this paper, we first assess the extent of biased representation of industrialized populations in high profile, international biomedical journals, then compare patterns of morbidity and health across world regions. We also compare demographic rates and the force of selection between subsistence and industrialized populations to reflect on the changes in how selection operates on fertility and survivorship across the lifespan. We argue that, contrary to simplistic misguided solutions like the PaleoDiet, the hypothesis of evolutionary mismatch needs critical consideration of population history, evolutionary biology and evolved reaction norms to prevent and treat diseases. We highlight the critical value of broader sampling by considering the effects of three key exposures that have radically changed over the past century in many parts of the world-pathogen burden, reproductive effort and physical activity-on autoimmune, cardiometabolic and other mismatch diseases.

Impact of Historic Migrations and Evolutionary Processes on Human Immunity

The evolution of mankind has constantly been influenced by the pathogens encountered. The various populations of modern humans that ventured out of Africa adapted to different environments and faced a large variety of infectious agents, resulting in local adaptations of the immune system for these populations. The functional variation of immune genes as a result of evolution is relevant in the responses against infection, as well as in the emergence of autoimmune and inflammatory diseases observed in modern populations. Understanding how host-pathogen interactions have influenced the human immune system from an evolutionary perspective might contribute to unveiling the causes behind different immune-mediated disorders and promote the development of new strategies to detect and control such diseases.

ImaGene: a convolutional neural network to quantify natural selection from genomic data

BACKGROUND

The genetic bases of many complex phenotypes are still largely unknown, mostly due to the polygenic nature of the traits and the small effect of each associated mutation. An alternative approach to classic association studies to determining such genetic bases is an evolutionary framework. As sites targeted by natural selection are likely to harbor important functionalities for the carrier, the identification of selection signatures in the genome has the potential to unveil the genetic mechanisms underpinning human phenotypes. Popular methods of detecting such signals rely on compressing genomic information into summary statistics, resulting in the loss of information. Furthermore, few methods are able to quantify the strength of selection. Here we explored the use of deep learning in evolutionary biology and implemented a program, called ImaGene, to apply convolutional neural networks on population genomic data for the detection and quantification of natural selection.

RESULTS

ImaGene enables genomic information from multiple individuals to be represented as abstract images. Each image is created by stacking aligned genomic data and encoding distinct alleles into separate colors. To detect and quantify signatures of positive selection, ImaGene implements a convolutional neural network which is trained using simulations. We show how the method implemented in ImaGene can be affected by data manipulation and learning strategies. In particular, we show how sorting images by row and column leads to accurate predictions. We also demonstrate how the misspecification of the correct demographic model for producing training data can influence the quantification of positive selection. We finally illustrate an approach to estimate the selection coefficient, a continuous variable, using multiclass classification techniques.

CONCLUSIONS

While the use of deep learning in evolutionary genomics is in its infancy, here we demonstrated its potential to detect informative patterns from large-scale genomic data. We implemented methods to process genomic data for deep learning in a user-friendly program called ImaGene. The joint inference of the evolutionary history of mutations and their functional impact will facilitate mapping studies and provide novel insights into the molecular mechanisms associated with human phenotypes.

Tuberculosis and impaired IL-23-dependent IFN-γ immunity in humans homozygous for a common TYK2 missense variant

Inherited IL-12Rβ1 and TYK2 deficiencies impair both IL-12- and IL-23-dependent IFN-γ immunity and are rare monogenic causes of tuberculosis, each found in less than 1/600,000 individuals. We show that homozygosity for the common TYK2 P1104A allele, which is found in about 1/600 Europeans and between 1/1000 and 1/10,000 individuals in regions other than East Asia, is more frequent in a cohort of patients with tuberculosis from endemic areas than in ethnicity-adjusted controls (P = 8.37 × 10^-8; odds ratio, 89.31; 95% CI, 14.7 to 1725). Moreover, the frequency of P1104A in Europeans has decreased, from about 9% to 4.2%, over the past 4000 years, consistent with purging of this variant by endemic tuberculosis. Surprisingly, we also show that TYK2 P1104A impairs cellular responses to IL-23, but not to IFN-α, IL-10, or even IL-12, which, like IL-23, induces IFN-γ via activation of TYK2 and JAK2. Moreover, TYK2 P1104A is properly docked on cytokine receptors and can be phosphorylated by the proximal JAK, but lacks catalytic activity. Last, we show that the catalytic activity of TYK2 is essential for IL-23, but not IL-12, responses in cells expressing wild-type JAK2. In contrast, the catalytic activity of JAK2 is redundant for both IL-12 and IL-23 responses, because the catalytically inactive P1057A JAK2, which is also docked and phosphorylated, rescues signaling in cells expressing wild-type TYK2. In conclusion, homozygosity for the catalytically inactive P1104A missense variant of TYK2 selectively disrupts the induction of IFN-γ by IL-23 and is a common monogenic etiology of tuberculosis.

Stereotypic Immune System Development in Newborn Children

Epidemiological data suggest that early life exposures are key determinants of immune-mediated disease later in life. Young children are also particularly susceptible to infections, warranting more analyses of immune system development early in life. Such analyses mostly have been performed in mouse models or human cord blood samples, but these cannot account for the complex environmental exposures influencing human newborns after birth. Here, we performed longitudinal analyses in 100 newborn children, sampled up to 4 times during their first 3 months of life. From 100 μL of blood, we analyze the development of 58 immune cell populations by mass cytometry and 267 plasma proteins by immunoassays, uncovering drastic changes not predictable from cord blood measurements but following a stereotypic pattern. Preterm and term children differ at birth but converge onto a shared trajectory, seemingly driven by microbial interactions and hampered by early gut bacterial dysbiosis.

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Cord blood is not representative of postnatal immunity

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Preterm and term children differ at birth but rapidly converge thereafter

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Immune system development follows a stereotypic pattern early in life

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Dynamic parameters imply microbial interactions during early immune development

Detecting Signatures of Positive Selection along Defined Branches of a Population Tree Using LSD

Identifying the genomic basis underlying local adaptation is paramount to evolutionary biology, and bears many applications in the fields of conservation biology, crop, and animal breeding, as well as personalized medicine. Although many approaches have been developed to detect signatures of positive selection within single populations and population pairs, the increasing wealth of high-throughput sequencing data requires improved methods capable of handling multiple, and ideally large number of, populations in a single analysis. In this study, we introduce LSD (levels of exclusively shared differences), a fast and flexible framework to perform genome-wide selection scans, along the internal and external branches of a given population tree. We use forward simulations to demonstrate that LSD can identify branches targeted by positive selection with remarkable sensitivity and specificity. We illustrate a range of potential applications by analyzing data from the 1000 Genomes Project and uncover a list of adaptive candidates accompanying the expansion of anatomically modern humans out of Africa and their spread to Europe.

A locus on chromosome 5 shows African ancestry-limited association with alloimmunization in sickle cell disease

Red blood cell (RBC) transfusion remains a critical therapeutic intervention in sickle cell disease (SCD); however, the apparent propensity of some patients to regularly develop RBC alloantibodies after transfusion presents a significant challenge to finding compatible blood for so-called alloimmunization responders. Predisposing genetic loci have long been thought to contribute to the responder phenomenon, but to date, no definitive loci have been identified. We undertook a genome-wide association study of alloimmunization responder status in 267 SCD multiple transfusion recipients, using genetic estimates of ancestral admixture to bolster our findings. Analyses revealed single nucleotide polymorphisms (SNPs) on chromosomes 2 and 5 approaching genome-wide significance (minimum P = 2.0 × 10-8 and 8.4 × 10-8, respectively), with local ancestry analysis demonstrating similar levels of admixture in responders and nonresponders at implicated loci. Association at chromosome 5 was nominally replicated in an independent cohort of 130 SCD transfusion recipients, with meta-analysis surpassing genome-wide significance (rs75853687, P meta = 6.6 × 10-9), and this extended to individuals forming multiple (>3) alloantibodies (P meta = 9.4 × 10-5). The associated variant is rare outside of African populations, and orthogonal genome-wide haplotype analyses, contingent on local ancestry, revealed genome-wide significant sharing of a ∼60-kb haplotype of African ancestry at the chromosome 5 locus (Bayes Factor = 4.95). This locus overlaps a putative cis-acting enhancer predicted to regulate transcription of ADRA1B and the lncRNA LINC01847, both members of larger ontologies associated with immune regulation. Our findings provide potential insights to the pathophysiology underlying the development of alloantibodies and implicate non-RBC ancestry-limited loci in the susceptibility to alloimmunization.

High Seroprevalence of Autoantibodies Typical of Autoimmune Liver Disease in Eastern Ethiopia: Is Chewing of Khat (Catha edulis) a Triggering Factor?

BACKGROUND

Recent studies have identified chewing of khat (Catha edulis) as an independent risk factor for liver injury; however, the pathogenetic mechanism remains poorly understood. Case series have found markers of autoimmune hepatitis in patients with khat-related liver disease, suggesting that khat chewing might trigger an autoimmune response. The aims of the present study were (i) to assess the prevalence of autoantibodies typical for autoimmune liver diseases in a healthy population in Ethiopia and (ii) to explore the hypothesis that khat usage triggers autoimmunity.

METHODS

Consenting adults (≥18 years) without known autoimmune disease or manifest liver disease were included. One-hundred-and-sixty-nine individuals with current khat use were compared to 104 individuals who never used khat. Seroprevalence of antinuclear (ANA), antismooth muscle (SMA), and antimitochondrial antibodies (AMA) were determined and compared between the groups using logistic regression models to adjust for age and sex.

RESULTS

Overall, 2.6% of the study subjects were positive for ANA, 15.4% for SMA, and 25.6% for AMA. When comparing khat users to nonusers, ANA was detected in 4.1% vs. 0% (p=0.047), SMA in 16.0% vs. 14.4% (p=0.730), and AMA in 24.9% vs. 26.9% (p=0.704). ANA was excluded from multivariable analysis since there was no seropositive in the reference group. After adjusting for sex and age, no significant association between khat use and SMA or AMA was found.

CONCLUSIONS

No association between khat usage and the seropresence of SMA or AMA was found, weakening the hypothesis that khat-related liver injury is mediated through autoimmune mechanisms. However, the seroprevalences of AMA and SMA were strikingly high in this Ethiopian population compared to global estimates, suggesting that diagnostic algorithms for autoimmune liver diseases developed in Europe and North America might lead to misdiagnosis of patients on the African continent.

Exploring the genetic basis of human population differences in DNA methylation and their causal impact on immune gene regulation

BACKGROUND

DNA methylation is influenced by both environmental and genetic factors and is increasingly thought to affect variation in complex traits and diseases. Yet, the extent of ancestry-related differences in DNA methylation, their genetic determinants, and their respective causal impact on immune gene regulation remain elusive.

RESULTS

We report extensive population differences in DNA methylation between 156 individuals of African and European descent, detected in primary monocytes that are used as a model of a major innate immunity cell type. Most of these differences (~ 70%) are driven by DNA sequence variants nearby CpG sites, which account for ~ 60% of the variance in DNA methylation. We also identify several master regulators of DNA methylation variation in trans, including a regulatory hub nearby the transcription factor-encoding CTCF gene, which contributes markedly to ancestry-related differences in DNA methylation. Furthermore, we establish that variation in DNA methylation is associated with varying gene expression levels following mostly, but not exclusively, a canonical model of negative associations, particularly in enhancer regions. Specifically, we find that DNA methylation highly correlates with transcriptional activity of 811 and 230 genes, at the basal state and upon immune stimulation, respectively. Finally, using a Bayesian approach, we estimate causal mediation effects of DNA methylation on gene expression in ~ 20% of the studied cases, indicating that DNA methylation can play an active role in immune gene regulation.

CONCLUSION

Using a system-level approach, our study reveals substantial ancestry-related differences in DNA methylation and provides evidence for their causal impact on immune gene regulation.

Gene expression variability across cells and species shapes innate immunity

As the first line of defence against pathogens, cells mount an innate immune response, which varies widely from cell to cell. The response must be potent but carefully controlled to avoid self-damage. How these constraints have shaped the evolution of innate immunity remains poorly understood. Here we characterize the innate immune response's transcriptional divergence between species and variability in expression among cells. Using bulk and single-cell transcriptomics in fibroblasts and mononuclear phagocytes from different species, challenged with immune stimuli, we map the architecture of the innate immune response. Transcriptionally diverging genes, including those that encode cytokines and chemokines, vary across cells and have distinct promoter structures. Conversely, genes that are involved in the regulation of this response, such as those that encode transcription factors and kinases, are conserved between species and display low cell-to-cell variability in expression. We suggest that this expression pattern, which is observed across species and conditions, has evolved as a mechanism for fine-tuned regulation to achieve an effective but balanced response.

Evolutionary and Medical Consequences of Archaic Introgression into Modern Human Genomes

The demographic history of anatomically modern humans (AMH) involves multiple migration events, population extinctions and genetic adaptations. As genome-wide data from complete genome sequencing becomes increasingly abundant and available even from extinct hominins, new insights of the evolutionary history of our species are discovered. It is currently known that AMH interbred with archaic hominins once they left the African continent. Current non-African human genomes carry fragments of archaic origin. This review focuses on the fitness consequences of archaic interbreeding in current human populations. We discuss new insights and challenges that researchers face when interpreting the potential impact of introgression on fitness and testing hypotheses about the role of selection within the context of health and disease.

Genetic and evolutionary determinants of human population variation in immune responses

Humans display remarkable immune response variation when exposed to identical immune challenges. However, our understanding of the genetic, evolutionary, and environmental factors that impact this inter-individual and inter-population immune response heterogeneity is still in its early days. In this review, we discuss three fundamental questions concerning the recent evolution of the human immune system: the degree to which individuals from different populations vary in their innate immune responses, the genetic variants accounting for such differences, and the evolutionary mechanisms that led to the establishment of these variants in modern human populations. We also discuss how past selective events might have contributed to the uneven distribution of immune-related disorders across populations.

Genetic ancestry and population differences in levels of inflammatory cytokines in women: Role for evolutionary selection and environmental factors

Selection pressure due to exposure to infectious pathogens endemic to Africa may explain distinct genetic variations in immune response genes. However, the impact of those genetic variations on human immunity remains understudied, especially within the context of modern lifestyles and living environments, which are drastically different from early humans in sub Saharan Africa. There are few data on population differences in constitutional immune environment, where genetic ancestry and environment are likely two primary sources of variation. In a study integrating genetic, molecular and epidemiologic data, we examined population differences in plasma levels of 14 cytokines involved in innate and adaptive immunity, including those implicated in chronic inflammation, and possible contributing factors to such differences, in 914 AA and 855 EA women. We observed significant differences in 7 cytokines, including higher plasma levels of CCL2, CCL11, IL4 and IL10 in EAs and higher levels of IL1RA and IFNα2 in AAs. Analyses of a wide range of demographic and lifestyle factors showed significant impact, with age, education level, obesity, smoking, and alcohol intake, accounting for some, but not all, observed population differences for the cytokines examined. Levels of two pro-inflammatory chemokines, CCL2 and CCL11, were strongly associated with percent of African ancestry among AAs. Through admixture mapping, the signal was pinpointed to local ancestry at 1q23, with fine-mapping analysis refined to the Duffy-null allele of rs2814778. In AA women, this variant was a major determinant of systemic levels of CCL2 (p = 1.1e-58) and CCL11 (p = 2.2e-110), accounting for 19% and 40% of the phenotypic variance, respectively. Our data reveal strong ancestral footprints in inflammatory chemokine regulation. The Duffy-null allele may indicate a loss of the buffering function for chemokine levels. The substantial immune differences by ancestry may have broad implications to health disparities between AA and EA populations.

Population Genetics and Natural Selection in Rheumatic Disease

Human genetic diversity is the result of population genetic forces. This genetic variation influences disease risk and contributes to health disparities. Natural selection is an important influence on human genetic variation. Because immune and inflammatory function genes are enriched for signals of positive selection, the prevalence of rheumatic disease-risk alleles seen in different populations is partially the result of differing selective pressures (eg, due to pathogens). This review summarizes the genetic regions associated with susceptibility to different rheumatic diseases and concomitant evidence for natural selection, including known agents of selection exerting selective pressure in these regions.

Genetic, Transcriptome, Proteomic, and Epidemiological Evidence for Blood-Brain Barrier Disruption and Polymicrobial Brain Invasion as Determinant Factors in Alzheimer's Disease

Diverse pathogens are detected in Alzheimer's disease (AD) brains. A bioinformatics survey showed that AD genome-wide association study (GWAS) genes (localized in bone marrow, immune locations and microglia) relate to multiple host/pathogen interactomes (Candida albicans, Cryptococcus neoformans, Bornavirus, Borrelia burgdorferri, cytomegalovirus, Ebola virus, HSV-1, HERV-W, HIV-1, Epstein-Barr, hepatitis C, influenza, Chlamydia pneumoniae, Porphyrymonas gingivalis, Helicobacter pylori, Toxoplasma gondii, Trypanosoma cruzi). These interactomes also relate to the AD hippocampal transcriptome and to plaque or tangle proteins. Upregulated AD hippocampal genes match those upregulated by multiple bacteria, viruses, fungi, or protozoa in immunocompetent cells. AD genes are enriched in GWAS datasets reflecting pathogen diversity, suggesting selection for pathogen resistance, as supported by the old age of AD patients, implying resistance to earlier infections. APOE4 is concentrated in regions of high parasitic burden and protects against childhood tropical infections and hepatitis C. Immune/inflammatory gain of function applies to APOE4, CR1, and TREM2 variants. AD genes are also expressed in the blood-brain barrier (BBB), which is disrupted by AD risk factors (age, alcohol, aluminum, concussion, cerebral hypoperfusion, diabetes, homocysteine, hypercholesterolemia, hypertension, obesity, pesticides, pollution, physical inactivity, sleep disruption, smoking) and by pathogens, directly or via olfactory routes to basal-forebrain BBB control centers. The BBB benefits from statins, NSAIDs, estrogen, melatonin, memantine, and the Mediterranean diet. Polymicrobial involvement is supported by upregulation of bacterial, viral, and fungal sensors/defenders in the AD brain, blood, or cerebrospinal fluid. AD serum amyloid-β autoantibodies may attenuate its antimicrobial effects favoring microbial survival and cerebral invasion leading to activation of neurodestructive immune/inflammatory processes, which may also be augmented by age-related immunosenescence. AD may thus respond to antibiotic, antifungal, or antiviral therapy.

Living in an adaptive world: Genomic dissection of the genus Homo and its immune response

More than a decade after the sequencing of the human genome, a deluge of genome-wide population data are generating a portrait of human genetic diversity at an unprecedented level of resolution. Genomic studies have provided new insight into the demographic and adaptive history of our species, Homo sapiens, including its interbreeding with other hominins, such as Neanderthals, and the ways in which natural selection, in its various guises, has shaped genome diversity. These studies, combined with functional genomic approaches, such as the mapping of expression quantitative trait loci, have helped to identify genes, functions, and mechanisms of prime importance for host survival and involved in phenotypic variation and differences in disease risk. This review summarizes new findings in this rapidly developing field, focusing on the human immune response. We discuss the importance of defining the genetic and evolutionary determinants driving immune response variation, and highlight the added value of population genomic approaches in settings relevant to immunity and infection.

Loss of CMAH during Human Evolution Primed the Monocyte-Macrophage Lineage toward a More Inflammatory and Phagocytic State

Humans and chimpanzees are more sensitive to endotoxin than are mice or monkeys, but any underlying differences in inflammatory physiology have not been fully described or understood. We studied innate immune responses in Cmah^-/- mice, emulating human loss of the gene encoding production of Neu5Gc, a major cell surface sialic acid. CMP-N-acetylneuraminic acid hydroxylase (CMAH) loss occurred ∼2-3 million years ago, after the common ancestor of humans and chimpanzees, perhaps contributing to speciation of the genus HomoCmah^-/- mice manifested a decreased survival in endotoxemia following bacterial LPS injection. Macrophages from Cmah^-/- mice secreted more inflammatory cytokines with LPS stimulation and showed more phagocytic activity. Macrophages and whole blood from Cmah^-/- mice also killed bacteria more effectively. Metabolic reintroduction of Neu5Gc into Cmah^-/- macrophages suppressed these differences. Cmah^-/- mice also showed enhanced bacterial clearance during sublethal lung infection. Although monocytes and monocyte-derived macrophages from humans and chimpanzees exhibited marginal differences in LPS responses, human monocyte-derived macrophages killed Escherichia coli and ingested E. coli BioParticles better. Metabolic reintroduction of Neu5Gc into human macrophages suppressed these differences. Although multiple mechanisms are likely involved, one cause is altered expression of C/EBPβ, a transcription factor affecting macrophage function. Loss of Neu5Gc in Homo likely had complex effects on immunity, providing greater capabilities to clear sublethal bacterial challenges, possibly at the cost of endotoxic shock risk. This trade-off may have provided a selective advantage when Homo transitioned to butchery using stone tools. The findings may also explain why the Cmah^-/- state alters severity in mouse models of human disease.

Genetic Ancestry and Natural Selection Drive Population Differences in Immune Responses to Pathogens

Individuals from different populations vary considerably in their susceptibility to immune-related diseases. To understand how genetic variation and natural selection contribute to these differences, we tested for the effects of African versus European ancestry on the transcriptional response of primary macrophages to live bacterial pathogens. A total of 9.3% of macrophage-expressed genes show ancestry-associated differences in the gene regulatory response to infection, and African ancestry specifically predicts a stronger inflammatory response and reduced intracellular bacterial growth. A large proportion of these differences are under genetic control: for 804 genes, more than 75% of ancestry effects on the immune response can be explained by a single cis- or trans-acting expression quantitative trait locus (eQTL). Finally, we show that genetic effects on the immune response are strongly enriched for recent, population-specific signatures of adaptation. Together, our results demonstrate how historical selective events continue to shape human phenotypic diversity today, including for traits that are key to controlling infection.

Genetic Adaptation and Neandertal Admixture Shaped the Immune System of Human Populations

Humans differ in the outcome that follows exposure to life-threatening pathogens, yet the extent of population differences in immune responses and their genetic and evolutionary determinants remain undefined. Here, we characterized, using RNA sequencing, the transcriptional response of primary monocytes from Africans and Europeans to bacterial and viral stimuli-ligands activating Toll-like receptor pathways (TLR1/2, TLR4, and TLR7/8) and influenza virus-and mapped expression quantitative trait loci (eQTLs). We identify numerous cis-eQTLs that contribute to the marked differences in immune responses detected within and between populations and a strong trans-eQTL hotspot at TLR1 that decreases expression of pro-inflammatory genes in Europeans only. We find that immune-responsive regulatory variants are enriched in population-specific signals of natural selection and show that admixture with Neandertals introduced regulatory variants into European genomes, affecting preferentially responses to viral challenges. Together, our study uncovers evolutionarily important determinants of differences in host immune responsiveness between human populations.

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.

The burden of multiple sclerosis variants in continental Italians and Sardinians

BACKGROUND

Recent studies identified > 100 non-HLA (human leukocyte antigen) multiple sclerosis (MS) susceptibility variants in Northern European populations, but their role in Southern Europeans is largely unexplored.

OBJECTIVE

We aimed to investigate the cumulative impact of those variants in two Mediterranean populations: Continental Italians and Sardinians.

METHODS

We calculated four weighted Genetic Risk Scores (wGRS), using up to 102 non-HLA MS risk variants and 5 HLA MS susceptibility markers in 1691 patients and 2194 controls from continental Italy; and 2861 patients and 3034 controls from Sardinia. We then assessed the differences between populations using Nagelkerke's R(2) and the area under the Receiver Operating Characteristic (ROC) curves.

RESULTS

As expected, the genetic burden (mean wGRS value) was significantly higher in MS patients than in controls, in both populations. Of note, the burden was significantly higher in Sardinians. Conversely, the proportion of variability explained and the predictive power were significantly higher in continental Italians. Notably, within the Sardinian patients, we also observed a significantly higher burden of non-HLA variants in individuals who do not carry HLA risk alleles.

CONCLUSIONS

The observed differences in MS genetic burden between the two Mediterranean populations highlight the need for more genetic studies in South Europeans, to further expand the knowledge of MS genetics.