The Legacy of Past Pandemics: Common Human Mutations That Protect against Infectious Disease

The paleopathology and paleoepidemiology of Upper paleolithic tuberculosis: Review of evidence and hypotheses

Molecular phylogeny work has shown that tuberculosis is ancient human-adapted infection predating the Neolithic period. They also show that the Upper Paleolithic is a key period of emergence of the MTB complex strains, contemporary with the exit of modern man from Africa. Despite the richness of Upper Paleolithic sites in Eurasia and the relative abundance of human remains, the only proven case of Paleolithic tuberculosis has been described so far date from the Azilian, a culture of the European Final Paleolithic, which is more recent than the ancient Neolithic sites of the Near East, area that currently hold the record for the oldest paleopathological evidence of tuberculosis. The purpose of this review is to present evidence for the existence of tuberculosis in the Paleolithic and to list hypotheses explaining the weak demonstrative contribution of paleopathology for pre-Neolithic periods.

Rickettsia felis DNA recovered from a child who lived in southern Africa 2000 years ago

The Stone Age record of South Africa provides some of the earliest evidence for the biological and cultural origins of Homo sapiens. While there is extensive genomic evidence for the selection of polymorphisms in response to pathogen-pressure in sub-Saharan Africa, e.g., the sickle cell trait which provides protection against malaria, there is inadequate direct human genomic evidence for ancient human-pathogen infection in the region. Here, we analysed shotgun metagenome libraries derived from the sequencing of a Later Stone Age hunter-gatherer child who lived near Ballito Bay, South Africa, c. 2000 years ago. This resulted in the identification of ancient DNA sequence reads homologous to Rickettsia felis, the causative agent of typhus-like flea-borne rickettsioses, and the reconstruction of an ancient R. felis genome.

Single-cell genome-wide association reveals that a nonsynonymous variant in ERAP1 confers increased susceptibility to influenza virus

During pandemics, individuals exhibit differences in risk and clinical outcomes. Here, we developed single-cell high-throughput human in vitro susceptibility testing (scHi-HOST), a method for rapidly identifying genetic variants that confer resistance and susceptibility. We applied this method to influenza A virus (IAV), the cause of four pandemics since the start of the 20th century. scHi-HOST leverages single-cell RNA sequencing (scRNA-seq) to simultaneously assign genetic identity to cells in mixed infections of cell lines of European, African, and Asian origin, reveal associated genetic variants for viral burden, and identify expression quantitative trait loci. Integration of scHi-HOST with human challenge and experimental validation demonstrated that a missense variant in endoplasmic reticulum aminopeptidase 1 (ERAP1; rs27895) increased IAV burden in cells and human volunteers. rs27895 exhibits population differentiation, likely contributing to greater permissivity of cells from African populations to IAV. scHi-HOST is a broadly applicable method and resource for decoding infectious-disease genetics.

A natural variant in ANP32B impairs influenza virus replication in human cells

Viruses require host factors to support their replication, and genetic variation in such factors can affect susceptibility to infectious disease. Influenza virus replication in human cells relies on ANP32 proteins, which are involved in assembly of replication-competent dimeric influenza virus polymerase (FluPol) complexes. Here, we investigate naturally occurring single nucleotide variants (SNV) in the human Anp32A and Anp32B genes. We note that variant rs182096718 in Anp32B is found at a higher frequency than other variants in either gene. This SNV results in a D130A substitution in ANP32B, which is less able to support FluPol activity than wild-type ANP32B and binds FluPol with lower affinity. Interestingly, ANP32B-D130A exerts a dominant negative effect over wild-type ANP32B and interferes with the functionally redundant paralogue ANP32A. FluPol activity and virus replication are attenuated in CRISPR-edited cells expressing wild-type ANP32A and mutant ANP32B-D130A. We propose a model in which the D130A mutation impairs FluPol dimer formation, thus resulting in compromised replication. We suggest that both homozygous and heterozygous carriers of rs182096718 may have some genetic protection against influenza viruses.

Evolution, Ecology, and Zoonotic Transmission of Betacoronaviruses: A Review

Coronavirus infections have been a part of the animal kingdom for millennia. The difference emerging in the twenty-first century is that a greater number of novel coronaviruses are being discovered primarily due to more advanced technology and that a greater number can be transmitted to humans, either directly or via an intermediate host. This has a range of effects from annual infections that are mild to full-blown pandemics. This review compares the zoonotic potential and relationship between MERS, SARS-CoV, and SARS-CoV-2. The role of bats as possible host species and possible intermediate hosts including pangolins, civets, mink, birds, and other mammals are discussed with reference to mutations of the viral genome affecting zoonosis. Ecological, social, cultural, and environmental factors that may play a role in zoonotic transmission are considered with reference to SARS-CoV, MERS, and SARS-CoV-2 and possible future zoonotic events.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

BACKGROUND

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.

RESULTS

Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.

CONCLUSIONS

Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .

Genetic factors affect the susceptibility to bacterial infections in diabetes

Diabetes increases the risk of bacterial infections. We investigated whether common genetic variants associate with infection susceptibility in Finnish diabetic individuals. We performed genome-wide association studies and pathway analysis for bacterial infection frequency in Finnish adult diabetic individuals (FinnDiane Study; N = 5092, Diabetes Registry Vaasa; N = 4247) using national register data on antibiotic prescription purchases. Replication analyses were performed in a Swedish diabetic population (ANDIS; N = 9602) and in a Finnish non-diabetic population (FinnGen; N = 159,166). Genome-wide data indicated moderate but significant narrow-sense heritability for infection susceptibility (h² = 16%, P = 0.02). Variants on chromosome 2 were associated with reduced infection susceptibility (rs62192851, P = 2.23 × 10^–7). Homozygotic carriers of the rs62192851 effect allele (N = 44) had a 37% lower median annual antibiotic purchase rate, compared to homozygotic carriers of the reference allele (N = 4231): 0.38 [IQR 0.22–0.90] and 0.60 [0.30–1.20] respectively, P = 0.01). Variants rs6727834 and rs10188087, in linkage disequilibrium with rs62192851, replicated in the FinnGen-cohort (P < 0.05), but no variants replicated in the ANDIS-cohort. Pathway analysis suggested the IRAK1 mediated NF-κB activation through IKK complex recruitment-pathway to be a mediator of the phenotype. Common genetic variants on chromosome 2 may associate with reduced risk of bacterial infections in Finnish individuals with diabetes.

Molecular Evolution of Transition Metal Bioavailability at the Host-Pathogen Interface

The molecular evolution of the adaptive response at the host-pathogen interface has been frequently referred to as an 'arms race' between the host and bacterial pathogens. The innate immune system employs multiple strategies to starve microbes of metals. Pathogens, in turn, develop successful strategies to maintain access to bioavailable metal ions under conditions of extreme restriction of transition metals, or nutritional immunity. However, the processes by which evolution repurposes or re-engineers host and pathogen proteins to perform or refine new functions have been explored only recently. Here we review the molecular evolution of several human metalloproteins charged with restricting bacterial access to transition metals. These include the transition metal-chelating S100 proteins, natural resistance-associated macrophage protein-1 (NRAMP-1), transferrin, lactoferrin, and heme-binding proteins. We examine their coevolution with bacterial transition metal acquisition systems, involving siderophores and membrane-spanning metal importers, and the biological specificity of allosteric transcriptional regulatory proteins tasked with maintaining bacterial metallostasis. We also discuss the evolution of metallo-β-lactamases; this illustrates how rapid antibiotic-mediated evolution of a zinc metalloenzyme obligatorily occurs in the context of host-imposed nutritional immunity.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches.

Low iron mitigates viral survival: insights from evolution, genetics, and pandemics-a review of current hypothesis

Background

Upon re-examination of our human history, evolutionary perspectives, and genetics, a prevailing iron deficiency phenotype appears to have evolved to protect the human race from extinction.

Body

In this review, we summarize the evolutionary and genetic perspectives pointing towards the hypothesis that low iron mitigates infection. The presence of infection promotes the generation of resistance alleles, and there are some evolutionary and genetic clues that suggest the presence of an iron deficiency phenotype that may have developed to protect against infection. Examples include the relative paucity of iron overload genes given the essential role of iron, as well as the persistence of iron deficiency among populations in spite of public health efforts to treat it. Additional examination of geographic areas with severe iron deficiency in the setting of pandemics including H1N1, SARS, and COVID-19 reveals that areas with higher prevalence of iron deficiency are less affected. RNA viruses have several evolutionary adaptations which suggest their absolute need for iron, and this dependency may be exploited during treatment.

Conclusion

RNA viruses pose a unique challenge to modern healthcare, with an average of 2-3 new pathogens being discovered yearly. Their overarching requirements for iron, along with human evolutionary and genetic adaptations which favored an iron deficiency phenotype, ultimately suggest the potential need for iron control in these infections.

Diversity of HLA Class I and Class II blocks and conserved extended haplotypes in Lacandon Mayans

Here we studied HLA blocks and haplotypes in a group of 218 Lacandon Maya Native American using a high-resolution next generation sequencing (NGS) method. We assessed the genetic diversity of HLA class I and class II in this population, and determined the most probable ancestry of Lacandon Maya HLA class I and class II haplotypes. Importantly, this Native American group showed a high degree of both HLA homozygosity and linkage disequilibrium across the HLA region and also lower class II HLA allelic diversity than most previously reported populations (including other Native American groups). Distinctive alleles present in the Lacandon population include HLA-A*24:14 and HLA-B*40:08. Furthermore, in Lacandons we observed a high frequency of haplotypes containing the allele HLA-DRB1*04:11, a relatively frequent allele in comparison with other neighboring indigenous groups. The specific demographic history of the Lacandon population including inbreeding, as well as pathogen selection, may have elevated the frequencies of a small number of HLA class II alleles and DNA blocks. To assess the possible role of different selective pressures in determining Native American HLA diversity, we evaluated the relationship between genetic diversity at HLA-A, HLA-B and HLA-DRB1 and pathogen richness for a global dataset and for Native American populations alone. In keeping with previous studies of such relationships we included distance from Africa as a covariate. After correction for multiple comparisons we did not find any significant relationship between pathogen diversity and HLA genetic diversity (as measured by polymorphism information content) in either our global dataset or the Native American subset of the dataset. We found the expected negative relationship between genetic diversity and distance from Africa in the global dataset, but no relationship between HLA genetic diversity and distance from Africa when Native American populations were considered alone.

Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.

Systematic detection of positive selection in the human-pathogen interactome and lasting effects on infectious disease susceptibility

Infectious disease has shaped the natural genetic diversity of humans throughout the world. A new approach to capture positive selection driven by pathogens would provide information regarding pathogen exposure in distinct human populations and the constantly evolving arms race between host and disease-causing agents. We created a human pathogen interaction database and used the integrated haplotype score (iHS) to detect recent positive selection in genes that interact with proteins from 26 different pathogens. We used the Human Genome Diversity Panel to identify specific populations harboring pathogen-interacting genes that have undergone positive selection. We found that human genes that interact with 9 pathogen species show evidence of recent positive selection. These pathogens are Yersenia pestis, human immunodeficiency virus (HIV) 1, Zaire ebolavirus, Francisella tularensis, dengue virus, human respiratory syncytial virus, measles virus, Rubella virus, and Bacillus anthracis. For HIV-1, GWAS demonstrate that some naturally selected variants in the host-pathogen protein interaction networks continue to have functional consequences for susceptibility to these pathogens. We show that selected human genes were enriched for HIV susceptibility variants (identified through GWAS), providing further support for the hypothesis that ancient humans were exposed to lentivirus pandemics. Human genes in the Italian, Miao, and Biaka Pygmy populations that interact with Y. pestis show significant signs of selection. These results reveal some of the genetic footprints created by pathogens in the human genome that may have left lasting marks on susceptibility to infectious disease.

Ancient oncogenesis, infection and human evolution

The recent discovery that malignant neoplastic lesions date back nearly 2 million years ago not only highlights the antiquity of cancer in the human lineage, but also provides remarkable insight into ancestral hominin disease pathology. Using these Early Pleistocene examples as a point of departure, we emphasize the prominent role of viral and bacterial pathogens in oncogenesis and evaluate the impact of pathogens on human evolutionary processes in Africa. In the Shakespearean vernacular "what's past is prologue," we highlight the significance of novel information derived from ancient pathogenic DNA. In particular, and given the temporal depth of human occupation in sub-Saharan Africa, it is emphasized that the region is ideally positioned to play a strategic role in the discovery of ancient pathogenic drivers of not only human mortality, but also human evolution. Ancient African pathogen genome data can provide novel revelations concerning human-pathogen coevolutionary processes, and such knowledge is essential for forecasting the ways in which emerging zoonotic and increasingly transmissible diseases might influence human demography and longevity in the future.

Why do Individuals Differ in Viral Susceptibility? A Story Told by Model Organisms

Viral susceptibility and disease progression is determined by host genetic variation that underlies individual differences. Genetic polymorphisms that affect the phenotype upon infection have been well-studied for only a few viruses, such as HIV-1 and Hepatitis C virus. However, even for well-studied viruses the genetic basis of individual susceptibility differences remains elusive. Investigating the effect of causal polymorphisms in humans is complicated, because genetic methods to detect rare or small-effect polymorphisms are limited and genetic manipulation is not possible in human populations. Model organisms have proven a powerful experimental platform to identify and characterize polymorphisms that underlie natural variations in viral susceptibility using quantitative genetic tools. We summarize and compare the genetic tools available in three main model organisms, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans, and illustrate how these tools can be applied to detect polymorphisms that determine the viral susceptibility. Finally, we analyse how candidate polymorphisms from model organisms can be used to shed light on the underlying mechanism of individual variation. Insights in causal polymorphisms and mechanisms underlying individual differences in viral susceptibility in model organisms likely provide a better understanding in humans.

Migrating microbes: what pathogens can tell us about population movements and human evolution

BACKGROUND

The biology of human migration can be observed from the co-evolutionary relationship with infectious diseases. While many pathogens are brief, unpleasant visitors to human bodies, others have the ability to become life-long human passengers. The story of a pathogen's genetic code may, therefore, provide insight into the history of its human host. The evolution and distribution of disease in Africa is of particular interest, because of the deep history of human evolution in Africa, the presence of a variety of non-human primates, and tropical reservoirs of emerging infectious diseases.

METHODS

This study explores which pathogens leave traces in the archaeological record, and whether there are realistic prospects that these pathogens can be recovered from sub-Saharan African archaeological contexts.

RESULTS

Three stories are then presented of germs on a journey. The first is the story of HIV's spread on the back of colonialism and the railway networks over the last 150 years. The second involves the spread of Schistosoma mansoni, a parasite which shares its history with the trans-Atlantic slave trade and the origins of fresh-water fishing. Finally, we discuss the tantalising hints of hominin migration and interaction found in the genome of human herpes simplex virus 2.

CONCLUSIONS

Evidence from modern African pathogen genomes can provide data on human behaviour and migration in deep time and contribute to the improvement of human quality-of-life and longevity.

Modelling idiopathic Parkinson disease as a complex illness can inform incidence rate in healthy adults: the PR EDIGT score

Fifty-five years after the concept of dopamine replacement therapy was introduced, Parkinson disease (PD) remains an incurable neurological disorder. To date, no disease-modifying therapeutic has been approved. The inability to predict PD incidence risk in healthy adults is seen as a limitation in drug development, because by the time of clinical diagnosis ≥ 60% of dopamine neurons have been lost. We have designed an incidence prediction model founded on the concept that the pathogenesis of PD is similar to that of many disorders observed in ageing humans, i.e. a complex, multifactorial disease. Our model considers five factors to determine cumulative incidence rates for PD in healthy adults: (i) DNA variants that alter susceptibility (D), e.g. carrying a LRRK2 or GBA risk allele; (ii) Exposure history to select environmental factors including xenobiotics (E); (iii) Gene-environment interactions that initiate pathological tissue responses (I), e.g. a rise in ROS levels, misprocessing of amyloidogenic proteins (foremost, α-synuclein) and dysregulated inflammation; (iv) sex (or gender; G); and importantly, (v) time (T) encompassing ageing-related changes, latency of illness and propagation of disease. We propose that cumulative incidence rates for PD (PR ) can be calculated in healthy adults, using the formula: PR (%) = (E + D + I) × G × T. Here, we demonstrate six case scenarios leading to young-onset parkinsonism (n = 3) and late-onset PD (n = 3). Further development and validation of this prediction model and its scoring system promise to improve subject recruitment in future intervention trials. Such efforts will be aimed at disease prevention through targeted selection of healthy individuals with a higher prediction score for developing PD in the future and at disease modification in subjects that already manifest prodromal signs.