Human T-bet Governs Innate and Innate-like Adaptive IFN-γ Immunity against Mycobacteria.

Inborn errors of human interferon gamma (IFN-γ) immunity underlie mycobacterial disease. We report a patient with mycobacterial disease due to inherited deficiency of the transcription factor T-bet. The patient has extremely low counts of circulating Mycobacterium-reactive natural killer (NK), invariant NKT (iNKT), mucosal-associated invariant T (MAIT), and Vδ2+ γδ T lymphocytes, and of Mycobacterium-non reactive classic TH1 lymphocytes, with the residual populations of these cells also producing abnormally small amounts of IFN-γ. Other lymphocyte subsets develop normally but produce low levels of IFN-γ, with the exception of CD8+ αß T and non-classic CD4+ αß TH1∗ lymphocytes, which produce IFN-γ normally in response to mycobacterial antigens. Human T-bet deficiency thus underlies mycobacterial disease by preventing the development of innate (NK) and innate-like adaptive lymphocytes (iNKT, MAIT, and Vδ2+ γδ T cells) and IFN-γ production by them, with mycobacterium-specific, IFN-γ-producing, purely adaptive CD8+ αß T, and CD4+ αß TH1∗ cells unable to compensate for this deficit.

Human Immunology through the Lens of Evolutionary Genetics.

Pathogen-imposed selection pressures have been paramount during human evolution. Detecting such selection signatures in ancient and modern human genomes can thus help us to identify genes of temporal and spatial immunological relevance. Admixture with ancient hominins and between human populations has been a source of genetic diversity open to selection by infections. Furthermore, cultural transitions, such as the advent of agriculture, have exposed humans to new microbial threats, with impacts on host defense mechanisms. The integration of population genetics and systems immunology holds great promise for the increased understanding of the factors driving immune response variation between individuals and populations.

Human TLRs and IL-1Rs in host defense: natural insights from evolutionary, epidemiological, and clinical genetics.

Toll-like receptors (TLRs) and interleukin-1 receptors (IL-1Rs) have TIR intracellular domains that engage two main signaling pathways, via the TIR-containing adaptors MyD88 (which is not used by TLR3) and TRIF (which is used only by TLR3 and TLR4). Extensive studies in inbred mice in various experimental settings have attributed key roles in immunity to TLR- and IL-1R-mediated responses, but what contribution do human TLRs and IL-1Rs actually make to host defense in the natural setting? Evolutionary genetic studies have shown that human intracellular TLRs have evolved under stronger purifying selection than surface-expressed TLRs, for which the frequency of missense and nonsense alleles is high in the general population. Epidemiological genetic studies have yet to provide convincing evidence of a major contribution of common variants of human TLRs, IL-1Rs, or their adaptors to host defense. Clinical genetic studies have revealed that rare mutations affecting the TLR3-TRIF pathway underlie herpes simplex virus encephalitis, whereas mutations in the TIR-MyD88 pathway underlie pyogenic bacterial diseases in childhood. A careful reconsideration of the contributions of TLRs and IL-1Rs to host defense in natura is required.

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.

Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors.

The quantification and characterization of circulating immune cells provide key indicators of human health and disease. To identify the relative effects of environmental and genetic factors on variation in the parameters of innate and adaptive immune cells in homeostatic conditions, we combined standardized flow cytometry of blood leukocytes and genome-wide DNA genotyping of 1,000 healthy, unrelated people of Western European ancestry. We found that smoking, together with age, sex and latent infection with cytomegalovirus, were the main non-genetic factors that affected variation in parameters of human immune cells. Genome-wide association studies of 166 immunophenotypes identified 15 loci that showed enrichment for disease-associated variants. Finally, we demonstrated that the parameters of innate cells were more strongly controlled by genetic variation than were those of adaptive cells, which were driven by mainly environmental exposure. Our data establish a resource that will generate new hypotheses in immunology and highlight the role of innate immunity in susceptibility to common autoimmune diseases.

Publisher Correction: Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors.

In the version of this article initially published, the name of one author was incorrect (James P. Santo). The correct name is James P. Di Santo. The error has been corrected in the HTML and PDF versions of the article.

Smoking changes adaptive immunity with persistent effects.

Individuals differ widely in their immune responses, with age, sex and genetic factors having major roles in this inherent variability1-6. However, the variables that drive such differences in cytokine secretion-a crucial component of the host response to immune challenges-remain poorly defined. Here we investigated 136 variables and identified smoking, cytomegalovirus latent infection and body mass index as major contributors to variability in cytokine response, with effects of comparable magnitudes with age, sex and genetics. We find that smoking influences both innate and adaptive immune responses. Notably, its effect on innate responses is quickly lost after smoking cessation and is specifically associated with plasma levels of CEACAM6, whereas its effect on adaptive responses persists long after individuals quit smoking and is associated with epigenetic memory. This is supported by the association of the past smoking effect on cytokine responses with DNA methylation at specific signal trans-activators and regulators of metabolism. Our findings identify three novel variables associated with cytokine secretion variability and reveal roles for smoking in the short- and long-term regulation of immune responses. These results have potential clinical implications for the risk of developing infections, cancers or autoimmune diseases.

Dissecting human population variation in single-cell responses to SARS-CoV-2.

Humans display substantial interindividual clinical variability after SARS-CoV-2 infection1-3, the genetic and immunological basis of which has begun to be deciphered4. However, the extent and drivers of population differences in immune responses to SARS-CoV-2 remain unclear. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells-from 222 healthy donors of diverse ancestries-that were stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces weaker, but more heterogeneous, interferon-stimulated gene activity compared with influenza A virus, and a unique pro-inflammatory signature in myeloid cells. Transcriptional responses to viruses display marked population differences, primarily driven by changes in cell abundance including increased lymphoid differentiation associated with latent cytomegalovirus infection. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell composition on population disparities in immune responses, with genetic variants exerting a strong effect on specific loci. Furthermore, we show that natural selection has increased population differences in immune responses, particularly for variants associated with SARS-CoV-2 response in East Asians, and document the cellular and molecular mechanisms by which Neanderthal introgression has altered immune functions, such as the response of myeloid cells to viruses. Finally, colocalization and transcriptome-wide association analyses reveal an overlap between the genetic basis of immune responses to SARS-CoV-2 and COVID-19 severity, providing insights into the factors contributing to current disparities in COVID-19 risk.

Genomic insights into population history and biological adaptation in Oceania.

The Pacific region is of major importance for addressing questions regarding human dispersals, interactions with archaic hominins and natural selection processes1. However, the demographic and adaptive history of Oceanian populations remains largely uncharacterized. Here we report high-coverage genomes of 317 individuals from 20 populations from the Pacific region. We find that the ancestors of Papuan-related ('Near Oceanian') groups underwent a strong bottleneck before the settlement of the region, and separated around 20,000-40,000 years ago. We infer that the East Asian ancestors of Pacific populations may have diverged from Taiwanese Indigenous peoples before the Neolithic expansion, which is thought to have started from Taiwan around 5,000 years ago2-4. Additionally, this dispersal was not followed by an immediate, single admixture event with Near Oceanian populations, but involved recurrent episodes of genetic interactions. Our analyses reveal marked differences in the proportion and nature of Denisovan heritage among Pacific groups, suggesting that independent interbreeding with highly structured archaic populations occurred. Furthermore, whereas introgression of Neanderthal genetic information facilitated the adaptation of modern humans related to multiple phenotypes (for example, metabolism, pigmentation and neuronal development), Denisovan introgression was primarily beneficial for immune-related functions. Finally, we report evidence of selective sweeps and polygenic adaptation associated with pathogen exposure and lipid metabolism in the Pacific region, increasing our understanding of the mechanisms of biological adaptation to island environments.

MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data.

Multivariate analysis is becoming central in studies investigating high-throughput molecular data, yet, some important features of these data are seldom explored. Here, we present MANOCCA (Multivariate Analysis of Conditional CovAriance), a powerful method to test for the effect of a predictor on the covariance matrix of a multivariate outcome. The proposed test is by construction orthogonal to tests based on the mean and variance and is able to capture effects that are missed by both approaches. We first compare the performances of MANOCCA with existing correlation-based methods and show that MANOCCA is the only test correctly calibrated in simulation mimicking omics data. We then investigate the impact of reducing the dimensionality of the data using principal component analysis when the sample size is smaller than the number of pairwise covariance terms analysed. We show that, in many realistic scenarios, the maximum power can be achieved with a limited number of components. Finally, we apply MANOCCA to 1000 healthy individuals from the Milieu Interieur cohort, to assess the effect of health, lifestyle and genetic factors on the covariance of two sets of phenotypes, blood biomarkers and flow cytometry-based immune phenotypes. Our analyses identify significant associations between multiple factors and the covariance of both omics data.

High-throughput droplet-based analysis of influenza A virus genetic reassortment by single-virus RNA sequencing.

The segmented RNA genome of influenza A viruses (IAVs) enables viral evolution through genetic reassortment after multiple IAVs coinfect the same cell, leading to viruses harboring combinations of eight genomic segments from distinct parental viruses. Existing data indicate that reassortant genotypes are not equiprobable; however, the low throughput of available virology techniques does not allow quantitative analysis. Here, we have developed a high-throughput single-cell droplet microfluidic system allowing encapsulation of IAV-infected cells, each cell being infected by a single progeny virion resulting from a coinfection process. Customized barcoded primers for targeted viral RNA sequencing enabled the analysis of 18,422 viral genotypes resulting from coinfection with two circulating human H1N1pdm09 and H3N2 IAVs. Results were highly reproducible, confirmed that genetic reassortment is far from random, and allowed accurate quantification of reassortants including rare events. In total, 159 out of the 254 possible reassortant genotypes were observed but with widely varied prevalence (from 0.038 to 8.45%). In cells where eight segments were detected, all 112 possible pairwise combinations of segments were observed. The inclusion of data from single cells where less than eight segments were detected allowed analysis of pairwise cosegregation between segments with very high confidence. Direct coupling analysis accurately predicted the fraction of pairwise segments and full genotypes. Overall, our results indicate that a large proportion of reassortant genotypes can emerge upon coinfection and be detected over a wide range of frequencies, highlighting the power of our tool for systematic and exhaustive monitoring of the reassortment potential of IAVs.

The genomic signatures of natural selection in admixed human populations.

Admixture has been a pervasive phenomenon in human history, extensively shaping the patterns of population genetic diversity. There is increasing evidence to suggest that admixture can also facilitate genetic adaptation to local environments, i.e., admixed populations acquire beneficial mutations from source populations, a process that we refer to as "adaptive admixture." However, the role of adaptive admixture in human evolution and the power to detect it remain poorly characterized. Here, we use extensive computer simulations to evaluate the power of several neutrality statistics to detect natural selection in the admixed population, assuming multiple admixture scenarios. We show that statistics based on admixture proportions, Fadm and LAD, show high power to detect mutations that are beneficial in the admixed population, whereas other statistics, including iHS and FST, falsely detect neutral mutations that have been selected in the source populations only. By combining Fadm and LAD into a single, powerful statistic, we scanned the genomes of 15 worldwide, admixed populations for signatures of adaptive admixture. We confirm that lactase persistence and resistance to malaria have been under adaptive admixture in West Africans and in Malagasy, North Africans, and South Asians, respectively. Our approach also uncovers other cases of adaptive admixture, including APOL1 in Fulani nomads and PKN2 in East Indonesians, involved in resistance to infection and metabolism, respectively. Collectively, our study provides evidence that adaptive admixture has occurred in human populations whose genetic history is characterized by periods of isolation and spatial expansions resulting in increased gene flow.

Human ancient DNA analyses reveal the high burden of tuberculosis in Europeans over the last 2,000 years.

Tuberculosis (TB), usually caused by Mycobacterium tuberculosis bacteria, is the first cause of death from an infectious disease at the worldwide scale, yet the mode and tempo of TB pressure on humans remain unknown. The recent discovery that homozygotes for the P1104A polymorphism of TYK2 are at higher risk to develop clinical forms of TB provided the first evidence of a common, monogenic predisposition to TB, offering a unique opportunity to inform on human co-evolution with a deadly pathogen. Here, we investigate the history of human exposure to TB by determining the evolutionary trajectory of the TYK2 P1104A variant in Europe, where TB is considered to be the deadliest documented infectious disease. Leveraging a large dataset of 1,013 ancient human genomes and using an approximate Bayesian computation approach, we find that the P1104A variant originated in the common ancestors of West Eurasians ∼30,000 years ago. Furthermore, we show that, following large-scale population movements of Anatolian Neolithic farmers and Eurasian steppe herders into Europe, P1104A has markedly fluctuated in frequency over the last 10,000 years of European history, with a dramatic decrease in frequency after the Bronze Age. Our analyses indicate that such a frequency drop is attributable to strong negative selection starting ∼2,000 years ago, with a relative fitness reduction on homozygotes of 20%, among the highest in the human genome. Together, our results provide genetic evidence that TB has imposed a heavy burden on European health over the last two millennia.

Impact of socioeconomic status on healthy immune responses in humans.

Individuals with low socioeconomic status (SES) are at greater risk of contracting and developing severe disease compared with people with higher SES. Age, sex, host genetics, smoking and cytomegalovirus (CMV) serostatus are known to have a major impact on human immune responses and thus susceptibility to infection. However, the impact of SES on immune variability is not well understood or explored. Here, we used data from the Milieu Intérieur project, a study of 1000 healthy volunteers with extensive demographic and biological data, to examine the effect of SES on immune variability. We developed an Elo-rating system using socioeconomic features such as education, income and home ownership status to objectively rank SES in the 1000 donors. We observed sex-specific SES associations, such as females with a low SES having a significantly higher frequency of CMV seropositivity compared with females with high SES, and males with a low SES having a significantly higher frequency of active smoking compared with males with a high SES. Using random forest models, we identified specific immune genes which were significantly associated with SES in both baseline and immune challenge conditions. Interestingly, many of the SES associations were sex stimuli specific, highlighting the complexity of these interactions. Our study provides a new way of computing SES in human populations that can help identify novel SES associations and reinforces biological evidence for SES-dependent susceptibility to infection. This should serve as a basis for further understanding the molecular mechanisms behind SES effects on immune responses and ultimately disease.

Standardized high-dimensional spectral cytometry protocol and panels for whole blood immune phenotyping in clinical and translational studies.

Flow cytometry is the method of choice for immunophenotyping in the context of clinical, translational, and systems immunology studies. Among the latter, the Milieu Intérieur (MI) project aims at defining the boundaries of a healthy immune response to identify determinants of immune response variation. MI used immunophenotyping of a 1000 healthy donor cohort by flow cytometry as a principal outcome for immune variance at steady state. New generation spectral cytometers now enable high-dimensional immune cell characterization from small sample volumes. Therefore, for the MI 10-year follow up study, we have developed two high-dimensional spectral flow cytometry panels for deep characterization of innate and adaptive whole blood immune cells (35 and 34 fluorescent markers, respectively). We have standardized the protocol for sample handling, staining, acquisition, and data analysis. This approach enables the reproducible quantification of over 182 immune cell phenotypes at a single site. We have applied the protocol to discern minor differences between healthy and patient samples and validated its value for application in immunomonitoring studies. Our protocol is currently used for characterization of the impact of age and environmental factors on peripheral blood immune phenotypes of >400 donors from the initial MI cohort.

Negative selection on human genes underlying inborn errors depends on disease outcome and both the mode and mechanism of inheritance.

Genetic variants underlying life-threatening diseases, being unlikely to be transmitted to the next generation, are gradually and selectively eliminated from the population through negative selection. We study the determinants of this evolutionary process in human genes underlying monogenic diseases by comparing various negative selection scores and an integrative approach, CoNeS, at 366 loci underlying inborn errors of immunity (IEI). We find that genes underlying autosomal dominant (AD) or X-linked IEI have stronger negative selection scores than those underlying autosomal recessive (AR) IEI, whose scores are not different from those of genes not known to be disease causing. Nevertheless, genes underlying AR IEI that are lethal before reproductive maturity with complete penetrance have stronger negative selection scores than other genes underlying AR IEI. We also show that genes underlying AD IEI by loss of function have stronger negative selection scores than genes underlying AD IEI by gain of function, while genes underlying AD IEI by haploinsufficiency are under stronger negative selection than other genes underlying AD IEI. These results are replicated in 1,140 genes underlying inborn errors of neurodevelopment. Finally, we propose a supervised classifier, SCoNeS, which predicts better than state-of-the-art approaches whether a gene is more likely to underlie an AD or AR disease. The clinical outcomes of monogenic inborn errors, together with their mode and mechanisms of inheritance, determine the levels of negative selection at their corresponding loci. Integrating scores of negative selection may facilitate the prioritization of candidate genes and variants in patients suspected to carry an inborn error.

Functional analysis via standardized whole-blood stimulation systems defines the boundaries of a healthy immune response to complex stimuli.

Standardization of immunophenotyping procedures has become a high priority. We have developed a suite of whole-blood, syringe-based assay systems that can be used to reproducibly assess induced innate or adaptive immune responses. By eliminating preanalytical errors associated with immune monitoring, we have defined the protein signatures induced by (1) medically relevant bacteria, fungi, and viruses; (2) agonists specific for defined host sensors; (3) clinically employed cytokines; and (4) activators of T cell immunity. Our results provide an initial assessment of healthy donor reference values for induced cytokines and chemokines and we report the failure to release interleukin-1α as a common immunological phenotype. The observed naturally occurring variation of the immune response may help to explain differential susceptibility to disease or response to therapeutic intervention. The implementation of a general solution for assessment of functional immune responses will help support harmonization of clinical studies and data sharing.

A genetic variant controls interferon-ß gene expression in human myeloid cells by preventing C/EBP-ß binding on a conserved enhancer.

Interferon ß (IFN-ß) is a cytokine that induces a global antiviral proteome, and regulates the adaptive immune response to infections and tumors. Its effects strongly depend on its level and timing of expression. Therefore, the transcription of its coding gene IFNB1 is strictly controlled. We have previously shown that in mice, the TRIM33 protein restrains Ifnb1 transcription in activated myeloid cells through an upstream inhibitory sequence called ICE. Here, we show that the deregulation of Ifnb1 expression observed in murine Trim33-/- macrophages correlates with abnormal looping of both ICE and the Ifnb1 gene to a 100 kb downstream region overlapping the Ptplad2/Hacd4 gene. This region is a predicted myeloid super-enhancer in which we could characterize 3 myeloid-specific active enhancers, one of which (E5) increases the response of the Ifnb1 promoter to activation. In humans, the orthologous region contains several single nucleotide polymorphisms (SNPs) known to be associated with decreased expression of IFNB1 in activated monocytes, and loops to the IFNB1 gene. The strongest association is found for the rs12553564 SNP, located in the E5 orthologous region. The minor allele of rs12553564 disrupts a conserved C/EBP-ß binding motif, prevents binding of C/EBP-ß, and abolishes the activation-induced enhancer activity of E5. Altogether, these results establish a link between a genetic variant preventing binding of a transcription factor and a higher order phenotype, and suggest that the frequent minor allele (around 30% worldwide) might be associated with phenotypes regulated by IFN-ß expression in myeloid cells.