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.

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.

Clinical, immunological, and genetic description of a Mexican cohort of patients with DOCK8 deficiency.

PURPOSE: We aimed to describe the clinical, immunological, and genetic features of patients with DOCK8 deficiency (DOCK8-Def) in a tertiary care center for children. METHODS: Retrospective chart review of patients' clinical, immunological, and genetic characteristics with DOCK8-Def. Genetic analysis was performed with targeted- or whole-exome sequencing; we also assessed DOCK8 protein expression and a lymphoproliferation assay and analyzed survival by the Kaplan-Meier method. RESULTS: We described 11 patients from 8 unrelated kindreds. The median age at symptoms' onset was 10 months (range 1-54 months). The median follow-up time was 53.4 months (4.8-118.8). All patients presented eczema and recurrent sinopulmonary and cutaneous infections. Besides those symptoms, the most frequent manifestations were bronchiectases (8/11), food allergies (6/11), and severe infections (6/11). Infrequent characteristics were detection of CMV in bronchial lavage, C. parvum-driven sclerosing cholangitis, Takayasu vasculitis, neurological syndromes, pulmonary tuberculosis, and lymphomatoid granulomatosis. CONCLUSION: DOCK8-Def has a broad spectrum of manifestations, including allergy, autoimmunity, inflammation, infection, and cancer. The hallmark of this inborn error of immunity is IEI-associated eczema with eosinophilia and increased IgE. Here, we report six new mutations causing human DOCK8 deficiency and symptoms previously unrecognized to occur in DOCK8-Def. Therefore, an early diagnosis of DOCK8-Def is essential to facilitate an adequate treatment such as HSCT.

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.

Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels.

Identifying the factors that shape protein expression variability in complex multi-cellular organisms has primarily focused on promoter architecture and regulation of single-cell expression in cis. However, this targeted approach has to date been unable to identify major regulators of cell-to-cell gene expression variability in humans. To address this, we have combined single-cell protein expression measurements in the human immune system using flow cytometry with a quantitative genetics analysis. For the majority of proteins whose variability in expression has a heritable component, we find that genetic variants act in trans, with notably fewer variants acting in cis. Furthermore, we highlight using Mendelian Randomization that these variability-Quantitative Trait Loci might be driven by the cis regulation of upstream genes. This indicates that natural selection may balance the impact of gene regulation in cis with downstream impacts on expression variability in trans.

Common homozygosity for predicted loss-of-function variants reveals both redundant and advantageous effects of dispensable human genes.

Humans homozygous or hemizygous for variants predicted to cause a loss of function (LoF) of the corresponding protein do not necessarily present with overt clinical phenotypes. We report here 190 autosomal genes with 207 predicted LoF variants, for which the frequency of homozygous individuals exceeds 1% in at least one human population from five major ancestry groups. No such genes were identified on the X and Y chromosomes. Manual curation revealed that 28 variants (15%) had been misannotated as LoF. Of the 179 remaining variants in 166 genes, only 11 alleles in 11 genes had previously been confirmed experimentally to be LoF. The set of 166 dispensable genes was enriched in olfactory receptor genes (41 genes). The 41 dispensable olfactory receptor genes displayed a relaxation of selective constraints similar to that observed for other olfactory receptor genes. The 125 dispensable nonolfactory receptor genes also displayed a relaxation of selective constraints consistent with greater redundancy. Sixty-two of these 125 genes were found to be dispensable in at least three human populations, suggesting possible evolution toward pseudogenes. Of the 179 LoF variants, 68 could be tested for two neutrality statistics, and 8 displayed robust signals of positive selection. These latter variants included a known FUT2 variant that confers resistance to intestinal viruses, and an APOL3 variant involved in resistance to parasitic infections. Overall, the identification of 166 genes for which a sizeable proportion of humans are homozygous for predicted LoF alleles reveals both redundancies and advantages of such deficiencies for human survival.

Recent Adaptive Acquisition by African Rainforest Hunter-Gatherers of the Late Pleistocene Sickle-Cell Mutation Suggests Past Differences in Malaria Exposure.

The hemoglobin ßS sickle mutation is a textbook case in which natural selection maintains a deleterious mutation at high frequency in the human population. Homozygous individuals for this mutation develop sickle-cell disease, whereas heterozygotes benefit from higher protection against severe malaria. Because the overdominant ßS allele should be purged almost immediately from the population in the absence of malaria, the study of the evolutionary history of this iconic mutation can provide important information about the history of human exposure to malaria. Here, we sought to increase our understanding of the origins and time depth of the ßS mutation in populations with different lifestyles and ecologies, and we analyzed the diversity of HBB in 479 individuals from 13 populations of African farmers and rainforest hunter-gatherers. Using an approximate Bayesian computation method, we estimated the age of the ßS allele while explicitly accounting for population subdivision, past demography, and balancing selection. When the effects of balancing selection are taken into account, our analyses indicate a single emergence of ßS in the ancestors of present-day agriculturalist populations ∼22,000 years ago. Furthermore, we show that rainforest hunter-gatherers have more recently acquired the ßS mutation from the ancestors of agriculturalists through adaptive gene flow during the last ∼6,000 years. Together, our results provide evidence for a more ancient exposure to malarial pressures among the ancestors of agriculturalists than previously appreciated, and they suggest that rainforest hunter-gatherers have been increasingly exposed to malaria during the last millennia.

Homozygosity for TYK2 P1104A underlies tuberculosis in about 1% of patients in a cohort of European ancestry.

The human genetic basis of tuberculosis (TB) has long remained elusive. We recently reported a high level of enrichment in homozygosity for the common TYK2 P1104A variant in a heterogeneous cohort of patients with TB from non-European countries in which TB is endemic. This variant is homozygous in ∼1/600 Europeans and ∼1/5,000 people from other countries outside East Asia and sub-Saharan Africa. We report a study of this variant in the UK Biobank cohort. The frequency of P1104A homozygotes was much higher in patients with TB (6/620, 1%) than in controls (228/114,473, 0.2%), with an odds ratio (OR) adjusted for ancestry of 5.0 [95% confidence interval (CI): 1.96-10.31, P = 2 × 10-3]. Conversely, we did not observe enrichment for P1104A heterozygosity, or for TYK2 I684S or V362F homozygosity or heterozygosity. Moreover, it is unlikely that more than 10% of controls were infected with Mycobacterium tuberculosis, as 97% were of European genetic ancestry, born between 1939 and 1970, and resided in the United Kingdom. Had all of them been infected, the OR for developing TB upon infection would be higher. These findings suggest that homozygosity for TYK2 P1104A may account for ∼1% of TB cases in Europeans.

Blacklisting variants common in private cohorts but not in public databases optimizes human exome analysis.

Computational analyses of human patient exomes aim to filter out as many nonpathogenic genetic variants (NPVs) as possible, without removing the true disease-causing mutations. This involves comparing the patient's exome with public databases to remove reported variants inconsistent with disease prevalence, mode of inheritance, or clinical penetrance. However, variants frequent in a given exome cohort, but absent or rare in public databases, have also been reported and treated as NPVs, without rigorous exploration. We report the generation of a blacklist of variants frequent within an in-house cohort of 3,104 exomes. This blacklist did not remove known pathogenic mutations from the exomes of 129 patients and decreased the number of NPVs remaining in the 3,104 individual exomes by a median of 62%. We validated this approach by testing three other independent cohorts of 400, 902, and 3,869 exomes. The blacklist generated from any given cohort removed a substantial proportion of NPVs (11-65%). We analyzed the blacklisted variants computationally and experimentally. Most of the blacklisted variants corresponded to false signals generated by incomplete reference genome assembly, location in low-complexity regions, bioinformatic misprocessing, or limitations inherent to cohort-specific private alleles (e.g., due to sequencing kits, and genetic ancestries). Finally, we provide our precalculated blacklists, together with ReFiNE, a program for generating customized blacklists from any medium-sized or large in-house cohort of exome (or other next-generation sequencing) data via a user-friendly public web server. This work demonstrates the power of extracting variant blacklists from private databases as a specific in-house but broadly applicable tool for optimizing exome analysis.

Associations between untargeted plasma metabolomic signatures and gut microbiota composition in the Milieu Intérieur population of healthy adults.

Host-microbial co-metabolism products are being increasingly recognised to play important roles in physiological processes. However, studies undertaking a comprehensive approach to consider host-microbial metabolic relationships remain scarce. Metabolomic analysis yielding detailed information regarding metabolites found in a given biological compartment holds promise for such an approach. This work aimed to explore the associations between host plasma metabolomic signatures and gut microbiota composition in healthy adults of the Milieu Intérieur study. For 846 subjects, gut microbiota composition was profiled through sequencing of the 16S rRNA gene in stools. Metabolomic signatures were generated through proton NMR analysis of plasma. The associations between metabolomic variables and α- and ß-diversity indexes and relative taxa abundances were tested using multi-adjusted partial Spearman correlations, permutational ANOVA and multivariate associations with linear models, respectively. A multiple testing correction was applied (Benjamini-Hochberg, 10 % false discovery rate). Microbial richness was negatively associated with lipid-related signals and positively associated with amino acids, choline, creatinine, glucose and citrate (-0·133 ≤ Spearman's ρ ≤ 0·126). Specific associations between metabolomic signals and abundances of taxa were detected (twenty-five at the genus level and nineteen at the species level): notably, numerous associations were observed for creatinine (positively associated with eleven species and negatively associated with Faecalibacterium prausnitzii). This large-scale population-based study highlights metabolites associated with gut microbial features and provides new insights into the understanding of complex host-gut microbiota metabolic relationships. In particular, our results support the implication of a 'gut-kidney axis'. More studies providing a detailed exploration of these complex interactions and their implications for host health are needed.

Polygenic adaptation and convergent evolution on growth and cardiac genetic pathways in African and Asian rainforest hunter-gatherers.

Different human populations facing similar environmental challenges have sometimes evolved convergent biological adaptations, for example, hypoxia resistance at high altitudes and depigmented skin in northern latitudes on separate continents. The "pygmy" phenotype (small adult body size), characteristic of hunter-gatherer populations inhabiting both African and Asian tropical rainforests, is often highlighted as another case of convergent adaptation in humans. However, the degree to which phenotypic convergence in this polygenic trait is due to convergent versus population-specific genetic changes is unknown. To address this question, we analyzed high-coverage sequence data from the protein-coding portion of the genomes of two pairs of populations: Batwa rainforest hunter-gatherers and neighboring Bakiga agriculturalists from Uganda and Andamanese rainforest hunter-gatherers and Brahmin agriculturalists from India. We observed signatures of convergent positive selection between the rainforest hunter-gatherers across the set of genes with "growth factor binding" functions ([Formula: see text]). Unexpectedly, for the rainforest groups, we also observed convergent and population-specific signatures of positive selection in pathways related to cardiac development (e.g., "cardiac muscle tissue development"; [Formula: see text]). We hypothesize that the growth hormone subresponsiveness likely underlying the adult small body-size phenotype may have led to compensatory changes in cardiac pathways, in which this hormone also plays an essential role. Importantly, in the agriculturalist populations, we did not observe similar patterns of positive selection on sets of genes associated with growth or cardiac development, indicating our results most likely reflect a history of convergent adaptation to the similar ecology of rainforests rather than a more general evolutionary pattern.

Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges.

The contribution of host genetic and nongenetic factors to immunological differences in humans remains largely undefined. Here, we generated bacterial-, fungal-, and viral-induced immune transcriptional profiles in an age- and sex-balanced cohort of 1,000 healthy individuals and searched for the determinants of immune response variation. We found that age and sex affected the transcriptional response of most immune-related genes, with age effects being more stimulus-specific relative to sex effects, which were largely shared across conditions. Although specific cell populations mediated the effects of age and sex on gene expression, including CD8+ T cells for age and CD4+ T cells and monocytes for sex, we detected a direct effect of these intrinsic factors for the majority of immune genes. The mapping of expression quantitative trait loci (eQTLs) revealed that genetic factors had a stronger effect on immune gene regulation than age and sex, yet they affected a smaller number of genes. Importantly, we identified numerous genetic variants that manifested their regulatory effects exclusively on immune stimulation, including a Candida albicans-specific master regulator at the CR1 locus. These response eQTLs were enriched in disease-associated variants, particularly for autoimmune and inflammatory disorders, indicating that differences in disease risk may result from regulatory variants exerting their effects only in the presence of immune stress. Together, this study quantifies the respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes.