A population genetics study of the Familial Mediterranean Fever gene: evidence of balancing selection under an overdominance regime

Bw4 ligand and direct T-cell receptor binding induced selection on HLA A and B alleles

Introduction

The HLA region is the hallmark of balancing selection, argued to be driven by the pressure to present a wide variety of viral epitopes. As such selection on the peptide-binding positions has been proposed to drive HLA population genetics. MHC molecules also directly binds to the T-Cell Receptor and killer cell immunoglobulin-like receptors (KIR).

Methods

We here combine the HLA allele frequencies in over six-million Hematopoietic Stem Cells (HSC) donors with a novel machine-learning-based method to predict allele frequency.

Results

We show for the first time that allele frequency can be predicted from their sequences. This prediction yields a natural measure for selection. The strongest selection is affecting KIR binding regions, followed by the peptide-binding cleft. The selection from the direct interaction with the KIR and TCR is centered on positively charged residues (mainly Arginine), and some positions in the peptide-binding cleft are not associated with the allele frequency, especially Tyrosine residues.

Discussion

These results suggest that the balancing selection for peptide presentation is combined with a positive selection for KIR and TCR binding.

IL-1 and autoinflammatory disease: biology, pathogenesis and therapeutic targeting

Over 20 years ago, it was first proposed that autoinflammation underpins a handful of rare monogenic disorders characterized by recurrent fever and systemic inflammation. The subsequent identification of novel, causative genes directly led to a better understanding of how the innate immune system is regulated under normal conditions, as well as its dysregulation associated with pathogenic mutations. Early on, IL-1 emerged as a central mediator for these diseases, based on data derived from patient cells, mutant mouse models and definitive clinical responses to IL-1 targeted therapy. Since that time, our understanding of the mechanisms of autoinflammation has expanded beyond IL-1 to additional innate immune processes. However, the number and complexity of IL-1-mediated autoinflammatory diseases has also multiplied to include additional monogenic syndromes with expanded genotypes and phenotypes, as well as more common polygenic disorders seen frequently by the practising clinician. In order to increase physician awareness and update rheumatologists who are likely to encounter these patients, this review discusses the general pathophysiological concepts of IL-1-mediated autoinflammation, the epidemiological and clinical features of specific diseases, diagnostic challenges and approaches, and current and future perspectives for therapy.

Distinguishing between recent balancing selection and incomplete sweep using deep neural networks

Balancing selection is an important adaptive mechanism underpinning a wide range of phenotypes. Despite its relevance, the detection of recent balancing selection from genomic data is challenging as its signatures are qualitatively similar to those left by ongoing positive selection. In this study, we developed and implemented two deep neural networks and tested their performance to predict loci under recent selection, either due to balancing selection or incomplete sweep, from population genomic data. Specifically, we generated forward-in-time simulations to train and test an artificial neural network (ANN) and a convolutional neural network (CNN). ANN received as input multiple summary statistics calculated on the locus of interest, while CNN was applied directly on the matrix of haplotypes. We found that both architectures have high accuracy to identify loci under recent selection. CNN generally outperformed ANN to distinguish between signals of balancing selection and incomplete sweep and was less affected by incorrect training data. We deployed both trained networks on neutral genomic regions in European populations and demonstrated a lower false-positive rate for CNN than ANN. We finally deployed CNN within the MEFV gene region and identified several common variants predicted to be under incomplete sweep in a European population. Notably, two of these variants are functional changes and could modulate susceptibility to familial Mediterranean fever, possibly as a consequence of past adaptation to pathogens. In conclusion, deep neural networks were able to characterize signals of selection on intermediate frequency variants, an analysis currently inaccessible by commonly used strategies.

Familial Mediterranean Fever and COVID-19: Friends or Foes?

Familial Mediterranean Fever (FMF) and COVID-19 show a remarkable overlap of clinical symptoms and similar laboratory findings. Both are characterized by fever, abdominal/chest pain, elevation of C-reactive protein, and leukocytosis. In addition, colchicine and IL-1 inhibitors treatments that are effective in controlling inflammation in FMF patients have recently been proposed for off-label use in COVID-19 patients. Thus, FMF may resemble a milder recapitulation of the cytokine storm that is a hallmark of COVID-19 patients progressing to severe disease. We analyzed the sequence of the MEFV-encoded Pyrin protein - whose mutations cause FMF- in mammals, bats and pangolin. Intriguingly, although Pyrin is extremely conserved in species that are considered either a reservoir or intermediate hosts for SARS-CoV-2, some of the most common FMF-causing variants in humans are present as wildtype residues in these species. We propose that in humans, Pyrin may have evolved to fight highly pathogenic infections.

Inflammasome-Dependent Cytokines at the Crossroads of Health and Autoinflammatory Disease

As key regulators of both innate and adaptive immunity, it is unsurprising that the activity of interleukin (IL)-1 cytokine family members is tightly controlled by decoy receptors, antagonists, and a variety of other mechanisms. Additionally, inflammasome-mediated proteolytic maturation is a prominent and distinguishing feature of two important members of this cytokine family, IL-1β and IL-18, because their full-length gene products are biologically inert. Although vital in antimicrobial host defense, deregulated inflammasome signaling is linked with a growing number of autoimmune and autoinflammatory diseases. Here, we focus on introducing the diverse inflammasome types and discussing their causal roles in periodic fever syndromes. Therapies targeting IL-1 or IL-18 show great efficacy in some of these autoinflammatory diseases, although further understanding of the molecular mechanisms leading to unregulated production of these key cytokines is required to benefit more patients.

Genetic architecture and balancing selection: the life and death of differentiated variants

Balancing selection describes any form of natural selection, which results in the persistence of multiple variants of a trait at intermediate frequencies within populations. By offering up a snapshot of multiple co-occurring functional variants and their interactions, systems under balancing selection can reveal the evolutionary mechanisms favouring the emergence and persistence of adaptive variation in natural populations. We here focus on the mechanisms by which several functional variants for a given trait can arise, a process typically requiring multiple epistatic mutations. We highlight how balancing selection can favour specific features in the genetic architecture and review the evolutionary and molecular mechanisms shaping this architecture. First, balancing selection affects the number of loci underlying differentiated traits and their respective effects. Control by one or few loci favours the persistence of differentiated functional variants by limiting intergenic recombination, or its impact, and may sometimes lead to the evolution of supergenes. Chromosomal rearrangements, particularly inversions, preventing adaptive combinations from being dissociated are increasingly being noted as features of such systems. Similarly, due to the frequency of heterozygotes maintained by balancing selection, dominance may be a key property of adaptive variants. High heterozygosity and limited recombination also influence associated genetic load, as linked recessive deleterious mutations may be sheltered. The capture of deleterious elements in a locus under balancing selection may reinforce polymorphism by further promoting heterozygotes. Finally, according to recent genomewide scans, balanced polymorphism might be more pervasive than generally thought. We stress the need for both functional and ecological studies to characterize the evolutionary mechanisms operating in these systems.

Literature-Informed Analysis of a Genome-Wide Association Study of Gestational Age in Norwegian Women and Children Suggests Involvement of Inflammatory Pathways

Background

Five-to-eighteen percent of pregnancies worldwide end in preterm birth, which is the major cause of neonatal death and morbidity. Approximately 30% of the variation in gestational age at birth can be attributed to genetic factors. Genome-wide association studies (GWAS) have not shown robust evidence of association with genomic loci yet.

Methods

We separately investigated 1921 Norwegian mothers and 1199 children from pregnancies with spontaneous onset of delivery. Individuals were further divided based on the onset of delivery: initiated by labor or prelabor rupture of membranes. Genetic association with ultrasound-dated gestational age was evaluated using three genetic models and adaptive permutations. The top-ranked loci were tested for enrichment in 12 candidate gene-sets generated by text-mining PubMed abstracts containing pregnancy-related keywords.

Results

The six GWAS did not reveal significant associations, with the most extreme empirical p = 5.1 × 10⁻⁷. The top loci from maternal GWAS with deliveries initiated by labor showed significant enrichment in 10 PubMed gene-sets, e.g., p = 0.001 and 0.005 for keywords "uterus" and "preterm" respectively. Enrichment signals were mainly caused by infection/inflammation-related genes TLR4, NFKB1, ABCA1, MMP9. Literature-informed analysis of top loci revealed further immunity genes: IL1A, IL1B, CAMP, TREM1, TFRC, NFKBIA, MEFV, IRF8, WNT5A.

Conclusion

Our analyses support the role of inflammatory pathways in determining pregnancy duration and provide a list of 32 candidate genes for a follow-up work. We observed that the top regions from GWAS in mothers with labor-initiated deliveries significantly more often overlap with pregnancy-related genes than would be expected by chance, suggesting that increased sample size would benefit similar studies.

Update on Pyrin Functions and Mechanisms of Familial Mediterranean Fever

Mutations in the MEFV gene, which encodes the protein named pyrin (also called marenostrin or TRIM20), are associated with the autoinflammatory disease familial Mediterranean fever (FMF). Recent genetic and immunologic studies uncovered novel functions of pyrin and raised several new questions in relation to FMF pathogenesis. The disease is clinically heterogeneous reflecting the complexity and multiplicity of pyrin functions. The main functions uncovered so far include its involvement in innate immune response such as the inflammasome assemblage and, as a part of the inflammasome, sensing intracellular danger signals, activation of mediators of inflammation, and resolution of inflammation by the autophagy of regulators of innate immunity. Based on these functions, the FMF-associated versions of pyrin confer a heightened sensitivity to a variety of intracellular danger signals and postpone the resolution of innate immune responses. It remains to be demonstrated, however, what kind of selective advantage the heterozygous carriage conferred in the past to be positively selected and maintained in populations from the Mediterranean basin.

Genetic variation in TLR genes in Ugandan and South African populations and comparison with HapMap data

Genetic epidemiological studies of complex diseases often rely on data from the International HapMap Consortium for identification of single nucleotide polymorphisms (SNPs), particularly those that tag haplotypes. However, little is known about the relevance of the African populations used to collect HapMap data for study populations conducted elsewhere in Africa. Toll-like receptor (TLR) genes play a key role in susceptibility to various infectious diseases, including tuberculosis. We conducted full-exon sequencing in samples obtained from Uganda (n = 48) and South Africa (n = 48), in four genes in the TLR pathway: TLR2, TLR4, TLR6, and TIRAP. We identified one novel TIRAP SNP (with minor allele frequency [MAF] 3.2%) and a novel TLR6 SNP (MAF 8%) in the Ugandan population, and a TLR6 SNP that is unique to the South African population (MAF 14%). These SNPs were also not present in the 1000 Genomes data. Genotype and haplotype frequencies and linkage disequilibrium patterns in Uganda and South Africa were similar to African populations in the HapMap datasets. Multidimensional scaling analysis of polymorphisms in all four genes suggested broad overlap of all of the examined African populations. Based on these data, we propose that there is enough similarity among African populations represented in the HapMap database to justify initial SNP selection for genetic epidemiological studies in Uganda and South Africa. We also discovered three novel polymorphisms that appear to be population-specific and would only be detected by sequencing efforts.

A signature of balancing selection in the region upstream to the human UGT2B4 gene and implications for breast cancer risk

UDP-glucuronosyltransferase 2 family, polypeptide B4 (UGT2B4) is an important metabolizing enzyme involved in the clearance of many xenobiotics and endogenous substrates, especially steroid hormones and bile acids. The HapMap data show that numerous SNPs upstream of UGT2B4 are in near-perfect linkage disequilibrium with each other and occur at intermediate frequency, indicating that this region might contain a target of natural selection. To investigate this possibility, we chose three regions (4.8 kb in total) for resequencing and observed a striking excess of intermediate-frequency alleles that define two major haplotypes separated by many mutation events and with little differentiation across populations, thus suggesting that the variation pattern upstream UGT2B4 is highly unusual and may be the result of balancing selection. We propose that this pattern is due to the maintenance of a regulatory polymorphism involved in the fine tuning of UGT2B4 expression so that heterozygous genotypes result in optimal enzyme levels. Considering the important role of steroid hormones in breast cancer susceptibility, we hypothesized that variation in this region could predispose to breast cancer. To test this hypothesis, we genotyped tag SNP rs13129471 in 1,261 patients and 825 normal women of African ancestry from three populations. The frequency comparison indicated that rs13129471 was significantly associated with breast cancer after adjusting for ethnicity [P = 0.003; heterozygous odds ratio (OR) 1.02, 95% confidence interval (CI) 0.81-1.28; homozygous OR 1.50, 95% CI 1.15-1.95]. Our results provide new insights into UGT2B4 sequence variation and indicate that a signal of natural selection may lead to the identification of disease susceptibility variants.

Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution

Previous genome-wide scans of positive natural selection in humans have identified a number of non-neutrally evolving genes that play important roles in skin pigmentation, metabolism, or immune function. Recent studies have also shown that a genome-wide pattern of local adaptation can be detected by identifying correlations between patterns of allele frequencies and environmental variables. Despite these observations, the degree to which natural selection is primarily driven by adaptation to local environments, and the role of pathogens or other ecological factors as selective agents, is still under debate. To address this issue, we correlated the spatial allele frequency distribution of a large sample of SNPs from 55 distinct human populations to a set of environmental factors that describe local geographical features such as climate, diet regimes, and pathogen loads. In concordance with previous studies, we detected a significant enrichment of genic SNPs, and particularly non-synonymous SNPs associated with local adaptation. Furthermore, we show that the diversity of the local pathogenic environment is the predominant driver of local adaptation, and that climate, at least as measured here, only plays a relatively minor role. While background demography by far makes the strongest contribution in explaining the genetic variance among populations, we detected about 100 genes which show an unexpectedly strong correlation between allele frequencies and pathogenic environment, after correcting for demography. Conversely, for diet regimes and climatic conditions, no genes show a similar correlation between the environmental factor and allele frequencies. This result is validated using low-coverage sequencing data for multiple populations. Among the loci targeted by pathogen-driven selection, we found an enrichment of genes associated to autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis, which lends credence to the hypothesis that some susceptibility alleles for autoimmune diseases may be maintained in human population due to past selective processes.

Adaptation to local environments is one of the most important factors shaping human genetic variation among different geographically distributed populations. Here we develop a statistical framework aimed at identifying signals of genetic adaptation. We correlate the spatial distribution of allele frequencies of a large sample of SNPs, genotyped in more than 50 populations distributed worldwide, to a set of environmental factors, describing local geographical features such as climate conditions, diet regimes, and pathogens load. Our results show an excess of putative functional variants for high levels of population differentiation, measured by the degree to which genetic variation correlates with a set of environmental variables. We demonstrate that selection on pathogens is the primary driver of local adaptation and affects the distribution of genetic variation at a large number of genes. Among the selected genes, we also identify an excess of genes associated with autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis.

Genetic adaptation of the antibacterial human innate immunity network

BACKGROUND

Pathogens have represented an important selective force during the adaptation of modern human populations to changing social and other environmental conditions. The evolution of the immune system has therefore been influenced by these pressures. Genomic scans have revealed that immune system is one of the functions enriched with genes under adaptive selection.

RESULTS

Here, we describe how the innate immune system has responded to these challenges, through the analysis of resequencing data for 132 innate immunity genes in two human populations. Results are interpreted in the context of the functional and interaction networks defined by these genes. Nucleotide diversity is lower in the adaptors and modulators functional classes, and is negatively correlated with the centrality of the proteins within the interaction network. We also produced a list of candidate genes under positive or balancing selection in each population detected by neutrality tests and showed that some functional classes are preferential targets for selection.

CONCLUSIONS

We found evidence that the role of each gene in the network conditions the capacity to evolve or their evolvability: genes at the core of the network are more constrained, while adaptation mostly occurred at particular positions at the network edges. Interestingly, the functional classes containing most of the genes with signatures of balancing selection are involved in autoinflammatory and autoimmune diseases, suggesting a counterbalance between the beneficial and deleterious effects of the immune response.

The emergence of human-evolutionary medical genomics

In this review, I describe how evolutionary genomics is uniquely suited to spearhead advances in understanding human disease risk, owing to the privileged position of genes as fundamental causes of phenotypic variation, and the ability of population genetic and phylogenetic methods to robustly infer processes of natural selection, drift, and mutation from genetic variation at the levels of family, population, species, and clade. I first provide an overview of models for the origins and maintenance of genetically based disease risk in humans. I then discuss how analyses of genetic disease risk can be dovetailed with studies of positive and balancing selection, to evaluate the degree to which the 'genes that make us human' also represent the genes that mediate risk of polygenic disease. Finally, I present four basic principles for the nascent field of human evolutionary medical genomics, each of which represents a process that is nonintuitive from a proximate perspective. Joint consideration of these principles compels novel forms of interdisciplinary analyses, most notably studies that (i) analyze tradeoffs at the level of molecular genetics, and (ii) identify genetic variants that are derived in the human lineage or in specific populations, and then compare individuals with derived versus ancestral alleles.