Early progression to active tuberculosis is a highly heritable trait driven by 3q23 in Peruvians

Mycobacterium tuberculosis-dependent monocyte expression quantitative trait loci, cytokine production, and TB pathogenesis

Introduction

The heterogeneity of outcomes after Mycobacterium tuberculosis (Mtb) exposure is a conundrum associated with millennia of host-pathogen co-evolution. We hypothesized that human myeloid cells contain genetically encoded, Mtb-specific responses that regulate critical steps in tuberculosis (TB) pathogenesis.

Methods

We mapped genome-wide expression quantitative trait loci (eQTLs) in Mtb-infected monocytes with RNAseq from 80 Ugandan household contacts of pulmonary TB cases to identify monocyte-specific, Mtb-dependent eQTLs and their association with cytokine expression and clinical resistance to tuberculin skin test (TST) and interferon-γ release assay (IGRA) conversion.

Results

cis-eQTLs (n=1,567) were identified in Mtb-infected monocytes (FDR<0.01), including 29 eQTLs in 16 genes which were Mtb-dependent (significant for Mtb:genotype interaction [FDR<0.1], but not classified as eQTL in uninfected condition [FDR≥0.01]). A subset of eQTLs were associated with Mtb-induced cytokine expression (n=8) and/or clinical resistance to TST/IGRA conversion (n=1). Expression of BMP6, an Mtb-dependent eQTL gene, was associated with IFNB1 induction in Mtb-infected and DNA ligand-induced cells. Network and enrichment analyses identified fatty acid metabolism as a pathway associated with eQTL genes.

Discussion

These findings suggest that monocyte genes contain Mtb-dependent eQTLs, including a subset associated with cytokine expression and/or clinical resistance to TST/IGRA conversion, providing insight into immunogenetic pathways regulating susceptibility to Mtb infection and TB pathogenesis.

Multi-ancestry meta-analysis of host genetic susceptibility to tuberculosis identifies shared genetic architecture

The heritability of susceptibility to tuberculosis (TB) disease has been well recognized. Over 100 genes have been studied as candidates for TB susceptibility, and several variants were identified by genome-wide association studies (GWAS), but few replicate. We established the International Tuberculosis Host Genetics Consortium to perform a multi-ancestry meta-analysis of GWAS, including 14,153 cases and 19,536 controls of African, Asian, and European ancestry. Our analyses demonstrate a substantial degree of heritability (pooled polygenic h2 = 26.3%, 95% CI 23.7-29.0%) for susceptibility to TB that is shared across ancestries, highlighting an important host genetic influence on disease. We identified one global host genetic correlate for TB at genome-wide significance (p<5 × 10-8) in the human leukocyte antigen (HLA)-II region (rs28383206, p-value=5.2 × 10-9) but failed to replicate variants previously associated with TB susceptibility. These data demonstrate the complex shared genetic architecture of susceptibility to TB and the importance of large-scale GWAS analysis across multiple ancestries experiencing different levels of infection pressure.

Mycobacterium tuberculosis-dependent Monocyte Expression Quantitative Trait Loci and Tuberculosis Pathogenesis

The heterogeneity of outcomes after Mycobacterium tuberculosis (Mtb) exposure is a conundrum associated with millennia of host-pathogen co-evolution. We hypothesized that human myeloid cells contain genetically encoded, Mtb-specific responses that regulate critical steps in tuberculosis (TB) pathogenesis. We mapped genome-wide expression quantitative trait loci (eQTLs) in Mtb-infected monocytes with RNAseq from 80 Ugandan household contacts of pulmonary TB cases to identify monocyte-specific, Mtb-dependent eQTLs and their association with cytokine expression and clinical resistance to tuberculin skin test (TST) and interferon-γ release assay (IGRA) conversion. cis-eQTLs (n=1,567) were identified in Mtb-infected monocytes (FDR<0.01), including 29 eQTLs in 16 genes which were Mtb-dependent (significant for Mtb:genotype interaction [FDR<0.1], but not classified as eQTL in media condition [FDR≥0.01]). A subset of eQTLs were associated with Mtb-induced cytokine expression (n=8) and/or clinical resistance to TST/IGRA conversion (n=1). Expression of BMP6, an Mtb-dependent eQTL gene, was associated with IFNB1 induction in Mtb-infected and DNA ligand-induced cells. Network and enrichment analyses identified fatty acid metabolism as a pathway associated with eQTL genes. These findings suggest that monocyte genes contain Mtb-dependent eQTLs, including a subset associated with cytokine expression and/or clinical resistance to TST/IGRA conversion, providing insight into immunogenetic pathways regulating susceptibility to Mtb infection and TB pathogenesis.

MUC5AC Genetic Variation Is Associated With Tuberculous Meningitis Cerebral Spinal Fluid Cytokine Responses and Mortality

BACKGROUND

The purpose of this study was to assess if single nucleotide polymorphisms (SNPs) in lung mucins MUC5B and MUC5AC are associated with Mycobacterium tuberculosis outcomes.

METHODS

Independent SNPs in MUC5B and MUC5AC (genotyped by Illumina HumanOmniExpress array) were assessed for associations with tumor necrosis factor (TNF) concentrations (measured by immunoassay) in cerebral spinal fluid (CSF) from tuberculous meningitis (TBM) patients. SNPs associated with CSF TNF concentrations were carried forward for analyses of pulmonary and meningeal tuberculosis susceptibility and TBM mortality.

RESULTS

MUC5AC SNP rs28737416 T allele was associated with lower CSF concentrations of TNF (P = 1.8 × 10-8) and IFN-γ (P = 2.3 × 10-6). In an additive genetic model, rs28737416 T/T genotype was associated with higher susceptibility to TBM (odds ratio [OR], 1.24; 95% confidence interval [CI], 1.03-1.49; P = .02), but not pulmonary tuberculosis (OR, 1.11, 95% CI, .98-1.25; P = .10). TBM mortality was higher among participants with the rs28737416 T/T and T/C genotypes (35/119, 30.4%) versus the C/C genotype (11/89, 12.4%; log-rank P = .005) in a Vietnam discovery cohort (n = 210), an independent Vietnam validation cohort (n = 87; 9/87, 19.1% vs 1/20, 2.5%; log-rank P = .02), and an Indonesia validation cohort (n = 468, 127/287, 44.3% vs 65/181, 35.9%; log-rank P = .06).

CONCLUSIONS

MUC5AC variants may contribute to immune changes that influence TBM outcomes.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians

A quarter of humanity is estimated to be latently infected with Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n=63) or did not progress to TB (controls, n=63). Transcriptomic profiling of monocyte-derived dendritic cells (DCs) and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Five genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk

Infectious diseases still threaten global human health, and host genetic factors have been indicated as determining risk factors for observed variations in disease susceptibility, severity, and outcome. We performed a genome-wide meta-analysis on 4624 subjects from the 10,001 Dalmatians cohort, with 14 infection-related traits. Despite a rather small number of cases in some instances, we detected 29 infection-related genetic associations, mostly belonging to rare variants. Notably, the list included the genes CD28, INPP5D, ITPKB, MACROD2, and RSF1, all of which have known roles in the immune response. Expanding our knowledge on rare variants could contribute to the development of genetic panels that could assist in predicting an individual's life-long susceptibility to major infectious diseases. In addition, longitudinal biobanks are an interesting source of information for identifying the host genetic variants involved in infectious disease susceptibility and severity. Since infectious diseases continue to act as a selective pressure on our genomes, there is a constant need for a large consortium of biobanks with access to genetic and environmental data to further elucidate the complex mechanisms behind host-pathogen interactions and infectious disease susceptibility.

Altered IL-6 signalling and risk of tuberculosis disease: a meta-analysis and Mendelian randomisation study

IL-6 responses are ubiquitous in Mycobacterium tuberculosis (Mtb) infections, but their role in determining human tuberculosis (TB) disease risk is unknown. We used single nucleotide polymorphisms (SNPs) in and near the IL-6 receptor (IL6R) gene, focusing on the non-synonymous variant, rs2228145, associated with reduced classical IL-6 signalling, to assess the effect of altered IL-6 activity on TB disease risk. We identified 16 genome wide association studies (GWAS) of TB disease collating 17,982 cases of TB disease and 972,389 controls across 4 continents. Meta-analyses and Mendelian randomisation analyses revealed that reduced classical IL-6 signalling was associated with lower odds of TB disease, a finding replicated using multiple, independent SNP instruments and 2 separate exposure variables. Our findings establish a causal relationship between IL-6 signalling and the outcome of Mtb infection, suggesting IL-6 antagonists do not increase the risk of TB disease and should be investigated as adjuncts in treatment.

Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection

BACKGROUND

The discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging. The present study aims to investigate the value of diagnostic models established by machine learning based on multiple laboratory data for distinguishing Mycobacterium tuberculosis (Mtb) infection status.

METHODS

T-SPOT, lymphocyte characteristic detection, and routine laboratory tests were performed on participants. Diagnostic models were built according to various algorithms.

RESULTS

A total of 892 participants (468 ATB and 424 LTBI) and another 263 participants (125 ATB and 138 LTBI), were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Receiver operating characteristic (ROC) curve analysis showed that the value of individual indicator for differentiating ATB from LTBI was limited (area under the ROC curve (AUC) < 0.8). A total of 28 models were successfully established using machine learning. Among them, the AUCs of 25 models were more than 0.9 in test set. It was found that conditional random forests (cforest) model, based on the implementation of the random forest and bagging ensemble algorithms utilizing conditional inference trees as base learners, presented best discriminative power in segregating ATB from LTBI. Specially, cforest model presented an AUC of 0.978, with the sensitivity of 93.39% and the specificity of 91.18%. Mtb-specific response represented by early secreted antigenic target 6 (ESAT-6) and culture filtrate protein 10 (CFP-10) spot-forming cell (SFC) in T-SPOT assay, as well as global adaptive immunity assessed by CD4 cell IFN-γ secretion, CD8 cell IFN-γ secretion, and CD4 cell number, were found to contribute greatly to the cforest model. Superior performance obtained in the discovery cohort was further confirmed in the validation cohort. The sensitivity and specificity of cforest model in validation set were 92.80% and 89.86%, respectively.

CONCLUSIONS

Cforest model developed upon machine learning could serve as a valuable and prospective tool for identifying Mtb infection status. The present study provided a novel and viable idea for realizing the clinical diagnostic application of the combination of machine learning and laboratory findings.

The Awesome Power of Human Genetics of Infectious Disease

Since the identification of sickle cell trait as a heritable form of resistance to malaria, candidate gene studies, linkage analysis paired with sequencing, and genome-wide association (GWA) studies have revealed many examples of genetic resistance and susceptibility to infectious diseases. GWA studies enabled the identification of many common variants associated with small shifts in susceptibility to infectious diseases. This is exemplified by multiple loci associated with leprosy, malaria, HIV, tuberculosis, and coronavirus disease 2019 (COVID-19), which illuminate genetic architecture and implicate pathways underlying pathophysiology. Despite these successes, most of the heritability of infectious diseases remains to be explained. As the field advances, current limitations may be overcome by applying methodological innovations such as cellular GWA studies and phenome-wide association (PheWA) studies as well as by improving methodological rigor with more precise case definitions, deeper phenotyping, increased cohort diversity, and functional validation of candidate loci in the laboratory or human challenge studies.

Identification and validation of a T-cell-related MIR600HG/hsa-mir-21-5p competing endogenous RNA network in tuberculosis activation based on integrated bioinformatics approaches

Background: T cells play critical roles in the progression of tuberculosis (TB); however, knowledge regarding these molecular mechanisms remains inadequate. This study constructed a critical ceRNA network was constructed to identify the potentially important role of TB activation via T-cell regulation.

Methods: We performed integrated bioinformatics analysis in a randomly selected training set from the GSE37250 dataset. After estimating the abundance of 18 types of T cells using ImmuCellAI, critical T-cell subsets were determined by their diagnostic accuracy in distinguishing active from latent TB. We then identified the critical genes associated with T-cell subsets in TB activation through co-expression analysis and PPI network prediction. Then, the ceRNA network was constructed based on RNA complementarity detection on the DIANA-LncBase and mirDIP platform. The gene biomarkers included in the ceRNA network were lncRNA, miRNA, and targeting mRNA. We then applied an elastic net regression model to develop a diagnostic classifier to assess the significance of the gene biomarkers in clinical applications. Internal and external validations were performed to assess the repeatability and generalizability.

Results: We identified CD4⁺ T, Tr1, nTreg, iTreg, and Tfh as T cells critical for TB activation. A ceRNA network mediated by the MIR600HG/hsa-mir-21-5p axis was constructed, in which the significant gene cluster regulated the critical T subsets in TB activation. MIR600HG, hsa-mir-21-5p, and five targeting mRNAs (BCL11B, ETS1, EPHA4, KLF12, and KMT2A) were identified as gene biomarkers. The elastic net diagnostic classifier accurately distinguished active TB from latent. The validation analysis confirmed that our findings had high generalizability in different host background cases.

Conclusion: The findings of this study provided novel insight into the underlying mechanisms of TB activation and identifying prospective biomarkers for clinical applications.

Polygenic risk prediction and SNCA haplotype analysis in a Latino Parkinson's disease cohort

BACKGROUND

Large-scale Parkinson's disease (PD) genome-wide association studies (GWAS) have, until recently, only been conducted on subjects with European-ancestry. Consequently, polygenic risk scores (PRS) constructed using PD GWAS data are likely to be less predictive when applied to non-European cohorts.

METHODS

Using GWAS data from the largest study to date, we constructed a PD PRS for a Latino PD cohort (1497 subjects from LARGE-PD) and tested it for association with PD status and age at onset. We validated the PRS performance by testing it in an independent Latino cohort (448 subjects) and by repeating the analysis in LARGE-PD with the addition of 440 external Peruvian controls. We also tested SNCA haplotypes for association with PD risk in LARGE-PD and a European-ancestry PD cohort.

RESULTS

The GWAS-significant PD PRS had an area under the receiver-operator curve (AUC) of 0.668 (95% CI: 0.640-0.695) in LARGE-PD. The inclusion of external Peruvian controls mitigated this result, dropping the AUC 0.632 (95% CI: 0.607-0.657). At the SNCA locus, haplotypes differ by ancestry. Ancestry-specific SNCA haplotypes were associated with PD status in both LARGE-PD and the European-ancestry cohort (p-value < 0.05). These haplotypes both include the rs356182 G-allele, but only share 14% of their variants overall.

CONCLUSION

The PD PRS has potential for PD risk prediction in Latinos, but variability caused by admixture patterns and bias in a European-ancestry PD PRS data limits its utility. The inclusion of diverse subjects can help elucidate PD risk loci and improve risk prediction in non-European cohorts.

Comprehensive identification of immuno-related transcriptional signature for active pulmonary tuberculosis by integrated analysis of array and single cell RNA-seq

BACKGROUND

Tuberculosis (TB) continues to be a major cause of morbidity and mortality worldwide. However, the molecular mechanism underlying immune response to human infection with Mycobacterium tuberculosis (Mtb) remains unclear. Assessing changes in transcript abundance in blood between health and disease on a genome-wide scale affords a comprehensive view of the impact of Mtb infection on the host defense and a reliable way to identify novel TB biomarkers.

METHODS

We combined expression profiling by array and single cell RNA-sequencing (scRNA-seq) via 10X Genomics platform to better illustrate the immuno-related transcriptional signature of TB and explore potential diagnostic markers for differentiating TB from latent tuberculosis infection (LTBI) and healthy control (HC).

FINDINGS

Pathway analysis based on differential expressed genes (DEGs) revealed that immune transcriptional profiling could effectively differ TB with LTBI and HC. Following WGCNA and PPI network analysis based on DEGs, we screened out three key immuno-related hub genes (ADM, IFIT3 and SERPING1) highly associated with TB. Further validation found only ADM expression significantly increased in TB patients in both adult and children's datasets. By comparing the scRNA-seq datasets from TB, LTBI and HC, we observed a remarkable elevated expression level and proportion of ADM in TB Myeloid cells, further supporting that ADM expression changes could distinguish patients with TB from LTBI and HC. Besides, the hsa-miR-24-3p-NEAT1-ADM-CEBPB regulation pathway might be one of the critical networks regulating the pathogenesis of TB. Although further investigation in a larger cohort is warranted, we provide useful and novel insight to explore the potential candidate genes for TB diagnosis and intervention.

INTERPRETATION

We propose that the expression of ADM in peripheral blood could be used as a novel biomarker for differentiating TB with LTBI and HC.

Tuberculosis Phenotypic and Genotypic Drug Susceptibility Testing and Immunodiagnostics: A Review

Tuberculosis (TB), considered an ancient disease, is still killing one person every 21 seconds. Diagnosis of Mycobacterium tuberculosis (M.tb) still has many challenges, especially in low and middle-income countries with high burden disease rates. Over the last two decades, the amount of drug-resistant (DR)-TB cases has been increasing, from mono-resistant (mainly for isoniazid or rifampicin resistance) to extremely drug resistant TB. DR-TB is problematic to diagnose and treat, and thus, needs more resources to manage it. Together with+ TB clinical symptoms, phenotypic and genotypic diagnosis of TB includes a series of tests that can be used on different specimens to determine if a person has TB, as well as if the M.tb strain+ causing the disease is drug susceptible or resistant. Here, we review and discuss advantages and disadvantages of phenotypic vs. genotypic drug susceptibility testing for DR-TB, advances in TB immunodiagnostics, and propose a call to improve deployable and low-cost TB diagnostic tests to control the DR-TB burden, especially in light of the increase of the global burden of bacterial antimicrobial resistance, and the potentially long term impact of the coronavirus disease 2019 (COVID-19) disruption on TB programs.

Higher native Peruvian genetic ancestry proportion is associated with tuberculosis progression risk

We investigated whether ancestry-specific genetic factors affect tuberculosis (TB) progression risk in a cohort of admixed Peruvians. We genotyped 2,105 patients with TB and 1,320 household contacts (HHCs) who were infected with Mycobacterium tuberculosis (M. tb) but did not develop TB and inferred each individual’s proportion of native Peruvian genetic ancestry. Our HHC study design and our data on potential confounders allowed us to demonstrate increased risk independent of socioeconomic factors. A 10% increase in individual-level native Peruvian genetic ancestry proportion corresponded to a 25% increased TB progression risk. This corresponds to a 3-fold increased risk for individuals in the highest decile of native Peruvian genetic ancestry versus the lowest decile, making native Peruvian genetic ancestry comparable in effect to clinical factors such as diabetes. Our results suggest that genetic ancestry is a major contributor to TB progression risk and highlight the value of including diverse populations in host genetic studies.

Our understanding of how genetic differences among human populations may affect susceptibility to infectious diseases is very limited. Asgari et al. show that the proportion of native genetic ancestry in contemporary Peruvians affects the risk of progression from latent to active tuberculosis even after accounting for differences in socio-demographic factors.

Single-cell eQTL models reveal dynamic T cell state dependence of disease loci

Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by differences in gene regulation across fluid functional cell states within cell types. These states-for example, neurotransmitter-driven programs in astrocytes or perivascular fibroblast differentiation-are obscured in eQTL studies that aggregate cells1,2. Here we modelled eQTLs at single-cell resolution in one complex cell type: memory T cells. Using more than 500,000 unstimulated memory T cells from 259 Peruvian individuals, we show that around one-third of 6,511 cis-eQTLs had effects that were mediated by continuous multimodally defined cell states, such as cytotoxicity and regulatory capacity. In some loci, independent eQTL variants had opposing cell-state relationships. Autoimmune variants were enriched in cell-state-dependent eQTLs, including risk variants for rheumatoid arthritis near ORMDL3 and CTLA4; this indicates that cell-state context is crucial to understanding potential eQTL pathogenicity. Moreover, continuous cell states explained more variation in eQTLs than did conventional discrete categories, such as CD4+ versus CD8+, suggesting that modelling eQTLs and cell states at single-cell resolution can expand insight into gene regulation in functionally heterogeneous cell types.

REL and BHLHE40 Variants Are Associated with IL-12 and IL-10 Responses and Tuberculosis Risk

The major human genes regulating Mycobacterium tuberculosis-induced immune responses and tuberculosis (TB) susceptibility are poorly understood. Although IL-12 and IL-10 are critical for TB pathogenesis, the genetic factors that regulate their expression in humans are unknown. CNBP, REL, and BHLHE40 are master regulators of IL-12 and IL-10 signaling. We hypothesized that common variants in CNBP, REL, and BHLHE40 were associated with IL-12 and IL-10 production from dendritic cells, and that these variants also influence adaptive immune responses to bacillus Calmette-Guérin (BCG) vaccination and TB susceptibility. We characterized the association between common variants in CNBP, REL, and BHLHE40, innate immune responses in dendritic cells and monocyte-derived macrophages, BCG-specific T cell responses, and susceptibility to pediatric and adult TB in human populations. BHLHE40 single-nucleotide polymorphism (SNP) rs4496464 was associated with increased BHLHE40 expression in monocyte-derived macrophages and increased IL-10 from peripheral blood dendritic cells and monocyte-derived macrophages after LPS and TB whole-cell lysate stimulation. SNP BHLHE40 rs11130215, in linkage disequilibrium with rs4496464, was associated with increased BCG-specific IL-2+CD4+ T cell responses and decreased risk for pediatric TB in South Africa. SNPs REL rs842634 and rs842618 were associated with increased IL-12 production from dendritic cells, and SNP REL rs842618 was associated with increased risk for TB meningitis. In summary, we found that genetic variations in REL and BHLHE40 are associated with IL-12 and IL-10 cytokine responses and TB clinical outcomes. Common human genetic regulation of well-defined intermediate cellular traits provides insights into mechanisms of TB pathogenesis.

Clinical predictors of pulmonary tuberculosis among South African adults with HIV

BACKGROUND

Tuberculosis (TB) clinical prediction rules rely on presence of symptoms, however many undiagnosed cases in the community are asymptomatic. This study aimed to explore the utility of clinical factors in predicting TB among people with HIV not seeking care.

METHODS

Baseline data were analysed from an observational cohort of ambulant adults with HIV in South Africa. Participants were tested for Mycobacterium tuberculosis (Mtb) sensitisation (interferon-γ release assay, IGRA) and microbiologically-confirmed prevalent pulmonary TB disease at baseline, and actively surveilled for incident TB through 15 months. Multivariable LASSO regression with post-selection inference was used to test associations with Mtb sensitisation and TB disease.

FINDINGS

Between March 22, 2017, and May 15, 2018, 861 participants were enrolled; Among 851 participants included in the analysis, 94·5% were asymptomatic and 45·9% sensitised to Mtb. TB prevalence was 2·0% at baseline and incidence 2·3/100 person-years through 15 months follow-up. Study site was associated with baseline Mtb sensitisation (p < 0·001), prevalent (p < 0·001), and incident TB disease (p = 0·037). Independent of site, higher CD4 counts (per 50 cells/mm³, aOR 1·48, 95%CI 1·12-1·77, p = 0·006) were associated with increased IGRA positivity, and participants without TB disease (aOR 0·80, 95%CI 0·69-0·94, p = 0·006) had reduced IGRA positivity; no variables were independently associated with prevalent TB. Mixed ancestry (aHR 1·49, 95%CI 1·30->1000, p = 0·005) and antiretroviral initiation (aHR 1·48, 95%CI 1·01-929·93, p = 0·023) were independently associated with incident TB. Models incorporating clinical features alone performed poorly in diagnosing prevalent (AUC 0·65, 95%CI 0·44-0·85) or predicting progression to incident (0·67, 0·46-0·88) TB.

INTERPRETATION

CD4 count and antiretroviral initiation, proxies for immune status and HIV stage, were associated with Mtb sensitisation and TB disease. Inadequate performance of clinical prediction models may reflect predominantly subclinical disease diagnosed in this setting and unmeasured local site factors affecting transmission and progression.

FUNDING

The CORTIS-HR study was funded by the Bill & Melinda Gates Foundation (OPP1151915) and by the Strategic Health Innovation Partnerships Unit of the South African Medical Research Council with funds received from the South African Department of Science and Technology. The regulatory sponsor was the University of Cape Town.

Histone acetylome-wide associations in immune cells from individuals with active Mycobacterium tuberculosis infection

Host cell chromatin changes are thought to play an important role in the pathogenesis of infectious diseases. Here we describe a histone acetylome-wide association study (HAWAS) of an infectious disease, on the basis of genome-wide H3K27 acetylation profiling of peripheral blood granulocytes and monocytes from persons with active Mycobacterium tuberculosis (Mtb) infection and healthy controls. We detected >2,000 differentially acetylated loci in either cell type in a Singapore Chinese discovery cohort (n = 46), which were validated in a subsequent multi-ethnic Singapore cohort (n = 29), as well as a longitudinal cohort from South Africa (n = 26), thus demonstrating that HAWAS can be independently corroborated. Acetylation changes were correlated with differential gene expression. Differential acetylation was enriched near potassium channel genes, including KCNJ15, which modulates apoptosis and promotes Mtb clearance in vitro. We performed histone acetylation quantitative trait locus (haQTL) analysis on the dataset and identified 69 candidate causal variants for immune phenotypes among granulocyte haQTLs and 83 among monocyte haQTLs. Our study provides proof-of-principle for HAWAS to infer mechanisms of host response to pathogens.

Genome-wide histone acetylation profiling in cohorts of patients with active and latent tuberculosis reveals acetylation changes in host immune cells modulating potassium channel expression and apoptosis response.

Using population-specific add-on polymorphisms to improve genotype imputation in underrepresented populations

Genome-wide association studies rely on the statistical inference of untyped variants, called imputation, to increase the coverage of genotyping arrays. However, the results are often suboptimal in populations underrepresented in existing reference panels and array designs, since the selected single nucleotide polymorphisms (SNPs) may fail to capture population-specific haplotype structures, hence the full extent of common genetic variation. Here, we propose to sequence the full genomes of a small subset of an underrepresented study cohort to inform the selection of population-specific add-on tag SNPs and to generate an internal population-specific imputation reference panel, such that the remaining array-genotyped cohort could be more accurately imputed. Using a Tanzania-based cohort as a proof-of-concept, we demonstrate the validity of our approach by showing improvements in imputation accuracy after the addition of our designed add-on tags to the base H3Africa array.

Genome-wide association studies, which study the association between genetic variants and various phenotypes, typically rely on genotyping arrays. Only a small proportion of genetic variants within the genome are typed on genotyping arrays. Untyped variants are statistically inferred through a process known as genotype imputation, where correlations between variants (haplotypes) observed in external reference panels are leveraged to infer untyped variants in the study population. However, for study populations that are underrepresented in existing reference panels, the quality of imputation is often sub-optimal. This is because typed variants incorporated on existing genotyping arrays can be unsuitable for the study population, and haplotype structures can be different between the reference and the study population. Here, we illustrate an approach to select a custom set of population-specific typed variants to improve genotype imputation in such underrepresented populations.

Local Ancestry Adjusted Allelic Association Analysis Robustly Captures Tuberculosis Susceptibility Loci

Pulmonary tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease. The risk of developing active TB is in part determined by host genetic factors. Most genetic studies investigating TB susceptibility fail to replicate association signals particularly across diverse populations. South African populations arose because of multi-wave genetic admixture from the indigenous KhoeSan, Bantu-speaking Africans, Europeans, Southeast Asian-and East Asian populations. This has led to complex genetic admixture with heterogenous patterns of linkage disequilibrium and associated traits. As a result, precise estimation of both global and local ancestry is required to prevent both false positive and false-negative associations. Here, 820 individuals from South Africa were genotyped on the SNP-dense Illumina Multi-Ethnic Genotyping Array (∼1.7M SNPs) followed by local and global ancestry inference using RFMix. Local ancestry adjusted allelic association (LAAA) models were utilized owing to the extensive genetic heterogeneity present in this population. Hence, an interaction term, comprising the identification of the minor allele that corresponds to the ancestry present at the specific locus under investigation, was included as a covariate. One SNP (rs28647531) located on chromosome 4q22 was significantly associated with TB susceptibility and displayed a SNP minor allelic effect (G allele, frequency = 0.204) whilst correcting for local ancestry for Bantu-speaking African ancestry (p-value = 5.518 × 10^-7; OR = 3.065; SE = 0.224). Although no other variants passed the significant threshold, clear differences were observed between the lead variants identified for each ancestry. Furthermore, the LAAA model robustly captured the source of association signals in multi-way admixed individuals from South Africa and allowed the identification of ancestry-specific disease risk alleles associated with TB susceptibility that have previously been missed.

A sex-specific evolutionary interaction between ADCY9 and CETP

Pharmacogenomic studies have revealed associations between rs1967309 in the adenylyl cyclase type 9 (ADCY9) gene and clinical responses to the cholesteryl ester transfer protein (CETP) modulator dalcetrapib, however, the mechanism behind this interaction is still unknown. Here, we characterized selective signals at the locus associated with the pharmacogenomic response in human populations and we show that rs1967309 region exhibits signatures of positive selection in several human populations. Furthermore, we identified a variant in CETP, rs158477, which is in long-range linkage disequilibrium with rs1967309 in the Peruvian population. The signal is mainly seen in males, a sex-specific result that is replicated in the LIMAA cohort of over 3400 Peruvians. Analyses of RNA-seq data further suggest an epistatic interaction on CETP expression levels between the two SNPs in multiple tissues, which also differs between males and females. We also detected interaction effects of the two SNPs with sex on cardiovascular phenotypes in the UK Biobank, in line with the sex-specific genotype associations found in Peruvians at these loci. We propose that ADCY9 and CETP coevolved during recent human evolution due to sex-specific selection, which points toward a biological link between dalcetrapib’s pharmacogene ADCY9 and its therapeutic target CETP.

Reduced thyroxine production in young household contacts of tuberculosis patients increases active tuberculosis disease risk

In the current study, we followed 839 household contacts (HHCs) of tuberculosis (TB) patients for 2 years and identified the factors that enhanced the development of TB. Fourteen of the 17 HHCs who progressed to TB were in the 15- to 30-year-old age group. At baseline (the “0“ time point, when all the individuals were healthy), the concentration of the thyroid hormone thyroxine (T4) was lower, and there were increased numbers of Tregs in PBMCs of TB progressors. At baseline, PBMCs from TB progressors stimulated with early secretory antigenic target 6 (ESAT-6) and 10 kDa culture filtrate antigen (CFP-10) produced less IL-1α. Thyroid hormones inhibited Mycobacterium tuberculosis (Mtb) growth in macrophages in an IL-1α–dependent manner. Mtb-infected Thra1^PV/+ (mutant thyroid hormone receptor) mice had increased mortality and reduced IL-1α production. Our findings suggest that young HHCs who exhibit decreased production of thyroid hormones are at high risk of developing active TB disease.

Underwhelming or Misunderstood? Genetic Variability of Pattern Recognition Receptors in Immune Responses and Resistance to Mycobacterium tuberculosis

Human genetic control is thought to affect a considerable part of the outcome of infection with Mycobacterium tuberculosis (Mtb). Most of us deal with the pathogen by containment (associated with clinical "latency") or sterilization, but tragically millions each year do not. After decades of studies on host genetic susceptibility to Mtb infection, genetic variation has been discovered to play a role in tuberculous immunoreactivity and tuberculosis (TB) disease. Genes encoding pattern recognition receptors (PRRs) enable a consistent, molecularly direct interaction between humans and Mtb which suggests the potential for co-evolution. In this review, we explore the roles ascribed to PRRs during Mtb infection and ask whether such a longstanding and intimate interface between our immune system and this pathogen plays a critical role in determining the outcome of Mtb infection. The scientific evidence to date suggests that PRR variation is clearly implicated in altered immunity to Mtb but has a more subtle role in limiting the pathogen and pathogenesis. In contrast to 'effectors' like IFN-γ, IL-12, Nitric Oxide and TNF that are critical for Mtb control, 'sensors' like PRRs are less critical for the outcome of Mtb infection. This is potentially due to redundancy of the numerous PRRs in the innate arsenal, such that Mtb rarely goes unnoticed. Genetic association studies investigating PRRs during Mtb infection should therefore be designed to investigate endophenotypes of infection - such as immunological or clinical variation - rather than just TB disease, if we hope to understand the molecular interface between innate immunity and Mtb.

Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease

Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA and surface protein data from 500,089 memory T cells to define 31 cell states from 259 individuals in a Peruvian tuberculosis (TB) progression cohort. At immune steady state >4 years after infection and disease resolution, we found that, after accounting for significant effects of age, sex, season and genetic ancestry on T cell composition, a polyfunctional type 17 helper T (TH17) cell-like effector state was reduced in abundance and function in individuals who previously progressed from Mycobacterium tuberculosis (M.tb) infection to active TB disease. These cells are capable of responding to M.tb peptides. Deconvoluting this state-uniquely identifiable with multimodal analysis-from public data demonstrated that its depletion may precede and persist beyond active disease. Our study demonstrates the power of integrative multimodal single-cell profiling to define cell states relevant to disease and other traits.

Immunological lessons from genome-wide association studies of infections

Over the past few years, genome-wide association studies (GWAS) have been increasingly applied to identify host genetic factors influencing clinical and laboratory traits related to immunity and infection, and to understand the interplay between the host and the microbial genomes. By screening large cohorts of individuals suffering from various infectious diseases, GWAS explored resistance against infection, natural history of the disease, development of life-threatening clinical signs, and innate and adaptive immune responses. These efforts provided fundamental insight on the role of major genes in the interindividual variability in the response to infection and on the mechanisms of the immune response against human pathogens both at the individual and population levels.

These Are the Genes You're Looking For: Finding Host Resistance Genes

Humanity's ongoing struggle with new, re-emerging and endemic infectious diseases serves as a frequent reminder of the need to understand host-pathogen interactions. Recent advances in genomics have dramatically advanced our understanding of how genetics contributes to host resistance or susceptibility to bacterial infection. Here we discuss current trends in defining host-bacterial interactions at the genome-wide level, including screens that harness CRISPR/Cas9 genome editing, natural genetic variation, proteomics, and transcriptomics. We report on the merits, limitations, and findings of these innovative screens and discuss their complementary nature. Finally, we speculate on future innovation as we continue to progress through the postgenomic era and towards deeper mechanistic insight and clinical applications.

Host genetics and infectious disease: new tools, insights and translational opportunities

Understanding how human genetics influence infectious disease susceptibility offers the opportunity for new insights into pathogenesis, potential drug targets, risk stratification, response to therapy and vaccination. As new infectious diseases continue to emerge, together with growing levels of antimicrobial resistance and an increasing awareness of substantial differences between populations in genetic associations, the need for such work is expanding. In this Review, we illustrate how our understanding of the host–pathogen relationship is advancing through holistic approaches, describing current strategies to investigate the role of host genetic variation in established and emerging infections, including COVID-19, the need for wider application to diverse global populations mirroring the burden of disease, the impact of pathogen and vector genetic diversity and a broad array of immune and inflammation phenotypes that can be mapped as traits in health and disease. Insights from study of inborn errors of immunity and multi-omics profiling together with developments in analytical methods are further advancing our knowledge of this important area.

Infectious diseases are an ever-present global threat. In this Review, Kwok, Mentzer and Knight discuss our latest understanding of how human genetics influence susceptibility to disease. Furthermore, they discuss emerging progress in the interplay between host and pathogen genetics, molecular responses to infection and vaccination, and opportunities to bring these aspects together for rapid responses to emerging diseases such as COVID-19.

Mycobacterium tuberculosis complex and human coadaptation: a two-way street complicating host susceptibility to TB

For centuries, the Mycobacterium tuberculosis complex (MTBC) has infected numerous populations, both human and non-human, causing symptomatic tuberculosis (TB) in some hosts. Research investigating the MTBC and how it has evolved with its host over time is sparse and has not resulted in many significant findings. There are even fewer studies investigating adaptation of the human host susceptibility to TB and these have largely focused on genome-wide association and candidate gene association studies. However, results emanating from these association studies are rarely replicated and appear to be population specific. It is, therefore, necessary to relook at the approach taken to investigate the relationship between the MTBC and the human host. Understanding that the evolution of the pathogen is coupled to the evolution of the host might be the missing link needed to effectively investigate their relationship. We hypothesize that this knowledge will bolster future efforts in combating the disease.

A positively selected FBN1 missense variant reduces height in Peruvian individuals

On average, Peruvian individuals are among the shortest in the world¹. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.

Challenges of Immune Response Diversity in the Human Population Concerning New Tuberculosis Diagnostics, Therapies, and Vaccines

Universal approaches to the prevention and treatment of human diseases fail to take into account profound immune diversity resulting from genetic variations across populations. Personalized or precision medicine takes into account individual lifestyle, environment, and biology (genetics and immune status) and is being adopted in several disease intervention strategies such as cancer and heart disease. However, its application in infectious diseases, particularly global diseases such as tuberculosis (TB), is far more complex and in a state of infancy. Here, we discuss the impact of human genetic variations on immune responses and how they relate to failures seen in current TB diagnostic, therapy, and vaccine approaches across populations. We offer our perspective on the challenges and potential for more refined approaches going forward.

Human global and population-specific genetic susceptibility to Mycobacterium tuberculosis infection and disease

PURPOSE OF REVIEW

Multiple lines of evidence support a role of the host genetic component in Mycobacterium tuberculosis infection and disease progression. However, genomic studies of tuberculosis susceptibility have been disappointing compared with that of other complex disorders. Recently the field has explored alternative strategies to facilitate locus discovery. Results emanating from these efforts during the last 18 months are addressed in this review.

RECENT FINDINGS

There has been a renewed focus on the refinement of phenotypic definitions of infection and disease as well as on age-related, sex-specific and population-specific effects. Genome-wide association studies have yielded candidate genes but the findings have not always been transferable to all population groups. Candidate gene association studies remain popular as it is used for GWAS replication and is affordable, particularly in lower and middle-income countries. Pharmacogenetic studies involving tuberculosis drugs may locate variants that can be cost-effectively genotyped to identify individuals at risk of developing adverse events during treatment.

SUMMARY

Additional GWAS and candidate gene association studies of crudely defined study participants are unlikely to make further important contributions to the TB susceptibility field. Instead refined phenotyping will allow the elucidation of genetic mechanisms contributing to infection and disease in distinct populations and the calculation of polygenic risk scores.