The X chromosome and sex-specific effects in infectious disease susceptibility

The X chromosome and X-linked variants have largely been ignored in genome-wide and candidate association studies of infectious diseases due to the complexity of statistical analysis of the X chromosome. This exclusion is significant, since the X chromosome contains a high density of immune-related genes and regulatory elements that are extensively involved in both the innate and adaptive immune responses. Many diseases present with a clear sex bias, and apart from the influence of sex hormones and socioeconomic and behavioural factors, the X chromosome, X-linked genes and X chromosome inactivation mechanisms contribute to this difference. Females are functional mosaics for X-linked genes due to X chromosome inactivation and this, combined with other X chromosome inactivation mechanisms such as genes that escape silencing and skewed inactivation, could contribute to an immunological advantage for females in many infections. In this review, we discuss the involvement of the X chromosome and X inactivation in immunity and address its role in sexual dimorphism of infectious diseases using tuberculosis susceptibility as an example, in which male sex bias is clear, yet not fully explored.

TLR1, 2, 4, 6 and 9 Variants Associated with Tuberculosis Susceptibility: A Systematic Review and Meta-Analysis

BACKGROUND

Studies investigating the influence of toll-like receptor (TLR) polymorphisms and tuberculosis susceptibility have yielded varying and often contradictory results in different ethnic groups. A meta-analysis was conducted to investigate the relationship between TLR variants and susceptibility to tuberculosis, both across and within specific ethnic groups.

METHODS

An extensive database search was performed for studies investigating the relationship between TLR and tuberculosis (TB) susceptibility. Data was subsequently extracted from included studies and statistically analysed.

RESULTS

32 articles involving 18907 individuals were included in this meta-analysis, and data was extracted for 14 TLR polymorphisms. Various genetic models were employed. An increased risk of TB was found for individuals with the TLR2 rs3804100 CC and the TLR9 rs352139 GA and GG genotypes, while decreased risk was identified for those with the AG genotype of TLR1 rs4833095. The T allele of TLR6 rs5743810 conferred protection across all ethnic groups. TLR2 rs5743708 subgroup analysis identified the A allele to increase susceptibility to TB in the Asian ethnic group, while conferring protection in the Hispanic group. The T allele of TLR4 rs4986791 was also found to increase the risk of TB in the Asian subgroup. All other TLR gene variants investigated were not found to be associated with TB in this meta-analysis.

DISCUSSION

Although general associations were identified, most TLR variants showed no significant association with TB, indicating that additional studies investigating a wider range of pattern recognition receptors is required to gain a better understanding of this complex disease.

Stable transfection of protein kinase C alpha cDNA in hormone-dependent breast cancer cell lines

An inverse relationship between protein kinase C (PKC) activity and oestrogen receptor (ER) expression in human breast cell lines and tumours has been firmly established over the past 10 years. To determine whether specific alterations in PKC expression accompany hormone-independence, we examined the expression of PKC isozymes in the hormone-independent human breast cancer cell clones MCF-7 5C and T47D:C42 compared with their hormone-dependent counterparts, MCF-7 A4, MCF-7 WS8 and T47D:A18 respectively. Both hormone-independent cell clones exhibit elevated PKC alpha expression and increased basal AP-1 activity compared with the hormone-dependent cell clones. To determine whether PKC alpha overexpression is sufficient to mediate the hormone-independent phenotype, we stably transfected an expression plasmid containing PKC alpha cDNA to the T47D:A18 and MCF-7 A4 cell lines. This is the first report of PKC alpha transfection in T47D cells. In contrast to MCF-7 cells, T47D has the propensity to lose the ER and more readily forms tamoxifen-stimulated tumours in athymic mice. We find that in T47D:A18/PKC alpha clones, there is concomitant up-regulation of PKC beta I and delta, whereas in the MCF-7 A4/PKC alpha transfectants PKC epsilon is up-regulated. In T47D:A18, but not in MCF-7 A4, PKC alpha stable transfection is accompanied by down-regulation of ER function whilst basal AP-1 activity is elevated. Our results suggest PKC alpha overexpression may play a role in growth signalling during the shift from hormone dependent to hormone-independent breast cancers.

Evaluating the Accuracy of Imputation Methods in a Five-Way Admixed Population

Genotype imputation is a powerful tool for increasing statistical power in an association analysis. Meta-analysis of multiple study datasets also requires a substantial overlap of SNPs for a successful association analysis, which can be achieved by imputation. Quality of imputed datasets is largely dependent on the software used, as well as the reference populations chosen. The accuracy of imputation of available reference populations has not been tested for the five-way admixed South African Colored (SAC) population. In this study, imputation results obtained using three freely-accessible methods were evaluated for accuracy and quality. We show that the African Genome Resource is the best reference panel for imputation of missing genotypes in samples from the SAC population, implemented via the freely accessible Sanger Imputation Server.

Lectin-associated proteins from the seeds of Leguminosae

The seeds of Pisum sativum (pea), Canavalia ensiformis, Vicia faba, Vicia sativa, and Ricinus communis were shown to contain proteins which are associated to the respective lectins (lectin binders). The lectin binders from Pisum sativum and Canavalia ensiformis were studied more closely. Both are single proteins not resembling the variety of membrane glycoproteins found in animals and plants which bind to lectins. The pea lectin binder is a tetrameric glycoprotein composed of identical subunits of the Mr 51 000. Its interaction with the lectin is abolished by acidic buffers or by glucose. The Concanavalin A binder, which does not contain sugar, is composed of one kind of subunit, Mr of 35 000. As in the case of the pea lectin binder, glucose and acid dissociate the lectin-lectin binder complex, but in contrast to the pea lectin binder low NaCl concentrations also cause this effect. During germination and growth, the Concanavalin A binder appears in the roots.

On effects of discretization on estimators of drift parameters for diffusion processes

In this paper statistical properties of estimators of drift parameters for diffusion processes are studied by modern numerical methods for stochastic differential equations. This is a particularly useful method for discrete time samples, where estimators can be constructed by making discrete time approximations to the stochastic integrals appearing in the maximum likelihood estimators for continuously observed diffusions. A review is given of the necessary theory for parameter estimation for diffusion processes and for simulation of diffusion processes. Three examples are studied.

A Sex-Stratified Genome-Wide Association Study of Tuberculosis Using a Multi-Ethnic Genotyping Array

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease with a known human genetic component. Males seem to be more affected than females and in most countries the TB notification rate is twice as high in males than in females. While socio-economic status, behavior and sex hormones influence the male bias they do not fully account for it. Males have only one copy of the X chromosome, while diploid females are subject to X chromosome inactivation. In addition, the X chromosome codes for many immune-related genes, supporting the hypothesis that X-linked genes could contribute to TB susceptibility in a sex-biased manner. We report the first TB susceptibility genome-wide association study (GWAS) with a specific focus on sex-stratified autosomal analysis and the X chromosome. A total of 810 individuals (410 cases and 405 controls) from an admixed South African population were genotyped using the Illumina Multi Ethnic Genotyping Array, specifically designed as a suitable platform for diverse and admixed populations. Association testing was done on the autosome (8,27,386 variants) and X chromosome (20,939 variants) in a sex stratified and combined manner. SNP association testing was not statistically significant using a stringent cut-off for significance but revealed likely candidate genes that warrant further investigation. A genome wide interaction analysis detected 16 significant interactions. Finally, the results highlight the importance of sex-stratified analysis as strong sex-specific effects were identified on both the autosome and X chromosome.

Polymorphisms in the Pattern Recognition Receptor Mincle Gene (CLEC4E) and Association with Tuberculosis

The mechanisms involved in interactions between Mycobacterium tuberculosis and host innate immune cells determine outcome. Antigen-presenting cells, including macrophages and dendritic cells, express many pattern recognition receptors to identify pathogen-associated molecular patterns, thereby initiating an immune response. A major mycobacterial virulence factor, trehalose-6',6-dimycolate, is recognised by the macrophage-inducible C-type lectin, Mincle, which leads to the activation of the Syk-Card9 signalling pathway in macrophages. Mincle is encoded by CLEC4E, and we investigated polymorphisms in this gene to assess its role in tuberculosis susceptibility. Four tagging single nucleotide polymorphisms (SNPs) (rs10841845, rs10841847, rs10841856 and rs4620776) were genotyped using TaqMan(®) SNP assays in 416 tuberculosis cases and 405 healthy controls. Logistic regression models were used for analysis. No association was detected with any of the SNPs analysed. This research highlights tuberculosis disease complexity where recognition proteins which specifically bind mycobacterial glycolipids cannot be conclusively associated with the disease in genetic studies.

The role of human host genetics in tuberculosis resistance

INTRODUCTION

Tuberculosis (TB) remains a public health problem: the latest estimate of new incident cases per year is a staggering 10.4 million. Despite this overwhelming number, the majority of the immunocompetent population can control infection with Mycobacterium tuberculosis. The human genome underlies the immune response and contributes to the outcome of TB infection. Areas covered: Investigations of TB resistance in the general population have closely mirrored those of other infectious diseases and initially involved epidemiological observations. Linkage and association studies, including studies of VDR, SLC11A1 and HLA-DRB1 followed. Genome-wide association studies of common variants, not necessarily sufficient for disease, became possible after technological advancements. Other approaches involved the identification of those individuals with rare disease-causing mutations that strongly predispose to TB, epistasis and the role of ethnicity in disease. Despite these efforts, infection outcome, on an individual basis, cannot yet be predicted. Expert commentary: The early identification of future disease progressors is necessary to stem the TB epidemic. Human genetics may contribute to this endeavour and could in future suggest pathways to target for disease prevention. This will however require concerted efforts to establish large, well-phenotyped cohorts from different ethnicities, improved genomic resources and a better understanding of the human genome architecture.

A regulatory variant in the C1Q gene cluster is associated with tuberculosis susceptibility and C1qA plasma levels in a South African population

Several genetic studies have implicated genes that encode for components of the innate immune response in tuberculosis (TB) susceptibility. The complement system is an early player in the innate immune response and provides the host with initial protection by promoting phagocytosis of apoptotic or necrotic cells. The C1q molecule is the first component of the classical pathway that leads to the activation of complement by binding to immune complexes and is encoded by the C1Q gene cluster. We investigated variants in this region to determine its association with TB susceptibility. Five single nucleotide polymorphisms (SNPs) (rs12033074, rs631090, rs172378, rs587585, and rs665691) were genotyped using TaqMan® SNP assays in 456 TB cases and 448 healthy controls and analysed by logistic regression models. The rs587585 variant showed a significant additive allelic association where the minor G allele was found more frequently in TB cases than in controls in both the discovery (p = 0.023; OR = 1.30; 95% CI, 1.04-1.64) and validation cohort (p = 0.038; OR = 1.31; 95% CI, 1.22-1.40). In addition, we detected increased C1qA expression when comparing cases and controls (p = 0.037) and linked this to a dosage effect of the G allele, which increased C1qA expression in TB cases. This is the first study to report the association of C1Q gene polymorphisms with progression to tuberculosis.

A multi-phenotype genome-wide association study of clades causing tuberculosis in a Ghanaian- and South African cohort

Despite decades of research and advancements in diagnostics and treatment, tuberculosis remains a major public health concern. New computational methods are needed to interrogate the intersection of host- and bacterial genomes. Paired host genotype datum and infecting bacterial isolate information were analysed for associations using a multinomial logistic regression framework implemented in SNPTest. A cohort of 853 admixed South African participants and a Ghanaian cohort of 1359 participants were included. Two directly genotyped variants, namely rs529920 and rs41472447, were identified in the Ghanaian cohort as being statistically significantly associated with risk for infection with strains of different members of the MTBC. Thus, a multinomial logistic regression using paired host-pathogen data may prove valuable for investigating the complex relationships driving infectious disease.

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.

IMPUTOR: Phylogenetically Aware Software for Imputation of Errors in Next-Generation Sequencing

We introduce IMPUTOR, software for phylogenetically aware imputation of missing haploid nonrecombining genomic data. Targeted for next-generation sequencing data, IMPUTOR uses the principle of parsimony to impute data marked as missing due to low coverage. Along with efficiently imputing missing variant genotypes, IMPUTOR is capable of reliably and accurately correcting many nonmissing sites that represent spurious sequencing errors. Tests on simulated data show that IMPUTOR is capable of detecting many induced mutations without making erroneous imputations/corrections, with as many as 95% of missing sites imputed and 81% of errors corrected under optimal conditions. We tested IMPUTOR with human Y-chromosomes from pairs of close relatives and demonstrate IMPUTOR's efficacy in imputing missing and correcting erroneous calls.

Persistence of Mycobacterium tuberculosis in response to infection burden and host-induced stressors

Introduction

As infection with Mycobacterium tuberculosis progresses, the bacilli experience various degrees of host stressors in the macrophage phagosome such as low pH, nutrient deprivation, or exposure to toxic agents, which promotes cell-to-cell phenotypic variation. This includes a physiologically viable but non- or slowly replicating persister subpopulation, which is characterised by a loss of growth on solid media, while remaining metabolically active. Persisters additionally evade the host immune response and macrophage antimicrobial processes by adapting their metabolic pathways to maintain survival and persistence in the host.

Methods

A flow cytometry-based dual-fluorescent replication reporter assay, termed fluorescence dilution, provided a culture-independent method to characterize the single-cell replication dynamics of M. tuberculosis persisters following macrophage infection. Fluorescence dilution in combination with reference counting beads and a metabolic esterase reactive probe, calcein violet AM, provided an effective approach to enumerate and characterize the phenotypic heterogeneity within M. tuberculosis following macrophage infection.

Results

Persister formation appeared dependent on the initial infection burden and intracellular bacterial burden. However, inhibition of phagocytosis by cytochalasin D treatment resulted in a significantly higher median percentage of persisters compared to inhibition of phagosome acidification by bafilomycin A1 treatment.

Discussion

Our results suggest that different host factors differentially impact the intracellular bacterial burden, adaptive mechanisms and entry into persistence in macrophages.

Deciphering Genetic Susceptibility to Tuberculous Meningitis

Tuberculous meningitis (TBM) is the most severe form of extrapulmonary tuberculosis (TB) that arises when a caseating meningeal granuloma discharges its contents into the subarachnoid space. It accounts for ~1% of all disease caused by Mycobacterium tuberculosis and the age of peak incidence is from 2-4 years. The exact pathogenesis of TBM is still not fully understood and the mechanism(s) by which the bacilli initially invade the blood-brain-barrier are still to be elucidated. This study investigated the involvement of the host genome in TBM susceptibility, by considering common variants (minor allele frequency (MAF) >5%) using microarray genotyping and rare variants (MAF <1%) via exome sequencing. A total of 123 TBM cases, 400 pulmonary TB (pTB) cases and 477 healthy controls were genotyped on the MEGA array. A genome-wide association study (GWAS) comparing 114 TBM cases to 395 healthy controls showed no association with TBM susceptibility. A second analysis comparing 114 TBM cases to 382 pTB cases was conducted to investigate variants associated with different TB phenotypes. No significant associations were found with progression from pTB to TBM. Ten TBM cases and 10 healthy controls were exome sequenced. Gene set association tests SKAT-O and SKAT Common Rare were used to assess the association of rare SNPs and the cumulative effect of both common and rare SNPs with susceptibility to TBM, respectively. Ingenuity Pathway Analysis (IPA) of the top-hits of the SKAT-O analysis showed that NOD2 and CYP4F2 are both important in TBM pathogenesis and highlighted these as targets for future study. For the SKAT Common Rare analysis Centriolar Coiled-Coil Protein 110 (CCP110) was nominally associated (p = 5.89x10^-6) with TBM susceptibility. In addition, several top-hit genes ascribed to the development of the central nervous system (CNS) and innate immune system regulation were identified. Exome sequencing and GWAS of our TBM cohort has identified a single previously undescribed association of CCP110 with TBM susceptibility. These results advance our understanding of TBM in terms of both variants and genes that influence susceptibility. In addition, several candidate genes involved in innate immunity have been identified for further genotypic and functional investigation.

African wild dogs (Lycaon pictus) from the Kruger National Park, South Africa are currently not inbred but have low genomic diversity

African wild dogs (Lycaon pictus) have undergone severe population reductions and are listed as endangered on the International Union for Conservation of Nature Red List. Small, isolated populations have the potential to suffer from threats to their genetic diversity that may impact species viability and future survival. This study provides the first set of population-wide genomic data to address conservation concerns for this endangered species. Whole genome sequencing data were generated for 71 free-ranging African wild dogs from the Kruger National Park (KNP), South Africa, and used to estimate important population genomic parameters. Genomic diversity metrics revealed that variation levels were low; however, this African wild dog population showed low levels of inbreeding. Very few first- and second-order relationships were observed in this cohort, with most relationships falling into the third-order or distant category. Patterns of homozygosity could have resulted from historical inbreeding or a loss in genome variation due to a population bottleneck. Although the results suggest that this stronghold African wild dog population maintains low levels of inbreeding, likely due to their cooperative breeding system, it may lead to a continuous population decline when a reduced number of suitable mates are available. Consequently, the low genomic variation may influence species viability over time. This study highlights the importance of assessing population genomic parameters to set conservation priorities. Future studies should include the investigation of the potential of this endangered species to adapt to environmental changes considering the low genomic diversity in this population.

Epidemiologic evidence for a new class of compounds associated with toxic oil syndrome

Toxic oil syndrome appeared in epidemic form in Spain in 1981. Epidemiologic studies have demonstrated that illness was caused by consumption of rapeseed oil that had been denatured with aniline. Chemical analyses of oil specimens conducted in conjunction with epidemiologic studies have established that consumption of specific oils containing fatty acid anilide contaminants was associated with increased risk for disease. New chemical analytic methods identified a family of compounds, the di-fatty acid esters of phenylamino propane-diol, and one of these compounds, the 1,2-di-oleyl ester of 3-(N-phenylamino)-1,2-propanediol (DPAP), has been found to be more strongly associated with disease status than the fatty acid anilides. We found the odds ratio for exposure to DPAP (OR = 26.4, 95% CI = 6.4-76.3) is much higher than the odds ratio for exposure to oleyl anilide (OR = 4.1, 95% CI = 2.2-7.8), implying that exposure to DPAP was a more relevant risk factor for development of toxic oil syndrome than exposure to oleyl anilide. In this paper, we review and present analyses of data from multiple studies of the possible etiologic role of DPAP in toxic oil syndrome. The presence of DPAP in oil collected from affected and unaffected households was a more specific correlate of case relatedness than was the presence of fatty acid anilides, and it was equally sensitive. Moreover, DPAP was found in oil from the only refinery whose oil was clearly associated with illness.

Simulating mismatch between calibration and target population in AI for mammography the retrospective VAIB study

AI cancer detection models require calibration to attain the desired balance between cancer detection rate (CDR) and false positive rate. In this study, we simulate the impact of six types of mismatches between the calibration population and the clinical target population, by creating purposefully non-representative datasets to calibrate AI for clinical settings. Mismatching the acquisition year between healthy and cancer-diagnosed screening participants led to a distortion in CDR between -3% to +19%. Mismatching age led to a distortion in CDR between -0.2% to +27%. Mismatching breast density distribution led to a distortion in CDR between +1% to 16%. Mismatching mammography vendors lead to a distortion in CDR between -32% to + 33%. Mismatches between calibration population and target clinical population lead to clinically important deviations. It is vital for safe clinical AI integration to ensure that important aspects of the calibration population are representative of the target population.

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.

Data Harmonization Guidelines to Combine Multi-platform Genomic Data from Admixed Populations and Boost Power in Genome-Wide Association Studies

Data harmonization involves combining data from multiple independent sources and processing the data to produce one uniform dataset. Merging separate genotypes or whole-genome sequencing datasets has been proposed as a strategy to increase the statistical power of association tests by increasing the effective sample size. However, data harmonization is not a widely adopted strategy due to the difficulties with merging data (including confounding produced by batch effects and population stratification). Detailed data harmonization protocols are scarce and are often conflicting. Moreover, data harmonization protocols that accommodate samples of admixed ancestry are practically non-existent. Existing data harmonization procedures must be modified to ensure the heterogeneous ancestry of admixed individuals is incorporated into additional downstream analyses without confounding results. Here, we propose a set of guidelines for merging multi-platform genetic data from admixed samples that can be adopted by any investigator with elementary bioinformatics experience. We have applied these guidelines to aggregate 1544 tuberculosis (TB) case-control samples from six separate in-house datasets and conducted a genome-wide association study (GWAS) of TB susceptibility. The GWAS performed on the merged dataset had improved power over analyzing the datasets individually and produced summary statistics free from bias introduced by batch effects and population stratification. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Processing separate datasets comprising array genotype data Alternate Protocol 1: Processing separate datasets comprising array genotype and whole-genome sequencing data Alternate Protocol 2: Performing imputation using a local reference panel Basic Protocol 2: Merging separate datasets Basic Protocol 3: Ancestry inference using ADMIXTURE and RFMix Basic Protocol 4: Batch effect correction using pseudo-case-control comparisons.

VAI-B: a multicenter platform for the external validation of artificial intelligence algorithms in breast imaging

Purpose

Multiple vendors are currently offering artificial intelligence (AI) computer-aided systems for triage detection, diagnosis, and risk prediction of breast cancer based on screening mammography. There is an imminent need to establish validation platforms that enable fair and transparent testing of these systems against external data.

Approach

We developed validation of artificial intelligence for breast imaging (VAI-B), a platform for independent validation of AI algorithms in breast imaging. The platform is a hybrid solution, with one part implemented in the cloud and another in an on-premises environment at Karolinska Institute. Cloud services provide the flexibility of scaling the computing power during inference time, while secure on-premises clinical data storage preserves their privacy. A MongoDB database and a python package were developed to store and manage the data on-premises. VAI-B requires four data components: radiological images, AI inferences, radiologist assessments, and cancer outcomes.

Results

To pilot test VAI-B, we defined a case-control population based on 8080 patients diagnosed with breast cancer and 36,339 healthy women based on the Swedish national quality registry for breast cancer. Images and radiological assessments from more than 100,000 mammography examinations were extracted from hospitals in three regions of Sweden. The images were processed by AI systems from three vendors in a virtual private cloud to produce abnormality scores related to signs of cancer in the images. A total of 105,706 examinations have been processed and stored in the database.

Conclusions

We have created a platform that will allow downstream evaluation of AI systems for breast cancer detection, which enables faster development cycles for participating vendors and safer AI adoption for participating hospitals. The platform was designed to be scalable and ready to be expanded should a new vendor want to evaluate their system or should a new hospital wish to obtain an evaluation of different AI systems on their images.