Model-based precision dosing and remedial dosing recommendations for delayed or missed doses of isoniazid in Chinese patients with tuberculosis

AIMS

Isoniazid (INH) has been used as a first-line drug to treat tuberculosis (TB) for more than 50 years. However, large interindividual variability was found in its pharmacokinetics, and effects of nonadherence to INH treatment and corresponding remedy regime remain unclear. This study aimed to develop a population pharmacokinetic (PPK) model of INH in Chinese patients with TB to provide model-informed precision dosing and explore appropriate remedial dosing regimens for nonadherent patients.

METHODS

In total, 1012 INH observations from 736 TB patients were included. A nonlinear mixed-effects modelling was used to analyse the PPK of INH. Using Monte Carlo simulations to determine optimal dosage regimens and design remedial dosing regimens.

RESULTS

A 2-compartmental model, including first-order absorption and elimination with allometric scaling, was found to best describe the PK characteristics of INH. A mixture model was used to characterize dual rates of INH elimination. Estimates of apparent clearance in fast and slow eliminators were 28.0 and 11.2 L/h, respectively. The proportion of fast eliminators in the population was estimated to be 40.5%. Monte Carlo simulations determined optimal dosage regimens for slow and fast eliminators with different body weight. For remedial dosing regimens, the missed dose should be taken as soon as possible when the delay does not exceed 12 h, and an additional dose is not needed. delay for an INH dose exceeds 12 h, the patient only needs to take the next single dose normally.

CONCLUSION

PPK modelling and simulation provide valid evidence on the precision dosing and remedial dosing regimen of INH.

Effects and mechanisms of polycyclic aromatic hydrocarbons in inflammatory skin diseases

Polycyclic aromatic hydrocarbons (PAHs) are hydrocarbons characterized by the presence of multiple benzene rings. They are ubiquitously found in the natural environment, especially in environmental pollutants, including atmospheric particulate matter, cigarette smoke, barbecue smoke, among others. PAHs can influence human health through several mechanisms, including the aryl hydrocarbon receptor (AhR) pathway, oxidative stress pathway, and epigenetic pathway. In recent years, the impact of PAHs on inflammatory skin diseases has garnered significant attention, yet many of their underlying mechanisms remain poorly understood. We conducted a comprehensive review of articles focusing on the link between PAHs and several inflammatory skin diseases, including psoriasis, atopic dermatitis, lupus erythematosus, and acne. This review summarizes the effects and mechanisms of PAHs in these diseases and discusses the prospects and potential therapeutic implications of PAHs for inflammatory skin diseases.

Life factors acting on systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a highly heterogeneous autoimmune disease that primarily affects women. Currently, in the search for the mechanisms of SLE pathogenesis, the association of lifestyle factors such as diet, cigarette smoking, ultraviolet radiation exposure, alcohol and caffeine-rich beverage consumption with SLE susceptibility has been systematically investigated. The cellular and molecular mechanisms mediating lifestyle effects on SLE occurrence, including interactions between genetic risk loci and environment, epigenetic changes, immune dysfunction, hyper-inflammatory response, and cytotoxicity, have been proposed. In the present review of the reports published in reputable peer-reviewed journals and government websites, we consider the current knowledge about the relationships between lifestyle factors and SLE incidence and outline directions of future research in this area. Formulation of practical measures with regard to the lifestyle in the future will benefit SLE patients and may provide potential therapy strategies.

Interactions Between Genome-Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus

OBJECTIVE

To identify interactions between genetic factors and current or recent smoking in relation to risk of developing systemic lupus erythematosus (SLE).

METHODS

For the study, 673 patients with SLE (diagnosed according to the American College of Rheumatology 1997 updated classification criteria) were matched by age, sex, and race (first 3 genetic principal components) to 3,272 control subjects without a history of connective tissue disease. Smoking status was classified as current smoking/having recently quit smoking within 4 years before diagnosis (or matched index date for controls) versus distant past/never smoking. In total, 86 single-nucleotide polymorphisms and 10 classic HLA alleles previously associated with SLE were included in a weighted genetic risk score (wGRS), with scores dichotomized as either low or high based on the median value in control subjects (low wGRS being defined as less than or equal to the control median; high wGRS being defined as greater than the control median). Conditional logistic regression models were used to estimate both the risk of SLE and risk of anti-double-stranded DNA autoantibody-positive (dsDNA+) SLE. Additive interactions were assessed using the attributable proportion (AP) due to interaction, and multiplicative interactions were assessed using a chi-square test (with 1 degree of freedom) for the wGRS and for individual risk alleles. Separate repeated analyses were carried out among subjects of European ancestry only.

RESULTS

The mean ± SD age of the SLE patients at the time of diagnosis was 36.4 ± 15.3 years. Among the 673 SLE patients included, 92.3% were female and 59.3% were dsDNA+. Ethnic distributions were as follows: 75.6% of European ancestry, 4.5% of Asian ancestry, 11.7% of African ancestry, and 8.2% classified as other ancestry. A high wGRS (odds ratio [OR] 2.0, P = 1.0 × 10^-51 versus low wGRS) and a status of current/recent smoking (OR 1.5, P = 0.0003 versus distant past/never smoking) were strongly associated with SLE risk, with significant additive interaction (AP 0.33, P = 0.0012), and associations with the risk of anti-dsDNA+ SLE were even stronger. No significant multiplicative interactions with the total wGRS (P = 0.58) or with the HLA-only wGRS (P = 0.06) were found. Findings were similar in analyses restricted to only subjects of European ancestry.

CONCLUSION

The strong additive interaction between an updated SLE genetic risk score and current/recent smoking suggests that smoking may influence specific genes in the pathogenesis of SLE.

Mechanisms of Environment-Induced Autoimmunity

Although numerous environmental exposures have been suggested as triggers for preclinical autoimmunity, only a few have been confidently linked to autoimmune diseases. For disease-associated exposures, the lung is a common site where chronic exposure results in cellular toxicity, tissue damage, inflammation, and fibrosis. These features are exacerbated by exposures to particulate material, which hampers clearance and degradation, thus facilitating persistent inflammation. Coincident with exposure and resulting pathological processes is the posttranslational modification of self-antigens, which, in concert with the formation of tertiary lymphoid structures containing abundant B cells, is thought to promote the generation of autoantibodies that in some instances demonstrate major histocompatibility complex restriction. Under appropriate gene-environment interactions, these responses can have diagnostic specificity. Greater insight into the molecular and cellular requirements governing this process, especially those that distinguish preclinical autoimmunity from clinical autoimmunedisease, may facilitate determination of the significance of environmental exposures in human autoimmune disease.

Impact of IL-10 gene polymorphisms and its interaction with environment on susceptibility to systemic lupus erythematosus

This study aims to explore the impact of interleukin (IL)-10 single nucleotide polymorphisms (SNPs) and its interaction with environment on the risk of systemic lupus erythematosus (SLE). Chi-square testing method was used to investigate whether the distributions for genotype of four SNPs were differed from Hardy-Weinberg equilibrium (HWE). Logistic regression was used to test the association between IL-10 SNPs and SLE risk. The best interaction combinations between IL-10 SNPs and environmental factors were assessed by generalized multifactor dimensionality reduction (GMDR). Both rs1800896-G and rs1800871-T alleles were associated with increased risk of SLE, the odds ratios (ORs) (95% confidence interval (CI)) for the two SNPs were 1.68 (1.25-2.09) and 1.47 (1.12-1.94), respectively. Then, we used the GMDR method to analyze the high-order interactions of four SNPs within IL-10 gene and environmental factors on SLE risk. We found a significant interaction combination (two-locus model with P = 0.001) between rs1800896 and smoking, after adjusting for gender, age, body mass index (BMI), and alcohol drinking. We also used two-variable stratified analysis by logistic regression to analyze the synergistic effect between two variables (rs1800896 and smoking), which had significant significance in GMDR model. We found that current smokers with rs1800896-AG or GG genotype have the highest SLE risk, compared with never smokers with the rs1800896-AA genotype, OR (95% CI) = 2.24 (1.52-3.58). The rs1800896-G and rs1800871-T alleles and interaction between rs1800896 and current smoking were all associated with increased risk of SLE.

Interaction between IL-33 Gene Polymorphisms and Current Smoking with Susceptibility to Systemic Lupus Erythematosus

Aims

This study is aimed at exploring the relation between IL-33 single-nucleotide polymorphisms (SNPs) and the risk of systemic lupus erythematosus (SLE).

Methods

SNPStats (online software) was used to test the Hardy-Weinberg equilibrium in controls. Generalized multifactor dimensionality reduction (GMDR) was adopted to screen the preferable interaction between IL-33 SNPs and current smoking.

Results

Logistic regression analysis based on the fundamental data of age, gender, BMI, current smoking, and alcohol drinking showed that both rs1929992-G and rs1891385-C alleles were correlated with an increasing risk of SLE, the ORs (95% CI) of which were 1.62 (1.21-2.05) and 1.64 (1.22-2.10), respectively. One two-locus model (rs1929992×current smoking) had a testing accuracy of 60.11% (P = 0.0010). Through an overall multidimensional model, optimum cross-validation consistency was obtained. The analysis indicated that current smoking status influenced the SLE risk depending on the genotypes at rs1929992. Pairwise LD analysis indicated that haplotype rs1929992G-rs7044343T was statistically related to the elevating risk of SLE (P < 0.05). Those subjects with the G-T haplotype had a higher SLE risk than those with other haplotypes, after correction with factors, including gender, alcohol drinking, age, BMI, and current smoking.

Conclusions

The rs1929992-G and rs1891385-C allele, interaction between the rs1929992 gene and current smoking, and haplotype rs1929992G-rs7044343T were all risk factors of SLE.

The study of interactions between genome and exposome in the development of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a systemic inflammatory autoimmune disease characterized by a broad spectrum of clinical and serological manifestations. This may reflect a complex and multifactorial etiology involving several identified genetic and environmental factors, though not explaining the full risk of SLE. Established SLE risk genotypes are either very rare or with modest effect sizes and twin studies indicate that other factors besides genetics must be operative in SLE etiology. The exposome comprises the cumulative environmental influences on an individual and associated biological responses through the lifespan. It has been demonstrated that exposure to silica, smoking and exogenous hormones candidate as environmental risk factors in SLE, while alcohol consumption seems to be protective. Very few studies have investigated potential gene-environment interactions to determine if some of the unexplained SLE risk is attributable hereto. Even less have focused on interactions between specific risk genotypes and environmental exposures relevant to SLE pathogenesis. Cohort and case-control studies may provide data to suggest such biological interactions and various statistical measures of interaction can indicate the magnitude of such. However, such studies do often have very large sample-size requirements and we suggest that the rarity of SLE to some extent can be compensated by increasing the ratio of controls. This review summarizes the current body of knowledge on gene-environment interactions in SLE. We argue for the prioritization of studies that comprise the increasing details available of the genome and exposome relevant to SLE as they have the potential to disclose new aspects of SLE pathogenesis including phenotype heterogeneity.

An Analytic Approach Using Candidate Gene Selection and Logic Forest to Identify Gene by Environment Interactions (G × E) for Systemic Lupus Erythematosus in African Americans

Development and progression of many human diseases, such as systemic lupus erythematosus (SLE), are hypothesized to result from interactions between genetic and environmental factors. Current approaches to identify and evaluate interactions are limited, most often focusing on main effects and two-way interactions. While higher order interactions associated with disease are documented, they are difficult to detect since expanding the search space to all possible interactions of p predictors means evaluating 2^p − 1 terms. For example, data with 150 candidate predictors requires considering over 10⁴⁵ main effects and interactions. In this study, we present an analytical approach involving selection of candidate single nucleotide polymorphisms (SNPs) and environmental and/or clinical factors and use of Logic Forest to identify predictors of disease, including higher order interactions, followed by confirmation of the association between those predictors and interactions identified with disease outcome using logistic regression. We applied this approach to a study investigating whether smoking and/or secondhand smoke exposure interacts with candidate SNPs resulting in elevated risk of SLE. The approach identified both genetic and environmental risk factors, with evidence suggesting potential interactions between exposure to secondhand smoke as a child and genetic variation in the ITGAM gene associated with increased risk of SLE.

Cigarette smoking and the pathogenesis of systemic lupus erythematosus

INTRODUCTION

Systemic lupus erythematosus (SLE) is a multi-system inflammatory autoimmune disease of incompletely understood etiology. It is thought that environmental exposures 'trigger' or accelerate the disease in genetically-predisposed individuals. Areas covered: Substantial epidemiological evidence exists to support the association between cigarette smoking and the risk of incident SLE. Recent evidence points to current smoking as the specific risk factor, with decreasing risk 5 years after smoking cessation, and the greatest risk for disease characterized by the presence of SLE-specific autoantibodies. Research has begun to search for possible explanations for the temporal nature of the relationship between current smoking and autoantibody positive-SLE. Here we review potential biologic mechanisms linking smoking and SLE risk, including effects upon T and B cells, inflammatory cytokines, oxidative stress, and the formation of short-lived DNA adducts. Expert commentary: The directions for future research in this field include studies of gene-environment interactions, epigenetics, metabolomics and putative biologic mechanisms.

Estrogen receptor alpha gene (ESR1) polymorphism and its interaction with smoking and drinking contribute to susceptibility of systemic lupus erythematosus

The aim of this study is to investigate the association of estrogen receptor alpha gene (ESR1) polymorphisms, additional gene-gene, and gene-environment interaction with systemic lupus erythematosus (SLE) risk. SNPStats (available online at http://bioinfo.iconcologia.net/SNPstats ) was used to investigate the Hardy-Weinberg equilibrium (HWE) in controls and association between SNP and SLE risk. Generalized multifactor dimensionality reduction (GMDR) was used to screen the interactions among SNPs and environmental risk factors; SLE risk was significantly higher in carriers of rs2234693 C allele than those with TT (TC + CC versus TT), adjusted OR (95%CI) = 1.57 (1.21-2.06), and was also higher in carriers of rs9340799 G allele than those with AA (AG + GG versus AA), adjusted OR (95%CI) = 1.68 (1.24-2.13). However, we also find no association between rs2228480 and SLE risk after covariates adjustment. We found a significant two-locus model (p = 0.0010) involving rs2234693 and smoking; the cross-validation consistency of this model was 10/10, and the testing accuracy was 62.70%. Smokers with TC or CC of rs2234693 genotype have the highest SLE risk, compared to never-smokers with TT of rs2234693 genotype, OR (95%CI) was 2.50 (1.65-3.42), after covariates adjustment for gender, age, alcohol drinking, and BMI. We found that C allele of rs2234693 and G allele of rs9340799 within ESR1 gene, their interaction between rs2234693 and current smoking were all associated with increased SLE risk.

Understanding the role of environmental factors in the development of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a multisystem disease with a complex etiology. Its risk is higher among women, racial and ethnic minorities, and individuals with a family history of SLE or related autoimmune diseases. It is believed that genetic factors interact with environmental exposures throughout the lifespan to influence susceptibility to developing SLE. The strongest epidemiologic evidence exists for increased risk of SLE associated with exposure to crystalline silica, current cigarette smoking, use of oral contraceptives, and postmenopausal hormone replacement therapy, while there is an inverse association with alcohol use. Emerging research results suggest possible associations of SLE risk with exposure to solvents, residential and agricultural pesticides, heavy metals, and air pollution. Ultraviolet light, certain infections, and vaccinations have also been hypothesized to be related to SLE risk. Mechanisms linking environmental exposures and SLE include epigenetic modifications resulting from exposures, increased oxidative stress, systemic inflammation and inflammatory cytokine upregulation, and hormonal effects. Research needs to include new studies of environmental risk factors for SLE in general, with a focus on lifetime exposure assessment. In addition, studies in susceptible subgroups, such as family members, studies based on genetic risk profiles, and studies in individuals with evidence of pre-clinical autoimmunity based on the detection of specific auto-antibodies are also required. Understanding the role of environmental exposures in the development of SLE may help identify modifiable risk factors and potential etiological mechanisms.

Environmental Basis of Autoimmunity

The three common themes that underlie the induction and perpetuation of autoimmunity are genetic predisposition, environmental factors, and immune regulation. Environmental factors have gained much attention for their role in triggering autoimmunity, with increasing evidence of their influence as demonstrated by epidemiological studies, laboratory research, and animal studies. Environmental factors known to trigger and perpetuate autoimmunity include infections, gut microbiota, as well as physical and environmental agents. To address these issues, we will review major potential mechanisms that underlie autoimmunity including molecular mimicry, epitope spreading, bystander activation, polyclonal activation of B and T cells, infections, and autoinflammatory activation of innate immunity. The association of the gut microbiota on autoimmunity will be particularly highlighted by their interaction with pharmaceutical agents that may lead to organ-specific autoimmunity. Nonetheless, and we will emphasize this point, the precise mechanism of environmental influence on disease pathogenesis remains elusive.

Polymorphisms in NAT2 (N-acetyltransferase 2) gene in patients with systemic lupus erythematosus

OBJECTIVE

To investigate potential associations of four substitutions in NAT2 gene and of acetylator phenotype of NAT2 with systemic lupus erythematosus (SLE) and clinical phenotypes.

METHODS

Molecular analysis of 481C>T, 590G>A, 857G>A, and 191G>A substitutions in the NAT2 gene was performed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique, from DNA extracted from peripheral blood samples obtained from patients with SLE (n=91) and controls (n=97).

RESULTS AND CONCLUSIONS

The 857GA genotype was more prevalent among nonwhite SLE patients (OR=4.01, 95% CI=1.18-13.59). The 481T allele showed a positive association with hematological disorders that involve autoimmune mechanisms, specifically autoimmune hemolytic anemia or autoimmune thrombocytopenia (OR=1.97; 95% CI=1.01-3.81).

Rapid identification of the NAT2 genotype in tuberculosis patients by multicolor melting curve analysis

AIM

NAT2 genotype is an indicator for isoniazid dosage adjusting for tuberculosis treatment. Multicolor melting curve analysis (MMCA) was evaluated as a potential method for NAT2 genotyping.

MATERIALS & METHODS

352 blood samples were analyzed by MMCA kit (Zeesan Biotech Co., Xiamen, China) targeting NAT2 SNPs at T341C, C481T, G590A and G857A, and direct sequencing was used as control.

RESULTS

The sensitivity, specificity and accuracy of the MMCA assay for rapid NAT2 genotype detection were 97.9, 99.6 and 99.1% respectively, whereas for intermediate genotypes the values were 99.5, 98.7 and 99.1%, respectively, and for slow genotypes the values were 100% for the three aspects. The 24 saliva and blood for the control samples were also successfully analyzed using the MMCA assay, both produced uniform outcomes.

CONCLUSION

The MMCA assay described in our study is very promising for the efficient determination of NAT2 genotype, and can facilitate the personalized dosing of isoniazid.

Cigarette smoking, alcohol consumption and risk of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a complex multisystem autoimmune disease whose pathogenesis is thought to involve both genetic and environmental factors. It is possible that common environmental exposures, such as cigarette smoking and alcohol consumption, might modify risk of disease development in certain individuals. Here we aim to review the epidemiologic evidence related to the association of cigarette smoking, alcohol consumption and the risk of developing SLE. A growing body of evidence suggests that cigarette smoking confers a short-term increased risk of SLE in genetically susceptible individuals. On the other hand, alcohol consumption in moderate doses may have a protective effect against the development of SLE, although this is still debated. We also have reviewed proposed mechanistic explanations underlying the role of cigarette smoking and alcohol consumption in SLE pathogenesis.

Arylamine N-acetyltransferase polymorphisms in Han Chinese patients with ankylosing spondylitis and their correlation to the adverse drug reactions to sulfasalazine

BACKGROUND

Polymorphisms of Arylamine N-acetyltransferase (NAT) that contribute to diverse susceptibilities of some autoimmune diseases are also linked to the metabolism of several drugs including sulfasalazine (SSZ). The aim of this study was to investigate the distribution of NAT polymorphisms in Han Chinese patients with ankylosing spondylitis (AS) and their correlation to sulfasalazine-induced adverse drug reactions (ADRs).

METHODS

Arylamine N-acetyltransferase 1 (NAT1) and arylamine N-acetyltransferase 2 (NAT2) genotypes were determined in 266 AS patients who received SSZ treatment and 280 healthy controls. The correlation between NAT polymorphisms and SSZ-induced ADRs was analyzed.

RESULTS

The co-occurrence frequency of NAT2 fast acetylator genotype and NAT1*10/NAT1*10 genotype was lower in AS patients than in controls. No positive correlations were detected between NAT polymorphisms and AS clinical features. The prevalence of SSZ-induced ADRs and drug withdrawal was 9.4% and 7.1%, respectively. The frequencies of overall ADRs, dose-related ADRs, and termination of drug treatment because of intolerance were higher in the NAT2 slow acetylator genotype carriers than in the fast-type carriers and in those with co-existence of NAT1 and NAT2 slow acetylator genotypes. Furthermore, the ADRs emerged earlier in the AS cases carrying both NAT1 and NAT2 slow acetylator genotypes.

CONCLUSIONS

The prevalence of co-occurring NAT2 fast acetylator genotype and NAT1*10/NAT1*10 genotype was lower in AS patients than in controls. The NAT2 slow acetylator genotype and co-existing NAT1 and NAT2 slow acetylator genotypes appear to be associated with higher risks of SSZ-induced ADRs.

Genetics, environment, and gene-environment interactions in the development of systemic rheumatic diseases

Rheumatic diseases offer distinct challenges to researchers because of heterogeneity in disease phenotypes, low disease incidence, and geographic variation in genetic and environmental factors. Emerging research areas, including epigenetics, metabolomics, and the microbiome, may provide additional links between genetic and environmental risk factors in the pathogenesis of rheumatic disease. This article reviews the methods used to establish genetic and environmental risk factors and studies gene-environment interactions in rheumatic diseases, and provides specific examples of successes and challenges in identifying gene-environment interactions in rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Emerging research strategies and future challenges are discussed.

Gene-environment interaction in autoimmune disease

Autoimmune disease manifests in numerous forms, but as a disease group is relatively common in the population. It is complex in aetiology, with genetic and environmental determinants. The involvement of gene variants in autoimmune disease is well established, and evidence for significant involvement of the environment in various disease forms is growing. These factors may act independently, or they may interact, with the effect of one factor influenced by the presence of another. Identifying combinations of genetic and environmental factors that interact in autoimmune disease has the capacity to more fully explain disease risk profile, and to uncover underlying molecular mechanisms contributing to disease pathogenesis. In turn, such knowledge is likely to contribute significantly to the development of personalised medicine, and targeted preventative approaches. In this review, we consider the current evidence for gene-environment (G-E) interaction in autoimmune disease. Large-scale G-E interaction research efforts, while well-justified, face significant practical and methodological challenges. However, it is clear from the evidence that has already been generated that knowledge on how genes and environment interact at a biological level will be crucial in fully understanding the processes that manifest as autoimmunity.

Smoking is not associated with autoantibody production in systemic lupus erythematosus patients, unaffected first-degree relatives, nor healthy controls

OBJECTIVE

The objective of this paper is to examine whether smoking is associated with autoantibody production in systemic lupus erythematosus (SLE) patients, unaffected first-degree relatives (FDR) of individuals with SLE--a group at increased risk of developing SLE--or unaffected, unrelated controls.

METHODS

Detailed demographic, environmental, clinical, and therapeutic information was collected by questionnaire on 1242 SLE patients, 981 FDRs, and 946 controls in the Lupus Family Registry and Repository; a blood sample was obtained. All sera were tested for multiple lupus autoantibodies by immunofluorescence and luminex bead-based assays. Generalized estimating equations, adjusting for age, gender, and ethnicity and accounting for correlation within families, were used to assess smoking status with the dichotomous outcome variables of positivity for SLE status, positivity of ANA by immunofluorescence (≥1:120), positivity for ≥1 autoantibody by the luminex assay, and positivity for each of the 11 autoantibodies.

RESULTS

Current smoking was associated with being positive for ≥1 autoantibody (excluding ANA) (adjusted OR = 1.53, 95% CI 1.04-2.24) in our subjects with SLE. No association was observed in unaffected FDRs or healthy controls. Former smoking was associated with anti-Ro/SS-A60 in our unaffected FDRs. There was an increased association with anti-nRNP A seropositivity, as well as a decreased association with anti-nRNP 68 positivity, in current smokers in SLE subjects.

CONCLUSIONS

No clear association between smoking status and individual autoantibodies was detected in SLE patients, unaffected FDRs, nor healthy controls within this collection. The association of smoking with SLE may therefore manifest its risk through mechanisms outside of autoantibody production, at least for the specificities tested.

Organic solvents as risk factor for autoimmune diseases: a systematic review and meta-analysis

BACKGROUND

Genetic and epigenetic factors interacting with the environment over time are the main causes of complex diseases such as autoimmune diseases (ADs). Among the environmental factors are organic solvents (OSs), which are chemical compounds used routinely in commercial industries. Since controversy exists over whether ADs are caused by OSs, a systematic review and meta-analysis were performed to assess the association between OSs and ADs.

METHODS AND FINDINGS

The systematic search was done in the PubMed, SCOPUS, SciELO and LILACS databases up to February 2012. Any type of study that used accepted classification criteria for ADs and had information about exposure to OSs was selected. Out of a total of 103 articles retrieved, 33 were finally included in the meta-analysis. The final odds ratios (ORs) and 95% confidence intervals (CIs) were obtained by the random effect model. A sensitivity analysis confirmed results were not sensitive to restrictions on the data included. Publication bias was trivial. Exposure to OSs was associated to systemic sclerosis, primary systemic vasculitis and multiple sclerosis individually and also to all the ADs evaluated and taken together as a single trait (OR: 1.54; 95% CI: 1.25-1.92; p-value<0.001).

CONCLUSION

Exposure to OSs is a risk factor for developing ADs. As a corollary, individuals with non-modifiable risk factors (i.e., familial autoimmunity or carrying genetic factors) should avoid any exposure to OSs in order to avoid increasing their risk of ADs.

Lung cancer and interstitial lung diseases: a systematic review

Interstitial lung diseases (ILDs) represent a heterogeneous group of more than two hundred diseases of either known or unknown etiology with different pathogenesis and prognosis. Lung cancer, which is the major cause of cancer death in the developed countries, is mainly attributed to cigarette smoking and exposure to inhaled carcinogens. Different studies suggest a link between ILDs and lung cancer, through different pathogenetic mechanisms, such as inflammation, coagulation, dysregulated apoptosis, focal hypoxia, activation, and accumulation of myofibroblasts as well as extracellular matrix accumulation. This paper reviews current evidence on the association between lung cancer and interstitial lung diseases such as idiopathic pulmonary fibrosis, sarcoidosis, systemic sclerosis, dermatomyositis/polymyositis, rheumatoid arthritis, systemic lupus erythematosus, and pneumoconiosis.

Impact of interactions of cigarette smoking with NAT2 polymorphisms on rheumatoid arthritis risk in African Americans

OBJECTIVE

To examine whether polymorphisms in genes coding for drug-metabolizing enzymes (DMEs) have an impact on rheumatoid arthritis (RA) risk due to cigarette smoking in African Americans.

METHODS

Smoking status was evaluated in African American patients with RA compared with non-RA controls, with smoking exposure categorized as heavy smoker (≥10 pack-years) versus never smoker/<10 pack-years. Individuals were genotyped for a homozygous deletion polymorphism in the M1 gene loci of glutathione S-transferase (GSTM1-null) in addition to tagging single-nucleotide polymorphisms (SNPs) in N-acetyltransferase 1 (NAT1), NAT2, and epoxide hydrolase 1 (EPXH1). Associations of these genotypes with RA risk were examined using logistic regression, and gene-smoking interactions were assessed.

RESULTS

There were no significant associations of any DME genotype with RA. After adjustment for multiple comparisons, there were significant additive interactions between heavy smoking and the NAT2 SNPs rs9987109 (P(additive) = 0.000003) and rs1208 (P(additive) = 0.00001); the attributable proportion due to interaction ranged from 0.61 to 0.67. None of the multiplicative gene-smoking interactions examined remained significant with regard to overall disease risk, after adjustment for multiple testing. There was no evidence of significant gene-smoking interactions in analyses of GSTM1-null, NAT1, or EPXH1. DME gene-smoking interactions were similar when cases were limited to those patients who were positive for anti-citrullinated protein antibodies.

CONCLUSION

Among African Americans, RA risk imposed by heavy smoking appears to be mediated in part by genetic variation in NAT2. While further studies are needed to elucidate the mechanisms underpinning these interactions, these SNPs appear to identify African American smokers at a much higher risk for RA, in whom the relative risk is at least 2-fold higher when compared to nonsmokers lacking these risk alleles.

N-acetyltransferase-2 genotypes among patients with rheumatoid arthritis attending Jordan University Hospital

AIM

To determine the frequency of major N-acetyltransferase (NAT2) alleles and genotypes among Jordanian patients with rheumatoid arthritis (RA).

METHODS

The study was approved by the IRB of the Jordan University Hospital. An informed consent was signed by every patient. DNA samples from 150 healthy volunteers and 108 patients with RA were analyzed by polymerase chain reaction followed by a restriction fragment length polymorphism assay (PCR-RFLP) to determine the frequency of four major alleles: NAT2*4, NAT2*5, NAT2*6, and NAT2*7.

RESULTS

The most prevalent genotypes are those that encode the slow acetylation phenotype. About 59.3% of the patients with RA carried the slow, 33.3% the intermediate, and 7.4% the fast-encoding genotypes. The frequency of NAT2 alleles was 0.241 (95% confidence interval [CI] 0.184-0.298) for NAT2*4, 0.449 (95% CI 0.383-0.515) for NAT2*5, 0.273 (95% CI 0.214-0.332) for NAT2*6, and 0.037 (95% CI 0.012-0.062) for NAT2*7 allele. The overall frequency of the slow acetylation genotype in patients with RA is similar to that in healthy Jordanian volunteers. However, the NAT2*5/7 genotype was found in seven patients (6.5%) with RA and was absent in Jordanian volunteers, and the z test revealed that the difference was statistically significant. This genotype constituted 10.9% of the genotypes encoding slow acetylation.

CONCLUSION

The overall acetylator genotype in RA is similar to that in healthy volunteers. The overall slow acetylator genotypes do not seem to be a genetic risk factor for RA among Jordanians. However, the NAT2*5/7 genotype seems to be related to RA. The nature of this relationship needs further clarification.

Air pollution in autoimmune rheumatic diseases: a review

Air pollution consists of a heterogeneous mixture of gasses and particles that include carbon monoxide, nitrates, sulfur dioxide, ozone, lead, toxic by-product of tobacco smoke and particulate matter. Oxidative stress and inflammation induced by inhaled pollutants may result in acute and chronic disorders in the respiratory system, as well as contribute to a state of systemic inflammation and autoimmunity. This paper reviews the mechanisms of air contaminants influencing the immune response and autoimmunity, and it focuses on studies of inhaled pollutants triggering and/or exacerbating rheumatic diseases in cities around the world. Remarkably, environmental factors contribute to the onset of autoimmune diseases, especially smoking and occupational exposure to silica in rheumatoid arthritis and systemic lupus erythematosus. Other diseases such as scleroderma may be triggered by the inhalation of chemical solvents, herbicides and silica. Likewise, primary vasculitis associated with anti-neutrophil cytoplasmic antibody (ANCA) may be triggered by silica exposure. Only few studies showed that air pollutants could trigger or exacerbate juvenile idiopathic arthritis and systemic lupus erythematosus. In contrast, no studies of tropospheric pollution triggering inflammatory myopathies and spondyloarthropathies were carried out. In conclusion, air pollution is one of the environmental factors involved in systemic inflammation and autoimmunity. Further studies are needed in order to evaluate air pollutants and their potentially serious effects on autoimmune rheumatic diseases and the mechanisms involved in the onset and the exacerbation of these diseases.

Geoepidemiology of autoimmune rheumatic diseases

The accumulative global burden of autoimmune and inflammatory rheumatic diseases is substantial. Studying the distribution of these conditions across various global regions and ethnic groups by means of geoepidemiology might readily provide epidemiological data and also advance our understanding of their genetic and environmental underpinnings. In order to depict the geoepidemiology of autoimmune and inflammatory rheumatic diseases, namely rheumatoid arthritis, juvenile rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis, ankylosing spondylitis and Sjögren's syndrome, we present a comprehensive collection of epidemiological reports from various world regions, including the prevalence of each of these conditions. The accumulated data show that the reviewed rheumatic diseases are global phenomena, and, with some variance, seem to be relatively evenly distributed. This finding is in contrast with the obviously uneven distribution of some major nonrheumatic autoimmune conditions. In addition, geoepidemiology demonstrates that ethnogenetic susceptibility interacts with lifestyle and environmental factors, which include socioeconomic status, infectious agents (triggering or protective agents), environmental pollutants, and vitamin D (dependent on sunlight exposure), in determining the risk of developing rheumatic autoimmunity.

Genetics research in systemic lupus erythematosus for clinicians: methodology, progress, and controversies

PURPOSE OF REVIEW

Clinical journals are reporting genetic associations with systemic lupus erythematosus (SLE) with increasing frequency. Interpreting these studies is difficult for clinicians without rigorous training in epidemiology, statistics, and genetics. In this review, we discuss basic issues important to understanding and contextualizing new genetic association studies. We, therefore, highlight literature related to methodology as well as recent genetic discoveries in SLE.

RECENT FINDINGS

Functional single nucleotide polymorphisms (SNPs) and/or haplotypes have now been identified for ITGAM, PTPN22, and IRF5, and several additional loci have been highlighted in recent genome-wide association studies in SLE. Recent work also indicates that several regions within the extended major histocompatibility complex contribute independently to SLE risk. Evidence of additive statistical interaction has been found between IRF5 and TYK2, IRF5, and STAT4, and between NAT2 and exposure to tobacco smoke.

SUMMARY

Many new genes have been associated with SLE susceptibility, revealing insight into SLE pathophysiology. Current research is focusing on further refining the initial genetic association results and extending this work to non-European populations. Research is also expanding beyond SNP associations to investigate the contribution of copy number variants (CNVs) and DNA methylation to SLE risk.