The influence of the COVID-19 pandemic on physical activity in Stockholm County - Evidence from time series models of smartphone measured daily steps data spanning over 3 years.

BACKGROUND: It has been reported that physical activity levels decreased during the COVID-19 pandemic. Previous studies often relied on self-reported physical activity, which has low accuracy. Studies based on objectively measured physical activity have had short data collection periods, thereby not allowing the consideration of pre-pandemic levels of physical activity or the influence over the different waves of the pandemic. METHODS: In this study, we utilize smartphone-measured step data from a nonprobability sample in Stockholm County, Sweden, where measures to limit the spread of COVID-19 differed from those in many other countries. The results are based on 522 individuals and 532,739 person-days with step data spanning from 2019 to 2021. Generalized additive models were fitted for each individual, and meta-regression was used to combine the results from individual models. RESULTS: Daily steps decreased during the first wave but increased during the third wave compared to individual pre-pandemic levels. The decrease in daily steps occurred primarily in young individuals and those with occupations allowing remote work. Individuals of retirement age on the contrary increased their daily steps during the same period. CONCLUSIONS: This study reveal that the influence of the COVID-19 pandemic was temporary and that younger age and the possibility of working from home were associated with a decreasing trend in physical activity.

Undiagnosed type 2 diabetes is common - intensified screening of established risk groups is imperative in Sweden: the SDPP cohort.

BACKGROUND: Undiagnosed type 2 diabetes (T2D) is a global problem. Current strategies for diagnosis in Sweden include screening individuals within primary healthcare who are of high risk, such as those with hypertension, obesity, prediabetes, family history of diabetes, or those who smoke daily. In this study, we aimed to estimate the proportion of individuals with undiagnosed T2D in Stockholm County and factors associated with T2D being diagnosed by healthcare. This information could improve strategies for detection. METHODS: We used data from the Stockholm Diabetes Prevention Programme (SDPP) cohort together with information from national and regional registers. Individuals without T2D aged 35-56 years at baseline were followed up after two ten-year periods. The proportion of diagnosed T2D was based on register information for 7664 individuals during period 1 and for 5148 during period 2. Undiagnosed T2D was assessed by oral glucose tolerance tests at the end of each period. With logistic regression, we analysed factors associated with being diagnosed among individuals with T2D. RESULTS: At the end of the first period, the proportion of individuals with T2D who had been diagnosed with T2D or not was similar (54.0% undiagnosed). At the end of the second period, the proportion of individuals with T2D was generally higher, but they were less likely to be undiagnosed (43.5%). The likelihood of being diagnosed was in adjusted analyses associated with overweight (OR=1.85; 95% CI 1.22-2.80), obesity (OR=2.73; 95% CI 1.76-4.23), higher fasting blood glucose (OR=2.11; 95% CI 1.67-2.66), and self-estimated poor general health (OR=2.42; 95% CI 1.07-5.45). Socioeconomic factors were not associated with being diagnosed among individuals with T2D. Most individuals (>71%) who developed T2D belonged to risk groups defined by having at least two of the prominent risk factors obesity, hypertension, daily smoking, prediabetes, or family history of T2D, including individuals with T2D who had not been diagnosed by healthcare. CONCLUSIONS: Nearly half of individuals who develop T2D during 10 years in Stockholm County are undiagnosed, emphasizing a need for intensified screening of T2D within primary healthcare. Screening can be targeted to individuals who have at least two prominent risk factors.

Mode of delivery and subsequent self-perceived sexual life satisfaction: a population-based cohort study.

BACKGROUND: The potential association between mode of obstetrical delivery and subsequent sexual outcomes of the birthing parent remains uncertain and has not been well investigated from the perspective of positive sexual life satisfaction. OBJECTIVE: This study aimed to investigate if there was any association between mode of delivery and subsequent sexual life satisfaction of the birthing parent. A secondary aim was to assess the extent to which this association changed when stratified by time elapsed since delivery. STUDY DESIGN: The study matched participants in the Stockholm Public Health Cohort with deliveries recorded in the Swedish Medical Birth Register. Any deliveries recorded in the registry before the participation in the Stockholm Public Health Cohort were included (n=46,078). The length of time from delivery to outcome assessment varied from 1 month to 41 years (mean, 18 years [±10.8]). Mode of delivery was retrieved from the same registry, whereas self-perceived sexual life satisfaction was retrieved from the Stockholm Public Health Cohort Questionnaires where participants had assessed their sexual life satisfaction as 1 out of 5 mutually exclusive options. Multinomial logistic regression was used to test for any association between mode of delivery (cesarean, instrumental, and spontaneous vaginal delivery) and sexual life satisfaction, both overall and stratified by time elapsed since delivery. RESULTS: After adjusting for covariates, no statistically significant (P < .05) difference in subsequent sexual life satisfaction of the birthing parent between modes of delivery was identified. Adjusted odds ratios for assessing sexual life satisfaction as the lowest level ("very unsatisfactory") were 1.11 (95% confidence interval, 0.98-1.25) for cesarean delivery and 1.16 (95% confidence interval, 0.99-1.35) for instrumental delivery, compared with spontaneous vaginal delivery. The difference in covariate-adjusted prevalence of the lowest level of sexual life satisfaction among the different groups categorized by time since delivery was small: 4.0% (95% confidence interval, 2.4%-5.6%) for cesarean delivery as opposed to 2.8% (95% confidence interval, 2.1%-3.6%) for spontaneous vaginal delivery within 2 years since delivery. CONCLUSION: These findings do not support any impact of mode of delivery on the subsequent self-perceived sexual life satisfaction among birthing people, either overall or across different time periods since delivery.

Multiple myeloma risk in relation to long-term air pollution exposure - A pooled analysis of four European cohorts.

BACKGROUND: Air pollution is a growing concern worldwide, with significant impacts on human health. Multiple myeloma is a type of blood cancer with increasing incidence. Studies have linked air pollution exposure to various types of cancer, including leukemia and lymphoma, however, the relationship with multiple myeloma incidence has not been extensively investigated. METHODS: We pooled four European cohorts (N = 234,803) and assessed the association between residential exposure to nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), and ozone (O3) and multiple myeloma. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. RESULTS: During 4,415,817 person-years of follow-up (average 18.8 years), we observed 404 cases of multiple myeloma. The results of the fully adjusted linear analyses showed hazard ratios (95% confidence interval) of 0.99 (0.84, 1.16) per 10 µg/m³ NO2, 1.04 (0.82, 1.33) per 5 µg/m³ PM2.5, 0.99 (0.84, 1.18) per 0.5 10-5 m-1 BCE, and 1.11 (0.87, 1.41) per 10 µg/m³ O3. CONCLUSIONS: We did not observe an association between long-term ambient air pollution exposure and incidence of multiple myeloma.

Peripheral blood cellular dynamics of rheumatoid arthritis treatment informs about efficacy of response to disease modifying drugs.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation and is mediated by multiple immune cell types. In this work, we aimed to determine the relevance of changes in cell proportions in peripheral blood mononuclear cells (PBMCs) during the development of disease and following treatment. Samples from healthy blood donors, newly diagnosed RA patients, and established RA patients that had an inadequate response to MTX and were about to start tumor necrosis factor inhibitors (TNFi) treatment were collected before and after 3 months of treatment. We used in parallel a computational deconvolution approach based on RNA expression and flow cytometry to determine the relative cell-type frequencies. Cell-type frequencies from deconvolution of gene expression indicate that monocytes (both classical and non-classical) and CD4+ cells (Th1 and Th2) were increased in RA patients compared to controls, while NK cells and B cells (naïve and mature) were significantly decreased in RA patients. Treatment with MTX caused a decrease in B cells (memory and plasma cell), and a decrease in CD4 Th cells (Th1 and Th17), while treatment with TNFi resulted in a significant increase in the population of B cells. Characterization of the RNA expression patterns found that most of the differentially expressed genes in RA subjects after treatment can be explained by changes in cell frequencies (98% and 74% respectively for MTX and TNFi).

Molecular signature of methotrexate response among rheumatoid arthritis patients.

Background: Methotrexate (MTX) is the first line treatment for rheumatoid arthritis (RA), but failure of satisfying treatment response occurs in a significant proportion of patients. Here we present a longitudinal multi-omics study aimed at detecting molecular and cellular processes in peripheral blood associated with a successful methotrexate treatment of rheumatoid arthritis. Methods: Eighty newly diagnosed patients with RA underwent clinical assessment and donated blood before initiation of MTX, and 3 months into treatment. Flow cytometry was used to describe cell types and presence of activation markers in peripheral blood, the expression of 51 proteins was measured in serum or plasma, and RNA sequencing was performed in peripheral blood mononuclear cells (PBMC). Response to treatment after 3 months was determined using the EULAR response criteria. We assessed the changes in biological phenotypes during treatment, and whether these changes differed between responders and non-responders with regression analysis. By using measurements from baseline, we also tried to find biomarkers of future MTX response or, alternatively, to predict MTX response. Results: Among the MTX responders, (Good or Moderate according to EULAR treatment response classification, n = 60, 75%), we observed changes in 29 partly overlapping cell types proportions, levels of 13 proteins and expression of 38 genes during treatment. These changes were in most cases suppressions that were stronger among responders compared to non-responders. Within responders to treatment, we observed a suppression of FOXP3 gene expression, reduction of immunoglobulin gene expression and suppression of genes involved in cell proliferation. The proportion of many HLA-DR expressing T-cell populations were suppressed in all patients irrespective of clinical response, and the proportion of many IL21R+ T-cells were reduced exclusively in non-responders. Using only the baseline measurements we could not detect any biomarkers or prediction models that could predict response to MTX. Conclusion: We conclude that a deep molecular and cellular phenotyping of peripheral blood cells in RA patients treated with methotrexate can reveal previously not recognized differences between responders and non-responders during 3 months of treatment with MTX. This may contribute to the understanding of MTX mode of action and explain non-responsiveness to MTX therapy.

Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort.

BACKGROUND: Established risk factors for breast cancer include genetic disposition, reproductive factors, hormone therapy, and lifestyle-related factors such as alcohol consumption, physical inactivity, smoking, and obesity. More recently a role of environmental exposures, including air pollution, has also been suggested. The aim of this study, was to investigate the relationship between long-term air pollution exposure and breast cancer incidence. METHODS: We conducted a pooled analysis among six European cohorts (n = 199,719) on the association between long-term residential levels of ambient nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), and ozone in the warm season (O3) and breast cancer incidence in women. The selected cohorts represented the lower range of air pollutant concentrations in Europe. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. RESULTS: During 3,592,885 person-years of follow-up, we observed a total of 9,659 incident breast cancer cases. The results of the fully adjusted linear analyses showed a HR (95% confidence interval) of 1.03 (1.00-1.06) per 10 µg/m³ NO2, 1.06 (1.01-1.11) per 5 µg/m³ PM2.5, 1.03 (0.99-1.06) per 0.5 10-5 m-1 BC, and 0.98 (0.94-1.01) per 10 µg/m³ O3. The effect estimates were most pronounced in the group of middle-aged women (50-54 years) and among never smokers. CONCLUSIONS: The results were in support of an association between especially PM2.5 and breast cancer. IMPACT: The findings of this study suggest a role of exposure to NO2, PM2.5, and BC in development of breast cancer.

Migration background, eating disorder symptoms and healthcare service utilisation: findings from the Stockholm Public Health Cohort.

BACKGROUND: From a global perspective, eating disorders are increasingly common, probably because of societal transformation and improved detection. However, research on the impact of migration on the development of eating disorders is scarce, and previously reported results are conflicting. AIMS: To explore if eating disorder symptom prevalence varies according to birth region, parents' birth region and neighbourhood characteristics, and analyse if the observed patterns match the likelihood of being in specialist treatment. METHOD: This study uses data from a large population-based health survey (N = 47 662) among adults in Stockholm, Sweden. A general linear model for complex samples, including adjustment for gender and age, was used to explore self-reported eating disorder symptoms. Odds ratios were calculated for individual symptoms. RESULTS: Eating disorder symptoms are substantially more common in individuals born abroad, especially for migrants from a non-European country. This holds true for all surveyed symptoms, including restrictive eating (odds ratio 5.5, 95% CI 4.5-6.7), compensatory vomiting (odds ratio 6.1, 95% CI 4.6-8.0), loss-of-control eating (odds ratio 2.6, 95% CI 2.3-3.1) and preoccupation with food (odds ratio 2.3, 95% CI 1.9-2.8). Likewise, symptoms are more common in individuals with both parents born abroad and individuals living in districts with a high percentage of migrant residents. A gap exists between district-level symptom scores and the likelihood of being in specialist eating disorder treatment. CONCLUSIONS: These findings call for oversight of current outreach strategies, and highlight the need for efforts to reduce stigma and increase eating disorder symptom recognition in broader groups.

Characterization of data-driven clusters in diabetes-free adults and their utility for risk stratification of type 2 diabetes.

BACKGROUND: The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. METHODS: Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and ß-cell function, systolic and diastolic blood pressure, and BMI. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. RESULTS: Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low ß-cell function (LRLB), low-risk high ß-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk ß-cell failure (HRBF), and high-risk insulin-resistant (HRIR). Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. CONCLUSIONS: Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.

Exposure to surrounding greenness and natural-cause and cause-specific mortality in the ELAPSE pooled cohort.

BACKGROUND: The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort. METHODS: Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants' baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise. RESULTS: The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found. CONCLUSIONS: We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise.

Antibodies to a Citrullinated Porphyromonas gingivalis Epitope Are Increased in Early Rheumatoid Arthritis, and Can Be Produced by Gingival Tissue B Cells: Implications for a Bacterial Origin in RA Etiology.

Based on the epidemiological link between periodontitis and rheumatoid arthritis (RA), and the unique feature of the periodontal bacterium Porphyromonas gingivalis to citrullinate proteins, it has been suggested that production of anti-citrullinated protein antibodies (ACPA), which are present in a majority of RA patients, may be triggered in the gum mucosa. To address this hypothesis, we investigated the antibody response to a citrullinated P. gingivalis peptide in relation to the autoimmune ACPA response in early RA, and examined citrulline-reactivity in monoclonal antibodies derived from human gingival B cells. Antibodies to a citrullinated peptide derived from P. gingivalis (denoted CPP3) and human citrullinated peptides were analyzed by multiplex array in 2,807 RA patients and 372 controls; associations with RA risk factors and clinical features were examined. B cells from inflamed gingival tissue were single-cell sorted, and immunoglobulin (Ig) genes were amplified, sequenced, cloned and expressed (n=63) as recombinant monoclonal antibodies, and assayed for citrulline-reactivities by enzyme-linked immunosorbent assay. Additionally, affinity-purified polyclonal anti-cyclic-citrullinated peptide (CCP2) IgG, and monoclonal antibodies derived from RA blood and synovial fluid B cells (n=175), were screened for CPP3-reactivity. Elevated anti-CPP3 antibody levels were detected in RA (11%), mainly CCP2+ RA, compared to controls (2%), p<0.0001, with a significant association to HLA-DRB1 shared epitope alleles, smoking and baseline pain, but with low correlation to autoimmune ACPA fine-specificities. Monoclonal antibodies derived from gingival B cells showed cross-reactivity between P. gingivalis CPP3 and human citrullinated peptides, and a CPP3+/CCP2+ clone, derived from an RA blood memory B cell, was identified. Our data support the possibility that immunity to P. gingivalis derived citrullinated antigens, triggered in the inflamed gum mucosa, may contribute to the presence of ACPA in RA patients, through mechanisms of molecular mimicry.

Early prediction of clinical response to anti-TNF treatment using multi-omics and machine learning in rheumatoid arthritis.

OBJECTIVES: Advances in immunotherapy by blocking TNF have remarkably improved treatment outcomes for Rheumatoid arthritis (RA) patients. Although treatment specifically targets TNF, the downstream mechanisms of immune suppression are not completely understood. The aim of this study was to detect biomarkers and expression signatures of treatment response to TNF inhibition. METHODS: Peripheral blood mononuclear cells (PBMCs) from 39 female patients were collected before anti-TNF treatment initiation (day 0) and after 3 months. The study cohort included patients previously treated with MTX who failed to respond adequately. Response to treatment was defined based on the EULAR criteria and classified 23 patients as responders and 16 as non-responders. We investigated differences in gene expression in PBMCs, the proportion of cell types and cell phenotypes in peripheral blood using flow cytometry and the level of proteins in plasma. Finally, we used machine learning models to predict non-response to anti-TNF treatment. RESULTS: The gene expression analysis in baseline samples revealed notably higher expression of the gene EPPK1 in future responders. We detected the suppression of genes and proteins following treatment, including suppressed expression of the T cell inhibitor gene CHI3L1 and its protein YKL-40. The gene expression results were replicated in an independent cohort. Finally, machine learning models mainly based on transcriptomic data showed high predictive utility in classifying non-response to anti-TNF treatment in RA. CONCLUSIONS: Our integrative multi-omics analyses identified new biomarkers for the prediction of response, found pathways influenced by treatment and suggested new predictive models of anti-TNF treatment in RA patients.

Understanding interactions between risk factors, and assessing the utility of the additive and multiplicative models through simulations.

Understanding the genetic background of complex diseases requires the expansion of studies beyond univariate associations. Therefore, it is important to use interaction assessments of risk factors in order to discover whether, and how genetic risk variants act together on disease development. The principle of interaction analysis is to explore the magnitude of the combined effect of risk factors on disease causation. In this study, we use simulations to investigate different scenarios of causation to show how the magnitude of the effect of two risk factors interact. We mainly focus on the two most commonly used interaction models, the additive and multiplicative risk scales, since there is often confusion regarding their use and interpretation. Our results show that the combined effect is multiplicative when two risk factors are involved in the same chain of events, an interaction called synergism. Synergism is often described as a deviation from additivity, which is a broader term. Our results also confirm that it is often relevant to estimate additive effect relationships, because they correspond to independent risk factors at low disease prevalence. Importantly, we evaluate the threshold of more than two required risk factors for disease causation, called the multifactorial threshold model. We found a simple mathematical relationship (square root) between the threshold and an additive-to-multiplicative linear effect scale (AMLES), where 0 corresponds to an additive effect and 1 to a multiplicative. We propose AMLES as a metric that could be used to test different effects relationships at the same time, given that it can simultaneously reveal additive, multiplicative and intermediate risk effects relationships. Finally, the utility of our simulation study was demonstrated using real data by analyzing and interpreting gene-gene interaction odds ratios from a rheumatoid arthritis case-control cohort.

Methylome and transcriptome signature of bronchoalveolar cells from multiple sclerosis patients in relation to smoking.

BACKGROUND: Despite compelling evidence that cigarette smoking impacts the risk of developing multiple sclerosis (MS), little is known about smoking-associated changes in the primary exposed lung cells of patients. OBJECTIVES: We aimed to examine molecular changes occurring in bronchoalveolar lavage (BAL) cells from MS patients in relation to smoking and in comparison to healthy controls (HCs). METHODS: We profiled DNA methylation in BAL cells from female MS (n = 17) and HC (n = 22) individuals, using Illumina Infinium EPIC and performed RNA-sequencing in non-smokers. RESULTS: The most prominent changes were found in relation to smoking, with 1376 CpG sites (adjusted P < 0.05) differing between MS smokers and non-smokers. Approximately 30% of the affected genes overlapped with smoking-associated changes in HC, leading to a strong common smoking signature in both MS and HC after gene ontology analysis. Smoking in MS patients resulted in additional discrete changes related to neuronal processes. Methylome and transcriptome analyses in non-smokers suggest that BAL cells from MS patients display very subtle (not reaching adjusted P < 0.05) but concordant changes in genes connected to reduced transcriptional/translational processes and enhanced cellular motility. CONCLUSIONS: Our study provides insights into the impact of smoking on lung inflammation and immunopathogenesis of MS.

Presence of autoantibodies in "seronegative" rheumatoid arthritis associates with classical risk factors and high disease activity.

BACKGROUND: Rheumatoid arthritis (RA) is classified as seropositive or seronegative, depending on the presence/absence of rheumatoid factor (RF), primarily IgM RF, and/or anti-citrullinated protein antibodies (ACPA), commonly detected using anti-cyclic citrullinated peptide (CCP) assays. Known risk factors associate with the more severe seropositive form of RA; less is known about seronegative RA. Here, we examine risk factors and clinical phenotypes in relation to presence of autoantibodies in the RA subset that is traditionally defined as seronegative. METHODS: Anti-CCP2 IgG, 19 ACPA fine-specificities, IgM/IgG/IgA RF, anti-carbamylated-protein (CarP) antibodies, and 17 other autoantibodies, were analysed in 2755 RA patients and 370 controls. Antibody prevalence, levels, and co-occurrence were examined, and associations with risk factors and disease activity during 5 years were investigated for different antibody-defined RA subsets. RESULTS: Autoantibodies were detected in a substantial proportion of the traditionally defined seronegative RA subset, with ACPA fine-specificities found in 30%, IgA/IgG RF in 9.4%, and anti-CarP antibodies in 16%, with a 9.6% co-occurrence of at least two types of RA-associated autoantibodies. HLA-DRB1 shared epitope (SE) associated with the presence of ACPA in anti-CCP2-negative RA; in anti-CCP2-positive RA, the SE association was defined by six ACPA fine-specificities with high co-occurrence. Smoking associated with RF, but not with ACPA, in anti-CCP2-negative RA. Presence of ACPA and RF, but not anti-CarP antibodies, in conventionally defined "seronegative" RA, associated with worse clinical outcome. CONCLUSIONS: "Seronegative" RA is not truly a seronegative disease subset. Additional screening for ACPA fine-specificities and IgA/IgG RF defines a group of patients that resembles seropositive patients with respect to risk factors and clinical picture and may contribute to earlier diagnosis for a subset of anti-CCP2-/IgM RF- patients with a high need for active treatment.

Distinct HLA Associations with Rheumatoid Arthritis Subsets Defined by Serological Subphenotype.

Rheumatoid arthritis (RA) is the most common immune-mediated arthritis. Anti-citrullinated peptide antibodies (ACPA) are highly specific to RA and assayed with the commercial CCP2 assay. Genetic drivers of RA within the MHC are different for CCP2-positive and -negative subsets of RA, particularly at HLA-DRB1. However, aspartic acid at amino acid position 9 in HLA-B (Bpos-9) increases risk to both RA subsets. Here we explore how individual serologies associated with RA drive associations within the MHC. To define MHC differences for specific ACPA serologies, we quantified a total of 19 separate ACPAs in RA-affected case subjects from four cohorts (n = 6,805). We found a cluster of tightly co-occurring antibodies (canonical serologies, containing CCP2), along with several independently expressed antibodies (non-canonical serologies). After imputing HLA variants into 6,805 case subjects and 13,467 control subjects, we tested associations between the HLA region and RA subgroups based on the presence of canonical and/or non-canonical serologies. We examined CCP2(+) and CCP2(-) RA-affected case subjects separately. In CCP2(-) RA, we observed that the association between CCP2(-) RA and Bpos-9 was derived from individuals who were positive for non-canonical serologies (omnibus_p = 9.2 × 10-17). Similarly, we observed in CCP2(+) RA that associations between subsets of CCP2(+) RA and Bpos-9 were negatively correlated with the number of positive canonical serologies (p = 0.0096). These findings suggest unique genetic characteristics underlying fine-specific ACPAs, suggesting that RA may be further subdivided beyond simply seropositive and seronegative.

Tobacco smoking induces changes in true DNA methylation, hydroxymethylation and gene expression in bronchoalveolar lavage cells.

BACKGROUND: While smoking is known to associate with development of multiple diseases, the underlying mechanisms are still poorly understood. Tobacco smoking can modify the chemical integrity of DNA leading to changes in transcriptional activity, partly through an altered epigenetic state. We aimed to investigate the impact of smoking on lung cells collected from bronchoalveolar lavage (BAL). METHODS: We profiled changes in DNA methylation (5mC) and its oxidised form hydroxymethylation (5hmC) using conventional bisulphite (BS) treatment and oxidative bisulphite treatment with Illumina Infinium MethylationEPIC BeadChip, and examined gene expression by RNA-seq in healthy smokers. FINDINGS: We identified 1667 total 5mC + 5hmC, 1756 5mC and 67 5hmC differentially methylated positions (DMPs) between smokers and non-smokers (FDR-adjusted P <.05, absolute Δß >0.15). Both 5mC DMPs and to a lesser extent 5mC + 5hmC were predominantly hypomethylated. In contrast, almost all 5hmC DMPs were hypermethylated, supporting the hypothesis that smoking-associated oxidative stress can lead to DNA demethylation, via the established sequential oxidation of which 5hmC is the first step. While we confirmed differential methylation of previously reported smoking-associated 5mC + 5hmC CpGs using former generations of BeadChips in alveolar macrophages, the large majority of identified DMPs, 5mC + 5hmC (1639/1667), 5mC (1738/1756), and 5hmC (67/67), have not been previously reported. Most of these novel smoking-associating sites are specific to the EPIC BeadChip and, interestingly, many of them are associated to FANTOM5 enhancers. Transcriptional changes affecting 633 transcripts were consistent with DNA methylation profiles and converged to alteration of genes involved in migration, signalling and inflammatory response of immune cells. INTERPRETATION: Collectively, these findings suggest that tobacco smoke exposure epigenetically modifies BAL cells, possibly involving a continuous active demethylation and subsequent increased activity of inflammatory processes in the lungs. FUND: The study was supported by the Swedish Research Council, the Swedish Heart-Lung Foundation, the Stockholm County Council (ALF), the King Gustav's and Queen Victoria's Freemasons' Foundation, Knut and Alice Wallenberg Foundation, Neuro Sweden, and the Swedish MS foundation.