Objective

To investigate the relationship of genetic and biochemical determinants of paraoxonase 1 activity to carotid plaque as a surrogate marker of cardiovascular (CV) risk in patients with rheumatoid arthritis (RA).

Methods

The relationships between paraoxonase 1 activity, PON1 genotype (for the functional polymorphism at position 192), and carotid plaque presence were determined in 168 RA patients. After an overnight fast, blood was collected for lipoprotein analysis, and paraoxonase 1 activity was measured using paraoxon as the substrate. The PON1 Q192R genotype was determined for all patients. Lipoprotein cholesterol levels, traditional CV risk factors, medication use, and RA disease characteristics were assessed for all patients.

Results

Paraoxonase 1 activity values in the RA patients were highest for the RR genotype, intermediate for the QR genotype, and lowest for the QQ genotype (P < 0.0001). Compared to patients with either the QQ genotype or the QR genotype, patients with the RR genotype demonstrated decreased risk of carotid plaque on multivariate analysis, controlling for traditional CV risk factors, high-sensitivity C-reactive protein levels, prednisone use, and cholesterol-lowering medication use (P < 0.05). Additional multivariate logistic regression analysis controlling for the above factors also revealed a significant association of plasma paraoxonase 1 activity with carotid plaque in RA patients. Lower plasma paraoxonase 1 activity was associated with increased risk of carotid plaque (P < 0.05).

Conclusion

The current findings suggest a relationship of the genetic determinants and activity of paraoxonase 1 to CV risk in RA patients, as assessed by the presence or absence of carotid plaque. Further CV outcome studies are warranted to validate the utility of paraoxonase 1 as a biomarker of CV risk in patients with RA.

Background

Patients with systemic lupus erythematosus (SLE) are at increased risk of atherosclerosis, even after accounting for traditional risk factors. High levels of leptin and low levels of adiponectin are associated with both atherosclerosis and immunomodulatory functions in the general population.

Objective

To examine the association between these adipokines and subclinical atherosclerosis in SLE, and also with other known inflammatory biomarkers of atherosclerosis.

Methods

Carotid ultrasonography was performed in 250 women with SLE and 122 controls. Plasma leptin and adiponectin levels were measured. Lipoprotein a (Lp(a)), oxidised phospholipids on apoB100 (OxPL/apoB100), paraoxonase, apoA-1 and inflammatory high-density lipoprotein (HDL) function were also assessed.

Results

Leptin levels were significantly higher in patients with SLE than in controls (23.7±28.0 vs 13.3±12.9 ng/ml, p<0.001). Leptin was also higher in the 43 patients with SLE with plaque than without plaque (36.4±32.3 vs 20.9±26.4 ng/ml, p=0.002). After multivariate analysis, the only significant factors associated with plaque in SLE were leptin levels in the highest quartile (≥29.5 ng/ml) (OR=2.8, p=0.03), proinflammatory HDL (piHDL) (OR=12.8, p<0.001), age (OR=1.1, p<0.001), tobacco use (OR=7.7, p=0.03) and hypertension (OR=3.0, p=0.01). Adiponectin levels were not significantly associated with plaque in our cohort. A significant correlation between leptin and piHDL function (p<0.001), Lp(a) (p=0.01) and OxPL/apoB100 (p=0.02) was also present.

Conclusions

High leptin levels greatly increase the risk of subclinical atherosclerosis in SLE, and are also associated with an increase in inflammatory biomarkers of atherosclerosis such as piHDL, Lp(a) and OxPL/apoB100. High leptin levels may help to identify patients with SLE at risk of atherosclerosis.

Objective

To compare colonic microbial composition in systemic sclerosis (SSc) patients and healthy controls and to determine whether certain microbial genera are associated with gastrointestinal (GI) tract symptoms in patients with SSc.

Methods

Healthy controls were age- and sex-matched (1:1) with adult SSc patients. Cecum and sigmoid mucosal lavage samples were obtained during colonoscopy. The microbiota in these samples were determined by Illumina HiSeq 2000 16S sequencing, and operational taxonomic units were selected. Linear discriminant analysis effect size was used to identify the genera that showed differential expression in SSc patients versus controls. Differential expression analysis for sequence count data was used to identify specific genera associated with GI tract symptoms.

Results

Among 17 patients with SSc (88% female; median age 52.1 years), the mean ± SD total GI Tract 2.0 score was 0.7 ± 0.6. Principal coordinate analysis illustrated significant differences in microbial communities in the cecum and sigmoid regions in SSc patients versus healthy controls (both P = 0.001). Similar to the findings in inflammatory disease states, SSc patients had decreased levels of commensal bacteria, such as Faecalibacterium and Clostridium, and increased levels of pathobiont bacteria, such as Fusobacterium and γ-Proteobacteria, compared with healthy controls. Bifidobacterium and Lactobacillus, which are typically reduced under conditions of inflammation, were also increased in abundance in patients with SSc. In SSc patients with moderate/severe GI tract symptoms, the abundance of Bacteroides fragilis was decreased, and that of Fusobacterium was increased, compared with patients who had no or mild symptoms.

Conclusion

This study demonstrates a distinct colonic microbial signature in SSc patients compared with healthy controls. This unique ecologic change may perpetuate immunologic aberrations and contribute to clinical manifestations of SSc.

Objective

The increase in cardiovascular events (CVEs) in systemic lupus erythematosus (SLE) is not fully explained by traditional risk factors. We previously identified four biomarkers (proinflammatory high-density lipoprotein, leptin, soluble TNF-like weak inducer of apoptosis (sTWEAK), and homocysteine) that we combined with age and diabetes to create the predictors of risk for elevated flares, damage progression, and increased cardiovascular diseasein patients with SLE (PREDICTS) risk profile. PREDICTS more accurately identified patients with SLE at risk for progression of subclinical atherosclerosis than any individual variable. We examined whether PREDICTS can also identify patients with SLE at risk for future CVEs.

Methods

A total of 342 patients with SLE and 155 matched control subjects participated in this longitudinal prospective study. A high PREDICTS score was defined as three or more predictors or diabetes + one or more predictor. The biomarkers were measured at baseline using published methods. All major adverse CVEs (MACEs) were confirmed by medical record review.

Results

During 116 months of follow-up, 5% of patients with SLE died, 12% had a cerebrovascular event, and 5% had a cardiac event. Overall, 20% of patients with lupus experienced any new MACE compared with 5% of control subjects (P < 0.0001). More patients with SLE with a new MACE had high PREDICTS score at baseline (77%) versus patients with no new events (34%) (P < 0.0001). High baseline PREDICTS score also associated with cerebrovascular (P < 0.0001) and cardiac events (P < 0.0001) in SLE. Using Cox regression, a baseline high PREDICTS score associated with a 3.7-fold increased hazard ratio (HR) for a new MACE (P < 0.0001) in SLE. Hypertension (HR = 2.1; P = 0.006) was also a risk.

Conclusion

A high PREDICTS score and hypertension confer increased risk for new MACEs in patients with SLE.

Objective

An increased frequency of atherosclerosis (ATH) in systemic lupus erythematosus (SLE) is well-documented but not fully explained by the presence of traditional cardiac risk factors. Several nontraditional biomarkers, including proinflammatory high-density lipoprotein (piHDL) and leptin, have been individually associated with subclinical ATH in SLE. The aim of this study was to examine whether these and other biomarkers can be combined into a risk profile, the Predictors of Risk for Elevated Flares, Damage Progression, and Increased Cardiovascular Disease in Patients with SLE (PREDICTS), that could be used to better predict future progression of ATH.

Methods

In total, 210 patients with SLE and 100 age-matched healthy control subjects (all women) participated in this prospective cohort study. The longitudinal presence of carotid plaque and intima-media thickness (IMT) were measured at baseline and followup (mean ± SD 29.6 ± 9.7 months).

Results

At followup, carotid plaque was present in 29% of SLE patients. Factors significantly associated with plaque, determined using Salford Predictive Modeling and multivariate analysis, included age ≥48 years (odds ratio [OR] 4.1, P = 0.002), high piHDL function (OR 9.1, P < 0.001), leptin levels ≥34 ng/dl (OR 7.3, P = 0.001), plasma soluble TWEAK levels ≥373 pg/ml (OR 28.8, P = 0.004), and history of diabetes (OR 61.8, P < 0.001). Homocysteine levels ≥12 μmoles/liter were also a predictor. However, no single variable demonstrated an ideal combination of good negative predictive values (NPVs), positive predictive values (PPVs), sensitivity, and specificity. A high-risk PREDICTS profile was defined as ≥3 positive biomarkers or ≥1 positive biomarker plus a history of diabetes; for high-risk SLE patients, the PPV was 64%, NPV was 94%, sensitivity was 89%, and specificity was 79%. In multivariate analysis, SLE patients with the high-risk profile had 28-fold increased odds for the longitudinal presence of plaque (P < 0.001) and increased progression of IMT (P < 0.001).

Conclusion

A high-risk PREDICTS score confers 28-fold increased odds of the presence of any current, progressive, or acquired carotid plaque, both in patients with SLE and in control subjects, and is significantly associated with higher rates of IMT progression.