Association of anti-β2-glycoprotein I/HLA-DR complex antibody with arterial thrombosis in female patients with systemic rheumatic diseases

doi:10.21203/rs.3.rs-3223959/v1

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Research Article

Association of anti-β2-glycoprotein I/HLA-DR complex antibody with arterial thrombosis in female patients with systemic rheumatic diseases

https://doi.org/10.21203/rs.3.rs-3223959/v1

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published 06 Oct, 2023

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Background.

β2-glycoprotein I (β2GPI) complexed with human leukocyte antigen DR (β2GPI/HLA-DR) was found to be a major autoantibody target in antiphospholipid syndrome (APS). This study aimed to reveal the association between anti-β2GPⅠ/HLA-DR antibodies and vascular thromboses in women with systemic rheumatic diseases.

Methods.

We conducted a retrospective longitudinal study. We measured anti-β2GPⅠ/HLA-DR antibodies and compared them with anti-phospholipid antibody (aPL) profiles and the adjusted global antiphospholipid syndrome score (aGAPSS). Using receiver operating characteristic (ROC) analysis, we determined the best cut-off value for arterial thrombosis. We also evaluated the validity of anti-β2GPⅠ/HLA-DR antibodies by adding to conventional cardiovascular risk factors in multivariate logistic analysis.

Results.

We evaluated 704 patients, including 66 (obstetric or thrombotic) APS, 13 primary APS, and 78 asymptomatic aPL carriers. Seventy-seven patients had a history of arterial thrombosis, and 14 patients had both arterial and venous thrombosis. These 14 patients, as well as patients with aGAPSS > 10 or triple-positive aPL profiles, displayed high anti-β2GPⅠ/HLA-DR antibody titers. The ROC curve showed a sensitivity, specificity, and area under the curve (AUC) for arterial thrombosis of 33.8%, 91.4%, and 0.6009, respectively, with a cut-off value of 172.359 U/mL. The anti-β2GPⅠ/HLA-DR antibody positivity using this cut-off value yielded an odds ratio of 5.13 (95%CI: 2.85–9.24), significantly improving the AUC from 0.677 to 0.730.

Conclusion.

Anti-β2GPⅠ/HLA-DR antibodies are associated with arterial thrombosis in female patients with systemic rheumatic diseases.

Antiphospholipid Autoantibody

Antiphospholipid Syndrome

Cardiovascular Diseases

Thrombosis

Rheumatic Disease

Antiphospholipid syndrome (APS) is an autoimmune disorder characterized by thrombotic or obstetric events with persistent aPL antibodies [1]. β2glycoprotein I (β2GPⅠ) is one of the primary phospholipid-binding proteins recognized by aPL [2]. When the circular type β2GPⅠ binds to negatively charged molecules, such as an immobilized anionic phospholipid like cardiolipin (CL) or negatively charged solid plates [3], it transforms into a linear domain that contains a pathogenic epitope [4]. The binding of β2GPⅠ to phospholipids is closely linked to the risk of thrombosis in APS [5].

We currently apply anti-β2GPⅠ and anti-CL antibody assays to detect aPL antibodies, which are pretty good at picking out APS patients. However, standardized quantitative solid-phase enzyme-linked immunosorbent assay (ELISA) cannot fully diagnose all APS patients with clinical manifestations satisfying the criteria [6].

We have recently discovered that β2GPⅠ could also bind to specific major histocompatibility complex (MHC) class II molecules and serve as one of the main autoantibody targets in the development of APS [7]. Anti-β2GPⅠ/HLA-DR antibodies can specifically detect patients with recurrent pregnancy loss [8] or with idiopathic chronic limb ulcers [9], are believed to provide two advantages with respect to the pathogenesis of APS. First, anti-β2GPⅠ/HLA-DR antibodies have an enhanced ability to bind to disease-susceptible HLA alleles [7]. Second, β2GPⅠ/HLA-DR molecules can appear on the endothelial cell surface under inflammatory conditions, such as in elevated levels of interferon (IFN)-gamma (IFNγ) and tumor necrosis factor-alpha (TNFα) [7, 10, 11]. These mechanisms may explain the positive correlation of increased IFN type I expression with anti-β2GPⅠ antibodies [12] and justify the finding that aPL-positive individuals with systemic rheumatic diseases are at a greater risk of thrombosis than those without systemic rheumatic diseases [13].

Therefore, we hypothesized that anti-β2GPⅠ/HLA-DR antibodies could be highly expressed in patients with systemic rheumatic diseases, possibly contributing to thrombosis.

Patients suffering from systemic rheumatic diseases (in particular with disorders characterized by systemic inflammation) are thought to be at increased risk for developing cardiovascular events [14]. Hence, this study aimed to determine the association between anti-β2GPⅠ/HLA-DR antibodies and vascular thrombosis in women with systemic rheumatic diseases and to elucidate whether the anti-β2GPⅠ/HLA-DR antibodies represent an additional risk factor.

Patients and ethics

This was a single-centered, retrospective longitudinal, and cross-sectional study. Our study followed the Declaration of Helsinki guidelines and was approved by the Institutional Review Boards of our centers (approval no. B190102 at Kobe University Hospital); the project focused on women aged above the reproductive age or those with a pregnancy history supported by the Japan Agency for Medical Research and Development (AMED).

All included participants were female patients who followed-up in our department from April 2020 to December 2021 with provided written informed consent.

We assessed medical records, questionnaires, and laboratory tests. We retrieved information regarding thrombotic events, conventional cardiovascular risk factors, and medications of corticosteroids, hydroxychloroquine, immunosuppressive agents, and oral anticoagulants.

Classification criteria for systemic rheumatic diseases

Patients with APS fulfilled the updated Sapporo–Sydney classification criteria [1], while asymptomatic aPL carriers only fulfilled the laboratory criteria. Patients with systemic lupus erythematosus (SLE) met the updated 1997 American College of Rheumatology (ACR) classification criteria for SLE or the 2012 Systemic Lupus International Collaborating Clinics classification criteria [15, 16]. Patients with mixed connective tissue disease (MCTD) were classified using the 2019 Diagnostic criteria for MCTD [17], but those who met the diagnosis of SLE were classified as SLE. Patients with systemic sclerosis (SSc) fulfilled the 2013 ACR/European Alliance of Associations for Rheumatology (ACR/EULAR) classification criteria [18]. Patients with Sjögren’s syndrome (SjS) satisfied the ACR/EULAR 2016 classification criteria [19]. Some patients with rheumatic autoimmune diseases who fulfilled the classification criteria were diagnosed with idiopathic inflammatory myositis (IIMs), Bechet’s disease, ANCA-associated arthritis, and large-vessel arteritis, including Takayasu's Arteritis and Giant cell arteritis. The remaining patients were evaluated based on clinical diagnoses by a rheumatologist. Two women who did not fulfill the classification criteria for rheumatic autoimmune disorders were included as unclassified connective tissue disease (UCTD).

Data collection

Demographic and study characteristics

Our survey considered factors such as age, disease duration, body mass index (BMI), current or past smoking, pack-year smoking index, arterial hypertension (≥ 140/90 mmHg or using antihypertensive drugs), dyslipidemia (total serum cholesterol or triglyceride levels > 230 mg/dL and 150 mg/dL, respectively, or being on lipid-lowering medications, such as statins), diabetes (plasma glycated hemoglobin levels ≥ 6.5% and fasting plasma glucose 126 mg/dL, 2 h after oral glucose tolerance test or casual plasma glucose above 200 mg/dL, respectively, or using insulin or oral antidiabetic drugs), past or present family history of stroke or myocardial infarction, and personal history of thrombosis.

Vascular thrombotic morbidity

Thrombotic complications were defined as previously described [20]. Arterial thrombotic events were confirmed by their clinical features or imaging studies using computed tomography (CT) scanning, magnetic resonance imaging (MRI), or angiography (arterial thromboses are compiled in Figure S1B). A transient ischemic attack (TIA) was excluded due to the absence of modalities.

Venous thrombotic events were defined as venous thrombosis by their clinical features or imaging studies using CT angiography or scintigraphy. Patients without these thrombotic events were considered to have no thrombosis.

Obstetric morbidity

Pregnancy complications were defined as follows:

・Three or more recurrent miscarriages at gestational age < 10 weeks

・Fetal death at gestational age > ten weeks

・Premature birth before the 34th week of gestation due to hypertensive disorders of pregnancy, such as preeclampsia or placental insufficiency.

Conventional cardiovascular risk factors for arterial thrombosis and adjusted global APS score calculation

The assessment of cardiovascular risk, age, arterial hypertension, diabetes, smoking habit, dyslipidemia, and BMI was considered to be based on some traditional risk factors [21]. The adjusted global APS score (aGAPSS) [22] was calculated as previously described. aGAPSS is a composite measure to estimate the risk of arterial thrombosis; aGAPSS > 10 points indicates a significant risk for ischemic stroke [23] and cardiovascular disease [24]. aGAPSS ≥ 14 (aGAPSS > 13) points are associated with the highest risk of clinical recurrence in patients with APS [25]. Referring to a previous study for risk stratification with aGAPSS [26], the aGAPSS cluster was categorized as follows: none (< 1 point), very low (1–3 points), low (4–5 points), middle (6–9 points), high (10–13 points), and very high (≥ 14 points).

Detection of autoantibodies

Serum samples were collected from 704 patients. Of these, 343 patients were tested for the aPL panel using commercially available chemiluminescent immunoassay (CIA) kits, including both aCL and anti-β2GPⅠ IgG/IgM antibodies, and evaluated multiple aPL antibodies. Positive aCL was defined as aCL IgG/IgM levels > 20 U/mL; positive anti-β2GPⅠ was defined as anti-β2GPⅠ IgG/IgM levels > 20 U/mL, as recommended by manufacturers [27]. Additionally, we retrospectively surveyed the following aPL autoantibodies detected by commercially available enzyme immunoassay (EIA) solid-phase kits: aCL IgG antibodies and aCL β2 glycoprotein I (anti-CLβ2GPⅠ) IgG antibodies. Positive aCL was defined as aCL IgG levels > 10 U/mL (10.2 U/mL is 99 percentile value); positive anti-CLβ2GPⅠ was defined as anti-CLβ2GPⅠ IgG levels > 3.5 U/mL (1.8 U/mL is 99 percentile value), as recommended by the manufacturer of each kit.

Lupus anticoagulant (LA) was measured according to the guidelines [28]. Positive LA using silica clotting time, the normalized screen ratio was defined as ≥ 1.20.

Positivity of either 1, 2, or 3 assays, including aCL IgG/IgM, anti-β2GPⅠ IgG/IgM antibodies using CIA or EIA kits, and LA, were defined as single, double, and triple-positive, respectively.

Non-criteria aPL autoantibodies, such as anti-phosphatidylserine-prothrombin (aPS/PT), were not measured since these are not yet covered by medical insurance.

Measurement of levels of antibodies for β2GPⅠ/HLA-DR

Anti-β2GPⅠ/HLA-DR antibodies (Revorf Co., Ltd. Tokyo, Japan.) were quantified based on a previously reported method [8]. The reference value was determined as 73.3 U/mL with a 99 percentile value in 374 healthy control participants after outlier removal [29].

Statistical analyses

All statistical analyses were performed using R (version 4.1.2).

The data are expressed in positive or negative numbers, percentages for categorical variables, mean ± standard deviation, or median and interquartile range. The Chi-squared and Fisher’s exact tests were used for categorical variables, as appropriate. Mann–Whitney U and Kruskal–Wallis’ test, with post hoc comparisons using the Steel–Dwass tests, were used to compare continuous variables between groups. A two-tailed p-value < 0.05 indicated a significant difference between arterial and non-arterial thrombosis groups.

Receiver operating characteristic (ROC) analyses were conducted to demonstrate the optimal cut-off value of anti-β2GPⅠ/HLA-DR antibodies in differentiating arterial thrombosis from non-arterial thrombosis. We evaluated the performances of different aPL antibodies by calculating the area under the curve (AUC), sensitivity, and specificity of the suggested cut-off values by using Fisher’s exact tests and the Youden index.

Multivariate logistic regression models were prepared to estimate the risk of arterial thrombosis associated with potential predictors, including clinical or sociodemographic variables such as age, disease duration, BMI, pack-year smoking index, current doses of prednisolone, dyslipidemia, arterial hypertension, diabetes, and the cut-off of anti-β2GPⅠ/HLA-DR antibodies. Variables in these models were based on conventional cardiovascular risk factors for arterial thrombosis, adjusted global APS score, and significant factors in univariate analysis. The variance inflation factor (VIF) was used to check multicollinearity. The AUC was evaluated, and compared the discrimination efficacy of the multivariate model. Further, the Delong test for comparison of AUCs, Net reclassification improvement (NRI), and integrated discrimination improvement (IDI) analyses were conducted to evaluate and compare potential net benefits by adding the threshold of anti-β2GPⅠ/HLA-DR antibody.

The outcome of the odds ratios is presented together with the 95% confidence interval (CI). The level of statistical significance was set at a two-tailed α-value of 0.05 by default.

Multiple imputation

BMI, disease duration, and pack-year smoking had missing values. We adjusted the dataset with multiple imputation (MI) by chained equation (MICE) package (version 3.15.0) [30]. we replaced missing values with complementary values by using the following covariates to produce 20 filled-in datasets through the imputation process: age, disease duration, height, body weight, BMI, smoking history, pack-year smoking index, dyslipidemia, arterial hypertension, diabetes, anti-β2GPⅠ/HLA-DR antibodies, aGAPSS, with or without arterial thrombosis, several laboratory data (platelet cell count, C-reactive protein, erythrocyte sedimentation rate, IgG subtype, complements component 3 and 4, different aPL titers, presence or absence of current medications, which include current doses of prednisolone, hydroxychloroquine, or immunosuppressive agents.

Demographic and clinical characteristics of enrolled patients

Among the 721 patients, 704 samples were collected in the dataset, and 17 were excluded owing to lost visits (Figure S1A). We identified 77 patients with histories of arterial thrombosis, including only arterial thrombosis (n = 63) and both arterial and venous thrombosis (n = 14). The group of non-arterial thrombosis (n = 627) included patients with no history of thrombosis (n = 583) or with venous thrombosis only (n = 44). Among the 77 patients with arterial thrombosis, the most common manifestation was cerebral infarction. (Figure S1B).

Clinical and demographic characteristics stratified according to the presence of arterial thrombosis are reported in Table 1. Some cardiovascular risks, such as age, arterial hypertension, smoking, and current dosage of prednisolone, were detected more frequently in patients with arterial thrombosis than among participants with non-arterial thrombosis (Table 1). Distributions of aPL autoantibodies, particularly aβ2GPⅠ IgG subtypes, LA positivity, anti-β2GPⅠ/HLA-DR antibody levels, and aGAPSS tended to be higher in the arterial thrombosis group than in the non-arterial thrombosis group.

Table 1

Baseline characteristics of patient epidemiology and laboratory findings.
Variables			Thrombosis
			Overall	Non-arterial	Arterial	p-value²
		N	all = 704¹	n = 627¹	n = 77¹	p-value²
Demographics
Age, mean (± SD), years	704	57.1 ± 15.8	56.7 ± 15.9	60.5 ± 14.4	0.046
Female sex, n (%)		704 (100%)	627 (100%)	77 (100%)	1.000
Disease duration, median (IQR), years	699	12 (6, 21)	12 (6, 20)	14 (5, 23)	0.405
The largest dose of prednisolone, median (IQR), mg/day	622	25 (5, 45)	20 (3.75, 45)	30 (10, 50)	0.020
Current dose of prednisolone, median (IQR), mg/day	704	2 (0, 5)	2 (0, 5)	4.5 (1, 5.5)	< 0.001
Conventional cardiovascular risk factors
BMI, mean (± SD), kg/m²	458	21.5 ± 4.0	21.4 ± 4.1	22.0 ± 3.4	0.124
Smoking history, n (%)
No		528 (75%)	475 (76%)	53 (69%)	0.133
Former		84 (12%)	70 (11%)	14 (18%)
Current		14 (2.0%)	11 (1.8%)	3 (3.9%)
Unknown		78 (11%)	71 (11%)	7 (9.1%)
Pack-year smoking, mean (± SD)	620	2.20 ± 6.68	1.90 ± 6.01	4.66 ± 10.4	0.026
Arterial hypertension, n (%)		169 (24%)	137 (22%)	32 (42%)	< 0.001
Diabetes mellitus, n (%)		76 (11%)	64 (10%)	12 (16%)	0.151
Dyslipidemia, n (%)		203 (29%)	179 (29%)	24 (31%)	0.632
Family History of thrombosis, n (%)
Coronary diseases		16 (2.3%)	16 (2.5%)	0 (0%)	1.000
Stroke		34 (4.8%)	31 (4.9%)	3 (3.9%)	1.000
Autoantibodies for aPL
aCL IgG [EIA], median (IQR), U/mL	304	6.00 (3.00, 10.25)	6.00 (2.70, 9.00)	7.99 (3.00, 21.50)	0.060
aCLβ2GPI IgG [EIA], median (IQR), U/mL	378	0.69 (0.69, 1.19)	0.69 (0.69, 1.19)	0.70 (0.69, 1.99)	0.022
aCL IgG [CLIA], median (IQR), U/mL	343	5.45 (3.73, 9.20)	5.35 (3.68, 8.75)	6.95 (4.00, 14.50)	0.050
aCL IgM [CLIA], median (IQR), U/mL	343	2.20 (1.30, 4.40)	2.10 (1.30, 4.35)	2.50 (1.60, 4.85)	0.339
aβ2GPI IgG [CLIA], median (IQR), U/mL	343	6.39 (6.39, 10.05)	6.39 (6.39, 8.90)	6.39 (6.39, 42.95)	0.006
aβ2GPI IgM [CLIA], median (IQR), U/mL	343	1.09 (1.09, 1.85)	1.09 (1.09, 1.80)	1.09 (1.09, 1.88)	0.802
LA test Positive no. /total no.	368	83/368 (23%)	59/314 (19%)	24/54 (44%)	< 0.001
Anti-β2GPI/HLA-DR, median (IQR), U/mL	704	34.15 (11.92, 80.21)	33.43 (11.82, 74.81)	61.61 (13.36, 256.39)	0.004
APS profile and adjusted global APS score (aGAPSS)
Patients of APS / aPL carrier, n (%)
Fulfill the APS classification criteria		66 (9.4%)	32 (5.1%)	34 (44%)	< 0.001
Primary APS (PAPS)		13 (1.8%)	9 (1.4%)	4 (5%)	< 0.001
Secondary APS (SAPS)		53 (7.5%)	23 (3.6%)	30 (39%)	< 0.001
Catastrophic APS (CAPS)		0 (0%)	0 (0%)	0 (0%)	1.000
Asymptomatic aPL carrier		78 (11%)	78 (12%)	0 (0%)	1.000
aGAPSS, median (IQR)	368	3.00 (0.00, 5.00)	1.00 (0.00, 4.00)	4.00 (1.50, 12.25)	< 0.001
Other laboratory data
PLT, median (IQR), ×10⁴/µL	702	23 (19, 27)	23 (19, 28)	23 (19, 26)	0.427
CRP, median (IQR), mg/dl	702	0.04 (0.02, 0.15)	0.04 (0.02, 0.14)	0.05 (0.02, 0.19)	0.409
IgG, median (IQR), mg/dl	527	1,230 (986, 1,531)	1,234 (993, 1,535)	1,187 (942, 1,512)	0.436
IgA, median (IQR), mg/dl	213	235 (164, 336)	236 (167, 333)	232 (149, 380)	0.998
IgM, median (IQR), mg/dl	211	83 (51, 119)	85 (52, 119)	72 (44, 117)	0.462
C3, median (IQR), mg/dl	316	84 (71, 100)	83 (70, 98)	92 (74, 105)	0.065
C4, median (IQR), mg/dl	311	17 (12, 23)	17 (12, 23)	15 (12, 22)	0.782
Abbreviations: APS, Antiphospholipid antibody syndrome; aGAPSS, adjusted Global Antiphospholipid Syndrome Score; aCL, anticardiolipin antibody; aβ2GPⅠ, anti-β2GPⅠ antibody; BMI, body mass index; CIA, Chemiluminescent immunoassay; CRP, C-reactive protein; EIA, Enzyme immunoassay; IQR, interquartile range; LA, Lupus anticoagulant; PLT, Platelet; SD, standard deviation.
¹ n (%) for categorical data; mean ± SD or median (IQR) for qualitative data.
² Pearson chi-square test (or chi-square test with the Yates continuity, or Fisher exact test if appropriate) for categorical data, and the Mann–Whitney U test for qualitative data.

Titers of anti-β2GPⅠ/HLA-DR antibodies in different clinical groups

Figure 1A illustrates the primary diseases among the 704 patients in a clockwise direction of the pie chart. Anti-β2GPⅠ/HLA-DR antibodies among different clinical groups are shown in Fig. 1B–F, and the frequencies of occurrence and details with arterial thrombosis are tabulated in Figure S1B and Table S1. The majority of the systemic rheumatic diseases had a high cut-off value of more than 99 percentile (Fig. 1B). Although patients with primary APS showed no deviations between the two groups, patients with secondary APS showed higher anti-β2GPⅠ/HLA-DR antibody levels in the arterial thrombosis group than those in the non-arterial thrombosis group (Fig. 1C). Anti-β2GPⅠ/HLA-DR antibody titers were significantly higher in patients with both arterial and venous thrombosis than those with no or venous-only thrombosis (Fig. 1D). There were no significant differences between the aPL carrier and definite APS (Figure S2A). The anti-β2GPⅠ/HLA-DR antibody levels were elevated in patients with thrombotic APS, while patients with obstetric APS did not show increased antibody levels compared with those in the aPL carrier (Figure S2B). The more remarkable clusters of aGAPSS or aPL positivity showed higher frequencies of arterial thrombosis and the median of anti-β2GPⅠ/HLA-DR antibodies (Fig. 1E, F). Frequencies of arterial thrombosis with the aGAPSS clusters are depicted in Figure S3.

The diagnostic value of anti-β2GPⅠ/HLA-DR antibodies

The ROC curve of the anti-β2GPⅠ/HLA-DR antibody showed a sensitivity, specificity, and AUC for arterial thrombosis of 33.8%, 91.4%, and 0.6009, respectively, with a cut-off value of 172.359 U/mL (Fig. 2A). We assessed the diagnostic performances of aPL antibodies for arterial thrombosis with univariate ROC analysis and Fisher’s exact test (Fig. 2B and Table 2, respectively). The anti-β2GPⅠ/HLA-DR antibody in the 99 percentile had greater sensitivity to aβ2GP Ⅰ than the other isotype. The anti-β2GPⅠ/HLA-DR antibodies had a plausible ROC curve, and their optimal cut-off (≥ 172.359 U/mL) yielded better accuracy than the other autoantibodies for aPL.

Table 2

Diagnostic performances of aPL antibodies for arterial thrombosis.
	Fisher’s exact test												ROC curve analysis (Youden index)
Parameters	All , n	Pos. , n	Neg. , n	Sn	Sp	PPV	NPV	Accuracy	LR+	LR-	OR (95% CI)	Cut-off	All , n	Pos. , n	Neg. , n	Sn	Sp	Accuracy	AUC	Youden's index	Optimal point
LA test	368	84	284	0.444	0.809	0.286	0.894	0.755	2.326	0.687	3.37 (1.75–6.45)	1.2	−	−	−	−	−	−	−	−	−
aCL IgG [EIA]	304	75	229	0.353	0.775	0.240	0.856	0.704	1.567	0.835	1.87 (0.92–3.72)	10	304	51	253	0.373	0.787	0.717	0.583	0.159	12.0
aCL IgG [CIA]	342	38	304	0.220	0.908	0.289	0.872	0.807	2.379	0.859	2.75 (1.14–6.32)	20	342	50	292	0.360	0.825	0.757	0.587	0.185	10.7
aCL IgM [CIA]	341	18	323	0.080	0.952	0.222	0.858	0.824	1.663	0.966	1.71 (0.39–5.79)	20	341	50	291	0.620	0.533	0.546	0.542	0.153	2.30
aCLβ2GPI IgG [EIA]	378	35	343	0.200	0.928	0.343	0.860	0.812	2.765	0.862	3.19 (1.35–7.22)	3.5	378	60	318	0.350	0.846	0.767	0.584	0.196	1.30
aβ2GPI IgG [CIA]	343	54	289	0.320	0.870	0.296	0.882	0.790	2.467	0.781	3.14 (1.47–6.53)	20	343	50	293	0.826	0.400	0.764	0.602	0.226	14.0
aβ2GPI IgM [CIA]	343	18	325	0.100	0.956	0.278	0.862	0.831	2.254	0.942	2.38 (0.63–7.57)	20	343	50	293	0.911	0.160	0.802	0.510	0.071	7.10
anti-β2GPI/ HLA-DR antibody	704	193	511	0.442	0.746	0.176	0.916	0.713	1.741	0.748	2.32 (1.39 − 3.88)	73.3	704	77	627	0.338	0.914	0.851	0.601	0.252	172.359
Abbreviations: aPL, antiphospholipid antibody; APS, Antiphospholipid antibody syndrome; aCL, anticardiolipin antibody; aβ2GPⅠ, anti-β2GPⅠ antibody; LA, Lupus anticoagulant; LR, likelihood ratio; OR, odds ratio; NPV, negative predictive value; PPV, positive predictive value.
Various aPL antibodies measured by EIA or chemiluminescent immunoassay (CIA) were evaluated by calculating the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, positive or negative likelihood ratio (LR + or LR−), and odds ratio.

Assessment for conventional cardiovascular risk factors with anti-β2GPⅠ/HLA-DR antibody

Further, we examined the impact of anti-β2GPⅠ/HLA-DR antibodies in the multivariate models.

Table 3 shows the results of the univariable or multivariable logistic regression analysis for arterial thrombosis with complete cases and MI. The VIFs were under five for all independent variables. In multivariate analysis with complete cases, higher age, higher current doses of prednisolone, and anti-β2GPⅠ/HLA-DR antibody levels ≥ 172.359 U/mL were significantly associated with arterial thrombosis. A high pack-year smoking index and a proportion of arterial hypertension were adequately related to arterial thrombosis in cases with MI.

Table 3

Univariable and multivariable logistic regression analysis with multiple imputation.
	Univariate		Multivariate
			Complete cases (n = 409)				Multiple imputation (n = 704)
			Conventional cardiovascular risk factors alone (model 1)		the addition of anti-β2GPI/HLA-DR antibody status (model 2)		the addition of anti-β2GPI/HLA-DR antibody status (model 2)
Variables	OR(95%CI)	p-value	OR(95%CI)	p-value	OR(95%CI)	p-value	OR(95%CI)	p-value
Age	1.02 (1.00–1.03)	0.050	1.02 (1.00–1.04)	0.043	1.03 (1.00–1.05)	0.027	1.01 (0.99–1.03)	0.059
Disease duration	1.01 (0.99–1.03)	0.341	1.00 (0.98–1.03)	0.790	1.00 (0.98–1.03)	0.850	1.00 (0.98–1.02)	0.610
Body mass index	1.04 (0.97–1.10)	0.270	1.02 (0.95–1.09)	0.651	1.01 (0.94–1.09)	0.730	1.01 (0.94–1.08)	0.750
Pack-year smoking	1.04 (1.02–1.07)	0.002	1.03 (1.00–1.07)	0.063	1.03 (1.00–1.07)	0.073	1.04 (1.01–1.07)	0.007
Current doses of prednisolone	1.07 (1.01–1.13)	0.014	1.11 (1.02–1.20)	0.012	1.11 (1.03–1.20)	0.009	1.07 (1.01–1.13)	0.018
Dyslipidemia	1.13 (0.68–1.89)	0.632	0.73 (0.35–1.49)	0.387	0.78 (0.37–1.61)	0.500	0.77 (0.42–1.40)	0.401
Arterial hypertension	2.54 (1.56–4.16)	< 0.001	1.82 (0.93–3.58)	0.081	1.81 (0.91–3.61)	0.092	2.37 (1.33–4.23)	0.003
Diabetes	1.62 (0.83–3.17)	0.155	1.04 (0.42–2.56)	0.932	1.26 (0.51–3.12)	0.620	1.15 (0.52–2.52)	0.723
Anti-β2GPI/HLA-DR antibody status (cut-off = 172.359 U/ml)	5.10 (2.94–8.87)	< 0.001	—	—	4.39 (2.14–9.03)	< 0.001	5.13 (2.85–9.24)	< 0.001
Abbreviations: CI, confidence interval; OR, odds ratio.
The variance inflation factors were < 5 for all of the independent variables. Compared with the non-arterial thrombosis group, the arterial thrombosis group had a significantly positive anti-β2GPⅠ/HLA-DR antibody cut-off (odds ratio: 5.11; 95% CI: 2.84–9.19) in multivariate logistic regression analysis with multiple imputation. Increased age, a high prednisolone dose, high pack-year smoking, and a history of arterial hypertension were significantly associated with arterial thrombosis.

The odds ratio for anti-β2GPⅠ/HLA-DR antibody levels ≥ 172.359 U/mL was 5.13 (95% CI: 2.85–9.24) for arterial thrombosis in multivariate analysis with MI. Disease duration, BMI, dyslipidemia, and diabetes were not linked to arterial thrombosis in this study.

Improvement in multivariate models with anti-β2GPⅠ/HLA-DR antibody

We compared two multivariate and multiclass ROC analyses (Table 3). These AUCs (Fig. 3) were used to evaluate and compare the discrimination efficacy of the multivariate models.

To detect arterial thrombotic events, anti-β2GPⅠ/HLA-DR antibody cut-off to the conventional cardiovascular risks improved the AUCs (model 1 vs. model 2; 0.677 to 0.730). Unfortunately, there were no significant differences (model 1 vs. model 2; p = 0.087) with C-index improvement. Further analyses with continuous NRI (model 1 vs. model 2; 0.447 [95% CI: 0.187–0.707], p-value < 0.001) and IDI (model 1 vs. model 2; 0.0446 [95% CI: 0.0143–0.0749], p-value = 0.004) were statistically significant.

To the best of our knowledge, this is the first study to elucidate the association between anti-β2GPⅠ/HLA-DR antibodies and arterial thrombotic episodes in female patients with various systemic rheumatic diseases.

In regard to venous thromboses, Many risk factors, such as age, immobility, dehydration, obesity, pregnancy, cancer, surgery, and anti-tumor drugs or estrogen therapy [31], vary considerably from those of arterial thrombosis and are sometimes transient. Hence, it was difficult to establish the association between anti-β2GPⅠ/HLA-DR antibodies and venous thrombosis from this cross-sectional study. Above all, β2GPI-dependent aCL and anti-β2GPI antibodies are reported to be key predictors of arterial thrombosis [32, 33]. Thus, this study focused on arterial thrombosis.

Moreover, Japanese APS patients are likely to have the predominant type of arterial thrombosis [34]. Most arterial thromboses in APS are cerebral vasculature, usually in the form of a stroke or TIA [35]. Similarly, our study population also showed an equivalent distribution of arterial thrombosis.

Interestingly, approximately one-third of the study participants showed anti-β2GPI antibody titers above the 99 percentile calculated from healthy controls. Although SLE or MCTD, wherein the HLA-DRs are related to disease susceptibility, tend to have high titers [36–38], HLA-DR variations alone could not justify this finding. The disease-susceptible MHC class II alleles of APS (HLA-DRB1*04, HLA-DRB1*07) are efficiently expressed on the cell surface in combination with non-peptide β2GPⅠ and recognized by aPL. Simultaneously, almost all HLA-DRs, except HLA-DRB1*04 and HLA-DRB1*07, also express β2GPⅠ and bind to aPL [7, 39]. Although we could not show evidence of the study patient’s MHC class II, its heterogeneity in background diseases influenced the variation in anti-β2GPI antibodies among various systemic rheumatic diseases.

Particularly, pro-inflammatory cytokines, such as IFNγ and TNFα, are important for MHC class Ⅱ expression on non-antigen-presenting cells [40, 41]. In addition, IFNγ and TNFα promote the β2GPⅠ/HLA-DR expression on endothelial cells [7]. The type I IFN signature affects the pathogenesis of several rheumatic autoimmune diseases, including SLE, RA, SSc, IIMs, and APS [42, 43]. Type I IFN upregulation also affects the increased production of circulating plasmablasts linked to aPL [44]. Thus, the upregulation of various cytokines, including type I IFN, in various primary diseases could explain the high titers of anti-β2GPⅠ/HLA-DR antibodies.

Additionally, the anti-β2GPⅠ/HLA-DR antibody titers were increased in the subset with arterial thrombotic episodes and were more frequent and significantly higher in patients with triple-positive or aGAPSS > 10, which were previously reported to be at an increased risk for arterial thrombosis. IFNγ or TNFα itself is crucial in accelerating inflammatory atherogenesis. Moreover, anti-β2GPI antibodies themselves may increase vascular inflammation and enhance atherosclerosis [45]. Anti-β2GPI antibodies are also significantly associated with the thickness of the intima-media [46]. Anti-β2GPI/HLA-DR antibodies induced on these inflammatory sites and mediated pro-inflammatory atherothrombosis may demonstrate pathogenic mechanisms of cardiovascular events in systemic rheumatic diseases. Hence, the anti-β2GPⅠ/HLA-DR antibody can indicate the quantitative risk for arterial thrombosis, which may aid in calculating the reasonable cut-off value using univariate ROC analysis.

In general, arterial thrombosis is frequent in triple-positive cases with high β2GPⅠ IgG levels. No thrombosis with aPL carriers is considered a pre-thrombotic phase and needs reevaluation as a trigger for the development of thrombotic APS [47]. These triggers include reported infection, smoking, long-term immobility, pregnancy, oral contraceptive, malignancy, nephrosis, arterial hypertension, and hyperlipidemia [48]. Therefore, it is necessary to investigate the independent performance of anti-β2GPⅠ/HLA-DR antibodies in a combination of generic cardiovascular risk factors. Accordingly, we confirmed the clinical benefit of setting an anti-β2GPⅠ/HLA-DR antibody cut-off to the conventional cardiovascular risks in a multivariate model.

Simultaneously, our results implied that high blood pressure, high amounts of smoking, increased age, and high daily glucocorticoid doses could help screen arterial thrombotic risk. Similarly, Erkan et al. reported high blood pressure and smoking as risk factors for arterial thrombosis [48]. Cumulative and higher daily glucocorticoid doses are considered clinical predictors of thrombosis or atherosclerosis in patients with SLE [49, 50]. EULAR recommendations for cardiovascular risk have indicated glucocorticoid dose minimization in SLE and vasculitis [51].

In some clinical studies, the global antiphospholipid syndrome score (GAPSS) is often applied as the scoring scale to identify the increased risk of thrombosis or APS. aGAPSS, which excludes aPS/PT antibody, is more straightforward than GAPSS. Yet, the glucocorticoid dose and the amount of smoking are not included in aGAPSS. We should consider these as risk factors for arterial thrombosis due to a lack of validated rheumatic disease-specific scales for cardiovascular risk, even if there is a small odds ratio.

In this study, we identified the clinical decision limit at 172.359 U/mL for arterial thrombosis. Most clinicians must verify if thromboses are related to APS because some patients require persistent prophylaxis in cases with severe, multiple, or recurrent thromboses. When the difference between the diagnostic and treatment threshold can be distinguished in these titers, this cut-off (≥ 172.359 U/mL) may guide clinical practice for improving cardiovascular risk management.

The limitations of this study are as follows. First, although patients in this study were tested for aPL, all patients were not confirmed for the LA test using the diluted Russell’s viper venom time, since multiple simultaneous tests are not accepted by medical insurance in Japan. Second, only female participants were included in this study. Male patients are known to be at high risk of thrombotic recurrence [52]. Third, the number of patients with arterial thrombosis was insufficient to establish firm conclusions from the multivariate logistic regression analysis with complete cases. Less than half of patients have been tested for classical APS antibodies, and complements also have less than half of the patient data. Imputation analysis on these values might be inaccurate. Fourth, this study was based on medical records and questionnaires; there may be non-respondent and recall bias. So, the titers of anti-β2GPⅠ/HLA-DR antibodies in the group of obstetric APS may not have shown increased levels compared with those in the aPL carrier. Fifth, we could not confirm the onset time of thrombosis. The values of anti-β2GPⅠ/HLA-DR antibodies may have already decreased because the samples were not collected in the active thrombotic phase.

In conclusion, we identified that the anti-β2GPⅠ/HLA-DR antibodies were related to arterial thrombosis in female patients with systemic rheumatic diseases. Considering that risk stratification is essential, the anti-β2GPⅠ/HLA-DR antibody may help suggest arterial thrombosis, even though they coexist with conventional cardiovascular risk factors, and determine the administration of anticoagulants. Nonetheless, the performance of anti-β2GPⅠ/HLA-DR antibodies should be confirmed in a further prospective investigation for external validation.

aβ2GPI: anti-β2-glycoprotein I

HLA-DR: human leukocyte antigen DR

APS: antiphospholipid syndrome

aGAPSS: adjusted global antiphospholipid syndrome score

ROC: receiver operating characteristic

AUC: area under the curve

aPL: anti-phospholipid antibody

aCL: anti-cardiolipin

ELISA: enzyme-linked immunosorbent assay

MHC: major histocompatibility complex

IFNγ: interferon-gamma

TNFα: tumor necrosis factor-alpha

AMED: Japan Agency for Medical Research and Development

SLE: systemic lupus erythematosus (SLE)

ACR: American College of Rheumatology

MCTD: mixed connective tissue disease

SSc: systemic sclerosis

EULAR: European Alliance of Associations for Rheumatology

SjS: Sjögren’s syndrome

IIMs: inflammatory myositis

UCTD: unclassified connective tissue disease (UCTD).

BMI: body mass index (BMI),

CT: computed tomography

MRI: magnetic resonance imaging (MRI)

TIA: transient ischemic attack

CIA: chemiluminescent immunoassay

aCLβ2GPⅠ: anti-cardiolipin β2 glycoprotein I

LA: Lupus anticoagulant

aPS/PT: anti-phosphatidylserine-prothrombin

VIF: variance inflation factor

NRI: net reclassification improvement

IRI: integrated discrimination improvement

CI: confidence interval

MI: multiple imputation

MICE: multiple imputation by chained equation

BD: Bechet disease

LVV: Large-vessel vasculitis

pAPS: primary Antiphospholipid antibody syndrome

RA: Rheumatoid arthritis

CRP: C-reactive protein

EIA: Enzyme immunoassay

IQR: interquartile range;

PLT: Platelet

SD: standard deviation.

LR: likelihood ratio

OR: odds ratio

NPV: negative predictive value

PPV: positive predictive value

AZA: Azathioprine

csDMARDs: conventional synthetic disease-modifying anti-rheumatic drugs

CNS: Central Nervous System

HCQ: Hydroxychloroquine

IGU: Iguratimod

IL-6R: Interleukin-6 receptor

IS: immunosuppressant

IVCY: Intravenous cyclophosphamide

IVIG: Intravenous immunoglobulin

LEF: Leflunomide

MMF: Mycophenolate mofetil

mPSL: Methylprednisolone

MTX: Methotrexate

MZR: Mizoribine

POCY: per oral cyclophosphamide

SASP: Salazosulfapyridine

TAC: Tacrolimus

JAK: Janus kinase.

Ethics approval and consent to participate: For the Patients and ethics in the section Patients and Methods

Consent for publication: Not applicable

Availability of data and materials: JS had complete access to all of the raw data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Data are available upon reasonable request.

Competing interests: Drs. Tanimura and Arase hold a patent related to autoantibody detection (patent no. WO2015008498). No other disclosures relevant to this article were reported.

Fundings: This work was supported by AMED under grant numbers JP21ek0410088 (to AH), JP21gk0110047 (to HY), and JP22gk0110061 (to HY); the Japan Society for the Promotion of Science KAKENHI under grant number JP20K09642 (to HY).

Authors' contributions: KY, YU, KT, HA, HY, and JS designed and supervised the study. KY and YU collected medical records and data. KY, YU, and JS performed the analysis and interpreted the data. All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version of the manuscript.

Acknowledgments: The authors would like to thank all the members of the “Baby and Infant in Research of Health and Development to Adolescent and Young Adults” supported by AMED for their advice and comments throughout the project.

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Competing interest reported. Drs. Tanimura and Arase hold a patent related to autoantibody detection (patent no. WO2015008498). No other disclosures relevant to this article were reported.

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Association of anti-β2-glycoprotein I/HLA-DR complex antibody with arterial thrombosis in female patients with systemic rheumatic diseases

Status:

Journal Publication

Version 1

Abstract

Background.

Methods.

Results.

Conclusion.

Figures

Introduction

Patients and Methods

Patients and ethics

Classification criteria for systemic rheumatic diseases

Data collection

Demographic and study characteristics

Vascular thrombotic morbidity

Obstetric morbidity

Conventional cardiovascular risk factors for arterial thrombosis and adjusted global APS score calculation

Detection of autoantibodies

Measurement of levels of antibodies for β2GPⅠ/HLA-DR

Statistical analyses

Multiple imputation

Results

Demographic and clinical characteristics of enrolled patients

Titers of anti-β2GPⅠ/HLA-DR antibodies in different clinical groups

The diagnostic value of anti-β2GPⅠ/HLA-DR antibodies

Assessment for conventional cardiovascular risk factors with anti-β2GPⅠ/HLA-DR antibody

Improvement in multivariate models with anti-β2GPⅠ/HLA-DR antibody

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1