Thrombotic microangiopathies (TMA) are a group of disorders characterized by thrombocytopenia, microangiopathic hemolytic anemia and microvascular occlusion resulting in end-organ ischemia and infarction.1 These disorders can be broadly categorized into primary and secondary syndromes. Primary syndromes include thrombotic thrombocytopenic purpura (congenital or acquired ADAMTS13 deficiency [aTTP]), shiga toxin-related hemolytic uremic syndrome (HUS) or complement-mediated HUS, also called atypical HUS (aHUS). Secondary TMA can be due to a variety of causes such as malignant hypertension, autoimmune diseases (systemic lupus erythematosus [SLE], scleroderma, catastrophic antiphospholipid antibody syndrome), disseminated intravascular coagulation (DIC), infections, sepsis, solid organ or hematopoietic stem cell transplantation, medications (e.g., cyclosporine, ticlopidine, clopidogrel, quinine), pregnancy associated (HELLP syndrome), and others.

Although TMA are rare (e.g., the incidence of aTTP in adults is 3 per 1,000,0002 and incidence of HUS in children is 3 per 100,0003) they require urgent intervention based on recognition of the underlying pathophysiology. However, diagnosing the specific cause is often challenging as these conditions have overlapping clinical features. The diagnosis requires an extensive work-up that can include stool culture or polymerase chain reaction (PCR) for shiga toxin gene detection (for HUS), complement levels and mutations involving complement factors (for aHUS), ADAMTS13 activity and antibodies/inhibitor levels (for aTTP), along with other tests including complete blood count with peripheral blood smear examination, lactate dehydrogenase (LDH), serum haptoglobin, liver function tests, renal function tests, antinuclear antibody (ANA), lupus anticoagulants, antiphospholipid antibodies, and viral serology among other things. Some of these assays, particularly ADAMTS13 and complement mutation analysis, are not available at all facilities, and thus samples are often sent to reference laboratories, making them unsuitable for real-time clinical decision making at most institutions.4

Given the high mortality rate for aTTP, treatment (therapeutic plasma exchange (TPE) and/or caplacizumab) is usually initiated urgently based on a high index of clinical suspicion, even without ADAMTS13 activity results; currently no gold standard for the diagnosis of aTTP is available. Recent studies have utilized the PLASMIC scoring system for rapid assessment of adults with TMA to predict the likelihood of aTTP.5 In a meta-analysis, Paydary et al.6 confirmed the diagnostic accuracy of the PLASMIC score (99% sensitivity, 57% specificity, and 99% negative predictive value [NPV]), while other studies have not found the PLASMIC score a reliable tool for establishing, or not establishing, a diagnosis of aTTP.7,8

Prior studies have shown increased susceptibility for aTTP with the presence of HLA-DRB1*11, DQB1*03:01, and DQB1*02:02, while the presence of HLA-DRB4 and HLA-DRB1*04 have been found to be protective.9-12 However, no studies have been performed to look for HLA associations with other causes of TMA.

HLA typing has a fast turnaround time and results can be available in less than five hours. Many facilities that perform TPE also have an associated HLA laboratory that routinely performs HLA testing for deceased organ donors or patients with platelet refractoriness during after-hours and on weekends. By comparison, ADAMTS13 testing is less commonly available in-house even at larger facilities and University hospitals and is often sent out to reference laboratories. Hence, HLA typing might be useful as an adjunct test, if available, to aid in differential diagnosis of TMA. The objective of this study was to look for associations between HLA and various causes of TMA, and to use this information to initiate specific therapy in a timelier manner.

This study was approved by the Institutional Review Board at University of Arkansas for Medical Sciences (UAMS). All 86 consecutive patients with suspected TMA between May 2013 and January 2021 were included in the study. These patients typically presented to the emergency room or clinical services with one or more symptoms including fever, neurological impairment, renal impairment and gastrointestinal symptoms. A provisional diagnosis of TMA was based on the presence of thrombocytopenia and microangiopathic hemolytic anemia at initial work-up (complete blood count and peripheral blood smear). Once a provisional diagnosis of TMA was made by the clinical team, transfusion medicine specialists were consulted to perform TPE for possible aTTP while waiting for additional testing results including ADAMTS13 activity and inhibitor levels, complement levels and mutations involving complement factors (aHUS genetic panel), DIC panel, serum haptoglobin, comprehensive metabolic panel, liver function tests, ANA, lupus anticoagulant panel, antiphospholipid antibodies, viral serology. Ethical approval was obtained from the institutional review board to perform HLA typing on blood obtained for routine clinical care after all diagnostic testing had been performed. HLA typing was performed using either rSSO-PCR (LabType®,OneLambda®) or NexGen Sequencing (TruSight® HLA v2, Illumina®) or both. PLASMIC score was calculated based on the study by Bendalapudi et al. (2017).5

While information and testing were gathered prospectively, the overall data analysis was performed retrospectively. Patients were sorted into three groups based on laboratory results. Patients with low ADAMTS13 activity (≤10) and presence of ADAMTS13 inhibitor were grouped as aTTP (33 patients) based on the International Society on Thrombosis and Haemostasis (ISTH) guidelines.13 Patients with complement factor mutations were grouped as aHUS (13 patients). The remaining patients were grouped as miscellaneous (secondary TMA, 40 patients) and included patients with SLE, scleroderma, dermatomyositis, sepsis, DIC, underlying malignancy, end stage renal disease, malignant hypertension, drug-induced TMA, HELLP syndrome, deceased donor transplant recipients, and hematopoietic cell transplant recipients. The study population is shown in Table 1.

The HLA allele frequencies (observed and expected) were determined for all patients in each TMA group. Briefly, the observed allele frequency was the actual number of occurrences of the specific allele in the current study population. The expected HLA frequencies based on the race (African Americans and Caucasian) were obtained as reported by the United Network for Organ Sharing (UNOS) (https://unos.org/wp-content/uploads/CPRA_frequencies.xls). The UNOS data are felt to accurately reflect the distributions of HLA types in the US population based on race/ethnicity. However, the racial/ethnic distribution of the current cohort varies in each TMA category and differs significantly from those of the general US population and shows an over-representation of African Americans (Supplemental Table 1). Additionally, African American patients are highly overrepresented in aTTP cohorts in the United States.14 Therefore, the expected allele frequencies for all patients in each TMA category were adjusted to accommodate the differences between this patient population and the general US population by race/ethnicity.15 Briefly, the expected allele frequency for a particular HLA allele was calculated by adjusting the known race/ethnic frequency of the specific HLA allele with the race/ethnic frequency found in the population of this study. The observed HLA allele frequencies were then compared with the expected HLA allele frequencies as percentages for each group. The observed versus expected allele frequencies for individual races in each group were also compared to determine the impact of individual races on disease association. Chi-square analyses were performed for samples with larger numbers (>20), and Fisher Exact analyses were performed with smaller sample sizes (≤ 20). The p-values were calculated using Microsoft Excel®, and although a p-value <0.05 is considered clinically significant, a more stringent p-value (≤0.01) was used for determining an association with specific HLA types.

Only a few prior studies have described HLA associations in aTTP.9-12,16 These studies compared the HLA associations in patients with aTTP to control populations. These prior studies were primarily performed with Caucasian populations with one study being carried out in the Japanese population. In comparison, the current study consists of both Caucasian and non-Caucasian subjects, with an overrepresentation of African American subjects. An overrepresentation of African American subjects has been previously reported by the aTTP registry in the United States.14 A recent study noted that race affects overall relapse risk and response to rituximab in aTTP (Chaturvedi et al.17), further emphasizing the importance of the current study for determining HLA associations in TMA in the United States. In addition, this study included other (non-aTTP) TMA patients in an effort to identify any unique HLA associations that would aid in the differential diagnosis of TMA.

Prior studies have shown an association of HLA-DRB1*11 with autoimmune diseases such as systemic sclerosis, juvenile chronic arthritis, and sarcoidosis.18-20 An increased incidence of HLA-DRB1*11 was also noted in aTTP patients in the European population (Scharrer et al., Scully et al., Sinkovits et al., Coppo et al.),9-12 although Sakai et al.16 did not see this trend in the Japanese population. An increased incidence of HLA-DQB1*03:01 has also been reported in prior studies (Scharrer et al., Scully et al., Sinkovits et al.),9,10,12 although the results did not reach statistical significance in the study by Scharrer et al.9 Scully et al.10 further suggested that the incidence of HLA-DRB1*11 is increased in aTTP due to it being in linkage-disequilibrium with HLA-DQB1*03:01.10,11 Scully et al. reported that 27.6% of aTTP patients were HLA-DQB1*03:01 positive but HLA-DRB1*11-negative, suggesting that HLA-DQB1*03:01 plays the dominant role in disease pathogenicity, while HLA-DRB1*11 is merely present due to its linkage-disequilibrium association with HLA-DQB1*03:01. The results of this study show similar findings with increased HLA-DRB1*11 and DQB1*03:01/19 allele frequencies and HLA-DRB1*11/DQB1*03:01/19 haplotype frequency in aTTP patients as compared with other TMA. Similar to previous studies, a subset of patients had HLA-DQB1*03:01/19 without HLA-DRB1*11 in the current cohort. This was seen in African American patients (7 of 11 patients expressed HLA-DQB1*03:01/19 without HLA-DRB1*11) while all of the Caucasian patients expressed both HLA-DQB1*03:01/19 and HLA-DRB1*11 (Supplemental Table 2). To further elucidate the role of these alleles/haplotypes, the PPV (Table 6) was calculated for the presence of individual alleles [HLA-DRB1*11 (69%), HLA-DQB1*03:01/19 (68%)], as well as the HLA-DRB1*11/DQB1*03:01/19 haplotype (67%) and were found to be similar to that of the PLASMIC score (69%). Combining the presence of HLA-DRB1*11 and HLA-DQB1*03:01/19 with a PLASMIC score of 6–7 in patients with aTTP allowed for a higher PPV (90%). Interestingly, the evaluation of the HLA-DQB1*03:01/19 allele in patients with aTTP and a PLASMIC score of 6–7 provided a PPV of 93%. Perhaps the presence of HLA-DQB1*03:01/19 is the most important HLA association with aTTP, in agreement with Scully et al. Thus, combining PLASMIC score with specific HLA alleles helps in distinguishing aTTP from other TMA.

It was also of note that none of the current patients with aHUS showed the presence of the HLA-DRB1*11/DQB1*03:01/19 haplotype, and thus the absence of this haplotype may be useful in differentiating aHUS from aTTP, where its presence correlates with aTTP.

Sakai et al. observed an increased incidence of HLA-DRB1*08:03 along with HLA-DRB1*08:03/DRB3/4/5*blank/DQA1*01:03/DQB1*06:01 in patients with aTTP.14 This haplotype and the HLA-DRB1*08:03 allele appear to be unique to the Japanese population, since none of the other studies noted this association. In the current cohort, a statistically significant increase in frequency of HLA-DRB1*08 was observed in aTTP patients, but none of these patients had HLA-DRB1*08:03. Six patients had HLA-DRB1*08:04 (one patient was homozygous) and one patient had HLA-DRB1*08:06. An increased incidence of HLA-DRB1*08/DQB1*06 was not observed either. No such trend was noted in other TMA groups. HLA-DRB1*08 commonly associates with HLA-DQB1*03:01/19 particularly in the African American population. In this study, 7 of 33 patients (all African American) with aTTP expressed HLA-DRB1*08/DQB1*03:01/19. Only two of the 53 (also African American) non-aTTP TMA patients expressed HLA-DRB1*08/DQB1*03:01/19. This haplotype association with aTTP has not been described previously, but it is likely that HLA-DQB1*03:01/19 is the primary association and the presence of HLA-DRB1*08 appears to be due to its linkage disequilibrium with HLA-DQB1*03:01/19.

Similar to Scully et al.10 an increased incidence of HLA-DRB3 (DR52) was observed in aTTP patients of the current cohort. Since HLA-DR52 commonly associates with HLA-DRB1*11, the apparent increased incidence of HLA-DR52 observed in this study could be due to its linkage-disequilibrium with HLA-DRB1*11/DQB1*03:01/19 (HLA-DRB1*11 and DQB1*03:01/19 versus DR52: p-value = 0.032; HLA-DQB1*03:01/19 versus DR52: p-value = 0.619).

Similar to Scully et al.10 this study found that HLA-DRB4 (DR53) appears to have a protective association for aTTP due to its low occurrence in the patient population (less than expected in the general population), whereas it is present in non-aTTP patients as expected in the general population.

Sinkovits et al.12 reported a reduced incidence of HLA-DRB1*07/DQB1*02 in aTTP patients. This haplotype was not observed in any aTTP patients in the current study, thus, the presence of this haplotype probably rules out the presence of aTTP (NPV: 100%).

Other statistically significant associations reported by Sinkovits et al.12 i.e. (i) increased frequencies for HLA-DRB1*14, and DRB1*15, and (ii) decreased frequencies for DRB1*13 in aTTP patients, were not observed in the current cohort.

Scharrer et al.9 reported an increased association of HLA-DQB1*02:02 (20% in aTTP versus 1.2% in control group; p-value <0.001); this association was not found in aTTP patients in this cohort. However, an increased presence of HLA-DQB1*02:02 was found in patients with aHUS.

Sakai et al. reported increased frequencies for HLA-DQA1*01:03 and DQB1*06:03, and a decreased frequency for HLA-DRB5*01:01.16 No such associations were reported by other studies or observed in the current study.

In summary, patients with aTTP are more likely to express HLA-DRB1*08, HLA-DRB1*11, HLA-DQB1*03:01/19, and HLA-DRB3, either as individual alleles or the HLA-DRB1*11/DQB1*03:01/19/DRB3 haplotype. They are less likely to express the HLA-DRB1*07/DQB1*02/DRB4 haplotype. Combining HLA associations with PLASMIC score achieved higher PPV (90%) and NPV (100%). Based on these findings, we propose an algorithm (Figure 1) that includes calculating a PLASMIC score and performing rapid HLA typing at the time of initial presentation, while waiting for ADAMTS13 results.

Figure 1.

Proposed algorithm for work-up and treatment.

(0.31MB).

We recommend proceeding with TPE (and/or other alternate therapies i.e., caplacizumab, or recombinant ADAMTS13 therapy when available) in patients with a PLASMIC score of 6 or more. The presence of any predisposing and absence of protective HLA associations, noted on HLA typing further strengthens the likelihood of aTTP (combined PPV: 90%). Likewise, in patients with a PLASMIC score of <6, the absence of predisposing and presence of protective HLA associations further strengthens that aTTP is unlikely (NPV: 100%). Additional testing (complement levels, complement genetic testing etc.) should be performed in these patients if not already requested at initial presentation. In patients with a PLASMIC score of <6, but presence of predisposing and absence of protective HLA associations, it may be reasonable to treat as if it were aTTP until ADAMTS13 results are available. This algorithm allowed us to identify two additional aTTP patients for TPE that would have been missed based on using the PLASMIC score alone (<6). Now that therapeutic ADAMTS13 is available (ADZYMA, ADAMTS13, recombinant-krhn, Takeda®)21 for clinical use in cTTP, it is only a matter of time before it is more generally available and thus it becomes increasingly important not to miss the aTTP cases where PLASMIC scores may not lead to immediate treatment. Likewise, this algorithm allowed us to identify four additional non-aTTP TMA patients that would have undergone treatment for aTTP based on PLASMIC score (6–7) alone, when it may not have been the appropriate treatment.

There are a number of strengths and potential limitations of this study. Strengths of the study include (i) a study population comprising both Caucasian and non-Caucasian subjects consistent with the patient population found in the United States; (ii) inclusion of non-aTTP TMA subjects in the study to determine any unique HLA associations that could aid in the differential diagnosis of TMA; (iii) determining PPV and NPV of the identified associations and comparing them with other indicators (PLASMIC score). Further, the study results are similar to previously published reports. Potential limitations include the small sample size, however, given the overall low incidence of TMA, it is difficult to enroll large number of patients at a single institution. Multi-institution studies are needed to further elucidate the role of HLA associations in TMA.

This study supports the previously identified HLA associations with aTTP, namely increased frequencies of HLA-DRB1*11, HLA-DQB1*03:01/19, HLA-DRB1*08 and HLA-DRB3, and decreased frequencies of HLA-DRB4, HLA-DRB1*07 and HLA-DQB1*02. In addition, combining the presence of HLA-DRB1*11/DQB1*03:01/19 and absence of HLA-DRB1*07/DQB1*02 with the PLASMIC score gives higher PPV and NPV for identifying aTTP, distinguishing it from other types of TMA, and initiating definitive therapy. Other novel findings of this study include (i) increased incidence of HLA-DQB1*02:02 and absence of HLA-DRB1*11/DQB1*03:01/19 in aHUS patients; (ii) presence of HLA-DRB1*07/DQB1*02 does not confer protection against the occurrence of other TMA as it does for aTTP.

Soumya Pandey: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. Akul Shrivastava: Formal analysis. Yanping Izak Harville: Formal analysis. Michele Cottler-Fox: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. Terry O. Harville: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.