Willrich, Maria Alice V.

Abstract Background Certolizumab pegol (CZP) has been successfully used for the treatment of Crohn disease (CD); however, real-world data regarding the utility of CZP trough levels (CTLs) are lacking. We aimed to correlate CTL with CD outcomes and to determine frequency of CZP antibodies. Methods Retrospective evaluation of all CD patients on maintenance CZP with CTL obtained between 2016 and 2019. Outcomes included: median CTL, presence of anti-CZP antibodies, biochemical response (BR), clinical response (CR), radiologic response (RR), radiologic healing (RH), and mucosal healing (MH). Results Seventy-seven CD patients were included. Median CTL was 18.9 µg/mL (interquartile range, 7.6–35.4). Twenty-three patients (27.3%) had positive antibody levels, with lower median CTL compared to patients with no antibodies (0.0 vs 29.8; P < 0.0001). Median CTL levels were higher in patients with vs without CR (30.4 vs 10.3 µg/mL; P = 0.0015) and RR (29.6 vs 5.8 µg/mL; P = 0.006). CZP dosing at least every 2 weeks was associated with higher odds of achieving MH (odds ratio, 3.2; 95% confidence interval, 1.03–9.97). CTL resulted in change in clinical management in 62.7% of cases and presence of CMZ antibodies was associated with an odds ratio of 5.83 (95% confidence interval, 1.57–21.73) of change in management. Receiver operating characteristic curve and quartile analysis suggested that CTL >19 µg/mL is associated with increased rates of CR and RR. Conclusions Higher CTL was significantly associated with CR and RR. The rate of CZP antibodies was 27.3%. Our data suggest maintenance CTL of ≥19 µg/mL should be achieved in order to optimize outcomes in clinical practice.

Background Eculizumab, a monoclonal antibody targeting C5, is an effective treatment for complement-mediated thrombotic microangiopathy (CM-TMA), also known as atypical hemolytic uremic syndrome. Although lifelong therapy has been suggested, the optimal treatment schedule is unknown, while eculizumab discontinuation does not universally lead to relapse. Data evaluating risk factors associated with an increased risk of CM-TMA recurrence following eculizumab withdrawal are scarce. Prior to the eculizumab era, complement genetic studies have been used to assess morbidity and mortality in patients with CM-TMA. Our aim was to assess the impact of complement gene variants on CM-TMA relapse rate (RR) after eculizumab discontinuation. Methods Search protocols were developed for the Ovid and PubMed databases to identify existing reports on CM-TMA and eculizumab withdrawal published before February 1st 2020. Cases were cross-referenced to eliminate duplicates. Inclusion criteria included patients diagnosed with CM-TMA who had undergone eculizumab discontinuation. Reasons for exclusion were patients with no follow-up after eculizumab withdrawal and patients lacking complement gene testing. Patients undergoing eculizumab dose extension, but not discontinuation, were not included. Results Fifteen studies including 557 individuals were retrieved. Of these, 363 (65.2%) were excluded as outlined in Figure 1 and 194 cases were included in the final analysis with a global RR of 28.9% (n=56). Distribution based on gene impacted and variant type are presented in Table 1. RR was highest among patients with CFH variants (52.5% to 60%) -particularly if involving exon 22 or nonsense mutations-, MCP/CD46 variants (38.9% to 45%) -particularly if affecting splice regions-, and cases with multiple concomitant variants (57.1%) -particularly those including CFH or a CFH-CFHR1 Hybrid (Table 2). Patients with relapse were more likely to have the presence of a complement variant (p<0.001), history of previously resolved CM-TMA events (p=0.022), younger age (mean age 22.4 years for patients with relapse vs. 32.33 years for patients without relapse; p=0.002) and, within those with detected variants, multiple vs. single variants (p=0.002) and CFH-inclusive variants (p=0.003). On univariate analysis, complement gene variants (OR 4.217 95%CI 1.97-9.026; p<0.001), age <30 years (OR 2.346 95%CI 1.159-4.749; p=0.018), and presence of multiple variants (OR 2.06 95%CI 1.172-3.621; p=0.012) or CFH-inclusive variants (OR 3.111 95%CI 1.443-6.71; p=0.004) were associated with increased odds of CM-TMA relapse, while no prior history of additional CM-TMA events was the only factor associated with lower RR (OR 0.327 95%CI 0.123-0.87; p=0.025). Presence of complement variants (OR 4.48 95%CI 1.132-17.724; p=0.033) and CFH-inclusive variants (OR 3.045 95%CI 1.136-8.159; p=0.027) were independently associated with increased RR on multivariate analysis (Table 3). Conclusion Relapse after eculizumab discontinuation is rare in cases with no genetic variants identified but can increase to more than 80% in high-risk subgroups. Complement genetic testing is not required for CM-TMA diagnosis or for initiation of complement inhibiting therapy; however, our results demonstrate the value of complement genetic testing when stratifying risk of patients for consideration of eculizumab discontinuation. Disclosures Sridharan: Alexion: Honoraria.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX has advantages including increased sensitivity, specificity, and the ability to distinguish therapeutic monoclonal antibodies. Herein, we report the laboratory characteristics and distribution of diagnoses of patients tested clinically at Mayo Clinic. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. We identified 9195 unique patients with MASS-FIX performed between 7/24/2018 and 3/6/2020. Seven-thousand nine hundred and forty-six patients provided consent for study enrollment, and 7689 had data available on index diagnosis. Given considerable variability in the interpretation of diagnostic criteria for light chain (LC) MGUS, patients with this diagnosis (1360, 18%) were excluded. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). Results: The final cohort consisted of 4118 patients with a positive MASS-FIX and 2211 patients with a negative MASS-FIX, all in the setting of underlying PCDs. Figure 1 illustrates the numbers and percentages of patients who are MASS-FIX positive versus MASS-FIX negative by diagnosis. MGUS and multiple myeloma (MM) were the most common diagnoses overall, and both were more common in the MASS-FIX positive cohort. More than 90% of patients with Waldenstrom's macroglobulinemia (WM), smoldering WM, smoldering MM, and cold agglutinin disease were positive by MASS-FIX. For MASS-FIX positive patients, IgG isotype was identified in 2575 patients (63%), IgA in 703 (17%) and IgM in 710 (17%). Bence Jones proteinemia was identified in 283 patients (7%) with lambda restriction being the most common (57%). 3625 patients (88%) had a monoclonal pattern, 228 patients (6%) had a bi-clonal pattern, and 7 (<1%) had a tri-clonal pattern. The majority of patients (58%) were kappa LC restricted by MASS-FIX, 222 (5%) had N-glycosylated LC, and 2 patients (<1%) had a heavy chain with no light chain. Conclusions: This single institution experience illustrates the practicality of MASS-FIX in detecting and following monoclonal proteins for a wide range of PCDs in a tertiary center. In this cohort, the percentage of patients who were MASS-FIX positive varied by diagnosis, reflecting cross sectional sampling of patients throughout their disease course. Disclosures Gertz: Research to Practice: Other; Springer Publishing: Patents & Royalties; Aurora Bio: Other; Johnson and Johnson: Speakers Bureau; Sanofi: Other; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Proclara: Other; DAVA oncology: Speakers Bureau; Celgene: Other; Teva: Speakers Bureau; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau. Kumar:AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Genecentrix: Consultancy; Adaptive Biotechnologies: Consultancy; Novartis: Research Funding; MedImmune: Research Funding; Sanofi: Research Funding; Tenebio: Other, Research Funding; Cellectar: Other; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments. Kapoor:Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Cellectar: Consultancy; Janssen: Research Funding; Celgene: Honoraria. Dingli:Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Alexion: Consultancy; Sanofi-Genzyme: Consultancy; Janssen: Consultancy; Apellis: Consultancy; Millenium: Consultancy. Lin:Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Gamida Cells: Consultancy; Takeda: Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Alnylam, Intellia, Janssen, Takeda, Pfizer, Prothena, Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced standard gel-based immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX can readily identify N-glycosylation of involved light chains (LC N-glycosylation) by its unique, polytypic spectral pattern. LC N-glycosylation is identified more commonly in light chain amyloidosis (AL) than other plasma cell disorders (PCDs), and is associated with an increased risk of progression from MGUS to both AL and other PCDs (Dispenzieri et. al. Leukemia 2020). Herein, we report the mass spectral characteristics and distribution of diagnoses among 222 patients with LC N-glycosylation detected during a 20 month period in our clinical lab. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. 9195 unique patients had MASS-FIX performed from 7/24/2018 to 03/06/2020. Inclusion criteria for this retrospective study included: 1) consent for record review; 2) a monoclonal protein identified on MASS-FIX; 3) an underlying PCD. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). The final positive cohort consisted of 4118 patients with definitive monoclonal proteins on MASS-FIX. Results: Two-hundred and twenty-two (5%) of the 4118 patients with a positive MASS-FIX had LC N-glycosylation. 202 patients (91%) had FLC assays performed. Of these, 110 (54%) were kappa LC restricted, 22 (11%) were lambda restricted, and 70 (35%) were normal. A quantifiable M-spike was identified in 110 patients (85%) of 129 patients who had serum protein electrophoresis performed. By MASS-FIX, 139 patients (63%) had an IgG isotype, 18 (8%) an IgA, and 55 (25%) an IgM. Two of these patients had a bi-clonal pattern in which both IgG kappa and IgM kappa LCs were N-glycosylated. 12 patients (5%) had monoclonal light chains with no corresponding heavy chain. Overall, 173 (78%) of 222 patients were kappa LC restricted and 44 (22%) were lambda. 189 patients (85%) had a monoclonal pattern, 18 (8%) had a bi-clonal pattern, and 3 (1%) had a tri-clonal pattern. The most common PCD diagnoses for the 222 patients with LC N-glycosylation were MGUS (45%), multiple myeloma (MM) (31%), and immunoglobulin light chain amyloidosis (AL) (8%). The percentage of MASS-FIX positive patients with LC N-glycosylation by diagnosis, stratified by kappa and lambda LC restriction, is illustrated in Figure 1. Cold agglutinin disease (CAD) had the highest relative percentage of patients with LC N-glycosylation, regardless of LC restriction. Eighteen AL patients (5%) had LC N-glycosylation; the percentage was higher in kappa restricted (13%) than lambda restricted AL patients (2%). Of note, LC N-glycosylation was not detected in patients with plasma cell leukemia, non-AL amyloidosis with associated MGUS, POEMS Syndrome or Castleman's Disease in this cross sectional sampling of patients. Conclusions: This retrospective study demonstrates that 5% of patients in a routine clinical setting with positive MASS-FIX have glycosylated LCs. Consistent with prior observations, CAD had the highest relative percentage of LC N-glycosylated patients. The percentage of AL patients with LC N-glycosylation in this cohort is lower than previously reported for newly diagnosed AL patients (Kumar et. al. Leukemia 2019), which is not surprising given that the current cohort study is a cross sectional evaluation of patients at various stages of diagnosis and treatment rather than a prevalence study. Further study will be done to exclude the presence of latent AL in patients with N-glycosylated LC and diagnoses of MGUS, SMM, MM, and Waldenstrom's macroglobulinemia. Disclosures Gertz: Springer Publishing: Patents & Royalties; Proclara: Other; DAVA oncology: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Teva: Speakers Bureau; Sanofi: Other; Research to Practice: Other; Celgene: Other; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Aurora Bio: Other. Kumar:Adaptive Biotechnologies: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Carsgen: Other, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Merck: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Cellectar: Other. Kapoor:Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria; Cellectar: Consultancy. Dingli:Alexion: Consultancy; Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Apellis: Consultancy; Rigel: Consultancy; Millenium: Consultancy. Lin:Janssen: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Intellia: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Alnylam: Research Funding.

Abstract Objective Regulations for clinical laboratories in the United States are complex. The goal of this review is to improve the clarity of laboratory-developed test (LDT) regulation to facilitate innovation. Methods A literature and regulation review of current legislation for compliance by U.S. clinical laboratories was performed, and examples of the steps to implement LDTs within compliance with the regulatory environment are shared. Results Many federal and state jurisdictions are critical to the functionality of a laboratory in addition to upcoming potential promulgation of the Verifying Accurate Leading-Edge IVCT Development Act. Increased regulation, although imperative to maintain consistent, high-standard clinical care, could mean additional costs for developers and healthcare while also hindering innovation. Conclusion An extensive discussion of proposed regulations for LDTs needs to occur. Laboratory testing requires the sustained use of innovative methods at a cost that will permit continued, timely, uninterrupted high-quality service.

Abstract Objectives A matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) method (Mass-Fix) as a replacement for gel-based immunofixation (IFE) has been recently described. To utilize Mass-Fix clinically, a validated automated method was required. Our aim was to automate the pre-analytical processing, improve positive specimen identification and ergonomics, reduce paper data storage and increase resource utilization without increasing turnaround time. Methods Serum samples were batched and loaded onto a liquid handler along with reagents and a barcoded sample plate. The pre-analytical steps included: (1) Plating immunopurification beads. (2) Adding 10 μl of serum. (3) Bead washing. (4) Eluting the immunoglobulins (Igs), and reducing to separate the heavy and light Ig chains. The resulting plate was transferred to a second low-volume liquid handler for MALDI plate spotting. MALDI-TOF mass spectra were collected. Integrated in-house developed software was utilized for sample tracking, driving data acquisition, data analysis, history tracking, and result reporting. A total of 1,029 residual serum samples were run using the automated system and results were compared to prior electrophoretic results. Results The automated Mass-Fix method was capable of meeting the validation requirements of concordance with IFE, limit of detection (LOD), sample stability and reproducibility with a low repeat rate. Automation and integrated software allowed a single user to process 320 samples in an 8 h shift. Software display facilitated identification of monoclonal proteins. Additionally, the process maintains positive specimen identification, reduces manual pipetting, allows for paper free tracking, and does not significantly impact turnaround time (TAT). Conclusions Mass-Fix is ready for implementation in a high-throughput clinical laboratory.

AbstractObjectivesFailure to produce sufficient quantities of functional α1-antitrypsin (AAT) can result in AAT deficiency (AATD) and significant comorbidities. Laboratory testing plays a vital role in AATD, with diagnosis requiring documentation of both a low AAT level and a mutated allele. This retrospective evaluation examines the efficacy of a liquid chromatography–tandem mass spectrometry (LC-MS/MS) (proteotyping)–based algorithm for AATD detection.MethodsA 16-month retrospective data analysis was performed on two cohorts: 5,474 samples tested with the proteotype-based algorithm and 16,147 samples directly tested by isoelectric focusing (IEF) phenotyping.ResultsLC-MS/MS reduced the rate of IEF testing by 97%. The 3% of cases reflexed to IEF resulted in 12 (0.2%) additional phenotype findings. Retrospectively applying the proteotype-based algorithm to the IEF cohort demonstrated a 99.9% sensitivity for the detection of deficiency-associated phenotypes. Most deficiency phenotypes missed by the proteotyping algorithm would come from heterozygous patients with an F, I, or P paired to an S or Z. In all of these cases, patient AAT levels were greater than 70 mg/dL, above the threshold for AAT augmentation therapy.ConclusionsThe proteotype algorithm is a sensitive and cost-effective approach for the diagnosis of clinical AAT deficiency.