Citations

Abstract Background Drugs use during pregnancy is a major social and medical issue, which may lead to significant pre- and post-natal complications, such as preterm birth and newborn mortality. Exposed newborns may have long-term behavioral, cognitive, and developmental problems. Accurate detection of in utero drug exposure is crucial for timely medical intervention for the newborn and the mother. Meconium is the ‘gold standard' matrix for detection of drugs in newborn which reflects drug exposure during pregnancy. This study aims to develop and optimize a clinical assay for simultaneous screening of 21 drugs in meconium using a custom biochip array. Methods Custom biochip array (Randox Laboratories Ltd.) included 21 discrete test regions (DTRs) for amphetamine, methamphetamine, opioids/opiates (targeting morphine, oxymorphone, oxycodone, hydrocodone, 6-monoacetyl morphine, tramadol, buprenorphine, fentanyl, and methadone), phencyclidine (PCP), cocaine (targeting benzoylecgonine), benzodiazepines (targeting oxazepam, lorazepam, and clonazepam), zolpidem, barbiturates (targeting phenobarbital), ethyl glucuronide, methylphenidate, and marijuana metabolite (targeting Delta-9-Carboxy-Tetrahydrocannabinol [THC-COOH]). Patient samples were obtained from the residual meconium samples that had been previously used for other tests. Blank meconium samples were spiked at in-house cutoff, negative and positive assay control levels. All samples were extracted in specimen diluent using Biotage® Lysera and centrifuged. The supernatant was analyzed on a fully automated Randox Evidence+® Analyzer. A robotic arm pipetted 60 µL sample on to a biochip and then the analyzer performed a competitive chemiluminescent immunoassay. The results were generated as relative light units (RLUs). Results The sample results were determined to be “positive” or “negative” based on average RLU of cutoff controls for each analyte on an assay. The intra-assay (CV ≤ 15%) and inter-assay (CV ≤ 18%) precision was 100% agreement for positive and negative controls and there was no observed carryover for any of the analytes. The sample recovery was excellent with minimal to no matrix suppression for all analytes. Accuracy was performed by comparing spiked analyte results from Randox Evidence+® Analyzer with the expected results and all the spiked samples matched (positive or negative). When authentic patient or spiked results were compared with external laboratory test results, some discordant results were obtained. However, the discrepancies could be explained based on the different cutoffs (e.g., the Randox assay had lower cutoffs) or the known assay cross reactivities within the analytes of same class. These deviations did not affect clinical utility of the assay. Conclusions We validated a novel and simple qualitative chemiluminescent immunoassay in meconium using a custom biochip array. Unlike other routine screening/ELISA methods, which require separate assays for detection of similar drug targets, the custom biochip array offers a convenient, rapid and efficient method that utilizes only a single sample preparation for the screening of all 21 drug targets. Therefore, this technology has potential to be utilized as high-throughput screening assay. Like all qualitative assays, the limitation of this test is that all positive results will need to be assessed quantitatively for a definitive interpretation.

Abstract Background Live cell-based assays (CBA) are considered the gold-standard methodology for detecting pathogenic antibodies targeting neural cell surface antigens. However, the adoption of these methods in clinical laboratories has been limited by their manual nature and low throughput. Here, we describe the development and validation of an automated system utilizing a live flow cytometry-based CBA to detect AQP4-IgG. Establishing AQP4-IgG serostatus is a critical component of the diagnostic criteria for Neuromyelitis optica spectrum disorders (NMOSD) as it enables the differentiation of NMOSD from Multiple Sclerosis where there may be significant clinical overlap. The accurate diagnosis of the correct disease state is vital, as the prognosis and treatment approach differ significantly for these two conditions. Two redundant systems were built that automatically receive reagents (live cells in suspension, buffers, diluents, secondary antibodies, and patients’ samples) and generate flow cytometer ready 96-well plates (each containing up to 45 serum or CSF samples tested in duplicate). Methods We assessed the analytical performance of an AQP4-IgG live flow cytometry-based CBA on these new automated systems. We measured intra- and inter-assay imprecision at three levels in 5x5 format and for end-point titer assessment, accuracy (20 positive and 20 negative sera; 5 positive and 5 negative CSF; established on the current manual assay), reference range (20 negative sera and 20 negative CSF from disease controls), analytical sensitivity (LOB and LOD) and specificity (high IgG containing serum specimens), within-plate draft (1 positive sample near the diagnostic cut-off [IgG-binding index of 2.0] that was tested across the entire plate), instrument to instrument correlation (42 positive samples/dilutions tested simultaneously on both systems), and total throughput for both CSF and Serum. Results Imprecision testing yielded the following results: Serum Intra/Inter precision level 1 (IBI = 2) CV% (current method:4.6%/20.7%), (system 1: 3.1%/18.4%), (system 2: 2.6%/22.5%), serum Intra/Inter precision level 2 (IBI=4) CV% (current method:4.9%/23.3%), (system 1: 3.2%/21.9%), (system 2: 2.6%/24.1%), and serum Intra/Inter precision level 3 (IBI =10) pos CV% (current method:6.0%/31.1%), (system 1: 3.8%/27.4%), (system 2: 4.2%/29.4%), and CSF Intra/Inter precision (IBI =2) CV% (System 1: 11.7%/16.8%), (system 2: 6.1%/10.7%). The median end-point titers for all four samples assessed matched within one end-point titer. For accuracy, 100% qualitative agreement between current and both automated systems, and titration accuracy (5 positive serums, 1 positive CSF) all matched within one titer between current and both automated systems. All reference range samples were negative. LOB/LOD in serum (Current: 0.85/1.11), (System 1: 0.82/0.95), (system 2: 0.82/0.96) and CSF (Current: 1.06/1.52), (System 1: 1.02/1.38), (system 2: 1.02/1.64) were comparable. All high IgG samples were negative. Plate drift analysis showed improved whole plate %CV: (Current:6.52%), (system 1: 4.51%), (system 2: 3.46%). Instrument to instrument comparison utilizing linear regression indicated strong agreement across the two systems (slope = 0.93 and R2= 0.95). Assessment of throughput based on real-time timings indicated a maximum output of approximately >700 patient samples per 24hrs per system. Conclusions An automated system for performing live CBAs provides equivalent to superior analytical performance compared to pre-existing manual methods with improved testing capacity.

Abstract Background Myasthenia gravis (MG) is caused by disrupting the function of postsynaptic acetylcholine receptors (AChRs) at the neuromuscular junction. 85% of MG patients have autoantibodies targeting AChRs, while 6% of MG patients have autoantibodies targeting the muscle-specific receptor tyrosine kinase (MuSK). MuSK is located on the muscle membrane and is activated by the low-density lipoprotein receptor-related protein 4 (LRP4) upon the binding with ligand Agrin. Activated MuSK undergoes autophosphorylation and stimulates downstream signaling to cluster AChRs, which is important for the formation and maintenance of neuromuscular synapses. IgG4 antibodies that bind MuSK are thought to directly disrupt the ability of MuSK to cluster AChR. The gold standard methodology for MuSK antibody testing is radioimmunoprecipitation assay (RIA) using anti-human IgG secondary antibodies. Performing RIA methods in the clinical laboratory is a burden due to radioactive biohazard concerns and the analytical limitations of these assays. This study is to assess the analytical and clinical performance of a live cell-based flow cytometry assay as a potential replacement for the MuSK RIA. Methods HEK293T cells were transiently transfected with a vector co-expressing human MuSK protein and GFP. Patient sera were incubated with a mix of HEK293 cells (GFP-positive cells that express MuSK protein on the cell surface and GFP-negative cells that do no express MuSK) followed by incubation with anti-human IgG4 secondary antibody conjugated with alexa fluor 647 (AF647). An IgG binding index (IBI) was calculated for each sample as the ratio of the median AF647 fluorescence intensity (MFI) of the MuSK-expressing cells (GFP+) to the MFI of the non-MuSK expressing cells (GFP-). An arbitrary positive IBI cut-off of 2.0 was selected. A preliminary assessment of assay imprecision was performed for the flow cytometry assay, as well as a method comparison study to compare this assay to RIA utilizing a cohort of 130 (34 positive and 96 negative) residual samples previously tested by the gold-standard assay. 133 disease control samples were also tested to assess the clinical specificity of the flow cytometry-based assay. Results To assess the imprecision, eight samples with varying IBIs were tested with 5 replicates in each assay over five days. The coefficient of variation (CV) for intra-assay replicates ranged from 1% to 7% for all samples, while CV for inter-assay replicates ranged from 2% to 15%. Based on the 130 samples previously tested by RIA, the Positive Percentage Agreement (PPA) between these two assays was 76.5% and the negative Percentage Agreement (NPA) was 100%. Of the discordant samples (n=8), clinical information was available for only 1 sample (positive by RIA, negative by flow). This patient had a final non-MG diagnosis (ALS). All control samples were negative on the flow cytometry-based assay. Conclusions The live cell-based flow cytometry MuSK IgG4 assay demonstrated encouraging preliminary analytical performance that warrants further development and validation.

Abstract Background Laboratory identification of lupus anticoagulant (LAC) is critical for diagnosing antiphospholipid antibody syndrome, a common cause of unprovoked thromboembolic events and pregnancy morbidity. Commonly used clot-based assays for LAC include the dilute Russell’s viper venom time (DRVVT) and activated partial thromboplastin time (APTT), but these are susceptible to anticoagulant interferences. Despite standardization efforts, LAC interpretation remains challenging due to pre- and post-analytical complexity and limited expertise. This study explored the use of deep neural networks (DNN) to facilitate LAC diagnosis. Methods Retrospective data for LAC profiling with 13 features performed at Mayo Clinic between 2021 and 2022 was collected. The profiles of 7,202 patients were randomly divided into training (n=4608), validation (n=1153), and test cohorts (n=1441). Diagnostic outputs including LAC positivity (determined by DRVVT or APTT) and the presence of warfarin (WAR) and heparin (HEP), were confirmed by expert assessment. Three DNN architectures were developed and evaluated (Figure 1): (1) four single output DNN models with a domain knowledge driven selection of input features, (2) four single output DNN models using the same 13 inputs across all models, and (3) a multi-output DNN model. Model performance was evaluated using the F1 score and the index of balanced accuracy (IBA) for each output label. Results Architecture 1 achieved high diagnostic accuracy with IBA values of 0.989-1.000 for all four outputs and F1 scores of 0.945-0.991. Architecture 2 exhibited F1 scores of 0.902-0.973 and IBA values of 0.935-0.992. Architecture 3 achieved F1 scores of 0.933-0.967 and IBA values of 0.941-0.983. Conclusions All three architectures accurately classify LAC and common anticoagulation effects. The comparable performance of architectures 1 and 2 suggests that manual feature extraction is unnecessary. Given its relative simplicity and versatility, architecture 3 is the preferred choice for implementation in a clinical laboratory to standardize LAC diagnosis.

Abstract Background Beta-quantification (BQ) is the reference method for LDL-C but is not widely available. It is difficult, therefore, for clinical laboratories to independently assess the accuracy of their methods for either calculating or directly measuring LDL-C. Our goal was to investigate if an interrelationship between the tests in the standard lipid panel could be used to compare the performance of different LDL-C methods against BQ, specifically in samples with hypertriglyceridemia, a major cause of bias for LDL-C testing. Methods BQ results from Mayo Medical Labs (n=39,667) and the NIH (n=18,338) were used to identify a linear relationship by least-squares regression analysis between lipid panel test results and LDL-C to facilitate a statistical comparison between different LDL-C methods. Results It is well established that the number of VLDL particles increases as TG increases, because VLDL is the main carrier of TG. As a consequence, the ratio of LDL-C to non-HDL-C is inversely related to TG, which can be made linear by taking the square root of TG (Figure). Nearly identical regression equations were found for this relationship, using two different BQ datasets. When LDL-C was calculated by either Sampson equation, the LDL-C/non-HDL-C regression lines nearly overlapped with the one for BQ. In contrast, the Martin equation showed a positive bias with increasing TG, whereas the Friedewald equation showed a negative bias, consistent with past reports on their LDL-C biases with hypertriglyceridemia. In the UKBiobank, the Beckman direct LDL-C showed a positive bias for TG, which was confirmed in CAP proficiency test surveys. By simulation analysis, approximately 80 samples with high (>200 mg/dL) and low (<100 mg/dL) TG is statistically sufficient to assess if the LDL-C/non-HDL-C regressions lines of LDL-C methods differ from BQ. Conclusions The LDL-C/non-HDL-C ratio method is a simple way to examine LDL-C methods for bias on hypertriglyceridemic samples.

Abstract Background Calculated LDL cholesterol (LDL-C) is a standard component of the lipid panel and an important risk factor in managing atherosclerotic cardiovascular disease (ASCVD). Due to the assumptions in the derivation of the Friedwald formula, fasting (≥8 hours) and triglyceride levels ≤400mg/dL have long been recommended. More recent data have shown that in most cases fasting has minimal effect on results, leading to the endorsement of non-fasting lipid panels for routine evaluation of ASCVD risk in clinical practice guidelines. Furthermore, newer equations (e.g. Sampson-NIH) allow for more accurate estimation of LDL-C even in the presence of hypertriglyceridemia. Mayo Clinic has implemented the Sampson-NIH LDL-C calculation and removed fasting/non-fasting designation from lipid panel orders. We hypothesized that the change to fasting designation would allow more afternoon draws for routine lipid panels and that increased non-fasting collections may increase triglyceride levels, but that the Sampson-NIH equation would prevent bias in LDL-C estimation. In order to test these hypotheses, we analyzed patient data from 1 year prior and 1 year post-implementation. Methods Results of lipid panels performed for one year preceding (n=334,719) and one year after (n=381,804) removal of the fasting/non-fasting designation and implementation of Sampson-NIH equation were collected. Median, 10th, and 90th percentile of draw time, triglyceride, and LDL-C calculated by either Sampson-NIH or Friedwald formulas were compared by quantile regression. Results Draw times shifted post-implementation at the 10th percentile (7:06 vs. 7:10, p<0.0001), median (8:49 vs. 9:08, p<0.0001) and 90th (12:02 vs. 13:46, p<0.0001). No difference in median triglyceride measurement was observed between pre-and post-implementation (110mg/dL), but slight differences were observed in the 10th and 90th percentile values (60 vs 59mg/dL and 224 vs 229mg/dL, p<0.0001). No difference was observed in 10th, 50th, or 90th percentile LDL values when calculated by Sampson-NIH equation (56, 99, 153mg/dL); however, if the Friedwald formula is used, a slight shift is observed in the 10th and 50th percentile LDL values (54 vs. 53, 97 vs. 96; p<0.0001) but not the 90th (150mg/dL). Conclusions Changing to the Sampson/NIH formula for LDL-C and removing fasting vs. non-fasting designation from routine lipid panels had minimal effect on reported triglyceride and LDL-C values, while allowing increased flexibility in draw time and reporting of LDL-C on patients with triglycerides ≥400mg/dL. Patients with TG ≥400mg/dL represented 1.7% of the dataset overall, including 5,387 patients before the change in which LDL-C could not be reported and 6,697 patients in the year post-implementation for whom LDL-C was reported based on the Sampson-NIH formula. Using an equation that is robust in patients with elevated triglyceride levels and removing fasting requirements from routine lipid panels allows greater flexibility and convenience for patients while allowing for more even distribution of phlebotomy workload and reporting of LDL-C results for patients with hypertriglyceridemia without evidence of clinically significant bias in reported results.

Abstract Background Our institution is facing increasing demand for oncology testing that requires high quality DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue. The current DNA extraction workflow involves a time and labor-intensive manual process that limits our ability to accommodate increasing downstream clinical testing volumes. We evaluated the KingFisher (KF) Flex utilizing Autolys M Tubes and the MagMAX FFPE DNA/RNA Ultra Kit as a possible high-throughput, automated DNA isolation workflow option that would decrease hands-on time and be conducive to volume growth without the need for additional staff. Methods DNA from 52 FFPE tissue samples (n=24 unique cases previously extracted by the current “manual method”) were extracted using Autolys M tubes, the MagMAX FFPE DNA/RNA Ultra Kit, and the KF Flex (Thermo Fisher Scientific Waltham, MA) over 4 “automated method” runs. Method modifications to the published procedure were introduced over the runs to determine any effects on DNA quality/quantity. Timings were taken during each run to compare hands-on and total run time against that of the manual method. Precision experiments were performed by extracting 4 replicates of sample on a single run (intra-assay precision) and 2 samples from 2 cases over 2 runs (inter-assay precision). Three cases were processed using varying tissue input levels to assess input-yield correlation. DNA yield was measured using HS dsDNA Qubit (Thermo Fisher Scientific, Waltham, MA). A subset of samples was tested by digital droplet PCR (ddPCR) (n=10), chromosomal microsomal microarray (CMA) (n=1), and next-generation sequencing (NGS) (n=3). Variants and QC metrics of the KF DNA were compared to those of the manual method DNA. Results The average total DNA yield was 3% lower from samples extracted following the manufacturer recommended KF procedure compared to matched samples extracted using the manual method (n=28 samples from 23 unique cases). A CV of 2.8% was observed in an intra-assay experiment (n=4 replicates from 1 case) and 3.0% in an average inter-assay experiment (n=2 replicates from 2 cases). There was a direct correlation between the tissue input amount (4 amounts of varied tissue input) and the total DNA yield (n=3 samples). We observed concordant fractional abundance values for ddPCR samples and concordant variant detection for NGS and CMA samples. We did not see a significant difference in the quality metrics tracked for any of the downstream testing assays. Conclusions This evaluation demonstrated that, as compared to our manual method, the automated method resulted in comparable DNA yields and downstream assay results. The incorporation of this automation would significantly increase our FFPE DNA extraction capacity without requiring additional staff while reducing hands-on time per run by about six hours. We would also be able to reduce ergonomic hazards related to tube cap manipulation, eliminate use of hazardous reagents, and leverage the plate format to better integrate extracted DNA into our clinical sample preparation workflows. These operational benefits highlight the value of automating high-throughput workflows.

Abstract Background In complex automated clinical laboratory Next Generation Sequencing (NGS) workflows, numerous opportunities exist for contamination events to occur. For oncology testing applications, detection of these events is crucial for accurate results reporting. A contamination detection module (MICon) using microhaplotype (MH) regions and an in-house designed analysis model was developed for use in a NGS assay for myeloid neoplasms (NGSHM) [1]. Variant detection for NGSHM has a validated analytical sensitivity of 2% variant allele frequency (VAF). Gross contamination events can potentially cause erroneous false positive variant detection whereas true low VAF mutations may be masked and evade detection. The following study was performed to evaluate MICon module performance on samples processed over the course of a year. Methods MH regions contain highly conserved tandem single nucleotide polymorphisms (SNPs) with high global heterogeneity occurring within a 300-nucleotide span. From the work of Kidd et al [2], 27 MH regions covering 92 SNPs and spanning 16 chromosomes were selected for inclusion in the 47 gene NGSHM target-capture panel. Sequencing was performed on a NovaSeq 6000 and analyzed through an internal bioinformatics pipeline, which incorporates the MICon module. MICon uses a binary classification model incorporating VAFs from MH regions, number of MH genotypes, and the contamination estimation score from verifyBamID to compute a single value on a 0-100 scale. Scores <50 are classified as non-contaminated and scores ≥50 require further investigation. Results The dataset was comprised of 10,990 samples. A total of 10,232 patient cases (93.1%) had non-contaminated MICon scores <50. Control replicates accounted for 261 samples (2.4%). There were 497 patient cases (4.5%) with MICon scores ≥50. Of the 497 patient cases, 137 (27.6%) had undergone hematopoietic stem cell transplantation (HSCT) and 114 (22.9%) contained gross chromosomal abnormalities, representing iatrogenic or tumor biological factors. An additional 135 (27.2%) of cases were contaminated from laboratory processing errors, 45 (9.1%) occurred due to chemistry failures during run processing, and 66 (13.2%) had an undetermined cause for a high score, representing laboratory-related and unknown factors. Overall, the 135 laboratory processing errors detected accounted for 1.3% of patient cases analyzed by the laboratory. These cases were repeated, and the non-contaminated results were accurately reported. Conclusions Herein it was shown the implementation of MICon has improved patient safety over the course of a year. The 1.3% of patient cases identified as arising from laboratory processing errors were successfully reprocessed. While the overall rate of laboratory processing errors appears low, the absolute number can be significant in a high-volume test setting, despite reliance on highly automated processes. Value is added by MICon through identifying errors that could result in the release of inaccurate patient results. By detecting previously unrealized errors, MICon has become an invaluable asset to the NGSHM assay by enhancing patient laboratory testing safety. References: [1] Balan J, et al. MICon Contamination Detection Workflow for Next-Generation Sequencing Laboratories Using Microhaplotype Loci and Supervised Learning. J Mol Diagn. 2023;25(8):602-610. doi:10.1016/j.jmoldx.2023.05.001. [2] Kidd KK, et al. Selecting microhaplotypes optimized for different purposes. Electrophoresis. 2018;39(21):2815-2823. doi:10.1002/elps.201800092.

Abstract Background Hemoglobin S (HbS) causes sickling disorders. In the laboratory, confirmation of HbS in patient samples with varying percentages is essential. Assessment is routinely performed using capillary electrophoresis (CE) and/or high-performance liquid chromatography. Sickle solubility (SS) exploits decreased solubility of HbS under reducing conditions and is a confirmatory test. SS is unreliable with low HbS, elevated HbF, severe anemia, erythrocytosis, hyperglobulinemia, extreme leukocytosis, hyperlipidemia, or increased serum proteins. Infant samples commonly have low percentages of HbS, high HbF, and limited sample volume. Intact globin chain Mass Spectrometry (MS) is used to identify abnormal hemoglobin variants by detecting the mass change (normal α/β/γ mass =15127/15867/15996 amu), respectively). MS has potential advantages in sensitivity and efficiency over SS and requires lower input sample volume. Herein we compare the utility of MS versus SS for confirmation of HbS. Methods Twenty-three EDTA-anticoagulated blood samples containing low percentages of HbS were identified. SS was performed on 30μL washed packed cells (requires 200μL whole blood) per standard methods. Intact Quadrupole Time-of-Flight MS (Accurate-Mass Q-TOF LC/MS 6520, Agilent Technologies, California) was performed using 10μL whole blood sample in acetonitrile solution reagent and results were compared. HbS and HbF levels were assayed by capillary electrophoresis (Sebia, France) per standard methods. Results Select results are summarized in Table 1. SS detected HbS percentages to 4.8% when HbF was low but not 6% HbS when Hb F is high. MS showed no HbF interference and identified HbS peaks (at 15837 amu) down to 3.1%. HbS percentages <3.1 were undetected by both methods. Conclusions Overall, MS was superior to SS for confirming HbS, particularly in samples with low variant percentage and/or elevated HbF. MS is also optimal when sample volume is minimal, such as for infants. Percentages of HbS <3% require methods such as IEF or DNA sequencing for confirmation.

Abstract Background Alpha fetoprotein (AFP) is a circulating tumor marker utilized clinically to detect liver cirrhosis, liver cancer and testicular seminomas. AFP molecule contains one single N-glycosylation site, with highly variable glycan structures, resulting in diverse AFP glycoforms in circulating blood. The core fucosylation of AFP (AFP-L3) is a clinical biomarker to monitor and predict risks of liver cancer progression and recurrence. Clinical testing for AFP-L3 utilizes lectin-binding and gel-shift electrophoresis. We developed a novel method to measure AFP glycoforms, based on immune-enrichment and liquid chromatography with high resolution mass spectrometry (LC-HRMS). Methods Immune enrichment of AFP was achieved by anti-AFP antibody, immobilized to magnetic beads. After binding and enrichment, the magnetic beads were washed, AFP was eluted, and the samples were analyzed by LC-HRMS (Exploris 480 MS and Vanquish UHPLC, Thermo Fisher Scientific), using full scan, positive polarity acquisition mode. Chromatographic separation was performed on PLRP column (Agilent); flow rate 200 µL/min. The HRMS data were processed and deconvoluted with intact mass analysis workflow in Biopharma Finder 5.1 (Thermo Fisher Scientific) to derive the intact AFP masses. The method’s sensitivity and imprecision were assessed by replicate analysis of serial diluted patient serum samples. AFP and its associated glycoforms were matched and identified with an in-house developed bioinformatics workflow. The deconvoluted intact masses and the sum intensity of detected charged species for each AFP glycoform were used to quantify relative abundance of AFP glycoforms. Results The method specificity for AFP was confirmed by bottom-up analysis after immune-enrichment with observed peptide sequence coverage over 35%. The recovery of the immune enrichment was shown to be independent of the AFP glycoform compositions. The identified AFP glycoforms and their relative abundance were consistent among replicates between AFP concentration 100 ng/mL and 5000 ng/mL. Analysis of authentic serum specimens from patients with different chronic liver diseases and liver cancer (n=102), revealed multiple complex biantennary branched AFP glycan modifications, with different numbers of terminal sialic acid and core fucose. Four AFP glycoforms were identified in over 60% patient samples with elevated AFP concentrations. Although occurring consistently, relative abundance of these AFP glycoforms varied significantly among patients. Assessment of the AFP fucosylation and sialylation features suggested that the two are orthogonal processes. Clinical correlations suggested that fewer terminal sialic acids were associated with impaired liver functions, while the fucosylation was linked to inflammatory responses and presence of liver malignancy. Strong linear correlation (Spearman’s rs=0.952, N=35) was observed between AFP-L3% quantitated by the LC-HRMS method, and AFP-L3% determined by the lectin-binding based isotachophoresis assay (Wako Diagnostics). Discrepancies between the two methods were observed in specimens containing < 400 ng/mL of AFP, in which the LC-HRMS method detected only a single predominant glycoform. Conclusions We developed and evaluated the LC-HRMS method for profiling circulating AFP glycoforms in patients with chronic liver diseases and liver cancer. The detected AFP glycoforms and their relative abundance were used to establish glycan features, which can be further linked to cancer development, impaired liver function, and inflammation.