Mills, John R.

ABSTRACT Objective To (1) validate GAD65‐ELISA detection and quantification for type 1 diabetes mellitus and autoimmune neurological diagnoses, (2) correlate ELISA results (reference range < 5 IU/mL) with established radioimmunoprecipitation assay (RIA; ≤ 0.02 nmol/L), and (3) define ELISA clinical utility and pitfalls. Methods Serum performance for diabetes (FDA‐cleared, undiluted) was verified, and neurological laboratory‐developed serum and CSF dilution protocols were validated to extend the reportable range beyond > 250 IU/mL. ELISA and RIA values were correlated, including established neurological RIA cut‐offs (serum ≥ 20 nmol/L; CSF any positive). Results ELISA met analytical criteria (precision, accuracy, sensitivity, specificity, reference range) in serum and CSF and was clinically equivalent to RIA for autoimmune diabetes. Neurological ELISA cut‐offs were established at 10,000 IU/mL (serum) and 100 IU/mL (CSF). Precision was better below 10,000 IU/mL (CVs < 20%) than above (CVs 30.8% serum; 26.5% CSF). ELISA–RIA correlation and agreement was stronger below the neurological cut‐off (R 2 = 0.89) than above (R 2 = 0.36). Positive agreement for RIA‐defined neurological disease was 100% in serum and CSF; all serums were > 10,000 IU/mL. Clinical specificity was 97.5% in serum and 100% in CSF, exceeding reported RIA specificity. Screen results > 250 IU/mL spanned a wide range of dilution values; many were below the neurological cut‐off. Most patients with paired serum/CSF positivity showed elevated GAD65 IgG indices. Interpretation GAD65 ELISA and RIA have equivalent sensitivity for autoimmune diabetes and neurological testing, with higher specificity for ELISA. A serum cut‐off of 10,000 IU/mL is informative but requires clinical context, and dilution of screen > 250 IU/mL samples is essential for neurological interpretation.

ABSTRACT Background and Aims Chronic inflammatory demyelinating polyradiculoneuropathy ( CIDP ) is a common, treatable, autoimmune, neuropathy frequently misdiagnosed. The complex electrodiagnostic ( EDX ) criteria required for diagnosis are challenging to apply in routine practice. This study evaluates the effectiveness of a machine‐assisted EDX tool in real‐time identification of demyelinating nerve conduction studies ( NCS ) stipulated by 2021‐ EAN / PNS CIDP criteria in conjunction with an online CIDP clinical probability calculator. Methods We prospectively evaluated 100 consecutive patients with referral or EDX diagnosis of polyradiculoneuropathy beginning January 1, 2024. Fifty patients were included, each from Jacksonville and Rochester Mayo Clinics. Routine electromyography ( EMG ) reports were compared to a machine‐assisted support tool applying 2021‐ EAN / PNS CIDP EDX criteria to NCS assessing demyelination. The EDX ‐assistant performance was compared to the final clinical diagnosis and our previously reported online CIDP clinical prediction tool ( https://news.mayocliniclabs.com/cidp‐calculator/ ). Results Among 100 patients (60% male; median age 64), 30 had a final clinical CIDP diagnosis with 29 having intravenous immunoglobulin follow‐up; 27 (93%) improved and 2 (7%) stabilized. Routine EMGs reported demyelination in 14 of 30 (47%), with 46% sensitivity and 79% specificity. The EDX ‐assistant identified CIDP demyelination in 28 of 30 (93%), with 93% sensitivity and 57% specificity. The clinical calculator detected CIDP in 30 of 30 (100%) with 86% specificity, increasing to 94% after excluding false positives lacking demyelinating features on the EDX tool. Interpretation A real‐time machine‐assisted EDX support tool, used with a clinical web‐based calculator, streamlines CIDP assessment by improving standardized identification of 2021‐EAN/PNS CIDP demyelinating NCS criteria and aiding clinical decisions.

ABSTRACT Objective We sought to characterize the sixth most common finding in our neuroimmunological laboratory practice (tissue assay‐observed unclassified neural antibodies [UNAs]), combining protein microarray and phage immunoprecipitation sequencing (PhIP‐Seq). Methods Patient specimens (258; 133 serums; 125 CSF) meeting UNA criteria were profiled; October 2022–September 2023. Top‐ranking candidate antigens were validated in silico, by dual‐staining confocal microscopy, and ≥ 1 protein‐specific assay. Clinical data were reviewed. Results Among 21 patients, 11 autoantibodies were characterized (serum, 19; CSF, all 9 available). Autoantigens were CACNA1I, 1; CAMK2B, 2; CLIP2, 1; FMN2, 2; MAP1A, 2; MAP2, 5; NECAB1, 1; SNAP91, 3; SRCIN1, 1; SYNJ1, 1; SYT3, 2. Analytical validation was by confocal TIIFA (all), western blot (10/10 available), and cell‐based assay (5/5 performed). Clinical accompaniments were: encephalitis, 6; brainstem encephalitis, 2; encephalomyelitis, 2; cerebellar ataxia, 2; longitudinally extensive transverse myelitis (LETM), 2; sensory neuronopathy, 1; peripheral neuropathy, 4, and movement disorders, 2. Inflammatory MRI abnormalities were identified in 5/16 patients (31%) with CNS disorders: T2 signal change (2), LETM (2), leptomeningeal enhancement (1). Seven of 8 (88%) had inflammatory CSF (pleocytosis, 5 [median 25.5 cells, range 7–294]; elevated IgG index/synthesis rate, 4; CSF‐exclusive oligoclonal bands, 4). Six had paraneoplastic causation (lung cancer, 2; other, 4); 3 were postinfectious (1 each of COVID‐19, HSV‐1, and post‐Group A streptococcal infection). Of 9 immunotherapy‐treated patients, 5 improved. Interpretation UNAs are partly accounted for by a repertoire of diverse mostly intracellular synaptic antigens. Their characterization is expedited by protein arrays and PhIPSeq. Further individual studies are needed to assess them as disease biomarkers.

Abstract Background To develop and validate a sensitive live cell-binding assay using flow cytometry to detect a3ß4-ganglionic nicotinic acetylcholine receptor (gnAChR) antibodies for diagnosis of autoimmune autonomic ganglionopathy (AAG, a subset of autoimmune autonomic neuropathies). The current radioimmunoprecipitation assay (RIPA) method has high false positive rate and utilizes radioactivity. Methods HEK293 cells were transiently transfected to express human a3ß4-gnAChR subunits, along with NACHO and RIC3 chaperons, and GFP for detection. Transfected cells were treated with 1mM nicotine liquid for 18-22 hours prior to lifting cells for flow cytometry. The IBI (IgG Binding Index) was then calculated as the median fluorescence intensity (MFI) of AF647 of the a3ß4-gnAChR subunits expressing cells divided by the MFI of the AF647 HEK293 expressing cells. Humanized AChR-specific monoclonal antibody (mAb03) was used as a single-point calibrator. The cut-off index (COI) ratio is calculated by dividing the IBI obtained from a sample by the established IBI cut-off value of the mAB03 calibrator set by the assay. A ratio &gt;1 indicates a positive result, while a ratio below 1 is negative. The study tested sera from 83 Mayo Clinic patients suspected of having autoimmune autonomic ganglionopathy (AAG), with a total of 100 samples collected over several years (40 from patients with clinically confirmed AAG, and 60 from patients without AAG), all previously positive for a3-gnAChR antibodies by RIPA. Additionally, 130 control samples were included: 90 from healthy individuals, 22 with hypergammaglobulinemia, and 18 with systemic lupus erythematosus. Results Median RIPA a3ß4-gnAChR value among 40 AAG patient samples was 2.58 nmol/L (range, 0.06-29.1 nmol/L) and among 60 non-AAG patients was 0.14 nmol/L (range, 0.01-4.43 nmol/L). The mAB03 calibrator median IBI value across assays was 2.1 (range, 1.6-2.7). The COI ratio was calculated using the calibrated IBI values. Thirty-eight of 40 AAG patient samples were considered positive, resulting in median IBI of 3.10 (range, 1.29-6.71); sensitivity 95%. None of non-AAG patients and controls were considered positive; median IBI of 0.38 (range, 0.14-0.51); specificity 100%. The two negative AAG patient samples (IBI, 0.43 and 0.43) were from patients in remission (treated with immune suppressants), and had RIPA titers of 0.06 nmol/L and 0.74 nmol/L. Conclusion The a3ß4-gnAChR-IgG flow cytometry assay has high sensitivity and specificity for AAG-related a3-AChR antibodies. It was able to distinguish AAG patients from non-AAG patients and controls effectively. The flow cytometry assay’s cut-off index ratio effectively identifies AAG patients while remaining negative for non-AAG and control samples.

Abstract Objectives γ‐Aminobutyric acid B receptor (GABA B R)‐IgG (immunoglobulin G) is an intermediate‐risk paraneoplastic autoantibody often associated with seizures. We aimed to assess the clinical and oncological features of GABA B R‐IgG autoimmune encephalitis (AE) and evaluate the performance of antibody testing. Methods Patients testing positive for GABA B R‐IgG in serum/cerebrospinal fluid (CSF) at Mayo Clinic Neuroimmunology Laboratory were identified. Archived sera were retested by cell‐based assay (CBA) at 1:100 and 1:200 dilutions. A live‐cell flow cytometry–based assay (LCFBA) was developed and validated using archived sera and CSF. True positivity included patients with classic presentations of GABA B R‐IgG AE or oncological explanations for antibody presence. Results Eighty‐six patients (median age 63 years; 43 female) presented with classic presentations of GABA B R‐IgG AE: encephalopathy with prominent seizures ( n = 55), status epilepticus ( n = 23), and rapidly progressive dementia ( n = 8). In addition, 44 patients (33%) had a false‐positive result for GABA B R‐IgG characterized by non‐specific symptoms/alternate diagnoses. Malignancy was identified in 78% of true‐positive patients, predominantly small cell lung carcinoma (SCLC). Testing serum at 1:100 dilution on CBA and using tissue immunofluorescence assay (IFA) in serum and CSF improved the identification of true‐positive patients ( p < 0.001). CBA at 1:100 dilution performed better than conventional CBA (at 1:10 dilution, p < 0.001) and tissue IFA ( p = 0.031). An in‐house LCFBA showed 100% sensitivity and specificity in CSF, performing similarly to conventional CBA ( p = 0.125) in CSF, but better than tissue IFA ( p = 0.031). Furthermore, serum LCFBA performed better than conventional CBA ( p = 0.022) and tissue IFA ( p = 0.006). LCFBA had the highest diagnostic accuracy and was closely followed by CBA at 1:100 dilution. Significance GABA B R‐IgG AE often presents as encephalopathy with seizures or status epilepticus in the context of an underlying SCLC. Multimodal evaluation using tissue IFA and fixed CBA at higher dilutions improves detection of true cases. LCFBA performs very well as a diagnostic test with very high sensitivity and specificity.

Abstract Purpose: Germ cell tumors (GCTs) pose significant diagnostic challenges due to the limited sensitivity and specificity of current tumor markers. Hereby we utilize phage immunoprecipitation sequencing (PhIP-Seq) technique to develop a unique immunosignature panel (iSIGN) with high sensitivity and specificity to improve the diagnosis and differentiation of GCTs. Patients and Methods: Serum samples from patients with confirmed gonadal or extragonadal GCTs and controls were collected from Mayo Clinic repositories. Controls included benign testicular lesions, autoimmune diseases, neurodegenerative disorders, and other cancers. Samples were randomized into development and validation cohorts. PhIP-Seq identified antigen-autoantibody interactions, and enrichment scores were calculated to develop a biomarker panel distinguishing GCT from non-GCT cases. A second biomarker panel was developed to predict seminoma from nonseminoma cases. Results: A total of 427 serum samples were analyzed, including 150 from GCT patients and 277 controls. For our primary model to distinguish GCT cases (GCT-iSIGN), 24 peptides from 16 antigens were identified based on significant differential autoantibody binding enrichment in GCT patients (p &lt; 0.05), ≥2 peptides per antigen, and enrichment scores ≥ 2.5-fold. GCT-iSIGN was highly sensitive (93%) and specific (99%) for identifying GCT cases from controls with an area under curve (AUC) of 0.93 and 9% Unknown Case Rate (UCR). The secondary panel (Sem-iSIGN) included 17 peptides corresponding to 5 unique proteins with high specificity (93%), moderate sensitivity (65%) and AUC of 0.77 to distinguish seminoma from nonseminoma GCT cases. Conclusion: This study demonstrates the potential use of PhIP-Seq to identify unique immunosignature panels that can serve as reliable biomarkers for GCT. These panels address the limitations of traditional markers and other proteomic techniques. This immunosignature model represents a cost-effective, stable, and scalable approach to enhancing GCT diagnosis and management. Citation Format: M Bakri Hammami, Andrew Knight, Haidara Kherbek, Brian Costello, Silvana De Lorenzo, Bradley C. Leibovich, John C. Cheville, Yong Guo, Jessica Sagen, Janet E. Olson, Alicia Algeciras-Schimnich, Sean J. Pittock, John R. Mills, Surendra Dasari, Divyanshu Dubey. iSIGN panel identifies germ cell tumors via whole-proteome phage immunoprecipitation sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr B027.

ABSTRACT Objectives To investigate the value of cytokine, chemokine, and neurofilament light chain (NfL) concentrations in predicting relapse risk, chronic epilepsy, and functional impairment in LGI1 autoimmune encephalitis (AE). Methods Cytokines/chemokines (IL‐1‐beta, IL‐2, IL‐4, IL‐5, IL‐6, IL‐8/CXCL8, IL‐10, IL‐12p70, IL‐13, IL‐17A, GM‐CSF, TNF‐alpha, IFN‐gamma, CXCL9, CXCL10, CXCL13, BAFF) and NfL concentrations were measured in CSF and paired serum from LGI1‐AE patients evaluated at Mayo Clinic (01/2015–02/2024), using a multiplex immunoassay system (ELLA, Bio‐Techne) and correlated with clinical outcomes. A laboratory‐based cohort of LGI1‐IgG‐positive patients and control cohorts, including patients with mixed non‐inflammatory disorders (MNID), Alzheimer's disease (AD), and temporal lobe epilepsy (TLE) were analyzed. Results Forty‐four patients with LGI1‐AE were included; 29 (66%) were male, with a median age of 68.5 years (range, 8–85). Median time from symptom onset to CSF sampling was eight months (IQR, 3–17); 19/42 (45%) experienced a clinical relapse and 27% developed chronic epilepsy. Serum IL‐6, serum and CSF IL‐8/CXCL8, and IL‐17A were higher in LGI1‐IgG positive patients than MNID ( p < 0.05). TLE cytokine/chemokine profiles were similar to LGI1 AE; AD patients had lower serum IL‐6 and CSF IL‐8/CXCL8 ( p = 0.04; p = 0.01), and higher serum IL‐17A and GM‐CSF ( p = 0.004; p = 0.01) than LGI1‐AE. Higher CSF IL‐6 and IL‐8/CXCL8 in LGI1‐AE associated with clinical relapse ( p < 0.05) and higher CSF NfL associated with chronic epilepsy ( p = 0.01). Conclusion Elevations in IL‐6, IL‐8/CXCL8, and IL‐17A were identified in this LGI1‐AE cohort. CSF IL‐6, IL‐8/CXCL8, and NfL levels are potential prognostic biomarkers for risk of relapse and chronic epilepsy in LGI1‐AE.