Citations

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 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 < 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.

ABSTRACTCavin‐4 was identified as a potential autoantigen for immune‐mediated rippling muscle disease (iRMD). To validate this, we developed and tested various immunoassays, including a cell‐based assay (CBA), cavin‐4 recombinant protein ELISA, and multi‐peptide ELISA. Among 19 iRMD patients, all exhibited muscle rippling, and 13 had percussion‐induced mounding. All immunoassays demonstrated clinical and analytical specificities greater than 95%. The protein ELISA had the highest sensitivity (94.7%) and specificity (99.9%), outperforming CBA (sensitivity 89.5%, specificity 99.6%) and the multi‐peptide ELISA (sensitivity 79.0%, specificity 97.2%). Our results suggest that the cavin‐4 protein ELISA is a promising tool for high‐throughput clinical testing in iRMD.

Abstract Humanity is facing an important existential threat—irreversible climate change caused by human activity. Until recently, most of the proposals to address climate change have downplayed or ignored the adverse impact of food systems, especially intensive animal agriculture. This is in spite of the fact that up to a third of global greenhouse gas production to date can be attributed to animal agriculture. Recent developments at COP28 have signaled that the tide is turning, however, and that food systems are becoming part of global discussions on climate change solutions. The pressing nature of irreversible climate change requires rethinking our food systems. To solve the climate change crisis, we propose transitioning to a predominantly plant-based diet, and phasing out intensive animal agriculture as diets shift, without increasing pastoral farming. We suggest that such transformations in global food systems can be accomplished largely through education and large-scale public information campaigns, removal of subsidies, taxation to account for externalized costs of animal agriculture, improved labelling of products, and various investment/divestment drivers. Better metrics and industry benchmarks involving food and agriculture-specific performance indicators that reflect food system sustainability will be important. Increased global awareness of these issues and a change in mindset (which will drive political will) also are needed. Our current trajectory is untenable, and we must begin to turn the ship now towards sustainable food systems and diets.

AbstractObjectiveTo describe the phenotypes, oncological associations, biomarker profiles, and outcomes across different age groups in patients with ANNA1 (anti‐Hu) autoimmunity.MethodsA retrospective review of patients with ANNA1‐IgG in serum/CSF between January 1, 2001, and December 31,2019 was performed. Patients were classified into three groups based on the age of symptom onset. Phage immunoprecipitation sequencing (PhIP‐Seq) and neurofilament light chain (NfL) measurements were done in patient sera/CSF with archived samples.ResultsOf 122 patients, 81 (66%), 20 (16%), and 21 (17%) patients belonged to older adults, young adults, and pediatric groups, respectively. Lung cancer and neuromuscular presentations were more common in older adults (p < 0.001), while limbic encephalitis and neuroblastoma were more common in pediatric patients (p < 0.005). Most young adults (75%) did not have cancer identified. Proportions of patients with a favorable response to immunotherapy were 20%, 30%, and 52% among older adults, young adults, and pediatric groups, respectively. PhIP‐Seq demonstrated significant enrichment for ELAVL4 peptides especially for amino acids 240–289, in the majority of samples evaluated (36/67, 54%). ZIC and SOX2 peptides were significantly enriched in those with central nervous system presentations. Serum NfL levels were elevated in patients with cancer and those with poor long‐term outcomes.InterpretationYoung adults with ANNA1 autoimmunity phenotypically resembled older adults but rarely had an underlying cancer. Pediatric patients frequently presented with limbic encephalitis and neuroblastoma and often responded favorably to immunotherapy. Distinct antigenic signatures may underlie differences in clinical presentations. Serum NfL levels may be a biomarker of poor long‐term outcomes in ANNA1 autoimmunity.

AbstractArtificial intelligence (AI) allows data analysis and integration at an unprecedented granularity and scale. Here we review the technological advances, challenges, and future perspectives of using AI for electro‐clinical phenotyping of animal models and patients with epilepsy. In translational research, AI models accurately identify behavioral states in animal models of epilepsy, allowing identification of correlations between neural activity and interictal and ictal behavior. Clinical applications of AI‐based automated and semi‐automated analysis of audio and video recordings of people with epilepsy, allow significant data reduction and reliable detection and classification of major motor seizures. AI models can accurately identify electrographic biomarkers of epilepsy, such as spikes, high‐frequency oscillations, and seizure patterns. Integrating AI analysis of electroencephalographic, clinical, and behavioral data will contribute to optimizing therapy for patients with epilepsy.