Neurology Minute

In part one of this two-part series, Dr. Justin Abbatemarco and Dr. Divyanshu Dubey discuss the original patient cohort with occupational exposure, what motivated this line of research, and the key findings from the initial workup.  Show citation:  Hinson SR, Gupta P, Paramasivan NK, et al. Neural synaptic vesicle autoimmunity following aerosolized porcine neural tissue exposure: insights into autoimmune inflammatory polyradiculoneuropathy. EBioMedicine. 2025;122:106053. doi:10.1016/j.ebiom.2025.106053 Show transcript:  Dr. Justin Abbatemacro: Hello and welcome. This is Justin Abbatemacro. And I'm here with Divyanshu Dubey to discuss his article published in eBiomedicine, Neurosynaptic Vessel Autoimmunity Following Aerosolized Porcine Neural Tissue Exposure: Insight into Autoimmune Inflammatory Polyradicular Neuropathy. Dr. Justin Abbatemacro: Div is a professor of neurology at the Mayo Clinic, and we just finished our interview, which I would encourage everyone to check out. Div, maybe we could talk about the original cohort with this occupational exposure, what inspired you to do this work and then what did you find with that initial workup? Dr.  Divyanshu Dubey: As recounted in our paper, this story began in 2006 to 2008, when a group of swine abattoir workers developed a striking neurological syndrome. These people were previously healthy and suddenly developed severe neuropathic pain, tingling, and variable weakness. The localization stood out, these cases were initially identified by Dan Lachance, who characterized these patients having an autoimmune neuropathy, which was further phenotypically characterized by the work done by Dr. Dyck, calling these inflammatory polyradicular neuropathy based on their nerve root plexus and proximal nerve collisions. And interestingly, a lot of work done back then by Dr. Lennon showed these patients had a unique synaptic staining pattern suggesting there was an underlying antibody driving this disease process. So as I joined the neuroimmunology lab a few years ago, this was one of the areas I wanted to go back and study, not only to find this mystery biomarker which caused the disease in these patients, but also to try and understand how this can help. Dr. Justin Abbatemacro: Yeah. I think my takeaway is be curious, right? You hear the story, you see this pattern. Be curious and investigate, and it takes a team or a village to do it. Dr.  Divyanshu Dubey: 100%. So observation, communication between, as you said, a team or a village with like-minded, passionate individuals is one of the successes of many of our discoveries, not just this one in this biomarker space. Dr.  Divyanshu Dubey: So the technique we use for discovery of these biomarkers was called a phage display where we use the archive sera to test from these patients, the swine abattoir worker patients with autoimmune polyradicular neuropathy. And we ended up finding two dominant antigens, which was synaptophysin and GAP-43, which were present in majority of these cases. Dr. Justin Abbatemacro: Please come back and check out part two where we discuss the latest findings and maybe some non-occupational exposures. And check out the podcast. Thanks.  

In the second installment of this two-part series, Drs. Stacey Clardy, Ayush Gupta, and Kuntal Sen discuss the most practical testing approach to minimize both under‑ and over‑testing for these disorders. Show citation: Gupta A, Sahjwani D, Kahn I, Gombolay GY, Sen K. Monogenic Mimics of Neuroinflammatory Phenotypes in Children and Young Adults: An Evolving Landscape. Neurol Genet. 2025;11(6):e200326. Published 2025 Nov 25. doi:10.1212/NXG.0000000000200326 Show transcript:  Dr. Stacey Clardy: Hi, this is Stacey Clardy from the Salt Lake City VA in the University of Utah. For a two-part podcast series this week, I've been speaking with Ayush Gupta, from the University of Nebraska Medical Center, and Kuntal Sen, from Children's National Hospital in Washington, DC about monogenic disorders that mimic neuroinflammatory disease. There are a lot of them, and they are no doubt sitting in our clinics waiting to be recognized. Ayush, for the minute, once a neurologist starts suspecting one of these disorders, what's the most practical testing strategy to avoid both under and over-testing for these disorders? Dr. Ayush Gupta: I think the most practical strategy is to write down all the phenotypic symptoms that you think could be related, put that exact information into a genetic testing panel that will be suitable. Or, if possible, try to do a broader genetic testing such as whole genome sequencing, and make yourself equipped to be able to analyze the results that you get from the testing. Dr. Stacey Clardy: I hear you saying, at least when you're thinking about this, be a bit of a lumper. As we covered in the podcast, if we are going to pursue that genetic testing, it is absolutely critical that we share that list with the interpreting geneticist because that determines how they score variants and how they rate them as related or not. Please take a listen to that two-part podcast series, where we get into all these details. I walked away with a great framework on how to do better in terms of picking these disorders out. Again, the paper that accompanies the two-part podcast series is in Neurology Genetics. It's a comprehensive review and called Monogenic Mimics of Neuroinflammatory Phenotypes in Children and Young Adults in Evolving Landscape. Thank you, Ayush. Dr. Ayush Gupta: Thank you so much.

In the second installment of this two-part series, Drs. Stacey Clardy, Ayush Gupta, and Kuntal Sen discuss the most practical testing approach to minimize both under‑ and over‑testing for these disorders. Show citation: Gupta A, Sahjwani D, Kahn I, Gombolay GY, Sen K. Monogenic Mimics of Neuroinflammatory Phenotypes in Children and Young Adults: An Evolving Landscape. Neurol Genet. 2025;11(6):e200326. Published 2025 Nov 25. doi:10.1212/NXG.0000000000200326 Show transcript:  Dr. Stacey Clardy: Hi, this is Stacey Clardy from the Salt Lake City VA in the University of Utah. For a two-part podcast series this week, I've been speaking with Ayush Gupta, from the University of Nebraska Medical Center, and Kuntal Sen, from Children's National Hospital in Washington, DC about monogenic disorders that mimic neuroinflammatory disease. There are a lot of them, and they are no doubt sitting in our clinics waiting to be recognized. Ayush, for the minute, once a neurologist starts suspecting one of these disorders, what's the most practical testing strategy to avoid both under and over-testing for these disorders? Dr. Ayush Gupta: I think the most practical strategy is to write down all the phenotypic symptoms that you think could be related, put that exact information into a genetic testing panel that will be suitable. Or, if possible, try to do a broader genetic testing such as whole genome sequencing, and make yourself equipped to be able to analyze the results that you get from the testing. Dr. Stacey Clardy: I hear you saying, at least when you're thinking about this, be a bit of a lumper. As we covered in the podcast, if we are going to pursue that genetic testing, it is absolutely critical that we share that list with the interpreting geneticist because that determines how they score variants and how they rate them as related or not. Please take a listen to that two-part podcast series, where we get into all these details. I walked away with a great framework on how to do better in terms of picking these disorders out. Again, the paper that accompanies the two-part podcast series is in Neurology Genetics. It's a comprehensive review and called Monogenic Mimics of Neuroinflammatory Phenotypes in Children and Young Adults in Evolving Landscape. Thank you, Ayush. Dr. Ayush Gupta: Thank you so much.

Dr. Aaron Zelikovich discusses the utility of neurofilament light chain as a serum biomarker in peripheral neuropathy.  Show citation: Karam C. Clinical Utility of Serum Neurofilament Light Chain in Peripheral Neuropathy. Muscle Nerve. 2026;73(1):86-92. doi:10.1002/mus.70073 Show transcript: Dr. Aaron Zelikovich: Welcome to today's neurology minute. My name is Aaron Zelikovich, a neuromuscular specialist at Lenox Hill Hospital in New York City. Today, we will discuss a recent article on the utility of neurofilament light chain as a serum biomarker in peripheral neuropathy. It has been studied in other neurological diseases like ALS and multiple sclerosis, as in the 2024 study by Robert Fox et al, which highlighted the limitations of serum neurofilament light chain in patients with multiple sclerosis, since the elevation was inconsistent and tended to occur weeks after MRI changes, and was really only found to be helpful in certain clinical situations. The study we highlight today is a single-center retrospective study that highlights the opportunities and limitations of using serum neurofilament light chain as a biomarker to monitor treatment response and peripheral neuropathy. Serum neurofilament light chain has been shown as an indicator of neuronal injury in both central and peripheral nervous system disease that has been associated with axonal injury or degeneration. It is now commercially available. The authors in this study provide a real-world single-center retrospective study that looked at various forms of peripheral neuropathy over 12 months. Patients had to be evaluated and meet criteria for peripheral neuropathy with either genetic testing, nerve conduction studies, and/or clinical exams. Neuropathies included TTR amyloid, vasculitis, CMT, CIDP, GBS, and anti-MAG neuropathy. Patients with TTR amyloid who were treatment naive and had elevated serum neurofilament light chain showed a reduction in neurofilament light chain levels with treatment. Additionally, patients with CIDP who were treatment naive with elevated serum neurofilament light chain also showed a reduction in neurofilament light chain levels with treatment. All patients with idiopathic peripheral neuropathy had normal serum neurofilament light chain levels. However, serum neurofilament light chain can vary in patients based on age, if they have diabetes, renal dysfunction, and body weight. And this makes it really challenging to interpret it in an isolated setting. Serum neurofilament light chain is a new biomarker for peripheral neuropathies. It can be a supplemental tool in the appropriate clinical context. Future studies are needed to identify its potential to be used as a treatment response biomarker in neuropathies like CADP, GBS, and TTR amyloid. Thank you so much, and have a wonderful day. 

Dr. Tesha Monteith discusses the different forms of menstrual migraines.  Show transcript:  Dr. Tesha Monteith: Hi, this is Tesha Monteith with the Neurology Minute. Welcome to our series on headache medicine and women's health. I want to start off this series with a discussion on menstrual migraine. Menstrual migraine is considered more frequent, more severe, and is associated with most migraine-associated symptoms with the exception of aura. The pathophysiology is linked to the effects of estrogen withdrawal and the impacts on the trigeminal vascular system. Do check out a recent paper by Pan and colleagues published just in neurology in November showing a robust hypothalamic activation prior to the headache phase in patients with menstrual migraine compared to controls. Now, there are two forms of menstrual migraine recognized in the International Classification of Headache Disorders III. First is menstrually related migraine which consists of attacks that occurred during the perimenstrual window. That's day one of menses plus or minus two days and at least two of three menstrual cycles and during additional times outside of the window. Perimenstrual migraine attacks occur exclusively during the perimenstrual window and is much less common than menstrually related migraine. A key point is that there's a predictable timing with each cycle, yet the condition is still very much underdiagnosed. Advise your patients to use an e-diary to improve the diagnosis and hopefully reduce disability. This is Tesha Monteith. Thank you for listening to the Neurology Minute.