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Ongoing biomarker development programs have been designed to identify serologic or imaging signatures of clinico-pathologic entities, assuming distinct biological boundaries between them. Identified putative biomarkers have exhibited large variability and inconsistency between cohorts, and remain inadequate for selecting suitable recipients for potential disease-modifying interventions. We launched the Cincinnati Cohort Biomarker Program (CCBP) as a population-based, phenotype-agnostic longitudinal study. While patients affected by a wide range of neurodegenerative disorders will be deeply phenotyped using clinical, imaging, and mobile health technologies, analyses will not be anchored on phenotypic clusters but on bioassays of to-be-repurposed medications as well as on genomics, transcriptomics, proteomics, metabolomics, epigenomics, microbiomics, and pharmacogenomics analyses blinded to phenotypic data. Unique features of this cohort study include (1) a reverse biology-to-phenotype direction of biomarker development in which clinical, imaging, and mobile health technologies are subordinate to biological signals of interest; (2) hypothesis free, causally- and data driven-based analyses; (3) inclusive recruitment of patients with neurodegenerative disorders beyond clinical criteria-meeting patients with Parkinson's and Alzheimer's diseases, and (4) a large number of longitudinally followed participants. The parallel development of serum bioassays will be aimed at linking biologically suitable subjects to already available drugs with repurposing potential in future proof-of-concept adaptive clinical trials. Although many challenges are anticipated, including the unclear pathogenic relevance of identifiable biological signals and the possibility that some signals of importance may not yet be measurable with current technologies, this cohort study abandons the anchoring role of clinico-pathologic criteria in favor of biomarker-driven disease subtyping to facilitate future biosubtype-specific disease-modifying therapeutic efforts.

The gold standard for a definitive diagnosis of Parkinson disease (PD) is the pathologic finding of aggregated α-synuclein into Lewy bodies and for Alzheimer disease (AD) aggregated amyloid into plaques and hyperphosphorylated tau into tangles. Implicit in this clinicopathologic-based nosology is the assumption that pathologic protein aggregation at autopsy reflects pathogenesis at disease onset. While these aggregates may in exceptional cases be on a causal pathway in humans (e.g., aggregated α-synuclein in SNCA gene multiplication or aggregated β-amyloid in APP mutations), their near universality at postmortem in sporadic PD and AD suggests they may alternatively represent common outcomes from upstream mechanisms or compensatory responses to cellular stress in order to delay cell death. These 3 conceptual frameworks of protein aggregation (pathogenic, epiphenomenon, protective) are difficult to resolve because of the inability to probe brain tissue in real time. Whereas animal models, in which neither PD nor AD occur in natural states, consistently support a pathogenic role of protein aggregation, indirect evidence from human studies does not. We hypothesize that (1) current biomarkers of protein aggregates may be relevant to common pathology but not to subgroup pathogenesis and (2) disease-modifying treatments targeting oligomers or fibrils might be futile or deleterious because these proteins are epiphenomena or protective in the human brain under molecular stress. Future precision medicine efforts for molecular targeting of neurodegenerative diseases may require analyses not anchored on current clinicopathologic criteria but instead on biological signals generated from large deeply phenotyped aging populations or from smaller but well-defined genetic-molecular cohorts.

We study thermal leptogenesis in realistic supersymmetric flipped SU(5) × U(1) unification. As up-type quarks and neutrinos are arranged in the same multiplets, they exhibit strong correlations, and it is commonly believed that the masses of right-handed (RH) neutrinos are too hierarchical to fit the low-energy neutrino data. This pattern generally predicts a lightest RH neutrino too light to yield successful leptogenesis, with any lepton-antilepton asymmetry generated from heavier neutrinos being washed out unless special flavour structures are assumed. We propose a different scenario in which the lightest two RH neutrinos N1 and N2 have nearby masses of order 109 GeV, with thermal leptogenesis arising non-resonantly from both N1 and N2. We show that this pattern is consistent with all data on fermion masses and mixing and predicts the lightest physical left-handed neutrino mass to be smaller than about 10−7 eV. The Dirac phase, which does not take the maximal CP-violating value, plays an important role in leptogenesis. [ABSTRACT FROM AUTHOR]

Background: Rare movement disorders often have a genetic etiology. New technological advances have increased the odds of achieving genetic diagnoses: next-generation sequencing (NGS) (whole-exome sequencing—WES; whole-genome sequencing—WGS) and long-read sequencing (LRS). In 2017, we launched a WES program for patients with rare movement disorders of suspected genetic etiology. We aim to describe the accumulated experience of a modern movement disorder genetic clinic, highlighting how different available genetic tests might be prioritized according to the clinical phenotype and pattern of inheritance. Methods: Participants were studied through WES analysis. Descriptive statistics, including the mean, standard deviation, counts, and percentages, were used to summarize demographic and clinical characteristics in all subjects and with each type of result [pathogenic or likely pathogenic, variants of uncertain significance (VUS), negative]. Results: We studied 88 patients (93.2% Caucasian, 5.72% African American, and 1.08% Hispanic or Latino). After excluding six family members from four index participants, the diagnostic yield of WES reached 27% (22/82 probands). The age at onset was significantly lower in patients with pathogenic/likely pathogenic variants. The most common clinical phenotypes were ataxia and parkinsonism. Dystonia, ataxia, leukoencephalopathy, and parkinsonism were associated with most genetic diagnoses. Conclusions: We propose a comprehensive protocol with decision tree testing for WGS and LRS, a return of results, and a re-analysis of inconclusive genetic data to increase the diagnostic yield of patients with rare neurogenetic disorders. [ABSTRACT FROM AUTHOR]

Dropped head syndrome (DHS) is characterized by severe forward flexion of the cervical spine due to an imbalance in neck muscle tone. This condition can be linked to various neuromuscular diseases, including myasthenia gravis (MG). On the other hand, Parkinson's disease (PD) patients may show a clinically indistinguishable picture named antecollis, which is caused by increased axial tone, but without muscle weakness. Differentiating between DHS and antecollis is crucial due to their distinct treatment requirements. We present the case of a 71-year-old White male with a one-month history of severe neck flexion, mild dysphagia, and dysphonia. His medical history included diabetes mellitus, coronary artery disease, arterial hypertension, and mild cervical spondylosis. Neurological examination revealed features of Parkinsonism, including hypomimia, asymmetric rigidity, and reduced arm swing. There was significant weakness in his neck extensor muscles, with no signs of ptosis or diplopia. Brain/spine MRI scans were unremarkable, but electromyography showed a reduced compound muscle action potentials amplitude in repetitive nerve stimulation, consistent with MG. High-titer acetylcholine receptor antibodies confirmed the diagnosis. Treatment with pyridostigmine (60 to 120 mg/day) and plasma exchange (daily, for five consecutive days) improved the patient's general condition and neck posture. Concurrently, the patient was diagnosed with PD based on established clinical criteria and improved with carbidopa/levodopa therapy (up to 150/600 mg/daily). This case highlights the rare co-occurrence of MG and PD, emphasizing the need for thorough clinical, neurophysiological, and laboratory evaluations in complex DHS presentations. Managing MG's life-threatening aspects and addressing PD symptoms requires a tailored approach, showcasing the critical role of neurophysiology in accurate diagnosis and effective treatment. [ABSTRACT FROM AUTHOR]

The article discusses the shift in the approach to initiating medication, particularly levodopa, in early Parkinson's disease (PD) patients. It emphasizes the importance of early dopaminergic treatment based on individual needs and preferences. The study explores a shorter combination of patient-reported items from the Movement Disorder Society-UPDRS scale to predict the initiation of dopaminergic therapy accurately. The findings suggest that patient-reported information at baseline can help predict relevant clinical outcomes, such as the timing of medication initiation, and may improve patient care and management in PD. [Extracted from the article]

The article "The Whistle-Smile Reflex in Parkinson's Disease: A Cross-Sectional Study" published in Movement Disorders Clinical Practice explores the absence of the whistle-smile reflex (WSR) in Parkinson's disease (PD) patients compared to healthy controls (HCs). The study involved video recordings of participants performing a whistle and assessing their immediate smile response. Results showed that 76.47% of PD patients did not exhibit a smile after whistling, indicating a potential diagnostic marker for PD. Further research is needed to validate these findings and explore the clinical implications of the WSR in PD diagnosis. [Extracted from the article]

Animal models have been used to gain pathophysiologic insights into Parkinson's disease (PD) and aid in the translational efforts of interventions with therapeutic potential in human clinical trials. However, no disease-modifying therapy for PD has successfully emerged from model predictions. These translational disappointments warrant a reappraisal of the types of preclinical questions asked of animal models. Besides the limitations of experimental designs, the one-size convergence and oversimplification yielded by a model cannot recapitulate the molecular diversity within and between PD patients. Here, we compare the strengths and pitfalls of different models, review the discrepancies between animal and human data on similar pathologic and molecular mechanisms, assess the potential of organoids as novel modeling tools, and evaluate the types of questions for which models can guide and misguide. We propose that animal models may be of greatest utility in the evaluation of molecular mechanisms, neural pathways, drug toxicity, and safety but can be unreliable or misleading when used to generate pathophysiologic hypotheses or predict therapeutic efficacy for compounds with potential neuroprotective effects in humans. To enhance the translational disease-modification potential, the modeling must reflect the biology not of a diseased population but of subtypes of diseased humans to distinguish What data are relevant and to Whom. [ABSTRACT FROM AUTHOR]

This document is an editorial from the journal Biomedicines, discussing the role of the immune system in neurological disorders. It highlights the increasing recognition of the immune system's involvement in various neurological conditions, including autoimmune movement disorders, autoimmune encephalitis, paraneoplastic neurological syndromes, and neurodegeneration. The editorial presents summaries of several research articles that explore these topics, including the pathophysiology, clinical presentation, and treatment perspectives of these immune-mediated neurological disorders. It emphasizes the importance of understanding immune mechanisms in order to improve the diagnosis, treatment, and management of these conditions. [Extracted from the article]

Background: Stuttering is a childhood-onset neurodevelopmental disorder affecting speech fluency. The diagnosis and clinical management of stuttering is currently based on perceptual examination and clinical scales. Standardized techniques for acoustic analysis have prompted promising results for the objective assessment of dysfluency in people with stuttering (PWS). Objective: We assessed objectively and automatically voice in stuttering, through artificial intelligence (i.e., the support vector machine - SVM classifier). We also investigated the age-related changes affecting voice in stutterers, and verified the relevance of specific speech tasks for the objective and automatic assessment of stuttering. Methods: Fifty-three PWS (20 children, 33 younger adults) and 71 age-/gendermatched controls (31 children, 40 younger adults) were recruited. Clinical data were assessed through clinical scales. The voluntary and sustained emission of a vowel and two sentences were recorded through smartphones. Audio samples were analyzed using a dedicated machine-learning algorithm, the SVM to compare PWS and controls, both children and younger adults. The receiver operating characteristic (ROC) curves were calculated for a description of the accuracy, for all comparisons. The likelihood ratio (LR), was calculated for each PWS during all speech tasks, for clinical-instrumental correlations, by using an artificial neural network (ANN). Results: Acoustic analysis based on machine-learning algorithm objectively and automatically discriminated between the overall cohort of PWS and controls with high accuracy (88%). Also, physiologic ageing crucially influenced stuttering as demonstrated by the high accuracy (92%) of machine-learning analysis when classifying children and younger adults PWS. The diagnostic accuracies achieved by machine-learning analysis were comparable for each speech task. The significant clinical-instrumental correlations between LRs and clinical scales supported the biological plausibility of our findings. Conclusion: Acoustic analysis based on artificial intelligence (SVM) represents a reliable tool for the objective and automatic recognition of stuttering and its relationship with physiologic ageing. The accuracy of the automatic classification is high and independent of the speech task. Machine-learning analysis would help clinicians in the objective diagnosis and clinical management of stuttering. The digital collection of audio samples here achieved through smartphones would promote the future application of the technique in a telemedicine context (home environment). [ABSTRACT FROM AUTHOR]

Paraneoplastic neurological syndromes (PNS) include any symptomatic and non-metastatic neurological manifestations associated with a neoplasm. PNS associated with antibodies against intracellular antigens, known as "high-risk" antibodies, show frequent association with underlying cancer. PNS associated with antibodies against neural surface antigens, known as "intermediate- or low-risk" antibodies, are less frequently associated with cancer. In this narrative review, we will focus on PNS of the central nervous system (CNS). Clinicians should have a high index of suspicion with acute/subacute encephalopathies to achieve a prompt diagnosis and treatment. PNS of the CNS exhibit a range of overlapping "high-risk" clinical syndromes, including but not limited to latent and overt rapidly progressive cerebellar syndrome, opsoclonus-myoclonus-ataxia syndrome, paraneoplastic (and limbic) encephalitis/encephalomyelitis, and stiff-person spectrum disorders. Some of these phenotypes may also arise from recent anti-cancer treatments, namely immune-checkpoint inhibitors and CAR T-cell therapies, as a consequence of boosting of the immune system against cancer cells. Here, we highlight the clinical features of PNS of the CNS, their associated tumors and antibodies, and the diagnostic and therapeutic strategies. The potential and the advance of this review consists on a broad description on how the field of PNS of the CNS is constantly expanding with newly discovered antibodies and syndromes. Standardized diagnostic criteria and disease biomarkers are fundamental to quickly recognize PNS to allow prompt treatment initiation, thus improving the long-term outcome of these conditions. [ABSTRACT FROM AUTHOR]

The aim of the present study was to obtain data from a large community sample of patients with Ménière's disease (MD) in Italy through a web-based nationwide survey. Demographic, clinical, and epidemiological features of MD among members of the Italian Association of Ménière's Disease (AMMI) were collected through a web-based survey. The questionnaire was posted on the AMMI website between 01/SEP/2021 and 31/OCT/2021. A total of 520 patients (374 F, 146 M) with MD were included. The age at interview (average ± standard deviation, SD) was 51.4 ± 10.9 years, with a disease duration of 9.9 ± 9.8 years. Eighty percent of cases were unilateral. No patients reported neurocognitive disorders or Parkinson's disease. A positive family history of MD was reported in 13% of participants, while a history of allergic diseases was reported in 33%. Comorbid thyroid disorders were present in 25% of participants, and 28% used betahistine as the main treatment. To our knowledge, this is the first study that has investigated the epidemiology and current patterns of care of MD in Italy, using an anonymous survey directly sent to patients, thus implying their active participation. We hope that future studies will support the utilization of web-based surveys to address the unmet needs in the management of patients with MD. [ABSTRACT FROM AUTHOR]