Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data.

Parkinson's disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals' phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.

Recent advances in non-Huntington's disease choreas.

INTRODUCTION: Chorea is primarily due to an imbalance of basal ganglia output pathways, often due to dysfunction or degeneration of the caudate nucleus and putamen, and can be due to many causes. METHODS: We reviewed the recent literature to identify newly-recognized causes of chorea, including auto-immune, metabolic, and genetic. We also focused upon developments in mechanisms relating to underlying pathophysiology of certain genetic choreas and advances in therapeutics. RESULTS: Novel autoantibodies continue to be identified as causes of chorea. Both COVID-19 infection and vaccination are reported to result rarely in chorea, although in some cases causality is not clearly established. Advances in genetic testing continue to find more causes of chorea, and to expand the phenotype of known genetic disorders. Deep brain stimulation can be successful in certain circumstances. CONCLUSION: Our understanding of mechanisms underlying this movement disorder continues to advance, however much remains to be elucidated.

Diagnostic Uncertainties: Chorea.

Chorea is a hyperkinetic movement disorder with a multitude of potential etiologies, both acquired and inherited. Although the differential diagnosis for new-onset chorea is extensive, there are often clues in the history, exam, and basic testing that can help to narrow the options. Evaluation for treatable or reversible causes should take priority, as rapid diagnosis can lead to more favorable outcomes. While Huntington's disease is most common genetic cause of chorea, multiple phenocopies also exist and should be considered if Huntington gene testing is negative. The decision of what additional genetic testing to pursue should be based on both clinical and epidemiological factors. The following review provides an overview of the many possible etiologies as well as a practical approach for a patient presenting with new-onset chorea.

Fatigue and fluid hydration status in multiple sclerosis: A hypothesis.

BACKGROUND: Fatigue is a prevalent and functionally disabling symptom for individuals living with multiple sclerosis (MS) which is poorly understood and multifactorial in etiology. Bladder dysfunction is another common MS symptom which limits social engagement and quality of life. To manage bladder issues, individuals with MS tend to limit their fluid intake, which may contribute to a low-hydration (LoH) state and fatigue. OBJECTIVE: To evaluate the relationship between patient-reported MS fatigue, bladder dysfunction, and hydration status. METHODS: We performed a prospective cross-sectional study in 50 women with MS. Participants submitted a random urine sample and completed several fatigue-related surveys. Using a urine specific gravity (USG) threshold of 1.015, we classified MS subjects into two groups: high-hydration (HiH) and LoH states. RESULTS: LoH status was more common in MS subjects with bladder dysfunction. Statistically significant differences in self-reported Fatigue Performance Scale were observed between HiH and LoH subjects (p = 0.022). USG was significantly correlated with fatigue as measured by the MS Fatigue Severity Scale (FSS) score (r = 0.328, p = 0.020). CONCLUSION: Hydration status correlates with self-reported fatigue, with lower fatigue scores found in those with HiH status (USG < 1.015).

Case Report of Granulicatella adiacens as a Cause of Bacterascites.

Granulicatella adiacens is a Gram-positive coccus, formerly grouped with nutritionally variant Streptococcus, often found as commensal bacteria of the human oral cavity, urogenital tract, and gastrointestinal tract. Prior case reports have demonstrated Granulicatella spp. as a pathogen that can cause bacteremia and infective endocarditis particularly of prosthetic valves and pacemaker leads. Here, we report on a unique case of Granulicatella adiacens bacterascites in a 50-year-old male.