Association Analysis of Essential Tremor-Associated Genetic Variants in Sporadic Late-Onset Parkinson's Disease.

Background: Parkinson's disease (PD) and Essential tremor (ET) are the two most common tremor diseases with recognized genetic pathogenesis. The overlapping clinical features suggest they may share genetic predispositions. Our previous study systematically investigated the association between rare coding variants in ET-associated genes and early-onset PD (EOPD), and found the suggestive association between teneurin transmembrane protein 4 (TENM4) and EOPD. In the current research, we explored the potential genetic interplay between ET-associated genetic loci/genes and sporadic late-onset PD (LOPD). Methods: We performed whole-genome sequencing in the 1962 sporadic LOPD cases and 1279 controls from mainland China. We first used logistic regression analysis to test the top 16 SNPs identified by the ET genome-wide association study for the association between ET and LOPD. Then we applied the optimized sequence kernel association testing to explore the rare variant burden of 33 ET-associated genes in this cohort. Results: We did not observe a significant association between the included SNPs with LOPD. We also did not discover a significant burden of rare deleterious variants of ET-associated genes in association with LOPD risk. Conclusion: Our results do not support the role of ET-associated genetic loci and variants in LOPD. Highlights: 1962 cases and 1279 controls were recruited to study the potential genetic interplay between ET-associated genetic loci/variants and sporadic LOPD.No significant association between the ET-associated SNPs and LOPD were observed.No significant burden of rare deleterious variants of ET-associated gene in LOPD risk were found.

Integrated proteomics reveals autophagy landscape and an autophagy receptor controlling PKA-RI complex homeostasis in neurons.

Autophagy is a conserved, catabolic process essential for maintaining cellular homeostasis. Malfunctional autophagy contributes to neurodevelopmental and neurodegenerative diseases. However, the exact role and targets of autophagy in human neurons remain elusive. Here we report a systematic investigation of neuronal autophagy targets through integrated proteomics. Deep proteomic profiling of multiple autophagy-deficient lines of human induced neurons, mouse brains, and brain LC3-interactome reveals roles of neuronal autophagy in targeting proteins of multiple cellular organelles/pathways, including endoplasmic reticulum (ER), mitochondria, endosome, Golgi apparatus, synaptic vesicle (SV) for degradation. By combining phosphoproteomics and functional analysis in human and mouse neurons, we uncovered a function of neuronal autophagy in controlling cAMP-PKA and c-FOS-mediated neuronal activity through selective degradation of the protein kinase A - cAMP-binding regulatory (R)-subunit I (PKA-RI) complex. Lack of AKAP11 causes accumulation of the PKA-RI complex in the soma and neurites, demonstrating a constant clearance of PKA-RI complex through AKAP11-mediated degradation in neurons. Our study thus reveals the landscape of autophagy degradation in human neurons and identifies a physiological function of autophagy in controlling homeostasis of PKA-RI complex and specific PKA activity in neurons.

The genetic landscape and phenotypic spectrum of GAA-FGF14 ataxia in China: a large cohort study.

BACKGROUND: An intronic GAA repeat expansion in FGF14 was recently identified as a cause of GAA-FGF14 ataxia. We aimed to characterise the frequency and phenotypic profile of GAA-FGF14 ataxia in a large Chinese ataxia cohort. METHODS: A total of 1216 patients that included 399 typical late-onset cerebellar ataxia (LOCA), 290 early-onset cerebellar ataxia (EOCA), and 527 multiple system atrophy with predominant cerebellar ataxia (MSA-c) were enrolled. Long-range and repeat-primed PCR were performed to screen for GAA expansions in FGF14. Targeted long-read and whole-genome sequencing were performed to determine repeat size and sequence configuration. A multi-modal study including clinical assessment, MRI, and neurofilament light chain was conducted for disease assessment. FINDINGS: 17 GAA-FGF14 positive patients with a (GAA)≥250 expansion (12 patients with a GAA-pure expansion, five patients with a (GAA)≥250-[(GAA)n (GCA)m]z expansion) and two possible patients with biallelic (GAA)202/222 alleles were identified. The clinical phenotypes of the 19 positive and possible positive cases covered LOCA phenotype, EOCA phenotype and MSA-c phenotype. Five of six patients with EOCA phenotype were found to have another genetic disorder. The NfL levels of patients with EOCA and MSA-c phenotypes were significantly higher than patients with LOCA phenotype and age-matched controls (p < 0.001). NfL levels of pre-ataxic GAA-FGF14 positive individuals were lower than pre-ataxic SCA3 (p < 0.001) and similar to controls. INTERPRETATION: The frequency of GAA-FGF14 expansion in a large Chinese LOCA cohort was low (1.3%). Biallelic (GAA)202/222 alleles and co-occurrence with other acquired or hereditary diseases may contribute to phenotypic variation and different progression. FUNDING: This study was funded by the National Key R&D Program of China (2021YFA0805200 to H.J.), the National Natural Science Foundation of China (81974176 and 82171254 to H.J.; 82371272 to Z.C.; 82301628 to L.W.; 82301438 to Z.L.; 82201411 to L.H.), the Innovation Research Group Project of Natural Science Foundation of Hunan Province (2020JJ1008 to H.J.), the Key Research and Development Program of Hunan Province (2020SK2064 to H.J.), the Innovative Research and Development Program of Development and Reform Commission of Hunan Province to H.J., the Natural Science Foundation of Hunan Province (2024JJ3050 to H.J.; 2022JJ20094 and 2021JJ40974 to Z.C.; 2022JJ40783 to L.H.; 2022JJ40703 to Z.L.), the Project Program of National Clinical Research Center for Geriatric Disorders (Xiangya Hospital, 2020LNJJ12 to H.J.), the Central South University Research Programme of Advanced Interdisciplinary Study (2023QYJC010 to H.J.) and the Science and Technology Innovation Program of Hunan Province (2022RC1027 to Z.C.). D.P. holds a Fellowship award from the Canadian Institutes of Health Research (CIHR).

Integrated analysis of gut metabolome, microbiome, and brain function reveal the role of gut-brain axis in longevity.

The role of microbiota-gut-brain axis in modulating longevity remains undetermined. Here, we performed a multiomics analysis of gut metagenomics, gut metabolomics, and brain functional near-infrared spectroscopy (fNIRS) in a cohort of 164 participants, including 83 nonagenarians (NAs) and 81 non-nonagenarians (NNAs) matched with their spouses and offspring. We found that 438 metabolites were significantly different between the two groups; among them, neuroactive compounds and anti-inflammatory substances were enriched in NAs. In addition, increased levels of neuroactive metabolites in NAs were significantly associated with NA-enriched species that had three corresponding biosynthetic potentials: Enterocloster asparagiformis, Hungatella hathewayi and Oxalobacter formigenes. Further analysis showed that the altered gut microbes and metabolites were linked to the enhanced brain connectivity in NAs, including the left dorsolateral prefrontal cortex (DLPFC)-left premotor cortex (PMC), left DLPFC-right primary motor area (M1), and right inferior frontal gyrus (IFG)-right M1. Finally, we found that neuroactive metabolites, altered microbe and enhanced brain connectivity contributed to the cognitive preservation in NAs. Our findings provide a comprehensive understanding of the microbiota-gut-brain axis in a long-lived population and insights into the establishment of a microbiome and metabolite homeostasis that can benefit human longevity and cognition by enhancing functional brain connectivity.

Unveiling the role of iPLA2ß in neurodegeneration: From molecular mechanisms to advanced therapies.

Calcium-independent phospholipase A2ß (iPLA2ß), a member of the phospholipase A2 (PLA2s) superfamily, is encoded by the PLA2G6 gene. Mutations in the PLA2G6 gene have been identified as the primary cause of infantile neuroaxonal dystrophy (INAD) and, less commonly, as a contributor to Parkinson's disease (PD). Recent studies have revealed that iPLA2ß deficiency leads to neuroinflammation, iron accumulation, mitochondrial dysfunction, lipid dysregulation, and other pathological changes, forming a complex pathogenic network. These discoveries shed light on potential mechanisms underlying PLA2G6-associated neurodegeneration (PLAN) and offer valuable insights for therapeutic development. This review provides a comprehensive analysis of the fundamental characteristics of iPLA2ß, its association with neurodegeneration, the pathogenic mechanisms involved in PLAN, and potential targets for therapeutic intervention. It offers an overview of the latest advancements in this field, aiming to contribute to ongoing research endeavors and facilitate the development of effective therapies for PLAN.

Brain eQTLs of European, African American, and Asian ancestry improve interpretation of schizophrenia GWAS.

Research on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet, the majority of these studies have been centered on European populations, leading to a constrained understanding of population diversities and disease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA, n=158), Europeans (EUR, n=408), and East Asians (EAS, n=217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patterns of genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737 cis-eQTLs (representing ∼17% of all eQTLs pairs) linked to 1,276 genes (about 10% of all eGenes) and 198,769 SNPs (approximately 16% of all eSNPs) were identified only in the non-EUR populations. Over 90% of observed population differences in eQTLs could be traced back to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare (MAF < 0.05) in the EUR population. Integrating brain eQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched populations compared to mismatched ones. Prioritization analysis identified seven new risk genes ( SFXN2 , RP11-282018.3 , CYP17A1 , VPS37B , DENR , FTCDNL1 , and NT5DC2 ), and three potential novel regulatory variants in known risk genes ( CNNM2 , C12orf65 , and MPHOSPH9 ) that were missed in the EUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merely increasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the biological underpinnings of population structures but also pave the way for the identification of novel risk genes in SCZ.

An Electroencephalography Profile of Paroxysmal Kinesigenic Dyskinesia.

Paroxysmal kinesigenic dyskinesia (PKD) is associated with a disturbance of neural circuit and network activities, while its neurophysiological characteristics have not been fully elucidated. This study utilized the high-density electroencephalogram (hd-EEG) signals to detect abnormal brain activity of PKD and provide a neural biomarker for its clinical diagnosis and PKD progression monitoring. The resting hd-EEGs are recorded from two independent datasets and then source-localized for measuring the oscillatory activities and function connectivity (FC) patterns of cortical and subcortical regions. The abnormal elevation of theta oscillation in wildly brain regions represents the most remarkable physiological feature for PKD and these changes returned to healthy control level in remission patients. Another remarkable feature of PKD is the decreased high-gamma FCs in non-remission patients. Subtype analyses report that increased theta oscillations may be related to the emotional factors of PKD, while the decreased high-gamma FCs are related to the motor symptoms. Finally, the authors established connectome-based predictive modelling and successfully identified the remission state in PKD patients in dataset 1 and dataset 2. The findings establish a clinically relevant electroencephalography profile of PKD and indicate that hd-EEG can provide robust neural biomarkers to evaluate the prognosis of PKD.

Risk factors associated with age at onset of Parkinson's disease in the UK Biobank.

Substantial evidence shown that the age at onset (AAO) of Parkinson's disease (PD) is a major determinant of clinical heterogeneity. However, the mechanisms underlying heterogeneity in the AAO remain unclear. To investigate the risk factors with the AAO of PD, a total of 3156 patients with PD from the UK Biobank were included in this study. We evaluated the effects of polygenic risk scores (PRS), nongenetic risk factors, and their interaction on the AAO using Mann-Whitney U tests and regression analyses. We further identified the genes interacting with nongenetic risk factors for the AAO using genome-wide environment interaction studies. We newly found physical activity (P < 0.0001) was positively associated with AAO and excessive daytime sleepiness (P < 0.0001) was negatively associated with AAO, and reproduced the positive associations of smoking and non-steroidal anti-inflammatory drug intake and the negative association of family history with AAO. In the dose-dependent analyses, smoking duration (P = 1.95 × 10-6), coffee consumption (P = 0.0150), and tea consumption (P = 0.0008) were positively associated with AAO. Individuals with higher PRS had younger AAO (P = 3.91 × 10-5). In addition, we observed a significant interaction between the PRS and smoking for AAO (P = 0.0316). Specifically, several genes, including ANGPT1 (P = 7.17 × 10-7) and PLEKHA6 (P = 4.87 × 10-6), may influence the positive relationship between smoking and AAO. Our data suggests that genetic and nongenetic risk factors are associated with the AAO of PD and that there is an interaction between the two.

VarCards2: an integrated genetic and clinical database for ACMG-AMP variant-interpretation guidelines in the human whole genome.

VarCards, an online database, combines comprehensive variant- and gene-level annotation data to streamline genetic counselling for coding variants. Recognising the increasing clinical relevance of non-coding variations, there has been an accelerated development of bioinformatics tools dedicated to interpreting non-coding variations, including single-nucleotide variants and copy number variations. Regrettably, most tools remain as either locally installed databases or command-line tools dispersed across diverse online platforms. Such a landscape poses inconveniences and challenges for genetic counsellors seeking to utilise these resources without advanced bioinformatics expertise. Consequently, we developed VarCards2, which incorporates nearly nine billion artificially generated single-nucleotide variants (including those from mitochondrial DNA) and compiles vital annotation information for genetic counselling based on ACMG-AMP variant-interpretation guidelines. These annotations include (I) functional effects; (II) minor allele frequencies; (III) comprehensive function and pathogenicity predictions covering all potential variants, such as non-synonymous substitutions, non-canonical splicing variants, and non-coding variations and (IV) gene-level information. Furthermore, VarCards2 incorporates 368 820 266 documented short insertions and deletions and 2 773 555 documented copy number variations, complemented by their corresponding annotation and prediction tools. In conclusion, VarCards2, by integrating over 150 variant- and gene-level annotation sources, significantly enhances the efficiency of genetic counselling and can be freely accessed at http://www.genemed.tech/varcards2/.

GGC expansions in NOTCH2NLC contribute to Parkinson disease and dopaminergic neuron degeneration.

BACKGROUND AND PURPOSE: The role of GGC repeat expansions within NOTCH2NLC in Parkinson's disease (PD) and the substantia nigra (SN) dopaminergic neuron remains unclear. Here, we profile the NOTCH2NLC GGC repeat expansions in a large cohort of patients with PD. We also investigate the role of GGC repeat expansions within NOTCH2NLC in the dopaminergic neurodegeneration of SN. METHODS: A total of 2,522 patients diagnosed with PD and 1,085 health controls were analyzed for the repeat expansions of NOTCH2NLC by repeat-primed PCR and GC-rich PCR assay. Furthermore, the effects of GGC repeat expansions in NOTCH2NLC on dopaminergic neurons were investigated by using recombinant adeno-associated virus (AAV)-mediated overexpression of NOTCH2NLC with 98 GGC repeats in the SN of mice by stereotactic injection. RESULTS: Four PD pedigrees (4/333, 1.2%) and three sporadic PD patients (3/2189, 0.14%) were identified with pathogenic GGC repeat expansions (larger than 60 GGC repeats) in the NOTCH2NLC gene, while eight PD patients and one healthy control were identified with intermediate GGC repeat expansions ranging from 41 to 60 repeats. No significant difference was observed in the distribution of intermediate NOTCH2NLC GGC repeat expansions between PD cases and controls (Fisher's exact test p-value = 0.29). Skin biopsy showed P62-positive intranuclear NOTCH2NLC-polyGlycine (polyG) inclusions in the skin nerve fibers of patient. Expanded GGC repeats in NOTCH2NLC produced widespread intranuclear and perinuclear polyG inclusions, which led to a severe loss of dopaminergic neurons in the SN. Consistently, polyG inclusions were presented in the SN of EIIa-NOTCH2NLC-(GGC)98 transgenic mice and also led to dopaminergic neuron loss in the SN. CONCLUSIONS: Overall, our findings provide strong evidence that GGC repeat expansions within NOTCH2NLC contribute to the pathogenesis of PD and cause degeneration of nigral dopaminergic neurons.

Genetic analysis of transcription factors in dopaminergic neuronal development in Parkinson's disease.

BACKGROUND: Genetic variants of dopaminergic transcription factor-encoding genes are suggested to be Parkinson's disease (PD) risk factors; however, no comprehensive analyses of these genes in patients with PD have been undertaken. Therefore, we aimed to genetically analyze 16 dopaminergic transcription factor genes in Chinese patients with PD. METHODS: Whole-exome sequencing (WES) was performed using a Chinese cohort comprising 1917 unrelated patients with familial or sporadic early-onset PD and 1652 controls. Additionally, whole-genome sequencing (WGS) was performed using another Chinese cohort comprising 1962 unrelated patients with sporadic late-onset PD and 1279 controls. RESULTS: We detected 308 rare and 208 rare protein-altering variants in the WES and WGS cohorts, respectively. Gene-based association analyses of rare variants suggested that MSX1 is enriched in sporadic late-onset PD. However, the significance did not pass the Bonferroni correction. Meanwhile, 72 and 1730 common variants were found in the WES and WGS cohorts, respectively. Unfortunately, single-variant logistic association analyses did not identify significant associations between common variants and PD. CONCLUSIONS: Variants of 16 typical dopaminergic transcription factors might not be major genetic risk factors for PD in Chinese patients. However, we highlight the complexity of PD and the need for extensive research elucidating its etiology.

The prevalence and risk factors study of cognitive impairment: Analysis of the elderly population of Han nationality in Hunan province, China.

OBJECTIVE: A large number of studies have found that the prevalence of cognitive impairment varies in different regions. However, data on cognitive impairment in the Chinese population is still lacking. The goal of this study was to assess the prevalence of cognitive impairment among the elderly in a region of China and explore the associated risk factors. METHODS: We performed a population-based cross-sectional survey from April to June 2022. Residents come from three villages and six urban communities in the county-level city of Liuyang in southern China (N = 3233) and the coverage rate of our study population reached 73%. Participants were assessed with a series of clinical examinations and neuropsychological measures. A total of 2598 participants were selected after filtering out those under 60 years old or with incomplete data. Patients with cognitive impairment included those with mild cognitive impairment (MCI) or dementia who met standard diagnostic criteria. RESULTS: The prevalence of cognitive impairment, MCI, and dementia among participants aged 60 years and older were 21.48% (95% CI, 19.90-23.10), 15.70% (95% CI, 14.30-17.10), and 5.77 (95% CI, 4.90-6.70), respectively. And residents in villagers were more likely to have cognitive impairment than in urban communities (p < 0.001). Age growth and education level were independent influencing factors for cognitive impairment in all populations (p < 0.001). For lifestyles factors, both smoking and drinking reduced the risk of cognitive impairment (p < 0.05), but when further quantified, the link disappeared. Moreover, having cerebrovascular disease and severe vision impairment were risk factors (p < 0.05). CONCLUSION: A representative prevalence of cognitive impairment, MCI, and dementia was found in the elderly Han Chinese population in Southern China. And we further explored the role of known risk factors, particularly in physical activity, smoking, and alcohol consumption.

Estimating the sequence of biomarker changes in Parkinson's disease.

OBJECTIVE: To estimate the sequence of several common biomarker changes in Parkinson's disease (PD) using a novel data-driven method. METHODS: We included 374 PD patients and 169 healthy controls (HC) from the Parkinson's Progression Markers Initiative (PPMI). Biomarkers, including the left putamen striatal binding ratio (SBR), right putamen SBR, left caudate SBR, right caudate SBR, cerebrospinal fluid (CSF) α-synuclein, and serum neurofilament light chain (NfL), were selected in our study. The discriminative event-based model (DEBM) was utilized to model the sequence of biomarker changes and establish the disease progression timeline. The estimated disease stages for each subject were obtained through cross-validation. The associations between the estimated disease stages and the clinical symptoms of PD were explored using Spearman's correlation. RESULTS: The left putamen is the earliest biomarker to become abnormal among the selected biomarkers, followed by the right putamen, CSF α-synuclein, right caudate, left caudate, and serum NfL. The estimated disease stages are significantly different between PD and HC and yield a high accuracy for distinguishing PD from HC, with an area under the curve (AUC) of 0.98 (95% confidence interval 0.97-0.99), a sensitivity of 0.95, and a specificity of 0.92. Moreover, the estimated disease stages correlate with motor experiences of daily living, motor symptoms, autonomic dysfunction, and anxiety in PD patients. CONCLUSION: We determined the sequence of several common biomarker changes in PD using DEBM, providing data-driven evidence of the disease progression of PD.

A detection model of cognitive impairment via the integrated gait and eye movement analysis from a large Chinese community cohort.

INTRODUCTION: Whether the integration of eye-tracking, gait, and corresponding dual-task analysis can distinguish cognitive impairment (CI) patients from controls remains unclear. METHODS: One thousand four hundred eighty-one participants, including 724 CI and 757 controls, were enrolled in this study. Eye movement and gait, combined with dual-task patterns, were measured. The LightGBM machine learning models were constructed. RESULTS: A total of 105 gait and eye-tracking features were extracted. Forty-six parameters, including 32 gait and 14 eye-tracking features, showed significant differences between two groups (P < 0.05). Of these, the Gait_3Back-TurnTime and Dual-task cost-TurnTime patterns were significantly correlated with plasma phosphorylated tau 181 (p-tau181) level. A model based on dual-task gait, dual-task smooth pursuit, prosaccade, and anti-saccade achieved the best area under the receiver operating characteristics curve (AUC) of 0.987 for CI detection, while combined with p-tau181, the model discriminated mild cognitive impairment from controls with an AUC of 0.824. DISCUSSION: Combining dual-task gait and dual-task eye-tracking analysis is feasible for the detection of CI. HIGHLIGHTS: This is the first study to report the efficiency of integrated parameters of dual-task gait and eye-tracking for cognitive impairment (CI) detection in a large cohort. We identified 46 gait and eye-tracking features associated with CI, and two were correlated to plasma phosphorylated tau 181. We constructed the model based on dual-task gait, smooth pursuit, prosaccade, and anti-saccade, achieving the best area under the curve of 0.987 for CI detection.

Association of TRMT2B gene variants with juvenile amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive degeneration of motor neurons, and it demonstrates high clinical heterogeneity and complex genetic architecture. A variation within TRMT2B (c.1356G>T; p.K452N) was identified to be associated with ALS in a family comprising two patients with juvenile ALS (JALS). Two missense variations and one splicing variation were identified in 10 patients with ALS in a cohort with 910 patients with ALS, and three more variants were identified in a public ALS database including 3317 patients with ALS. A decreased number of mitochondria, swollen mitochondria, lower expression of ND1, decreased mitochondrial complex I activities, lower mitochondrial aerobic respiration, and a high level of ROS were observed functionally in patient-originated lymphoblastoid cell lines and TRMT2B interfering HEK293 cells. Further, TRMT2B variations overexpression cells also displayed decreased ND1. In conclusion, a novel JALS-associated gene called TRMT2B was identified, thus broadening the clinical and genetic spectrum of ALS.

Mutation and clinical analysis of the CLCC1 gene in amyotrophic lateral sclerosis patients from Central South China.

INTRODUCTION: Recently, chloride channel CLIC-like 1 (CLCC1) was reported to be a novel ALS-related gene. We aimed to screen CLCC1 variants in our ALS cohort and further explore the genotype-phenotype correlation of CLCC1-related ALS. METHODS: We screened rare damaging variants in CLCC1 from our cohorts of 1005 ALS patients and 1224 healthy controls with whole-exome sequencing in Central South China. Fisher's exact test was conducted for association analysis at the entire gene level and single variant level. RESULTS: In total, four heterozygous missense variants in CLCC1 were identified from four unrelated sporadic ALS patients and predicted to be putative pathogenic by in silico tools and protein model prediction, accounting for 0.40% of all patients (4/1005). The four variants were c.A275C (p.Q92P), c.G1139A (p.R380K), c.C1244T (p.T415M), and c.G1328A (p.R443Q), respectively, which had not been reported in ALS patients previously. Three of four variants were located in exon 10. Patients harboring CLCC1 variants seemed to share a group of similar clinical features, including earlier age at onset, rapid progression, spinal onset, and vulnerable cognitive status. Statistically, we did not find CLCC1 to be associated with the risk of ALS at the entire gene level or single variant level. CONCLUSION: Our findings further expanded the genetic and clinical spectrum of CLCC1-related ALS and provided more genetic evidence for anion channel involvement in the pathogenesis of ALS, but further investigations are needed to verify our findings.

Peripheral Inflammatory and Immune Landscape in Multiple System Atrophy: A Cross-Sectional Study.

BACKGROUND: Neuroinflammation might contribute to the pathogenesis of multiple systemic atrophy (MSA). However, specific alterations in the peripheral inflammatory and immune profiles of patients with MSA remain unclear. OBJECTIVES: To determine the peripheral inflammatory and immune profiles of patients with MSA and their potential value as biomarkers for facilitating clinical diagnosis and monitoring disease severity. METHODS: This cross-sectional study included 235, 240, and 235 patients with MSA, patients with Parkinson's disease (PD), and healthy controls (HCs), respectively. Inflammatory and immune parameters were measured in peripheral blood, differences between groups were assessed, and clusters were analyzed. Associations between the parameters and clinical characteristics of MSA were assessed using Spearman and partial correlation analyses. RESULTS: Significant differences were observed especially in monocytes, neutrophils-to-lymphocyte ratio (NLR) and neutrophils-to-lymphocyte ratio (MPV) between MSA patients and HCs (P < 0.01). Monocytes and uric acid (UA) levels were also significantly different between the MSA and PD patients (P < 0.05). The combination of NLR and MPV distinguished MSA-P patients from HCs (areas under the curve = 0.824). In addition, complement components C4 and C3 were significantly correlated with the Scale Outcomes in PD for Autonomic Symptoms and Wexner scale, whereas immunoglobulin G (IgG) was significantly correlated with scores of Unified Multiple System Atrophy Rating Scale (P < 0.05). CONCLUSIONS: In MSA patients, monocytes, NLR and MPV might serve as potential diagnostic biomarkers, whereas MLR, C3, C4, and IgG significantly correlate with disease severity. © 2023 International Parkinson and Movement Disorder Society.

Specific serum autoantibodies predict the development and progression of Alzheimer's disease with high accuracy.

Autoimmunity plays a key role in the pathogenesis of Alzheimer's disease (AD). However, whether autoantibodies in peripheral blood can be used as biomarkers for AD has been elusive. Serum samples were obtained from 1,686 participants, including 767 with AD, 146 with mild cognitive impairment (MCI), 255 with other neurodegenerative diseases, and 518 healthy controls. Specific autoantibodies were measured using a custom-made immunoassay. Multivariate support vector machine models were employed to investigate the correlation between serum autoantibody levels and disease states. As a result, seven candidate AD-specific autoantibodies were identified, including MAPT, DNAJC8, KDM4D, SERF1A, CDKN1A, AGER, and ASXL1. A classification model with high accuracy (area under the curve (AUC) = 0.94) was established. Importantly, these autoantibodies could distinguish AD from other neurodegenerative diseases and out-performed amyloid and tau protein concentrations in cerebrospinal fluid in predicting cognitive decline (P < 0.001). This study indicated that AD onset and progression are possibly accompanied by an unappreciated serum autoantibody response. Therefore, future studies could optimize its application as a convenient biomarker for the early detection of AD.

Parkinson's disease and gut microbiota: from clinical to mechanistic and therapeutic studies.

Parkinson's disease (PD) is one of the most prevalent neurodegenerative diseases. The typical symptomatology of PD includes motor symptoms; however, a range of nonmotor symptoms, such as intestinal issues, usually occur before the motor symptoms. Various microorganisms inhabiting the gastrointestinal tract can profoundly influence the physiopathology of the central nervous system through neurological, endocrine, and immune system pathways involved in the microbiota-gut-brain axis. In addition, extensive evidence suggests that the gut microbiota is strongly associated with PD. This review summarizes the latest findings on microbial changes in PD and their clinical relevance, describes the underlying mechanisms through which intestinal bacteria may mediate PD, and discusses the correlations between gut microbes and anti-PD drugs. In addition, this review outlines the status of research on microbial therapies for PD and the future directions of PD-gut microbiota research.

Escherichia coli triggers α-synuclein pathology in the LRRK2 transgenic mouse model of PD.

Alpha-synuclein (α-syn) pathology is the hallmark of Parkinson's disease (PD). The leucine-rich repeat kinase 2 (LRRK2) gene is a major-effect risk gene for sporadic PD (sPD). However, what environmental factors may trigger the formation of α-syn pathology in carriers of LRRK2 risk variants are still unknown. Here, we report that a markedly increased abundance of Escherichia coli (E. coli) in the intestinal microbiota was detected in LRRK2 risk variant(R1628P or G2385R) carriers with sPD compared with carriers without sPD. Animal experiments showed that E. coli administration triggered pathological α-syn accumulation in the colon and spread to the brain via the gut-brain axis in Lrrk2 R1628P mice, due to the co-occurrence of Lrrk2 variant-induced inhibition of α-syn autophagic degradation and increased phosphorylation of α-syn caused by curli in E. coli-derived extracellular vesicles. Fecal microbiota transplantation (FMT) effectively ameliorated motor deficits and α-syn pathology in Lrrk2 R1628P mice. Our findings elaborate on the mechanism that E. coli triggers α-syn pathology in Lrrk2 R1628P mice, and highlight a novel gene-environment interaction pattern in LRRK2 risk variants. Even more importantly, the findings reveal the interplay between the specific risk gene and the matched environmental factors triggers the initiation of α-syn pathology in sPD.