"Hot cross bun" is a potential imaging marker for the severity of cerebellar ataxia in MSA-C

"One a penny, two a penny", I saw the hot cross bun sign"

The hot cross bun sign is a radiological sign seen on MRI due to pontocerebellar demyelination and loss of neurons along with preservation of the pontine tegmentum and corticospinal tracts which is classically seen in Multiple System Atrophy (MSA). Hot cross buns have been in existence since as early as the 14th century up until the point when Schrag et al. (1998) coupled the appearance of this age-old bread with the T2 imaging characteristics of MSA. Over time the radiological sign has expanded with a differential diagnosis of spinocerebellar ataxia, progressive multifocal leukoencephalopathy, paraneoplastic cerebellar degeneration, and variant Creutzfeldt-Jakob disease.

Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

Imaging Markers of Multiple System Atrophy and Their Association With Disease Severity: A Cross-Sectional Study

Background Multiple system atrophy (MSA) is a rare, adult-onset neurodegenerative disorder marked by autonomic failure, parkinsonism, and cerebellar ataxia, with subtypes classified as parkinsonian (MSA-P), cerebellar (MSA-C), and autonomic (MSA-A). This study aims to identify MRI biomarkers for MSA and their correlation with disease severity. Methodology A total of 30 patients with probable MSA (20 MSA-C, 10 MSA-P) aged 45-65 years were studied. Motor and non-motor symptoms were assessed using the Unified Multiple System Atrophy Rating Scale (UMSARS), and all patients underwent 3T MRI brain imaging. Data analysis was performed using SPSS version 22 (IBM Corp., Armonk, NY, USA) with Spearman's correlation for clinical-imaging correlations. Results The mean age of the study population was 54.43 years, with a male predominance (56.7%). The most common symptoms included gait ataxia (43.3%) and urinary dysfunction (96.7%), with orthostatic symptoms in 33.3%. Moderate disease severity was observed, with mean UMSARS scores of 15.9 (Part 1) and 16 (Part 2), showing no significant subtype differences. MRI revealed abnormalities in all patients, predominantly cerebellar atrophy (90%). The "hot cross bun" (HCB) sign was seen in 75% of MSA-C patients, but none of MSA-P patients showed the same. The HCB sign was significantly correlated with severity in MSA-C (USMSARS-4). Putaminal signs were less frequent and slightly more prevalent in MSA-P, without significant clinical-imaging correlation. Conclusions This study reinforces the critical role of MRI biomarkers in the diagnosis of MSA patients. Notably, the HCB sign exhibited a significant association with clinical severity in MSA-C patients, while such correlation was absent in MSA-P cases.

"Hot Cross Bun" Sign in a Patient with Glutamic Acid Decarboxylase 65-KDa Isoform Associated Cerebellar Ataxia: Case Report and Review of the Literature

The "hot cross bun" sign (HCBs) is a cruciform hyperintensity on T2-weighted imaging within the pons initially found in patients diagnosed as multiple system atrophy. However, recent findings have broadened the disease spectrum presented with HCBs. Here is a case report at an academic medical center. Cerebral magnetic resonance imaging (MRI), electroneuromyography, serum, and CSF analysis were performed. Literature is comprehensively reviewed. We investigated a woman presented with blurred speech and cerebellar ataxia. Her MRI showed the vertical line of HCBs 2 weeks after disease onset and gradually enhanced, presenting as an intact HCBs in a year. Glutamic acid decarboxylase 65-kDa isoform (GAD65) antibody IgG was detected in serum and CSF. The patient was diagnosed as GAD65 associated cerebellar ataxia and treated with corticosteroid and rituximab. We found 6 previously reported autoimmune cerebellar ataxia patients with HCBs. Anti-KLHL-11, anti-Homer-3, anti-Ri, and anti-Amphiphysin were associated. All patients had cerebellar ataxia with other neurological symptoms. Five patients were diagnosed with tumor. First-line immunotherapy including corticosteroid, intravenous immunoglobulin, and plasma exchange for most patients was unsatisfied. This case highlights the importance of considering GAD65 IgG evaluation in patients with progressive cerebellar syndrome and HCBs. Early diagnosis and therapy are challenging but imperative. Further studies are required in regard to therapeutic management.

MRl and MRS hints for the differentiation of cerebellar multiple system atrophy from spinocerebellar ataxia type II

Background and objectives

The differentiation of spinocerebellar ataxia type II (SCA 2) from idiopathic multiple systemic atrophy of the cerebellar type (MSA-C) is often difficult in patients with cerebellar ataxia when molecular testing is not available. Besides genetic testing, magnetic resonance imagining (MRI) and magnetic resonance spectroscopy (MRS) prove to be beneficial. Nevertheless, the characteristics observed through radiology change as the disease advances. Different radiological criteria may be needed across different stages of the disease. This study aimed to assess the radiological characteristics of MSA-C or SCA 2 patients across various stages of the disease and to identify potential distinguishing factors.

Methods

Between January 2000 and January 2020, a total of 390 patients, diagnosed with probable MSA-C according to the second consensus on MSA (317 cases) or with molecularly confirmed SCA 2 (73 cases), who had undergone at least one brain MRI and MRS targeting the cerebellar hemispheres, were enrolled in the study. The clinical parameters and neuroimaging features between these two diseases were compared and analyzed.

Results

A greater occurrence of a pontine hot cross bun sign (HCBS), higher scores on the scale for the assessment and rating of ataxia, and reduced levels of cerebellar N-acetyl aspartate (NAA)/creatine (Cr), and cerebellar choline (Cho)/Cr were found in MSA-C patients as compared with SCA 2 patients at similar disease durations. For the patients with an HCBS, a cerebellar Cho/Cr level of <0.53 was indicative of the potential presence of MSA-C, with significant level of specificity (85.96%).

Discussion

Discerning SCA2 from MSA-C using MRI and MRS appears to be plausible at various disease stages.

Identification of Parkinson's disease and multiple system atrophy using multimodal PET/MRI radiomics

OBJECTIVES

To construct a machine learning model for differentiating Parkinson's disease (PD) and multiple system atrophy (MSA) by using multimodal PET/MRI radiomics and clinical characteristics.

METHODS

One hundred and nineteen patients (81 with PD and 38 with MSA) underwent brain PET/CT and MRI to obtain metabolic images ([18F]FDG, [11C]CFT PET) and structural MRI (T1WI, T2WI, and T2-FLAIR). Image analysis included automatic segmentation on MRI, co-registration of PET images onto the corresponding MRI. Radiomics features were then extracted from the putamina and caudate nuclei and selected to construct predictive models. Moreover, based on PET/MRI radiomics and clinical characteristics, we developed a nomogram. Receiver operating characteristic (ROC) curves were performed to evaluate the performance of the models. Decision curve analysis (DCA) was employed to access the clinical usefulness of the models.

RESULTS

The combined PET/MRI radiomics model of five sequences outperformed monomodal radiomics models alone. Further, PET/MRI radiomics-clinical combined model could perfectly distinguish PD from MSA (AUC = 0.993), which outperformed the clinical model (AUC = 0.923, p = 0.028) in training set, with no significant difference in test set (AUC = 0.860 vs 0.917, p = 0.390). However, no significant difference was found between PET/MRI radiomics-clinical model and PET/MRI radiomics model in training (AUC = 0.988, p = 0.276) and test sets (AUC = 0.860 vs 0.845, p = 0.632). DCA demonstrated the highest clinical benefit of PET/MRI radiomics-clinical model.

CONCLUSIONS

Our study indicates that multimodal PET/MRI radiomics could achieve promising performance to differentiate between PD and MSA in clinics.

CLINICAL RELEVANCE STATEMENT

This study developed an optimal radiomics signature and construct model to distinguish PD from MSA by multimodal PET/MRI imaging methods in clinics for parkinsonian syndromes, which achieved an excellent performance.

KEY POINTS

•Multimodal PET/MRI radiomics from putamina and caudate nuclei increase the diagnostic efficiency for distinguishing PD from MSA. •The radiomics-based nomogram was developed to differentiate between PD and MSA. •Combining PET/MRI radiomics-clinical model achieved promising performance to identify PD and MSA.

Identifying New Subtypes of Multiple System Atrophy Using Cluster Analysis

Background

Multiple system atrophy (MSA) is a disease with diverse symptoms and the commonly used classifications, MSA-P and MSA-C, do not cover all the different symptoms seen in MSA patients. Additionally, these classifications do not provide information about how the disease progresses over time or the expected outcome for patients.

Objective

To explore clinical subtypes of MSA with a natural disease course through a data-driven approach to assist in the diagnosis and treatment of MSA.

Methods

We followed 122 cases of MSA collected from 3 hospitals for 3 years. Demographic characteristics, age of onset, clinical signs, scale assessment scores, and auxiliary examination were collected. Age at onset; time from onset to assisted ambulation; and UMSARS I, II, and IV, COMPASS-31, ICARS, and UPDRS III scores were selected as clustering elements. K-means, partitioning around medoids, and self-organizing maps were used to analyze the clusters.

Results

The results of all three clustering methods supported the classification of three MSA subtypes: The aggressive progression subtype (MSA-AP), characterized by mid-to-late onset, rapid progression and severe clinical symptoms; the typical subtype (MSA-T), characterized by mid-to-late onset, moderate progression and moderate severity of clinical symptoms; and the early-onset slow progression subtype (MSA-ESP), characterized by early-to-mid onset, slow progression and mild clinical symptoms.

Conclusions

We divided MSA into three subtypes and summarized the characteristics of each subtype. According to the clustering results, MSA patients were divided into three completely different types according to the severity of symptoms, the speed of disease progression, and the age of onset.

Heterozygous nonsense variants in the ferritin heavy-chain gene FTH1 cause a neuroferritinopathy

Ferritin, the iron-storage protein, is composed of light- and heavy-chain subunits, encoded by FTL and FTH1, respectively. Heterozygous variants in FTL cause hereditary neuroferritinopathy, a type of neurodegeneration with brain iron accumulation (NBIA). Variants in FTH1 have not been previously associated with neurologic disease. We describe the clinical, neuroimaging, and neuropathology findings of five unrelated pediatric patients with de novo heterozygous FTH1 variants. Children presented with developmental delay, epilepsy, and progressive neurologic decline. Nonsense FTH1 variants were identified using whole-exome sequencing, with a recurrent variant (p.Phe171∗) identified in four unrelated individuals. Neuroimaging revealed diffuse volume loss, features of pontocerebellar hypoplasia, and iron accumulation in the basal ganglia. Neuropathology demonstrated widespread ferritin inclusions in the brain. Patient-derived fibroblasts were assayed for ferritin expression, susceptibility to iron accumulation, and oxidative stress. Variant FTH1 mRNA transcripts escape nonsense-mediated decay (NMD), and fibroblasts show elevated ferritin protein levels, markers of oxidative stress, and increased susceptibility to iron accumulation. C-terminal variants in FTH1 truncate ferritin's E helix, altering the 4-fold symmetric pores of the heteropolymer, and likely diminish iron-storage capacity. FTH1 pathogenic variants appear to act by a dominant, toxic gain-of-function mechanism. The data support the conclusion that truncating variants in the last exon of FTH1 cause a disorder in the spectrum of NBIA. Targeted knockdown of mutant FTH1 transcript with antisense oligonucleotides rescues cellular phenotypes and suggests a potential therapeutic strategy for this pediatric neurodegenerative disorder.

Automatic classification of MSA subtypes using Whole-brain gray matter function and Structure-Based radiomics approach

BACKGROUND

This study aims to develop a radiomics method based on the function and structure of whole-brain gray matter to accurately classify multiple system atrophy with predominant Parkinsonism (MSA-P) or predominant cerebellar ataxia (MSA-C).

METHODS

We enrolled 30 MSA-C and 41 MSA-P cases for the internal cohort and 11 MSA-C and 10 MSA-P cases for the external test cohort. We extracted 7,308 features, including gray matter volume (GMV), mean amplitude of low-frequency fluctuation (mALFF), mean regional homogeneity (mReHo), degree of centrality (DC), voxel-mirrored homotopic connectivity (VMHC), and resting-state functional connectivity (RSFC) from 3D-T1 and Rs-fMR data. Feature selection was conducted with t-test and least absolute shrinkage and selection operator (Lasso). Classification was performed using the support vector machine with linear and RBF kernel (SVM-linear/SVM-RBF), random forest and logistic regression. Model performance was assessed via receiver operating characteristic (ROC) curve and compared with DeLong's test.

RESULTS

Feature selection resulted in 12 features, including 1 ALFF, 1 DC and 10 RSFC. All the classifiers showed remarkable classification performance, especially the RF model which exhibited AUC values of 0.91 and 0.80 in the validation and test datasets, respectively. The brain functional activity and connectivity in the cerebellum, orbitofrontal lobe and limbic system were important features to distinguish MSA subtypes with the same disease severity and duration.

CONCLUSION

Radiomics approach has the potential to support clinical diagnostic systems and to achieve high classification accuracy for distinguishing between MSA-C and MSA-P patients at the individual level.

QEEG Signatures are Associated with Nonmotor Dysfunctions in Parkinson's Disease and Atypical Parkinsonism: An Integrative Analysis

Parkinson's disease (PD) and atypical parkinsonism (AP), including progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), share similar nonmotor symptoms. Quantitative electroencephalography (QEEG) can be used to examine the nonmotor symptoms. This study aimed to characterize the patterns of QEEG and functional connectivity (FC) that differentiate PD from PSP or MSA, and explore the correlation between the differential QEEG indices and nonmotor dysfunctions in PD and AP. We enrolled 52 patients with PD, 31 with MSA, 22 with PSP, and 50 age-matched health controls to compare QEEG indices among specific brain regions. One-way analysis of variance was applied to assess QEEG indices between groups; Spearman's correlations were used to examine the relationship between QEEG indices and nonmotor symptoms scale (NMSS) and mini-mental state examination (MMSE). FCs using weighted phase lag index were compared between patients with PD and those with MSA/PSP. Patients with PSP revealed higher scores on the NMSS and lower MMSE scores than those with PD and MSA, with similar disease duration. The delta and theta powers revealed a significant increase in PSP, followed by PD and MSA. Patients with PD presented a significantly lower slow-to-fast ratio than those with PSP in the frontal region, while patients with PD presented significantly higher EEG-slowing indices than patients with MSA. The frontal slow-to-fast ratio showed a negative correlation with MMSE scores in patients with PD and PSP, and a positive correlation with NMSS in the perception and mood domain in patients with PSP but not in those with PD. Compared to PD, MSA presented enhanced FC in theta and delta bands in the posterior region, while PSP revealed decreased FC in the delta band within the frontal-temporal cortex. These findings suggest that QEEG might be a useful tool for evaluating the nonmotor dysfunctions in PD and AP. Our QEEG results suggested that with similar disease duration, the cortical neurodegenerative process was likely exacerbated in patients with PSP, followed by those with PD, and lastly in patients with MSA.

Heterozygous Nonsense Variants in the Ferritin Heavy Chain Gene FTH1 Cause a Novel Pediatric Neuroferritinopathy

Ferritin, the iron storage protein, is composed of light and heavy chain subunits, encoded by FTL and FTH1 , respectively. Heterozygous variants in FTL cause hereditary neuroferritinopathy, a type of neurodegeneration with brain iron accumulation (NBIA). Variants in FTH1 have not been previously associated with neurologic disease. We describe the clinical, neuroimaging, and neuropathology findings of five unrelated pediatric patients with de novo heterozygous FTH1 variants. Children presented with developmental delay, epilepsy, and progressive neurologic decline. Nonsense FTH1 variants were identified using whole exome sequencing, with a recurrent de novo variant (p.F171*) identified in three unrelated individuals. Neuroimaging revealed diffuse volume loss, features of pontocerebellar hypoplasia and iron accumulation in the basal ganglia. Neuropathology demonstrated widespread ferritin inclusions in the brain. Patient-derived fibroblasts were assayed for ferritin expression, susceptibility to iron accumulation, and oxidative stress. Variant FTH1 mRNA transcripts escape nonsense-mediated decay (NMD), and fibroblasts show elevated ferritin protein levels, markers of oxidative stress, and increased susceptibility to iron accumulation. C-terminus variants in FTH1 truncate ferritin's E-helix, altering the four-fold symmetric pores of the heteropolymer and likely diminish iron-storage capacity. FTH1 pathogenic variants appear to act by a dominant, toxic gain-of-function mechanism. The data support the conclusion that truncating variants in the last exon of FTH1 cause a novel disorder in the spectrum of NBIA. Targeted knock-down of mutant FTH1 transcript with antisense oligonucleotides rescues cellular phenotypes and suggests a potential therapeutic strategy for this novel pediatric neurodegenerative disorder.

Efficacy of repetitive transcranial magnetic stimulation in Parkinson's disease: A systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive form of brain stimulation that positively regulates the motor and non-motor symptoms of Parkinson's disease (PD). Although, most reviews and meta-analysis have shown that rTMS intervention is effective in treating motor symptoms and depression, very few have used randomised controlled trials (RCTs) to analyse the efficacy of this intervention in PD. We aimed to review RCTs of rTMS in patients with PD to assess the efficacy of rTMS on motor and non-motor function in patients with PD.

METHODS

In this systematic review and meta-analysis, we searched PubMed, MEDLINE and Web of Science databases for RCTs on rTMS in PD published between January 1, 1988 to January 1, 2022. Eligible studies included sham-controlled RCTs that used rTMS stimulation for motor or non-motor symptoms in PD. RCTs not focusing on the efficacy of rTMS in PD were excluded. Summary data were extracting from those RCTs by two investigators independently. We then calculated standardised mean difference with random-effect models. The main outcome included motor and non-motor examination of scales that were used in PD motor or non-motor assessment. This study was registered with PROSPERO, CRD42022329633.

FINDINGS

Fourteen studies with 469 patients met the criteria for our meta-analysis. Twelve eligible studies with 381 patients were pooled to analyse the efficacy of rTMS on motor function improvement. The effect size on motor scale scores was 0.51 (P < 0.0001) and were not distinctly heterogeneous (I² = 29%). Five eligible studies with 202 patients were collected to evaluate antidepressant-like effects. The effect size on depression scale scores was 0.42 (P = 0.004), and were not distinctly heterogeneous (I² = 25%), indicating a significant anti-depressive effect (P = 0.004). The results suggest that high-frequency of rTMS on primary motor cortex (M1) is effective in improving motor symptoms; while the dorsolateral prefrontal cortex (DLPFC) may be a potentially effective area in alleviating depressive symptom.

INTERPRETATION

The findings suggest that rTMS could be used as a possible adjuvant therapy for PD mainly to improve motor symptoms, but could have potential efficacy on depressive symptoms of PD. However, further investigation is needed.

FUNDING

The National Natural Science Foundation of China (NO: 81873777, 82071414), Initiated Foundation of Zhujiang Hospital (NO: 02020318005), Scientific Research Foundation of Guangzhou (NO: 202206010005), and Science and Technology Program of Guangdong of China (NO: 2020A0505100037).

Radiological hints for differentiation of cerebellar multiple system atrophy from spinocerebellar ataxia

Differentiation cerebellar multiple systemic atrophy (MSA-C) from spinocerebellar ataxia (SCA) is important. The "hot cross bun" sign (HCBS) at pons and magnetic resonance spectroscopy (MRS) are helpful. However, the prevalence of HCBS and the alteration of cerebellar MRS parameters are evolving with disease progression. We hypothesized that since the HCBS and MRS are evolving with time, different parameters for differentiation of MSA-C and SCA are required at different disease stages. The aim of this study was to evaluate the HCBS and MRS changes in patients with MSA-C and SCA at different disease stages. A total of 398 patients with molecularly confirmed SCA (SCA1, 2, 3, 6, 17) and 286 patients diagnosed with probable MSA-C (without mutations in SCA1, 2, 3, 6, 17 genes), who had received brain magnetic resonance imaging (MRI) and MRS from January 2000 to January 2020, were recruited. Twenty-five patients were molecularly identified as having SCA1, 68 as SCA2, 253 as SCA3, 34 as SCA6, and 18 as SCA17. We compared their clinical parameters and neuroimaging features at different disease stages. The presence of HCBS was assessed using an axial T2 fast spin-echo or FLAIR sequence. Proton MRS was recorded with voxel of interest focusing on cerebellar hemispheres and cerebellar vermis and avoiding cerebrospinal fluid spaces space using a single-voxel stimulated echo acquisition mode sequence. We found that patients with MSA-C tend to have a higher prevalence of pontine HCBS, worse Scale for the Assessment and Rating of Ataxia scores, lower cerebellar N-acetyl aspartate (NAA)/creatinine (Cr), and choline (Cho)/Cr, compared to patients with SCA at corresponding disease stages. In MSA-C patients with a disease duration < 1 year and without pontine HCBS, a cerebellar NAA/Cr ≤ 0.79 is a good indicator of the possibility of MSA-C. By using the pontine HCBS and cerebellar MRS, discerning MSA-C from SCA became possible. This study provides cutoff values of MRS to serve as clues in differentiating MSA-C from SCAs.

Erythrocytes Are an Independent Protective Factor for Vascular Cognitive Impairment in Patients With Severe White Matter Hyperintensities

Background and Purpose: Hemoglobin is one of the main proteins in erythrocytes. There are significant correlations between low hemoglobin and white matter hyperintensities (WMH) and cognitive impairment. This study explored whether erythrocytopenia has predictive value for vascular cognitive impairment (VCI) in patients with WMH.

Method: We conducted a cross-sectional study of 302 patients, including 62 with cerebral small vessel disease and 240 with stroke. Basic demographic data and fasting blood were collected. First, all patients were divided into normal cognition (NC), mild VCI (mVCI), and severe VCI (sVCI) groups (subgroups later) based on cognitive behavior scores. Second, all patients were divided into mild WMH (mWMH) and severe WMH (sWMH) groups based on Fazekas scores. The differences in blood markers between different groups or subgroups with different cognitive levels were analyzed by univariate analysis. Then, binary logistic regression was used to analyze the diagnostic value of erythrocyte counts for VCI in the sWMH group, and ordinal logistic regression was used to analyze the predictive value of multiple variables for different cognitive levels.

Results: Univariate analysis showed that erythrocytes, hemoglobin, high-sensitivity C-reactive protein, retinol binding protein and prealbumin were potential blood markers for different cognitive levels in sWMH patients. Among them, erythrocytopenia has good predictive value for the diagnosis of mVCI (AUC = 0.685, P = 0.008) or sVCI (AUC = 0.699, P = 0.003) in patients with sWMH. Multivariate joint analysis showed that erythrocytes were an independent protective factor reducing the occurrence of VCI in patients with sWMH (OR = 0.633, P = 0.045). Even after adjusting for age, there was still a significant difference (P = 0.047).

Conclusion: Erythrocytes are an independent protective factor for VCI in patients with sWMH. Promoting hematopoietic function may have potential value for prevention of cognitive decline in patients with cerebrovascular disease.

Retinal Nerve Fiber Layer Thickness and Associations With Cognitive Impairment in Parkinson’s Disease

Objective

This study intended to investigate whether retinal nerve fiber layer (RNFL) thickness could become a potential marker in patients with Parkinson’s disease with cognitive impairment (PD-CI).

Methods

Fifty-seven PD patients and 45 age-matched healthy controls (HCs) were recruited in our cross-sectional study and completed optical coherence tomography (OCT) evaluations. PD with normal cognition (PD-NC) and cognitive impairment (PD-CI) patients were divided following the 2015 Movement Disorder Society criteria. RNFL thickness was quantified in subfields of the 3.0-mm circle surrounding the optic disk; while a battery of neuropsychiatric assessments was conducted to estimate the Parkinsonism severity. General linear models and one-way ANOVA were adopted to assess RNFL thickness between subgroups with different cognitive statuses; logistic regression analyses were applied to determine the relation between RNFL and PD-CI cases.

Results

Compared with HCs, more thinning of the RNFL was observed in the inferior and temporal sectors in PD patients, especially in the PD-CI group. Inferior RNFL thickness was reduced in PD-CI compared with PD-NC patients. Logistic regression analysis found that inferior RNFL thickness was independently associated with PD-CI cases (odds ratio = 0.923, p = 0.014). Receiver operating characteristic analysis showed that the RNFL-involved combined model provided a high accuracy in screening cognitive deficiency in PD cases (area under the curve = 0.85, p &lt; 0.001).

Conclusion

Reduced RNFL thickness especially in the inferior sector is independently associated with PD-CI patients. Our study present new perspectives into verifying possible indicators for neuropathological processes or disease severity in Parkinsonians with cognitive dysfunction.

Narcolepsy in Parkinson's disease with insulin resistance

Background: Parkinson’s disease (PD) is characterized by its progression of motor-related symptoms such as tremors, rigidity, slowness of movement, and difficulty with walking and balance. Comorbid conditions in PD individuals include insulin resistance (IR) and narcolepsy-like sleep patterns. The intersecting sleep symptoms of both conditions include excessive daytime sleepiness, hallucinations, insomnia, and falling into REM sleep more quickly than an average person. Understanding of the biological basis and relationship of these comorbid disorders with PD may help with early detection and intervention strategies to improve quality of life. Methods: In this study, an integrative genomics and systems biology approach was used to analyze gene expression patterns associated with PD, IR, and narcolepsy in order to identify genes and pathways that may shed light on how these disorders are interrelated. A correlation analysis with known genes associated with these disorders (LRRK2, HLA-DQB1, and HCRT) was used to query microarray data corresponding to brain regions known to be involved in PD and narcolepsy. This includes the hypothalamus, dorsal thalamus, pons, and subcoeruleus nucleus. Risk factor genes for PD, IR, and narcolepsy were also incorporated into the analysis. Results: The PD and narcolepsy signaling networks are connected through insulin and immune system pathways. Important genes and pathways that link PD, narcolepsy, and IR are CACNA1C, CAMK1D, BHLHE41, HMGB1, and AGE-RAGE. Conclusions: We have identified the genetic signatures that link PD with its comorbid disorders, narcolepsy and insulin resistance, from the convergence and intersection of dopaminergic, insulin, and immune system related signaling pathways. These findings may aid in the design of early intervention strategies and treatment regimes for non-motor symptoms in PD patients as well as individuals with diabetes and narcolepsy.

Prolactin and Its Altered Action in Alzheimer's Disease and Parkinson's Disease

BACKGROUND

Prolactin (PRL) is one of the most diverse pituitary hormones and is known to modulate normal neuronal function and neurodegenerative conditions. Many studies have described the influence that PRL has on the central nervous system and addressed its contribution to neurodegeneration, but little is known about the mechanisms responsible for the effects of PRL on neurodegenerative disorders, especially on Alzheimer's disease (AD) and Parkinson's disease (PD).

SUMMARY

We review and summarize the existing literature and current understanding of the roles of PRL on various PRL aspects of AD and PD.

KEY MESSAGES

In general, PRL is viewed as a promising molecule for the treatment of AD and PD. Modulation of PRL functions and targeting of immune mechanisms are needed to devise preventive or therapeutic strategies.

Profiling of Differentially Expressed MicroRNAs in Saliva of Parkinson's Disease Patients

Objective: This study aims to identify differentially expressed salivary miRNAs and validate the diagnostic potential for idiopathic Parkinson's disease (PD). Also, the disease specificity of candidate miRNAs was evaluated between PD, multiple system atrophy (MSA), and essential tremor (ET).

Methods: We collected salivary samples from 50 PD, 20 ET, and 20 MSA patients, as well as 30 healthy controls (HCs). In the discovery phase, salivary miRNA microarray analysis was performed. In-silico analysis was used to investigate the target genes of differentially expressed miRNAs and clustered pathways. In validation phase, RT-qPCR was performed with samples from 30 PD patients and 30 HCs. Subsequently, we investigated candidate miRNAs in all recruited subjects. Receiver operating characteristic curve and Spearman correlation analysis was performed to determine diagnostic usefulness.

Results: We identified 43 miRNAs that were differentially expressed between 5 PD patients and 5 HCs by miRNA microarray analysis. Computational analysis revealed the target genes were clustered in the pathways associated with ubiquitin protein ligase activity. The result of RT-qPCR showed that the miR-29a-3p and miR-29c-3p were found to be significantly downregulated (p = 0.004, p = 0.027), whereas the miR-6756-5p was significantly upregulated in 30 PD patients compared with 30 HCs (p = 0.032). The miR-29a-3p expression level in PD patients was significantly lower than ET patients (p = 0.035), but higher than MSA patients (p < 0.0001). The diagnostic efficacy reached a little higher when the combination of miR-29a-3p and miR-29c-3p.

Conclusion: The miRNA combination of salivary miR-29a-3p and miR-29c-3p has potential to be a diagnostic biomarker for idiopathic PD.

FTD-PSP is an Unusual Clinical Phenotype in A Frontotemporal Dementia Patient with A Novel Progranulin Mutation

Progranulin (GRN) mutations are a major cause of frontotemporal dementia (FTD); the spectrum of clinical phenotypes of FTD is much more extensive than previously reported. The frequency and locations of GRN mutations in Chinese patients with FTD remain uncertain. We performed cDNA sequencing in one sporadic male patient who initially presented FTD symptoms. Brain magnetic resonance imaging (MRI) and positron emission computed tomography/computed tomography (PET/CT) were applied to further confirm the diagnosis of FTD from this patient. Cellular apoptosis and survival test were performed to identify the function of GRN. We identified one novel missense GRN mutation (c.1498G>A, p.V500I) in this patient, who initially presented typical behavioral-variant frontotemporal dementia (bvFTD) features but then presented progressive supranuclear palsy (PSP) clinical characteristics 5 years after onset. Besides, WT GRN protein showed an adequate trophic stimulus to preserve the survival of SH-SY5Y cells in the medium free of serum, while GRN mutation (c.1498G>A, p.V500I) may impair the ability of supporting cell survival. This study owns significant implications for genetic counseling and clinical heterogeneity. We illustrate the fact that FTD presenting features of bvFTD and PSP in one patient could be considered as a specific phenotype in patients with GRN mutations. GRN p.V500I led to the neuronal degeneration in vitro; this finding provides a significant evidence that this mutation may be a new causative mutation in patients with FTD.

Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease

Alzheimer’s disease (AD) has a long preclinical stage that can last for decades prior to progressing toward amnestic mild cognitive impairment (aMCI) and/or dementia. Subjective cognitive decline (SCD) is characterized by self-experienced memory decline without any evidence of objective cognitive decline and is regarded as the later stage of preclinical AD. It has been reported that the changes in structural covariance patterns are affected by AD pathology in the patients with AD and aMCI within the specific large-scale brain networks. However, the changes in structural covariance patterns including normal control (NC), SCD, aMCI, and AD are still poorly understood. In this study, we recruited 42 NCs, 35 individuals with SCD, 43 patients with aMCI, and 41 patients with AD. Gray matter (GM) volumes were extracted from 10 readily identifiable regions of interest involved in high-order cognitive function and AD-related dysfunctional structures. The volume values were used to predict the regional densities in the whole brain by using voxel-based statistical and multiple linear regression models. Decreased structural covariance and weakened connectivity strength were observed in individuals with SCD compared with NCs. Structural covariance networks (SCNs) seeding from the default mode network (DMN), salience network, subfields of the hippocampus, and cholinergic basal forebrain showed increased structural covariance at the early stage of AD (referring to aMCI) and decreased structural covariance at the dementia stage (referring to AD). Moreover, the SCN seeding from the executive control network (ECN) showed a linearly increased extent of the structural covariance during the early and dementia stages. The results suggest that changes in structural covariance patterns as the order of NC-SCD-aMCI-AD are divergent and dynamic, and support the structural disconnection hypothesis in individuals with SCD.

The influence of white matter hyperintensity on cognitive impairment in Parkinson's disease

The aim of this meta‐analysis was to review systematically and to identify the relationship between the severity and location of white matter hyperintensities (WMHs) and the degree of cognitive decline in patients with Parkinson’s disease (PD). We searched the PubMed, EMBASE, Web of Science, Ovid, and Cochrane Library databases for clinical trials of the severity and location of WMHs on the degree of cognitive impairment in PD through October 2020. We conducted the survey to compare the association of WMH burden in patients with PD with mild cognitive impairment (PD‐MCI) versus those with normal cognition (PD‐NC) and in patients with PD with dementia (PDD) versus those with PD without dementia (PD‐ND). Nine studies with PD‐MCI versus PD‐NC and 10 studies with PDD versus PD‐ND comparisons were included. The WMH burden in PD‐MCI patients was significantly different compared to that in PD‐NC patients (standard mean difference, SMD = 0.39, 95% CI: 0.12 to 0.66, p = 0.005), while there was no correlation shown in the age‐matched subgroup of the comparison. In addition, PDD patients had a significantly higher burden of WMHs (SMD = 0.8, 95% CI: 0.44 to 1.71, p < 0.0001), especially deep white matter hyperintensities (SMD = 0.54, 95% CI: 0.36 to 0.73, p < 0.00001) and periventricular hyperintensities (SMD = 0.70, 95% CI: 0.36 to 1.04, p < 0.0001), than PD‐NC patients, regardless of the adjustment of age. WMHs might be imaging markers for cognitive impairment in PDD but not in PD‐MCI, regardless of age, vascular risk factors, or race. Further prospective studies are needed to validate the conclusions.

Integrative Analysis of lncRNA and mRNA and Profiles in Postoperative Delirium Patients

Delirium is a common serious complication that often occurs after major surgery. The goals of this study were to explore the expression profiles and functional networks of long non-coding RNAs (lncRNAs) and mRNAs in patients of postoperative delirium (POD). Microarray analysis was performed on the peripheral blood samples to identify differentially expressed (DE) lncRNAs and mRNAs in 4 POD patients and 4 non-POD volunteers. DE lncRNAs and mRNAs were validated by quantitative reverse transcription PCR (RT-qPCR). Bioinformatic analyses were performed to identify the critical biological functions and signaling pathways involved in POD. A total of 1195 DE lncRNAs and 735 DE mRNAs were identified between the POD and non-POD groups. Verified by the RT-qPCR, we identified 14 DE lncRNAs that may relate to the pathogenesis of POD. These 14 DE lncRNAs play important regulatory roles in “glutamate and 5-hydroxytryptamine,” “synaptotagmin 7,” “transient receptor potential channel,” “interleukin-2 production.” There was a regulatory relationship between lncRNA ENST00000530057 and synaptotagmin (Syt) 7 mRNA. The mRNA level of PCLO was up-regulated in POD group. This study showed abundant DE lncRNAs and mRNAs in POD that might help in deciphering the disease pathogenesis.