Asymptomatic carriers of the p.A53T SNCA mutation: data from the PPMI study

IntroductionThere has been great interest in the prodromal phase of Parkinson’s disease (PD), especially in subjects who are asymptomatic carriers of genetic mutations leading to PD because of the high risk to convert to PD. The objective of the present study was to assess non motor characteristics of asymptomatic p.A53T mutation carriers (A53T-AC) compared with healthy controls (HC).MethodsWe compared 12 A53T-AC with 36 matched HC enrolled into in the Parkinson’s Progression Markers Initiative (PPMI) study. Baseline data extracted from the PPMI database, contained demographics and non-motor symptoms (e.g. the Montreal Cognitive Assessment (MOCA) for cognition, the University of Pennsylvania Smell Identification Test (UPSIT) for olfaction, MDS-UPDRS I etc.)ResultsThe mean UPSIT score was lower in A53T-AC vs HC (p =0.000). MoCA test showed a trend towards lower scores in A53T AC. We found a significant positive correlation between UPSIT score and MOCA in A53T-AC (rs = 0,68, p=0,021) but not in HC. Total scores for MDS-UPDRS I did not differ between the groups but the subscore of anxiety was more prevalent in A53T-AC.ConclusionThe more affected olfaction in A53T-AC may indicate that olfactory function is affected quite early in A53T carriers. The strong positive correlation between UPSIT and MOCA in the A53T-AC group may indicate that cognitive dysfunction and olfactory impairment progress alongside, prior to nigrostriatal degeneration. Anxiety was also more prevalent in A53T-AC and may represent an additional prodromal feature in this group of subjects.

Correlation of Dopaminergic Denervation and the Progression of Autonomic Dysfunctions in Different Clinical Subtypes of Parkinson’s Disease

Background. Autonomic dysfunctions occur in the early stage of Parkinson’s disease (PD) and impact the quality of life during the progression of the disease. In this study, we evaluated the serial progression of autonomic dysfunctions between different subtypes of a prospective PD cohort. Materials and Methods. From the Parkinson’s Progression Markers Initiative (PPMI) database, 325 PD patients (age: 61.2 ± 9.7, M : F = 215 : 110) were enrolled. Patients were subgrouped into tremor-dominant (TD), indeterminate, and postural instability and gait disorder (PIGD) subtypes. The progression of autonomic dysfunctions and dopaminergic denervation from I-123 FP-CIT SPECT images of each group were analyzed and compared at baseline, 12 months, 24 months, and 48 months of follow-up periods. Results. The SCOPA-AUT score of the indeterminate subtype was significantly higher than that of the TD subtype ( P < 0.05 ) at baseline and was significantly higher than that of both TD and PIGD subtypes ( P < 0.05 ) at 48 months. The indeterminate subtype had the most significant correlation between the aggravation of dopaminergic denervation in I-123 FP-CIT SPECT images and the increase of SCOPA-AUT scores during 48 months of follow-up (r = 0.56, P < 0.01 ). Conclusions. Autonomic dysfunctions were most severe in the indeterminate subtype throughout the 48 months of the follow-up period, with a significant correlation with dopaminergic denervation. We suggest a positive relationship between dopaminergic denervation and autonomic dysfunctions of the indeterminate subtype, beginning from the early stage of PD.

Effect of data leakage in brain MRI classification using 2D convolutional neural networks

In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high performances reported in numerous studies, developing CNN models with good generalization abilities is still a challenging task due to possible data leakage introduced during cross-validation (CV). In this study, we quantitatively assessed the effect of a data leakage caused by 3D MRI data splitting based on a 2D slice-level using three 2D CNN models to classify patients with Alzheimer’s disease (AD) and Parkinson’s disease (PD). Our experiments showed that slice-level CV erroneously boosted the average slice level accuracy on the test set by 30% on Open Access Series of Imaging Studies (OASIS), 29% on Alzheimer’s Disease Neuroimaging Initiative (ADNI), 48% on Parkinson’s Progression Markers Initiative (PPMI) and 55% on a local de-novo PD Versilia dataset. Further tests on a randomly labeled OASIS-derived dataset produced about 96% of (erroneous) accuracy (slice-level split) and 50% accuracy (subject-level split), as expected from a randomized experiment. Overall, the extent of the effect of an erroneous slice-based CV is severe, especially for small datasets.

Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort

Renal cell carcinoma (RCC) is among the 10 most common cancer entities and can be categorised into distinct subtypes by differential expression of Krebs cycle genes. We investigated the predictive value of several targeted metabolites with regards to tumour stages and patient survival in an unselected cohort of 420 RCCs. Unsupervised hierarchical clustering of metabolite ratios identified two main clusters separated by α-ketoglutarate (α-KG) levels and sub-clusters with differential levels of the oncometabolite 2-hydroxyglutarate (2HG). Sub-clusters characterised by high 2HG were enriched in higher tumour stages, suggesting metabolite profiles might be suitable predictors of tumour stage or survival. Bootstrap forest models based on single metabolite signatures showed that lactate, 2HG, citrate, aspartate, asparagine, and glutamine better predicted the cancer-specific survival (CSS) of clear cell RCC patients, whereas succinate and α-ketoglutarate were better CSS predictors for papillary RCC patients. Additionally, this assay identifies rare cases of tumours with SDHx mutations, which are caused predominantly by germline mutations and which predispose to development of different neoplasms. Hence, analysis of selected metabolites should be further evaluated for potential utility in liquid biopsies, which can be obtained using less invasive methods and potentially facilitate disease monitoring for both patients and caregivers.

High diagnostic performance of independent alpha-synuclein seed amplification assays for detection of early Parkinson’s disease

Alpha-synuclein seed amplification assays (αSyn-SAAs) are promising diagnostic tools for Parkinson’s disease (PD) and related synucleinopathies. They enable detection of seeding-competent alpha-synuclein aggregates in living patients and have shown high diagnostic accuracy in several PD and other synucleinopathy patient cohorts. However, there has been confusion about αSyn-SAAs for their methodology, nomenclature, and relative accuracies when performed by various laboratories. We compared αSyn-SAA results obtained from three independent laboratories to evaluate reproducibility across methodological variations. We utilized the Parkinson’s Progression Markers Initiative (PPMI) cohort, with DATSCAN data available for comparison, since clinical diagnosis of early de novo PD is critical for neuroprotective trials, which often use dopamine transporter imaging to enrich their cohorts. Blinded cerebrospinal fluid (CSF) samples for a randomly selected subset of PPMI subjects (30 PD, 30 HC, and 20 SWEDD), from both baseline and year 3 collections for the PD and HC groups (140 total CSF samples) were analyzed in parallel by each lab according to their own established and optimized αSyn-SAA protocols. The αSyn-SAA results were remarkably similar across laboratories, displaying high diagnostic performance (sensitivity ranging from 86 to 96% and specificity from 93 to 100%). The assays were also concordant for samples with results that differed from clinical diagnosis, including 2 PD patients determined to be clinically inconsistent with PD at later time points. All three assays also detected 2 SWEDD subjects as αSyn-SAA positive who later developed PD with abnormal DAT-SPECT. These multi-laboratory results confirm the reproducibility and value of αSyn-SAA as diagnostic tools, illustrate reproducibility of the assay in expert hands, and suggest that αSyn-SAA has potential to provide earlier diagnosis with comparable or superior accuracy to existing methods.

Sex-Related Longitudinal Change of Motor, Non-Motor, and Biological Features in Early Parkinson’s Disease

Background: Investigation of sex-related motor and non-motor differences and biological markers in Parkinson’s disease (PD) may improve precision medicine approach. Objective: To examine sex-related longitudinal changes in motor and non-motor features and biologic biomarkers in early PD. Methods: We compared 5-year longitudinal changes in de novo, untreated PD men and women (at baseline N = 423; 65.5%male) of the Parkinson’s Progression Markers Initiative (PPMI), assessing motor and non-motor manifestations of disease; and biologic measures in cerebrospinal fluid (CSF) and dopamine transporter deficit on DaTscanTM uptake. Results: Men experienced greater longitudinal decline in self-reported motor (p < 0.001) and non-motor (p = 0.009) aspects of experiences of daily living, such that men had a yearly increase in MDS-UPDRS part II by a multiplicative factor of 1.27 compared to women at 0.7, while men had a yearly increase in MDS-UPDRS part I by a multiplicative factor of 0.98, compared to women at 0.67. Compared to women, men had more longitudinal progression in clinician-assessed motor features in the ON medication state (p = 0.010) and required higher dopaminergic medication dosages over time (p = 0.014). Time to reach specific disease milestones and longitudinal changes in CSF biomarkers and DaTscanTM uptake were not different by sex. Conclusion: Men showed higher self-assessed motor and non-motor burden of disease, with possible contributions from suboptimal dopaminergic therapeutic response in men. However, motor features of disease evaluated with clinician-based scales in the OFF medication state, as well as biological biomarkers do not show specific sex-related progression patterns.

Blood Neurofilament Light Chain in Parkinson’s Disease: Comparability between Parkinson’s Progression Markers Initiative (PPMI) and Asian Cohorts

Elevated blood neurofilament light chain (NfL), which indicates the loss of neuronal integrity, is increasingly implicated as a diagnostic and outcome-predicting biomarker for neurological diseases. However, its diagnostic implication for Parkinson’s disease (PD) remains unclear, with conflicting data reported by several studies. This may result from the demographic heterogeneity of the studied cohorts. The present study investigated the comparability of blood NfL between a domestic, single-centered PD cohort from Shuang Ho Hospital (SHH) in Taiwan, with the large international, multi-center cohort, Parkinson’s Progression Markers Initiative (PPMI). In the SHH PD cohort, with 61 people with PD (PwP) and 25 healthy non-PD controls, plasma NfL unexpectedly was significantly higher in the control group than PwP (14.42 ± 13.84 vs. 9.39 ± 6.91 pg/mL, p = 0.05). Interestingly, subgroup analysis revealed a non-significant difference of plasma NfL levels in male PwP compared with controls (8.58 ± 6.21 vs. 7.25 ± 4.43 pg/mL, p =0.575), whereas NfL levels were significantly lower in the female PwP group than in their healthy control peers (10.29 ± 7.62 vs. 17.79 ± 15.52 pg/mL, p = 0.033). Comparative analysis of the SHH and PPMI cohorts revealed a comparable gender-stratified distribution of blood NfL based on approximate theoretical quantiles. After adjusting for age and gender, no apparent difference in NfL value distribution was observed between the SHH and PPMI cohorts’ control or PD groups. Significant downregulation of blood NfL levels were positively correlated with a reduced probability of having a PD diagnosis in both cohorts. These results demonstrated that the adjustment for demographic background enhances comparability between cohorts, and may be required to eliminate covariate/confounder-associated conflict in blood NfL results between different PD studies. This experience may be beneficial to other researchers around the world who are saddled with limited study participants, especially as data from small cohort sizes are often at greater risk of being skewed by specific variables.

Cluster Analysis of Categorical Variables of Parkinson’s Disease Patients

Parkinson’s disease (PD) is a chronic disease. No treatment stops its progression, and it presents symptoms in multiple areas. One way to understand the PD population is to investigate the clustering of patients by demographic and clinical similarities. Previous PD cluster studies included scores from clinical surveys, which provide a numerical but ordinal, non-linear value. In addition, these studies did not include categorical variables, as the clustering method utilized was not applicable to categorical variables. It was discovered that the numerical values of patient age and disease duration were similar among past cluster results, pointing to the need to exclude these values. This paper proposes a novel and automatic discovery method to cluster PD patients by incorporating categorical variables. No estimate of the number of clusters is required as input, whereas the previous cluster methods require a guess from the end user in order for the method to be initiated. Using a patient dataset from the Parkinson’s Progression Markers Initiative (PPMI) website to demonstrate the new clustering technique, our results showed that this method provided an accurate separation of the patients. In addition, this method provides an explainable process and an easy way to interpret clusters and describe patient subtypes.

Apathy: an underestimated feature in GBA and LRRK2 non-manifesting mutation carriers.

Introduction: Higher prevalence of motor and non-motor features has been observed in non-manifesting mutation carriers of Parkinson s Disease (PD) compared to Healthy Controls (HC). The aim was to detect the differences between GBA and LRRK2 mutation carriers without PD and HC on neuropsychiatric symptoms. Methods: This is a cross-sectional retrospective study of non-manifesting GBA and LRRK2 mutation carriers and HC enrolled into Parkinsons Progression Markers Initiative (PPMI). Data extracted from the PPMI database contained: demographics and performance in MoCA scale and MDS-UPDRS scale part 1A (neuropsychiatric symptoms). All six features were treated as both continuous (MDS-UPDRS individual scores) and categorical variables (MDS-UPDRS individual score>0 and MDS-UPDRS individual score=0). Logistic regression analyses were applied to evaluate the association between mutation carrying status and neuropsychiatric symptoms. Results: In this study, the neuropsychiatric evaluation was performed in 285 GBA non-manifesting carriers, 369 LRRK2 non-manifesting carriers and 195 HC. We found that GBA non-manifesting mutation carriers were 2.6 times more likely to present apathy compared to HC, even after adjustment for covariates (adjusted OR=2.6, 95% CI=1.1-6.3, p=0.031). The higher percentage of apathy for LRRK2 carriers compared to HC was marginally non-significant. Other neuropsychiatric symptoms, such as psychotic or depressive manifestations, did not differ between groups. Conclusion: Symptoms of apathy could be present in the prediagnostic period of non-manifesting mutation carriers, especially, GBA. Longitudinal data, including detailed neuropsychiatric evaluation and neuroimaging, would be essential to further investigate the pathophysiological basis of this finding

TOMM40 ‘523’ poly-T repeat length is a determinant of longitudinal cognitive decline in Parkinson’s disease

The translocase of outer mitochondrial membrane 40 (TOMM40) ‘523’ polymorphism has previously been associated with age of Alzheimer’s disease onset and cognitive functioning in non-pathological ageing, but has not been explored as a candidate risk marker for cognitive decline in Parkinson’s disease (PD). Therefore, this longitudinal study investigated the role of the ‘523’ variant in cognitive decline in a patient cohort from the Parkinson’s Progression Markers Initiative. As such, a group of 368 people with PD were assessed annually for cognitive performance using multiple neuropsychological protocols, and were genotyped for the TOMM40 ‘523’ variant using whole-genome sequencing data. Covariate-adjusted generalised linear mixed models were utilised to examine the relationship between TOMM40 ‘523’ allele lengths and cognitive scores, while taking into account the APOE ε genotype. Cognitive scores declined over the 5-year study period and were lower in males than in females. When accounting for APOE ε4, the TOMM40 ‘523’ variant was not robustly associated with overall cognitive performance. However, in APOE ε3/ε3 carriers, who accounted for ~60% of the whole cohort, carriage of shorter ‘523’ alleles was associated with more severe cognitive decline in both sexes, while carriage of the longer alleles in females were associated with better preservation of global cognition and a number of cognitive sub-domains, and with a delay in progression to dementia. The findings indicate that when taken in conjunction with the APOE genotype, TOMM40 ‘523’ allele length is a significant independent determinant and marker for the trajectory of cognitive decline and risk of dementia in PD.