Metabolic brain biomarkers have been incorporated in various diagnostic guidelines of neurodegenerative diseases, recently. To improve their diagnostic accuracy a biologically and clinically ...homogeneous sample is needed for their identification. Alzheimer's disease-related pattern (ADRP) has been identified previously in cohorts of clinically diagnosed patients with dementia due to Alzheimer's disease (AD), meaning that its diagnostic accuracy might have been reduced due to common clinical misdiagnosis. In our study, we aimed to identify ADRP in a cohort of AD patients with CSF confirmed diagnosis, validate it in large out-of-sample cohorts and explore its relationship with patients' clinical status. For identification we analyzed 2-
FFDG PET brain scans of 20 AD patients and 20 normal controls (NCs). For validation, 2-
FFDG PET scans from 261 individuals with AD, behavioral variant of frontotemporal dementia, mild cognitive impairment and NC were analyzed. We identified an ADRP that is characterized by relatively reduced metabolic activity in temporoparietal cortices, posterior cingulate and precuneus which co-varied with relatively increased metabolic activity in the cerebellum. ADRP expression significantly differentiated AD from NC (AUC = 0.95) and other dementia types (AUC = 0.76-0.85) and its expression correlated with clinical measures of global cognition and neuropsychological indices in all cohorts.
Dopaminergic pathway is the most disrupted pathway in the pathogenesis of Parkinson's disease. Several studies reported associations of dopaminergic genes with the occurrence of adverse events of ...dopaminergic treatment. However, none of these studies adopted a pathway based approach. The aim of this study was to comprehensively evaluate the influence of selected single nucleotide polymorphisms of key dopaminergic pathway genes on the occurrence of motor and non-motor adverse events of dopaminergic treatment in Parkinson's disease. In total, 231 Parkinson's disease patients were enrolled. Demographic and clinical data were collected. Genotyping was performed for 16 single nucleotide polymorphisms from key dopaminergic pathway genes. Logistic and Cox regression analyses were used for evaluation. Results were adjusted for significant clinical data. We observed that carriers of at least one
rs165815 C allele had lower odds for developing visual hallucinations (OR = 0.34; 95% CI = 0.16-0.72;
= 0.004), while carriers of at least one
rs6280 C allele and CC homozygotes had higher odds for this adverse event (OR = 1.88; 95% CI = 1.00-3.54;
= 0.049 and OR = 3.31; 95% CI = 1.37-8.03;
= 0.008, respectively). Carriers of at least one
rs921451 C allele and CT heterozygotes had higher odds for orthostatic hypotension (OR = 1.86; 95% CI = 1.07-3.23;
= 0.028 and OR = 2.30; 95% CI = 1.26-4.20;
= 0.007, respectively). Heterozygotes for
rs3837091 and
rs628031 AA carriers also had higher odds for orthostatic hypotension (OR = 1.94; 95% CI = 1.07-3.51;
= 0.028 and OR = 2.57; 95% CI = 1.11-5.95;
= 0.028, respectively). Carriers of the
rs628031 AA genotype had higher odds for peripheral edema and impulse control disorders (OR = 4.00; 95% CI = 1.62-9.88;
= 0.003 and OR = 3.16; 95% CI = 1.03-9.72;
= 0.045, respectively). Finally, heterozygotes for
rs628031 and carriers of at least one
rs628031 A allele had lower odds for dyskinesia (OR = 0.48; 95% CI = 0.24-0.98,
= 0.043 and OR = 0.48; 95% CI = 0.25-0.92;
= 0.027, respectively). Gene-gene interactions, more specifically
, and
, also significantly influenced the occurrence of some adverse events. Additionally, haplotypes of
and
were associated with the occurrence of visual hallucinations (AT vs. GC: OR = 0.34; 95% CI = 0.16-0.72;
= 0.005) and orthostatic hypotension (ATG vs. ACG: OR = 2.48; 95% CI: 1.01-6.07;
= 0.047), respectively. Pathway based approach allowed us to identify new potential candidates for predictive biomarkers of adverse events of dopaminergic treatment in Parkinson's disease, which could contribute to treatment personalization.
Inflammation and oxidative stress are recognized as important contributors to Parkinson's disease pathogenesis. As such, genetic variability in these pathways could have a role in susceptibility for ...the disease as well as in the treatment outcome. Dopaminergic treatment is effective in management of motor symptoms, but poses a risk for motor and non-motor adverse events. Our aim was to evaluate the impact of selected single-nucleotide polymorphisms in genes involved in inflammation and oxidative stress on Parkinson's disease susceptibility and the occurrence of adverse events of dopaminergic treatment.
In total, 224 patients were enrolled, and their demographic and clinical data on the disease course were collected. Furthermore, a control group of 146 healthy Slovenian blood donors were included for Parkinson's disease' risk evaluation. Peripheral blood was obtained for DNA isolation. Genotyping was performed for NLRP3 rs35829419, CARD8 rs2043211, IL1β rs16944, IL1β rs1143623, IL6 rs1800795, CAT rs1001179, CAT rs10836235, SOD2 rs4880, NOS1 rs2293054, NOS1 rs2682826, TNF-α rs1800629, and GPX1 rs1050450. Logistic regression was used for analysis of possible associations.
We observed a nominally significant association of the IL1β rs1143623 C allele with the risk for Parkinson's disease (OR = 0.59; 95%CI = 0.38-0.92, p = 0.021). CAT rs1001179 A allele was significantly associated with peripheral edema (OR = 0.32; 95%CI = 0.15-0.68; p = 0.003). Other associations observed were only nominally significant after adjustments: NOS1 rs2682826 A allele and excessive daytime sleepiness and sleep attacks (OR = 1.75; 95%CI = 1.00-3.06, p = 0.048), SOD2 rs4880 T allele and nausea/vomiting (OR = 0.49, 95%CI = 0.25-0.94; p = 0.031), IL1β rs1143623 C allele and orthostatic hypotension (OR = 0.57, 95%CI = 0.32-1.00, p = 0.050), and NOS1 rs2682826 A allele and impulse control disorders (OR = 2.59; 95%CI = 1.09-6.19; p = 0.032). We did not find any associations between selected polymorphisms and motor adverse events.
Apart from some nominally significant associations, one significant association between CAT genetic variability and peripheral edema was observed as well. Therefore, the results of our study suggest some links between genetic variability in inflammation- and oxidative stress-related pathways and non-motor adverse events of dopaminergic treatment. However, the investigated polymorphisms do not play a major role in the occurrence of the disease and the adverse events of dopaminergic treatment.
Vitamin D is a lipid-soluble molecule and an important transcriptional regulator in many tissues and organs, including the brain. Its role has been demonstrated also in Parkinson's disease (PD) ...pathogenesis. Vitamin D receptor (VDR) is responsible for the initiation of vitamin D signaling cascade. The aim of this study was to assess the associations of
genetic variability with PD risk and different PD-related phenotypes. We genotyped 231 well characterized PD patients and 161 healthy blood donors for six
single nucleotide polymorphisms, namely rs739837, rs4516035, rs11568820, rs731236, rs2228570, and rs1544410. We observed that
rs2228570 is associated with PD risk (
< 0.001). Additionally, we observed associations of specific
genotypes with adverse events of dopaminergic treatment.
rs1544410 (GG vs. GA + AA:
= 0.005; GG vs. GA:
= 0.009) was associated with the occurrence of visual hallucinations and
rs739837 (TT vs. GG:
= 0.036), rs731236 (TT vs. TC + CC:
= 0.011; TT vs. TC:
= 0.028; TT vs. CC:
= 0.035), and rs1544410 (GG vs. GA:
= 0.014) with the occurrence of orthostatic hypotension. We believe that the reported study may support personalized approach to PD treatment, especially in terms of monitoring vitamin D level and vitamin D supplementation in patients with high risk
genotypes.
Background
Metabolic brain imaging with 2-
18
Ffluoro-2-deoxy-D-glucose positron emission tomography (FDG PET) is a supportive diagnostic and differential diagnostic tool for neurodegenerative ...dementias. In the clinic, scans are usually visually interpreted. However, computer-aided approaches can improve diagnostic accuracy. We aimed to build two machine learning classifiers, based on two sets of FDG PET-derived features, for differential diagnosis of common dementia syndromes.
Methods
We analyzed FDG PET scans from three dementia cohorts 63 dementia due to Alzheimer’s disease (AD), 79 dementia with Lewy bodies (DLB) and 23 frontotemporal dementia (FTD), and 41 normal controls (NCs). Patients’ clinical diagnosis at follow-up (25 ± 20 months after scanning) or cerebrospinal fluid biomarkers for Alzheimer’s disease was considered a gold standard. FDG PET scans were first visually evaluated. Scans were pre-processed, and two sets of features extracted: (1) the expressions of previously identified metabolic brain patterns, and (2) the mean uptake value in 95 regions of interest (ROIs). Two multi-class support vector machine (SVM) classifiers were tested and their diagnostic performance assessed and compared to visual reading. Class-specific regional feature importance was assessed with Shapley Additive Explanations.
Results
Pattern- and ROI-based classifier achieved higher overall accuracy than expert readers (78% and 80% respectively, vs. 71%). Both SVM classifiers performed similarly to one another and to expert readers in AD (F1 = 0.74, 0.78, and 0.78) and DLB (F1 = 0.81, 0.81, and 0.78). SVM classifiers outperformed expert readers in FTD (F1 = 0.87, 0.83, and 0.63), but not in NC (F1 = 0.71, 0.75, and 0.92). Visualization of the SVM model showed bilateral temporal cortices and cerebellum to be the most important features for AD; occipital cortices, hippocampi and parahippocampi, amygdala, and middle temporal lobes for DLB; bilateral frontal cortices, middle and anterior cingulum for FTD; and bilateral angular gyri, pons, and vermis for NC.
Conclusion
Multi-class SVM classifiers based on the expression of characteristic metabolic brain patterns or ROI glucose uptake, performed better than experts in the differential diagnosis of common dementias using FDG PET scans. Experts performed better in the recognition of normal scans and a combined approach may yield optimal results in the clinical setting.
Background Parkinson’s disease is associated with increased impulsivity, which can be divided into several domains: motor (consisting of proactive and reactive subdomains), reflection, and cognitive ...impulsivity. Evidence suggests that both dopaminergic medication and subthalamic nucleus deep brain stimulation can affect impulsivity. Therefore, we set out to investigate the effects of dopaminergic medication and subthalamic nucleus deep brain stimulation on motor, reflection, and cognitive impulsivity in Parkinson’s disease patients. Methods Twenty Parkinson’s disease patients who underwent subthalamic nucleus deep brain stimulation were tested ON and OFF dopaminergic medication and ON and OFF subthalamic nucleus deep brain stimulation. They performed three different impulsivity tasks: the AX continuous performance task (AX-CPT) to test for motor impulsivity, the Beads task for reflection impulsivity, and the Delay discounting task for cognitive impulsivity. Results The combination of subthalamic nucleus deep brain stimulation and dopaminergic medication led to an increase in motor impulsivity ( p = 0.036), both proactive ( p = 0.045) and reactive ( p = 0.006). There was no effect of either dopaminergic medication or subthalamic nucleus deep brain stimulation on reflection and cognitive impulsivity. Conclusion The combination of dopaminergic medication and subthalamic nucleus deep brain stimulation leads to increased motor, but not cognitive or reflection, impulsivity in patients with Parkinson’s disease. Both proactive and reactive motor impulsivity were impaired by the combination of dopaminergic medication and subthalamic nucleus deep brain stimulation.
Background
Alzheimer’s disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer’s disease (AD). While ADRP is being introduced into research, the effect of the size of the ...identification cohort and the effect of the resolution of identification and validation images on ADRP’s performance need to be clarified.
Methods
240 2-
18
Ffluoro-2-deoxy-
d
-glucose positron emission tomography images 120 AD/120 cognitive normals (CN) were selected from the Alzheimer's disease neuroimaging initiative database. A total of 200 images (100 AD/100 CN) were used to identify different versions of ADRP using a scaled subprofile model/principal component analysis. For this purpose, five identification groups were randomly selected 25 times. The identification groups differed in the number of images (20 AD/20 CN, 30 AD/30 CN, 40 AD/40 CN, 60 AD/60 CN, and 80 AD/80 CN) and image resolutions (6, 8, 10, 12, 15 and 20 mm). A total of 750 ADRPs were identified and validated through the area under the curve (AUC) values on the remaining 20 AD/20 CN with six different image resolutions.
Results
ADRP’s performance for the differentiation between AD patients and CN demonstrated only a marginal average AUC increase, when the number of subjects in the identification group increases (AUC increase for about 0.03 from 20 AD/20 CN to 80 AD/80 CN). However, the average of the lowest five AUC values increased with the increasing number of participants (AUC increase for about 0.07 from 20 AD/20 CN to 30 AD/30 CN and for an additional 0.02 from 30 AD/30 CN to 40 AD/40 CN). The resolution of the identification images affects ADRP’s diagnostic performance only marginally in the range from 8 to 15 mm. ADRP’s performance stayed optimal even when applied to validation images of resolution differing from the identification images.
Conclusions
While small (20 AD/20 CN images) identification cohorts may be adequate in a favorable selection of cases, larger cohorts (at least 30 AD/30 CN images) shall be preferred to overcome possible/random biological differences and improve ADRP’s diagnostic performance. ADRP’s performance stays stable even when applied to the validation images with a resolution different than the resolution of the identification ones.
Deep brain stimulation of the subthalamic nucleus (STN DBS) has become an accepted tool for the treatment of Parkinson's disease (PD). Although the precise mechanism of action of this intervention is ...unknown, its effectiveness has been attributed to the modulation of pathological network activity. We examined this notion using positron emission tomography (PET) to quantify stimulation-induced changes in the expression of a PD-related covariance pattern (PDRP) of regional metabolism. These metabolic changes were also compared with those observed in a similar cohort of patients undergoing STN lesioning.
We found that PDRP activity declined significantly (
P < 0.02) with STN stimulation. The degree of network modulation with DBS did not differ from that measured following lesioning (
P = 0.58). Statistical parametric mapping (SPM) revealed that metabolic reductions in the internal globus pallidus (GPi) and caudal midbrain were common to both STN interventions (
P < 0.01), although declines in GPi were more pronounced with lesion. By contrast, elevations in posterior parietal metabolism were common to the two procedures, albeit more pronounced with stimulation.
These findings indicate that suppression of abnormal network activity is a feature of both STN stimulation and lesioning. Nonetheless, these two interventions may differ metabolically at a regional level.
Device-aided therapies (DAT), such as continuous subcutaneous apomorphine infusion (CSAI), levodopa-carbidopa intestinal gel infusion (LCIG), and deep brain stimulation of the subthalamic nucleus ...(STN-DBS), have markedly changed the treatment landscape of advanced Parkinson's disease (aPD). In some patients, it is necessary to switch or combine DATs for various reasons. The aim of this retrospective study was to explore the frequency and reasons for switching between or combining DATs in two movement disorders centres in Slovenia and Israel.
We collected and analysed demographic and clinical data from aPD patients who switched between or combined DATs. Motor and non-motor reasons, adverse events for switching/combining, and their frequency were examined, as was the effect of DAT using the Global Improvement subscale of the Clinical Global Impression Scale, Movement Disorders Society Unified Parkinson's Disease Rating Scale part III, Mini Mental State Examination, and Parkinson's Disease Questionnaire 39. Descriptive statistics and non-parametric tests were used to analyse the data.
Of 505 aPD patients treated with DATs at both centres between January 2009 and June 2021, we identified in a total of 30 patients (6%) who either switched DAT (
= 24: 7
, 1
, 5
, 8
, 1
, 1
, and 1
) or combined DATs (
= 6:5
and 1
). In most of these patients, an inadequate control of motor symptoms was the main reason for switching or combining DATs, but non-motor reasons (related to the disease and/or DAT) were also identified.
Switching between and combining DATs is uncommon, but in some patients brings substantial clinical improvement and should be considered in those who have either inadequate symptom control on DAT treatment or have developed DAT-related complications.
•Dementia with Lewy bodies is associated with a unique metabolic brain network.•Individual patient expression levels for this network correlate with measures of cognitive dysfunction and ...survival.•The topography of this network differs from that associated with cognitive impairment in PD patients.•Expression levels for this network can help differentiate between the two most common dementia disorders.
Dementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia, that shares clinical and metabolic similarities with both Alzheimer’s and Parkinson’s disease. In this study we aimed to identify a DLB-related pattern (DLBRP), study its relationship with other metabolic brain patterns and explore its diagnostic and prognostic value.
A cohort of 79 participants with DLB, 63 with dementia due to Alzheimer’s disease (AD) and 41 normal controls (NCs) and their 2-18FFDG PET scans were analysed for identification and validation of DLBRP. Voxel-wise correlation and multiple linear regression were used to study the relation between DLBRP and Alzheimer’s disease-related pattern (ADRP), Parkinson’s disease-related pattern (PDRP) and PD-related cognitive pattern (PDCP). Diagnostic and prognostic value of DLBRP and of modified DLBRP after accounting for ADRP overlap (DLBRP ⊥ ADRP), were explored.
The newly identified DLBRP shared topographic similarities with ADRP (R2 = 24%) and PDRP (R2 = 37%), but not with PDCP. We could accurately discriminate between DLB and NC (AUC = 0.99) based on DLBRP expression, and between DLB and AD (AUC = 0.87) based on DLBRP ⊥ ADRP expression. DLBRP expression correlated with cognitive impairment, but the correlation was lost after accounting for ADRP overlap. DLBRP and DLBRP ⊥ ADRP correlated with patients’ survival time.
DLBRP has proven to be a specific metabolic brain biomarker of DLB, sharing similarities with ADRP and PDRP, but not PDCP. We observed a similar metabolic mechanism underlying cognitive impairment in DLB and AD. DLB-specific metabolic changes were more detrimental for overall survival.
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