Background
Lewy Body Dementia (LBD) is the second most common neurodegenerative dementia. To date, no validated biochemical marker is available to support clinical diagnosis. The development of the ...Real‐Time Quaking‐Induced Conversion (RT‐QuIC) assay for detecting alpha‐synuclein (aSyn) seeds in biological samples can be a sensitive biomarker specific for the diagnosis easily applicable in a clinical setting. We aimed to describe the diagnostic performance of RT‐QuIC aSyn assay in cerebrospinal fluid (CSF) to diagnose LBD in a clinical cohort with cognitive impairment.
Method
A cohort of subjects with cognitive impairment (neurodegenerative and non‐neurodegenerative) with available CSF sample at the moment of first evaluation was selected by convenience sample in our database. Subjects had clinical follow‐ups ranging from 6 months to 12 years and current clinical diagnosis according to established consensus criteria. The diagnostic performance of RT‐QuIC aSyn for the diagnosis of LBD were evaluated.
Result
The test was evaluated in 155 subjects (age 65 years (SD 11), MMSE 24 (SD 4.5), 56% male) with the following clinical diagnoses: LBD (n = 40), Alzheimer’s disease (AD) (n = 73)(all with compatible CSF profile), frontotemporal dementia (FTD) (n = 7), non‐neurodegenerative mild cognitive impairment (MCI) (n = 21), other neurodegenerative diagnoses (n = 12) and healthy controls (n = 2). aSyn was detected in 33/40 (83%) LBD patients, 7/73 (10%) AD, 0/7 FTD patients, 0/21 MCI patients, 0/12 patients with other neurodegenerative diseases and 0/2 healthy controls.
Only 3/7 (42%) LBD subjects with a negative RT‐QuIC asyn fulfilled criteria for LBD (established or prodromal) at the moment of first evaluation as compared with 23/33 (69%) of LBD with positive RTQuIC suggesting a more initial disease in the negative group at the moment of CSF sampling.
The sensitivity and specificity of the assay were 83% and 94% respectively for the diagnosis of LBD, with a PPV of 83% and a NPV of 94%.
Conclusion
Detection of αSyn seeds by RT‐QuIC has a good performance in identifying patients with LBD in a clinical cohort of cognitively impaired subjects. The test also identifies aSyn co‐pathology in a subgroup of subjects diagnosed with AD.
Background
Currently used biomarkers for the differential diagnosis of cognitive impairment are expensive and/or relatively invasive, limiting their availability to the general population. Blood ...protein biomarkers have showed promising results for screening, differential diagnosis, and prognosis. We aimed to study the diagnostic performance of plasma p‐tau181 in a daily clinical practice, prospective memory clinic cohort.
Method
All patients referred for a first clinical evaluation with suspected cognitive impairment between January 1st, 2020 and March 30th, 2021, were invited to participate in the study. Plasma p‐tau181 was measured using SIMOA technology (Quanterix). Clinical diagnoses were made following current diagnostic criteria and blinded to plasma p‐tau181 results.
Result
A total of 232 participants were recruited (mean age 69y, mean MMSE 24), including 25 cognitively unimpaired (CU) controls (mean age 67y, MMSE 28). Clinical diagnoses were AD (82 subjects, 43 of them with prodromal AD CDR = 0.5), 83 non‐neurodegenerative cognitive impairment (non‐ND, 75 of them CDR = 0.5), 22 frontotemporal dementia (FTD) and 20 Lewy body disease (LBD).
Plasma p‐tau181 levels were statistically higher in AD (mean 2.39 pg/mL) compared with CU (mean 1.09 pg/mL), non‐ND (mean 1.43 pg/mL), FTD (mean 1.69 pg/mL) and LBD (mean 1.64 pg/mL) with a relatively good diagnostic performance for the differential diagnosis between AD and CU, non‐ND, LBD and FTD (AUC of 0.89, 0.80, 0.73 and 0.71, respectively).
128 subjects (55% of the cohort) had specific AD biomarkers (CSF or PET) available. In this subgroup, p‐tau181 differentiated AD from CU and non‐ND (AUC 0.91 and 0.92, respectively) and prodromal AD from CDR = 0.5 non‐ND participants (2.32 vs 1.02 pg/mL, p<0.001, AUC 0.90). Plasma p‐tau181 discriminated between a positive and negative amyloid beta status (defined by CSF/PET) with an AUC of 0.87 and AD subjects from those with a clinical diagnosis of LBD and FTD who had a negative amyloid beta status (AUC of 0.94 and 0.86, respectively). Plasma p‐tau181 correlated with CSF p‐tau181 (rs = 0.48, p<0.001).
Conclusion
In our cohort of everyday clinical practice, plasma p‐tau181 is an accurate biomarker for predicting the AD pathophysiological process and discriminating AD from other neurodegenerative and non‐neurodegenerative causes of cognitive impairment.
Sporadic early-onset Alzheimer’s disease (EOAD) and autosomal dominant Alzheimer’s disease (ADAD) provide the opportunity to investigate the physiopathological mechanisms in the absence of aging, ...present in late-onset forms. Frontotemporal dementia (FTD) causes early-onset dementia associated to tau or TDP43 protein deposits. A 15% of FTD cases are caused by mutations in
C9orf72
,
GRN
, or
MAPT
genes. Lymphoblastoid cell lines (LCLs) have been proposed as an alternative to brain tissue for studying earlier phases of neurodegenerative diseases. The aim of this study is to investigate the expression profile in EOAD, ADAD, and sporadic and genetic FTD (sFTD and gFTD, respectively), using brain tissue and LCLs. Sixty subjects of the following groups were included: EOAD, ADAD, sFTD, gFTD, and controls. Gene expression was analyzed with Clariom D microarray (Affymetrix). Brain tissue pairwise comparisons revealed six common differentially expressed genes (DEG) for all the patients’ groups compared with controls:
RGS20
,
WIF1
,
HSPB1
,
EMP3
,
S100A11
and
GFAP.
Common up-regulated biological pathways were identified both in brain and LCLs (including inflammation and glial cell differentiation), while down-regulated pathways were detected mainly in brain tissue (including synaptic signaling, metabolism and mitochondrial dysfunction).
CD163, ADAMTS9
and
LIN7A
gene expression disruption was validated by qPCR in brain tissue and
NrCAM
in LCLs in their respective group comparisons. In conclusion, our study highlights neuroinflammation, metabolism and synaptic signaling disturbances as common altered pathways in different AD and FTD forms. The use of LCLs might be appropriate for studying early immune system and inflammation, and some neural features in neurodegenerative dementias.
Highlights • Subdural hematoma can complicate REM sleep behavior disorder. • Abrupt discontinuation of clonazepam may cause a rebound of RBD symptomatology and increase the risk for injuries. • ...Pharmacological treatment with clonazepam or melatonin and safety measures in the bedroom are important to prevent injuries in RBD patients.
Early-onset Alzheimer’s disease (EOAD) and frontotemporal dementia (FTD) have a high proportion of genetically determined cases. Next-generation sequencing technologies have triggered the discovery ...of new mutations and genetic variants in dementia-causal genes. We performed whole-exome sequencing and selective analysis of known genes causative of EOAD and FTD in a well-characterized Spanish cohort of 103 patients (60 EOAD, 43 FTD) to find genetic variants associated to patients’ phenotype. In EOAD patients, a new likely pathogenic variant in PSEN1 gene (p.G378R) was found. In FTD patients, 2 likely pathogenic variants were found, one in MAPT gene (p.P397S) and one in VCP gene (p.R159H). In our series, 2% of early-onset dementia without criteria for clinical genetic testing according to current guidelines presented a likely pathogenic mutation. We have also detected 13 additional variants of uncertain significance in causal genes, as well as rare variants in risk genes for dementia (ABCA7, SORL1, SQSTM1, and TREM2). Next-generation technologies in neurodegenerative diseases constitute a powerful tool that significantly contributes to patients’ diagnosis.
•Whole-exome sequencing analysis of 103 patients with early-onset dementia.•A novel likely pathogenic variant is described in PSEN1 gene (p.G378R) in AD.•Novel likely pathogenic variants are found in MAPT (p.P397S) and VCP (p.R159H) in FTD.•We have found likely pathogenic variants in 2% of patients without early-onset family history of disease.•Clinical criteria for genetic testing may disappear as WES becomes more available.
Background
Blood‐based biomarkers have recently emerged as minimally‐invasive, accessible and relatively inexpensive diagnostic and prognostic tools for people with cognitive impairment. Before being ...routinely implemented in clinical practice, the diagnostic performance of distinct commercially available assays should be studied in real‐world cohorts. We aimed to study and compare the diagnostic accuracy of different plasma biomarkers measured using two different assay platforms in a memory clinic cohort.
Method
Participants were selected from a prospective memory clinic cohort; all had Alzheimer’s disease (AD) CSF biomarkers performed. Plasma p‐tau181, GFAP and NfL were measured using Simoa (Quanterix), while plasma p‐tau181, Aβ1‐40 and Aβ1‐42 were quantified using Lumipulse G (Fujirebio). Clinical diagnoses were made according to published criteria, blinded to plasma biomarkers. Aβ status (‐/+) was defined by CSF Aβ concentration using local cutoffs.
Result
One hundred and ten participants were included (mean age standard deviation 66 7.8 years, 56% women). Diagnostic categories included 10 cognitively unimpaired controls, 24 with suspected non‐neurodegenerative cause of cognitive impairment (SND), 53 AD, 9 Lewy body disease (LBD, 4 Aβ+) and 14 frontotemporal dementia (FTD, 1 Aβ+).
Plasma p‐tau181Quanterix and Aβ1‐42/Aβ1‐40 had the highest diagnostic accuracy (Figure 1) to discriminate between SND and AD (AUC CI 0.94 0.89‐0.99 and 0.94 0.85‐1), followed by GFAP (0.93 0.87‐0.99), p‐tau181Fujirebio (0.90 0.82‐0.98) and Aβ1‐42 (0.71 0.58‐0.85). Plasma NfL performed the best to differentiate FTD from SND and AD (AUC 0.95 0.88‐1 and 0.85 0.71‐0.99, respectively).
For Aβ status discrimination (Figure 2), p‐tau181Quanterix had an AUC CI of 0.91 0.85‐0.96, followed by p‐tau181Fujirebio (0.86 0.79‐0.93), Aβ1‐42/Aβ1‐40 (0.85 0.76‐0.93) and GFAP (0.84 0.77‐0.92) with no statistically significant differences in AUCs. Balanced (Youden index) cut‐offs were calculated to study diagnostic performance, resulting in sensitivities of 79‐83%, specificities of 74‐83% and accuracies of 76‐83%. No combination of plasma biomarkers resulted in a significantly increased discriminative accuracy for Aβ status. All plasma biomarkers were moderately correlated with p‐tau181Quanterix (ρ = 0.40‐0.75, Figure 3).
Conclusion
In our cohort, p‐tau181Quanterix, p‐tau181Fujirebio, Aβ1‐42/Aβ1‐40 and GFAP had a high diagnostic performance to discriminate CSF‐defined Aβ status. Plasma NfL identified individuals with FTD. Further studies comparing different plasma biomarkers are needed before implementation in clinical practice.
Background
Several previous studies have analyzed the genetic expression in late‐onset Alzheimer’s disease (AD). In this study, we aim to analyze the differential gene expression between sporadic ...early‐onset AD (sEOAD) and autosomal dominant AD due to the presence of PSEN1 mutations (PSEN1) in two type of samples, brain tissue and lymphoblastoid cell lines (LCL).
Method
Frozen prefrontal cortex (5 CTRL, 4 sEOAD and 4 PSEN1) was obtained from the Neurological Tissue Bank and LCL (5 CTRL, 5 sEOAD and 5 PSEN1) from the Alzheimer’s Disease Unit, both from the Hospital Clinic of Barcelona, IDIBAPS. Gene expression was measured with microarray Clariom D (Affymetrix). Differentially expressed genes (DEG) were obtained selecting the 35% most variable genes (n = 8473) by adjusting a linear model with empirical Bayes moderation of the variance. Significance threshold was set at p.value < 0.05 and fold change in absolute value >0.5. The analysis of biological significance was based on gene set enrichment analysis on Reactome Pathway Knowledge database.
Result
781/355 (brain/LCL) genes were differentially expressed in the sEOAD vs CTRL comparison, 503/275 in the PSEN1 vs CTRL, and 244/115 in the PSEN1 vs EOAD. No DEG were found with a significance threshold of an adjusted p.value <0.05. Any of the DEG survived after multiple comparisons correction. The top 10 enriched pathways for each comparison, using the most significative p.value and a normalized enrichment score (NES) absolute value >1.8, were considered. Pathways involved in synapsis were found in 2 comparisons: sEOAD vs CTRL (brain) and PSEN1 vs CTRL (LCL). Pathways related to metabolism (mainly Krebs cycle) were identified in all comparisons between patients and controls in both tissues. Signal transduction pathways were found in all comparisons. Immune system was observed in all comparisons between PSEN1 and sEOAD, as well as sEOAD vs CTRL in brain.
Conclusion
Genes involved in the immune system and signal transduction pathways were differentially expressed in sporadic and autosomal dominant AD caused by PSEN1 mutations. The number of DEG was higher in brain tissue than in LCL comparisons. Validation of these findings by quantitative‐PCR would be necessary to discard false positive results.
Abstract
Background
Several previous studies have analyzed the genetic expression in late‐onset Alzheimer’s disease (AD). In this study, we aim to analyze the differential gene expression between ...sporadic early‐onset AD (sEOAD) and autosomal dominant AD due to the presence of
PSEN1
mutations (PSEN1) in two type of samples, brain tissue and lymphoblastoid cell lines (LCL).
Method
Frozen prefrontal cortex (5 CTRL, 4 sEOAD and 4 PSEN1) was obtained from the Neurological Tissue Bank and LCL (5 CTRL, 5 sEOAD and 5 PSEN1) from the Alzheimer’s Disease Unit, both from the Hospital Clinic of Barcelona, IDIBAPS. Gene expression was measured with microarray Clariom D (Affymetrix). Differentially expressed genes (DEG) were obtained selecting the 35% most variable genes (n = 8473) by adjusting a linear model with empirical Bayes moderation of the variance. Significance threshold was set at p.value < 0.05 and fold change in absolute value >0.5. The analysis of biological significance was based on gene set enrichment analysis on Reactome Pathway Knowledge database.
Result
781/355 (brain/LCL) genes were differentially expressed in the sEOAD vs CTRL comparison, 503/275 in the PSEN1 vs CTRL, and 244/115 in the PSEN1 vs EOAD. No DEG were found with a significance threshold of an adjusted p.value <0.05. Any of the DEG survived after multiple comparisons correction. The top 10 enriched pathways for each comparison, using the most significative p.value and a normalized enrichment score (NES) absolute value >1.8, were considered. Pathways involved in synapsis were found in 2 comparisons: sEOAD vs CTRL (brain) and PSEN1 vs CTRL (LCL). Pathways related to metabolism (mainly Krebs cycle) were identified in all comparisons between patients and controls in both tissues. Signal transduction pathways were found in all comparisons. Immune system was observed in all comparisons between PSEN1 and sEOAD, as well as sEOAD vs CTRL in brain.
Conclusion
Genes involved in the immune system and signal transduction pathways were differentially expressed in sporadic and autosomal dominant AD caused by
PSEN1
mutations. The number of DEG was higher in brain tissue than in LCL comparisons. Validation of these findings by quantitative‐PCR would be necessary to discard false positive results.
Hippocampal subfields’ sex differences in EOAD Contador, José; Pérez‐Millan, Agnés; Guillén, Núria ...
Alzheimer's & dementia,
June 2023, 2023-06-00, Letnik:
19, Številka:
S3
Journal Article
Recenzirano
Odprti dostop
Background
In healthy ageing, there is evidence of sex differences in vulnerability of hippocampal subfields to volume loss. However, this has not been investigated in early‐onset Alzheimer’s disease ...(<65 years; EOAD).
Method
We included 106 subjects: 62 EOAD (A+T+N+, MMSE>15) and 44 healthy controls (HC; A‐T‐N‐) that underwent lumbar puncture for analysis of AD biomarkers, 3T‐MRI scan and neuropsychological assessment. Hippocampal subfield segmentation was performed using T1‐weighted images and Freesurfer 6.0. Volume was adjusted by intracranial volume. Adjusted linear models were used to analyze differences between EOAD and HC and differences between sexes. We calculated Cohen’s d as a measure of the effect size of volume change by sex, restricted to volume differences between EOAD and HC. In EOAD, we used linear models adjusted by age and education to investigate the association of volume loss with 18 cognition z‐scores. Results were adjusted using Bonferroni correction for multiple comparisons.
Result
There were no demographic differences across groups. APOEε4 carriers were higher in EOAD‐female/EOAD‐male than HC‐female. EOAD‐female showed higher T‐Tau and P‐Tau levels than EOAD‐male (all p<0.05; Table1). Comparing EOAD vs. HC, differences were found in volume of all subfields and hippocampus (p<0.05, Bonferroni corrected), except for bilateral parasubiculum and right cornu ammonis (CA) 2/3. No differences were found between EOAD‐female and EOAD‐male (p>0.05). When compared to HC of the same sex, EOAD‐female showed differences in the same regions as the whole sample, while EOAD‐male showed differences in bilateral hippocampal tail and left presubiculum and hippocampus (all p<0.05, Bonferroni corrected, Figure 1). We observed larger effect sizes than in women in these regions, except for left hippocampus (Figure 2).
In EOAD, higher volume in left CA2/3 predicted higher memory z‐scores, including free and total learning and delayed total recall (p<0.05 Bonferroni corrected; Figure 3). No associations were found in EOAD‐female nor EOAD‐male.
Conclusion
In EOAD, the pattern of volume loss in hippocampal subfields was similar between sexes. However, females showed more marked differences from HC, except for bilateral hippocampal tail and left presubiculum. Further studies are necessary to elucidate the existence of sex differences in EOAD and their implication for cognitive impairment.
Background
MRI atrophy predicts cognitive status in AD. However, this relationship has not been investigated in early-onset AD (EOAD, < 65 years) patients with a biomarker-based diagnosis.
Methods
...Forty eight EOAD (MMSE ≥ 15; A + T + N +) and forty two age-matched healthy controls (HC; A − T − N −) from a prospective cohort underwent full neuropsychological assessment, 3T-MRI scan and lumbar puncture at baseline. Participants repeated the cognitive assessment annually. We used linear mixed models to investigate whether baseline cortical thickness (CTh) or subcortical volume predicts two-year cognitive outcomes in the EOAD group.
Results
In EOAD, hemispheric CTh and ventricular volume at baseline were associated with global cognition, language and attentional/executive functioning 2 years later (
p
< 0.0028). Regional CTh was related to most cognitive outcomes (
p
< 0.0028), except verbal/visual memory subtests. Amygdalar volume was associated with letter fluency test (
p
< 0.0028). Hippocampal volume did not show significant associations.
Conclusion
Baseline hemispheric/regional CTh, ventricular and amygdalar volume, but not the hippocampus, predict two-year cognitive outcomes in EOAD.
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