Matching Clinical Diagnosis and Amyloid Biomarkers in Alzheimer's Disease and Frontotemporal Dementia

The role of plasma neurofilament light chain and glial fibrillary acidic protein in subjective cognitive decline and mild cognitive impairment

INTRODUCTION AND AIM

NfL and GFAP are promising blood-based biomarkers for Alzheimer's disease. However, few studies have explored plasma GFAP in the prodromal and preclinical stages of AD. In our cross-sectional study, our aim is to investigate the role of these biomarkers in the earliest stages of AD.

MATERIALS AND METHODS

We enrolled 40 patients (11 SCD, 21 MCI, 8 AD dementia). All patients underwent neurological and neuropsychological examinations, analysis of CSF biomarkers (Aβ42, Aβ42/Aβ40, p-tau, t-tau), Apolipoprotein E (APOE) genotype analysis and measurement of plasma GFAP and NfL concentrations. Patients were categorized according to the ATN system as follows: normal AD biomarkers (NB), carriers of non-Alzheimer's pathology (non-AD), prodromal AD, or AD with dementia (AD-D).

RESULTS

GFAP was lower in NB compared to prodromal AD (p = 0.003, d = 1.463) and AD-D (p = 0.002, d = 1.695). NfL was lower in NB patients than in AD-D (p = 0.011, d = 1.474). NfL demonstrated fair accuracy (AUC = 0.718) in differentiating between NB and prodromal AD, with a cut-off value of 11.65 pg/mL. GFAP showed excellent accuracy in differentiating NB from prodromal AD (AUC = 0.901) with a cut-off level of 198.13 pg/mL.

CONCLUSIONS

GFAP exhibited excellent accuracy in distinguishing patients with normal CSF biomarkers from those with prodromal AD. Our results support the use of this peripheral biomarker for detecting AD in patients with subjective and objective cognitive decline.

Evaluation of the Polygenic Risk Score for Alzheimer's Disease in Russian Patients with Dementia Using a Low-Density Hydrogel Oligonucleotide Microarray

The polygenic risk score (PRS), together with the ɛ4 allele of the APOE gene (APOE-ɛ4), has shown high potential for Alzheimer's disease (AD) risk prediction. The aim of this study was to validate the model of polygenic risk in Russian patients with dementia. A microarray-based assay was developed to identify 21 markers of polygenic risk and ɛ alleles of the APOE gene. This case-control study included 348 dementia patients and 519 cognitively normal volunteers. Cerebrospinal fluid (CSF) amyloid-β (Aβ) and tau protein levels were assessed in 57 dementia patients. PRS and APOE-ɛ4 were significant genetic risk factors for dementia. Adjusted for APOE-ɛ4, individuals with PRS corresponding to the fourth quartile had an increased risk of dementia compared to the first quartile (OR 1.85; p-value 0.002). The area under the curve (AUC) was 0.559 for the PRS model only, and the inclusion of APOE-ɛ4 improved the AUC to 0.604. PRS was positively correlated with tTau and pTau181 and inversely correlated with Aβ42/Aβ40 ratio. Carriers of APOE-ɛ4 had higher levels of tTau and pTau181 and lower levels of Aβ42 and Aβ42/Aβ40. The developed assay can be part of a strategy for assessing individuals for AD risk, with the purpose of assisting primary preventive interventions.

PSEN2 Thr421Met Mutation in a Patient with Early Onset Alzheimer’s Disease

Presenilin-2 (PSEN2) mutation Thr421Met was identified from a 57-years old patient with early onset Alzheimer’s disease (EOAD) for the first time in Korea. Previously, this mutation was discovered in an EOAD patient in Japan without a change on amyloid production from the cellular study. Both Korean and Japanese patients developed the disease in their 50s. Memory loss was prominent in both cases, but no additional clinical information was available on the Japanese patient. Magnetic resonance imaging (MRI) images of the Korean patient revealed asymmetric atrophies in both temporo-parietal lobes. In addition, amyloid positron emission tomography (PET) also revealed amyloid deposits in the gray matter of the temporo-parietal lobes asymmetrically. PSEN2 Thr421 was conserved among a majority of vertebrates (such as zebras, elephants, and giant pandas); hence, Thr421 could play an important role in its functions and any mutations could cause detrimental ramifications in its interactions. Interestingly, PSEN2 Thr421 could have homology with PSEN1 Thr440, as PSEN1 T440del mutations were reported from patients with AD or dementia with Lewy bodies. Hence, the changed amino acid from threonine to methionine of PSEN2 Thr421 could cause significant structural alterations in causing local protein dynamics, leading to its pathogenicity in EOAD. Lastly, PSEN2 Thr421Met may interact with other mutations in neurodegenerative disease related genes, which were found in the proband patient, such as ATP binding cassette subfamily A member 7 (ABCA7), Notch Receptor 3 (NOTCH3), or Leucine-rich repeat kinase 2 (LRRK2). These interactions of pathway networks among PSEN2 and other disease risk factors could be responsible for the disease phenotype through other pathways. For example, PSEN2 and ABCA7 may impact amyloid processing and reduce amyloid clearance. Interaction between PSEN2 and NOTCH3 variants may be associated with abnormal NOTCH signaling and a lower degree of neuroprotection. Along with LRRK2 variants, PSEN2 Thr421Met may impact neurodegeneration through Wnt related pathways. In the future, cellular studies of more than one mutation by CRISPR-Cas9 method along with biomarker profiles could be helpful to understand the complicated pathways.

Alzheimer’s Disease CSF Biomarker Profiles in Idiopathic Normal Pressure Hydrocephalus

Patients with idiopathic normal pressure hydrocephalus (iNPH) frequently show pathologic CSF Aβ₄₂ levels, comparable with Alzheimer’s Disease (AD). Nevertheless, the clinical meaning of these findings has not been fully explained. We aimed to assess the role of AD CSF biomarkers (Aβ₄₂, Aβ₄₂/Aβ₄₀, p-tau, t-tau) in iNPH. To this purpose, we enrolled 44 patients diagnosed with iNPH and 101 with AD. All the patients underwent CSF sampling. We compared CSF biomarker levels in iNPH and AD: Aβ₄₂ levels were not different between iNPH and AD, while Aβ₄₂/Aβ₄₀, p-tau, and t-tau were significantly different and showed excellent accuracy in distinguishing iNPH and AD. A multiple logistic regression analysis showed that Aβ₄₂/Aβ₄₀ was the variable that most contributed to differentiating the two groups. Furthermore, iNPH patients with positive Aβ₄₂/Aβ₄₀ had higher p-tau and t-tau than iNPH patients with negative Aβ₄₂/Aβ₄₀. Those iNPH patients who showed cognitive impairment had lower Aβ₄₂/Aβ₄₀ and higher p-tau than patients without cognitive impairment. We concluded that positive CSF Aβ₄₂ with negative Aβ₄₂/Aβ₄₀, p-tau, and t-tau is a typical CSF profile of iNPH. On the contrary, positive Aβ₄₂/Aβ₄₀ in iNPH patients, especially when associated with positive p-tau, may lead to suspicion of a coexistent AD pathology.

Cerebral amyloid load determination in a clinical setting: interpretation of amyloid biomarker discordances aided by tau and neurodegeneration measurements

BACKGROUND

Alzheimer's disease (AD) diagnosis can be hindered by amyloid biomarkers discordances.

OBJECTIVE

We aim to interpret discordances between amyloid positron emission tomography (Amy-PET) and cerebrospinal fluid (CSF) (Aβ₄₂ and Aβ_42/40), using Amy-PET semiquantitative analysis, [¹⁸F]fluorodeoxyglucose (FDG)-PET pattern, and CSF assays.

METHOD

Thirty-six subjects with dementia or mild cognitive impairment, assessed by neuropsychological tests, structural and functional imaging, and CSF assays (Aβ₄₂, Aβ_42/40, p-tau, t-tau), were retrospectively examined. Amy-PET and FDG-PET scans were analyzed by visual assessment and voxel-based analysis. SUVR were calculated on Amy-PET scans.

RESULTS

Groups were defined basing on the agreement among CSF Aβ₄₂ (A), CSF Aβ_42/40 Ratio (R), and Amy-PET (P) dichotomic results ( ±). In discordant groups, CSF assays, Amy-PET semiquantification, and FDG-PET patterns supported the diagnosis suggested by any two agreeing amyloid biomarkers. In groups with discordant CSF Aβ₄₂, the ratio always agrees with Amy-PET results, solving both false-negative and false-positive Aβ₄₂ results, with Aβ₄₂ levels close to the cut-off in A + R-P- subjects. The A + R + P- group presented high amyloid deposition in relevant areas, such as precuneus, posterior cingulate cortex (PCC) and dorsolateral frontal inferior cortex at semiquantitative analysis.

CONCLUSION

The amyloid discordant cases could be overcome by combining CSF Aβ₄₂, CSF ratio, and Amy-PET results. The concordance of any 2 out of the 3 biomarkers seems to reveal the remaining one as a false result. A cut-off point review could avoid CSF Aβ₄₂ false-negative results. The regional semiquantitative Amy-PET analysis in AD areas, such as precuneus and PCC, could increase the accuracy in AD diagnosis.