New high‐throughput fully automated BD‐Tau immunoassay

Background Glial Fibrillary Acidic Protein (GFAP) levels are shown to be an indicator of neurologic injury in conditions like Traumatic Brain Injury (TBI) and stroke and as a marker of disease progression in neuromuscular disorders such as multiple sclerosis. Plasma GFAP is also implicated in detecting AD pathology, correlating to the clinical stage of the disease. The performance characteristics of the plasma GFAP immunoassay currently being developed on Beckman Coulter Access 2 and DxI 9000 analyzers are described. Methods The prototype GFAP assay is a one-step sandwich assay utilizing an anti-GFAP mouse monoclonal (MAb) antibody/alkaline phosphatase conjugate and paramagnetic particles coated with a complementary anti-GFAP mouse MAb. Sample and reactants are incubated and washed, and then a chemiluminescent substrate is added. The light generated is directly proportional to the GFAP concentration in the sample. The assay time to the first result is ∼30 minutes. Analytical performance evaluation and method comparison across different platforms was performed. 43 EDTA plasma samples, consisting of 19 Alzheimer’s Disease (AD) patient samples and 24 age-matched healthy normal samples, were evaluated. Results The prototype GFAP assay has a targeted analytical measuring range of 1.0 pg/ml to approximately 700.0 pg/ml (up to 10,000 pg/ml). All normal samples were quantified with 90% measuring below 20.0 pg/ml and a low dose coefficient of variation <4.0%. A comparison of the prototype GFAP assay on DxI 9000 and Access 2 analyzers shows a Passing-Bablok slope of 0.94 (R=0.992) and an intercept of 0.37 pg/ml. Concordance analysis shows excellent agreement between the Access 2 and DxI 9000 assays. The dose ratio of the median of AD over the median of normal samples for Access 2 and DxI 9000 is 2.31 and 2.41, respectively, with AD patient median dose values of 14.3 pg/ml and 14.6 pg/mL, respectively, and normal sample median dose values of 6.2 pg/ml and 6.0 pg/mL, respectively. Conclusions The prototype GFAP assay provides fast, highly sensitive, and precise results in an automated immunoassay on the Beckman Coulter Access 2 and DxI 9000 platforms. The prototype plasma GFAP assay holds promise for diagnosing and monitoring various neurodegenerative diseases, including AD.

Osteocalcin (Oc), a serum marker of bone turnover, circulates in several forms. We developed an assay for intact human Oc and investigated its clinical features. We generated goat antibodies and N- and C-terminal Oc. The former was used on solid phase (polystyrene beads), and the latter was used as the tracer in an IRMA. The assay was linear with no cross-reactivity to Oc(1-43), total imprecision (CV) of <10%, and recovery of 100% +/- 10%. Assay values for intact Oc in EDTA plasma samples were unchanged at 18-25 degrees C for 6 h. Values for intact Oc in serum, EDTA plasma, and heparin plasma samples did not change after storage on ice for 8 h. Serum samples from patients with various conditions were stored at -70 or -135 degrees C for up to 5 years and yielded z-scores comparable to an Oc(1-43) IRMA for all conditions except for renal failure. In renal failure, the Oc(1-43) assay values were increased, whereas the intact assay values were in the reference interval. Decreases in Oc assay values are inhibited by calcium chelation, and slowed by reduced temperatures. The described assay for intact Oc allows improved specificity for bone compared with an assay for Oc(1-43).

BackgroundVisual rating of medial temporal lobe atrophy (MTA‐scale) has been well recognized as a biomarker for Alzheimer’s disease (AD), and automatic quantification of MTA (QMTA) based on the volume of hippocampus and inferior lateral ventricle (ILV) has been proposed. However, a comprehensive comparison of MTA‐scale, QMTA as well as the components of MTA (i.e. volume of hippocampus and ILV) is still lacking in differential diagnosis or early detection of AD. Also, it’s not clear about the difference of performance between the conventional MTA measures and the recently proposed AD resemblance atrophy index (AD‐RAI) that integrates multiple brain regions more than MTA.MethodWe included 132 AD, 132 normal control (NC) subjects, and 353 subjects with mild cognitive impairment (MCI) from ADNI. Among the MCI patients, 290 remained stable (MCIs) and 63 converted to AD (MCIc) in a two‐year follow‐up. The AD and NC subjects, and the MCIs and MCIc subjects were matched in age, gender and education, respectively (Table 1). MTA‐scale was visually rated by an experienced neuroradiologist. Baseline T1‐weighted images were processed with AccuBrain to quantify the volume of hippocampus and ILV as well as the AD‐RAI. Receiver operating characteristic (ROC) curve analyses were performed to compare these measured when differentiating AD from NC and MCIc from MCIs. Sub‐analyses were conducted by grouping the study cohort by age (&gt;75 years or not) and gender. The optimal threshold was determined by Youden Index.ResultThe Spearmen correlation of QMTA and MTA‐scale was 0.805 (p&lt;0.001). Regarding the ROC analyses, the AD‐RAI performed the best in differentiating AD from NC (AUC=0.860, Youden Index=59.1% for all individuals) and MCIc from MCIs (AUC=0.768, Youden Index=41.6% for all individuals), followed by the hippocampal fraction/volume, QMTA, MTA, and ILV fraction/volume (Table 2 and Table 3). For all the MRI‐based measures, the differentiation performance was better for those with age≤75 years in both classifications, and better for men in AD vs. NC and women for MCIc vs. MCIs.ConclusionMTA measures based on automated brain volumetry performed better than visual rating, and the superiority of AD‐RAI over MTA measures needs further validations in a larger population.

PurposeGlaucoma is the second commonest cause of blindness. We assessed the gene expression profile of astrocytes in the optic nerve head to identify possible prognostic biomarkers for glaucoma.MethodA total of 20 patient and nine normal control subject samples were derived from the GSE9944 (six normal samples and 13 patient samples) and GSE2378 (three normal samples and seven patient samples) datasets, screened by microarray-tested optic nerve head tissues, were obtained from the Gene Expression Omnibus (GEO) database. We used a weighted gene coexpression network analysis (WGCNA) to identify coexpressed gene modules. We also performed a functional enrichment analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Genes expression was represented by boxplots, functional geneset enrichment analyses (GSEA) were used to profile the expression patterns of all the key genes. Then the key genes were validated by the external dataset.ResultsA total 8,606 genes and 19 human optic nerve head samples taken from glaucoma patients in the GSE9944 were compared with normal control samples to construct the co-expression gene modules. After selecting the most common clinical traits of glaucoma, their association with gene expression was established, which sorted two modules showing greatest correlations. One with the correlation coefficient is 0.56 (P = 0.01) and the other with the correlation coefficient is −0.56 (P = 0.01). Hub genes of these modules were identified using scatterplots of gene significance versus module membership. A functional enrichment analysis showed that the former module was mainly enriched in genes involved in cellular inflammation and injury, whereas the latter was mainly enriched in genes involved in tissue homeostasis and physiological processes. This suggests that genes in the green–yellow module may play critical roles in the onset and development of glaucoma. A LASSO regression analysis identified three hub genes: Recombinant Bone Morphogenetic Protein 1 gene (BMP1), Duchenne muscular dystrophy gene (DMD) and mitogens induced GTP-binding protein gene (GEM). The expression levels of the three genes in the glaucoma group were significantly lower than those in the normal group. GSEA further illuminated that BMP1, DMD and GEM participated in the occurrence and development of some important metabolic progresses. Using the GSE2378 dataset, we confirmed the high validity of the model, with an area under the receiver operator characteristic curve of 85%.ConclusionWe identified several key genes, including BMP1, DMD and GEM, that may be involved in the pathogenesis of glaucoma. Our results may help to determine the prognosis of glaucoma and/or to design gene- or molecule-targeted drugs.

The aim of this study was to evaluate the structural integrity of the thalamic connectivity of specific fiber tracts in different stages of Alzheimer's disease (AD) using diffusion tensor imaging (DTI). Thirty-five patients with AD and 22 normal control (NC) subjects were recruited. Based on Mini Mental State Examination score, the AD patients were divided into three subgroups for comparison with the NC group: mild (mi-AD, n=14), moderate (mo-AD, n=12), and severe (se-AD, n=9) AD. The fornix (FX), anterior thalamic radiation (ATR), and posterior thalamic radiation (PTR) were selected to represent the thalamic connectivity with other brain regions. The fornix was divided into the column and body of the fornix (FX-1) and the bilateral fornix (crus)/stria terminalis (FX-2/ST) based on the atlas. Through the atlas-based analysis and fiber tracking method, we measured fractional anisotropy (FA), mean diffusivity (MD), and tract volume to reflect the microstructural and macrostructural changes of these fibers during AD progression. There were significant differences in the FA and MD of all fibers, except the right PTR, between the AD and NC subjects. Further subgroup analyses revealed that the mi-AD subgroup had decreased FA only in the FX-1 and increased MD in the FX-1 and bilateral ATR, the mo-AD subgroup showed declined FA and increased MD in the FX-1, bilateral FX-2/ST and ATR; the se-AD subgroup exhibited lower FA and higher MD values in all fibers except the right PTR. We also found reduced tract volume values in the FX and left ATR in the AD patients. Further subgroup analyses revealed that these differences only existed in the se-AD patients. Our DTI analyses indicate that the integrity of thalamic connectivity is progressively disrupted following cognitive decline in AD and that DTI parameters in the column and body of the fornix show promise as potential markers for the early diagnosis of AD and for monitoring disease progression.

To assess the ability of a brief neuropsychological bedside screening battery to discriminate between Alzheimer disease, frontotemporal dementia, and semantic dementia. Subjects were 21 patients with frontotemporal dementia, 14 patients with semantic dementia, and 30 patients with Alzheimer disease comparable in terms of Mini Mental Status Examination score, age, and education. Frontotemporal dementia and semantic dementia diagnoses were made clinically using the consensus criteria of Neary et al. 1 Subjects were administered a brief neuropsychological screening assessing episodic memory, working memory, executive function, naming, spatial ability, abstract reasoning, and calculations. Both the Alzheimer disease and semantic dementia groups were significantly impaired relative to the frontotemporal dementia group on verbal memory, whereas only the Alzheimer disease group was impaired on visual memory. Frontotemporal dementia patients performed significantly worse on backward digit span and made significantly more executive errors than Alzheimer disease and semantic dementia patients. Semantic dementia patients were more impaired than Alzheimer disease and frontotemporal dementia patients on confrontation naming. Discriminant function analyses identified the 5 most discriminating variables that correctly classified 89.2% of cases. Frontotemporal dementia, semantic dementia, and Alzheimer disease are associated with distinct neuropsychological profiles that classify these dementia syndromes with considerable success. The neuropsychological profiles highlight the distinctiveness between the 3 syndromes, are consistent with the known loci of neuropathology in these conditions, and can potentially serve as an adjunct to the current clinical criteria.

Accurate recognition of progressive mild cognitive impairment (MCI) is helpful to reduce the risk of developing Alzheimer's disease (AD). However, it is still challenging to extract effective biomarkers from multivariate brain structural magnetic resonance imaging (MRI) features to accurately differentiate the progressive MCI from stable MCI. We develop novel biomarkers by combining subspace learning methods with the information of AD as well as normal control (NC) subjects for the prediction of MCI conversion using multivariate structural MRI data. Specifically, we first learn two projection matrices to map multivariate structural MRI data into a common label subspace for AD and NC subjects, where the original data structure and the one-to-one correspondence between multiple variables are kept as much as possible. Afterwards, the multivariate structural MRI features of MCI subjects are mapped into a common subspace according to the projection matrices. We then perform the self-weighted operation and weighted fusion on the features in common subspace to extract the novel biomarkers for MCI subjects. The proposed biomarkers are tested on Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Experimental results indicate that our proposed biomarkers outperform the competing biomarkers on the discrimination between progressive MCI and stable MCI. And the improvement from the proposed biomarkers is not limited to a particular classifier. Moreover, the results also confirm that the information of AD and NC subjects is conducive to predicting conversion from MCI to AD. In conclusion, we find a good representation of brain features from high-dimensional MRI data, which exhibits promising performance for predicting conversion from MCI to AD.

BackgroundThe content of circulating exosomes has been observed to be altered in response to changes in physiological and pathological conditions, and they are detectable in different human fluids such as blood. Studies focused on the quantification of Aβ and tau proteins, as molecules contained within exosomes, suggest that they are related with Alzheimer disease (AD) and frontotemporal dementia (FTD) development, demonstrated that plasma‐derived exosome analysis is a good approach for searching for biomarkers in the development of dementia. Our aim is to identify new blood biomarkers to detect the AD or FTD in the Chilean population using machine learning based on exosomal miRNAs.MethodmiRNAs were extracted from circulating exosomes from plasma samples of 25 healthy controls (HC), 25 AD patients and 10 FTD patients. miRNAs were sequencing to identify and measure the expression levels. Dysregulated miRNAs were analyzed to create machine learning algorithms. miRNAs obtained from algorithms were validated in a new population of subjects 30 HC, 30 AD and 10 FTD using qRT‐PCR.ResultAfter the sequencing and machine learning analysis, we identified 8 miRNAs as potential predictors of AD and FTD. These miRNAs were further assessed in new samples using the qRT‐PCR technique. We identified 4 miRNAs with variable expression in patients with AD and FTD, with three miRNAs downregulated in AD and one upregulated in FTD. For the four miRNAs, significant differences in expression are observed between AD and FTD.ConclusionThis is the first study in the Chilean population that evaluates miRNAs in patients with AD and FTD. The study of miRNAs as biomarkers of dementia provides the opportunity to develop low‐cost and easy‐to‐obtain diagnostic methods, in addition to the possibility of being implemented in a greater number of health centers, making them more accessible to the population.

A 'frontal variant of Alzheimer's disease' has been described in patients with predominant behavioural or dysexecutive deficits caused by Alzheimer's disease pathology. The description of this rare Alzheimer's disease phenotype has been limited to case reports and small series, and many clinical, neuroimaging and neuropathological characteristics are not well understood. In this retrospective study, we included 55 patients with Alzheimer's disease with a behavioural-predominant presentation (behavioural Alzheimer's disease) and a neuropathological diagnosis of high-likelihood Alzheimer's disease (n = 17) and/or biomarker evidence of Alzheimer's disease pathology (n = 44). In addition, we included 29 patients with autopsy/biomarker-defined Alzheimer's disease with a dysexecutive-predominant syndrome (dysexecutive Alzheimer's disease). We performed structured chart reviews to ascertain clinical features. First symptoms were more often cognitive (behavioural Alzheimer's disease: 53%; dysexecutive Alzheimer's disease: 83%) than behavioural (behavioural Alzheimer's disease: 25%; dysexecutive Alzheimer's disease: 3%). Apathy was the most common behavioural feature, while hyperorality and perseverative/compulsive behaviours were less prevalent. Fifty-two per cent of patients with behavioural Alzheimer's disease met diagnostic criteria for possible behavioural-variant frontotemporal dementia. Overlap between behavioural and dysexecutive Alzheimer's disease was modest (9/75 patients). Sixty per cent of patients with behavioural Alzheimer's disease and 40% of those with the dysexecutive syndrome carried at least one APOE ε4 allele. We also compared neuropsychological test performance and brain atrophy (applying voxel-based morphometry) with matched autopsy/biomarker-defined typical (amnestic-predominant) Alzheimer's disease (typical Alzheimer's disease, n = 58), autopsy-confirmed/Alzheimer's disease biomarker-negative behavioural variant frontotemporal dementia (n = 59), and controls (n = 61). Patients with behavioural Alzheimer's disease showed worse memory scores than behavioural variant frontotemporal dementia and did not differ from typical Alzheimer's disease, while executive function composite scores were lower compared to behavioural variant frontotemporal dementia and typical Alzheimer's disease. Voxel-wise contrasts between behavioural and dysexecutive Alzheimer's disease patients and controls revealed marked atrophy in bilateral temporoparietal regions and only limited atrophy in the frontal cortex. In direct comparison with behavioural and those with dysexecutive Alzheimer's disease, patients with behavioural variant frontotemporal dementia showed more frontal atrophy and less posterior involvement, whereas patients with typical Alzheimer's disease were slightly more affected posteriorly and showed less frontal atrophy (P < 0.001 uncorrected). Among 24 autopsied behavioural Alzheimer's disease/dysexecutive Alzheimer's disease patients, only two had primary co-morbid FTD-spectrum pathology (progressive supranuclear palsy). In conclusion, behavioural Alzheimer's disease presentations are characterized by a milder and more restricted behavioural profile than in behavioural variant frontotemporal dementia, co-occurrence of memory dysfunction and high APOE ε4 prevalence. Dysexecutive Alzheimer's disease presented as a primarily cognitive phenotype with minimal behavioural abnormalities and intermediate APOE ε4 prevalence. Both behavioural Alzheimer's disease and dysexecutive Alzheimer's disease presentations are distinguished by temporoparietal-predominant atrophy. Based on the relative sparing of frontal grey matter, we propose to redefine these clinical syndromes as 'the behavioural/dysexecutive variant of Alzheimer's disease' rather than frontal variant Alzheimer's disease. Further work is needed to determine whether behavioural and dysexecutive-predominant presentations of Alzheimer's disease represent distinct phenotypes or a single continuum.

To investigate the specific pattern of cerebral blood flow (CBF) in subjects with idiopathic normal pressure hydrocephalus (iNPH) using voxel-based analysis. N-isopropyl-p-[123I]iodoamphetamine (IMP) single photon emission computed tomography (SPECT) images were performed in 30 iNPH patients, who met probable iNPH criteria, 30 Alzheimer disease (AD) patients and 15 normal control (NC) subjects. Inter-group comparisons between iNPH patients and NC subjects and between AD patients and NC subjects were performed using three-dimensional stereotactic surface projection (3D-SSP) analysis. Individual 3D-SSP images of the iNPH patients were assessed by visual inspection. On the Z-score maps, areas of relative hypoperfusion were recognized around the corpus callosum in all 30 iNPH patients, as well as in the Sylvian fissure regions in 19 of 30 iNPH patients which included artifacts by dilated ventricles and the Sylvian fissures. Ten frontal dominant, eight parietotemporal dominant, and 12 diffuse hypoperfusion types were demonstrated. Inter-group comparison between iNPH and NC subjects showed relative hypoperfusion in the frontal and parietotemporal areas and severe hypoperfusion around the corpus callosum and Sylvian fissure regions, while parietotemporal and posterior cingulate CBF reduction was demonstrated between the AD and NC groups. Voxel-based analysis showed a characteristic pattern of regional CBF reduction with frontal dominant or diffuse cerebral hypoperfusion accompanying severe hypoperfusion around the corpus callosum and Sylvian fissures with artifacts.

Alzheimer's disease (AD) and frontal lobe dementia (FLD) show characteristic patterns of regional cerebral blood flow (rCBF). However, these patterns may overlap with those observed in the aging brain in elderly normal individuals. The aim of this study was to develop a new method for better classification and recognition of AD and FLD cases as compared with normal controls. Forty-six patients with AD, 7 patients with FLD and 34 normal controls (CTR) were included in the study. rCBF was assessed by technetium-99m hexamethylpropylene amine oxime and a three-headed single-photon emission tomography (SPET) camera. A brain atlas was used to define volumes of interest (VOIs) corresponding to the brain lobes. In addition to conventional image processing methods, based on count density/voxel, the new approach also analysed other intrinsic properties of the data by means of gradient computation steps. Hereby, five factors were assessed and tested separately: the mean count density/voxel and its histogram, the mean gradient and its histogram, and the gradient angle co-occurrence matrix. A feature vector concatenating single features was also created and tested. Preliminary feature discrimination was performed using a two-sided t-test and a K-means clustering was then used to classify the image sets into categories. Finally, five-dimensional co-occurrence matrices combining the different intrinsic properties were computed for each VOI, and their ability to recognise the group to which each individual scan belonged was investigated. For correct classification of the AD-CTR groups, the gradient histogram in the parieto-temporal lobes was the most useful single feature (accuracy 91%). FLD and CTR were better classified by the count density/voxel histogram (frontal and occipital lobes) and by the mean gradient (frontal, temporal and parietal lobes, accuracy 98%). For AD and FLD the count density/voxel histogram in the frontal, parietal and occipital lobes classified the groups with the highest accuracy (85%). The concatenated joint feature correctly classified 96% of the AD-CTR, 98% of the FLD-CTR and 94% of the AD-FLD cases. 5D co-occurrence matrices correctly recognised 98% of the AD-CTR cases, 100% of the FLD-CTR cases and 98% of the AD-FLD cases. The proposed approach classified and diagnosed AD and FLD patients with higher accuracy than conventional analytical methods used for rCBF-SPET. This was achieved by extracting from the SPET data the intrinsic information content in each of the selected VOIs.

To characterize the clinical course of pathologically diagnosed hippocampal sclerosis dementia (HSD). Dementia associated with HSD is incompletely characterized. Previous studies suggest similarities to both Alzheimer disease (AD) and frontotemporal dementia (FTD). Case-control analysis of the clinical course of patients with HSD, FTD, and AD from a neuropathology autopsy series conducted by a university hospital. Case histories were reviewed. Cumulative prevalence of behavioral, cognitive, psychiatric, and language symptoms were compared between groups, as was time of symptom onset. Clinical diagnostic criteria for FTD and AD were applied to case histories. Sensitivity and specificity of clinical FTD diagnostic criteria (Report of the Work Group on FTD and Pick's disease) were computed. Cumulative prevalence of symptoms in HSD was most similar to that of FTD and differed from AD. Behavioral abnormalities such as decreased grooming and inappropriate behavior were more prevalent in HSD and FTD than AD. Hyperorality, inappropriate behavior, and decreased interest had earlier onset in HSD and FTD. Cognitive symptoms of disorientation, dyscalculia, apraxia, and agnosia were more prevalent in AD, as were psychiatric symptoms of hallucinations, delusions, and aggression. Most HSD patients met diagnostic criteria for FTD. Criteria sensitivity was 64.0% and specificity was 73.7%. FTD is a clinical syndrome associated with heterogeneous neuropathology. The clinical course of HSD is more similar to that of FTD than AD. These findings, together with the neuropathologic data presented in the accompanying article, support expanding the scope of FTD (Pick complex) to include HSD.

Objective: To assess the usability of archived plasma and serum by multiplex (Luminex) analysis of circulating proteins (analytes) by evaluating the day to day variation, the effect of several freeze-thaw cycles, and the influence of the media and choice of anticoagulant.Methods: Nineteen analytes in plasma and serum from 86 head and neck cancer patients and 33 controls were evaluated: EGFR, leptin, OPN, VEGFR-1, VEGFR-2, IL-2, IL-13, PDGF-bb, TNF, PAI-1, SDF-1a, IL-4, IL-6, IL-8, eotaxin, G-CSF, VEGF, GRO-a, and HGF.Results: The correlation between measurements of the same samples analyzed on different dates was reasonable. However, samples run on different dates could exhibit different absolute values. The 75th percentile of the fold differences for samples run on different dates was 2.2. No significant difference was found between one and four freeze-thaw cycles (except for HGF), and the correlation was high. We found significant differences in mean concentrations of the majority of analytes in different media and with different anticoagulants. Only the following analytes did not show difference in mean concentrations: EDTA plasma vs. serum: leptin and VEGFR-2, LH plasma vs. serum: IL-2, IL-13, and VEGF, LH plasma levels vs. EDTA plasma: IL-2 and IL-4.Conclusion: Stored serum, LH plasma, and EDTA plasma from clinical trials can be used for analysis of circulating cytokines and proteins. Variations in measurements occur, but are within reasonable ranges. The optimal type of media depends on the analytes, as different analytes have low number of measurements below the lower limit of quantification and higher dynamic ranges in different media.

Studies of oxidative damage during the progression of Alzheimer's disease (AD) suggest its central role in disease pathogenesis. To investigate levels of nucleic acid oxidation in both early and late stages of AD, levels of multiple base adducts were quantified in nuclear and mitochondrial DNA from the superior and middle temporal gyri (SMTG), inferior parietal lobule (IPL), and cerebellum (CER) of age-matched normal control subjects, subjects with mild cognitive impairment, preclinical AD, late-stage AD, and non-AD neurological disorders (diseased control; DC) using gas chromatography/mass spectrometry. Median levels of multiple DNA adducts in nuclear and mitochondrial DNA were significantly (p ≤ 0.05) elevated in the SMTG, IPL, and CER in multiple stages of AD and in DC subjects. Elevated levels of fapyguanine and fapyadenine in mitochondrial DNA suggest a hypoxic environment early in the progression of AD and in DC subjects. Overall, these data suggest that oxidative damage is an early event not only in the pathogenesis of AD but is also present in neurodegenerative diseases in general. Levels of oxidized nucleic acids in nDNA and mtDNA were found to be significantly elevated in mild cognitive impairment (MCI), preclinical Alzheimer's disease (PCAD), late-stage AD (LAD), and a pooled diseased control group (DC) of frontotemporal dementia (FTD) and dementia with Lewy bodies (DLB) subjects compared to normal control (NC) subjects. Nucleic acid oxidation peaked early in disease progression and remained elevated. The study suggests nucleic acid oxidation is a general event in neurodegeneration.

"Frontotemporal dementia - Clinical and pathophysiological aspects." Nordic Journal of Psychiatry, 54(2), pp. 149–150