Mild Alzheimer's Disease Research Articles

Validation of the Moroccan version of the MMSE test (MMSE-MA) in Moroccan patients with mild cognitive impairment or Alzheimer's disease

Validation of the Moroccan version of the MMSE test (MMSE-MA) in Moroccan patients with mild cognitive impairment or Alzheimer's disease

Associations of serum DNA methylation levels of chemokine signaling pathway genes with mild cognitive impairment (MCI) and Alzheimer's disease (AD).

To investigate the associations of serum DNA methylation levels of chemokine signaling pathway genes with Alzheimer's disease (AD) and mild cognitive impairment (MCI) in elderly people in Xinjiang, China, and to screen out genes whose DNA methylation could distinguish AD and MCI. 37 AD, 40 MCI and 80 controls were included in the present study. DNA methylation assay was done using quantitative methylation-specific polymerase chain reaction (qMSP). Genotyping was done using Sanger sequencing. DNA methylation levels of ADCY2, MAP2K1 and AKT1 were significantly different among AD, MCI and controls. In the comparisons of each two groups, AKT1 and MAP2K1's methylation was both significantly different between AD and MCI (p < 0.05), whereas MAP2K1's methylation was also significantly different between MCI and controls. Therefore, AKT1's methylation was considered as the candidate serum marker to distinguish AD from MCI, and its association with AD was independent of APOE ε4 allele (p < 0.05). AKT1 hypermethylation was an independent risk factor for AD and MAP2K1 hypomethylation was an independent risk factor for MCI in logistic regression analysis (p < 0.05). This study found that the serum of AKT1 hypermethylation is related to AD independently of APOE ε4, which was differentially expressed in the Entorhinal Cortex of the brain and was an independent risk factor for AD. It could be used as one of the candidate serum markers to distinguish AD and MCI. Serum of MAP2K1 hypomethylation is an independent risk factor for MCI.

Validation of the free and cued selective reminding test in Moroccan patients with mild cognitive impairment or Alzheimer's disease

Validation of the free and cued selective reminding test in Moroccan patients with mild cognitive impairment or Alzheimer's disease

Comparison of metrological qualities of the Moroccan versions of MMSE (MMSE-MA) and MOCA (MOCA-MA) for detecting mild cognitive impairment and Alzheimer's disease in Moroccan population

Comparison of metrological qualities of the Moroccan versions of MMSE (MMSE-MA) and MOCA (MOCA-MA) for detecting mild cognitive impairment and Alzheimer's disease in Moroccan population

Plasma biomarkers across the Alzheimer’s disease continuum in the New Zealand‐Dementia Prevention Research Clinics

AbstractBackgroundAdvances in ultra‐sensitive immunoassay methods, like Single molecule array (Simoa) technology, show that Alzheimer’s disease (AD) neuropathology can be detected in blood at the earliest stages of AD. This study compared cross‐sectional biomarker profiles for participants from the New Zealand‐Dementia Prevention Research Clinics (NZ‐DPRCs) who spanned the continuum from healthy older adults to a clinical diagnosis of AD.MethodBlood plasma samples were obtained from 253 NZ‐DPRC participants (aged 55 to 87) from their baseline assessment. Participants were classified as cognitively normal adults (CN, n = 34), subjective cognitive decline (SCD, n = 64), non‐amnestic mild cognitive impairment (single and multi‐domain, non‐aMCI, n = 23), amnestic MCI (single and multi‐domain, aMCI, n = 105), and AD (n = 27). Six plasma biomarkers were selected for quantification by the HD‐X Simoa analyser (Quanterix, Billerica, MA; University of Gothenburg, Sweden): AD biomarkers amyloid‐beta peptides (Aß1‐40; Aß1‐42) and phosphorylated tau species (p‐tau181; p‐tau231); neurofilament light (NfL), for general neuronal damage; and glial fibrillary acidic protein (GFAP), for astrocyte activation. Clinical, imaging and genetic demographic data were assessed in relation to the plasma biomarkers.ResultPlasma biomarkers across the five groups (figure 1) were assessed by linear regression adjusted for age and sex. P‐tau181, p‐tau231, GFAP and NfL were natural log‐transformed to approximate normality and improve homogeneity of variance. Biomarkers p‐tau181, p‐tau231, GFAP, NfL, Aß1‐42/Aß1‐40 ratio and Aß1‐42, all showed group effects (P &lt; 0.05; Aß1‐40, p&lt;0.08). Tukey’s HSD post‐hoc test for pairwise group comparisons showed significant differences in GFAP for AD vs CN, SCD, non‐aMCI as well as SCD vs MCI (P &lt; 0.05); p‐tau181 for AD vs CN and SCD (P &lt; 0.05); p‐tau231 for AD vs non‐aMCI (P &lt; 0.05); Aß1‐42 for aMCI vs CN and SCD (P &lt; 0.05); Aß1‐42/Aß1‐40 ratio for SCD vs aMCI (P &lt; 0.05). ROC analysis will be reported for the diagnostic accuracy of these blood analytes.ConclusionSimoa‐quantitated blood biomarkers in the NZ‐DPRC cohort differentiates clinical groups spanning the AD continuum cross‐sectionally.

Relationships between KLOTHO and APOE4‐associated β‐amyloid and tau alterations across AD continuum

AbstractBackgroundApolipoprotein E ε4 allele (APOE4) is the leading genetic risk factor for Alzheimer’s disease (AD). APOE4 carriers (APOE4+) exhibit greater accumulation of the two AD neuropathological hallmarks, beta‐amyloid (β‐amyloid) and tau. KLOTHO KL‐VS heterozygosity (KL‐VSHET) attenuates APOE4‐related β‐amyloid and age‐related tau burden in cognitively normal individuals. It remains unclear whether this holds true for individuals with mild cognitive impairment (MCI) and AD. Here we investigate whether KL‐VSHET attenuates APOE4‐related cerebrospinal fluid (CSF) AD‐biomarker burden across the AD continuum.MethodMiddle‐aged and older adults (N = 396; MeanAge = 65) from the Wisconsin Registry for Alzheimer’s Prevention and Wisconsin Alzheimer’s Disease Research Center who were genotyped for KLOTHO and APOE and underwent CSF sampling were included in analyses. General linear models, covarying for sex, age, and AD family history, examined whether APOE4 yielded expected outcomes on β‐amyloid and tau burden. Follow‐up regression analyses, stratified by KL‐VS genotype [non‐carriers(KL‐VSNC,N = 293); KL‐VSHET (N = 103)], evaluated whether the APOE4 associations with β‐amyloid and tau differed between KL‐VSHET and KL‐VSNC. Analyses were stratified further by diagnosis [cognitively normal (N = 308) or MCI/AD (N = 88)] to investigate whether the relationships between APOE4 and β‐amyloid or tau differed among KL‐VSHET and KL‐VSNC in cognitively normal and MCI/AD participants.ResultResults for the entire sample, as well as stratified by KL‐VS status and diagnosis, are presented in Table 1. When the analysis was stratified by KL‐VS status, the APOE4+ effect on both β‐amyloid and tau burden was seen among KL‐VSNC but not KL‐VSHET. When further stratifying by diagnosis, the same pattern of attenuation among KL‐VSHET was observed for β‐amyloid burden in both cognitively normal individuals and MCI/AD whereas for tau burden, we only observed a non‐significant trend among cognitively normal persons (KL‐VSNC: p = 0.10; KL‐VSHET: p = 0.74).ConclusionKL‐VSHET attenuates both APOE4‐related CSF β‐amyloid and tau burden in cognitively normal individuals. This attenuation extends to CSF β‐amyloid but not tau accumulation in MCI/AD. These results add to the literature suggesting that KL‐VS heterozygosity is protective against APOE‐related biomolecular alterations that confer AD risk.

Microbial infection and associated inflammasome in the retina of Alzheimer’s disease patients

AbstractBackgroundRecent advances in Alzheimer’s disease (AD) research revealed that AD pathology is not confined to the brain but also occur in the neurosensory retina. Data have further suggested parallels between retinal and brain AD biomarkers. While the exact etiology of AD pathogenesis is undefined, an emerging theory has linked AD with microbial infection as a plausible cause for AD progression. The presence of several microbes including Chlamydia pneumoniae (Cp), Borrelia burgdorferi, Porphyromonas gingivalis, and Toxoplasma gondii have been reported in the post‐mortem brain of AD patients and murine models. However, the existence and role of microbial infection in AD retina has never been studied.MethodWe employed a range of histological, biochemical, and genetic techniques to detect bacterial infection and other associated biomarkers in postmortem retinas of patients with mild cognitive impairment (MCI) or AD dementia, compared to retinas from age‐matched individuals who displayed normal cognition (NC). We assessed the presence and burden of Cp and correlated with gliosis, inflammasome, and apoptosis markers.ResultWe discovered the presence of Cp inclusions in postmortem retinas of patients with MCI and AD as compared to age‐ and sex‐matched NC individuals. Our experimental evidence revealed Cp‐infected retinal neuronal cells in AD patients, with no increase in retinal Cp infection in MCI versus CN and a significant 4‐fold increase in of Cp immunoreactivity in retinas of AD patients versus MCI and CN subjects. These data possibly indicate that Cp infection mainly occur during the dementia phase of AD and is less observable at the early functional impairment stages of AD. Retinal microglia were found to aggregate around and engulf Cp‐infected cells. Alongside Cp infection, retinal tissues from MCI and AD patients exhibited increased NLRP3 inflammasome and gliosis. Our data suggest Cp‐triggered inflammasome activation, that can lead to neuronal degeneration. We further found a relationship between the severity of retinal Cp infection and brain pathology; retinal Cp burden was associated with brain neurofibrillary tangles, neuropil threads, Braak stage.ConclusionCp‐triggered chronic inflammation could be a detrimental process leading to retinal degeneration in AD, suggesting potential new therapeutic avenues involving early antibiotic treatment or inflammasome attenuation.

The impact of young controls in the detection of tau load in cognitively impaired and asymptomatic elderly

AbstractBackgroundNeuropathological observations report incipient tau accumulation in the human brain starting in the third decade of life, with the proportion of individuals with some degree of tau deposition increasing with age. Given the high prevalence of tau positive cases among cognitively unimpaired (CU) older adults, one may question whether these individuals constitute an ideal reference group when assessing tau load in symptomatic population. Here, we compare tau biomarker levels of participants with Alzheimer’s disease (AD) and CU of different ages.MethodWe evaluated 35 CU young individuals (aged &lt;26 years) and 124 amyloid‐beta (Aβ)‐ elderly, considered the two control groups. We also assessed 42 Aβ+ CU and 122 Aβ+ cognitively impaired (CI) individuals, diagnosed with either mild cognitive impairment or AD dementia. Participants were assessed with 18F‐MK6240 positron emission tomography (PET) and CSF and plasma pTau181, 217, 231 and 235. We used linear regression to perform voxel‐wise comparisons of tau‐PET signal between groups. We compared the standardized uptake value ratio (SUVR) in medial‐temporal and Braak‐like regions‐of‐interest (ROI) and fluid biomarkers levels using the Wilcoxon rank sum test.ResultIn the voxel‐wise comparisons (Figure 1A‐E), CI participants presented more widespread cortical signal than control groups. Less signal in the parietal cortex was observed in the comparison with CU young. Higher t‐values were observed in Aβ+ CU individuals in the medial temporal region, compared to both control groups, and adjacent neocortex, especially compared to CU young. Temporal and Braak V‐VI SUVR were higher in CI but not in Aβ+ CU individuals compared to controls. Moreover, Braak I‐II and III‐IV SUVR and the fluid biomarkers levels were higher in both Aβ+ groups compared to controls (Figures 2A‐D; 3A‐G). Importantly, Braak I‐II SUVR and the CSF biomarkers levels were higher in CU old Aβ‐ versus young.ConclusionHere, we provide in vivo evidence that tau‐load in age‐matched Aβ‐ controls constitutes a bias for identifying tau pathology, particularly in individuals at early stages of AD pathophysiology. Age‐related tau load should be considered when selecting control groups to assess tau in symptomatic populations, especially those with early AD, and when defining criteria for tau abnormality.

Blood co‐expression network analysis identifies molecular pathways involved in cognitive resilience

AbstractBackgroundTwo major risk factors of Alzheimer’s disease (AD) are advanced age and the APOE‐ε4 risk allele. However, despite having these risk factors, some individuals escape from developing AD or have slower cognitive decline. In this study we hypothesized that “resilient” individuals, defined as those who remain cognitively normal despite being &gt;80 years‐old and carrying at least one copy of the APOE‐ε4 allele, have concerted changes in their blood transcriptomes that are associated with resilience to AD.MethodWe generated blood RNA‐sequence data from 105 APOE‐ε4 carriers from the Mayo Clinic Study of Aging (MCSA) who remained cognitively normal after age 80 (resilient), or who developed mild cognitive impairment (MCI) or AD (non‐resilient). Weighted gene co‐expression network analysis (WGCNA) was performed to evaluate the association of the blood co‐expression network with primary phenotypes of resilience and memory scores. To validate our findings, we constructed a consensus co‐expression network using both MCSA and a replication cohort of blood microarray data from 91 Alzheimer’s Disease Neuroimaging Initiative (ADNI) study participants who had a similar demographic profile. We annotated the consensus modules for their enrichment of cell types, biological processes, genes within previously published genome‐wide significant (GWS) AD‐associated loci, and genes that reside in consensus modules built from seven brain regions across three different autopsy cohorts. To identify genetic variants regulating blood consensus module co‐expression, we performed module quantitative trait locus (modQTL) analysis.ResultWe found co‐expression modules significantly (q&lt;0.05) correlated with the memory phenotype, logical memory delayed recall, across both MCSA and ADNI cohorts. Some of these modules were enriched with blood cell types and biological processes, including telomere maintenance, mitochondrial functions, and immune response. We found 1 module significantly (q&lt;0.05) enriched with genes near GWS AD‐associated loci and 4 modules with genes in brain consensus modules. Lastly, we found 8 modQTLs significantly (Bonferroni‐p&lt;0.05) associated with the co‐expression of 5 different modules.ConclusionWe identified blood co‐expression modules, biological pathways and specific genetic variants associated with cognitive resilience in the presence of AD risk factors. This study provides novel insights into the potential role of peripheral blood in the development of and resilience to AD.

MiR‐431 attenuates synaptic plasticity and memory deficits in APPswe/PS1dE9 mice

AbstractBackgroundSynaptic plasticity impairment plays a critical role in the pathogenesis of Alzheimer’s disease (AD), and emerging evidence has shown that microRNAs (miRNAs) are alternative biomarkers and therapeutic targets for synaptic dysfunctions in AD. Our previous miRNA assay data have shown that miR‐431 is downregulated in the hippocampus of APPswe/PS1dE9 (APP/PS1) mice. However, the potential role of miR‐431 in AD has not been fully defined.MethodLv‐miR‐431 (1×109 TU/ml, 2 µl), Lv‐Smad4 (1×109 TU/ml, 2 µl) or AAV‐sh‐Smad4 (5×1012 GC/ml, 200 nl) was slowly injected into the bilateral hippocampus of APP/PS1 mice. The behavioral or electrophysiological tests were performed 1 month following the injection, and the mice were then sacrificed for other experiments. QRT‐PCR was used to detect the expression of miR‐431 in plasma and hippocampus. Golgi staining and electron microscopy were performed to evaluate the synaptic structure. Western blot was employed to test the levels of synaptic associated proteins. Immunofluorescence staining and ELISA were utilized to assess hippocampal Aβ levels. Cut&amp;Tag assay and ChIP were used to explore and confirm the potential targets of Smad4.ResultThe level of miR‐431 was downregulated in the plasma of amnestic mild cognitive impairment (aMCI) and AD patients, and it was also decreased in the hippocampus and plasma of APP/PS1 mice. MiR‐431 overexpression in the hippocampus ameliorated synaptic plasticity and memory deficits of APP/PS1 mice, while it didn’t affect the Aβ levels. Smad4 was identified as a target of miR‐431, and Smad4 overexpression reversed the protective effects of miR‐431 in APP/PS1 mice. Furthermore, Smad4 knockdown modulated the expression of synaptic proteins including SAP102, and protected against synaptic plasticity and memory dysfunctions in APP/PS1 mice.ConclusionMiR‐431 attenuates synaptic impairment at least partially by Smad4 inhibition and miR‐431/Smad4 may be a potential therapeutic target for AD treatment.

Associations of white matter hyperintensities with cerebrovascular architecture in Alzheimer’s disease and related dementias

AbstractBackgroundMRI‐detected white matter hyperintensities (WMHs), a marker of cerebrovascular‐pathology, are common in Alzheimer’s disease (AD) and related dementias (ADRDs). In stroke, WMH‐volume was found to correlate most with stroke risk‐factors in the anterior cerebral arterial‐territory. Since the relationship between WMHs and arterial‐territories remains unexplored in the ADRDs, we systematically investigated WMHs’ spatial distribution (1) in 8 ADRDs relative to cognitively unimpaired (CU), and (2) across arterial‐territories per ADRD.MethodsThe extensive CCNA‐COMPASS‐ND cohort (N = 927) allowed us to investigate 9 clinical categories: CU, subjective (SCI) and mild (MCI) cognitive impairment, vascular MCI (V‐MCI), AD, vascular AD (V‐AD), Lewy‐body dementia (LBD), fronto‐temporal dementia (FTD), and Parkinson’s disease (PD) (Fig.1A). FLAIR and T1w MRI‐scans were used to segment WMHs (Dadar et al.,2017). Following registration to standard space, an arterial‐territory atlas (Schirmer et al.,2019) was used to calculate WMH‐volumes in 10 regions (Fig.1B). Statistical analyses were run on whole‐brain‐WMH‐volume and regional‐WMH‐ratios (region‐size‐normalized‐WMH‐volume/whole‐brain‐WMH‐volume). Data‐analyses used a series of linear models accounting for clinical category, age, and sex – followed by pairwise group‐comparisons corrected for multiple comparisons.Results 1) Relative to CU: Whole‐brain‐WMH‐volumes were higher for V‐MCI, V‐AD, and FTD. WMH‐ratios were higher in MCA and LMCA for 2 ADRDs (SCI;V‐MCI) and lower in PCA, LPCA, and RPCA for SCI. WMH‐ratios were higher in ACA or LACA and lower in PCA, LPCA, or RPCA for 4 ADRDs (V‐MCI;V‐AD;FTD;PD) (Fig.1C). Sex‐analyses: Men’s WMH‐volumes were higher in whole‐brain (CU;V‐MCI;FTD), while their WMH‐ratios were higherin LMCA (CU), but lower in ACA (SCI;MCI), LACA (MCI), and RACA (SCI). 2) MCA contained higher WMH‐ratios than ACA and PCA in all clinical categories. Relative to PCA, ACA’s WMH‐ratio was higher in 2 ADRDs (V‐MCI;V‐AD) and lower in 4 (CU;MCI;AD;PD). Pairwise‐group comparisons between all left/right arterial‐territories demonstrated consistent results (Fig.2). Asymmetry‐analyses: The right arterial side had higher WMH‐ratios in ACA (CU;V‐MCI), MCA (CU;SCI;MCI;V‐MCI;AD;V‐AD;PD), and PCA (MCI;AD).ConclusionWe identified arterial‐territories of increased susceptibility to WMH‐formation per ADRD. The two most prevalent ADRDs (AD;V‐AD) were found to accumulate WMHs in a territory‐specific manner – higher WMH‐ratios in ACA for V‐AD and PCA for AD. Overall, the arterial‐territory‐specific WMH‐signatures identified may improve ADRD‐diagnosis accuracy.

Epigenetic age from peripheral blood predicts progression to Alzheimer’s disease, white matter disease burden, and cortical atrophy

AbstractBackgroundCross‐sectional studies suggest a limited but promising relationship between epigenetic clocks, estimated using DNA methylation patterns, and Alzheimer’s disease (AD) pathophysiology and risk. However, prior analyses did not utilize longitudinal analyses or neuroimaging biomarkers of AD. Herein, we employed survival and structural neuroimaging analyses to test the hypothesis that DNA methylation age predicts AD progression.MethodUsing data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), we calculated two established epigenetic ages, ‘DNAmPhenoAge’ and ‘DNAmGrimAge’ which proxy biologic age and mortality risk, respectively. Using Cox proportional hazard regression analysis in normal controls (NC), we tested whether DNAmPhenoAge/DNAmGrimAge associated with progression to mild cognitive impairment (MCI) or AD. Structural magnetic resonance (MR) images were segmented using Freesurfer 5.1 and a previously described white matter hyperintensity (WMH) quantification pipeline. Multiple regression analysis was used to test whether DNAmPhenoAge/DNAmGrimAge predicted WMH volumes and cortical atrophy.ResultReplicating prior work, we found no significant differences in DNAmPhenoAge and DNAmGrimAge between NC (n = 128), MCI (n = 251), and AD (n = 50) diagnoses. Strikingly, however, in NC participants, both DNAmPhenoAge (p = 0.004) and DNAmGrimAge (p = 0.05) associated with progression to MCI or AD (Figure 1). Even after correction for chronologic age, DNAmPhenoAge remained significantly associated with progression to MCI or AD (p = 0.01). Utilizing samples from across the spectrum of normal aging to AD, DNAmPhenoAge and DNAmGrimAge strongly associated with WMH in all diagnoses (Table 1). Moreover, DNAmPhenoAge remained significantly associated with WMH in select groups after correction for chronologic age (Table 1). Finally, both DNAmPhenoAge and DNAmGrimAge predicted cortical thickness in multiple AD‐relevant regions (Figure 2).ConclusionIn contrast to earlier work suggesting limited applicability of blood‐based DNA methylation scores in the context of AD, our novel survival and neuroimaging analyses have revealed the broad utility of second‐generation epigenetic clocks not only in predicting progression to MCI and AD but also via their association with neuroimaging biomarkers of AD, including white matter disease burden and cortical atrophy in AD‐relevant regions. Easily accessible, blood‐based measures of biologic age therefore represent promising predictors of AD risk and pathophysiology.

Association between known Alzheimer’s disease risk loci and in vivo brain amyloid pathology in a Korean Cohort

AbstractBackgroundMost genome‐wide association studies (GWAS) of Alzheimer’s disease (AD) have been conducted in populations of European ancestry. It is important to determine if known AD‐related variants from these studies are associated with AD biomarkers. Therefore, we investigated the association between known AD risk loci and in vivo brain Aβ deposition in older Korean adults.MethodParticipants (n = 503) from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s disease (KBASE) were analyzed. Older adults who were cognitively normal (CN), had mild cognitive impairment (MCI) or AD dementia (264 CN, 148 MCI, 91 AD) underwent comprehensive assessments including 11C‐PiB‐PET/MRI and blood sampling. Among 76 AD‐related target single nucleotide polymorphisms (SNPs) with genetic evidence compiled by the AD Sequencing Project (ADSP), 38 SNPs with minor allele frequency (MAF)&gt;1% were extracted from TOPMed‐based imputed GWAS genotyping data in KBASE. We employed exploratory univariable logistic regression analysis with Aβ positivity as the dependent variable for each SNP. Then, SNPs with a significance level of p&lt;0.05 were subjected to confirmatory multivariable logistic regression analysis, adjusting for age and sex, with Bonferroni correction.ResultIn the first step of exploratory analyses, we discovered significant differences in Aβ positivity rates between carriers and noncarriers of minor allele of several loci, including rs16824536 in MME, rs11218343 in SORL1, rs4985556 in IL34, rs4277405 in ACE and rs3851179, located in the intergenic region between EED and PICALM. The subsequent confirmatory analysis found an association between these variants and Aβ positivity after adjusting age and sex (Table 1). Notably, the negative association of rs3851179 with Aβ positivity remained significant after correcting for multiple comparisons and after controlling for APOE4 carrier status, age, and sex (OR 0.529, 95% CI 0.345–0.813).ConclusionWe identified associations between several known AD risk loci and Aβ positivity on PET. rs3851179, demonstrated a robust association with in vivo brain Aβ positivity that was independent of APOE4 status. Our findings suggest that rs3851179 may be protective for in vivo Aβ accumulation. Additionally, the findings are needed to be replicated in other populations with different ancestries.

Synaptic Marker NPTX2 Predicts Risk of MCI Clinical Symptom Onset

AbstractBackgroundNeuronal pentraxin 2 (NPTX2) is a synaptic protein involved in the homeostatic regulation of cortical network dynamics and synaptic plasticity. Prior cross‐sectional studies suggest that NPTX2 levels decline across the spectrum of Alzheimer’s disease (AD), and that NPTX2 levels can distinguish individuals with normal cognition vs. mild cognitive impairment (MCI) and AD dementia. Less is known about how levels of NPTX2 among individuals with normal cognition relate to future clinical outcomes. To address this, we examined whether baseline levels of NPTX2 predicted time to onset of clinical symptoms of MCI, both alone and in combination with AD biomarkers, among individuals who were cognitively normal at baseline and have undergone 16.3y of follow‐up, on average.MethodCerebrospinal fluid (CSF) was collected at baseline from 269 cognitively normal BIOCARD Study participants (M baseline age = 57.7y), including 77 (29%) who subsequently progressed to MCI or dementia (Table 1). Baseline NPTX2 levels were measured from three highly correlated peptides using quantitative parallel reaction monitoring mass spectrometry. NPTX2 peptide levels were standardized and averaged to create an NPTX2 composite score. Baseline levels of Aβ42/Aβ40, p‐tau181, and t‐tau were measured using Lumipulse automated electrochemiluminescence assays.ResultIn Cox regression models, lower NPTX2 levels were significantly associated with earlier time to MCI clinical symptom onset (HR = 0.76, 95% CI (0.601, 0.962), p = 0.02; Figure 1a). After accounting for CSF AD biomarkers (i.e., Aβ42/Aβ40 and tau), the association between NPTX2 levels and MCI symptom onset appeared stronger (Table 2; Figure 1b). Importantly, NPTX2 did not interact with AD biomarker levels (all p &gt; 0.11) or APOE‐ε4 genetic status (p = 0.71) in relation to MCI symptom onset.ConclusionCSF levels of the synaptic marker NPTX2 predict time to progress to MCI among individuals with normal cognition, suggesting that NPTX2 may be an early prognostic biomarker of synaptic dysfunction. Moreover, this association appears to be additive and independent of AD biomarker levels. Future work is underway to determine if NPTX2 provides resilience to cognitive impairment in the presence of AD pathology, and if there is a differential relationship with markers of amyloid vs. tau.

Relationships between polymorphisms in keratin genes and Alzheimer’s disease phenotypes.

AbstractBackgroundKeratins are genetically polymorphic and are the largest subset of intermediate filaments. Keratins are also implicated in signaling pathways, inflammation, and disease states. Keratin 9 (KRT9) protein has been identified to have high diagnostic accuracy for Alzheimer’s disease (AD) (PMID:22045497); it was detected in cerebrospinal fluid (CSF) of AD patients but not healthy controls (PMID:24959311). Plasma keratin 9 concentrations also positively correlated with AD‐associated proteins (e.g., apolipoprotein E and tau) in AD patients (PMID:26973255). Post‐translational modification of keratin 83 (KRT83) protein has been associated with serum asymmetric dimethylarginine levels (PMID:34181092), a vascular risk factor implicated in AD. However, our understanding of the role of genetic variation in AD risk is incomplete. Here, we investigate associations between single nucleotide polymorphisms (SNPs) in KRT9, KRT83, and KRT2 (Keratin 2, couples with keratin 9) and AD biomarker phenotypes.MethodIndividuals with mild cognitive impairment (MCI) or AD, and clinically normal controls were selected among ADNI participants. Participants underwent genome‐wide genotyping. Keratin gene variants were identified from the genome‐wide data using dbSNP variant IDs and genotypes were coded additively. Linkage‐disequilibrium‐based clumping on minor allele frequency (MAF) was applied to prioritize more common SNPs. CSF‐Aβ42, ‐tau, and phosphorylated‐tau (p‐tau) levels were quantified via Roche Elecsys immunoassays. Brain‐Aβ deposition was evaluated via normalized PET‐18F‐AV‐45 cortical summary measures (SUVR). White matter hyperintensities (WMH) were obtained from MRI 3D‐T1 and FLAIR sequences via an automated atlas‐based segmentation pipeline. Linear regression models controlling for age, sex, Mini‐Mental State Exam, APOE‐ε4 status, and head size were used to assess association and interaction effects between SNPs and the AD phenotypes in R.ResultAmong included participants (n = 907, 73±7.2 years, 44% female), SNPs in KRT2 (e.g. 3’UTR‐variant rs117041267‐G/A; MAF = 1.4%) and KRT83 (e.g. upstream‐variant KRT83‐rs17119838‐C/T; MAF = 15.6%) were associated with higher CSF‐Aβ42 concentrations (F(2,905) = 4.26,p = 0.014; and F(2,905) = 6.61,p = 0.0014, respectively). Upstream‐variant KRT83‐rs182354391‐C/G (MAF = 1%) showed an association with lower CSF‐tau (F(1,904) = 5.44,p = 0.020). Multiple KRT9 and KRT2 SNPs also showed association with WMH, while KRT2 and KRT83 intron variants showed associations with PET‐Aβ.ConclusionThese candidate gene analyses suggest involvement of multiple keratin family genes in AD, as indicated by differences in amyloid and tau biomarkers, and white matter disease.

Identification of leukocyte surface biomarkers associated with late‐onset Alzheimer’s disease

AbstractBackgroundAltered innate immunity has been long associated with late‐onset Alzheimer’s disease (AD) and its associated blood‐based biomarkers are important for AD diagnosis and prognosis.MethodWe collected 38 participants from the AIBL study, including 22 cognitive normal (CN) individuals with negative amyloid burden (Centiloid [CL] &lt; 15), 5 CN individuals with positive amyloid burden (CL &gt; 15), and 11 mild cognitive impairment (MCI) and AD cases. A total of 17 leukocyte surface antigens were examined by flow cytometry immunophenotyping and compared between healthy controls (CN Ab ‐ve), pre‐clinical patients (CN Ab +ve), and clinical cases (MCI &amp; AD), including CD36, MerTK, Clec7a, RAGE, Tyro3, CR1 (CD35), CX3CR1, CCR2, Axl, LILRB2, LILRB3, LILRB4, PILRA, and P2×7.ResultWe identified leukocyte surface markers differentially expressed between HC, pre‐clinical patients, and clinical cases. Mean fluorescence intensities of CD85d and CD85k were significantly reduced in pre‐clinical patients and cases compared with HC, implicating CD85d and CD85k downregulation in AD pathogenesis. Significant upregulation of RAGE, Tyro3, CCR2, CD85a, and PILRA was also noted in cases compared with HC. Leukocyte surface expressions of RAGE, CCR2, PILRA, and CD85k were significantly associated with the Preclinical Alzheimer’s Cognitive Composite (PACC), which is one of the most accurate estimates of cognition in AD diagnosis.ConclusionOur preliminary investigations into these leukocyte markers demonstrated their dysregulations in pre‐clinical stage of AD, implicating early deficits in innate immunity, as supported by genomic studies of AD. This project will continue collecting more AIBL participants up to 200 to evaluate leukocyte surface markers more comprehensively, which would benefit AD screening and diagnosis.

Correlation between fMRI complexity and cognition in early‐onset Alzheimer’s disease

AbstractBackgroundResting state fMRI (rs‐fMRI) studies in Alzheimer’s disease (AD) have shown that the functional connectivity (FC) of resting brain networks is progressively diminished in subjects with mild cognitive impairment (MCI) and AD. However, FC analysis of rs‐fMRI has limited capability to characterize the dynamic fluctuations of rs‐fMRI signals that possess clinically meaningful information. Recently the use of entropy measures as indices of the complexity of rs‐fMRI time‐series that provide alternative and complementary information to current fMRI‐based approaches has been proposed. Unlike FC that relies on the parcellation of nodes or selection of seed regions for network analysis, entropy measures of rs‐fMRI can be calculated on a voxel‐wise basis across the whole brain.MethodHere we investigated the correlation between cognitive performance and rs‐fMRI complexity in a sample of 35 participants (Table1) from the Estudio de Enfermedad de Alzheimer en Jalisciences (EEAJ) project that recruits Latino persons (age 18‐80 yrs) at‐risk for fully‐penetrant ADAD. Imaging data underwent standard preprocessing. Multi‐scale entropy was calculated using Sample Entropy at 6 temporal scales using a pattern matching threshold of m = 2 and sensitivity threshold of r = 0.5. Voxel‐wise partial Spearman‐rank correlation was used to assess the relation between cognitive scores (MoCA, Trails‐B and Reverse Digit Span) including age and gender as covariates.ResultWe found significant positive associations between fMRI complexity and all three cognitive scores across the study cohort. We did not observe any significant negative correlations. The maps for MoCA and Trails‐B show areas in the anterior cingulate cortex (ACC), bilateral dorsolateral prefrontal cortex (dlPFC) and bilateral parietal cortex. Trails‐B additionally revealed areas in the insular cortex and temporal cortex. For Reverse Digit Span the correlation was more widespread and also showed associations in motor and supplementary motor cortex beside dlPFC and parietal cortex.ConclusionAcross three cognitive tests we observed positive correlation with fMRI complexity in areas representing brain networks involved in executive function and memory processes. Impaired cognitive function thus is represented by reduced fMRI complexity. fMRI complexity might provide a novel imaging metric that is indicative of impaired cognitive function and is complementary to existing imaging approaches.

Comparison of Functional Mobility Performances of People with Alzheimer’s Disease, Mild Cognitive Impairment, and Cognitively Healthy Individuals

AbstractBackgroundOne of the important factors that make it difficult to carry out activities of daily living independently is the decrease in functional mobility. Mobility‐related disability is a major public health issue that reduces the quality of life and increases the need for care, the burden, and the cost of care. However, in the early stages of dementia, the deterioration in motor skills is often overlooked. This study aimed to compare the mobility performance of healthy individuals and people with Mild Cognitive Impairment (pwMCI) and Alzheimer’s disease (pwAD).MethodCognitive level was measured with Montreal Cognitive Assessment (MoCA) and mobility performance was measured using Timed Up and Go Test (TUG) and 5 Times Sit to Stand Test (5XSTST). Statistical analysis was performed using One Way ANOVA in SPSS v.26 and the level of significance was accepted as p&lt;0.05.Results36 pwAD (Age: 74.90±9.25, 53.12% Female), 14 pwMCI (Age: 63.82±12.55 years, 52.6% Female), and 10 cognitively healthy individuals (Age: 60.25±10.23 years, 82% Female) were included the study. The mean of MoCA scores were 12.62±6.36, 22.25±3.04 and 28.5±0.5; TUG results were 15.34±11.83 sec, 7.47±1.41 sec and 6.86±1.98 sec; 5XSTST results were 16,31±7.75 sec, 11.06±1.98 sec and 9.34±2.37 sec. A significant difference was found between the three groups in terms of TUG and 5XSTST results (p = 0.027, p = 0.015, respectively).ConclusionIn pwAD and pwMCI, the decrease in cognition appears to be accompanied by impairment in functional mobility. Motor skills should be evaluated not only in AD diagnosis but also during the prodromal stage to provide early intervention for loss of motor function. Improving motor function should be added to rehabilitation goals before impaired functional mobility begins to affect activities of daily living.

Longitudinal changes of self‐ and informant‐reported cognitive decline in elderly with regard to clinical progression and amyloid‐status

AbstractBackgroundSelf‐ and informant‐reports of cognitive decline have been previously associated with a higher risk of cognitive decline in elderly. Yet, few studies assessed their longitudinal changes over time with regard to both incident mild cognitive impairment (iMCI) and Alzheimer’s disease (AD) pathology. This study aims at describing these links to better understand which trajectories are indicative of higher AD‐risk.MethodWe used data from 501 participants followed‐up annually (2.51±1.35 years) in the DELCODE project. All were cognitively unimpaired, and had an amyloid measurement available, at inclusion. Among them, 145 were amyloid‐positive, and 65 progressed to iMCI during the follow‐up period (31 iMCI‐Aß+). The SCD‐Interview was used to measure (i) the number of cognitive domains in which the participants or its relative perceived a decline (i.e., self‐ and informant‐SCD‐I), and (ii) the number of fulfilled SCD‐plus criteria. Linear mixed‐effect models were used to assess SCD trajectories over time, according to four groups defined by amyloid status and clinical progression (Stable‐Aß‐, Stable‐Aß+, iMCI‐Aß‐ and iMCI‐Aß+). Analyses were adjusted for age, sex and education; and their interaction with time.ResultBoth self‐SCD‐I levels and SCD‐plus scores decreased significantly over time, without significant differences between groups (Figure 1A, 1B). Conversely, informant‐SCD‐I levels did not significantly change over time in the whole sample, although slopes significantly differed between groups. Compared to the Stable‐Aß‐ group, there was a greater increase over time of informant‐SCD‐I report only in iMCI‐Aß+ [est 0.16, SE 0.05, p&lt;.001] (Figure 1C). The resulting discrepancy score (Self‐SCD‐I minus Informant‐SCD‐I) tended to decrease over time with significant differences between groups. Compared to the Stable‐Aß‐ group, the discrepancy score showed a faster decrease over time in iMCI‐Aß+ [est ‐0.21, SE 0.056 p&lt;.001] (Figure 1D).ConclusionLongitudinal patterns in subjective reports of cognitive decline might help identify preclinical AD subjects at higher risk of clinical progression. Specifically, an increase of informant‐reported cognitive decline over time may indicate objective cognitive decline in amyloid‐positive subjects. Conversely, the decrease of self‐reported cognitive decline over time, regardless of the group, may reflect generally reduced concerns after inclusion, or result from current limitations in longitudinal SCD assessment.

A composite measure of atrophy using volumetric T1‐weighted and T2‐FLAIR imaging using the Boundary Shift Integral

AbstractBackgroundWhole‐brain volume loss using T1‐weighted imaging is an established measurement of neurodegeneration. The Boundary Shift Integral (BSI) produces reliable metrics of longitudinal volume loss, used in research studies and clinical trials. With the increased acquisition of volumetric T2‐FLAIR imaging in studies, there is opportunity to produce atrophy metrics using a composite atrophy measure (T1‐weighted and T2‐FLAIR) that is more precise than either modality alone.MethodData from Alzheimer’s Disease Neuroimaging Initiative (ADNI3) were used. Volumetric T1 and T2‐FLAIR weighted imaging were obtained (n = 269), for baseline and follow‐up; Table 1. T1‐weighted images were bias corrected and underwent Geodesic Information Flow (GIF), producing probabilistic brain masks. Masks were resampled to T2‐FLAIR space. The BSI was performed on serial T1‐weighted (gBSI), and T2‐FLAIR (fBSI) separately. We tested differences by diagnosis (control (CN), mild cognitive impairment (MCI) and Alzheimer’s disease (AD)) between indirect volume change, gBSI, fBSI, and composite BSI, using linear regression and effect size. We further compared metric differences within diagnosis, using pairwise correlation, paired samples t‐test, and Pitman’s test of variance.ResultDemographic information is reported in Table 1. fBSI showed good Pearson’s correlation (r) with both gBSI (CN 0.7, p &lt; 0.001; MCI 0.8, p &lt; 0.001; AD 0.9, p &lt; 0.001), and indirect change (CN 0.6, p &lt; 0.001; MCI 0.6, &lt; 0.001; AD 0.7, &lt; 0.001). The composite BSI further showed good correlation with indirect change (CN 0.8, p &lt; 0.001; MCI 0.8, p &lt; 0.001; AD 0.8, 0.004). Mean values by diagnosis are shown in figure 1, along with paired samples t and variance tests. Pairwise comparisons reported in table 2, highlight good diagnostic group separation in all BSI metrics, with overall strong effect sizes for fBSI, composite BSI, and gBSI respectively.ConclusionCalculating atrophy using T2‐weighted imaging is possible using fBSI. This can be used in a composite atrophy measure using fBSI and gBSI. Both fBSI and composite BSI perform well with group separation, and with good correlations with classical atrophy metrics. Future work will explore the influence of White Matter Hyperintensities on BSI.