Citations

AbstractBackgroundWhite matter (WM) damage is seen with neurodegenerative and cerebrovascular pathologies and contributes to cognitive dysfunction. We hypothesized that there are multiple disease progression patterns in WM microstructural changes related to aging and dementia, and these can be identified using SuStaIn (data‐driven clustering algorithm for disease subtype and stage discovery) on multishell diffusion MRI (NODDI) data. NODDI provides information on cellular tissue architecture – neurite density index (NDI) measures packing density of axons and dendrites, and free water fraction (FWF) measures unrestricted water, e.g., interstitial and cerebrospinal fluid.MethodWe identified 1136 participants (mean age=70 years, 51% male, 40% Aβ‐positive, 19% MCI/AD dementia) from the Mayo ADRC and Mayo Clinic Study of Aging. We analyzed NDI and FWF in 55 WM regions. We selected a subset of WM features that monotonically changed with clinical disease progression and then applied the Z‐score SuStaIn algorithm.ResultNDI in seven regions and FWF in six regions survived selection criteria (Figure 1). Noteworthy, the NDI regions were predominantly located in the temporal lobe, while FWF regions were primarily distributed in the frontal and subcortical regions. The SuStaIn algorithm discovered two stable clusters: the NDI‐First (Temporal) and FWF‐First (Frontal) groups (Figure 2). For the NDI‐First group, temporal lobe NDI changed early followed by frontal FWF. The FWF‐First group had the reverse order. There was clear phase separation based on which measure changed first. Stages of the NDI‐First group correlated better with meta‐ROI Tau‐PET SUVR and with MMSE than the FWF‐First group (p<0.01), suggesting that NDI‐First may be indicative of a primarily AD pathway.ConclusionGiven NDI changes are likely degenerative and FWF are suggested to be other processes such as neurodegeneration or inflammatory, the observed changes in the temporal and frontal regions may be due to distinct etiologies, i.e., neurodegenerative in the temporal lobes vs. vascular dysfunction often observed in the frontal lobes. The SuStaIn algorithm showed promise in discovering disease subtypes of WM microstructural changes. Further work is needed to understand the mechanistic basis of these observed changes and integrate WM changes for differential etiology identification and disease staging.

AbstractBackgroundScanning laser ophthalmoscopy (SLO) visualizes two important markers of cognitive dysfunction in the retina: vascular changes and amyloid plaque (AP) deposition. The relationship between retinal arteriolar versus venular changes and perivascular amyloid deposition across the continuum of neurodegeneration is imperfectly understood. We investigate the retinal perivascular AP distribution in relationship to cognitive and neuroimaging measures in a cohort of cognitively normal and impaired individuals.Method34 subjects with normal or impaired cognition underwent retinal SLO, brain magnetic resonance imaging and standard neuropsychometric testing. Retinal peri‐arteriolar and peri‐venular curcumin positive AP were quantified in the supero‐temporal retinal quadrant, in the first, second and third‐order retinal vascular branches. The peri‐venular and peri‐arteriolar AP count were compared between patients with normal and impaired cognition, and their correlation with brain volumes, white matter hyperintensities and cognitive Z‐scores was determined.ResultWe analyzed retinal para‐venous and para‐arteriolar amyloid count in 28 subjects, mean (SD) age 65 (7.3), 50% female, 19 (52.6%) with impaired cognition. Para‐arteriolar plaque count was higher than peri‐venular plaque in the entire cohort (p<0.0001). Secondary branch peri‐venular amyloid plaque count was higher in patients with MOCA ≤26. Tertiary branch perivascular AP count significantly and negatively correlated with hippocampal volume and positively correlated white matter hyperintensity lesion count.ConclusionRetinal AP deposit peri‐arteriolarly overall and peri‐venularly in the secondary branches in cognitively impaired. Perivascular amyloid burden in small retinal branches correlates with hippocampal volume and white matter hyperintensities.

AbstractBackgroundThe quantification of neurofilament light chain (NfL) in blood and cerebrospinal fluid (CSF) has proved useful in many contexts, for the diagnosis and prognosis of various neurological disorders. There is, however, a diversity of practices between centers, essentially linked to the context of use (COU), analytical methods, consideration of comorbidities, determination of cut‐points or use of interpretation scales. Finally, for the same biochemical profile, the interpretation and reporting of results may differ from one center to another, raising the question of test commutability. To date, no consensus has been reached between the different laboratories involved to define the most appropriate conclusions/comments based on COU and cut‐points. This work is an essential step towards consensual harmonization of the clinical use of NfL after CSF and/or blood analysis in various neurological contexts, as advocated by the Alzheimer's Association "Biofluid Based Biomarkers PIA" working group.MethodThis international project involves 58 clinical laboratories in 16 countries, specializing in the biochemical diagnosis of neurological disorders. By means of a questionnaire, we obtained a description of the COU, pre‐analytical and analytical (biological fluid and method used to quantify NfL) protocols of all the centers involved.ResultsOf the centers, 42% quantified NfL in CSF, 29% in serum and 28% in plasma, and 1% in dried blood spot. The COUs were as follows: Frontotemporal dementia (FTD, 17%), Alzheimer's disease (AD, 16%), multiple sclerosis (MS, 16%), amyotrophic lateral sclerosis (ALS, 11%), psychiatric syndrome (PS, 10%), Creutzfeldt‐Jakob disease (CJD, 8%), Parkinson's disease (PD, 8%), peripheral neuropathy (PN, 7%) and traumatic brain injury (TBI, 7%). Most centers define pathological cut‐points based on published literature and take age into account (50%).ConclusionOur initial results highlight the state of the art in terms of the clinical use of NfL analysis in CSF and blood in the context of different neurological diseases. We have now defined a coordinator for each COU subgroup and are organizing consensus meetings to harmonize the use and reporting of NfL measurements for the identified clinical applications. The results of these next steps will be presented.

AbstractBackgroundGlial fibrillary acidic protein (GFAP) is a marker of cerebral astrogliosis and occasionally elevated in patients with dementia. GFAP in cerebrospinal fluid (CSF), is routinely requested in referrals to neurochemistry laboratories; however, its ability to differentiate dementias and diagnostic capability is unclear. Our aim was to elucidate this, using two large datasets.MethodFirst, GFAP data measured since 2015 was retrieved from the database of the Clinical Neurochemistry Laboratory at the Sahlgrenska University hospital. We then cross‐referenced with the Swedish dementia registry (SveDem). Here, information on ten different diagnoses such as early onset AD (EAD [<65 years]), late onset AD (LAD [≥65 years]), Parkinson disease with dementia (PDD), vascular dementia (VaD) and frontotemporal dementia (FTD), each with specific diagnostic criteria, were retrieved.The GFAP data was log10‐transformed, followed by an analysis of covariance (ANCOVA) and a subsequent post‐hoc Tukey’s test, with GFAP as dependent variable, diagnosis as independent variable and sex and age as covariates.ResultIn total, 1912 individuals (mean [SD] age, 71.9 [8.2] years; 52% male), were included. Lower log10‐transformed GFAP concentrations were seen in PDD (mean [SD], 2.68, [0.28] pg/mL), than in EAD, LAD, VaD and FTD; here, mean concentrations of 2.76 (0.24), 2.89 (0.23), 2.89 (0.32) and 2.76 (0.25) pg/mL were observed, respectively.In the post hoc analysis, GFAP differentiated VaD from EAD (p<0.001). PDD concentrations were significantly different from VaD (p<0.001) and LAD (p<0.001). Further, it also differentiated FTD from VaD (p=0.006) and LAD (p=0.001).ConclusionCSF GFAP could on a group level help differentiate VaD from EAD, FTD and PDD. Also, it could differentiate PDD from LAD. These results bear potential clinical relevance, where clinicians in some uncertain cases could use this marker as a differential tool.

AbstractBackgroundThere is limited information on biomarker‐defined Alzheimer’s disease (AD) pathology in community‐recruited individuals of diverse racial and ethnic groups. Here, we assessed the association of race/ethnicity with baseline biomarkers and cognitive measures and hypothesized a lower impact of AD pathology in non‐Hispanic White (nHW) participants in the U.S. POINTER study clinical trial, which evaluates the benefits of a multidomain lifestyle intervention on cognition of community‐recruited at‐risk elderly individuals.MethodWe included 879 participants from the U.S. POINTER study enrolled in the imaging substudy (∼50% of participants) who self‐identified as nHW (n=644), African American/Black (AA/B, n=132), Asian (n=29), and Hispanic (n=74). Outcomes measures included global Aβ pathology (18F‐florbetaben), temporal meta‐ROI tau (18F‐MK‐6240), MRI‐measured white matter hyperintensity volume (WMH) volumes, global clinical dementia rating (gCDR), and global, executive, and memory standardized cognitive scores. The nHW participants were selected as reference. Power transformations normalized skewed distributions. Multivariable linear regressions include age, sex, education, Framingham risk score, and area deprivation index (ADI) as covariates.ResultAA/B harbored lower WMHs, and meta‐temporal tau ROI values. In the full model, 0.5 gCDR participants had higher centiloid values, were more likely to be AA/B and Hispanic, and had a greater burden of WMHs. In addition, higher centiloid values were associated with a 0.5 gCDR in all groups except for the AA/B participants. Hispanic, AA/B, and Asian participants had lower cognitive scores than the nHW group. A higher ADI score was associated with lower global and executive cognitive scores but not with WMH volume or Aβ centiloid score.ConclusionThe analyses of the community‐based U.S. POINTER indicate that AA/B individuals present differences in AD and related dementia biomarker values. nHW had higher fully adjusted cognitive scores. These results indicate a significant heterogeneity in the cognitive testing performance and biomarker values of individuals at risk for dementia in the community.

AbstractBackgroundTransactive response DNA‐binding protein of 43 kDa (TDP‐43) is implicated in numerous neurodegenerative diseases, including Alzheimer’s disease (AD). Immunohistochemically stained TDP‐43 is linked to faster rates of hippocampal atrophy (HA) in AD. However, it is unclear whether phosphorylated TDP‐43 (pTDP‐43) measured using an immunoassay is also associated with HA. We explored associations between pTDP‐43 levels, TDP‐43 immunohistochemistry, and annual rate of HA in AD. We hypothesized that higher pTDP‐43 levels would be associated with positive TDP‐43 immunohistochemistry, and faster rates of HA.MethodThirty‐seven cognitively impaired participants from the Mayo Clinic Alzheimer’s Disease Research Center underwent serial brain MRIs and brain autopsy. Hippocampal TDP‐43 was detected histochemically, and pTDP‐43 was quantified using biochemical assay. Hippocampal volumes were measured using the longitudinal pipeline in FreeSurfer‐7 and annualized HA rates were calculated. Linear regression analyzed the relationship between HA and pTDP‐43 biochemical assay levels. pTDP‐43 was categorized as positive (≥400) or negative (<400), and logistic regression tested the association of these levels with HA rates. The correlation between TDP‐43 immunohistochemistry status and biochemical assay levels was evaluated using descriptive statistics. All analyses were adjusted for potential confounders.ResultsThe mean age at death was 83.5 (±9.9) years with 49% females. Median scan interval was 3‐years. A negative relationship was observed between age at death and annual HA rate (β=‐3.1; 95% CI [‐5.3,‐0.9]; p=0.007), and a positive relationship was observed between pTDP‐43 level and annual HA rate (β=0.02; 95% CI [0.003,0.03]; p=0.015). A one‐unit increase in HA rate was associated with a 3% increase in the odds of being pTDP‐43 positive (≥400) (odds ratio=1.03; CI [1.007,1.05]; p=0.014). Cases that tested positive for Immunohistochemistry TDP‐43 had significantly higher mean pTDP‐43 immunoassay levels (1508 ± 2072 vs. 202 ± 131; p=0.008). More cases with positive IHC TDP‐43 surpassed the pTDP‐43 immunoassay cut‐off level of 400 vs the negative participants (p=0.003).ConclusionHigher pTDP‐43 levels in the hippocampus are linked to faster HA in AD and correlated with immunohistochemistry TDP‐43 positivity. These findings underscore the role of TDP‐43 in AD neurodegeneration. The biological and clinical implications of these observations necessitate further exploration in subsequent studies.

AbstractBackgroundCerebral small vessel disease (SVD) related vascular contributions represent a major factor contributing to cognitive decline and dementia (VCID) in older adults. However, there has not been a validated biomarker for the diagnosis and treatment monitoring of this condition. Recently, the US National Institute on Neurological Disorders and Stroke (NINDS) funded the MarkVCID Consortium to identify and validate clinical‐trial‐ready biomarkers for VCID. Cerebrovascular reactivity (CVR) MRI is one of the selected biomarkers that underwent multi‐site testing in the Consortium. The present study aimed to report the relationship between CVR and cognitive function at independent sites, based on a pre‐specified hypothesis.MethodCVR, the ability of cerebral small vessels to dilate upon stimulus, is thought to directly reflect physiological function of the brain microvasculature. Based on previous single‐site findings, the pre‐defined hypothesis was that CVR will be associated with the global cognitive function measured by Montreal Cognitive Assessment (MoCA) after adjusting for age, sex, and education, and this association will be observed in data collected and analyzed at each individual site.A total of 264 older participants from three sites were included (Table 1). Each site performed an identical CVR MRI procedure using 5% CO2 inhalation, and a standardized clinical and cognitive evaluation. Multi‐linear regression analysis was conducted on a site‐by‐site basis to examine the pre‐defined hypothesis.ResultGray‐matter CVR showed a positive association with MoCA score after adjustment for age, sex, and education, in which participants with higher CVR had higher MoCA scores. This relationship was reproduced at each site (Figure 1, p<0.05 for each), confirming our pre‐specified hypothesis.In the secondary analysis of all data together, higher gray‐matter CVR was found to be significantly associated with better executive function measure of item response theory (IRT) score (β=2.87, p=0.003).ConclusionThe present study evaluated the relationship between CVR and cognition in a multi‐center setting. CVR was found to be positively associated with global cognitive function measured by the MoCA, which was shown to be reproducible across different sites with diverse cohorts. These findings support the utility of CVR as a biomarker in future clinical trials of SVD and VCID.

AbstractBackgroundChronic kidney disease (CKD) has been associated with increased plasma phosphorylated Tau217 (pTau217) concentrations, potentially confounding its utility in the evaluation of Alzheimer's disease (AD). We assessed the association of estimated glomerular filtration rate (eGFR) with plasma pTau217 concentrations measured by various assays.MethodWe included 195 participants from the Mayo Clinic Study of Aging or the Alzheimer’s Disease Research Center with diagnoses of cognitively unimpaired (n=114), mild cognitive impairment (n=70), and AD dementia (n=11). Amyloid‐PET was performed with Pittsburgh 11C‐Compound B; abnormal amyloid (A+) was defined as SUVR ≥1.52 (Centiloid ≥25). eGFR was determined based on serum creatinine concentrations. pTau217 was quantified using ALZpath Simoa pTau217 immunoassay, Fujirebio Lumipulse G pTau217(N‐Terminal) immunoassay, and a pTau217 mass spectrometry (MS) assay (C2N Diagnostics). Additionally, a pTau217 ratio (pTau217 to non‐phosphorylated [npTau217]) was calculated using the MS assay. Linear regression was used to assess associations of continuous eGFR with plasma pTau217 and amyloid PET. Differences in mean plasma concentrations between eGFR groups by amyloid PET status were evaluated with one‐way ANOVA tests and associated confidence intervals for each sample mean.ResultMedian pTau217 concentrations in the A+ and A‐ groups were higher in individuals with eGFR <60 mL/min/1.73 m2 compared to those with eGFR ≥60 in all assays except for the A+ group when using the pTau217/npTau217 ratio. A 10‐unit worsening of eGFR was associated with higher pTau217 mean concentrations as follows: 24% (95% CI, 13‐36%) for C2N pTau217, 16% (9‐24%) for ALZpath pTau217, and 12% (5‐20%) for Lumipulse pTau217. eGFR was not significantly associated with the pTau217/npTau217 ratio or amyloid‐PET.ConclusionCKD was associated with increased pTau217 concentrations when measuring pTau217 but not when using the pTau217 ratio. Additional research is needed to better understand the confounding effects of CKD in the clinical interpretation of plasma pTau217 assays.

AbstractBackgroundTau phosphorylated at threonine 217 (pTau217) is one of the most promising blood‐based biomarkers of Alzheimer’s disease (AD). This study compares the performance of two plasma pTau217 immunoassays on the Simoa platform for detection of abnormal amyloid‐PET.MethodPlasma samples from 112 individuals without cognitive impairment and 114 with mild cognitive impairment (MCI) or AD related dementia were evaluated. Testing was performed on the Quanterix Simoa® HD‐X Analyzer using the ALZpath Simoa® pTau217 and the Simoa® ACC pTau217 (Janssen antibodies) commercial assays. Amyloid‐PET imaging was performed using 11C‐Pittsburgh Compound B and a standard uptake value ratio (SUVR) cutoff of ≥1.52 (≥25 Centiloid) was used for abnormal (n= 147) vs. normal (n= 79) classification. Passing‐Bablok regression analysis and Spearman’s correlation coefficient (rho) were used to estimate bias and correlation between the assays, respectively. Correlation of each assay with Amyloid‐PET SUVR was evaluated. Amyloid‐PET status as the outcome and plasma pTau217 as predictor was used to estimate the area under the receiver operating characteristic (ROC) curve (AUC).ResultThe pTau217 concentrations between the two assays showed an excellent correlation (Spearman’s rho= 0.94 [95% CI= 0.93 to 0.96, p<0.0001]). However, the Passing‐Bablok regression analysis equation for ALZpath (x‐axis) and ACC (y‐axis) was y= 0.1324x ‐ 0.0019, showing that measured pTau217 concentrations with the ALZpath assay were higher (∼87%) than with the ACC assay (concentrations ranged 0.057 to 3.5 pg/mL and 0.003 to 0.5 pg/mL, respectively). Correlations between amyloid‐PET SUVR and the two pTau217 immunoassays were almost identical with Spearman’s rho= 0.70 (95% CI= 0.62 to 0.76, p<0.0001) for ALZpath and 0.69 (95% CI= 0.61 to 0.75, p<0.0001) for ACC. The AUC for detection of an abnormal amyloid‐PET among the MCI/AD group was 0.88 (95% CI= 0.81 to 0.95) for ALZpath, and 0.89 (95% CI= 0.83 to 0.96) for ACC.ConclusionAnalytically, the two Simoa® pTau217 assays correlate well with each other, but results are not interchangeable due to a significant proportional bias. Clinically, the performance of the assays was largely equivalent for the detection of abnormal amyloid‐PET by AUC analysis based on their almost identical correlations with amyloid‐PET SUVR.

AbstractBackgroundPlasma biomarker development is of increasing interest due to improved accessibility compared to established diagnostic modalities for Alzheimer’s disease (AD). However, current plasma biomarker candidates have not been tested comprehensively in diverse populations, and these markers represent only a fraction of pathways perturbed in AD. Therefore, there is a need to identify novel plasma biomarkers that account for both disease heterogeneity and patient diversity. This study seeks to address these knowledge gaps through untargeted plasma biomarker discovery in African Americans (AA), an underrepresented group in AD research despite having a higher risk of developing AD compared to non‐Hispanic Whites.MethodsUntargeted proteomics were performed using the SomaScan 7k assay on plasma samples from AA study participants clinically diagnosed as AD (n=142) or cognitively unimpaired (CU, n=144). Linear regression models adjusted for age, sex, and batch were implemented to identify differentially expressed proteins (DEPs). APOE was additionally adjusted for in a sensitivity analysis. DEPs with the lowest q‐values were selected as predictors in a receiver operating characteristic (ROC) analysis to assess their accuracy to discriminate AD versus CU individuals.ResultsA total of 153 DEPs were identified (q<0.05) when adjusting for age, sex, and batch, and 100 DEPs were identified when additionally adjusting for APOE. Of the 66 proteins overlapping between these models, SERPINA3, C7, IGFBP‐2, DKK3, SMOC1, and ACES had the lowest q‐values and were included in a ROC model adjusted for age, sex, and APOE. That model classified AD versus CU with an area under the curve (AUC) of 0.87 (95%CI: 0.83‐0.91), a 10.4% improvement over the base model including age, sex, and APOE (AUC=0.78; 95%CI: 0.72‐0.83). Despite the unbiased selection of proteins included in the ROC model, all selected proteins have been associated with AD and implicated in related functional pathways such as neuroinflammation, synaptic function, and insulin signaling.ConclusionThis preliminary plasma biomarker panel demonstrates the potential diagnostic capabilities of biomarker discovery through untargeted proteomics. Future directions include validation of findings in external datasets, concomitant assessment of p‐tau217, and evaluation of machine learning models to define the optimal diagnostic and predictive set of plasma protein biomarkers for AD in AA.