Browsing by Author "Henson, Rachel L."

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    Comparative Analysis of Alzheimer's Disease Cerebrospinal Fluid Biomarkers Measurement by Multiplex SOMAscan Platform and Immunoassay-Based Approach
    (IOS Press, 2022) Timsina, Jigyasha; Gomez-Fonseca, Duber; Wang, Lihua; Do, Anh; Western, Dan; Alvarez, Ignacio; Aguilar, Miquel; Pastor, Pau; Henson, Rachel L.; Herries, Elizabeth; Xiong, Chengjie; Schindler, Suzanne E.; Fagan, Anne M.; Bateman, Randall J.; Farlow, Martin; Morris, John C.; Perrin, Richard J.; Moulder, Krista; Hassenstab, Jason; Vöglein, Jonathan; Chhatwal, Jasmeer; Mori, Hiroshi; Alzheimer’s Disease Neuroimaging Initiative; Dominantly Inherited Alzheimer Network Consortia; Sung, Yun Ju; Cruchaga, Carlos; Neurology, School of Medicine
    Background: The SOMAscan assay has an advantage over immunoassay-based methods because it measures a large number of proteins in a cost-effective manner. However, the performance of this technology compared to the routinely used immunoassay techniques needs to be evaluated. Objective: We performed comparative analyses of SOMAscan and immunoassay-based protein measurements for five cerebrospinal fluid (CSF) proteins associated with Alzheimer's disease (AD) and neurodegeneration: NfL, Neurogranin, sTREM2, VILIP-1, and SNAP-25. Methods: We compared biomarkers measured in ADNI (N = 689), Knight-ADRC (N = 870), DIAN (N = 115), and Barcelona-1 (N = 92) cohorts. Raw protein values were transformed using z-score in order to combine measures from the different studies. sTREM2 and VILIP-1 had more than one analyte in SOMAscan; all available analytes were evaluated. Pearson's correlation coefficients between SOMAscan and immunoassays were calculated. Receiver operating characteristic curve and area under the curve were used to compare prediction accuracy of these biomarkers between the two platforms. Results: Neurogranin, VILIP-1, and NfL showed high correlation between SOMAscan and immunoassay measures (r > 0.9). sTREM2 had a fair correlation (r > 0.6), whereas SNAP-25 showed weak correlation (r = 0.06). Measures in both platforms provided similar predicted performance for all biomarkers except SNAP-25 and one of the sTREM2 analytes. sTREM2 showed higher AUC for SOMAscan based measures. Conclusion: Our data indicate that SOMAscan performs as well as immunoassay approaches for NfL, Neurogranin, VILIP-1, and sTREM2. Our study shows promise for using SOMAscan as an alternative to traditional immunoassay-based measures. Follow-up investigation will be required for SNAP-25 and additional established biomarkers.
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    Comparison of amyloid accumulation between Down syndrome and autosomal-dominant Alzheimer disease
    (Wiley, 2022) Boerwinkle, Anna H.; Gordon, Brian A.; Wisch, Julie K.; Flores, Shaney; Henson, Rachel L.; Butt, Omar Hameed; Chen, Charles D.; Benzinger, Tammie L. S.; Fagan, Anne M.; Handen, Benjamin L.; Christian, Bradley T.; Head, Elizabeth; Mapstone, Mark; Klunk, William E.; Rafii, Michael S.; O’Bryant, Sid E.; Price, Julie C.; Schupf, Nicole; Laymon, Charles M.; Krinsky-McHale, Sharon J.; Lai, Florence; Rosas, H. Diana; Hartley, Sigan L.; Zaman, Shahid; Lott, Ira T.; Silverman, Wayne; Brickman, Adam M.; Lee, Joseph H.; Allegri, Ricardo Francisco; Berman, Sarah; Chhatwal, Jasmeer P.; Chui, Helena C.; Cruchaga, Carlos; Farlow, Martin R.; Fox, Nick C.; Goate, Alison; Day, Gregory S.; Graff-Radford, Neill R.; Jucker, Mathias; Lee, Jae-Hong; Levin, Johannes; Martins, Ralph N.; Mori, Hiroshi; Perrin, Richard J.; Salloway, Stephen P.; Sanchez-Valle, Raquel; Schofield, Peter R.; Xiong, Chengjie; Karch, Celeste M.; Hassenstab, Jason J.; McDade, Eric; Bateman, Randall J.; Ances, Beau M.; Neurology, School of Medicine
    Background: Given the triplication of chromosome 21 and the location of the amyloid precursor protein gene on chromosome 21, almost all adults with Down syndrome (DS) develop Alzheimer disease (AD)-like pathology and dementia during their lifetime. Comparing amyloid accumulation in DS to autosomal dominant AD (ADAD), another genetic form of AD, may improve our understanding of early AD pathology development. Method: We assessed amyloid positron emission tomography (PET) imaging in 192 participants with DS and 33 sibling controls from the Alzheimer’s Biomarker Consortium-Down Syndrome (ABC-DS) and 265 mutation-carriers (MC) and 169 familial controls from the Dominantly Inherited Alzheimer Network (DIAN) (Table 1). We calculated regional standard uptake value ratios (SUVR) using a cerebellar cortex reference region and converted global amyloid burden SUVR to centiloids. We compared amyloid PET by cognitive status and estimated-years-to-symptom-onset (EYO). EYO was calculated for DIAN participants by subtracting their age from parental age of symptom onset and for ABC-DS participants by subtracting their age from 50.2 years, a published average age of symptom onset in a large sample of individuals with DS (Fortea et al., 2020). In a subset of participants, we assessed the relationship between amyloid PET and CSF Aβ42/40. Result: The relationship between CSF Aβ42/40 and amyloid PET was similar in DS and MC participants (Figure 1). We did not observe significant differences between MC and DS grouped by cognitive status (Figure 2). However, when assessed over EYO, global amyloid burden was significantly elevated in MC at EYO ≥ -23 but was not elevated in DS until EYO ≥ -15 (Figure 3). We observed early cortical and subcortical amyloid PET increases in both groups, but we also measured some regional differences in amyloid PET changes between MC and DS, specifically in the medial occipital region (Figure 4 and 5). Conclusion: These results demonstrate similarities in the relationship between amyloid biomarkers and the levels of amyloid accumulation in ADAD and DS. However, we also observed a 5-10 year delay and some regional differences in amyloid accumulation in DS. This is important for future clinical trials to consider when recruiting participants and determining treatment efficacy.
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    Utility of CSF biomarkers in assessing neurodegeneration in Early‐Onset Alzheimer’s disease
    (Wiley, 2025-01-09) Eldaief, Mark C.; Touroutoglou, Alexandra; Brickhouse, Michael; Katsumi, Yuta; Eloyan, Ani; Nudelman, Kelly N.; Foroud, Tatiana M.; Carrillo, Maria C.; Rabinovici, Gil D.; Apostolova, Liana G.; Schindler, Suzanne E.; Herries, Elizabeth M.; Henson, Rachel L.; Dage, Jeffrey L.; Dickerson, Bradford C.; Medical and Molecular Genetics, School of Medicine
    Background: There is a significant need for biomarkers of neurodegenerative burden in Early‐onset Alzheimer’s disease (EOAD). Evidence suggests that levels of specific CSF biomarkers (e.g., Neurofilament light (NfL), Synaptosomal‐Associated Protein (SNAP‐25), neurogranin, Visinin‐like protein 1 (VILIP‐1), Aß 42/40, phospho‐tau and total tau) index the extent of neurodegeneration in dementing illnesses. However, it remains unclear whether these biomarkers correlate to cortical atrophy patterns in EOAD. Based on prior work demonstrating correlations between NfL, SNAP‐25, neurogranin and Aß 42/40 CSF levels and cognitive impairment in EOAD (Dage et al. 2023), we hypothesized that these biomarkers (and not VILIP‐1, phospho‐tau or total tau) would variably predict cortical atrophy within our recently described EOAD signature (Touroutoglou et al. 2023). Method: We recruited 92 EOAD patients. In each patient, atrophy within the EOAD cortical signature were calculated as W‐scores (i.e., Z‐scores adjusted for age and sex relative to a sample of healthy controls). We first ran a simple regression analysis of each of the 7 CSF biomarkers and W‐scores in the EOAD signature across EOAD patients. We then entered the biomarkers with significant correlations to the EOAD signature into a stepwise regression analysis with backward elimination to ascertain the most parsimonious model predicting atrophy in the EOAD signature. As a control region not expected to be related to these biomarkers, we assessed correlations to calcarine fissure cortical atrophy. Result: As predicted, we observed a significant correlation between CSF levels of NfL, SNAP‐25, neurogranin and Aß 42/40 and atrophy within the EOAD signature. After entering these four biomarkers into the stepwise regression analysis, the most parsimonious model identified complementary contributions of NfL, SNAP‐25, and Aß 42/40, in predicting atrophy in the EOAD signature. There were no correlations between any biomarker and calcarine atrophy. Conclusion: Selected CSF biomarkers in EOAD patients predict the degree of atrophy within the EOAD cortical signature. Ongoing work includes correlating these biomarkers with topographical atrophy patterns on the whole‐brain voxel‐wise level. Our results suggest that certain CSF biomarkers could assess neurodegenerative burden within EOAD individuals. This would provide valuable information regarding disease progression for clinical care and clinical trials involving disease‐modifying therapies.