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Henson, Rachel L.

https://orcid.org/0000-0002-0664-0629

Mayo Clinic

Knight Alzheimer Disease Research Center, Saint Louis, MO USA

Citations 12

CSF biomarkers of immune activation and Alzheimer’s disease for predicting cognitive impairment risk in the elderly
White, Launia J. , Hendrix, Rachel , Ulrich, Jason D. , Henson, Rachel L. , Knight, William C. , Martens, Yuka A. , Wang, Ni , Starling, Skylar C , Ren, Yingxue , Asmann, Yan W. , Syrjanen, Jeremy A. , Vassilaki, Maria , Petersen, Ronald C. , Kanekiyo, Takahisa , Shue, Francis , Roy, Bhaskar, Xiong, Chengjie , Mielke, Michelle M. , Cruchaga, Carlos , Holtzman, David M. , Bu, Guojun , Heckman, Michael G.

Alzheimer's & Dementia | January 9, 2025 | Volume: 20 | Issue: S2 | Pages: No page available

10.1002/alz.087693 Get It

AbstractBackgroundThe immune system is substantially involved in the development and progression of age‐related cognitive decline and Alzheimer’s disease (AD).MethodAs genetic and environmental factors interactively impact these conditions, we investigated how risk factors such as APOE genotype, age, and sex influence immune activation markers and AD biomarkers in cerebrospinal fluid (CSF) in elderly individuals enrolled in the Mayo Clinic Study of Aging cohort. Among cognitively unimpaired individuals aged over 65 at the baseline visit (N=298), we measured 365 CSF immune activation markers using the proximity extension assay.ResultWe found that age, sex, and diabetes status are associated with altered CSF levels of immune activation markers independently of other factors. For CSF AD biomarkers, we observed significant positive correlations between age and total tau, phosphorylated tau‐181 (p‐tau181), neurofilament light (NfL), and YKL40. APOE4 was also associated with lower Aβ42 and higher SNAP25 in CSF. We further examined whether baseline visit variables can predict cognitive decline, represented by the conversion from CDR=0 to CDR>0. We found that age, Aβ42, NfL, and REG4 were independently correlated with CDR conversion risk. When the cohort was dichotomized by their median values, older participants with lower Aβ42, higher NfL, and higher REG4 at baseline developed cognitive impairment during the follow up with a c‐index of 0.762 while age alone had a c‐index of 0.699.ConclusionTogether, our results suggest that assessing CSF immune activation markers and AD biomarkers can improve the prediction of cognitive impairment risk in the elderly.
CSF biomarkers of immune activation and Alzheimer's disease for predicting cognitive impairment risk in the elderly
White, Launia J. , Hendrix, Rachel , Ulrich, Jason D. , Henson, Rachel L. , Knight, William C. , Martens, Yuka A. , Wang, Ni , Starling, Skylar C , Ren, Yingxue , Asmann, Yan W. , Syrjanen, Jeremy A. , Vassilaki, Maria , Petersen, Ronald C. , Kanekiyo, Takahisa , Shue, Francis , Roy, Bhaskar, Xiong, Chengjie , Mielke, Michelle M. , Cruchaga, Carlos , Holtzman, David M. , Bu, Guojun , Heckman, Michael G.

Alzheimer's & Dementia | January 9, 2025 | Volume: 20 | Issue: S9 | Pages: No page available

10.1002/alz.093743 Get It

AbstractBackgroundThe immune system is substantially involved in the development and progression of age‐related cognitive decline and Alzheimer’s disease (AD).MethodAs genetic and environmental factors interactively impact these conditions, we investigated how risk factors such as APOE genotype, age, and sex influence immune activation markers and AD biomarkers in cerebrospinal fluid (CSF) in elderly individuals enrolled in the Mayo Clinic Study of Aging cohort. Among cognitively unimpaired individuals aged over 65 at the baseline visit (N=298), we measured 365 CSF immune activation markers using the proximity extension assay.ResultWe found that age, sex, and diabetes status are associated with altered CSF levels of immune activation markers independently of other factors. For CSF AD biomarkers, we observed significant positive correlations between age and total tau, phosphorylated tau‐181 (p‐tau181), neurofilament light (NfL), and YKL40. APOE4 was also associated with lower Aß42 and higher SNAP25 in CSF. We further examined whether baseline visit variables can predict cognitive decline, represented by the conversion from CDR=0 to CDR>0. We found that age, Aß42, NfL, and REG4 were independently correlated with CDR conversion risk. When the cohort was dichotomized by their median values, older participants with lower Aß42, higher NfL, and higher REG4 at baseline developed cognitive impairment during the follow up with a c‐index of 0.762 while age alone had a c‐index of 0.699.ConclusionTogether, our results suggest that assessing CSF immune activation markers and AD biomarkers can improve the prediction of cognitive impairment risk in the elderly.
Diagnostic Applications of Cerebrospinal Fluid Biomarkers in Patients with Rapidly Progressive Dementia (P6-9.003)
Day, Gregory, Martens, Yuka A. , Satyadev, Nihal , Lazar, Evelyn, Dacquel, Maxwell V., Henson, Rachel L. , Geschwind, Michael D., Herries, Elizabeth, Graff‐Radford, Neill R. , Day, Gregory S. , Kuchenbecker, Lindsey A. , Tipton, Philip W. , Brier, Matthew R. , Dunham, Steven , Bu, Guojun , Morris, John C. , Schindler, Suzanne E.

Neurology | April 9, 2024 | Volume: 102 | Issue: 7_supplement_1 | Pages: No page available

10.1212/wnl.0000000000205469 Get It

CSF biomarkers of immune activation and Alzheimer’s disease for predicting cognitive impairment risk in the elderly
Shue, Francis , White, Launia J. , Hendrix, Rachel , Ulrich, Jason D. , Henson, Rachel L. , Knight, William D., Martens, Yuka A. , Wang, Ni , Starling, Skylar C , Ren, Yingxue , Asmann, Yan W. , Syrjanen, Jeremy A. , Vassilaki, Maria , Sung, Yun Ju , Petersen, Ronald C. , Kanekiyo, Takahisa , Ulrich, Jason , Asmann, Yan W , Syrjanen, Jeremy A , Vassilaki, Maria , Mielke, Michelle M , Timsina, Jigyasha , Sung, Yun Ju , Cruchaga, Carlos , Holtzman, David M , Bu, Guojun , Petersen, Ronald C , Kanekiyo, Takahisa , Shue, Francis , Roy, Bhaskar, Xiong, Chengjie , Mielke, Michelle M. , Holtzman, David M. , Bu, Guojun , Heckman, Michael G.

Science Advances | April 3, 2024 | Volume: 10 | Issue: 14 | Pages: No page available

10.1126/sciadv.adk3674 Get It

The immune system substantially influences age-related cognitive decline and Alzheimer’s disease (AD) progression, affected by genetic and environmental factors. In a Mayo Clinic Study of Aging cohort, we examined how risk factors like APOE genotype, age, and sex affect inflammatory molecules and AD biomarkers in cerebrospinal fluid (CSF). Among cognitively unimpaired individuals over 65 ( N = 298), we measured 365 CSF inflammatory molecules, finding age, sex, and diabetes status predominantly influencing their levels. We observed age-related correlations with AD biomarkers such as total tau, phosphorylated tau-181, neurofilament light chain (NfL), and YKL40. APOE4 was associated with lower Aβ42 and higher SNAP25 in CSF. We explored baseline variables predicting cognitive decline risk, finding age, CSF Aβ42, NfL, and REG4 to be independently correlated. Subjects with older age, lower Aβ42, higher NfL, and higher REG4 at baseline had increased cognitive impairment risk during follow-up. This suggests that assessing CSF inflammatory molecules and AD biomarkers could predict cognitive impairment risk in the elderly.
Cross‐sectional comparison of the role of tau burden among Down Syndrome Alzheimer disease and autosomal‐dominant Alzheimer disease
Boerwinkle, Anna H. , Henson, Rachel L. , Thippabhotla, Sharmila, Kennedy, James Tyler, Butt, Omar H. , Chen, Charles D., Christian, Bradley T. , Mapstone, Mark , Tudorascu, Dana , Cohen, Annie , Fagan, Anne M. , Price, Julie C. , Schupf, Nicole , Laymon, Charles M. , Krinsky‐McHale, Sharon J. , Lai, Florence , Rosas, H. Diana , Lott, Ira T. , Silverman, Wayne , Chhatwal, Jasmeer P. , Chui, Helena C., Farlow, Martin R. , Graff‐Radford, Neill R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Wisch, Julie K. , Gordon, Brian A. , Flores, Shaney , McKay, Nicole S. , Handen, Benjamin L. , Head, Elizabeth , Zammit, Matthew D. , Johnson, Sterling C. , Klunk, William E. , Rafii, Michael S. , O’Bryant, Sid E. , Yassa, Michael A. , Keator, David B. , Hartley, Sigan L. , Zaman, Shahid H. , Lao, Patrick , Brickman, Adam M. , Lee, Joseph H. , Allegri, Ricardo , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Fox, Nick C. , Goate, Alison , Day, Gregory S. , Jucker, Mathias , Lee, Jae‐Hong , Xiong, Chengjie , Martins, Ralph N. , Sánchez‐Valle, Raquel , Schofield, Peter William , Xiong, Chengjie , Schindler, Suzanne E. , Morris, John C. , Karch, Celeste M. , Hassenstab, Jason , Benzinger, Tammie L.S. , McDade, Eric , Bateman, Randall J. , Ances, Beau M.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S14 | Pages: No page available

10.1002/alz.079102 Get It

AbstractBackgroundAdults with Down Syndrome (DS) develop Alzheimer disease (AD)‐like pathology and dementia as they age. This is attributed to triplication of the amyloid precursor protein gene. Recent work demonstrated that amyloid is elevated in DS and accumulates in a similar topography to autosomal dominant AD (ADAD). Tau accumulation is the second hallmark of AD and may be measured using tau positron emission tomography (PET) imaging. The pattern of tau accumulation remains unknown in DS.MethodIn a cross‐sectional analysis we evaluated amyloid and tau positron emission tomography (PET) in 124 participants with DS (109 cognitively stable, 8 symptomatic, 7 no consensus), 29 ADAD mutation carriers (26 asymptomatic, 3 symptomatic), and 201 cognitively normal non‐mutation carriers (CN). Regional cortical standard uptake value ratios (SUVR) for tau imaging were obtained and compared by cognitive status. Similarly, regional cortical amyloid SUVR were obtained and converted to centiloids. We then compared the magnitude of tau burden as well as spatial spread of tau across groups relative to amyloid burden.ResultCompared to CN, tau PET binding was elevated in participants with (µDS = 2.12 ± 0.22 SUVR, µADAD = 2.52 ± 0.37 SUVR) and without (µDS = 1.24 ± 0.15 SUVR, µADAD = 1.16 ± 0.19 SUVR) cognitive changes. For both groups, tau increased with increasing amyloid (centiloids). In some regions, DS had greater tau burden for a given amyloid level (centiloids) (Figure 1). There was increased spatial distribution of tau throughout the brain for participants with DS compared to CN. In contrast, tau burden was more focal in participants with ADAD with tau primarily elevated in posterior regions (Figure 2).ConclusionWhile tau burden was higher with symptomatic disease for both groups, significant differences existed in the overall amount and spatial spread. Tau spread was greatest in participants with DS and more diffuse compared to ADAD. These results indicate a substantial tau burden is present in DS, and suggest not only anti‐amyloid but also tau‐reducing agents should be considered for treating cognitive decline in adults with DS.
Predictors of treatment-responsiveness in cerebral amyloid angiopathy with related inflammation (3000)
Plotzker, Alan, Henson, Rachel L. , Fagan, Anne M. , Morris, John, Day, Gregory S.

Neurology | December 7, 2023 | Volume: 96 | Issue: 15_supplement | Pages: No page available

10.1212/wnl.96.15_supplement.3000 Get It

Diagnostic Utility of Cerebrospinal Fluid Biomarkers in Patients with Rapidly Progressive Dementia
Kuchenbecker, Lindsey A. , Tipton, Philip W. , Martens, Yuka A. , Brier, Matthew R. , Satyadev, Nihal , Dunham, Steven , Lazar, Evelyn, Dacquel, Maxwell V., Henson, Rachel L. , Geschwind, Michael D., Morris, John C. , Herries, Elizabeth, Graff‐Radford, Neill R. , Day, Gregory S. , Martens, Yuka, Dunham, S Richard , Lazar, Evelyn B, Day, Gregory S , Tipton, Philip W , Morris, John C , Satyadev, N , Bu, Guojun , Schindler, Suzanne E.

Annals of Neurology | October 28, 2023 | Volume: 95 | Issue: 2 | Pages: 299-313

10.1002/ana.26822 Get It

ObjectiveThis study was undertaken to apply established and emerging cerebrospinal fluid (CSF) biomarkers to improve diagnostic accuracy in patients with rapidly progressive dementia (RPD). Overlap in clinical presentation and results of diagnostic tests confounds etiologic diagnosis in patients with RPD. Objective measures are needed to improve diagnostic accuracy and to recognize patients with potentially treatment‐responsive causes of RPD.MethodsBiomarkers of Alzheimer disease neuropathology (amyloid‐β 42/40 ratio, phosphorylated tau [p‐tau181, p‐tau231]), neuroaxonal/neuronal injury (neurofilament light chain [NfL], visinin‐like protein‐1 [VILIP‐1], total tau), neuroinflammation (chitinase‐3‐like protein [YKL‐40], soluble triggering receptor expressed on myeloid cells 2 [sTREM2], glial fibrillary acidic protein [GFAP], monocyte chemoattractant protein‐1 [MCP‐1]), and synaptic dysfunction (synaptosomal‐associated protein 25kDa, neurogranin) were measured in CSF obtained at presentation from 78 prospectively accrued patients with RPD due to neurodegenerative, vascular, and autoimmune/inflammatory diseases; 35 age‐ and sex‐matched patients with typically progressive neurodegenerative disease; and 72 cognitively normal controls. Biomarker levels were compared across etiologic diagnoses, by potential treatment responsiveness, and between patients with typical and rapidly progressive presentations of neurodegenerative disease.ResultsAlzheimer disease biomarkers were associated with neurodegenerative causes of RPD. High NfL, sTREM2, and YKL‐40 and low VILIP‐1 identified patients with autoimmune/inflammatory diseases. MCP‐1 levels were highest in patients with vascular causes of RPD. A multivariate model including GFAP, MCP‐1, p‐tau181, and sTREM2 identified the 44 patients with treatment‐responsive causes of RPD with 89% accuracy. Minimal differences were observed between typical and rapidly progressive presentations of neurodegenerative disease.InterpretationSelected CSF biomarkers at presentation were associated with etiologic diagnoses and treatment responsiveness in patients with heterogeneous causes of RPD. The ability of cross‐sectional biomarkers to inform upon mechanisms that drive rapidly progressive neurodegenerative disease is less clear. ANN NEUROL 2024;95:299–313
Comparison of amyloid accumulation between Down syndrome and autosomal‐dominant Alzheimer disease
Boerwinkle, Anna H. , Henson, Rachel L. , Butt, Omar H. , Chen, Charles D., Fagan, Anne M. , Christian, Bradley T. , Mapstone, Mark , Price, Julie C. , Schupf, Nicole , Laymon, Charles M. , Krinsky‐McHale, Sharon J. , Lai, Florence , Rosas, H. Diana , Lott, Ira T. , Silverman, Wayne , Chhatwal, Jasmeer P. , Chui, Helena C., Farlow, Martin R. , Graff‐Radford, Neill R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Gordon, Brian A. , Wisch, Julie K. , Flores, Shaney , Benzinger, Tammie L.S. , Handen, Benjamin L. , Head, Elizabeth , Klunk, William E. , Rafii, Michael S. , O’Bryant, Sid E. , Hartley, Sigan L. , Zaman, Shahid H. , Brickman, Adam M. , Lee, Joseph H. , Allegri, Ricardo , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Fox, Nick C. , Goate, Alison , Day, Gregory S. , Jucker, Mathias , Lee, Jae‐Hong , Xiong, Chengjie , Martins, Ralph N. , Sánchez‐Valle, Raquel , Schofield, Peter R. , Karch, Celeste M. , Hassenstab, Jason , McDade, Eric , Bateman, Randall J. , Ances, Beau M.

Alzheimer's & Dementia | December 20, 2022 | Volume: 18 | Issue: S6 | Pages: No page available

10.1002/alz.064684 Get It

AbstractBackgroundGiven 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.MethodWe 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.ResultThe 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).ConclusionThese 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.
Comparison of amyloid accumulation between Down syndrome and autosomal‐dominant Alzheimer disease
Boerwinkle, Anna H. , Henson, Rachel L. , Butt, Omar H. , Chen, Charles D., Fagan, Anne M. , Christian, Bradley T. , Mapstone, Mark , Price, Julie C. , Schupf, Nicole , Laymon, Charles M. , Krinsky‐McHale, Sharon J. , Lai, Florence , Rosas, H. Diana , Lott, Ira T. , Silverman, Wayne , Chhatwal, Jasmeer P. , Chui, Helena C., Farlow, Martin R. , Graff‐Radford, Neill R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Gordon, Brian A. , Wisch, Julie K. , Flores, Shaney , Benzinger, Tammie L.S. , Handen, Benjamin L. , Head, Elizabeth , Klunk, William E. , Rafii, Michael S. , O’Bryant, Sid E. , Hartley, Sigan L. , Zaman, Shahid H. , Brickman, Adam M. , Lee, Joseph H. , Allegri, Ricardo , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Fox, Nick C. , Goate, Alison , Day, Gregory S. , Jucker, Mathias , Lee, Jae‐Hong , Xiong, Chengjie , Martins, Ralph N. , Sánchez‐Valle, Raquel , Schofield, Peter R. , Xiong, Chengjie , Karch, Celeste M. , Hassenstab, Jason , McDade, Eric , Bateman, Randall J. , Ances, Beau M.

Alzheimer's & Dementia | December 20, 2022 | Volume: 18 | Issue: S1 | Pages: No page available

10.1002/alz.063959 Get It

AbstractBackgroundGiven 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.MethodWe 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.ResultThe 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).ConclusionThese 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.