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Johnson, Keith A.

Mayo Clinic

Brigham and Women's Hospital

Citations 6

Plasma levels of an N‐terminal tau fragment predict core AD and neurodegenerative biomarkers in autosomal dominant Alzheimer’s disease: Findings from DIAN
Ostaszewski, Beth L., Fitzpatrick, Colleen , Fagan, Anne M. , Farlow, Martin R. , Schofield, Peter W., Perrin, Richard J. , Johnson, Keith A., Chhatwal, Jasmeer P. , Network, Dominantly Inherited Alzheimer, Schultz, Stephanie A. , Liu, Lei , Xiong, Chengjie , Noble, James M. , Rosa-Neto, Pedro , Schofield, Peter W., Morris, John C. , Jucker, Mathias , Jack, Clifford R. , Karch, Celeste M. , Gordon, Brian A. , Johnson, Keith A. , McDade, Eric , Sperling, Reisa Anne , Bateman, Randall J. , Selkoe, Dennis J. , Network, Dominantly Inherited Alzheimer

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

10.1002/alz.069285 Get It

AbstractBackgroundBlood based biomarkers that predict cognitive decline and Alzheimer’s disease (AD) pathology have the potential to accelerate AD therapeutic development and improve clinical care. Prior work suggests that plasma biomarkers of tau pathology (particularly post‐translational modifications of tau) may be highly useful in diagnosis and risk stratification for AD‐related neurodegeneration and cognitive decline. Levels of tau species lacking truncation of the N‐terminal region, particularly plasma and cerebrospinal fluid (CSF) levels of N‐terminal tau fragment 1 (NT1), have previously been shown to predict cognitive decline, neurodegeneration, and tau pathology in preclinical and symptomatic late‐onset AD. Here we examined plasma NT1 as a possible predictor of cognitive, clinical, pathologic, and neurodegenerative trajectories in autosomal dominant AD (ADAD) using data from the Dominantly Inherited Alzheimer Network Observational Study (DIAN‐Obs).MethodsAssociations between plasma NT1 levels and Mini‐Mental State Exam (MMSE), Clinical Dementia Rating SumBox® (CDR‐SB), hippocampal volume (HV), estimated years to symptom onset (EYO), Pittsburgh‐Compound‐B PET, and CSF Aβ42, and p‐tau181 were assessed using linear regression (150 pathogenic variant carriers, 81 non‐carriers; mean[SD] carrier age = 40.1 [10.4] years and EYO = ‐5.4 [10.4]). Plasma NT1 was measured using the Quanterix HD‐X platform. PET, MRI, clinical, and biofluid measures were derived using previously described procedures in DIAN‐Obs.ResultsCross‐sectional plasma NT1 levels in ADAD carriers were significantly associated with MMSE, CDR‐SB, HV, and p‐tau181 even after adjusting for EYO (Table 1; Figure 1). NT1 levels statistically diverged between carriers and non‐carriers 6.8 years before estimated symptom onset (Figure 2). In contrast, plasma NT1 levels were not significantly correlated with measures of β‐amyloid pathology after adjusting for EYO.ConclusionPlasma NT1 levels mirrored changes in clinical, cognitive, and neurodegenerative measures in ADAD, particularly in late asymptomatic and early symptomatic phases of disease. NT1 levels correlated with CSF measures of tau pathology, but NT1 levels were not strongly associated with CSF or PET measures of β‐amyloid pathology, unlike some previously‐studied plasma tau measures. Together with previous supportive findings in preclinical and symptomatic sporadic AD, these results suggest that plasma NT1 may be a useful biomarker of AD‐related tau pathology and neurodegeneration across a broad spectrum of disease.
Progressive white matter injury in autosomal dominant Alzheimer’s disease is strongly associated with cerebral microbleeds and neurodegeneration
Shirzadi, Zahra , Yau, Wai‐Ying Wendy , Preboske, Gregory M., Farlow, Martin R. , Fagan, Anne M. , Fitzpatrick, Colleen , Salloway, Stephen , Perrin, Richard J. , Graff‐Radford, Neill R. , Koeppe, Robert, Chui, Helena C., Mori, Hiroshi , Johnson, Keith A., Greenberg, Steven M. , Chhatwal, Jasmeer P. , Investigators, DIAN, Schultz, Stephanie A. , Joseph‐Mathurin, Nelly , Kantarci, Kejal , Jack, Clifford R. , Hassenstab, Jason , Jucker, Mathias , Morris, John C. , Xiong, Chengjie , Karch, Celeste M. , Levey, Allan I. , Gordon, Brian A. , Schofield, Peter William , McDade, Eric , Xiong, Chengjie , Cruchaga, Carlos , Allegri, Ricardo , Fox, Nick C. , Goate, Alison , Noble, James M. , Chui, Helena C. , Berman, Sarah , Sánchez‐Valle, Raquel , Lee, Jae‐Hong , Rosa-Neto, Pedro , Benzinger, Tammie L.S. , Sohrabi, Hamid R. , Martins, Ralph N. , Schultz, Aaron P. , Bateman, Randall J. , Johnson, Keith A. , Sperling, Reisa Anne , Investigators, DIAN

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

10.1002/alz.066715 Get It

AbstractBackgroundWhite matter (WM) injury visible on MRI is a common finding in Alzheimer’s disease (AD) and is often attributed to small vessel ischemic changes secondary to increased systemic vascular risk. Increased WM injury has been associated with the progression of Autosomal Dominant AD (ADAD), though ADAD pathogenic variant carriers are relatively young and may not have elevated vascular risk factors. We hypothesized that WM injury in ADAD may reflect worsening of cerebral amyloid angiopathy (CAA) and neurodegeneration. Here we examine this hypothesis using cross‐sectional and longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN).MethodMRI data from ADAD pathogenic variant carriers (n=223) and non‐carriers (n=136) were used in the present study (Table 1). We extracted FreeSurfer‐based WM lesion (WML) volume from T1‐weighted images (hypointensities). Cortical microbleed (CMB) burden was assessed visually on susceptibility weighted/T2*‐weighted gradient echo images by experienced radiologists (blineded to the mutation status) at the Mayo Clinic in Rochester. Linear regression models compared WML volume at baseline in people with and without CMB. Linear mixed effect models assessed the relationships between longitudinal WML and both CMBs and FreeSurfer‐based total gray matter (GM) volume. Models were corrected for age and estimated years to symptom onset (EYO).ResultGreater baseline WML volume was seen in ADAD carriers vs. non‐carriers, particularly close to the age of estimated symptom onset. Baseline WML volume was greater in carriers with CMBs compared to those without (t=2.9, p=0.003, Figure 1). Longitudinal increase in WML amongst ADAD pathogenic variant carriers with CMBs was estimated to be 214 mm3/year greater than that amongst carriers without CMBs (t=4.1, p<0.001, Figure 2). Independent of this CMB effect, decreasing GM volume was strongly associated with increasing longitudinal WML volume (t=‐6.2, p<0.001, Figure 3). Similar analyses in the non‐carrier group yielded no significant findings.ConclusionConsistent with prior reports, WML volume was increased in ADAD pathogenic variant carriers. However, the results here suggest WML in ADAD may not solely be due to small vessel ischemic changes, but rather may be a result of worsening CAA and more rapid neurodegeneration.
AD‐causing variants that affect PSEN1 transmembrane domains are associated with faster neurodegeneration and cognitive decline compared to those affecting cytoplasmic domains
Fagan, Anne M. , Chen, Charles D., Fitzpatrick, Colleen , Chui, Helena C., Mori, Hiroshi , Johnson, Keith A., Farlow, Martin R. , Farrell, Michelle E. , Graff‐Radford, Neill R. , Perrin, Richard J. , Salloway, Stephen , Shirzadi, Zahra , Chhatwal, Jasmeer P. , Schultz, Stephanie A. , Allegri, Ricardo , Schultz, Aaron P. , Goate, Alison , Levey, Allan I. , Hanseeuw, Bernard , Koeppe, Robert A. , Gordon, Brian A. , Cruchaga, Carlos , Karch, Celeste M. , Xiong, Chengjie , Jack, Clifford R. , McDade, Eric , Chui, Helena C. , Lee, Jae‐Hong , Noble, James M. , Hassenstab, Jason , Xiong, Chengjie , Morris, John C. , Johnson, Keith A. , Liu, Lei , Jucker, Mathias , Joseph‐Mathurin, Nelly , Fox, Nick C. , Schofield, Peter R. , Martins, Ralph N. , Sánchez‐Valle, Raquel , Berman, Sarah , Rosa-Neto, Pedro , Benzinger, Tammie L.S. , Bateman, Randall J. , Sperling, Reisa Anne

Alzheimer's & Dementia | December 20, 2022 | Volume: 18 | Issue: S4 | Pages: No page available

10.1002/alz.067186 Get It

AbstractBackgroundRates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross‐sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN‐Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini‐Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®‐SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4‐year trial with annual assessments; 80% power; α = 0.05).ResultsPSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = ‐0.42[0.1], p=0.002), CDR®‐SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = ‐58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.
AD‐causing variants that affect PSEN1 transmembrane domains are associated with faster neurodegeneration and cognitive decline compared to those affecting cytoplasmic domains.
Schultz, Stephanie A. , Fagan, Anne M. , Hanseeuw, Bernard , Gordon, Brian A. , Chen, Charles D., Xiong, Chengjie , Fitzpatrick, Colleen , Chui, Helena C., Mori, Hiroshi , Morris, John C. , Johnson, Keith A., Liu, Lei , Farlow, Martin R. , Farrell, Michelle E. , Graff‐Radford, Neill R. , Perrin, Richard J. , Berman, Sarah , Salloway, Stephen , Shirzadi, Zahra , Bateman, Randall J. , Chhatwal, Jasmeer P. , Gordon, Brian A , Bateman, Randall J , Xiong, Chengjie , Morris, John C , Berman, Sarah , Allegri, Ricardo , Schultz, Aaron P. , Goate, Alison , Levey, Allan I. , Koeppe, Robert A. , Cruchaga, Carlos , Karch, Celeste M. , Xiong, Chengjie , Jack, Clifford R. , McDade, Eric , Chui, Helena C. , Lee, Jae‐Hong , Noble, James M. , Hassenstab, Jason , Johnson, Keith A. , Jucker, Mathias , Joseph‐Mathurin, Nelly , Fox, Nick C. , Schofield, Peter R. , Martins, Ralph N. , Sánchez‐Valle, Raquel , Rosa-Neto, Pedro , Benzinger, Tammie L.S. , Sperling, Reisa Anne

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

10.1002/alz.068221 Get It

AbstractBackgroundRates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross‐sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN‐Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini‐Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®‐SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4‐year trial with annual assessments; 80% power; α = 0.05).Results PSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = ‐0.42[0.1], p=0.002), CDR®‐SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = ‐58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.
The location of PSEN1 pathogenic variants in transmembrane vs. cytoplasmic domains may alter neurodegenerative and cognitive trajectories: Findings from the DIAN study
Fitzpatrick, Colleen , Chui, Helena C., Fagan, Anne M. , Farlow, Martin R. , Graff‐Radford, Neill R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Johnson, Keith A., Chhatwal, Jasmeer P. , DIAN, Schultz, Stephanie A. , Schultz, Aaron P. , Joseph‐Mathurin, Nelly , McDade, Eric , Klunk, William E. , Fox, Nick C. , Xiong, Chengjie , Hassenstab, Jason , Goate, Alison , Hanseeuw, Bernard , Lee, Jae‐Hong , Jucker, Mathias , Allegri, Ricardo , Benzinger, Tammie L.S. , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Gordon, Brian A. , Martins, Ralph N. , Noble, James M. , Sánchez‐Valle, Raquel , Schofield, Peter R. , Levey, Allan I. , Karch, Celeste M. , Johnson, Keith A. , Bateman, Randall J. , Sperling, Reisa Anne , DIAN

Alzheimer's & Dementia | February 1, 2022 | Volume: 17 | Issue: S4 | Pages: No page available

10.1002/alz.050864 Get It

AbstractBackgroundThough pathogenic variations in PSEN1 leading to Autosomal Dominant Alzheimer's disease (ADAD) are all highly penetrant, there is substantial inter‐individual variability in the rates of cognitive decline and biomarker change observed in ADAD. We hypothesized that this inter‐individual variability may be associated with the location of the pathogenic variant within PSEN1. We tested this hypothesis using biomarker and cognitive data from the Dominantly Inherited Alzheimer Network (DIAN) observational study.MethodPSEN1 pathogenic variant carriers [grouped based on whether their ADAD genotype affected transmembrane (PSEN1 TM; N = 125) or cytoplasmic (PSEN1 CY; N = 62) domains] and non‐carriers [NC; N = 176] enrolled in DIAN underwent clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF). Linear mixed effects models with a restricted cubic spline were used to determine cross‐sectional differences in clinical and biomarker measures between NC, PSEN1 TM, and PSEN1 CY groups, across the disease course (estimated years to symptom onset; EYO).ResultBackground characteristics are reported in Table 1. PSEN1 CY and PSEN1 TM groups had elevated β‐amyloid (PiB‐PET) and phosphorylated‐tau levels (CSF pTauT181) compared to NC, but these biomarker measures were not different between PSEN1 TM and CY groups (Figure 1a‐b). Additionally, the PSEN1 TM group had decreased glucose metabolism compared to NC but was similar to the PSEN1 CY group (Figure 1c). However, we observed that PSEN1 TM carriers had significantly smaller hippocampal volume, greater lateral ventricle volume, and greater cognitive impairment (Figure 1d‐f) across EYO as compared to PSEN1 CY carriers.ConclusionDespite similar β‐amyloid PET and CSF pTauT181 levels across EYO, individuals with pathogenic variants affecting transmembrane domains in PSEN1 may have more rapid progression of disease as measured by cognitive function and neurodegeneration as compared to those with variants affecting cytoplasmic domains. These results have implications both for understanding the heterogeneity in ongoing ADAD clinical trials and for better understanding the pathobiology of ADAD.
Vascular burden and Alzheimer disease pathologic progression
Lo, Raymond Y. , Jagust, William J. , Weiner, Michael W. , Aisen, Paul , Petersen, Ronald , Trojanowki, John Q., Liu, Enchi , Montine, Tom, Petersen, Ronald, Gamst, Anthony, Thomas, Ronald G. , Walter, Sarah , Gessert, Devon, Sather, Tamie, Kornak, John , Felmlee, Joel P. , Schuff, Norbert, Alexander, Gene, DeCarli, Charles , Bandy, Dan, Foster, Norm, Reiman, Eric M. , Mathis, Chet, Cairns, Nigel J., Taylor‐Reinwald, Lisa, Shaw, Les, Korecka, Magdalena , Crawford, Karen , Neu, Scott, Foroud, Tatiana M., Potkin, Steven, Kachaturian, Zaven, Frank, Richard , Molchan, Susan, Quinn, Joseph, Lind, Betty, Dolen, Sara, Schneider, Lon S. , Pawluczyk, Sonia, Spann, Bryan M., Brewer, James, Vanderswag, Helen, Heidebrink, Judith L. , Johnson, Kris , Doody, Rachelle S., Villanueva‐Meyer, Javier , Chowdhury, Munir , Bell, Karen L. , Carroll, Maria , Leon, Sue, Mintun, Mark A., Schneider, Stacy, Marson, Daniel , Griffith, Randall, Clark, David, Grossman, Hillel, Mitsis, Effie, Romirowsky, Aliza, deToledo‐Morrell, Leyla, Duara, Ranjan , Varón, Daniel , Roberts, Peggy, Albert, Marilyn, Onyike, Chiadi, Kielb, Stephanie , Glodzik, Lidia , Santi, Susan De , Doraiswamy, P. Murali , Petrella, Jeffrey R. , Coleman, R. Edward, Arnold, Steven E. , Karlawish, Jason H., Smith, Charles D., Jicha, Gregory A. , Hardy, Peter , Oakley, MaryAnn, Simpson, Donna M., Goldstein, Bonnie S., Martin, Kim, Makino, Kelly M., Ismail, M. Saleem , Brand, Connie, Mulnard, Ruth A., Thai, Gaby , Mc-Adams-Ortiz, Catherine, Mathews, Dana, Quiceno, Mary , King, Richard, Weiner, Myron, Martin-Cook, Kristen, Devous, Michael D. , Cellar, Janet S., Anderson, Heather S., Swerdlow, Russell H. , Apostolova, Liana , Lu, Po H. , Bartzokis, George, Graff‐Radford, Neill R. , Parfitt, Francine, Farlow, Martin R. , Hake, Ann Marie , Matthews, Brandy R., Herring, Scott, Dyck, Christopher H. van , Carson, Richard E. , MacAvoy, Martha G., Chertkow, Howard , Bergman, Howard , Hosein, Chris, Black, Sandra, Stefanovic, Dr Bojana, Caldwell, Curtis, Hsiung, Ging‐Yuek Robin , Mudge, Benita, Assaly, Michele, Kertesz, Andrew, Rogers, John, Trost, Dick, Bernick, Charles , Munic, Donna, Mesulam, Marek-Marsel, Lipowski, Kristina, Wu, Chuang‐Kuo, Johnson, Nancy , Sadowsky, Carl, Villena, Teresa, Johnson, Kathleen, Reynolds, Brigid, Johnson, Keith A., Marshall, Gad A. , Frey, Meghan , Yesavage, Jerome A. , Taylor, Joy L. , Lane, Barton , Rosen, Allyson , Tinklenberg, Jared, Sabbagh, Marwan N. , Belden, Christine M. , Jacobson, Sandra A. , Kowall, Neil W. , Budson, Andrew E. , Johnson, Patricia Lynn, Wolday, Saba, Bwayo, Salome K., Lerner, Alan J. , Hudson, Leon, Ogrocki, Paula, Fletcher, Evan, Olichney, John , Kittur, Smita, Borrie, Michael, Lee, T‐Y, Bartha, Dr Rob, Asthana, Sanjay , Carlsson, Cynthia M., Preda, Adrian , Tariot, Pierre N. , Fleisher, Adam , Reeder, Stephanie, Bates, Vernice, Capote, Horacio, Rainka, Michelle, Kataki, Maria , Zimmerman, Earl A. , Celmins, Dzintra, Brown, Alice D., Blank, Karen, Anderson, Karen, Santulli, Robert B. , Schwartz, Eben S., Williamson, Jeff D. , Garg, Pradeep , Watkins, Franklin, Ott, Brian R. , Querfurth, Henry, Tremont, Geoffrey , Salloway, Stephen , Malloy, Paul, Correia, Stephen , Rosen, Howard J. , Mintzer, Jacobo , Longmire, Crystal Flynn, Spicer, Kenneth, Rachinsky, Irina, Rogers, John , Drost, Dick, Lee, Ting‐Yim , Jack, Clifford R. , Toga, Arthur W. , Beckett, Laurel , Green, Robert C. , Saykin, Andrew J. , Morris, John C. , Donohue, Michael , Harvey, Danielle , Dale, Anders M. , Bernstein, Matt A. , Fox, Nick C. , Thompson, Paul M. , Koeppe, Robert A. , Chen, Kewei , Mathis, Chet, Lee, Virginia M.‐Y. , Shen, Li , Snyder, Peter J. , Kaye, Jeffrey , Lord, Joanne L. , Stern, Yaakov , Honig, Lawrence S. , Ances, Beau M. , Shah, Raj C. , Duara, Ranjan , Rusinek, Henry , Leon, Mony J. de , Karlawish, Jason , Wolk, David A. , López, Oscar L. , Porsteinsson, Anton P. , Womack, Kyle , Diaz‐Arrastia, Ramon , Levey, Allan I. , Lah, James J. , Burns, Jeffrey M. , Silverman, Daniel H.S. , Johnson, Heather K. , Stefanovic, Bojana , Feldman, Howard , Kerwin, Diana , Martínez, Walter Fabián , Turner, Raymond Scott , Sperling, Reisa Anne , Killiany, Ronald , Norbash, Alexander , Obisesan, Thomas O. , Carmichael, Owen , Johnson, Sterling C. , Nguyen, Dana R. , Reeder, Stephanie, Scharre, Douglas W. , Pearlson, Godfrey D. , Sink, Kaycee M. , Miller, Bruce L. , Finger, Elizabeth C. , Preda, Adrian , Hsiung, Gink-Yuek , Jicha, Gregory A

Neurology | September 13, 2012 | Volume: 79 | Issue: 13 | Pages: 1349-1355

10.1212/wnl.0b013e31826c1b9d Get It