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Schäfer S, Tröger J, Kray J. Modern scores for traditional tests - Review of the diagnostic potential of scores derived from word list learning tests in mild cognitive impairment and early Alzheimer's Disease. Neuropsychologia 2024; 201:108908. [PMID: 38744410 DOI: 10.1016/j.neuropsychologia.2024.108908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 05/11/2024] [Accepted: 05/11/2024] [Indexed: 05/16/2024]
Abstract
Episodic memory impairment is one of the early hallmarks in Alzheimer's Disease. In the clinical diagnosis and research, episodic memory impairment is typically assessed using word lists that are repeatedly presented to and recalled by the participant across several trials. Until recently, total learning scores, which consist of the total number of words that are recalled by participants, were almost exclusively used for diagnostic purposes. The present review aims at summarizing evidence on additional scores derived from the learning trials which have recently been investigated more frequently regarding their diagnostic potential. These scores reflect item acquisition, error frequencies, strategy use, intertrial fluctuations, and recall consistency. Evidence was summarized regarding the effects of clinical status on these scores. Preclinical, mild cognitive impairment and mild Alzheimer's Disease stages were associated with a pattern of reduced item acquisition, more errors, less strategy use, and reduced access of items, indicating slowed and erroneous encoding. Practical implications and limitations of the present research will be discussed.
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Affiliation(s)
| | | | - Jutta Kray
- Saarland University, Saarbrücken, Germany
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Billaud CHA, Yu J. The hippocampus as a structural and functional network epicentre for distant cortical thinning in neurocognitive aging. Neurobiol Aging 2024; 139:82-89. [PMID: 38657394 DOI: 10.1016/j.neurobiolaging.2024.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 04/05/2024] [Accepted: 04/09/2024] [Indexed: 04/26/2024]
Abstract
Alterations in grey matter (GM) and white matter (WM) are associated with memory impairment across the neurocognitive aging spectrum and theorised to spread throughout brain networks. Functional and structural connectivity (FC,SC) may explain widespread atrophy. We tested the effect of SC and FC to the hippocampus on cortical thickness (CT) of connected areas. In 419 (223 F) participants (agemean=73 ± 8) from the Alzheimer's Disease Neuroimaging Initiative, cortical regions associated with memory (Rey Auditory Verbal Learning Test) were identified using Lasso regression. Two structural equation models (SEM), for SC and resting-state FC, were fitted including CT areas, and SC and FC to the left and right hippocampus (LHIP,RHIP). LHIP (β=-0.150,p=<.001) and RHIP (β=-0.139,p=<.001) SC predicted left temporopolar/rhinal CT; RHIP SC predicted right temporopolar/rhinal CT (β=-0.191,p=<.001). LHIP SC predicted right fusiform/parahippocampal (β=-0.104,p=.011) and intraparietal sulcus/superior parietal CT (β=0.101,p=.028). Increased RHIP FC predicted higher left inferior parietal CT (β=0.132,p=.042) while increased LHIP FC predicted lower right fusiform/parahippocampal CT (β=-0.97; p=.023). The hippocampi may be epicentres for cortical thinning through disrupted connectivity.
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Affiliation(s)
- Charly Hugo Alexandre Billaud
- Nanyang Technological University, Psychology, School of Social Sciences, 48 Nanyang Avenue, Singapore City 639798, Singapore.
| | - Junhong Yu
- Nanyang Technological University, Psychology, School of Social Sciences, 48 Nanyang Avenue, Singapore City 639798, Singapore
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Ikanga J, Patrick SD, Schwinne M, Patel SS, Epenge E, Gikelekele G, Tshengele N, Kavugho I, Mampunza S, Yarasheski KE, Teunissen CE, Stringer A, Levey A, Rojas JC, Chan B, Lario Lago A, Kramer JH, Boxer AL, Jeromin A, Alonso A, Spencer RJ. Sensitivity of the African neuropsychology battery memory subtests and learning slopes in discriminating APOE 4 and amyloid pathology in adult individuals in the Democratic Republic of Congo. Front Neurol 2024; 15:1320727. [PMID: 38601333 PMCID: PMC11004441 DOI: 10.3389/fneur.2024.1320727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 03/14/2024] [Indexed: 04/12/2024] Open
Abstract
Background The current study examined the sensitivity of two memory subtests and their corresponding learning slope metrics derived from the African Neuropsychology Battery (ANB) to detect amyloid pathology and APOEε4 status in adults from Kinshasa, the Democratic Republic of the Congo. Methods 85 participants were classified for the presence of β-amyloid pathology and based on allelic presence of APOEε4 using Simoa. All participants were screened using CSID and AQ, underwent verbal and visuospatial memory testing from ANB, and provided blood samples for plasma Aβ42, Aβ40, and APOE proteotype. Pearson correlation, linear and logistic regression were conducted to compare amyloid pathology and APOEε4 status with derived learning scores, including initial learning, raw learning score, learning over trials, and learning ratio. Results Our sample included 35 amyloid positive and 44 amyloid negative individuals as well as 42 without and 39 with APOEε4. All ROC AUC ranges for the prediction of amyloid pathology based on learning scores were low, ranging between 0.56-0.70 (95% CI ranging from 0.44-0.82). The sensitivity of all the scores ranged between 54.3-88.6, with some learning metrics demonstrating good sensitivity. Regarding APOEε4 prediction, all AUC values ranged between 0.60-0.69, with all sensitivity measures ranging between 53.8-89.7. There were minimal differences in the AUC values across learning slope metrics, largely due to the lack of ceiling effects in this sample. Discussion This study demonstrates that some ANB memory subtests and learning slope metrics can discriminate those that are normal from those with amyloid pathology and those with and without APOEε4, consistent with findings reported in Western populations.
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Affiliation(s)
- Jean Ikanga
- Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, United States
- Department of Psychiatry, School of Medicine, University of Kinshasa and Catholic University of Congo, Kinshasa, Democratic Republic of Congo
| | - Sarah D. Patrick
- Veteran Affairs Ann Arbor Healthcare System, Ann Arbor, MI, United States
| | - Megan Schwinne
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States
| | - Saranya Sundaram Patel
- Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Emmanuel Epenge
- Department of Neurology, University of Kinshasa, Kinshasa, Democratic Republic of Congo
| | - Guy Gikelekele
- Department of Psychiatry, School of Medicine, University of Kinshasa and Catholic University of Congo, Kinshasa, Democratic Republic of Congo
| | - Nathan Tshengele
- Department of Psychiatry, School of Medicine, University of Kinshasa and Catholic University of Congo, Kinshasa, Democratic Republic of Congo
| | | | - Samuel Mampunza
- Department of Psychiatry, School of Medicine, University of Kinshasa and Catholic University of Congo, Kinshasa, Democratic Republic of Congo
| | | | - Charlotte E. Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Neurodegeneration, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, Netherlands
| | - Anthony Stringer
- Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Allan Levey
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, United States
| | - Julio C. Rojas
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Brandon Chan
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Argentina Lario Lago
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Joel H. Kramer
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Adam L. Boxer
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | | | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Robert J. Spencer
- Veteran Affairs Ann Arbor Healthcare System, Ann Arbor, MI, United States
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Boscarino JJ, Weitzner DS, Bailey EK, Kamper JE, Vanderbleek EN. Utility of learning ratio scores from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word List Memory Test in distinguishing patterns of cognitive decline in veterans referred for neuropsychological evaluation. Clin Neuropsychol 2024:1-13. [PMID: 38494420 DOI: 10.1080/13854046.2024.2330144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 03/07/2024] [Indexed: 03/19/2024]
Abstract
Background: The Learning Ratio (LR) is a novel learning score that has shown improved utility over other learning metrics in detecting Alzheimer's disease (AD) across multiple memory tasks. However, its utility on the Consortium to Establish a Registry for Alzheimer's Disease Word List Memory Test (CERAD WLMT), a widely used list learning measure sensitive to decline in neurodegenerative disease, is unknown. The goal of the current study was to determine the utility of LR on the CERAD WLMT in differentiating between diagnostic (MiNCD vs MaNCD) and etiologic groups (VaD vs AD) in a veteran sample. Methods: Raw learning slope (RLS) and LR scores were examined in 168 veterans diagnosed with major neurocognitive disorder (MaNCD), mild neurocognitive disorder (MiNCD), or normal aging following neuropsychological evaluation. Patients with MaNCD were further classified by suspected etiology (i.e. microvascular disease vs AD). Results: Whereas RLS scores were not significantly different between MiNCD and MaNCD, LR scores were significantly different between all diagnostic groups (p's < .05). Those with AD had lower LR scores and RLS scores compared to those with VaD (p's < .05). LR classification accuracy was acceptable for MiNCD (AUC = .76), excellent for MaNCD (AUC = .86) and VaD (AUC = .81), and outstanding for AD (AUC = .91). Optimal cutoff scores for WLMT LR were derived from Youden's index. Conclusion: Results support the use of LR scores over RLS when interpreting the CERAD WLMT and highlight the clinical utility of LR in differentiating between diagnostic groups and identifying suspected etiology.
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Affiliation(s)
- Joseph J Boscarino
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
| | - Daniel S Weitzner
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
| | - Erin K Bailey
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
- Department of Psychiatry, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
| | - Joel E Kamper
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
| | - Emily N Vanderbleek
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
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Heston MB, Hanslik KL, Zarbock KR, Harding SJ, Davenport-Sis NJ, Kerby RL, Chin N, Sun Y, Hoeft A, Deming Y, Vogt NM, Betthauser TJ, Johnson SC, Asthana S, Kollmorgen G, Suridjan I, Wild N, Zetterberg H, Blennow K, Rey FE, Bendlin BB, Ulland TK. Gut inflammation associated with age and Alzheimer's disease pathology: a human cohort study. Sci Rep 2023; 13:18924. [PMID: 37963908 PMCID: PMC10646035 DOI: 10.1038/s41598-023-45929-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 10/25/2023] [Indexed: 11/16/2023] Open
Abstract
Age-related disease may be mediated by low levels of chronic inflammation ("inflammaging"). Recent work suggests that gut microbes can contribute to inflammation via degradation of the intestinal barrier. While aging and age-related diseases including Alzheimer's disease (AD) are linked to altered microbiome composition and higher levels of gut microbial components in systemic circulation, the role of intestinal inflammation remains unclear. To investigate whether greater gut inflammation is associated with advanced age and AD pathology, we assessed fecal samples from older adults to measure calprotectin, an established marker of intestinal inflammation which is elevated in diseases of gut barrier integrity. Multiple regression with maximum likelihood estimation and Satorra-Bentler corrections were used to test relationships between fecal calprotectin and clinical diagnosis, participant age, cerebrospinal fluid biomarkers of AD pathology, amyloid burden measured using 11C-Pittsburgh compound B positron emission tomography (PiB PET) imaging, and performance on cognitive tests measuring executive function and verbal learning and recall. Calprotectin levels were elevated in advanced age and were higher in participants diagnosed with amyloid-confirmed AD dementia. Additionally, among individuals with AD dementia, higher calprotectin was associated with greater amyloid burden as measured with PiB PET. Exploratory analyses indicated that calprotectin levels were also associated with cerebrospinal fluid markers of AD, and with lower verbal memory function even among cognitively unimpaired participants. Taken together, these findings suggest that intestinal inflammation is linked with brain pathology even in the earliest disease stages. Moreover, intestinal inflammation may exacerbate the progression toward AD.
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Affiliation(s)
- Margo B Heston
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kendra L Hanslik
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Katie R Zarbock
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Sandra J Harding
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nancy J Davenport-Sis
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Robert L Kerby
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Nathaniel Chin
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Yi Sun
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Ana Hoeft
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Yuetiva Deming
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Nicholas M Vogt
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | | | | | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Federico E Rey
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA.
| | - Barbara B Bendlin
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
| | - Tyler K Ulland
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI, USA.
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Hammers DB, Nemes S, Diedrich T, Eloyan A, Kirby K, Aisen P, Kramer J, Nudelman K, Foroud T, Rumbaugh M, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu JC, Mendez MF, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha SJ, Turner RS, Weintraub S, Wingo TS, Wolk DA, Wong B, Carrillo MC, Dickerson BC, Rabinovici GD, Apostolova LG. Learning slopes in early-onset Alzheimer's disease. Alzheimers Dement 2023; 19 Suppl 9:S19-S28. [PMID: 37243937 PMCID: PMC10806757 DOI: 10.1002/alz.13159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/16/2023] [Accepted: 02/16/2023] [Indexed: 05/29/2023]
Abstract
OBJECTIVE Investigation of learning slopes in early-onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early-onset dementia with and without β-amyloid positivity METHOD: Data from 310 participants in the Longitudinal Early-Onset Alzheimer's Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determined RESULTS: Worse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric-the learning ratio (LR)-outperformed other learning slope calculations across analyses CONCLUSIONS: Learning slopes appear to be sensitive to early-onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses. HIGHLIGHTS Learning is impaired in amyloid-positive EOAD, beyond cognitive severity scores alone. Amyloid-positive EOAD participants perform worse on learning slopes than amyloid-negative participants. Learning ratio appears to be the learning metric of choice for EOAD participants.
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Affiliation(s)
- Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Sára Nemes
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Taylor Diedrich
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Joel Kramer
- Department of Neurology, University of California, San Francisco, California, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S. Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph C. Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Steve Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon J. Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | | | - Sandra Weintraub
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Thomas S. Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Bonnie Wong
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Maria C. Carrillo
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA
| | - Bradford C. Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gil D. Rabinovici
- Department of Neurology, University of California, San Francisco, California, USA
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
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Spencer RJ, Williams TF, Kordovski VM, Patrick SD, Lengu K, Gradwohl BD, Hammers DB. A quantitative review of competing learning slope metrics: effects of age, sex, and clinical diagnosis. J Clin Exp Neuropsychol 2023; 45:744-757. [PMID: 38357915 DOI: 10.1080/13803395.2024.2314741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 12/27/2023] [Indexed: 02/16/2024]
Abstract
INTRODUCTION In learning and memory tests that involve multiple presentations of the same material, learning slope refers to the degree to which examinees improve performances over successive learning trials. We aimed to quantitatively review the traditional raw learning slope (RLS), and the newly created learning ratio (LR) to understand the effects of demographic variables and clinical diagnoses on learning slope (e.g., limited improvement over multiple trials), and to develop demographically sensitive norms. METHOD A systematic literature search was conducted to evaluate the potential for these aims to be examined across the most popular contemporary multi-trial learning tests. Two databases were searched. Following this, hierarchical linear modeling was used to examine how demographic variables predict learning slope indices. These results were in turn used to contrast the performance of clinical groups with the predicted performance of demographically similar healthy controls. Finally, preliminary normative estimates for learning slope indices were presented. RESULTS A total of 82 studies met criteria for inclusion in this study. However, the Rey Auditory Verbal Learning Test (RAVLT) was the only test to have sufficient trial-level learning and demographic data. Fifty-eight samples from 19 studies were quantitatively examined. Hierarchical linear models provided evidence of sex differences and a curvilinear decline in learning slope with age, with strongest and most consistent effects for LR relative to RLS. Regression-based norms for demographically corrected RLS and LR scores for the RAVLT are presented. The effect of clinical diagnoses was consistently stronger for LR, and Alzheimer's disease had the strongest effect, followed by invalid performances, severe traumatic brain injury, and seizures/epilepsy. CONCLUSION Overall, LR enjoys both conceptual and demonstrated psychometric advantages over RLS. Replication of these findings can be completed by reanalyzing existing datasets. Further work may focus on the utility of using LR in diagnosis and prediction of clinical prognosis.
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Affiliation(s)
- Robert J Spencer
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan Health System, Ann Arbor, MI, USA
| | - Trevor F Williams
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Victoria M Kordovski
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Physical Medicine and Rehabilitation, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Sarah D Patrick
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Ketrin Lengu
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Physical Medicine and Rehabilitation, The MetroHealth System, Cleveland, OH, USA
| | - Brian D Gradwohl
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Trinity Health Hauenstein Neurosciences, Trinity Health, Muskegon, MI, USA
| | - Dustin B Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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Hammers DB, Pentchev JV, Kim HJ, Spencer RJ, Apostolova LG. The relationship between learning slopes and Alzheimer's Disease biomarkers in cognitively unimpaired participants with and without subjective memory concerns. J Clin Exp Neuropsychol 2023; 45:727-743. [PMID: 37676258 PMCID: PMC10916703 DOI: 10.1080/13803395.2023.2254444] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 08/29/2023] [Indexed: 09/08/2023]
Abstract
OBJECTIVE Learning slopes represent serial acquisition of information during list-learning tasks. Although several calculations for learning slopes exist, the Learning Ratio (LR) has recently demonstrated the highest sensitivity toward changes in cognition and Alzheimer's disease (AD) biomarkers. However, investigation of learning slopes in cognitively unimpaired individuals with subjective memory concerns (SMC) has been limited. The current study examines the association of learning slopes to SMC, and the role of SMC in the relationship between learning slopes and AD biomarkers in cognitively unimpaired individuals. METHOD Data from 950 cognitively unimpaired participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 89) were used to calculate learning slope metrics. Learning slopes among those with and without SMC were compared with demographic correction, and the relationships of learning slopes with AD biomarkers of bilateral hippocampal volume and β-amyloid pathology were determined. RESULTS Learning slopes were consistently predictive of hippocampal atrophy and β-amyloid deposition. Results were heightened for LR relative to the other learning slopes. Additionally, interaction analyses revealed different associations between learning slopes and hippocampal volume as a function of SMC status. CONCLUSIONS Learning slopes appear to be sensitive to SMC and AD biomarkers, with SMC status influencing the relationship in cognitively unimpaired participants. These findings advance our knowledge of SMC, and suggest that LR - in particular - can be an important tool for the detection of AD pathology in both SMC and in AD clinical trials.
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Affiliation(s)
- Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Julian V. Pentchev
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Robert J. Spencer
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor MI, USA, 48105
- Michigan Medicine, Department of Psychiatry, Neuropsychology Section, Ann Arbor MI, USA, 48105
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA, 46202
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Hall MG, Wollman SC, Haines ME, Boyle MA, Richardson HK, Hammers DB. Novel learning ratio from the NAB list learning test distinguishes between clinical groups: clinical validation and sex-related differences. J Clin Exp Neuropsychol 2023; 45:715-726. [PMID: 37477412 DOI: 10.1080/13803395.2023.2236772] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 07/09/2023] [Indexed: 07/22/2023]
Abstract
List-learning tasks provide a wealth of information about an individual's cognitive abilities: attention, encoding, storage, retrieval, recognition. A more recently developed metric, the Learning Ratio (LR), supplements information about cognitive ability and can assist the clinician in determining whether an individual has cognitive impairment. The LR is calculated by taking the difference between the individuals' raw score on the first learning trial and their raw score on the last learning trial, which is then divided by the number of words left to be learned after the first learning trial. A LR derived from the list-learning task from the Neuropsychological Assessment Battery (NAB) was evaluated to determine ability to distinguish those with normal cognition from those with mild cognitive impairment (MCI) and dementia. Results from the present study indicate the NAB LR is able to distinguish between clinical groups; recommended cutoffs for the NAB LR scores are provided. We also found a significant female sex-advantage for the NAB LR in those with normal memory ability and demonstrated the female sex advantage decreased with increasing memory impairment. Taken together, the NAB LR may assist clinicians in making an accurate and early diagnosis and may be helpful for tracking learning and functioning across multiple assessments. .
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Affiliation(s)
- Matthew G Hall
- University of Toledo Medical Center Rehabilitation Services, Toledo, Ohio, USA
| | | | - Mary E Haines
- University of Toledo Medical Center Rehabilitation Services, Toledo, Ohio, USA
| | - Mellisa A Boyle
- University of Toledo Medical Center Rehabilitation Services, Toledo, Ohio, USA
| | | | - Dustin B Hammers
- Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
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Hammers DB, Kostadinova RV, Spencer RJ, Ikanga JN, Unverzagt FW, Risacher SL, Apostolova LG. Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer's Disease. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2023; 30:866-884. [PMID: 36074015 PMCID: PMC9992455 DOI: 10.1080/13825585.2022.2120957] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 08/30/2022] [Indexed: 10/14/2022]
Abstract
Despite extensive use of the Alzheimer's Disease (AD) Assessment Scale - Cognitive Subscale (ADAS-Cog) in AD research, exploration of memory subtests or process scores from the measure has been limited. The current study sought to establish validity for the ADAS-Cog Word Recall Immediate and Delayed Memory subtests and learning slope scores by showing that they are sensitive to AD biomarker status. Word Recall subtest and learning slope scores were calculated for 441 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90). All participants were categorized using the NIA-AA Research Framework - based on PET-imaging of β-amyloid (A) and tau (T) deposition - as Normal AD Biomarkers (A-T-), Alzheimer's Pathologic Change (A + T-), or Alzheimer's disease (A + T+). Memory subtest and learning slope performances were compared between biomarker status groups, and with regard to how well they discriminated samples with (A + T+) and without (A-T-) biomarkers. Lower Word Recall memory subtest scores - and scores for a particular learning slope calculation, the Learning Ratio - were observed for the AD (A + T+) group than the other biomarker groups. Memory subtest and Learning Ratio scores further displayed fair to good receiver operator characteristics when differentiating those with and without AD biomarkers. When comparing across learning slopes, the Learning Ratio metric consistently outperformed others. ADAS-Cog memory subtests and the Learning Ratio score are sensitive to AD biomarker status along the continuum of the NIA-AA Research Framework, and the results offer criterion validity for use of these subtests and process scores as unique markers of memory capacity.
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Affiliation(s)
- Dustin B. Hammers
- Indiana University School of Medicine, Department of Neurology, Indianapolis, IN, USA
| | | | - Robert J. Spencer
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor MI, USA
- Michigan Medicine, Department of Psychiatry, Neuropsychology Section, Ann Arbor MI, USA
| | - Jean N. Ikanga
- Emory University, School of Medicine, Department of Rehabilitation Medicine, GA, USA
- University of Kinshasa, Department of Psychiatry, Democratic Republic of Congo (DRC)
| | | | - Shannon L. Risacher
- Indiana University School of Medicine, Department of Radiology, Indianapolis, IN, USA
| | - Liana G. Apostolova
- Indiana University School of Medicine, Department of Neurology, Indianapolis, IN, USA
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