Predicting probable Alzheimer's disease using linguistic deficits and biomarkers

BackgroundThe manual diagnosis of neurodegenerative disorders such as Alzheimer’s disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological examinations. The use of several Machine Learning algorithms to build automated diagnostic models using low-level linguistic features resulting from verbal utterances could aid diagnosis of patients with probable AD from a large population. For this purpose, we developed different Machine Learning models on the DementiaBank language transcript clinical dataset, consisting of 99 patients with probable AD and 99 healthy controls.ResultsOur models learned several syntactic, lexical, and n-gram linguistic biomarkers to distinguish the probable AD group from the healthy group. In contrast to the healthy group, we found that the probable AD patients had significantly less usage of syntactic components and significantly higher usage of lexical components in their language. Also, we observed a significant difference in the use of n-grams as the healthy group were able to identify and make sense of more objects in their n-grams than the probable AD group. As such, our best diagnostic model significantly distinguished the probable AD group from the healthy elderly group with a better Area Under the Receiving Operating Characteristics Curve (AUC) using the Support Vector Machines (SVM).ConclusionsExperimental and statistical evaluations suggest that using ML algorithms for learning linguistic biomarkers from the verbal utterances of elderly individuals could help the clinical diagnosis of probable AD. We emphasise that the best ML model for predicting the disease group combines significant syntactic, lexical and top n-gram features. However, there is a need to train the diagnostic models on larger datasets, which could lead to a better AUC and clinical diagnosis of probable AD

Macro-Level Cognitive and Linguistic Function in Early Stage Alzheimer’s Disease and Mild Cognitive Impairment

Alzheimer’s disease (AD) is a global health concern, particularly as there is currently no cure for the disease. Interventions to slow progression of disease, pharmacological or non-pharmacological, need to be targeted early on before any significant neurodegeneration has occurred, as these changes are irreversible, and lost cognitive function cannot be recovered. This makes it imperative to detect pathological cognitive decline as early as possible. Although biomarkers have received a lot of attention in this regard, they have several limitations, particularly outside of research settings, such as cost and availability. Cognitive markers, other than traditional neuropsychological test measures, on the other hand, have received comparatively less attention with regards to early detection; and, particularly cognitive markers that are rooted in real-world, everyday cognition, have been lacking. Due to the disease being incurable, interventions are aimed at maintaining independent living and good quality of life for as long as possible. This necessitates outcomes that can measure meaningful change in cognition and everyday functioning. The goal of the present dissertation was to identify gaps in the current literature on cognitive and linguistic assessments that are embedded in aspects of everyday cognition in AD, and work towards developing paradigms to address the gaps. Due to the emphasis on early detection, the work focused on patients in the very early stage of AD and on its preceding stage of Mild Cognitive Impairment (MCI). In light of evidence reporting the inability of AD patients to follow narratives, be it verbal or non-verbal, a systematic review of text comprehension studies was conducted to characterize and evaluate macro-level measures of discourse comprehension in their sensitivity to early stage AD, and their ability to distinguish pathological ageing due to AD or MCI from cognitive ageing. Results showed that, not only AD patients, but also MCI patients were significantly more impaired on macro-level measures of comprehension compared to cognitively healthy older adults. These findings were consistent across all eight studies included in the review, indicating a robust effect, though there were minor differences in the sensitivity of different measures. Next, moving towards non-verbal narratives, a novel picture-based paradigm assessing event cognition, with a focus on event integration and macro-event recognition, was introduced. This study aimed to examine the macro-level processing of events by using a format requiring integration of micro-events, depicted in pictures, into a larger macro-event. AD and MCI patients’ ability to connect the micro-events temporally and causally to identify the depicted macro-event was assessed. As hypothesized, the findings showed that patient groups had significant difficulties in determining temporal order of micro-events, even when provided with a verbal cue, as well as in conceptualizing the macro-event from the presented micro-events, when compared to healthy older adults. Finally, using traditional neuropsychological tests, the cognitive processes involved in performing the macro-event recognition task were determined by examining correlations. Primarily, semantic memory and executive functioning appear to play a role. However, the strength of correlations was fairly moderate, indicating added value of event recognition task in cognitive assessment. Taken together, these findings show the sensitivity of macro-level cognitive and linguistic markers based in everyday cognition in the early stages of AD, and highlight the positive role of such cognitive assessment methods in bringing together objective assessment methods and everyday cognition

The Linguistic and Cultural Aspects of Neuropsychological Assessment in People with Dementia

Objectives: Given the public health crisis that Alzheimer's disease (AD) has become (Naylor et al., 2012),neuropsychological assessment tools that provide timely and accurate identification of cognitive decline in older adults have gained increasing focus in the scientific literature. Accurate evaluation of cognitive function and early identification of cognitive changes are paramount to understanding the disease course of AD and improving effective treatments and patients' quality of life. To this end, language offers a cognitive neuropsychological approach to identifying cognitive decline in the early stages of AD. Moreover, it represents a multi-dimensional variable that may influence the neuropsychological test performance of older adults due to its potential contribution to cognitive reserve. Therefore, the present thesis aims at combining two aspects of language to explore its potential in the early detection of AD and its association with neuropsychological test performance in older adults and cross-cultural neuropsychology. Study 1 assessed the currently available studies to explore whether discourse processing, particularly macro-structural discourse comprehension, offers a novel approach to neuropsychological testing in distinguishing normal cognitive aging from AD pathology-related decline. Study 2 evaluated the results of the studies that examined the impact of bilingualism on neuropsychological test performance in monolingual and bilingual older adults to inform the neuropsychological evaluation of these groups in clinical practice. Study 3 investigated the influence of bilingualism and its associated factors, namely, cultural background and acculturation, on cognitive screening tests in three clinically diagnosed AD patient groups to identify a cross-culturally/linguistically appropriate measure of cognition. Method: Data of Study 1 and Study 2 were based on the original research studies published in English investigating discourse comprehension and bilingualism in healthy older adults, individuals with mild cognitive impairment (MCI), and AD. A literature search focusing on these topics with participant groups aged 60 years and over was conducted in PubMed, Web of Science, and PsycINFO databases. Study 1 included eight articles consisting of studies only with cross sectional designs. Study 2 was comprised of twenty-seven articles, of which sixteen articles had cross-sectional designs. On the other hand, Study 3 was original research based on a cross sectional design targeting culturally/linguistically diverse patients diagnosed with AD. Specifically, the study sample consisted of Turkish immigrant (n=21) and monolingual, non-immigrant German (n=20) and Turkish (n=24) patients with AD. All participants were administered the Mini-Mental State Examination (MMSE), Rowland Universal Dementia Assessment Scale (RUDAS), a dementia severity rating scale, and a self-report measure of depression. Additionally, self-report measures of bilingualism and acculturation were conducted with Turkish-immigrant participants with AD. Results: Study 1 revealed that people with AD and MCI have significant deficits in discourse comprehension, which are not observed in cognitively normal older adults of any age. On five of six discourse comprehension measures, groups with AD were significantly worse than healthy older adults, with one measure yielding mixed findings. Furthermore, compared to the cognitively healthy groups, individuals with MCI showed significant performance deficits in discourse comprehension measures similar to those with AD. Study 2 indicated better performance for bilingual older adults on executive function tests when compared to their monolingual counterparts. On the other hand, bilinguals were found to perform poorer than monolinguals on tests assessing the language domain. However, these findings did not remain robust when the impact of bilingualism on test performance was investigated longitudinally. Lastly, Study 3 provided further evidence on the linguistic and educational bias of the MMSE when employed in culturally and linguistically diverse individuals with AD. Bilingualism was linked to better performance on the MMSE in the Turkish immigrant group. German patients with AD obtained higher scores on this test than the other two groups. Furthermore, RUDAS was shown to be a better alternative for assessing global cognition in German and Turkish individuals with AD. Conclusion: The macro-structural discourse comprehension assessment paradigm has shown promising results in identifying the preclinical stages of AD. Further research on this paradigm may help develop a diagnostic tool with a clinical value that can be utilized for differential diagnosis, predicting conversion from MCI to dementia in research and clinical settings. On the other hand, another aspect of linguistic skills, namely, the evaluation of research on the link between bilingualism and neuropsychological test performance, did not provide definitive answers to the question of bilingual advantages and disadvantages addressed in the second study due to methodological challenges in the field. However, it identified a comprehensive and critical list of clinically and empirically relevant bilingualism-associated variables which may guide future research and neuropsychological practice. In light of the Study 2 findings, Study 3 filled an important gap in the literature by exploring cultural, demographic, and immigration related factors that may influence neuropsychological testing experiences in Germany. The study findings may help the field of cross-cultural neuropsychology serve culturally and linguistically diverse populations more efficiently. Overall, the present thesis contributed to the literature by highlighting the importance and potential of linguistic abilities in the clinical diagnosis and neuropsychological evaluation of individuals with dementia

Validation of brief cognitive tests in mild cognitive impairment, Alzheimer's disease and dementia with Lewy bodies.

Background It is estimated that 34 million people suffer from dementia, costing society US$422 billion each year. Alzheimer’s disease (AD) is the most common dementia and the global prevalence is predicted to increase to over 100 million people by the year 2050, with the greatest increase in developing countries. Therefore, inexpensive and efficient instruments are required for investigation and evaluation. Aim To evaluate the brief cognitive tests cube copying, clock drawing, the Mini-Mental State Examination (MMSE) and A Quick Test of Cognitive Speed (AQT) in the early diagnosis, treatment evaluation and differential diagnosis of dementias. Populations I. 85 patients with AD. II. 33 patients with dementia with Lewy bodies (DLB) and 66 with AD. III. 75 patients with AD. IV. 99 patients with mild cognitive impairment (MCI). Findings I. Cube copying was found useful for evaluating treatment with acetylcholinesterase inhibitors (AChEI) in patients with AD. II. Easy and quick interpretations of the MMSE, clock drawing and cube copying differentiated patients with DLB from patients with AD. III. AQT was twice as sensitive as the MMSE in detecting treatment response to AChEI in patients with AD. IV. The MMSE, AQT and clock drawing were as accurate as cerebrospinal fluid biomarkers (tau, Aβ42 and P-tau) in predicting development of AD and dementia in mild cognitive impairment during an average of five years. Conclusion This thesis has improved the validity of brief cognitive tests and contributed with results that can be clinically relevant for evaluating treatment of AD, differentiating DLB from AD, and predicting development of AD and other dementias

A Machine Learning-Based Linguistic Battery for Diagnosing Mild Cognitive Impairment Due to Alzheimer\u27s Disease

This is an open access article distributedunder the terms of the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproductionin any medium,provided the original author and source are credited. There is a limited evaluation of an independent linguistic battery for early diagnosis of Mild Cognitive Impairment due to Alzheimer\u27s disease (MCI-AD). We hypothesized that an independent linguistic battery comprising of only the language components or subtests of popular test batteries could give a better clinical diagnosis for MCI-AD compared to using an exhaustive battery of tests. As such, we combined multiple clinical datasets and performed Exploratory Factor Analysis (EFA) to extract the underlying linguistic constructs from a combination of the Consortium to Establish a Registry for Alzheimer\u27s disease (CERAD), Wechsler Memory Scale (WMS) Logical Memory (LM) I and II, and the Boston Naming Test. Furthermore, we trained a machine-learning algorithm that validates the clinical relevance of the independent linguistic battery for differentiating between patients with MCI-AD and cognitive healthy control individuals. Our EFA identified ten linguistic variables with distinct underlying linguistic constructs that show Cronbach\u27s alpha of 0.74 on the MCI-AD group and 0.87 on the healthy control group. Our machine learning evaluation showed a robust AUC of 0.97 when controlled for age, sex, race, and education, and a clinically reliable AUC of 0.88 without controlling for age, sex, race, and education. Overall, the linguistic battery showed a better diagnostic result compared to the Mini-Mental State Examination (MMSE), Clinical Dementia Rating Scale (CDR), and a combination of MMSE and CDR

Serial Position Effect Profiles and Their Neuroanatomical Correlates: Predictors of Conversion to Alzheimer\u27s Disease

The current study was designed to determine whether targeted, premorbid, neuropsychological measures of the serial position effect (SPE) can detect and explain risk for later development of Alzheimer’s disease (AD). The study tested the utility of SPE measures in healthy controls (HC) and individuals already diagnosed with mild cognitive impairment (MCI) or AD. Aim 1 was to determine whether these sensitive, valid neuropsychological measures can explain disease risk. SPE of list-learning are highly sensitive cognitive markers that capture important elements of both linguistic and amnestic mechanisms of encoding, learning, and retrieval. Using the Rey Auditory Verbal Learning Test (RAVLT), we tested two measures of serial position effect scores (SPE-Index) calculated as accuracy recall at different serial positions at Learning, Short-Delay or Long-Delay, as well as SPE profile scores (SPE-Contrast), which compared accuracy recall of two SPE positions. The three SPE-contrast scores were calculated from primacy, middle, and recency list regions at Learning (Learning), short and long delay recall (SD, LD) trials as follows: (1) J-Shape captures difference between recency and primacy scores at Learning (RecencyLearning - PrimacyLearning); (2) Recency-Drop captures change of recency scores from Learning to SD (RecencyLearning – RecencySD); and (3) Primacy Progression captures how primacy accuracy progresses from Learning to LD (PrimacyLD -PrimacyLearning). We first entered both measures to explain risk of conversion to disease status from a) HC (N = 200) to MCI or AD; and b) from MCI (N = 353) to AD using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. We then contrasted the SPE-Index and SPE-Contrast scores to traditional total list-learning scores from the RAVLT as predictors of conversion. In Aim 2 we performed whole-brain analyses and posited that performance of SPE-Index scores would be subserved by distinct brain regions relevant to learning and encoding. We hypothesized that relevant language and memory driven SPE scores would be associated with corresponding neuroanatomical correlates. For example, we predicted that SPE-Primacy scores would be positively correlated with hippocampal, medial temporal, and frontal lobe regions given their associations with semantic encoding and retrieval. Alternately, we hypothesized that SPE-Recency scores would be positively correlated with inferior parietal and superior temporal gyrus regions, which would explain preserved phonological processing of items. Findings supported our Aim 1 hypothesis. We demonstrated that in preclinical (HC) individuals, diminished Short Delay recall performance of a word-list task best explained conversion risk. The Primacy item recall at Short Delay emerged as a particularly sensitive predictor of progression along the clinical AD spectrum for preclinical individuals. Total-RAVLT list scores at Short Delay also emerged as a predictor, although subsequent analyses highlighted that the primacy items at Short Delay were driving this signal. To our knowledge, these data are the first to support the importance of short delay primacy items as a predictor of disease development in the preclinical population. In MCI, all SPE-Contrast profiles in addition to all SPE-Index scores, with the exception of Recency at SD, significantly explained risk of progression to AD. In MCI, the SPE scores’ utility was similar to that of Total-RAVLT list scores. Findings for Aim 2 were mixed. Contrary to our hypotheses, in HC, we found Recency at Long Delay to be associated with left medial orbitofrontal cortical thickness, but no other significant SPE-Index or Total-RAVLT list score to have significant cortical volume or thickness correlates. By the MCI stage, the SPE-Index measures of Primacy and Middle list positions were associated with a range of regional volumes and thicknesses as were Total-RAVLT scores. The SPE-Index scores at this stage of disease did associate with more specific regions than Total-Scores; but SD, which was of primary interest in preclinical individuals, did not emerge with any significant SPE-Index correlates. Together, this study demonstrated that well-selected, theoretically driven neuropsychological measures can play a prominent role in identifying healthy individuals at great risk of developing AD. Importantly, the initial primacy items of long word-lists rely on semantic processing to be encoded. We propose that future study of other biomarkers to associate with SPE-Primacy in healthy individuals will be critical in order to capitalize on its sensitivity as a predictor of future disease. Furthermore, these SPE scores have the benefit of drawing on theoretical underpinnings and mapping on to specific AD disease processes that may be missed by total scores

EANM-EAN recommendations for the use of brain 18 F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) in neurodegenerative cognitive impairment and dementia: Delphi consensus

BACKGROUND: Recommendations for using FDG-PET to support the diagnosis of dementing neurodegenerative disorders are sparse and poorly structured. METHODS: We defined 21 questions on diagnostic issues and on semi-automated analysis to assist visual reading. Literature was reviewed to assess study design, risk of bias, inconsistency, imprecision, indirectness and effect size. Critical outcomes were sensitivity, specificity, accuracy, positive/negative predictive value, area under the receiving operating characteristic curve, and positive/negative likelihood ratio of FDG-PET in detecting the target conditions. Using the Delphi method, an expert panel voted for/against the use of FDG-PET based on published evidence and expert opinion. RESULTS: Of the 1435 papers, 58 provided proper quantitative assessment of test performance. The panel agreed on recommending FDG-PET for 14 questions: diagnosing mild cognitive impairment due to Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD) or dementia with Lewy bodies (DLB); diagnosing atypical AD and pseudodementia; differentiating between AD and DLB, FTLD, or vascular dementia, between DLB and FTLD, and between Parkinson's disease (PD) and progressive supranuclear palsy; suggesting underlying pathophysiology in corticobasal degeneration and progressive primary aphasia, and cortical dysfunction in PD; using semi-automated assessment to assist visual reading. Panelists did not support FDG-PET use for preclinical stages of neurodegenerative disorders, for amyotrophic lateral sclerosis (ALS) and Huntington disease (HD) diagnoses, and ALS or HD-related cognitive decline. CONCLUSIONS: Despite limited formal evidence, panelists deemed FDG-PET useful in the early and differential diagnosis of the main neurodegenerative disorders, and semiautomated assessment helpful to assist visual reading. These decisions are proposed as interim recommendations. This article is protected by copyright. All rights reserved

Diagnostic and prognostic role of semantic processing in preclinical Alzheimer's disease

Relatively spared during most of the timeline of normal aging, semantic memory shows a subtle yet measurable decline even during the pre-clinical stage of Alzheimer's disease. This decline is thought to reflect early neurofibrillary changes and impairment is detectable using tests of language relying on lexical-semantic abilities. A promising approach is the characterization of semantic parameters such as typicality and age of acquisition of words, and propositional density from verbal output. Seminal research like the Nun Study or the analysis of the linguistic decline of famous writers and politicians later diagnosed with Alzheimer's disease supports the early diagnostic value of semantic processing and semantic memory. Moreover, measures of these skills may play an important role for the prognosis of patients with mild cognitive impairment