How Bayesian statistics may help answer some of the controversial questions in clinical research on Alzheimer's disease

Temp, Anna G. M.; Lutz, Michael W.; Trépel, Dominic; Tang, Yi; Wagenmakers, Eric‐Jan; Khachaturian, Ara S.; Teipel, Stefan J.

doi:10.1002/alz.12374

Cited by 10 publications

(16 citation statements)

References 25 publications

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“…Additionally, the 95% credible interval of the posterior distribution of the parameter estimates is directly interpretable as the range in which the parameter lies with 95% probability given the data. This is different from the interpretation of the frequentist 95% confidence interval: the parameter estimate will lie in this interval in 95% of future repeated experiments 15,17,18 …”

Section: Introductionmentioning

confidence: 70%

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline

Teipel,

Dyrba,

Kleineidam

et al. 2024

Alz & Dem Diag Ass & Dis Mo

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INTRODUCTIONWe investigated the association of inflammatory mechanisms with markers of Alzheimer's disease (AD) pathology and rates of cognitive decline in the AD spectrum.METHODSWe studied 296 cases from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study (DELCODE) cohort, and an extension cohort of 276 cases of the Alzheimer's Disease Neuroimaging Initiative study. Using Bayesian confirmatory factor analysis, we constructed latent factors for synaptic integrity, microglia, cerebrovascular endothelial function, cytokine/chemokine, and complement components of the inflammatory response using a set of inflammatory markers in cerebrospinal fluid.RESULTSWe found strong evidence for an association of synaptic integrity, microglia response, and cerebrovascular endothelial function with a latent factor of AD pathology and with rates of cognitive decline. We found evidence against an association of complement and cytokine/chemokine factors with AD pathology and rates of cognitive decline.DISCUSSIONLatent factors provided access to directly unobservable components of the neuroinflammatory response and their association with AD pathology and cognitive decline.

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Section: Introductionmentioning

confidence: 70%

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline

Teipel,

Dyrba,

Kleineidam

et al. 2024

Alz & Dem Diag Ass & Dis Mo

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“…This algorithm is moreover model-free, not making a-priori assumptions about functional dependencies or particular distributions in the variates. The inference principles on which it is based have recently been recommended for the study of Alzheimer's Disease (Temp et al, 2021; see also ASA, 2016ASA, , 2019, and have been successfully demonstrated in a simpler predictor setting (Antoniano-Villalobos et al, 2014). We showed its application in an example of prognosis and treatment of conversion from Mild Cognitive Impairment to Alzheimer's Disease for four different patients, where all three categories of differences listed above appeared.…”

Section: Predictor Importancementioning

confidence: 90%

Personalized prognosis & treatment using an optimal predictor machine: An example study on conversion from Mild Cognitive Impairment to Alzheimer's Disease

Mana¹,

Rye²,

Vik³

et al. 2023

Preprint

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The present work presents a statistically sound, rigorous, and model-free algorithm – the Ledley-Jaynes machine – for use in personalized medicine. The Ledley-Jaynes machine is designed first to learn from a dataset of clinical with relevant predictors and predictands, and then to assist a clinician in the assessment of prognosis & treatment for new patients. It allows the clinician to input, for each new patient, additional patient-dependent clinical information, as well as patient-dependent information about benefits and drawbacks of available treatments. We apply the algorithm in a realistic setting for clinical decision-making, incorporating clinical, environmental, imaging, and genetic data, using a data set of subjects suffering from mild cognitive impairment and Alzheimer’s Disease. We show how the algorithm is theoretically optimal, and discuss some of its major advantages for decision-making under risk, resource planning, imputation of missing values, assessing the prognostic importance of each predictor, and more.

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“…Given the small number of cases and the indirect structural imaging approach, we want to point out again that our findings should not be interpreted as confirmatory but that they justify future testing of the hypothesis of a cholinergic deficit in limbic TDP‐43. Finally, our data show the ability of Bayesian analysis to provide quantitative evidence for either the presence or absence of an effect given the data, which is more informative than just accepting or rejecting the null hypothesis of no effect based on classical p ‐values [28].…”

Section: Discussionmentioning

confidence: 99%

Antemortem basal forebrain atrophy in pure limbic TAR DNA‐binding protein 43 pathology compared with pure Alzheimer pathology

Teipel

Grothe

2022

Euro J of Neurology

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Background and purpose: Currently, the extent of cholinergic basal forebrain atrophy in relatively pure limbic TAR DNA-binding protein 43 (TDP-43) pathology compared with relatively pure Alzheimer disease (AD) is unclear. Methods:We compared antemortem magnetic resonance imaging (MRI)-based atrophy of the basal forebrain and medial and lateral temporal lobe volumes between 10 autopsy cases with limbic TDP-43 pathology and 33 cases with AD pathology on postmortem neuropathologic examination from the Alzheimer's Disease Neuroimaging Initiative cohort. For reference, we studied MRI volumes from cognitively healthy, amyloid positron emission tomography-negative subjects (n = 145). Group differences were assessed using Bayesian analysis of covariance. In addition, we assessed brain-wide regional volume changes using partial least squares regression (PLSR). Results:We found extreme evidence (Bayes factor [BF] 01 > 600) for a smaller basal forebrain volume in both TDP-43 and AD cases compared with amyloid-negative controls, and moderate evidence (BF 01 = 4.9) that basal forebrain volume was not larger in TDP-43 than in AD cases. The ratio of hippocampus to lateral temporal lobe volumes discriminated between TDP-43 and AD cases with an accuracy of 0.78. PLSR showed higher gray matter in lateral temporal lobes and cingulate and precuneus, and reduced gray matter in precentral and postcentral gyri and hippocampus in TDP-43 compared with AD cases.Conclusions: Atrophy of the cholinergic basal forebrain appears to be similarly pronounced in cases with limbic TDP-43 pathology as in AD. This suggests that a clinical trial of the efficacy of cholinesterase inhibitors in amyloid-negative cases with amnestic dementia and an imaging signature of TDP-43 pathology may be warranted.

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How Bayesian statistics may help answer some of the controversial questions in clinical research on Alzheimer's disease

Cited by 10 publications

References 25 publications

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline

Personalized prognosis & treatment using an optimal predictor machine: An example study on conversion from Mild Cognitive Impairment to Alzheimer's Disease

Antemortem basal forebrain atrophy in pure limbic TAR DNA‐binding protein 43 pathology compared with pure Alzheimer pathology

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How Bayesian statistics may help answer some of the controversial questions in clinical research on Alzheimer's disease

Cited by 10 publications

References 25 publications

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline

Personalized prognosis &amp; treatment using an optimal predictor machine: An example study on conversion from Mild Cognitive Impairment to Alzheimer's Disease

Antemortem basal forebrain atrophy in pure limbic TAR DNA‐binding protein 43 pathology compared with pure Alzheimer pathology

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Personalized prognosis & treatment using an optimal predictor machine: An example study on conversion from Mild Cognitive Impairment to Alzheimer's Disease