Use of Vitamin K Antagonists and Brain Volumetry in Older Adults: Preliminary Results From the <scp>GAIT</scp> Study
Bibliographic record
Abstract
To the Editor: Older adults use vitamin K antagonists (VKAs) widely for the prophylaxis and treatment of thromboembolic diseases.1, 2 VKAs reduce the bioavailability of the active form of vitamin K,3, 4 but recent data suggest that vitamin K could positively influence brain function,1, 2 particularly by regulating the synthesis of sphingolipids, which are constituents of the myelin sheath and neuronal membrane,2 and by regulating the biological activation of vitamin K–dependent proteins (VKDPs), which are involved in neuronal health and function.2 Epidemiological data indicate a positive association between serum vitamin K concentrations and episodic memory function in older adult.3 In contrast, use of VKAs was associated with cognitive impairment in older adults, regardless of atrial fibrillation or stroke.4 It was hypothesized that the onset of volumetric brain changes while using VKAs could explain such cognitive disorders. For instance, maternal exposure to VKA in the second trimester affects fetal brain development.5 This effect has not been examined in older adult. The objective of the current study was to determine whether the use of VKAs was associated with lower brain volume in older adult. Given the preferential localization of vitamin K in the temporal lobes6 and the onset of episodic memory disorders in people using VKAs,3 the association between VKAs and hippocampal atrophy was examined. Community-dwelling individuals included in the Gait and Alzheimer Interactions Tracking (GAIT) study between 2009 and 2013 were studied.7 The main exclusion criteria were age younger than 60, stroke, a Mini-Mental State Examination score less than 10, and severe depression. The local ethics committee approved the study. Participants with a three-dimensional T1-weighted magnetization prepared rapid gradient echo sagittal magnetic resonance imaging (MRI) scan (acquisition matrix 256 × 256 × 144, field of view 240 × 240 × 187 mm, TE/TR/TI = 4.07/2,170/1,100 ms) acquired on 1.5-Tesla MRI scanner (Magnetom Avanto, Siemens, Erlangen, Germany) were included in the present analysis. Brain subvolumes (total brain, lateral ventricles, total white matter, total gray matter, cortical gray matter, temporal cortex, entorhinal cortex, hippocampus) were measured using FreeSurfer, a set of tools that automatically segments, labels, and quantifies brain volumes based on established processing steps (http://surfer.nmr.mgh.harvard.edu/).8 Measured subvolumes were normalized to intracranial volume. Brain imaging was also used to diagnose intracranial hemorrhage. The regular use of VKAs (warfarin, acenocoumarol, fluindione), other anticoagulants (heparin, direct oral anticoagulant), and antiplatelet medications (aspirin, clopidogrel, ticlopidine, dipyridamole) was noted from family physician prescriptions regardless of indication, length of treatment, or international normalized ratio. History of atrial fibrillation, mechanical heart valve, hyperlipidemia, carotid artery stenosis, and severe renal impairment (creatinine clearance <30 mL/min) was recorded from the individual's file. Mean arterial pressure at rest (MAP) was calculated from systolic (SBP) and diastolic blood pressure (DBP) (MAP = (SBP + 2 × DBP)/3). Diagnosis of cognitive disorders was based on Dubois criteria for mild cognitive impairment, and Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition, criteria for dementia.9 Comparisons of participants separated into two groups based on VKA use were performed using nonparametric Mann-Whitney U-tests or chi-square tests. Pearson correlation and linear regressions were performed using SPSS version 19 (IBM Corp., Chicago, IL) to examine the association between VKA use and normalized brain subvolumes. P < .05 was considered significant. One hundred ninety-seven participants (mean age 72.4 ± 5.6; 58.4% male; 53.8% with a college education or more; 0.5% with intracranial hemorrhage, 57% with hyperlipidemia, 2.5% with carotid artery stenosis, 5.1% with cognitive disorder, 0.5% with severe renal impairment) were recruited. Four participants were taking VKAs, 33 were taking antiplatelet medications, and none were taking other anticoagulants. Participants with VKAs had larger lateral ventricles (P = .02) than those without, and lower normalized brain (P = .01), total gray matter (P = .01), cortical gray matter (P = .02), and hippocampal (P = .04) volumes (Table 1). Taking VKAs was associated with smaller normalized brain (β = −4.71, P = .048), total gray matter (β = −3.41, P = .02), entorhinal cortex (β = −0.03, P = .02), and hippocampal (β = −0.09, P = .01) volumes and larger ventricles (β = 1.36, P = .01). After adjustment for all potential confounders, taking VKAs was still associated with larger ventricles (β = 1.26, P = .03) and lower total gray matter volume (β = −2.92, P = .04) (Table 1). The use of VKA by older adults was associated with smaller brain volume normalized to intracranial volume; specifically, lower volumes of gray matter were found, including in the temporal cortex and hippocampus. Exactly how VKAs and brain changes are associated is not known. It is possible that taking blood-thinning drugs suggests underlying conditions, such as atrial fibrillation, that may result in brain changes.10 However, the associations between VKAs and normalized lateral ventricle volume (a proxy for brain atrophy) or normalized total gray matter volume remained significant after adjustment for atrial fibrillation and use of other blood-thinning drugs. This suggests a specific effect of VKAs on the brain. Previous studies support a role of vitamin K in the CNS, particularly in the regulation of VKDPs, which are involved in cell growth, myelination, and neuroprotection1, 2 and in the metabolism of sphingolipids,1, 2 whose concentration in the hippocampus correlates positively with serum vitamin K concentration.6 Less available vitamin K―because of VKAs, for example―may lead to less protection in the CNS and subsequently a greater risk of atrophy, but the use of a cross-sectional design prevented causality from being inferred. Longitudinal prospective studies with more participants are required to investigate the effect of VKAs on brain volumetry with higher levels of evidence. We are grateful to the participants for their cooperation. Conflict of Interest: Dr. Annweiler serves as an unpaid associate editor for Gériatrie, Psychologie et Neuropsychiatrie du Vieillissement and for the Journal of Alzheimer's Disease. He has no relevant financial interest in this manuscript. Prof. Beauchet serves as an unpaid associate editor for Gériatrie, Psychologie et Neuropsychiatrie du Vieillissement. He has no relevant financial interest in this manuscript. Author Contributions: Dr. Annweiler had full access to the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analyses. Study concept and design: Annweiler. Data acquisition: Annweiler, Denis, Beauchet. Data analysis and interpretation: Annweiler, Denis. Drafting of manuscript: Annweiler. Critical revision of manuscript for important intellectual content: Denis, Duval, Ferland, Bartha, Beauchet. Obtained funding: Beauchet. Statistical expertise: Annweiler. Administrative, technical, or material support: Annweiler. Study supervision: Annweiler, Beauchet. Sponsor's Role: The study was financially supported by the French Ministry of Health (Projet Hospitalier de Recherche Clinique national no 2009-A00533–54). The sponsor had no role in the design or conduct of the study; in the collection, management, analysis, or interpretation of the data; or in the preparation, review, or approval of the manuscript.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".