The Association of Serum Uric Acid Level, Gout, and Alzheimer’s Disease: A Bidirectional Mendelian Randomization Study

Ou, Ya‐Nan; Zhao, Bing; Fu, Yan; Sheng, Ze-Hu; Gao, Pei-Yang; Tan, Lan; Yu, Jin‐Tai

doi:10.3233/jad-220649

Cited by 4 publications

(1 citation statement)

References 70 publications

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“…One study suggests a causal relationship between elevated serum uric acid levels and the risk of AD [22]. Study also suggested that the association between low uric acid levels and cognitive decline may be superior to underlying malnutrition [23].…”

Section: Discussionmentioning

confidence: 99%

Predicting the Rapid Progression of Mild Cognitive Impairment by Intestinal Flora and Blood Indicators through Machine Learning Method

Wang,

Yan,

Liu

et al. 2023

Neurodegener Dis

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Introduction: The aim of the work was to establish a prediction model of mild cognitive impairment (MCI) progression based on intestinal flora by machine learning method. Method: A total of 1013 patients were recruited, in which 87 patients with MCI finished a two-year follow-up. To establish a prediction model, 61 patients were randomly divided into a training set and 26 patients were divided into a testing set. A total of 121 features including demographic characteristics, hematological indicators, and intestinal flora abundance were analyzed. Results: Of the 87 patients who finished a two-year follow-up, 44 presented rapid progression. Model 1 was established based on 121 features with the accuracy 85%, sensitivity 85%, and specificity 83%. Model 2 was based on the first fifteen features of Model 1, (triglyceride, uric acid, alanine transaminase, F-Clostridiaceae, G-Megamonas, S-Megamonas, G-Shigella, G-Shigella, S-Shigella, average hemoglobin concentration, G-Alistipes, S-Collinsella, median cell count, average hemoglobin volume, Low-density lipoprotein), with the accuracy 97%, sensitivity 92%, and specificity 100%. Model 3 was based on the first ten features of Model 1, with the accuracy 97%, sensitivity 86%, and specificity 100%. Other models based on the demographic characteristics, hematological indicators, or intestinal flora abundance features presented lower sensitivity and specificity. Conclusion: The 15 features (including intestinal flora abundance) could establish an effective model for predicting rapid MCI progression.

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Section: Discussionmentioning

confidence: 99%

Predicting the Rapid Progression of Mild Cognitive Impairment by Intestinal Flora and Blood Indicators through Machine Learning Method

Wang,

Yan,

Liu

et al. 2023

Neurodegener Dis

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Role of uric acid in neurodegenerative diseases, focusing on Alzheimer and Parkinson disease: A new perspective

Alrouji,

Al‐kuraishy,

Al‐Gareeb

et al. 2024

Neuropsychopharm Rep

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Neurodegenerative diseases (NDs) such as Alzheimer disease (AD) and Parkinson disease (PD) are group of diseases affecting the central nervous system (CNS) characterized by progressive neurodegenerations and cognitive impairment. Findings from different studies highlighted the beneficial and detrimental effects of serum uric acid on the development and progression of NDs. Therefore, this mini‐review aims to discuss the beneficial and detrimental effects of uric on NDs. The neuroprotective effect of uric acid is mainly related to the antioxidant effect of uric acid which alleviates oxidative stress‐induced neurodegeneration in AD and PD. However, long‐term effect of hyperuricemia prompts for the development and progression of cognitive impairment. Hyperuricemia is associated with cognitive impairment and dementia, and gout increases dementia risk. In addition, hyperuricemia can cause cerebral vascular injury which is a risk factor for vascular dementia and cognitive impairment. Taken together, the relationship between uric acid and NDs risk remains conflicting. Hence, preclinical and clinical studies are indicated in this regard.

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Association of gout with brain reserve and vulnerability to neurodegenerative disease

et al. 2023

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Studies of neurodegenerative disease risk in gout are contradictory. Relationships with neuroimaging markers of brain structure, which may offer insights, are uncertain. Here we investigated associations between gout, brain structure, and neurodegenerative disease incidence. Gout patients had smaller global and regional brain volumes and markers of higher brain iron, using both observational and genetic approaches. Participants with gout also had higher incidence of all-cause dementia, Parkinson’s disease, and probable essential tremor. Risks were strongly time dependent, whereby associations with incident dementia were highest in the first 3 years after gout diagnosis. These findings suggest gout is causally related to several measures of brain structure. Lower brain reserve amongst gout patients may explain their higher vulnerability to multiple neurodegenerative diseases. Motor and cognitive impairments may affect gout patients, particularly in early years after diagnosis.

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The Association of Serum Uric Acid Level, Gout, and Alzheimer’s Disease: A Bidirectional Mendelian Randomization Study

Cited by 4 publications

References 70 publications

Predicting the Rapid Progression of Mild Cognitive Impairment by Intestinal Flora and Blood Indicators through Machine Learning Method

Predicting the Rapid Progression of Mild Cognitive Impairment by Intestinal Flora and Blood Indicators through Machine Learning Method

Role of uric acid in neurodegenerative diseases, focusing on Alzheimer and Parkinson disease: A new perspective

Association of gout with brain reserve and vulnerability to neurodegenerative disease

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