Associations of serum uric acid variability with neuroimaging metrics and cognitive decline: a population-based cohort study.

BACKGROUND: The relationship between variation in serum uric acid (SUA) levels and brain health is largely unknown. This study aimed to examine the associations of long-term variability in SUA levels with neuroimaging metrics and cognitive function. METHODS: This study recruited 1111 participants aged 25-83 years from a multicenter, community-based cohort study. The SUA concentrations were measured every two years from 2006 to 2018. We measured the intraindividual SUA variability, including the direction and magnitude of change by calculating the slope value. The associations of SUA variability with neuroimaging markers (brain macrostructural volume, microstructural integrity, white matter hyperintensity, and the presence of cerebral small vessel disease) and cognitive function were examined using generalized linear models. Mediation analyses were performed to assess whether neuroimaging markers mediate the relationship between SUA variation and cognitive function. RESULTS: Compared with the stable group, subjects with increased or decreased SUA levels were all featured by smaller brain white matter volume (beta = - 0.25, 95% confidence interval [CI] - 0.39 to - 0.11 and beta = - 0.15, 95% CI - 0.29 to - 0.02). Participants with progressively increased SUA exhibited widespread disrupted microstructural integrity, featured by lower global fractional anisotropy (beta = - 0.24, 95% CI - 0.38 to - 0.10), higher mean diffusivity (beta = 0.16, 95% CI 0.04 to 0.28) and radial diffusivity (beta = 0.19, 95% CI 0.06 to 0.31). Elevated SUA was also associated with cognitive decline (beta = - 0.18, 95% CI - 0.32 to - 0.04). White matter atrophy and impaired brain microstructural integrity mediated the impact of SUA increase on cognitive decline. CONCLUSIONS: It is the magnitude of SUA variation rather than the direction that plays a critical negative role in brain health, especially for participants with hyperuricemia. Smaller brain white matter volume and impaired microstructural integrity mediate the relationship between increased SUA level and cognitive function decline. Long-term stability of SUA level is recommended for maintaining brain health and preventing cognitive decline.

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation.

BACKGROUND: The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impairment (CI) recognition. METHODS: We included 908 participants from a community-based cohort followed for over 15 years (the prospective KaiLuan Study) who underwent brain magnetic resonance imaging (MRI) and fundus photography between 2021 and 2022. The cohort consisted of both cognitively healthy individuals (N = 417) and those with cognitive impairment (N = 491). We employed the NFN+ deep learning framework for retinal vessel segmentation and measurement. Associations between Retinal microvascular parameters (RMPs: central retinal arteriolar / venular equivalents, arteriole to venular ratio, fractal dimension) and CI were assessed by Pearson correlation. P < 0.05 was considered statistically significant. The correlation between the CI and RMPs were explored, then the correlation coefficients between CI and RMPs were analyzed. Random Forest nonlinear classification model was used to predict whether one having cognitive decline or not. The assessment criterion was the AUC value derived from the working characteristic curve. RESULTS: The fractal dimension (FD) and global vein width were significantly correlated with the CI (P < 0.05). Age (0.193), BMI (0.154), global vein width (0.106), retinal vessel FD (0.099), and CRAE (0.098) were the variables in this model that were ranked in order of feature importance. The AUC values of the model were 0.799. CONCLUSIONS: Establishment of a predictive model based on the extraction of vascular features from fundus images has a high recognizability and predictive power for cognitive function and can be used as a screening method for CI.

Gray matter volume mediates the association of long-term blood pressure variability with cognitive function in an adult population.

INTRODUCTION: We delineated the associations among long-term blood pressure variability (BPV), brain structure, and cognitive function. METHODS: We included 1254 adult participants from the Kailuan study. BPV was calculated from 2006 to 2020. Brain magnetic resonance imaging (MRI) and Montreal Cognitive Assessment (MoCA) were conducted in 2020. RESULTS: Higher systolic BPV (SBPV) and diastolic BPV (DBPV) were associated with lower total and frontal gray matter (GM) volume, and higher SBPV was associated with lower temporal GM volume. Elevated DBPV was associated with lower volume of total brain and parietal GM, and higher white matter hyperintensity (WMH) volume. Higher SBPV and DBPV were associated with lower MoCA scores. Decreased total and regional GM volume and increased WMH volume were associated with lower MoCA scores. The association between SBPV and cognitive function was mediated by total, frontal, and temporal GM volume. DISCUSSION: GM volume may play key roles in the association between SBPV and cognitive function. HIGHLIGHTS: SBPV and DBPV were negatively associated with total and regional brain volume. SBPV and DBPV were negatively associated with cognitive function. Decreased brain volume was associated with cognitive decline. GM volume mediated the negative association between SBPV and cognitive function.

Association between Body Mass Index and Brain Health in Adults: A 16-Year Population-Based Cohort and Mendelian Randomization Study.

Background: The cumulative effect of body mass index (BMI) on brain health remains ill-defined. The effects of overweight on brain health across different age groups need clarification. We analyzed the effect of cumulative BMI on neuroimaging features of brain health in adults of different ages. Methods: This study was based on a multicenter, community-based cohort study. We modeled the trajectories of BMI over 16 years to evaluate cumulative exposure. Multimodality neuroimaging data were collected once for volumetric measurements of the brain macrostructure, white matter hyperintensity (WMH), and brain microstructure. We used a generalized linear model to evaluate the association between cumulative BMI and neuroimaging features. Two-sample Mendelian randomization analysis was performed using summary level of BMI genetic data from 681,275 individuals and neuroimaging genetic data from 33,224 individuals to analyze the causal relationships. Results: Clinical and neuroimaging data were obtained from 1,074 adults (25 to 83 years). For adults aged under 45 years, brain volume differences in participants with a cumulative BMI of >26.2 kg/m2 corresponded to 12.0 years [95% confidence interval (CI), 3.0 to 20.0] of brain aging. Differences in WMH were statistically substantial for participants aged over 60 years, with a 6.0-ml (95% CI, 1.5 to 10.5) larger volume. Genetic analysis indicated causal relationships between high BMI and smaller gray matter and higher fractional anisotropy in projection fibers. Conclusion: High cumulative BMI is associated with smaller brain volume, larger volume of white matter lesions, and abnormal microstructural integrity. Adults younger than 45 years are suggested to maintain their BMI below 26.2 kg/m2 for better brain health. Trial Registration: This study was registered on clinicaltrials.gov (Clinical Indicators and Brain Image Data: A Cohort Study Based on Kailuan Cohort; No. NCT05453877; https://clinicaltrials.gov/ct2/show/NCT05453877).

The association of global vessel width with cognitive decline and cerebral small vessel disease burden in the KaiLuan study.

Background: As the retinal microvasculature shares similarities with the cerebral microvasculature, numerous studies have shown that retinal vascular is associated with cognitive decline. In addition, several population-based studies have confirmed the association between retinal vascular and cerebral small vessel disease (CSVD) burden. However, the association of retinal vascular with CSVD burden as well as cognitive function has not been explored simultaneously. This study investigated the relations of retinal microvascular parameters (RMPs) with CSVD burden and cognitive function. Methods: We conducted a cross-sectional study of participants in the KaiLuan study. Data were collected from subjects aged ≥18 years old who could complete retinal photography and brain magnetic resonance imaging (MRI) between December 2020 to October 2021 in the Kailuan community of Tangshan. RMPs were evaluated using a deep learning system. The cognitive function was measured using the Montreal Cognitive Assessment (MoCA). We conducted logistic regression models, and mediation analysis to evaluate the associations of RMPs with CSVD burden and cognitive decline. Results: Of the 905 subjects (mean age: 55.42±12.02 years, 54.5% female), 488 (53.9%) were classified with cognitive decline. The fractal dimension (FD) [odds ratio (OR), 0.098, 95% confidence interval (CI): 0.015-0.639, P=0.015] and global vein width (OR: 1.010, 95% CI: 1.005-1.015, P<0.001) were independent risk factors for cognitive decline after adjustment for potential confounding factors. The global artery width was significantly associated with severe CSVD burden (OR: 0.985, 95% CI: 0.974-0.997, P=0.013). The global vein width was sightly associated with severe CSVD burden (OR: 1.005, 95% CI: 1.000-1.010, P=0.050) after adjusting for potential confounders. The multivariable-adjusted odds ratios (95% CI) in highest tertile versus lowest tertile of global vein width were 1.290 (0.901-1.847) for cognitive decline and 1.546 (1.004-2.290) for severe CSVD burden, respectively. Moreover, CSVD burden played a partial mediating role in the association between global vein width and cognitive function (mediating effect 6.59%). Conclusions: RMPs are associated with cognitive decline and the development of CSVD. A proportion of the association between global vein width and cognitive decline may be attributed to the presence of CSVD burden.

Hippocampal volume mediates the association of arterial stiffness with cognitive impairment in adult population.

OBJECTIVES: To investigate the association of arterial stiffness with brain perfusion, brain tissue volume and cognitive impairment in the general adult population. MATERIALS AND METHODS: This prospective study included 1488 adult participants (age range: 22.8-83.9 years) from the Kailuan study. All participants underwent brachial-ankle pulse wave velocity (PWV) measurement, brain MRI, and Montreal Cognitive Assessment (MoCA). The association of PWV with cerebral blood flow (CBF), brain tissue volume and MoCA score was investigated. Mediation analysis was used to determine whether CBF and brain tissue volume changes mediated the associations between PWV and MoCA score. RESULTS: A 1 standard deviation (SD) increase in PWV was associated with lower total brain CBF [ ß (95% CI) -0.67 (-1.2 to -0.14)], total gray matter CBF [ß (95% CI) -0.7 [-1.27 to -0.13)], frontal lobe CBF [ ß (95% CI) -0.59 (-1.17 to -0.01)], parietal lobe CBF [ ß (95% CI) -0.8 (-1.43 to -0.18)], and temporal lobe CBF [ ß (95% CI) -0.68 (-1.24 to -0.12)]. Negative associations were found for PWV and total brain volume [ ß (95% CI) -4.8 (-7.61 to -1.99)] and hippocampus volume [ ß (95% CI) -0.08 (-0.13 to -0.04)]. A 1 SD increase PWV was significantly associated with elevated odds of developing cognitive impairment [odds ratio (95% CI) 1.21 (1.01-1.45)]. Mediation analysis showed that hippocampal volume partially mediated the negative association between PWV and MoCA scores (proportion: 14.173%). CONCLUSION: High arterial stiffness was associated with decreased total and regional CBF, brain tissue volume, and cognitive impairment. Hippocampal volume partially mediated the effects of arterial stiffness on cognitive impairment.