Association between depressive symptoms, metabolic risk factors, and cognitive function: cross-sectional results from a community study in Quebec, Canada

The effects of sensorial and mobility frailty on the overall and domain-specific cognition performance of Chinese community-dwelling older adults

This study aimed to investigate the different impacts of sensorial and mobility frailty on overall and domain-specific cognitive function. Further, the independent associations between other intricate capacity (IC) dimensions, including vitality and psychological dimensions, and overall and domain-specific cognitive function were investigated. A total of 429 participants (mean age, 72.91 ± 7.014 years; 57.30% female) underwent IC capacity assessment. Other covariates, such as demographics, health-related variables were also assessed. Overall or domain-specific cognitive impairment was used as a dependent variable in logistic regression analyses adjusted for demographic, health-related, and psychosocial confounders. After adjustment for demographic, health-related, and psychosocial confounders, individuals with sensorial frailty (odds ratio [OR] = 0.435; 95% confidence interval [CI] = 0.236-0.801; P = .008) had a significantly lower risk of mild cognitive impairment (MCI), marginally low delayed memory impairment (OR = 0.601, 95% CI = 0.347-1.040; P = .069), and language impairment (OR = 0.534, 95% CI = 0.305-0.936; OR = 0.318, P = .029; OR = 0.318,95% CI = 0.173-0.586; P < .001) by Boston naming and animal fluency tests than did those with both sensorial and mobility frailty or mobility frailty only. Depressive symptoms had a significant negative influence on executive function. Cardiovascular disease and non-skin malignancy were independent determinants of MCI, and diabetes mellitus was independently associated with processing speed, attention, and executive function. Sensorial and mobility frailty were independent risk factors for cognitive impairment. Mobility frailty had a greater negative influence on the overall cognitive function and memory and language function than did sensorial frailty. The reserve decline in the psychological dimension of IC and chronic diseases also had a significant adverse influence on overall and domain-specific cognition function.

Neurocognitive correlates of metabolic dysregulation in individuals with mood disorders: a systematic review and meta-analysis

Individuals with mood disorders are predisposed to metabolic dysfunction, while those with metabolic dysregulation such as diabetes and obesity experience more severe depressive symptoms. Both metabolic dysfunction and mood disorders are independently associated with cognitive deficits. Therefore, given their close association, this study aimed to explore the association between metabolic dysfunction in individuals with mood disorders in relation to cognitive outcomes. A comprehensive search comprised of these three domains was carried out; a random-effects meta-analysis pooling mean cognitive outcomes was conducted (PROSPERO ID: CRD42022295765). Sixty-three studies were included in this review; 26 were synthesized in a quantitative meta-analysis. Comorbid metabolic dysregulation was associated with significantly lower global cognition among individuals with mood disorders. These trends were significant within each mood disorder subgroup, including major depressive disorder, bipolar disorder, and self-report depression/depressive symptoms. Type 2 diabetes was associated with the lowest cognitive performance in individuals with mood disorders, followed by peripheral insulin resistance, body mass index ⩾25 kg/m2, and metabolic syndrome. Significant reduction in scores was also observed among individual cognitive domains (in descending order) of working memory, attention, executive function, processing speed, verbal memory, and visual memory. These findings demonstrate the detrimental effects of comorbid metabolic dysfunction in individuals with mood disorders. Further research is required to understand the underlying mechanisms connecting mood disorders, metabolism, and cognition.

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.

Factors leading to the trajectory of cognitive decline in middle-aged and older adults using group-based trajectory modeling: A cohort study

Currently, studies exploring factors associated with the cognition at some time point and no study identifying the trajectories of cognitive changes and factors might associate with the trajectories of cognitive changes in people. This study was to identify factors associated with the trend of cognitive decline in middle-aged and older people. In this cohort study, the data of 6954 subjects were collected from China Health and Retirement Longitudinal Survey database. Group-based trajectory modeling was applied for identifying three different trajectories of cognitive function change [high initial level and slow decline group (n = 1024), moderate initial level and moderate decline group (n = 2673) and low initial level and rapid decline (LRD) group (n = 3277)]. Univariate and multivariate logistic regression analysis was conducted to identify variables influencing factors of the trajectories of cognitive function in middle-aged and older people. The follow-up interval was 2 years from 2011 to 2015, and 3 years from 2015 to 2018 via face-to-face interview. High initial level and slow decline group versus LRD group, age (OR = 2.591, 95% CI: 1.962-3.421), gender (OR = 1.398, 95% CI: 1.133-1.725), education (OR = 0.051, 95% CI: 0.039-0.068), place of residence (OR = 2.768, 95% CI: 1.663-4.606), disabled (OR = 1.557, 95% CI: 1.189-2.039), family annual income (OR = 0.757, 95% CI: 0.618-0.929), sleep duration (OR = 1.266, 95% CI: 1.023-1.567), instrumental activity of daily living impairment (OR = 2.513, 95% CI: 1.947-3.245), community activities participation (OR = 0.611, 95% CI: 0.500-0.748), depression (OR = 1.471, 95% CI: 1.185-1.828), and systolic blood pressure (OR = 1.005, 95% CI: 1.001-1.009) were factors influencing the trajectories of cognitive function. Comparing moderate initial level and moderate decline group and LRD group, age (OR = 1.245, 95% CI: 1.052-1.474), gender (OR = 1.244, 95% CI: 1.062-1.458), education (OR = 0.244, 95% CI: 0.190-0.314), marital status (OR = 1.291, 95% CI: 1.079-1.546), place of residence (OR = 1.677, 95% CI: 1.358-2.071), disability (OR = 1.396, 95% CI: 1.180-1.652), smoking (OR = 1.249, 95% CI: 1.071-1.457), family annual income (OR = 0.863, 95% CI: 0.768-0.970), sleep duration (OR = 1.215, 95% CI: 0.973-1.541), instrumental activity of daily living impairment (OR = 1.309, 95% CI: 1.098-1.560), community activities participation (OR = 0.804, 95% CI: 0.718-0.900) and depression (OR = 1.383, 95% CI: 1.217-1.571) were factors associated with the trajectories of cognitive function changes. Middle-aged and older adults who had characteristics associated with increased risk of cognitive decline might be provided with timely interventions.

White matter hyperintensities in Burning Mouth Syndrome assessed according to the Age-Related White Matter Changes scale

Background

White matter hyperintensities (WMHs) of the brain are observed in normal aging, in various subtypes of dementia and in chronic pain, playing a crucial role in pain processing. The aim of the study has been to assess the WMHs in Burning Mouth Syndrome (BMS) patients by means of the Age-Related White Matter Changes scale (ARWMCs) and to analyze their predictors.

Methods

One hundred BMS patients were prospectively recruited and underwent magnetic resonance imaging (MRI) of the brain. Their ARWMCs scores were compared with those of an equal number of healthy subjects matched for age and sex. Intensity and quality of pain, psychological profile, and blood biomarkers of BMS patients were further investigated to find potential predictors of WMHs. Specifically, the Numeric Rating Scale (NRS), Short-Form McGill Pain Questionnaire (SF-MPQ), Hamilton rating scale for Depression and Anxiety (HAM-D and HAM-A), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS) were administered.

Results

The BMS patients presented statistically significant higher scores on the ARWMCs compared to the controls, especially in the right frontal, left frontal, right parietal-occipital, left parietal-occipital, right temporal and left temporal lobes (p-values: <0.001, <0.001, 0.005, 0.002, 0.009, 0.002, and <0.001, respectively). Age, a lower educational level, unemployment, essential hypertension, and hypercholesterolemia were correlated to a higher total score on the ARWMCs (p-values: <0.001, 0.016, 0.014, 0.001, and 0.039, respectively). No correlation was found with the blood biomarkers, NRS, SF-MPQ, HAM-A, HAM-D, PSQI, and ESS.

Conclusion

Patients with BMS showed a higher frequency of WMHs of the brain as suggested by the higher ARWCs scores compared with the normal aging of the healthy subjects. These findings could have a role in the pathophysiology of the disease and potentially affect and enhance pain perception.

Burning Fog: Cognitive Impairment in Burning Mouth Syndrome

Background: Due to its common association with chronic pain experience, cognitive impairment (CI) has never been evaluated in patients with burning mouth syndrome (BMS). The purpose of this study is to assess the prevalence of CI in patients with BMS and to evaluate its relationship with potential predictors such as pain, mood disorders, blood biomarkers, and white matter changes (WMCs).

Methods: A case-control study was conducted by enrolling 40 patients with BMS and an equal number of healthy controls matched for age, gender, and education. Neurocognitive assessment [Mini Mental State Examination (MMSE), Digit Cancellation Test (DCT), the Forward and Backward Digit Span task (FDS and BDS), Corsi Block-Tapping Test (CB-TT), Rey Auditory Verbal Learning Test (RAVLT), Copying Geometric Drawings (CGD), Frontal Assessment Battery (FAB), and Trail Making A and B (TMT-A and TMT-B)], psychological assessment [Hamilton Rating Scale for Depression and Anxiety (HAM-D and HAM-A), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and 36-Item Short Form Health Survey (SF-36)], and pain assessment [Visual Analogic Scale (VAS), Total Pain Rating index (T-PRI), Brief Pain Inventory (BPI), and Pain DETECT Questionnaire (PD-Q)] were performed. In addition, blood biomarkers and MRI of the brain were recorded for the detection of Age-Related WMCs (ARWMCs). Descriptive statistics, the Mann-Whitney U-test, the Pearson Chi-Squared test and Spearman's correlation analysis were used.

Results: Patients with BMS had impairments in most cognitive domains compared with controls (p < 0.001^**) except in RAVLT and CGD. The HAM-D, HAM-A, PSQI, ESS, SF-36, VAS, T-PRI, BPI and PD-Q scores were statistically different between BMS patients and controls (p < 0.001^**) the WMCs frequency and ARWMC scores in the right temporal (RT) and left temporal (LT) lobe were higher in patients with BMS (p = 0.023^*).

Conclusions: Meanwhile, BMS is associated with a higher decline in cognitive functions, particularly attention, working memory, and executive functions, but other functions such as praxis-constructive skills and verbal memory are preserved. The early identification of CI and associated factors may help clinicians to identify patients at risk of developing time-based neurodegenerative disorders, such as Alzheimer's disease (AD) and vascular dementia (VD), for planning the early, comprehensive, and multidisciplinary assessment and treatment.