The amount of attention to age-related hearing loss (ARHL) has been growing, not only from the perspective of being one of the most common health conditions affecting older adults, but also from the perspective of its relation to cognition. Results from a number of epidemiological and laboratory studies have demonstrated a significant link between ARHL and cognitive decline. The Lancet International Commission on Dementia, Prevention, Intervention, and Care has estimated that mid-life hearing loss, if eliminated, might decrease the risk of dementia by nine percent, since hearing loss is a modifiable age-associated condition linked to dementia. Despite numerous research efforts, elucidation of the underlying causal relationships between auditory and cognitive decline has not yet reached a consensus. In this review article, we focused on the hypotheses of etiological mechanisms between ARHL and cognitive decline: (1) cognitive load hypothesis; (2) common cause hypothesis; (3) cascade hypothesis; and (4) overdiagnosis or harbinger hypothesis. Factual evidence obtained in previous studies was assessed to understand the link between ARHL and cognitive decline or dementia. Additionally, an overview of the conceivable effects of hearing intervention, e.g., hearing aids and cochlear implants, on cognition were presented, and the role of hearing aid use was considered for the relevant hypotheses. We should continue to strive for social enlightenment towards the importance of 'hearing well', and cultivate a necessity for hearing screening among patients at risk of cognitive decline.
Dysregulation of the gut microbiome is associated with several life-threatening conditions and thus might represent a useful target for the prevention of dementia. However, the relationship between the gut microbial population and dementia has not yet been fully clarified. We recruited outpatients visiting our memory clinic to participate in this study. Information on patient demographics, risk factors, and activities of daily living was collected, and cognitive function was assessed using neuropsychological tests and brain magnetic resonance imaging scans. Faecal samples were obtained, and the gut microbiome was assessed by terminal restriction fragment length polymorphism (T-RFLP) analysis, one of the most well-established and reliable 16S ribosomal RNA-based methods for classifying gut microbiota. Patients were divided into two groups, demented and non-demented. Multivariable logistic regression models were used to identify the variables independently associated with dementia. The T-RFLP analysis revealed differences in the composition of the gut microbiome: the number of Bacteroides (enterotype I) was lower and the number of ‘other’ bacteria (enterotype III) was higher in demented than non-demented patients. Multivariable analyses showed that the populations of enterotype I and enterotype III bacteria were strongly associated with dementia, independent of the traditional dementia biomarkers. Further studies of the metabolites of gut microbes are needed to determine the mechanism underlying this association.
Recent studies have revealed an association between the dysregulation of the gut microbiome and dementia. However, whether this dysregulation is associated with mild cognitive impairment (MCI), an early stage of cognitive decline, in patients without dementia remains unclear. We performed a cross-sectional analysis to determine the association between the gut microbiome and MCI. Data, including patient demographics, risk factors, cognitive function, and brain imaging, were collected. The gut microbiome was assessed through terminal restriction fragment length polymorphism analysis. Multivariable logistic regression models were used to identify factors independently associated with MCI. Graphical modelling was used to illustrate mutual associations between MCI and identified factors. We analysed 82 patients, 61 of whom exhibited MCI. Patients with MCI had a higher prevalence of Bacteroides. Furthermore, patients with more Bacteroides were more likely to present with white matter hyperintensity and high voxel-based specific regional analysis system for Alzheimer’s Disease (VSRAD) scores, indicating cortical and hippocampal atrophy. A multivariable logistic regression analysis revealed that a greater prevalence of Bacteroides was independently associated with MCI. Graphical modelling also showed a close association between Bacteroides and MCI. In conclusion, an increased prevalence of Bacteroides is independently associated with the presence of MCI in patients without dementia.
Dysregulation of the gut microbiome is associated with dementia. However, the relationship between microbiome-associated metabolites and dementia has yet to be identified. Outpatients visiting a memory clinic in Japan enrolled in this cross-sectional study; 107 subjects were eligible for the study, 25 of which had dementia. We collected demographics, activities of daily living, risk factors, cognitive function, and brain imaging data. The gut microbiome was assessed using terminal restriction fragment length polymorphism analysis. Concentrations of faecal metabolite were measured. We used multivariable logistic regression analyses to identify whether metabolites were independently related to dementia. The concentrations of metabolites were significantly different between subjects with and those without dementia. Every 1 standard deviation increment in faecal ammonia concentration was associated with around a 1.6-fold risk for the presence of dementia. A higher faecal lactic acid concentration was related to a lower risk of dementia, by around 60%. A combination of higher faecal ammonia and lactic acid concentrations was indicative of the presence of dementia, and had a similar predictive value as traditional biomarkers of dementia. Thus, faecal ammonia and lactic acid are related to dementia, independently of the other risk factors for dementia and dysregulation of the gut microbiome.
We examined the nutritional status and its association with behavioral psychiatric symptoms of dementia (BPSD) among 741 memory clinic patients (normal cognition (NC), 152; mild cognitive impairment (MCI), 271; early-stage Alzheimer disease (AD), 318). Nutritional status and BPSD were assessed using the Mini Nutritional Assessment Short-Form (MNA-SF) and the Dementia Behavior Disturbance Scale (DBD), respectively. Compared to subjects with NC, more subjects with MCI and early-stage AD were at risk of malnutrition (MNA-SF, 8–11: NC, 34.2%; MCI, 47.5%; early-stage AD, 53.8%) and were malnourished (MNA-SF, 0–7: NC, 4.6%; MCI, 5.9%; early-stage AD, 8.2%). Among patients with MCI or early-stage AD, those at risk of/with malnutrition showed higher DBD scores than those well-nourished (12.7 ± 9.0 vs. 9.5 ± 7.3; p < 0.001). Moreover, analysis of covariance adjusting for confounders showed that nutritional status was significantly associated with specific BPSD, including “verbal aggressiveness/emotional disinhibition” (F = 5.87, p = 0.016) and “apathy/memory impairment” (F = 15.38, p < 0.001), which were revealed by factor analysis of DBD. Our results suggest that malnutrition is common among older adults with mild cognitive decline, and possibility that nutritional problems are associated with individual BPSD.