Gender-specific relationship between thigh muscle and fat mass and brain amyloid-β positivity

Effects and mechanisms of APP and its cleavage product Aβ in the comorbidity of sarcopenia and Alzheimer's disease

Sarcopenia and AD are both classic degenerative diseases, and there is growing epidemiological evidence of their comorbidity with aging; however, the mechanisms underlying the biology of their commonality have not yet been thoroughly investigated. APP is a membrane protein that is expressed in tissues and is expressed not only in the nervous system but also in the NMJ and muscle. Deposition of its proteolytic cleavage product, Aβ, has been described as a central component of AD pathogenesis. Recent studies have shown that excessive accumulation and aberrant expression of APP in muscle lead to pathological muscle lesions, but the pathogenic mechanism by which APP and its proteolytic cleavage products act in skeletal muscle is less well understood. By summarizing and analyzing the literature concerning the role, pathogenicity and pathological mechanisms of APP and its cleavage products in the nervous system and muscles, we aimed to explore the intrinsic pathological mechanisms of myocerebral comorbidities and to provide new perspectives and theoretical foundations for the prevention and treatment of AD and sarcopenia comorbidities.

Sarcopenia is a predictor for Alzheimer's continuum and related clinical outcomes

Low body mass index is closely related to a high risk of Alzheimer's disease (AD) and related biomarkers including amyloid-β (Aβ) deposition. However, the association between sarcopenia and Aβ-confirmed AD remains controversial. Therefore, we investigated the relationship between sarcopenia and the AD continuum. We explored sarcopenia's association with clinical implications of participants on the AD continuum. We prospectively enrolled 142 participants on the AD continuum (19 with preclinical AD, 96 with mild cognitive impairment due to AD, and 28 with AD dementia) and 58 Aβ-negative cognitively unimpaired participants. Sarcopenia, assessed using dual-energy X-ray absorptiometry and hand grip measurements, was considered a predictor. AD continuum, defined by Aβ deposition on positron emission tomography served as an outcome. Clinical severity in participants on the AD continuum assessed using hippocampal volume, Mini-Mental State Examination (MMSE), Seoul Verbal Learning Test (SVLT), and Clinical Dementia Rating Scale Sum of Boxes Scores (CDR-SOB) were also considered an outcome. Sarcopenia (odds ratio = 4.99, p = 0.004) was associated independently with the AD continuum after controlling for potential confounders. Moreover, sarcopenia was associated with poor downstream imaging markers (decreased hippocampal volume, β = - 0.206, p = 0.020) and clinical outcomes (low MMSE, β = - 1.364, p = 0.025; low SVLT, β = - 1.077, p = 0.025; and high CDR-SOB scores, β = 0.783, p = 0.022) in participants on the AD continuum. Sarcopenia was associated with the AD continuum and poor clinical outcome in individuals with AD continuum. Therefore, our results provide evidence for future studies to confirm whether proper management of sarcopenia can effective strategies are required for sarcopenia management to prevent the AD continuum and its clinical implications.

Different associations between body mass index and Alzheimer's markers depending on metabolic health

BACKGROUND

Increasing evidence supports the association between body mass index (BMI), Alzheimer's disease, and vascular markers. Recently, metabolically unhealthy conditions have been reported to affect the expression of these markers. We aimed to investigate the effects of BMI status on Alzheimer's and vascular markers in relation to metabolic health status.

METHODS

We recruited 1,736 Asians without dementia (71.6 ± 8.0 years). Participants were categorized into underweight, normal weight, or obese groups based on their BMI. Each group was further divided into metabolically healthy (MH) and unhealthy (MU) groups based on the International Diabetes Foundation definition of metabolic syndrome. The main outcome was Aβ positivity, defined as a Centiloid value of 20.0 or above and the presence of vascular markers, defined as severe white matter hyperintensities (WMH). Logistic regression analyses were performed for Aβ positivity and severe WMH with BMI status or interaction terms between BMI and metabolic health status as predictors. Mediation analyses were performed with hippocampal volume (HV) and baseline Mini-Mental State Examination (MMSE) scores as the outcomes, and linear mixed models were performed for longitudinal change in MMSE scores.

RESULTS

Being underweight increased the risk of Aβ positivity (odds ratio [OR] = 2.37, 95% confidence interval [CI] 1.13-4.98), whereas obesity decreased Aβ positivity risk (OR = 0.63, 95% CI 0.50-0.80). Especially, obesity decreased the risk of Aβ positivity (OR = 0.38, 95% CI 0.26-0.56) in the MH group, but not in the MU group. Obesity increased the risk of severe WMH (OR = 1.69, 1.16-2.47). Decreased Aβ positivity mediate the relationship between obesity and higher HV and MMSE scores, particularly in the MH group. Obesity demonstrated a slower decline in MMSE (β = 1.423, p = 0.037) compared to being normal weight, especially in the MH group.

CONCLUSIONS

Our findings provide new evidence that metabolic health has a significant effect on the relationship between obesity and Alzheimer's markers, which, in turn, lead to better clinical outcomes.

Development of a prediction model for cognitive impairment of sarcopenia using multimodal neuroimaging in non-demented older adults

INTRODUCTION

Despite prior research on the association between sarcopenia and cognitive impairment in the elderly, a comprehensive model that integrates various brain pathologies is still lacking.

METHODS

We used data from 528 non-demented older adults with or without sarcopenia in the Catholic Aging Brain Imaging (CABI) database, containing magnetic resonance imaging scans, positron emission tomography scans, and clinical data. We also measured three key components of sarcopenia: skeletal muscle index (SMI), hand grip strength (HGS), and the five times sit-to-stand test (5STS).

RESULTS

All components of sarcopenia were significantly correlated with global cognitive function, but cortical thickness and amyloid-beta (Aβ) retention had distinctive relationships with each measure. In the path model, brain atrophy resulting in cognitive impairment was mediated by Aβ retention for SMI and periventricular white matter hyperintensity for HGS, but directly affected by the 5STS.

DISCUSSION

Treatments targeting each sub-domain of sarcopenia should be considered to prevent cognitive decline.

HIGHLIGHTS

We identified distinct impacts of three sarcopenia measures on brain structure and Aβ. Muscle mass is mainly associated with Aβ and has an influence on the brain atrophy. Muscle strength linked with periventricular WMH and brain atrophy. Muscle function associated with cortical thinning in specific brain regions. Interventions on sarcopenia may be important to ease cognitive decline in the elderly.

Reduced skeletal muscle mass to visceral fat area ratio is independently associated with reduced cognitive function in type 2 diabetes mellitus

AIM

Skeletal muscle mass to visceral fat area ratio (SVR) has been recognised as an index of sarcopenic obesity. SVR is associated with type 2 diabetes mellitus (T2DM), metabolic syndrome and arterial stiffness which are known risk factors for cognitive dysfunction. We aimed to investigate association between SVR and cognitive function in patients with T2DM.

METHODS

This was a cross-sectional study of 1326 patients with T2DM and mean age 61.3 ± 8.0 years. SVR was assessed based on bioelectrical impedance measurements of muscle mass and visceral fat area (VFA). Cognitive function was assessed using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Linear regression was used to examine the association between SVR in quartiles and RBANS score, adjusting for demographics, education, presence of depressive symptoms, clinical covariates and medications.

RESULTS

The lower SVR quartiles were negatively associated with RBANS total score in the unadjusted analysis. The corresponding coefficients for Quartiles 1 and 2 SVR were -3.79 (95 % CI -5.39 to -2.19; p < 0.001) and -1.47 (95 % CI -2.86 to -0.07; p = 0.039) in fully adjusted analysis. The negative association between Quartile 1 SVR and RBANS score was evident in immediate memory, delayed memory, visuo-spatial construction, language and attention domains. Muscle mass and VFA alone had weaker associations with RBANS scores.

CONCLUSION

Our study demonstrated, for the first time, an independent association between reduced SVR and lower cognitive function. This is evident in global and multiple cognitive domains. The synergistic effects of reduced muscle mass and visceral obesity may be more pronounced than their independent effects on cognitive function.

The QPLEX™ Plus Assay Kit for the Early Clinical Diagnosis of Alzheimer's Disease

We recently developed a multiplex diagnostic kit, QPLEX™ Alz plus assay kit, which captures amyloid-β1-40, galectin-3 binding protein, angiotensin-converting enzyme, and periostin simultaneously using microliters of peripheral blood and utilizes an optimized algorithm for screening Alzheimer's disease (AD) by correlating with cerebral amyloid deposition. Owing to the demand for early AD detection, we investigate the potential of our kit for the early clinical diagnosis of AD. A total of 1395 participants were recruited, and their blood samples were analyzed with the QPLEX™ kit. The average of QPLEX™ algorithm values in each group increased gradually in the order of the clinical progression continuum of AD: cognitively normal (0.382 ± 0.150), subjective cognitive decline (0.452 ± 0.130), mild cognitive impairment (0.484 ± 0.129), and AD (0.513 ± 0.136). The algorithm values between each group showed statistically significant differences among groups divided by Mini-Mental State Examination and Clinical Dementia Rating. The QPLEX™ algorithm values could be used to distinguish the clinical continuum of AD or cognitive function. Because blood-based diagnosis is more accessible, convenient, and cost- and time-effective than cerebral spinal fluid or positron emission tomography imaging-based diagnosis, the QPLEX™ kit can potentially be used for health checkups and the early clinical diagnosis of AD.

Prevalence and Mechanisms of Skeletal Muscle Atrophy in Metabolic Conditions

Skeletal muscle atrophy is prevalent in a myriad of pathological conditions, such as diabetes, denervation, long-term immobility, malnutrition, sarcopenia, obesity, Alzheimer's disease, and cachexia. This is a critically important topic that has significance in the health of the current society, particularly older adults. The most damaging effect of muscle atrophy is the decreased quality of life from functional disability, increased risk of fractures, decreased basal metabolic rate, and reduced bone mineral density. Most skeletal muscle in humans contains slow oxidative, fast oxidative, and fast glycolytic muscle fiber types. Depending on the pathological condition, either oxidative or glycolytic muscle type may be affected to a greater extent. This review article discusses the prevalence of skeletal muscle atrophy and several mechanisms, with an emphasis on high-fat, high-sugar diet patterns, obesity, and diabetes, but including other conditions such as sarcopenia, Alzheimer's disease, cancer cachexia, and heart failure.