Neurodegenerative diseases and blood pressure variability: A comprehensive review from HOPE Asia

Bioinformatics-led identification of pathophysiological hallmark genes in diabesotension via graph clustering method

Background

Diabesotension, an overlapping triad of diabetes, hypertension, and obesity, remains a diagnostic challenge due to its complex underlying molecular mechanisms. Individuals with diabesotension face twice the risk of microvascular and macrovascular complications compared to those with either condition alone. However, the complexity of diabesotension poses significant diagnostic challenges due to limited knowledge of this disease trifecta.

Methods

The protein network was constructed, and the DPClusOST algorithm was applied to determine the protein clusters with a density ranging from 0.1 to 1.0 and those relevant to the pathophysiology of diabesotension. The significance score (SScore) was computed using the p-value from Fisher's exact test to evaluate each cluster, and the clusters containing proteins associated with diabesotension were classified using receiver operating characteristic (ROC) analysis. The significant density of the cluster, as indicated by the AUC, was determined and subsequently subjected to pathway enrichment analysis using ShinyGO.

Results

At densities of 0.6 and 0.8, 14 proteins (STX3, VAMP2, STX4, SYT1, DNAJC5, HSD17B10, DLD, AIFM1, PDHA1, PDHB, DLAT, PDHX, OGDH, and STAT5A) from clusters 13 and 53 were significantly identified as potential diabesotension-related proteins. Key pathways associated with the tripartite interplay of the three pathologies were found to involve amino acid metabolism, glycolysis/gluconeogenesis, SNARE-mediated vesicle transport, insulin and salivary secretion, and the glucagon and HIF-1 signaling pathways, thus identifying novel candidates for diabesotension biomarkers and therapeutic targets.

Conclusions

This study highlights the use of graph clustering to identify potential biomarkers for the comorbid triad, which could enhance personalized future treatment strategies.

The assessment of the relationship between anticholinergic burden and short-term blood pressure variability

BACKGROUND

This study aimed to investigate the relationship between short-term blood pressure variability (BPV) and anticholinergic burden (ACB) in adults with hypertension.

METHODS

This study included 238 hypertensive patients aged 50 and older who underwent ambulatory blood pressure monitoring. The medications used by the patients were recorded, and the ACB of each medication was calculated using the ACB Scale. The BPV was assessed based on 24-hour ambulatory blood pressure measurements using three methods: standard deviation (SD), coefficient of variation of the standard deviation (SD-CoV), and weighted standard deviation (wSD), with evaluations conducted for both day-time and night-time periods.

RESULTS

A total of 139 patients (58.40%) had no ACB score, 64 (26.89%) had an ACB score of 1, and 35 (14.71%) had an ACB score of 2 or higher. ACB scores were significantly higher among patients with heart disease, and ACB tended to increase with age. However, no statistically significant relationship was found between ACB and mean blood pressure, nocturnal blood pressure dips, or any parameters of short-term BPV including Sd, SD-CoV and wSD.

CONCLUSION

No significant association was found between ACB and short-term BPV. To the best of our knowledge, this is the first study to investigate this relationship, which may inspire further research.

Multiple system biology approaches reveals the role of the hsa-miR-21 in increasing risk of neurological disorders in patients suffering from hypertension

Hypertension is a prevalent disease that substantially elevates the risk of neurological disorders such as dementia, stroke and Parkinson's disease. MicroRNAs (miRNAs) play a critical role in the regulation of gene expression related to brain function and disorders. Understanding the involvement of miRNAs in these conditions could provide new insights into potential therapeutic targets. The main objective of this study is to target and investigate microRNAs (miRNAs) associated with neurological disorders in patients suffering from hypertension. The genes involved in hypertension were identified from various databases including GeneCard, MalaCard, DisGeNet, OMIM & GEO2R. The key gene for hypertension was identified using a systems biology approach. Also, potent phytochemical for hypertension was determined by computer-aided drug-designing approach. Functional miRNAs were determined for the key target gene using miRNet analytics platform by hypergeometric tests. Further, the gene-miRNA interaction was determined and enrichment analysis was done. RPS27A was identified as a key target gene for hypertension. Naringenin showed effective molecular interaction with RPS27A with a binding energy score (-6.28). Further, a list of miRNAs which were targeting brain disorders was determined from miRNet. A gene-miRNA network was constructed using the PSRR tool for Parkinson's Disease, Autism Spectrum Disorder, Acute Cerebral Infarction, ACTH-Secreting Pituitary Adenoma, & Ependymoma. Further, miRNA 21 & miRNA 16 were found to be associated with four of the neurological disorders. The study identifies specific miRNAs that may serve as potential biomarkers for brain disorders in hypertensive patients. Targeting these miRNAs could open new avenues for therapeutic strategies aimed at mitigating neurological damage in this patient population.

Life-threatening risk factors contribute to the development of diseases with the highest mortality through the induction of regulated necrotic cell death

Chronic diseases affecting the cardiovascular system, diabetes mellitus, neurodegenerative diseases, and various other organ-specific conditions, involve different underlying pathological processes. However, they share common risk factors that contribute to the development and progression of these diseases, including air pollution, hypertension, obesity, high cholesterol levels, smoking and alcoholism. In this review, we aim to explore the connection between four types of diseases with different etiologies and various risk factors. We highlight that the presence of risk factors induces regulated necrotic cell death, leading to the release of damage-associated molecular patterns (DAMPs), ultimately resulting in sterile inflammation. Therefore, DAMP-mediated inflammation may be the link explaining how risk factors can lead to the development and maintenance of chronic diseases. To explore these processes, we summarize the main cell death pathways activated by the most common life-threatening risk factors, the types of released DAMPs and how these events are associated with the pathophysiology of diseases with the highest mortality. Various risk factors, such as smoking, air pollution, alcoholism, hypertension, obesity, and high cholesterol levels induce regulated necrosis. Subsequently, the release of DAMPs leads to chronic inflammation, which increases the risk of many diseases, including those with the highest mortality rates.

Microbial signatures and therapeutic strategies in neurodegenerative diseases

Neurodegenerative diseases (NDs), including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS), arise from complex interactions between genetic factors, environmental exposures, and aging. Additionally, gut dysbiosis has been linked to systemic inflammation and neurodegeneration. Advances in microbiome and metabolome profiling techniques have provided deeper insights into how alterations in gut microbiota and dietary patterns affect metabolic pathways and contribute to the progression of NDs. This review explores the profiles of gut microbiome and metabolome derived biomarkers and their roles in NDs. Across phyla, families, and genera, we identified 55 microbial alterations in PD, 24 in AD, 4 in ALS, and 17 in MS. Some notable results include an increase in Akkermansia in PD, AD, and MS and a decrease in short-chain fatty acids (SCFAs) in PD and AD. We examined the effects of probiotics, prebiotics, fecal microbiota transplants (FMT), sleep, exercise, and diet on the microbiota, all of which contributed to delayed onset and alleviation of symptoms. Further, artificial intelligence (AI) and machine learning (ML) algorithms applied to omics data have been crucial in identifying novel therapeutic targets, diagnosing and predicting prognosis, and enabling personalized medicine using microbiota-modulating therapies in NDs patients.

Correlation between intradialytic blood pressure variability and cognitive impairment in patients on maintenance hemodialysis

BACKGROUND

The relationship between intradialytic blood pressure variability (BPV) and mild cognitive impairment (MCI) in maintenance hemodialysis (MHD) patients is currently unclear. Our present study aimed to illustrate the correlation between intra-dialysis BPV and CI in MHD patients.

METHODS

Intradialytic SBP within 3 months before cognitive assessment of the patients were collected as baseline data and averaged as final data. The intradialytic SBP was converted to the following 4 candidate short-term BPV indices: standard deviation (SD), coefficient of variation (CV), average real variability (ARV), RANGE. Overall cognitive function was assessed by the Montreal Cognitive Assessment (MoCA) scale.

RESULTS

The study finally enrolled 170 patients with 6662 dialysis records and 26,580 SBP measurements. The mean age of the patients was 57.99 years, the MCI prevalence was 78.24%. Intradialytic SBP ARV (average real variability) was notably higher in patients with MCI than in the non-MCI (NMCI) group (8.91 vs. 7.60, P = 0.042), but there was no statistical difference in the mean SBP and other BPV indices between the two groups. There was a non-linear relationship between SBP ARV and MCI, and the inflection point of SBP ARV was 7.52.

CONCLUSION

Our study found that high SBP ARV was closely associated with MCI, indicating that high SBP ARV may act as an indicator of MCI in MHD patients.

Beat-to-beat blood pressure variability, hippocampal atrophy, and memory impairment in older adults

Visit-to-visit blood pressure variability (BPV) predicts age-related hippocampal atrophy, neurodegeneration, and memory decline in older adults. Beat-to-beat BPV may represent a more reliable and efficient tool for prospective risk assessment, but it is unknown whether beat-to-beat BPV is similarly associated with hippocampal neurodegeneration, or with plasma markers of neuroaxonal/neuroglial injury. Independently living older adults without a history of dementia, stroke, or other major neurological disorders were recruited from the community (N = 104; age = 69.5 ± 6.7 (range 55-89); 63% female). Participants underwent continuous blood pressure monitoring, brain MRI, venipuncture, and cognitive testing over two visits. Hippocampal volumes, plasma neurofilament light, and glial fibrillary acidic protein levels were assessed. Beat-to-beat BPV was quantified as systolic blood pressure average real variability during 7-min of supine continuous blood pressure monitoring. The cross-sectional relationship between beat-to-beat BPV and hippocampal volumes, cognitive domain measures, and plasma biomarkers was assessed using multiple linear regression with adjustment for demographic covariates, vascular risk factors, and average systolic blood pressure. Elevated beat-to-beat BPV was associated with decreased left hippocampal volume (P = .008), increased plasma concentration of glial fibrillary acidic protein (P = .006), and decreased memory composite score (P = .02), independent of age, sex, average systolic blood pressure, total intracranial volume, and vascular risk factor burden. In summary, beat-to-beat BPV is independently associated with decreased left hippocampal volume, increased neuroglial injury, and worse memory ability. Findings are consistent with prior studies examining visit-to-visit BPV and suggest beat-to-beat BPV may be a useful marker of hemodynamic brain injury in older adults.

Risk factors for the neurodegenerative dementias in the Western Pacific region

The Western Pacific Region (WPR) is characterized by a group of socioeconomically, culturally, and geopolitically heterogenous countries and represents a microcosm of the global endemic of neurodegeneration. This review will chart the known risk factors for dementia across the WPR. We explore the intersection between the established risk factors for dementia including the biomedical and lifestyle (cardiovascular and metabolic disease, sleep, hearing loss, depression, alcohol, smoking, traumatic brain injury, genetics) and social determinants (social disadvantage, limited education, systemic racism) as well as incorporate neuroimaging data, where available, to predict disease progression in the WPR. In doing so, we highlight core risk factors for dementia in the WPR, as well as geographical epicentres at heightened risk for dementia, to orient future research towards addressing these disparities.

Investigating the Neuroprotective and Cognitive-Enhancing Effects of Bacopa monnieri: A Systematic Review Focused on Inflammation, Oxidative Stress, Mitochondrial Dysfunction, and Apoptosis

The aging of the global population has increased the prevalence of neurodegenerative conditions. Bacopa monnieri (BM), an herb with active compounds, such as bacosides A and B, betulinic acid, loliolide, asiatic acid, and quercetin, demonstrates the potential for brain health. Limited research has been conducted on the therapeutic applications of BM in neurodegenerative conditions. This systematic review aims to project BM's beneficial role in brain disorders. BM has anti-apoptotic and antioxidant actions and can repair damaged neurons, stimulate kinase activity, restore synaptic function, improve nerve transmission, and increase neuroprotection. The included twenty-two clinical trials demonstrated that BM can reduce Nuclear Factor-κB phosphorylation, improve emotional function, cognitive functions, anhedonia, hyperactivity, sleep routine, depression, attention deficit, learning problems, memory retention, impulsivity, and psychiatric problems. Moreover, BM can reduce the levels of pro-inflammatory biomarkers and oxidative stress. Here, we highlight that BM provides notable therapeutic benefits and can serve as a complementary approach for the care of patients with neurodegenerative conditions associated with brain disorders. This review adds to the growing interest in natural products and their potential therapeutic applications by improving our understanding of the mechanisms underlying cognitive function and neurodegeneration and informing the development of new therapeutic strategies for neurodegenerative diseases.

The Constrained-Disorder Principle Assists in Overcoming Significant Challenges in Digital Health: Moving from "Nice to Have" to Mandatory Systems

The success of artificial intelligence depends on whether it can penetrate the boundaries of evidence-based medicine, the lack of policies, and the resistance of medical professionals to its use. The failure of digital health to meet expectations requires rethinking some of the challenges faced. We discuss some of the most significant challenges faced by patients, physicians, payers, pharmaceutical companies, and health systems in the digital world. The goal of healthcare systems is to improve outcomes. Assisting in diagnosing, collecting data, and simplifying processes is a "nice to have" tool, but it is not essential. Many of these systems have yet to be shown to improve outcomes. Current outcome-based expectations and economic constraints make "nice to have," "assists," and "ease processes" insufficient. Complex biological systems are defined by their inherent disorder, bounded by dynamic boundaries, as described by the constrained disorder principle (CDP). It provides a platform for correcting systems' malfunctions by regulating their degree of variability. A CDP-based second-generation artificial intelligence system provides solutions to some challenges digital health faces. Therapeutic interventions are held to improve outcomes with these systems. In addition to improving clinically meaningful endpoints, CDP-based second-generation algorithms ensure patient and physician engagement and reduce the health system's costs.