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The oldest-old population, those aged ≥ 80 years, is the fastest-growing group in the United States (US), grappling with an increasingly heavy burden of dementia. We aimed to dissect the trends in dementia prevalence, mortality, and risk factors, and predict future levels among this demographic. Leveraging data from the Global Burden of Disease Study 2019, we examined the trends in dementia prevalence, mortality, and risk factors (with a particular focus on body mass index, BMI) for US oldest-old adults. Through decomposition analysis, we identified key population-level contributors to these trends. Predictive modeling was employed to estimate future prevalence and mortality levels over the next decade. Between 1990 and 2019, the number of dementia cases and deaths among the oldest-old in the US increased by approximately 1.37 million and 60,000 respectively. The population growth and aging were highlighted as the primary drivers of this increase. High BMI emerged as a growing risk factor. Females showed a disproportionately higher dementia burden, characterized by a unique risk factor profile, including BMI. Predictions for 2030 anticipate nearly 4 million dementia cases and 160,000 related deaths, with a marked increase in prevalence and mortality anticipated among those aged 80–89. The past 30 years have witnessed a notable rise in both the prevalence and mortality of dementia among the oldest-old in the US, accompanied by a significant shift in risk factors, with obesity taking a forefront position. Targeted age and sex-specific public health strategies that address obesity control are needed to mitigate the dementia burden effectively. [ABSTRACT FROM AUTHOR]

Alzheimer’s disease (AD) is a multifactorial neurodegenerative disease that lacks convenient and accessible peripheral blood diagnostic markers and effective drugs. Metabolic dysfunction is one of AD risk factors, which leaded to alterations of various metabolites in the body. Pathological changes of the brain can be reflected in blood metabolites that are expected to explain the disease mechanisms or be candidate biomarkers. The aim of this study was to investigate the changes of targeted metabolites within peripheral blood of AD mouse model, with the purpose of exploring the disease mechanism and potential biomarkers. Targeted metabolomics was used to quantify 256 metabolites in serum of triple transgenic AD (3 × Tg-AD) male mice. Compared with controls, 49 differential metabolites represented dysregulation in purine, pyrimidine, tryptophan, cysteine and methionine and glycerophospholipid metabolism. Among them, adenosine, serotonin, N-acetyl-5-hydroxytryptamine, and acetylcholine play a key role in regulating neural transmitter network. The alteration of S-adenosine-l-homocysteine, S-adenosine-l-methionine, and trimethylamine-N-oxide in AD mice serum can served as indicator of AD risk. The results revealed the changes of metabolites in serum, suggesting that metabolic dysregulation in periphery in AD mice may be related to the disturbances in neuroinhibition, the serotonergic system, sleep function, the cholinergic system, and the gut microbiota. This study provides novel insights into the dysregulation of several key metabolites and metabolic pathways in AD, presenting potential avenues for future research and the development of peripheral biomarkers. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is one of the common neurodevelopmental disorders in children. Its etiology and pathogenesis are poorly understood. Previous studies have suggested potential changes in the complement and coagulation pathways in individuals with ASD. In this study, using multiple reactions monitoring proteomic technology, 16 of the 33 proteins involved in this pathway were identified as differentially-expressed proteins in plasma between children with ASD and controls. Among them, CFHR3, C4BPB, C4BPA, CFH, C9, SERPIND1, C8A, F9, and F11 were found to be altered in the plasma of children with ASD for the first time. SERPIND1 expression was positively correlated with the CARS score. Using the machine learning method, we obtained a panel composed of 12 differentially-expressed proteins with diagnostic potential for ASD. We also reviewed the proteins changed in this pathway in the brain and blood of patients with ASD. The complement and coagulation pathways may be activated in the peripheral blood of children with ASD and play a key role in the pathogenesis of ASD. [ABSTRACT FROM AUTHOR]

Chronic arsenic poisoning is a global health problem that affects millions of people, and studies have found that long-term ingestion of arsenic-containing compounds can lead to lung damage, but the exact mechanism is unknown. In this study, Sprague–Dawley (SD) rats were used as the research object, and the proteomic analysis method based on sequential window acquisition of all theoretical fragment ions (SWATH) was used to detect the changes in the expression levels of related proteins in the lung tissue of arsenic-exposed rats, and to explore the mechanism of arsenic compound-induced lung injury. The results showed that arsenic exposure resulted in the abnormal expression of collagen type III and proteins involved in metabolic, immune, and cellular processes, leading to the dysfunction of important pathways associated with these proteins, resulting in lung injury. It suggested that the underlying mechanism of arsenic-induced lung injury may be related to oxidative stress, immune injury, cell junction, and collagen type III. This result provides a new research idea for revealing the mechanism of lung injury caused by arsenic exposure. [ABSTRACT FROM AUTHOR]

Existing data demonstrate a significant correlation between autism spectrum disorder (ASD) and the status of biologically essential and toxic trace elements. However, there is still a lack of data on the steady state of trace elements in ASD. We performed a case–control study to explore the association between the risk of ASD and 23 trace elements in plasma. The results showed that children with ASD had considerably decreased lithium (Li), manganese (Mn), selenium (Se), barium (Ba), mercury (Hg), and tin (Sn) levels when compared to their age- and sex-matched controls. Meanwhile, children with ASD had considerably increased plasma chromium (Cr) and vanadium (V) concentrations. We also divided each group into subgroups based on age and gender and created element-related networks for each subgroup. We detected significant element correlations within or between subgroups, as well as changes in correlations that included all elements examined. Finally, more element correlations were observed among males, which may open a new avenue for understanding the complicated process behind the sex ratio of children with ASD. Overall, our data revealed a novel relationship between elements and ASD, which may extend current understanding about ASD. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) has become one of the most common neurological developmental disorders in children. However, the study of ASD diagnostic markers faces significant challenges due to the existence of heterogeneity. In this study, genetic testing was performed on children who were clinically diagnosed with ASD. Children with ASD susceptibility genes and healthy controls were studied. The proteomics of plasma and peripheral blood mononuclear cells (PBMCs) as well as plasma metabolomics were carried out. The results showed that although there was genetic heterogeneity in children with ASD, the differentially expressed proteins (DEPs) in plasma, peripheral blood mononuclear cells, and differential metabolites in plasma could still effectively distinguish autistic children from controls. The mechanism associated with them focuses on several common and previously reported mechanisms of ASD. The biomarkers for ASD diagnosis could be found by taking differentially expressed proteins and differential metabolites into consideration. Integrating omics data, glycerophospholipid metabolism and N-glycan biosynthesis might play a critical role in the pathogenesis of ASD. [ABSTRACT FROM AUTHOR]