Background: Age-related cognitive decline (ARCD) is a common condition among older adults, affecting 100 million people worldwide. Traditional Chinese Medicine’s (TCM) constitution is closely related to the occurrence and development of diseases in the elderly population. However, little is known about the relationships between TCM constitution and ARCD in the super-aged population. The present study aimed to investigate the relationships between the TCM constitution and ARCD in Chinese centenarians and to explore the application of the constitution to prevent ARCD in the elderly population.Methods: Each participant underwent a standardized epidemiological investigation and physical examination, based on the China Hainan Centenarian Cohort Study. Data on the demographic characteristics and TCM constitution were collected using structured questionnaires.Results: The present study included 636 centenarians aged 100–116 years. The prevalence of ARCD was 87.7% (n = 558 centenarians). In multiple linear regression analysis, an inverse relationship between Qi depression and Mini-Mental State Examination scales was significant after controlling for a wide range of other factors (P < 0.05). In multiple logistic regression analysis, Qi depression was positively associated with ARCD after full adjustment (P < 0.05).Conclusion: As the first study in the world, the present study provides strong epidemiological evidence that Qi depression has a significant relationship with ARCD in Chinese centenarians, and regulating Qi depression may be a valuable method to prevent and treat ARCD in the elderly population.

Objective: The number of older people is estimated to increase from 524 million in 2010 to 1.5 billion in 2050. The factors and models of human longevity and successful aging are questions that have intrigued individuals for thousands of years. For the first time, the current study was designed to investigate the relationships between sex hormones, bone turnover, abdominal obesity, nutritional status and centenarian longevity in the oldest females. Methods: The China Hainan Centenarian Cohort Study was performed in 18 cities and counties of Hainan Province using standard methodology in 500 centenarian females and 237 oldest females aged between 80 and 99 years. Results: Centenarians were inversely associated with the geriatric nutritional risk index [Exp(B) (95% CI): 0.901 (0.883–0.919)] and abdominal obesity [Exp(B) (95% CI): 0.719 (0.520–0.996)] and positively associated with prolactin [Exp(B) (95% CI): 1.073 (1.044–1.103)], progesterone [Exp(B) (95% CI): 44.182 (22.036–88.584)], estradiol [Exp(B) (95% CI): 1.094 (1.071–1.119)], osteocalcin [Exp(B) (95% CI): 1.041 (1.028–1.054)], β-crossLaps [Exp(B) (95% CI): 63.141 (24.482–162.848)] and parathyroid [Exp(B) (95% CI): 1.022 (1.013–1.031)] hormone levels (P < 0.05 for all). The geriatric nutritional risk index and abdominal obesity were inversely associated with luteinizing hormone [β coefficient (95% CI): − 0.001 (− 0.002 to 0.001)]; Exp(B) (95% CI): 0.985 (0.974–0.996)], follicle-stimulating hormone [β coefficient (95% CI): 0.000 (− 0.001 to 0.000)]; Exp(B) (95% CI): 0.990 (0.985–0.996)], osteocalcin [β coefficient (95% CI): − 0.001 (− 0.001 to 0.000)]; Exp(B) (95% CI): 0.987(0.977–0.997)] and β-crossLaps [β coefficient (95% CI): − 0.100 (− 0.130 to 0.071)]; Exp(B) (95% CI): 0.338 (0.166–0.689)] levels (P < 0.05 for all). Conclusions: Centenarian longevity had inverse relationships with nutritional status and abdominal obesity and positive relationships with sex hormones and bone turnover. Nutritional status and abdominal obesity had inverse relationships with sex hormones and bone turnover. Increased sex hormones and bone turnover may be representative of centenarian longevity. Optimizing nutritional status and avoiding abdominal obesity may increase sex hormones and bone turnover and promote centenarian longevity and successful aging.

Background: Depression is considered to be an immune-related disease; however, previous studies have focused on inflammatory factors, and there is no conclusive conclusion on the relationships between immunoglobulins and depression. Therefore, the objective of this cross-sectional study was to evaluate the associations between immunoglobulins and depressive symptoms in Chinese older adults. Results: The China Hainan Centenarian Cohort Study (CHCCS) provides a significant population-based sample of older adults in Hainan, China. A total of 1547 older adults were included in this study. A baseline survey was conducted using a structured questionnaire. Blood samples were obtained following standard procedures. The Geriatric Depression Scale (GDS-15) was used to evaluate depressive symptoms of the participants. This sample of older adults had a median age of 94.75 (range: 80–116) years, and the proportion of women was 72.07%. The prevalence of older adults with depressive symptoms was 20.36% (315 older adults). After adjusting for all covariates, we found that immunoglobulin A levels were positively associated with depression. The adjusted reliability of the association between immunoglobulin A and depression was 0.106 (beta) and 1.083 (odds ratio) (P < 0.05 for both). Conclusions: The present study provides epidemiological evidence that depression has significant associations with immunoglobulin A levels in older adults. Further research should be conducted on the effects of regulating immunoglobulin A to improve depressive symptoms.

Objective: Age-related hearing loss (ARHL) and age-related cognitive decline (ARCD) are leading causes of disability in older adults. ARHL may increase ARCD risk and cause depression development. This study aimed to explore the associations of ARHL with ARCD and depression in Chinese centenarians and oldest-old adults. Methods: A household survey was conducted on 859 centenarians and oldest-old adults residing in 16 cities and counties in China. Basic information was collected using interview questionnaires, physical examinations, and blood tests conducted by systematically trained local doctors and nurses. Results: In total, 501 (58.3%), 649 (75.6%), and 211 (24.6%) participants had ARHL, ARCD, and depression, respectively. The prevalence of ARCD and depression was significantly higher in participants with ARHL than in those without ARHL (all p < 0.05). Participants with ARHL had significantly lower Mini-Mental State Examination (MMSE) scores indicative of more cognitive decline, and significantly higher 15-item version of the Geriatric Depression Scale (GDS-15) scores suggesting greater levels of depression, than those without ARHL (all p < 0.05). Multivariate logistic regression analyses (Stepwise) indicated that ARHL was significantly and positively associated with ARCD [odds ratio (OR): 1.594, 95% confidence interval (CI): 1.132, 2.245] and depression (OR: 1.623, 95% CI: 1.139, 2.314; all p < 0.05). Multivariate linear regression analyses (Stepwise) indicated that ARHL was significantly and inversely associated with MMSE scores ( B: −2.520, 95% CI: −3.356, −1.684) and significantly and positively associated with GDS-15 scores ( B: 0.713, 95% CI: 0.328, 1.098; all p < 0.05). Conclusion: ARHL is independently associated with ARCD and depression in Chinese centenarians and oldest-old adults.

Background: Physical independence is crucial for overall health in the elderly individuals. The life expectancy of women has been shown to be higher than that of men, which is also known as the “male–female health-survival paradox”. Sex hormones may be one of the explanations. However, the relationships between sex hormones and physical function remain unclear in the elderly females. This study was designed to explore these relationships among the Chinese oldest-old and centenarian women. Methods: Data from 1226 women were obtained from the China Hainan Centenarian Cohort Study. Home interviews, physical examinations and blood analyses were conducted using standardized procedures. Variables including age, Han ethnicity, illiteracy, smoker, drinker, estradiol (E2), testosterone (T), follicle-stimulating hormone, and luteinizing hormone were used in the multivariate logistic and linear regression analyses. Results: In all the participants, age [beta (95% confidence interval): − 0.84 (− 0.98, − 0.71)] and E2 levels [beta (95% confidence interval): − 0.22 (− 0.28, − 0.17)] were negatively associated with activities of daily living (ADLs) in the multivariate linear regression analyses (P < 0.05 for all). We also observed significantly negative associations of age [odds ratio (95% confidence interval): 0.90 (0.88, 0.91)] and E2 levels [odds ratio (95% confidence interval): 0.98 (0.98, 0.99)] with physical normality in the multivariate logistic regression analyses (P < 0.05 for all). Age and E2 levels gradually decreased with increases in the ADL quartiles across all the participants (P < 0.05 for all). Conclusions: This study demonstrated that E2 levels were negatively associated with physical function among the Chinese oldest-old and centenarian women.

Glioblastoma multiforme (GBM) is the most aggressive primary brain cancer (with a median survival time of 14.5 months), characterized by heterogeneity. Identifying prognostic molecular subtypes could provide a deeper exposition of GBM biology with potential therapeutic implications. In this study, we classified GBM into two prognostic subtypes, C1-GBM (n = 57; OS: 313 days) and C2-GBM (n = 109; OS: 452 days), using pathway-based signatures derived from RNA-seq data. Unsupervised consensus clustering revealed that only binary classification (cluster number, CN = 2; mean cluster consensus score = 0.84) demonstrated statistically prognostic differences. We characterized C1 and C2 based on oncogenic pathway and immune signatures. Specifically, C1-GBM was categorized as an immune-infiltrated “hot” tumor, with high infiltration of immune cells, particularly macrophages and CD4⁺ T cells, while C2-GBM as an “inherent driving” subtype, showing elevated activity in G2/M checkpoint genes. To predict the C1 or C2 classification and explore therapeutic interventions, we developed a neural network model. By using Weighted Correlation Network Analysis (WGCNA), we obtained the gene co-expression module based on both gene expression pattern and distribution among patients in TCGA dataset (n = 166) and identified nine hub genes as potentially prognostic biomarkers for the neural network. The model showed strong accuracy in predicting C1/C2 classification and prognosis, validated by the external CGGA-GBM dataset (n = 85). Based on the classification of the BP neural network model, we constructed a Cox nomogram prognostic prediction model for the TCGA-GBM dataset. We predicted potential therapeutic small molecular drugs by targeting subtype-specific oncogenic pathways and validated drug sensitivity (C1-GBM: Methotrexate and Cisplatin; C2-GBM: Cytarabine) by assessing IC₅₀ values against GBM cell lines (divided into C1/C2 subtypes based on the nine hub genes) from the Genomics of Drug Sensitivity in Cancer database. This study introduces a pathway-based prognostic molecular classification of GBM with “hot” (C1-GBM) and “inherent driving” (C2-GBM) tumor subtypes, providing a prediction model based on hub biomarkers and potential therapeutic targets for treatments.