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Journal of Translational Medicine Jul 2023Diet may influence biological aging and the discrepancy (∆age) between a subject's biological age (BA) and chronological age (CA). We aimed to investigate the...
BACKGROUND
Diet may influence biological aging and the discrepancy (∆age) between a subject's biological age (BA) and chronological age (CA). We aimed to investigate the correlation of dietary flavonoids with the ∆age of organs (heart, kidney, liver) and the whole body.
METHOD
A total of 3193 United States adults were extracted from the National Health and Nutrition Examination Survey (NHANES) in 2007-2008 and 2017-2018. Dietary flavonoids intake was assessed using 24-h dietary recall method. Multiple linear regression analysis was performed to evaluate the association of dietary flavonoids intake with the ∆age of organs (heart, kidney, liver) and the whole body. BA was computed based on circulating biomarkers, and the resulting ∆age was tested as an outcome in linear regression analysis.
RESULTS
The ∆age of the whole body, heart, and liver was inversely associated with higher flavonoids intake (the whole body ∆age β = - 0.58, cardiovascular ∆age β = - 0.96, liver ∆age β = - 3.19) after adjustment for variables. However, higher flavonoids intake positively related to renal ∆age (β = 0.40) in participants with chronic kidney disease (CKD). Associations were influenced by population characteristics, such as age, health behavior, or chronic diseases. Anthocyanidins, isoflavones and flavones had the strongest inverse associations between the whole body ∆age and cardiovascular ∆age among all the flavonoids subclasses.
CONCLUSION
Flavonoids intake positively contributes to delaying the biological aging process, especially in the heart, and liver organ, which may be beneficial for reducing the long-term risk of cardiovascular or liver disease.
Topics: Adult; Humans; Flavonoids; Nutrition Surveys; Heart; Liver; Aging
PubMed: 37480074
DOI: 10.1186/s12967-023-04321-1 -
Human Reproduction Update Nov 2023Modern lifestyle has led to an increase in the age at conception. Advanced age is one of the critical risk factors for female-related infertility. It is well known that... (Review)
Review
BACKGROUND
Modern lifestyle has led to an increase in the age at conception. Advanced age is one of the critical risk factors for female-related infertility. It is well known that maternal age positively correlates with the deterioration of oocyte quality and chromosomal abnormalities in oocytes and embryos. The effect of age on endometrial function may be an equally important factor influencing implantation rate, pregnancy rate, and overall female fertility. However, there are only a few published studies on this topic, suggesting that this area has been under-explored. Improving our knowledge of endometrial aging from the biological (cellular, molecular, histological) and clinical perspectives would broaden our understanding of the risks of age-related female infertility.
OBJECTIVE AND RATIONALE
The objective of this narrative review is to critically evaluate the existing literature on endometrial aging with a focus on synthesizing the evidence for the impact of endometrial aging on conception and pregnancy success. This would provide insights into existing gaps in the clinical application of research findings and promote the development of treatment options in this field.
SEARCH METHODS
The review was prepared using PubMed (Medline) until February 2023 with the keywords such as 'endometrial aging', 'receptivity', 'decidualization', 'hormone', 'senescence', 'cellular', 'molecular', 'methylation', 'biological age', 'epigenetic', 'oocyte recipient', 'oocyte donation', 'embryo transfer', and 'pregnancy rate'. Articles in a language other than English were excluded.
OUTCOMES
In the aging endometrium, alterations occur at the molecular, cellular, and histological levels suggesting that aging has a negative effect on endometrial biology and may impair endometrial receptivity. Additionally, advanced age influences cellular senescence, which plays an important role during the initial phase of implantation and is a major obstacle in the development of suitable senolytic agents for endometrial aging. Aging is also accountable for chronic conditions associated with inflammaging, which eventually can lead to increased pro-inflammation and tissue fibrosis. Furthermore, advanced age influences epigenetic regulation in the endometrium, thus altering the relation between its epigenetic and chronological age. The studies in oocyte donation cycles to determine the effect of age on endometrial receptivity with respect to the rates of implantation, clinical pregnancy, miscarriage, and live birth have revealed contradictory inferences indicating the need for future research on the mechanisms and corresponding causal effects of women's age on endometrial receptivity.
WIDER IMPLICATIONS
Increasing age can be accountable for female infertility and IVF failures. Based on the complied observations and synthesized conclusions in this review, advanced age has been shown to have a negative impact on endometrial functioning. This information can provide recommendations for future research focusing on molecular mechanisms of age-related cellular senescence, cellular composition, and transcriptomic changes in relation to endometrial aging. Additionally, further prospective research is needed to explore newly emerging therapeutic options, such as the senolytic agents that can target endometrial aging without affecting decidualization. Moreover, clinical trial protocols, focusing on oocyte donation cycles, would be beneficial in understanding the direct clinical implications of endometrial aging on pregnancy outcomes.
Topics: Pregnancy; Female; Humans; Infertility, Female; Epigenesis, Genetic; Senotherapeutics; Pregnancy Outcome; Pregnancy Rate; Embryo Implantation; Endometrium
PubMed: 37468438
DOI: 10.1093/humupd/dmad019 -
BMC Public Health Aug 2023Even though cadmium (Cd) exposure and cellular senescence (telomere length) have been linked in previous studies, composite molecular aging biomarkers are more...
INTRODUCTION
Even though cadmium (Cd) exposure and cellular senescence (telomere length) have been linked in previous studies, composite molecular aging biomarkers are more significant and reliable factors to consider when examining the connection between metal exposure and health outcomes. The purpose of this research was to assess the association between urinary cadmium (U-Cd) and whole-body aging (phenotypic age).
METHODS
Phenotypic age was calculated from chronological age and 9 molecular biomarkers. Multivariate linear regression models, subgroup analysis, and smoothing curve fitting were used to explore the linear and nonlinear relationship between U-Cd and phenotypic age. Mediation analysis was performed to explore the mediating effect of U-Cd on the association between smoking and phenotypic age.
RESULTS
This study included 10,083 participants with a mean chronological age and a mean phenotypic age of 42.24 years and 42.34 years, respectively. In the fully adjusted model, there was a positive relationship between U-Cd and phenotypic age [2.13 years per 1 ng/g U-Cd, (1.67, 2.58)]. This association differed by sex, age, and smoking subgroups (P for interaction < 0.05). U-Cd mediated a positive association between serum cotinine and phenotypic age, mediating a proportion of 23.2%.
CONCLUSIONS
Our results suggest that high levels of Cd exposure are associated with whole-body aging.
Topics: Adult; Humans; Aging; Cadmium; Cotinine; Mediation Analysis; Nutrition Surveys; Male; Female
PubMed: 37653508
DOI: 10.1186/s12889-023-16643-2 -
Human Reproduction (Oxford, England) Sep 2023Are there associations between natural or surgical menopause and incident dementia by age at menopause?
STUDY QUESTION
Are there associations between natural or surgical menopause and incident dementia by age at menopause?
SUMMARY ANSWER
Compared to age at menopause of 46-50 years, earlier natural menopause (≤40 and 41-45 years) was related to higher risk of all-cause dementia, while a U-shape relationship was observed between age at surgical menopause and risk of dementia.
WHAT IS KNOWN ALREADY
Menopause marks the end of female reproductive period. Age at menopause reflects the length of exposure to endogenous estrogen. Evidence on the association between age at natural, surgical menopause, and risk of dementia has been inconsistent.
STUDY DESIGN, SIZE, DURATION
A population-based cohort study involving 160 080 women who participated in the UK Biobank study.
PARTICIPANTS/MATERIALS, SETTING, METHODS
Women with no dementia at baseline, and had no missing data on key exposure variables and covariates were included. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs on the association of categorical menopause age with incident all-cause dementia, Alzheimer's disease (AD) and vascular dementia (VD). Restricted cubic splines were used to model the non-linear relationship between continuous age at natural, surgical menopause, and risk of dementia. In addition, we analyzed the interaction effect of ever-used menopausal hormone therapy (MHT) at baseline, income level, leisure activities, and age at menopause on risk of dementia.
MAIN RESULTS AND THE ROLE OF CHANCE
Compared to women with age at menopause of 46-50 years, women with earlier natural menopause younger than 40 years (1.36, 1.01-1.83) and 41-45 years (1.19, 1.03-1.39) had a higher risk of all-cause dementia, while late natural menopause >55 years was linked to lower risk of dementia (0.83, 0.71-0.98). Compared to natural menopause, surgical menopause was associated with 10% higher risk of dementia (1.10, 0.98-1.24). A U-shape relationship was observed between surgical menopause and risk of dementia. Women with surgical menopause before age 40 years (1.94, 1.38-2.73) and after age 55 years (1.65, 1.21-2.24) were both linked to increased risk of all-cause dementia. Women with early natural menopause without ever taking MHT at baseline had an increased risk of AD. Also, in each categorized age at the menopause level, higher income level or higher number of leisure activities was linked to a lowers risk of dementia.
LIMITATIONS, REASONS FOR CAUTION
Menopausal age was based on women's self-report, which might cause recall bias.
WIDER IMPLICATION OF THE FINDINGS
Women who experienced natural menopause or had surgical menopause at an earlier age need close monitoring and engagement for preventive health measures to delay the development of dementia.
STUDY FUNDING/COMPETING INTERESTS
This work was supported by the Start-up Foundation for Scientific Research in Shandong University (202099000066), Science Fund Program for Excellent Young Scholars of Shandong Provence (Overseas) (2022HWYQ-030), and the National Natural Science Foundation of China (82273702). There are no competing interests.
TRIAL REGISTRATION NUMBER
N/A.
Topics: Female; Humans; Middle Aged; Adult; Cohort Studies; Biological Specimen Banks; Menopause; Menopause, Premature; United Kingdom
PubMed: 37344154
DOI: 10.1093/humrep/dead130 -
Journal of the Endocrine Society Jul 2023The roles of age at menarche and age at menopause in the etiology of lung and colorectal cancers are unclear.
BACKGROUND
The roles of age at menarche and age at menopause in the etiology of lung and colorectal cancers are unclear.
OBJECTIVE
We aimed to investigate potential causal associations between age at menarche, age at natural menopause, and risk of lung and colorectal cancers using a Mendelian randomization (MR) approach.
METHODS
From the Trøndelag Health Study in Norway, we defined two cohorts of 35 477 and 17 118 women to study the effects of age at menarche and age at natural menopause, respectively. We ran univariable MR to evaluate the potential causal associations. We performed multivariable MR adjusting for genetic variants of adult body mass index (BMI) to estimate the direct effect of age at menarche.
RESULTS
Genetically predicted 1-year increase in age at menarche was associated with a lower risk of lung cancer overall (hazard ratio [HR, 0.64; 95% CI, 0.48-0.86), lung adenocarcinoma (HR, 0.61; 95% CI, 0.38-0.99), and lung non-adenocarcinoma (HR, 0.66; 95% CI, 0.45-0.95). After adjusting for adult BMI using a multivariable MR model, the direct effect estimates reduced to HR 0.72 (95% CI, 0.54-0.95) for lung cancer overall, HR 0.67 (95% CI, 0.43-1.03) for lung adenocarcinoma, and HR 0.77 (95% CI, 0.54-1.09) for lung non-adenocarcinoma. Age at menarche was not associated with colorectal cancer. Moreover, genetically predicted age at natural menopause was not associated with lung and colorectal cancers.
CONCLUSION
Our MR study suggested that later age at menarche was causally associated with a decreased risk of lung cancer overall and its subtypes, and adult BMI might be a mediator.
PubMed: 37404243
DOI: 10.1210/jendso/bvad077 -
Aging and Disease Aug 2023With aging, the incidence of age-related diseases increases. Hence, age-related diseases are inevitable. However, the mechanisms by which aging leads to the onset and... (Review)
Review
With aging, the incidence of age-related diseases increases. Hence, age-related diseases are inevitable. However, the mechanisms by which aging leads to the onset and progression of age-related diseases remain unclear. It has been reported that inflammation is closely associated with age-related diseases and that the cGAS-STING signaling pathway, which can sense the aberrant presence of cytosolic DNA during aging and induce an inflammatory response, is an important mediator of inflammation in age-related diseases. With a better understanding of the structure and molecular biology of the cGAS-STING signaling axis, numerous selective inhibitors and agonists targeting the cGAS-STING pathway in human age-related diseases have been developed to modulate inflammatory responses. Here, we provide a narrative review of the activity of the cGAS-STING pathway in age-related diseases and discuss its general mechanisms in the onset and progression of age-related diseases. In addition, we outline treatments targeting the cGAS-STING pathway, which may constitute a potential therapeutic alternative for age-related diseases.
PubMed: 37163421
DOI: 10.14336/AD.2023.0117 -
The Lancet. Healthy Longevity Dec 2023Biological age is a measure of health that offers insights into ageing. The existing age clocks, although valuable, often trade off accuracy and interpretability. We...
BACKGROUND
Biological age is a measure of health that offers insights into ageing. The existing age clocks, although valuable, often trade off accuracy and interpretability. We introduce ExplaiNAble BioLogical Age (ENABL Age), a computational framework that combines machine-learning models with explainable artificial intelligence (XAI) methods to accurately estimate biological age with individualised explanations.
METHODS
To construct the ENABL Age clock, we first predicted an age-related outcome (eg, all-cause or cause-specific mortality), and then rescaled these predictions to estimate biological age, using UK Biobank and National Health and Nutrition Examination Survey (NHANES) datasets. We adapted existing XAI methods to decompose individual ENABL Ages into contributing risk factors. For broad accessibility, we developed two versions: ENABL Age-L, based on blood tests, and ENABL Age-Q, based on questionnaire characteristics. Finally, we validated diverse ageing mechanisms captured by each ENABL Age clock through genome-wide association studies (GWAS) association analyses.
FINDINGS
Our ENABL Age clock was significantly correlated with chronological age (r=0·7867, p<0·0001 for UK Biobank; r=0·7126, p<0·0001 for NHANES). These clocks distinguish individuals who are healthy (ie, their ENABL Age is lower than their chronological age) from those who are unhealthy (ie, their ENABL Age is higher than their chronological age), predicting mortality more effectively than existing clocks. Groups of individuals who were unhealthy showed approximately three to 12 times higher log hazard ratio than healthy groups, as per ENABL Age. The clocks achieved high mortality prediction power with an area under the receiver operating characteristic curve of 0·8179 for 5-year mortality and 0·8115 for 10-year mortality on the UK Biobank dataset, and 0·8935 for 5-year mortality and 0·9107 for 10-year mortality on the NHANES dataset. The individualised explanations that revealed the contribution of specific characteristics to ENABL Age provided insights into the important characteristics for ageing. An association analysis with risk factors and ageing-related morbidities and GWAS results on ENABL Age clocks trained on different mortality causes showed that each clock captures distinct ageing mechanisms.
INTERPRETATION
ENABL Age brings an important leap forward in the application of XAI for interpreting biological age clocks. ENABL Age also carries substantial potential in practical settings, assisting medical professionals in untangling the complexity of ageing mechanisms, and potentially becoming a valuable tool in informed clinical decision-making processes.
FUNDING
National Science Foundation and National Institutes of Health.
Topics: United States; Humans; Artificial Intelligence; Genome-Wide Association Study; Nutrition Surveys; Machine Learning; Aging
PubMed: 37944549
DOI: 10.1016/S2666-7568(23)00189-7 -
Neurobiology of Aging Dec 2023Biological age and brain age estimated using biological and neuroimaging measures have recently emerged as surrogate aging biomarkers shown to be predictive of diverse...
Biological age and brain age estimated using biological and neuroimaging measures have recently emerged as surrogate aging biomarkers shown to be predictive of diverse health outcomes. As aging underlies the development of many chronic conditions, surrogate aging biomarkers capture health at the whole person level, having the potential to improve our understanding of multimorbidity. Our study investigates whether elevated biological age and brain age are associated with an increased risk of multimorbidity using a large dataset from the Midlife in the United States Refresher study. Ensemble learning is utilized to combine multiple machine learning models to estimate biological age using a comprehensive set of biological markers. Brain age is obtained using Gaussian processes regression and neuroimaging data. Our study is the first to examine the relationship between accelerated brain age and multimorbidity. Furthermore, it is the first attempt to explore how biological age and brain age are related to multimorbidity in mental health. Our findings hold the potential to advance the understanding of disease accumulation and their relationship with aging.
Topics: Humans; United States; Multimorbidity; Mental Health; Aging; Brain; Biomarkers; Chronic Disease
PubMed: 37804610
DOI: 10.1016/j.neurobiolaging.2023.09.003