Genetic and non-genetic factors associated with the phenotype of exceptional longevity & normal cognition

Risk Prediction Model for Non-Suicidal Self-Injury in Chinese Adolescents with Major Depressive Disorder Based on Machine Learning

Background

Non-suicidal self-injury (NSSI) is a significant social issue, especially among adolescents with major depressive disorder (MDD). This study aimed to construct a risk prediction model using machine learning (ML) algorithms, such as XGBoost and random forest, to identify interventions for healthcare professionals working with adolescents with MDD.

Methods

This study investigated 488 adolescents with MDD. Adolescents was randomly divided into 75% training set and 25% test set to testify the predictive value of risk prediction model. The prediction model was constructed using XGBoost and random forest algorithms. We evaluated the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, recall, F Score of the two models for comparing the performance of the two models.

Results

There were 161 (33.00%) participants having NSSI. Compared without NSSI, there were statistically significant differences in gender (P=0.035), age (P=0.036), depressive symptoms (P=0.042), sleep quality (P=0.030), dysfunctional attitudes (P=0.048), childhood trauma (P=0.046), interpersonal problems (P=0.047), psychoticism (P) (P=0.049), neuroticism (N) (P=0.044), punishing and Severe (F2) (P=0.045) and Overly-intervening and Protecting (M2) (P=0.047) with NSSI. The AUC values for random forest and XGBoost were 0.780 and 0.807, respectively. The top five most important risk predictors identified by both machine learning methods were dysfunctional attitude, childhood trauma, depressive symptoms, F2 and M2.

Conclusion

The study demonstrates the suitability of prediction models for predicting NSSI behavior in Chinese adolescents with MDD based on ML. This model improves the assessment of NSSI in adolescents with MDD by health care professionals working. This provides a foundation for focused prevention and interventions by health care professionals working with these adolescents.

Global Research on Centenarians: A Historical and Comprehensive Bibliometric Analysis from 1887 to 2023

BACKGROUND

Centenarians are considered the most successful human biological aging model. However, the characteristics and patterns of research among centenarians have not been described or analyzed. Thus, this study aimed to disclose the historical landscape of global research on centenarians.

METHODS

This bibliometric study investigated historical evidence on centenarian research published in the Scopus database. The bibliometrix package in R was used to perform visual and quantitative analyses of research metrics, trends, and patterns.

RESULTS

Of the 2,061 documents included between 1887 and 2023, 84.2% (n=1,736) were published as articles with primary data. We identified international collaboration and annual growth rates of 21.4% and 3.15%, respectively. The United States published the highest number of papers on centenarians (n=786), whereas the publications from Italy had the highest impact (h-index of 90). Based on the frequency of keywords, mortality, genetics, dementia, Alzheimer's disease, and immunosenescence are a few of the most studied topics among centenarians, with emerging research related to mitochondrial DNA and comparison of results between nonagenarians and centenarians. Italy, the United States, and China lead the global research collaboration network, collaborating most frequently with Japan and European countries.

CONCLUSION

Global research on centenarians has grown over the last 20 years, primarily led by Italy, the United States, and China. Latin American and African countries have conducted little or no research on centenarians. The most widely studied topics include mortality, cognition, immunosenescence, and genetics.

Nutraceutical blends predict enhanced health via microbiota reshaping improving cytokines and life quality: a Brazilian double-blind randomized trial

Nutraceutical interventions supporting microbiota and eliciting clinical improvements in metabolic diseases have grown significantly. Chronic stress, gut dysbiosis, and metainflammation have emerged as key factors intertwined with sleep disorders, consequently exacerbating the decline in quality of life. This study aimed to assess the effects of two nutraceutical formulations containing prebiotics (fructooligosaccharides (FOS), galactooligosaccharides (GOS), yeast β-glucans), minerals (Mg, Se, Zn), and the herbal medicine Silybum marianum L. Gaertn., Asteraceae (Milk thistle or Silymarin). These formulations, namely NSupple (without silymarin) and NSupple_Silybum (with silymarin) were tested over 180 days in overweight/obese volunteers from Brazil's southeastern region. We accessed fecal gut microbiota by partial 16S rRNA sequences; cytokines expression by CBA; anthropometrics, quality of life and sleep, as well as metabolic and hormonal parameters, at baseline (T0) and 180 days (T180) post-supplementation. Results demonstrated gut microbiota reshaping at phyla, genera, and species level post-supplementation. The Bacteroidetes phylum, Bacteroides, and Prevotella genera were positively modulated especially in the NSupple_Silybum group. Gut microbiota modulation was associated with improved sleep patterns, quality-of-life perception, cytokines expression, and anthropometric parameters post-supplementation. Our findings suggest that the nutraceutical blends positively enhance cardiometabolic and inflammatory markers. Particularly, NSupple_Silybum modulated microbiota composition, underscoring its potential significance in ameliorating metabolic dysregulation. Clinical trial registry number: NCT04810572. 23/03/2021.

Phenotypic molecular features of long-lived animal species

One of the challenges facing science/biology today is uncovering the molecular bases that support and determine animal and human longevity. Nature, in offering a diversity of animal species that differ in longevity by more than 5 orders of magnitude, is the best 'experimental laboratory' to achieve this aim. Mammals, in particular, can differ by more than 200-fold in longevity. For this reason, most of the available evidence on this topic derives from comparative physiology studies. But why can human beings, for instance, reach 120 years whereas rats only last at best 4 years? How does nature change the longevity of species? Longevity is a species-specific feature resulting from an evolutionary process. Long-lived animal species, including humans, show adaptations at all levels of biological organization, from metabolites to genome, supported by signaling and regulatory networks. The structural and functional features that define a long-lived species may suggest that longevity is a programmed biological property.

Cognitive impairment in long-living adults: a genome-wide association study, polygenic risk score model and molecular modeling of the APOE protein

Background

Cognitive impairment is an irreversible, aging-associated condition that robs people of their independence. The purpose of this study was to investigate possible causes of this condition and propose preventive options.

Methods

We assessed cognitive status in long-living adults aged 90+ (n = 2,559) and performed a genome wide association study using two sets of variables: Mini-Mental State Examination scores as a continuous variable (linear regression) and cognitive status as a binary variable (> 24, no cognitive impairment; <10, impairment) (logistic regression).

Results

Both variations yielded the same polymorphisms, including a well-known marker of dementia, rs429358in the APOE gene. Molecular dynamics simulations showed that this polymorphism leads to changes in the structure of alpha helices and the mobility of the lipid-binding domain in the APOE protein.

Conclusion

These changes, along with higher LDL and total cholesterol levels, could be the mechanism underlying the development of cognitive impairment in older adults. However, this polymorphism is not the only determining factor in cognitive impairment. The polygenic risk score model included 45 polymorphisms (ROC AUC 69%), further confirming the multifactorial nature of this condition. Our findings, particularly the results of PRS modeling, could contribute to the development of early detection strategies for predisposition to cognitive impairment in older adults.

The many "Neurofaces" of Prohibitins 1 and 2: Crucial for the healthy brain, dysregulated in numerous brain disorders

Prohibitin 1 (PHB1) and prohibitin 2 (PHB2) are proteins that are nearly ubiquitously expressed. They are localized in mitochondria, cytosol and cell nuclei. In the healthy CNS, they occur in neurons and non-neuronal cells (oligodendrocytes, astrocytes, microglia, and endothelial cells) and fulfill pivotal functions in brain development and aging, the regulation of brain metabolism, maintenance of structural integrity, synapse formation, aminoacidergic neurotransmission and, probably, regulation of brain action of certain hypothalamic-pituitary hormones.With regard to the diseased brain there is increasing evidence that prohibitins are prominently involved in numerous major diseases of the CNS, which are summarized and discussed in the present review (brain tumors, neurotropic viruses, Alzheimer disease, Down syndrome, Fronto-temporal and vascular dementia, dementia with Lewy bodies, Parkinson disease, Huntington disease, Multiple sclerosis, Amyotrophic lateral sclerosis, stroke, alcohol use disorder, schizophrenia and autism). Unfortunately, there is no PHB-targeted therapy available for any of these diseases.

Investigation of long-term symptoms and influencing factors in patients with mild traumatic brain injury: A cross-sectional study

BACKGROUND

Traumatic brain injury is the leading cause of death and disability in individuals under the age of 45, which places a heavy disease burden on patients and society. However, the prevalence of long-term symptoms in individuals who suffered from mild traumatic brain injury and how psychosocial factors affect their long-term symptoms remain unclear.

OBJECTIVE

To determine howpsychosocial factors influence long-term symptomsin individuals who suffered from mild traumatic brain injury as well as the prevalence of long-term symptoms.

METHODS

A demographic characteristics questionnaire, adapted self-report questionnaire of family relationship quality, revised Chinese version of the disease perception questionnaire, Rivermead postconcussion syndrome symptom questionnaire, Glasgow Outcome Scale-Extended, and Brief Symptoms Inventory 18 were used to collect data anonymously. Psychosocial factors associated with long-term symptoms in individuals who suffered from mild traumatic brain injury weremeasuredusingmultiple linear regression.

RESULTS

More than half of individuals who suffered from mild traumatic brain injury showed at least 1 long-term symptom after injury. Our results indicated that family relationship quality, disease perception, and demographic characteristics were related to the long-term symptoms of individuals who suffered from mild traumatic brain injury.

CONCLUSIONS

Our study shows that theprevalence of long-term symptomsfollowingmild traumatic brain injuryishigh. Psychosocial factors are related to patients' long-term symptoms. The findings indicate that healthcare administrators ought to adopt a robust health promotion strategy that prioritizes familial support and health education of diseases to ameliorate long-term symptoms in individuals who suffered from mild traumatic brain injury.

Development and Validation of a Lifespan Prediction Model in Chinese Adults Aged 65 Years or Older

OBJECTIVES

Previous studies investigated factors associated with mortality. Nevertheless, evidence is limited regarding the determinants of lifespan. We aimed to develop and validate a lifespan prediction model based on the most important predictors.

DESIGN

A prospective cohort study.

SETTING AND PARTICIPANTS

A total of 23,892 community-living adults aged 65 years or older with confirmed death records between 1998 and 2018 from 23 provinces in China.

METHODS

Information including demographic characteristics, lifestyle, functional health, and prevalence of diseases was collected. The risk prediction model was generated using multivariate linear regression, incorporating the most important predictors identified by the Lasso selection method. We used 1000 bootstrap resampling for the internal validation. The model performance was assessed by adjusted R2, root mean square error (RMSE), mean absolute error (MAE), and intraclass correlation coefficient (ICC).

RESULTS

Twenty-one predictors were included in the final lifespan prediction model. Older adults with longer lifespans were characterized by older age at baseline, female, minority race, living in rural areas, married, with healthier lifestyles and more leisure engagement, better functional status, and absence of diseases. The predicted lifespans were highly consistent with observed lifespans, with an adjusted R2 of 0.893. RMSE was 2.86 (95% CI 2.84-2.88) and MAE was 2.18 (95% CI 2.16-2.20) years. The ICC between observed and predicted lifespans was 0.971 (95% CI 0.971-0.971).

CONCLUSIONS AND IMPLICATIONS

The lifespan prediction model was validated with good performance, the web-based prediction tool can be easily applied in practical use as it relies on all easily accessible variables.

The integrated landscape of eRNA in gastric cancer reveals distinct immune subtypes with prognostic and therapeutic relevance

The comprehensive regulation effect of eRNA on tumor immune cell infiltration and the outcome remains obscure. We comprehensively identify the eRNA-mediated immune infiltration patterns of gastric cancer (GC) samples. We creatively proposed a random forest machine-learning (ML) algorithm to map eRNA to mRNA expression patterns. The eRNA score was constructed using principal component analysis algorithms and validated in an independent cohort. Three subtypes with distinct eRNA expression patterns were determined in GC. There were significant differences between the three subtypes in the overall survival rate, immune cell infiltration characteristics, and immunotherapy response indicators. The patients in the high eRNA score group have a higher overall survival rate and might benefit from immunotherapy. This work revealed that eRNA regulation might be a new prognostic index and might offer a potential biomarker in the response of immunotherapy. Evaluating the eRNA regulation manner of GC will contribute to guiding more effective immunotherapy strategies.

Clozapine Long-Term Treatment Might Reduce Epigenetic Age Through Hypomethylation of Longevity Regulatory Pathways Genes

Long-term studies have shown significantly lower mortality rates in patients with continuous clozapine (CLZ) treatment than other antipsychotics. We aimed to evaluate epigenetic age and DNA methylome differences between CLZ-treated patients and those without psychopharmacological treatment. The DNA methylome was analyzed using the Infinium MethylationEPIC BeadChip in 31 CLZ-treated patients with psychotic disorders and 56 patients with psychiatric disorders naive to psychopharmacological treatment. Delta age (Δage) was calculated as the difference between predicted epigenetic age and chronological age. CLZ-treated patients were stratified by sex, age, and years of treatment. Differential methylation sites between both groups were determined using linear regression models. The Δage in CLZ-treated patients was on average lower compared with drug-naive patients for the three clocks analyzed; however, after data-stratification, this difference remained only in male patients. Additional differences were observed in Hannum and Horvath clocks when comparing chronological age and years of CLZ treatment. We identified 44,716 differentially methylated sites, of which 87.7% were hypomethylated in CLZ-treated patients, and enriched in the longevity pathway genes. Moreover, by protein-protein interaction, AMPK and insulin signaling pathways were found enriched. CLZ could promote a lower Δage in individuals with long-term treatment and modify the DNA methylome of the longevity-regulating pathways genes.

Alterations in the gut microbiota contribute to cognitive impairment induced by the ketogenic diet and hypoxia

Many genetic and environmental factors increase susceptibility to cognitive impairment (CI), and the gut microbiome is increasingly implicated. However, the identity of gut microbes associated with CI risk, their effects on CI, and their mechanisms remain unclear. Here, we show that a carbohydrate-restricted (ketogenic) diet potentiates CI induced by intermittent hypoxia in mice and alters the gut microbiota. Depleting the microbiome reduces CI, whereas transplantation of the risk-associated microbiome or monocolonization with Bilophila wadsworthia confers CI in mice fed a standard diet. B. wadsworthia and the risk-associated microbiome disrupt hippocampal synaptic plasticity, neurogenesis, and gene expression. The CI is associated with microbiome-dependent increases in intestinal interferon-gamma (IFNg)-producing Th1 cells. Inhibiting Th1 cell development abrogates the adverse effects of both B. wadsworthia and environmental risk factors on CI. Together, these findings identify select gut bacteria that contribute to environmental risk for CI in mice by promoting inflammation and hippocampal dysfunction.

Interaction between APOE ε4 and dietary protein intake on cognitive decline: A longitudinal cohort study

OBJECTIVE

To exam the association of cognitive decline with APOE ε4 allele carriage and dietary protein intake and investigate whether there is a gene-diet (GxD) interaction of APOE ε4 allele carriage and dietary protein intake on cognitive decline in a nationwide cohort of older adults.

METHODS

A cohort study of participants from Chinese Longitudinal Healthy Longevity Survey was conducted from 2008 to 2014. A total of 3029 participants (mean age of 77.0 years, SD = 9.0; 49.3% were women) was enrolled. We genotyped APOE ε4 allele for each participant and calculated the diversity of dietary protein intake (DDPI) by summing up the frequency of intake of the 6 protein-rich foods (meats, fish, eggs, nuts, dairy products, and bean products). We assessed cognitive function using the Mini-Mental State Examination (MMSE). We used ordinal regression model to estimate the independent and joint effects of APOE ε4 carrier and dietary protein intake on cognitive decline, adjusting for potential confounders of age, sex, education, socio-economic status, lifestyles, BMI, and cardiometabolic conditions.

RESULTS

There was significant association between carrying APOE ε4 allele and faster cognitive decline (Odds ratio: 1.19, 95% CI = 1.00-1.42), independent of potential confounders. While the associations of DDPI and the intake of 6 protein-rich foods with cognitive decline did not reach any statistical significance. We observed significant interactions of APOE ε4 with DDPI and fish intake, at multiple correction-adjusted Ps < 0.05. In those who were APOE ε4 carriers rather than non-carriers, both high DDPI (OR = 0.54, 95% CI: 0.34-0.88) and daily fish intake (OR = 0.43, 95% CI: 0.22-0.78) were significantly associated with slower cognitive decline, respectively. We also found that frequent intake of fish benefits women more than men regarding the mitigating of cognitive decline among APOE ε4 allele carriers (P for interaction = 0.016).

CONCLUSIONS

The results of this study support the hypothesis that diversified protein food intake in addition to frequent fish intake may reduce the detrimental effect of APOE ε4 on cognitive health.