The EPMA journal最新文献

Due to their phenotype-associated attitude predominantly oriented towards high performance, Flammer syndrome (FS) phenotype carriers are blessed to a successful career in corresponding professional branches. This advantage is however associated with significant health risks. FSP carriers are extremely stress-sensitive. Corresponding pathways are epigenetically regulated, and modifiable risk factors are associated with the phenotype-specific psycho-somatic patterns such as a drive for meticulousness, perfectionism and exercised rigour applying strictness, discipline, or thoroughness to their own behaviour and actions. The FS phenotype is typically characterised by chronication of the transient sympathoexcitation and its dominance over parasympathetic relaxation. Chronification of the parasympathetic-sympathetic imbalance in form of sympathetic overdrive leads to chronic ischemic events in peripheral vessels and progressing tissue damage associated with the cyclic ischemia-reperfusion. Ischemic damage can be roughly estimated by levels of the vasoconstrictor endotelin-1 (ET-1) measured in blood. However, other risk factors on the one hand and compensatory mechanisms on the other hand are decisive for the damage extent at individual level. For example, chronically increased ET-1 and even mild hyperhomocysteinaemia synergistically may cause a progressing disease of small vessels, systemic inflammation and chronification of mitochondrial stress potentially resulting in chronic fatigue and mitochondrial burnout with a spectrum of associated pathologies in affected individuals. That is why predictive diagnostics utilising comprehensive individualised patient profiles are crucial for the cost-effective targeted prevention and creation of personalised treatment algorithms. Due to the high level of algorithms' complexity, an application of AI is essential. FS is usually established early in life during pubertal maturation of otherwise healthy individuals. Therefore, FS phenotyping is instrumental for 3PM-guided cost-effective primary healthcare. To meet the needs of this patient cohort, an application of the digital health monitoring including records of mitochondrial homeostasis is strongly recommended to protect the FS phenotype carriers against health-to-disease transition. To this end, patient friendly non-invasive approach is already established utilising tear fluid multi-omics, mitochondria as vital biosensors and AI-based multi-professional data interpretation; the approach is offered to the FS phenotype carriers.

Background: Traumatic pancreatitis (TP) is a distinct subtype of pancreatitis. Although ferroptosis of pancreatic acinar cells is well documented in acute pancreatitis (AP), studies on ferroptosis in TP and its relationship with subsequent intra-abdominal infections (IAIs) remain limited and unclear. Incorporating predictive, preventive, and personalized medicine (3PM) strategies could significantly enhance TP management, particularly through early detection and targeted interventions.

Methods: A total of 60 male rats were divided into four groups: TP model, ferroptosis activation, and inhibition groups. Physiological parameters, mortality rates, and serum cytokine, pancreatic enzyme expression, and oxidative stress factor levels were observed. Pathological evaluation of pancreatic tissue was performed. Subsequently, iron staining, ACSL4 immunofluorescence detection, and mRNA and protein expression of ferroptosis-related molecules were assessed in pancreatic tissues. Furthermore, 16S rDNA sequencing of peritoneal lavage fluid was performed to evaluate the impact of TP and ferroptosis modulation on the intra-abdominal microbiota and infection. Finally, clinical data from TP patients with IAIs were analyzed to identify commonalities with animal findings, offering predictive insights for human treatment.

Results: TP caused severe pancreatic tissue damage, and activation of ferroptosis further exacerbated tissue damage, systemic inflammation, and animal mortality. Inhibition of ferroptosis improved these indicators in TP rats. Furthermore, 16S rDNA sequencing results showed that TP rats had enhanced intra-abdominal microbiota dysbiosis and an increased proportion of pathogenic bacteria. The use of ferroptosis activators further aggravated the IAIs in TP rats. Clinical analysis showed elevated serum ferroptosis biomarkers in TP patients, with higher proportions of antibiotic-resistant Acinetobacter and Pseudomonas aeruginosa found in abdominal cultures, highlighting the need for predictive biomarkers and personalized therapeutic strategies.

Conclusions: Inhibiting ferroptosis alleviates pancreatic damage and reduces mortality in TP rats. Ferroptosis exacerbates IAIs by increasing oxidative stress and inflammatory responses. From a 3PM perspective, targeting ferroptosis offers predictive and preventive potential, enabling earlier interventions and personalized therapies to improve patient outcomes and reduce complications.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-025-00418-3.

Creatine, traditionally recognized for its role in skeletal muscle energy metabolism, is increasingly emerging as a mitochondria-targeted theranostic agent with significant relevance to the framework of predictive, preventive, and personalized medicine (PPPM). However, several critical gaps currently limit its translation into clinical practice: (1) the lack of sensitive and standardized biomarkers for early detection of bioenergetic deficits, (2) limited incorporation of creatine profiling into predictive risk models, (3) insufficient personalization of supplementation strategies despite known interindividual variability in transporter function, endogenous synthesis, and tissue kinetics, and (4) underdeveloped clinical validation of advanced creatine formulations and delivery systems. This mini review addresses these unmet needs by consolidating evidence on creatine's multifaceted biological functions-including stabilization of mitochondrial membranes, regulation of oxidative stress, support of mitochondrial biogenesis, and modulation of apoptotic signaling-across physiological and pathological states. By sustaining ATP homeostasis via the creatine kinase-phosphocreatine system and influencing mitochondrial dynamics and redox balance, creatine represents both a therapeutic and diagnostic candidate for diseases characterized by impaired bioenergetics. From a PPPM perspective, creatine profiling through biofluids, tissue sampling, and advanced imaging (e.g., proton magnetic resonance spectroscopy) offers a minimally invasive approach for early detection, patient stratification, and monitoring of mitochondrial function. Personalized intervention strategies-guided by molecular and phenotypic profiling-have the potential to maximize efficacy and minimize risk, while creatine loading or depletion tests may serve as functional biomarkers of mitochondrial reserve capacity and supplementation responsiveness. Finally, integration of creatine-centered diagnostics and therapeutics with multi-omics data, computational modeling, and digital health monitoring could overcome existing translational barriers. By reframing creatine from a sports nutrition supplement to a scalable, safe, and cost-effective component of mitochondrial medicine, this review outlines a pathway to address current diagnostic, predictive, and therapeutic deficits, ultimately supporting proactive, systems-level approaches to health maintenance and disease prevention.

Background: Diminished ovarian reserve (DOR) is increasingly recognized as a multifactorial condition, not solely related to aging. Emerging evidence suggests that environmental and biological factors, including the pelvic microbiota, may influence ovarian function across different age groups. In this study, we examined the association between pelvic microbiota dysbiosis and DOR, with the broader goal of identifying early microbiota-based markers to support predictive diagnosis, preventive strategies, and personalized reproductive care.

Methods: Ascitic fluid samples were collected from women with normal ovarian reserve and those diagnosed with DOR. Microbial profiling was performed using 16S ribosomal RNA (rRNA) gene sequencing to compare the composition and diversity of the pelvic microbiota between the two groups. A multivariable predictive model was constructed by combining key microbial genera with clinical indicators such as body mass index (BMI), aiming to support early risk estimation of DOR.

Results: Microbial analysis revealed a significantly higher abundance of Capnocytophaga in the DOR group compared to controls, suggesting its potential role as a microbial marker of diminished ovarian reserve. The predictive model integrating microbial and clinical data demonstrated moderate accuracy, with an area under the curve (AUC) of 0.88 ± 0.16.

Conclusions: Women with a BMI ≥ 24.0 face an increased risk of ovarian function decline. If pelvic microbiota profiling further reveals dysbiosis, particularly Capnocytophaga enrichment, early microbial screening and individualized probiotic treatment with Lactobacillus or Bifidobacterium may be warranted. This strategy embodies the core principles of predictive, preventive, and personalized medicine (PPPM/3PM).

Background: Immunoglobulin G (IgG) N-glycosylation plays a vital role in the pathogenesis of autoimmune disorders, inflammatory diseases, and viral infections. While various models of serum IgG N-glycosylation have been developed to identify individuals at high risk for relevant diseases, reference intervals (RIs) for the levels of IgG N-glycans have not been established yet. Identifying RIs for serum IgG N-glycans closely associated with biological aging and disease risk contributes to predictive, preventive, and personalized medicine (PPPM/3PM), which results in improvement of patients' outcomes, enhancement of healthcare efficiency, and in reducing burden of chronic diseases. This study is aimed at defining the age- and sex-specific RI in healthy Chinese adults.

Methods: The healthy participants aged 18 years and above were recruited from Shandong and Guangdong provinces. Serum IgG N-glycans were analyzed using hydrophilic interaction liquid chromatography using ultra-performance liquid chromatography (HILIC-UPLC), quantifying 24 glycan peaks (GPs). The 2.5th and 97.5th percentile reference limits for the glycans and their derived glycosylation features were used to define the 95 percentile of the reference distribution for glycan levels and derived glycosylation features.

Results: A total of 927 participants (median age 52 years; 566 women and 361 men) were included. Of 24 glycan peaks, 14 differed significantly between sexes, and 18 varied by age. Age- and sex-specific RIs were independently calculated for all 24 glycan peaks. For key glycosylation features, the RIs were 87.37-97.63% for fucosylation, 11.08-21.69% for bisecting N-acetylglucosamine (GlcNAc), 15.37-30.10% for sialylation, 15.93-41.91% for agalactosylation (G0), 22.60-36.93% for monogalactosylation (G1), and 10.46-26.99% for digalactosylation (G2). Individuals whose glycan indices locate in these RIs could be considered in a healthy glycosylation level.

Conclusions: This study identified and verified significant age- and sex-related differences in IgG N-glycosylation features and established RIs for IgG N-glycans in healthy Chinese adults. These RIs may serve as a useful benchmark for identifying individuals with abnormal glycosylation profiles. In PPPM/3PM, IgG N-glycosylation RIs can predict disease risk, enable targeted prevention, and support personalized medical and health plans that consider age and gender.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-025-00416-5.

Rationale and purpose: Periodontitis is a common source of chronic systemic inflammation, driven by bacterial translocation and cytokine release through ulcerated gingival epithelium, and may contribute to the development of various chronic ocular diseases. This study investigated the association between periodontitis and multiple ocular conditions, interpreting the findings within the framework of Predictive, Preventive, and Personalized Medicine (3PM).

Working hypothesis and methods: We hypothesized that periodontitis, as a treatable inflammatory condition, serves as a predictive marker and modifiable risk factor for ocular diseases involving vascular and immune-mediated mechanisms. Data from 11,448 adults aged ≥ 40 years from the Korea National Health and Nutrition Examination Survey (2008-2010) were analyzed. Periodontal status was classified using the Community Periodontal Index (CPI): no periodontitis (CPI ≤ 2), moderate (CPI = 3), and severe (CPI = 4). Ophthalmologists assessed ocular diseases, including cataract, pterygium, diabetic retinopathy, glaucoma suspect, blepharoptosis, and age-related macular degeneration (AMD), using standardized diagnostic protocols. Multivariable logistic regression adjusted for key covariates, and Pearson correlation analysis was conducted.

Results: Periodontitis was independently associated with higher risks of cataract (adjusted OR = 1.26), diabetic retinopathy (OR = 1.66), pterygium (OR = 1.22), glaucoma suspect (OR = 1.10), and blepharoptosis (OR = 1.16). These associations were more pronounced in individuals with severe periodontitis. No significant association was observed with early or late AMD. CPI scores showed weak but significant positive correlations with several ocular conditions, particularly cataract and diabetic retinopathy.

Conclusions and expert recommendations in the framework of 3pm: Periodontitis may serve as a predictive biomarker for ocular diseases with shared inflammatory and vascular pathways. Early identification and management of periodontal disease offer a targeted preventive strategy to reduce systemic inflammatory burden and ocular comorbidities. Personalized care models incorporating periodontal status into ocular screening protocols may improve diagnostic precision and enable risk-adapted interventions. These findings support the integration of oral health into multidisciplinary care frameworks, advancing the paradigm shift from reactive to predictive and personalized ophthalmology.

This review examines advanced predictive, preventive, and personalized medicine (3PM) strategies, along with the targeted modern approach for enhancing the performance and clinical utility of traditional Chinese medicine (TCM) gels for wound healing. These strategies are based on recent technological advancements involving 3D/4D printing, network pharmacology and multiomics technologies. TCM gels, characterized by their multicomponent and multitarget mechanisms, hold great potential for addressing the diverse challenges in the wound healing process, including inflammation, angiogenesis disorders and microbial infections. Their therapeutic effects are optimized through the modernization of classical TCM formulas, innovative design of matrix materials and functionalized drug delivery techniques. The underlying mechanisms of TCM gels are elucidated using multiomics technologies, while clinical translation focuses on standardization, quality control and rigorous clinical trial design. Future directions may include personalized treatment plans, care for complex wounds and the integration of environmentally sustainable and smart technologies. To achieve broader utilization in modern wound healing, challenges related to standardization and regulatory compliance must be addressed. The successful incorporation of TCM gels into current wound care systems can significantly contribute to public health, supporting the goal of ensuring healthy lives and promoting well-being for all.

Graphical abstract:

Over the past two decades, significant progress has been made in the study of minimal residual disease (MRD) in patients with solid tumors. Increasing evidence supports that monitoring and quantifying MRD can provide prognostic insights and enable personalized treatment strategies for patients who achieve complete remission. Although MRD is gradually being integrated into the clinical management of solid tumors, several challenges remain unresolved. This review combines bibliometric analysis with advances in cutting-edge technologies to examine the evolving landscape of MRD, emphasizing its alignment with the predictive, preventive, and personalized medicine (PPPM/3PM) paradigm. By synthesizing research trends, key challenges, and innovative approaches, we highlight the predictive value of MRD for relapse risk, its preventive role in early intervention, and its potential to guide real-time personalized therapies. We advocate for the standardization and integration of MRD monitoring into routine clinical oncology practice, reinforced by expert recommendations grounded in 3PM principles.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-025-00413-8.

Objective: Diabetes and hypertension pose significant health risks, especially when poorly managed. Retinal evaluation though fundus photography can provide non-invasive assessment of these diseases, yet prior studies focused on disease presence, overlooking control statuses. This study evaluated vision transformer (ViT)-based models for assessing the presence and control statuses of diabetes and hypertension from retinal images.

Methods: ViT-based models with ResNet-50 for patch projection were trained on images from the UK Biobank (n = 113,713) and Singapore Epidemiology of Eye Diseases study (n = 17,783), and externally validated on the Singapore Prospective Study Programme (n = 7,793) and the Beijing Eye Study (n = 6064). Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC) for multiple tasks: detecting disease, identifying poorly controlled and well-controlled cases, distinguishing between poorly and well-controlled cases, and detecting pre-diabetes or pre-hypertension.

Results: The models demonstrated strong performance in detecting disease presence, with AUROC values of 0.820 for diabetes and 0.781 for hypertension in internal testing. External validation showed AUROCs ranging from 0.635 to 0.755 for diabetes, and 0.727 to 0.832 for hypertension. For identifying poorly controlled cases, the performance remained high with AUROCs of 0.871 (internal) and 0.655-0.851 (external) for diabetes, and 0.853 (internal) and 0.792-0.915 (external) for hypertension. Detection of well-controlled cases also yielded promising results for diabetes (0.802 [internal]; 0.675-0.838 [external]), and hypertension (0.740 [internal] and 0.675-0.807 [external]). In distinguishing between poorly and well-controlled disease, AUROCs were more modest with 0.630 (internal) and 0.512-0.547 (external) for diabetes, and 0.651 (internal) and 0.639-0.683 (external) for hypertension. For pre-disease detection, the models achieved AUROCs of 0.746 (internal) and 0.523-0.590 (external) for pre-diabetes, and 0.669 (internal) and 0.645-0.679 (external) for pre-hypertension.

Conclusion: ViT-based models show promise in classifying the presence and control statuses of diabetes and hypertension from retinal images. These findings support the potential of retinal imaging as a tool in primary care for opportunistic detection of diabetes and hypertension, risk stratification, and individualised treatment planning. Further validation in diverse clinical settings is warranted to confirm practical utility.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-025-00412-9.