Ischemic stroke of unclear aetiology: a case-by-case analysis and call for a multi-professional predictive, preventive and personalised approach

Energy metabolism as the hub of advanced non-small cell lung cancer management: a comprehensive view in the framework of predictive, preventive, and personalized medicine

Energy metabolism is a hub of governing all processes at cellular and organismal levels such as, on one hand, reparable vs. irreparable cell damage, cell fate (proliferation, survival, apoptosis, malignant transformation etc.), and, on the other hand, carcinogenesis, tumor development, progression and metastazing versus anti-cancer protection and cure. The orchestrator is the mitochondria who produce, store and invest energy, conduct intracellular and systemically relevant signals decisive for internal and environmental stress adaptation, and coordinate corresponding processes at cellular and organismal levels. Consequently, the quality of mitochondrial health and homeostasis is a reliable target for health risk assessment at the stage of reversible damage to the health followed by cost-effective personalized protection against health-to-disease transition as well as for targeted protection against the disease progression (secondary care of cancer patients against growing primary tumors and metastatic disease). The energy reprogramming of non-small cell lung cancer (NSCLC) attracts particular attention as clinically relevant and instrumental for the paradigm change from reactive medical services to predictive, preventive and personalized medicine (3PM). This article provides a detailed overview towards mechanisms and biological pathways involving metabolic reprogramming (MR) with respect to inhibiting the synthesis of biomolecules and blocking common NSCLC metabolic pathways as anti-NSCLC therapeutic strategies. For instance, mitophagy recycles macromolecules to yield mitochondrial substrates for energy homeostasis and nucleotide synthesis. Histone modification and DNA methylation can predict the onset of diseases, and plasma C7 analysis is an efficient medical service potentially resulting in an optimized healthcare economy in corresponding areas. The MEMP scoring provides the guidance for immunotherapy, prognostic assessment, and anti-cancer drug development. Metabolite sensing mechanisms of nutrients and their derivatives are potential MR-related therapy in NSCLC. Moreover, miR-495-3p reprogramming of sphingolipid rheostat by targeting Sphk1, 22/FOXM1 axis regulation, and A2 receptor antagonist are highly promising therapy strategies. TFEB as a biomarker in predicting immune checkpoint blockade and redox-related lncRNA prognostic signature (redox-LPS) are considered reliable predictive approaches. Finally, exemplified in this article metabolic phenotyping is instrumental for innovative population screening, health risk assessment, predictive multi-level diagnostics, targeted prevention, and treatment algorithms tailored to personalized patient profiles-all are essential pillars in the paradigm change from reactive medical services to 3PM approach in overall management of lung cancers. This article highlights the 3PM relevant innovation focused on energy metabolism as the hub to advance NSCLC management benefiting vulnerable subpopulations, affected patients, and healthcare at large.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00357-5.

Mini-encyclopedia of mitochondria-relevant nutraceuticals protecting health in primary and secondary care-clinically relevant 3PM innovation

Despite their subordination in humans, to a great extent, mitochondria maintain their independent status but tightly cooperate with the "host" on protecting the joint life quality and minimizing health risks. Under oxidative stress conditions, healthy mitochondria promptly increase mitophagy level to remove damaged "fellows" rejuvenating the mitochondrial population and sending fragments of mtDNA as SOS signals to all systems in the human body. As long as metabolic pathways are under systemic control and well-concerted together, adaptive mechanisms become triggered increasing systemic protection, activating antioxidant defense and repair machinery. Contextually, all attributes of mitochondrial patho-/physiology are instrumental for predictive medical approach and cost-effective treatments tailored to individualized patient profiles in primary (to protect vulnerable individuals again the health-to-disease transition) and secondary (to protect affected individuals again disease progression) care. Nutraceuticals are naturally occurring bioactive compounds demonstrating health-promoting, illness-preventing, and other health-related benefits. Keeping in mind health-promoting properties of nutraceuticals along with their great therapeutic potential and safety profile, there is a permanently growing demand on the application of mitochondria-relevant nutraceuticals. Application of nutraceuticals is beneficial only if meeting needs at individual level. Therefore, health risk assessment and creation of individualized patient profiles are of pivotal importance followed by adapted nutraceutical sets meeting individual needs. Based on the scientific evidence available for mitochondria-relevant nutraceuticals, this article presents examples of frequent medical conditions, which require protective measures targeted on mitochondria as a holistic approach following advanced concepts of predictive, preventive, and personalized medicine (PPPM/3PM) in primary and secondary care.

Mediterranean diet in the targeted prevention and personalized treatment of chronic diseases: evidence, potential mechanisms, and prospects

The prevalence of chronic diseases is currently a major public health issue worldwide and is exploding with the population growth and aging. Dietary patterns are well known to play a important role in our overall health and well-being, and therefore, poor diet and malnutrition are among the most critical risk factors for chronic disease. Thus, dietary recommendation and nutritional supplementation have significant clinical implications for the targeted treatment of some of these diseases. Multiple dietary patterns have been proposed to prevent chronic disease incidence, like Dietary Approaches to Stop Hypertension (DASH) and Diabetes Risk Reduction Diet (DRRD). Among them, the MedDiet, which is one of the most well-known and studied dietary patterns in the world, has been related to a wide extent of health benefits. Substantial evidence has supported an important reverse association between higher compliance to MedDiet and the risk of chronic disease. Innovative strategies within the healthcare framework of predictive, preventive, and personalized medicine (PPPM/3PM) view personalized dietary customization as a predictive medical approach, cost-effective preventive measures, and the optimal dietary treatment tailored to the characteristics of patients with chronic diseases in primary and secondary care. Through a comprehensive collection and review of available evidence, this review summarizes health benefits of MedDiet in the context of PPPM/3PM for chronic diseases, including cardiovascular disease, hypertension, type 2 diabetes, obesity, metabolic syndrome, osteoporosis, and cancer, thereby a working hypothesis that MedDiet can personalize the prevention and treatment of chronic diseases was derived.

Personalized Drug Therapy: Innovative Concept Guided With Proteoformics

Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy and are currently the mainstay, which possess higher target specificity and biological activity than small-molecule chemical drugs, making them efficient in regulating disease-related biological processes, and have significant potential in the development of personalized drugs. Currently, protein drugs are designed and developed for specific protein targets based on patient-specific protein data. However, due to the rapid development of two-dimensional gel electrophoresis and mass spectrometry, it is now widely recognized that a canonical protein actually includes multiple proteoforms, and the differences between these proteoforms will result in varying responses to drugs. The variation in the effects of different proteoforms can be significant and the impact can even alter the intended benefit of a drug, potentially making it harmful instead of lifesaving. As a result, we propose that protein drugs should shift from being targeted through the lens of protein (proteomics) to being targeted through the lens of proteoform (proteoformics). This will enable the development of personalized protein drugs that are better equipped to meet patients' specific needs and disease characteristics. With further development in the field of proteoformics, individualized drug therapy, especially personalized protein drugs aimed at proteoforms as a drug target, will improve the understanding of disease mechanisms, discovery of new drug targets and signaling pathways, provide a theoretical basis for the development of new drugs, aid doctors in conducting health risk assessments and making more cost-effective targeted prevention strategies conducted by artificial intelligence/machine learning, promote technological innovation, and provide more convenient treatment tailored to individualized patient profile, which will benefit the affected individuals and society at large.

The mediating effect of perceived stress on the relationship between big five personality traits and suboptimal health status in Chinese population: a nationwide survey in the framework of predictive, preventive, and personalized medicine

Background

The effects of psychological factors on suboptimal health status (SHS) have been widely described; however, mechanisms behind the complex relationships among the Big Five personality traits and SHS are unclear. Identifying people with specific traits who are susceptible to SHS will help improve life quality and reduce the chronic disease burden under the framework of predictive, preventive, and personalized medicine (PPPM / 3PM). This study investigated the relationships among personality traits and SHS. It also explored whether perceived stress plays a mediating role in SHS development.

Method

A nationwide cross-sectional survey based on multistage random sampling was conducted in 148 cities in China between June 20 and August 31, 2022. Personality traits, perceived stress, and SHS were evaluated using the Big Five Inventory-10 (BFI-10), the 4-item Perceived Stress Scale (PSS-4), and the Short-Form Suboptimal Health Status Questionnaire (SHSQ-SF), respectively. Pearson's correlation analysis was employed to examine the associations between personality traits, perceived stress, and SHS. Structural equation modeling (SEM) was used to discern the mediating role of perceived stress in the relationships among personality traits and SHS.

Result

A total of 22,897 participants were enrolled in this study, among whom the prevalence of SHS was 52.9%. SHS was negatively correlated with three trait dimensions (i.e., extraversion, agreeableness, and conscientiousness) but positively correlated with neuroticism. Meanwhile, stress was negatively correlated with extraversion, agreeableness, conscientiousness, and openness, whereas it was positively correlated with neuroticism. The SEM results showed that, when adjusting for covariates (i.e., gender, age, BMI, educational level, current residence, marital status, and occupational status), higher agreeableness (β =  - 0.049, P < 0.001) and conscientiousness (β =  - 0.103, P < 0.001) led to lower SHS prevalence, higher neuroticism (β = 0.130, P < 0.001), and openness (β = 0.026, P < 0.001) caused SHS to be more prevalent. Perceived stress played a partial mediating role in the relationships among personality traits and SHS, respectively, contributing 41.3%, 35.9%, and 32.5% to the total effects of agreeableness, conscientiousness, and neuroticism on SHS. Additionally, the mediating impact of stress was significant even though extraversion had no direct effect on SHS.

Conclusion

This study revealed a high prevalence of SHS in Chinese residents. Personality traits significantly influenced SHS rates, which perceived stress tended to mediate. From a PPPM perspective, early screening and targeted intervention for people with neuroticism (as well as stress alleviation) might contribute to health enhancement and chronic disease prevention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00349-x.

Cancer screening in hospitalized ischemic stroke patients: a multicenter study focused on multiparametric analysis to improve management of occult cancers

Background/aims

The reciprocal promotion of cancer and stroke occurs due to changes in shared risk factors, such as metabolic pathways and molecular targets, creating a "vicious cycle." Cancer plays a direct or indirect role in the pathogenesis of ischemic stroke (IS), along with the reactive medical approach used in the treatment and clinical management of IS patients, resulting in clinical challenges associated with occult cancer in these patients. The lack of reliable and simple tools hinders the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) approach. Therefore, we conducted a multicenter study that focused on multiparametric analysis to facilitate early diagnosis of occult cancer and personalized treatment for stroke associated with cancer.

Methods

Admission routine clinical examination indicators of IS patients were retrospectively collated from the electronic medical records. The training dataset comprised 136 IS patients with concurrent cancer, matched at a 1:1 ratio with a control group. The risk of occult cancer in IS patients was assessed through logistic regression and five alternative machine-learning models. Subsequently, select the model with the highest predictive efficacy to create a nomogram, which is a quantitative tool for predicting diagnosis in clinical practice. Internal validation employed a ten-fold cross-validation, while external validation involved 239 IS patients from six centers. Validation encompassed receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and comparison with models from prior research.

Results

The ultimate prediction model was based on logistic regression and incorporated the following variables: regions of ischemic lesions, multiple vascular territories, hypertension, D-dimer, fibrinogen (FIB), and hemoglobin (Hb). The area under the ROC curve (AUC) for the nomogram was 0.871 in the training dataset and 0.834 in the external test dataset. Both calibration curves and DCA underscored the nomogram's strong performance.

Conclusions

The nomogram enables early occult cancer diagnosis in hospitalized IS patients and helps to accurately identify the cause of IS, while the promotion of IS stratification makes personalized treatment feasible. The online nomogram based on routine clinical examination indicators of IS patients offered a cost-effective platform for secondary care in the framework of PPPM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00354-8.

Automated detection of nine infantile fundus diseases and conditions in retinal images using a deep learning system

Purpose

We developed an Infant Retinal Intelligent Diagnosis System (IRIDS), an automated system to aid early diagnosis and monitoring of infantile fundus diseases and health conditions to satisfy urgent needs of ophthalmologists.

Methods

We developed IRIDS by combining convolutional neural networks and transformer structures, using a dataset of 7697 retinal images (1089 infants) from four hospitals. It identifies nine fundus diseases and conditions, namely, retinopathy of prematurity (ROP) (mild ROP, moderate ROP, and severe ROP), retinoblastoma (RB), retinitis pigmentosa (RP), Coats disease, coloboma of the choroid, congenital retinal fold (CRF), and normal. IRIDS also includes depth attention modules, ResNet-18 (Res-18), and Multi-Axis Vision Transformer (MaxViT). Performance was compared to that of ophthalmologists using 450 retinal images. The IRIDS employed a five-fold cross-validation approach to generate the classification results.

Results

Several baseline models achieved the following metrics: accuracy, precision, recall, F1-score (F1), kappa, and area under the receiver operating characteristic curve (AUC) with best values of 94.62% (95% CI, 94.34%-94.90%), 94.07% (95% CI, 93.32%-94.82%), 90.56% (95% CI, 88.64%-92.48%), 92.34% (95% CI, 91.87%-92.81%), 91.15% (95% CI, 90.37%-91.93%), and 99.08% (95% CI, 99.07%-99.09%), respectively. In comparison, IRIDS showed promising results compared to ophthalmologists, demonstrating an average accuracy, precision, recall, F1, kappa, and AUC of 96.45% (95% CI, 96.37%-96.53%), 95.86% (95% CI, 94.56%-97.16%), 94.37% (95% CI, 93.95%-94.79%), 95.03% (95% CI, 94.45%-95.61%), 94.43% (95% CI, 93.96%-94.90%), and 99.51% (95% CI, 99.51%-99.51%), respectively, in multi-label classification on the test dataset, utilizing the Res-18 and MaxViT models. These results suggest that, particularly in terms of AUC, IRIDS achieved performance that warrants further investigation for the detection of retinal abnormalities.

Conclusions

IRIDS identifies nine infantile fundus diseases and conditions accurately. It may aid non-ophthalmologist personnel in underserved areas in infantile fundus disease screening. Thus, preventing severe complications. The IRIDS serves as an example of artificial intelligence integration into ophthalmology to achieve better outcomes in predictive, preventive, and personalized medicine (PPPM / 3PM) in the treatment of infantile fundus diseases.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00350-y.

The paradigm change from reactive medical services to 3PM in ischemic stroke: a holistic approach utilising tear fluid multi-omics, mitochondria as a vital biosensor and AI-based multi-professional data interpretation

Worldwide stroke is the second leading cause of death and the third leading cause of death and disability combined. The estimated global economic burden by stroke is over US$891 billion per year. Within three decades (1990-2019), the incidence increased by 70%, deaths by 43%, prevalence by 102%, and DALYs by 143%. Of over 100 million people affected by stroke, about 76% are ischemic stroke (IS) patients recorded worldwide. Contextually, ischemic stroke moves into particular focus of multi-professional groups including researchers, healthcare industry, economists, and policy-makers. Risk factors of ischemic stroke demonstrate sufficient space for cost-effective prevention interventions in primary (suboptimal health) and secondary (clinically manifested collateral disorders contributing to stroke risks) care. These risks are interrelated. For example, sedentary lifestyle and toxic environment both cause mitochondrial stress, systemic low-grade inflammation and accelerated ageing; inflammageing is a low-grade inflammation associated with accelerated ageing and poor stroke outcomes. Stress overload, decreased mitochondrial bioenergetics and hypomagnesaemia are associated with systemic vasospasm and ischemic lesions in heart and brain of all age groups including teenagers. Imbalanced dietary patterns poor in folate but rich in red and processed meat, refined grains, and sugary beverages are associated with hyperhomocysteinaemia, systemic inflammation, small vessel disease, and increased IS risks. Ongoing 3PM research towards vulnerable groups in the population promoted by the European Association for Predictive, Preventive and Personalised Medicine (EPMA) demonstrates promising results for the holistic patient-friendly non-invasive approach utilising tear fluid-based health risk assessment, mitochondria as a vital biosensor and AI-based multi-professional data interpretation as reported here by the EPMA expert group. Collected data demonstrate that IS-relevant risks and corresponding molecular pathways are interrelated. For examples, there is an evident overlap between molecular patterns involved in IS and diabetic retinopathy as an early indicator of IS risk in diabetic patients. Just to exemplify some of them such as the 5-aminolevulinic acid/pathway, which are also characteristic for an altered mitophagy patterns, insomnia, stress regulation and modulation of microbiota-gut-brain crosstalk. Further, ceramides are considered mediators of oxidative stress and inflammation in cardiometabolic disease, negatively affecting mitochondrial respiratory chain function and fission/fusion activity, altered sleep-wake behaviour, vascular stiffness and remodelling. Xanthine/pathway regulation is involved in mitochondrial homeostasis and stress-driven anxiety-like behaviour as well as molecular mechanisms of arterial stiffness. In order to assess individual health risks, an application of machine learning (AI tool) is essential for an accurate data interpretation performed by the multiparametric analysis. Aspects presented in the paper include the needs of young populations and elderly, personalised risk assessment in primary and secondary care, cost-efficacy, application of innovative technologies and screening programmes, advanced education measures for professionals and general population-all are essential pillars for the paradigm change from reactive medical services to 3PM in the overall IS management promoted by the EPMA.

CADASIL: A NOTCH3-associated cerebral small vessel disease

BACKGROUND

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common hereditary cerebral small vessel disease (CSVD), pathologically characterized by a non-atherosclerotic and non-amyloid diffuse angiopathy primarily involving small to medium-sized penetrating arteries and leptomeningeal arteries. In 1996, mutation in the notch receptor 3 gene (NOTCH3) was identified as the cause of CADASIL. However, since that time other genetic CSVDs have been described, including the HtrA serine peptidase 1 gene-associated CSVD and the cathepsin A gene-associated CSVD, that clinically mimic the original phenotype. Though NOTCH3-associated CSVD is now a well-recognized hereditary disorder and the number of studies investigating this disease is increasing, the role of NOTCH3 in the pathogenesis of CADASIL remains elusive.

AIM OF REVIEW

This review aims to provide insights into the pathogenesis and the diagnosis of hereditary CSVDs, as well as personalized therapy, predictive approach, and targeted prevention. In this review, we summarize the current progress in CADASIL, including the clinical, neuroimaging, pathological, genetic, diagnostic, and therapeutic aspects, as well as differential diagnosis, in which the role of NOTCH3 mutations is highlighted.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In this review, CADASIL is revisited as a NOTCH3-associated CSVD along with other hereditary CSVDs.

Quality of life and cost-effectiveness of different breast cancer surgery procedures: a Markov decision tree-based approach in the framework of Predictive, Preventive, and Personalized Medicine

Purpose

Breast cancer is a complex disease with heterogeneous outcomes that may benefit from the implementation of Predictive, Preventive, and Personalized Medicine (PPPM/3PM) strategies. In this study, we aimed to explore the potential of PPPM approaches by investigating the 10-year trends in quality of life (QOL) and the cost-effectiveness of different types of surgeries for patients with breast cancer.

Methods

This prospective cohort study recruited 144 patients undergoing breast conserving surgery (BCS), 199 undergoing modified radical mastectomy (MRM), and 44 undergoing total mastectomy with transverse rectus abdominis myocutaneous flap (TRAMF) from three medical centers in Taiwan between June 2007 and June 2010.

Results

All patients exhibited a significant decrease in most QOL dimension scores from before surgery to 6 months postoperatively (p < 0.05); however, from postoperative year 1 to 2, improvement in most QOL dimension scores was significantly better in the TRAMF group than in the BCS and MRM groups (p < 0.05). At 2, 5, and 10 years after surgery, the patients' QOL remained stable. In the Markov decision tree model, the TRAMF group had higher total direct medical costs than the MRM and BCS groups (US$ 32,426, US$ 29,487, and US$ 28,561, respectively) and higher average QALYs gained (7.771, 6.773, and 7.385, respectively), with an incremental cost-utility ratio (ICUR) of US$ 2,944.39 and US$ 10,013.86 per QALY gained.

Conclusions

TRAMF appeared cost effective compared with BCS and MRM, and it has been proved with considerable QOL improvements in the framework of PPPM. Future studies should continue to explore the potential of PPPM approaches in breast cancer care. By incorporating predictive models, personalized treatment plans, and preventive strategies into routine clinical practice, we can further optimize patient outcomes and reduce healthcare costs associated with breast cancer treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00326-4.

Identification of potential necroinflammation-associated necroptosis-related biomarkers for delayed graft function and renal allograft failure: a machine learning-based exploration in the framework of predictive, preventive, and personalized medicine

Delayed graft function (DGF) is one of the key post-operative challenges for a subset of kidney transplantation (KTx) patients. Graft survival is significantly lower in recipients who have experienced DGF than in those who have not. Assessing the risk of chronic graft injury, predicting graft rejection, providing personalized treatment, and improving graft survival are major strategies for predictive, preventive, and personalized medicine (PPPM/3PM) to promote the development of transplant medicine. However, since PPPM aims to accurately identify disease by integrating multiple omics, current methods to predict DGF and graft survival can still be improved. Renal ischemia/reperfusion injury (IRI) is a pathological process experienced by all KTx recipients that can result in varying occurrences of DGF, chronic rejection, and allograft failure depending on its severity. During this process, a necroinflammation-mediated necroptosis-dependent secondary wave of cell death significantly contributes to post-IRI tubular cell loss. In this article, we obtained the expression matrices and corresponding clinical data from the GEO database. Subsequently, nine differentially expressed necroinflammation-associated necroptosis-related genes (NiNRGs) were identified by correlation and differential expression analysis. The subtyping of post-KTx IRI samples relied on consensus clustering; the grouping of prognostic risks and the construction of predictive models for DGF (the area under the receiver operating characteristic curve (AUC) of the internal validation set and the external validation set were 0.730 and 0.773, respectively) and expected graft survival after a biopsy (the internal validation set's 1-year AUC: 0.770; 2-year AUC: 0.702; and 3-year AUC: 0.735) were based on the least absolute shrinkage and selection operator regression algorithms. The results of the immune infiltration analysis showed a higher infiltration abundance of myeloid immune cells, especially neutrophils, macrophages, and dendritic cells, in the cluster A subtype and prognostic high-risk groups. Therefore, in the framework of PPPM, this work provides a comprehensive exploration of the early expression landscape, related pathways, immune features, and prognostic impact of NiNRGs in post-KTx patients and assesses their capabilities as.predictors of post-KTx DGF and graft loss,targets of the vicious loop between regulated tubular cell necrosis and necroinflammation for targeted secondary and tertiary prevention, andreferences for personalized immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00320-w.

Multi-faceted CRISPR/Cas technological innovation aspects in the framework of 3P medicine

Since 2009, the European Association for Predictive, Preventive and Personalised Medicine (EPMA, Brussels) promotes the paradigm change from reactive approach to predictive, preventive, and personalized medicine (PPPM/3PM) to protect individuals in sub-optimal health conditions from the health-to-disease transition, to increase life-quality of the affected patient cohorts improving, therefore, ethical standards and cost-efficacy of healthcare to great benefits of the society at large. The gene-editing technology utilizing CRISPR/Cas gene-editing approach has demonstrated its enormous value as a powerful tool in a broad spectrum of bio/medical research areas. Further, CRISPR/Cas gene-editing system is considered applicable to primary and secondary healthcare, in order to prevent disease spread and to treat clinically manifested disorders, involving diagnostics of SARS-Cov-2 infection and experimental treatment of COVID-19. Although the principle of the proposed gene editing is simple and elegant, there are a lot of technological challenges and ethical considerations to be solved prior to its broadly scaled clinical implementation. This article highlights technological innovation beyond the state of the art, exemplifies current achievements, discusses unsolved technological and ethical problems, and provides clinically relevant outlook in the framework of 3PM.

Gut microbiome plays a vital role in post-stroke injury repair by mediating neuroinflammation

Cerebral stroke is a common neurological disease and often causes severe neurological deficits. With high morbidity, mortality, and disability rates, stroke threatens patients' life quality and brings a heavy economic burden on society. Ischemic cerebral lesions incur pathological changes as well as spontaneous nerve repair following stroke. Strategies such as drug therapy, physical therapy, and surgical treatment, can ameliorate blood and oxygen supply in the brain, hamper the inflammatory responses and maintain the structural and functional integrity of the brain. The gut microbiome, referred to as the "second genome" of the human body, participates in the regulation of multiple physiological functions including metabolism, digestion, inflammation, and immunity. The gut microbiome is not only inextricably associated with dangerous factors pertaining to stroke, including high blood pressure, diabetes, obesity, and atherosclerosis, but also influences stroke occurrence and prognosis. AMPK functions as a hub of metabolic control and is responsible for the regulation of metabolic events under physiological and pathological conditions. The AMPK mediators have been found to exert dual roles in regulating gut microbiota and neuroinflammation/neuronal apoptosis in stroke. In this study, we reviewed the role of the gut microbiome in cerebral stroke and the underlying mechanism of the AMPK signaling pathway in stroke. AMPK mediators in nerve repair and the regulation of intestinal microbial balance were also summarized.

Development and validation of a routine blood parameters-based model for screening the occurrence of retinal detachment in high myopia in the context of PPPM

Background/aims

Timely detection and treatment of retinal detachment (RD) could effectively save vision and reduce the risk of progressing visual field defects. High myopia (HM) is known to be associated with an increased risk of RD. Evidently, it should be clearly discriminated the individuals with high or low risk of RD in patients with HM. By using multi-parametric analysis, risk assessment, and other techniques, it is crucial to create cutting-edge screening programs that may be utilized to improve population eye health and develop person-specific, cost-effective preventative, and targeted therapeutic measures. Therefore, we propose a novel, routine blood parameters-based prediction model as a screening program to help distinguish who should offer detailed ophthalmic examinations for RD diagnosis, prevent visual field defect progression, and provide personalized, serial monitoring in the context of predictive, preventive, and personalized medicine (PPPM/3 PM).

Methods

This population-based study included 20,870 subjects (HM = 19,284, HMRD = 1586) who underwent detailed routine blood tests and ophthalmic evaluations. HMRD cases and HM controls were matched using a nested case-control design. Then, the HMRD cases and HM controls were randomly assigned to the discovery cohort, validation cohort 1, and validation cohort 2 maintaining a 6:2:2 ratio, and other subjects were assigned to the HM validation cohort. Receiver operating characteristic curve analysis was performed to select feature indexes. Feature indexes were integrated into seven algorithm models, and an optimal model was selected based on the highest area under the curve (AUC) and accuracy.

Results

Six feature indexes were selected: lymphocyte, basophil, mean platelet volume, platelet distribution width, neutrophil-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio. Among the algorithm models, the algorithm of conditional probability (ACP) showed the best performance achieving an AUC of 0.79, a diagnostic accuracy of 0.72, a sensitivity of 0.71, and a specificity of 0.74 in the discovery cohort. A good performance of the ACP model was also observed in the validation cohort 1 (AUC = 0.81, accuracy = 0.72, sensitivity = 0.71, specificity = 0.73) and validation cohort 2 (AUC = 0.77, accuracy = 0.71, sensitivity = 0.70, specificity = 0.72). In addition, ACP model calibration was found to be good across three cohorts. In the HM validation cohort, the ACP model achieved a diagnostic accuracy of 0.81 for negative classification.

Conclusion

We have developed a routine blood parameters-based model with an ACP algorithm that could potentially be applied in the clinic with a PPPM approach for serial monitoring and predicting the occurrence of RD in HM and can facilitate the prevention of HM progression to RD. According to the current study, routine blood measures are essential in patient risk classification, predictive diagnosis, and targeted therapy. Therefore, for high-risk RD persons, novel screening programs and prompt treatment plans are essential to enhance individual outcomes and healthcare offered to the community with HM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00319-3.

Short communication: unique metabolic signature of proliferative retinopathy in the tear fluid of diabetic patients with comorbidities - preliminary data for PPPM validation

Type 2 diabetes (T2DM) defined as the adult-onset type that is primarily not insulin-dependent, comprises over 95% of all diabetes mellitus (DM) cases. According to global records, 537 million adults aged 20-79 years are affected by DM that means at least 1 out of 15 persons. This number is projected to grow by 51% by the year 2045. One of the most common complications of T2DM is diabetic retinopathy (DR) with an overall prevalence over 30%. The total number of the DR-related visual impairments is on the rise, due to the growing T2DM population. Proliferative diabetic retinopathy (PDR) is the progressing DR and leading cause of preventable blindness in working-age adults. Moreover, PDR with characteristic systemic attributes including mitochondrial impairment, increased cell death and chronic inflammation, is an independent predictor of the cascading DM-complications such as ischemic stroke. Therefore, early DR is a reliable predictor appearing upstream of this "domino effect". Global screening, leading to timely identification of DM-related complications, is insufficiently implemented by currently applied reactive medicine. A personalised predictive approach and cost-effective targeted prevention shortly - predictive, preventive and personalised medicine (PPPM / 3PM) could make a good use of the accumulated knowledge, preventing blindness and other severe DM complications. In order to reach this goal, reliable stage- and disease-specific biomarker panels are needed characterised by an easy way of the sample collection, high sensitivity and specificity of analyses. In the current study, we tested the hypothesis that non-invasively collected tear fluid is a robust source for the analysis of ocular and systemic (DM-related complications) biomarker patterns suitable for differential diagnosis of stable DR versus PDR. Here, we report the first results of the comprehensive ongoing study, in which we correlate individualised patient profiles (healthy controls versus patients with stable D as well as patients with PDR with and without co-morbidities) with their metabolic profiles in the tear fluid. Comparative mass spectrometric analysis performed has identified following metabolic clusters which are differentially expressed in the groups of comparison: acylcarnitines, amino acid & related compounds, bile acids, ceramides, lysophosphatidyl-choline, nucleobases & related compounds, phosphatidyl-cholines, triglycerides, cholesterol esters, and fatty acids. Our preliminary data strongly support potential clinical utility of metabolic patterns in the tear fluid indicating a unique metabolic signature characteristic for the DR stages and PDR progression. This pilot study creates a platform for validating the tear fluid biomarker patterns to stratify T2DM-patients predisposed to the PDR. Moreover, since PDR is an independent predictor of severe T2DM-related complications such as ischemic stroke, our international project aims to create an analytical prototype for the "diagnostic tree" (yes/no) applicable to healthrisk assessment in diabetes care.

Diabetic retinopathy as the leading cause of blindness and early predictor of cascading complications-risks and mitigation

Proliferative diabetic retinopathy (PDR) the sequel of diabetic retinopathy (DR), a frequent complication of diabetes mellitus (DM), is the leading cause of blindness in the working-age population. The current screening process for the DR risk is not sufficiently effective such that often the disease is undetected until irreversible damage occurs. Diabetes-associated small vessel disease and neuroretinal changes create a vicious cycle resulting in the conversion of DR into PDR with characteristic ocular attributes including excessive mitochondrial and retinal cell damage, chronic inflammation, neovascularisation, and reduced visual field. PDR is considered an independent predictor of other severe diabetic complications such as ischemic stroke. A "domino effect" is highly characteristic for the cascading DM complications in which DR is an early indicator of impaired molecular and visual signaling. Mitochondrial health control is clinically relevant in DR management, and multi-omic tear fluid analysis can be instrumental for DR prognosis and PDR prediction. Altered metabolic pathways and bioenergetics, microvascular deficits and small vessel disease, chronic inflammation, and excessive tissue remodelling are in focus of this article as evidence-based targets for a predictive approach to develop diagnosis and treatment algorithms tailored to the individual for a cost-effective early prevention by implementing the paradigm shift from reactive medicine to predictive, preventive, and personalized medicine (PPPM) in primary and secondary DR care management.