Breast cancer belongs to the most commonly diagnosed malignancies worldwide, with its increasing incidence paralleled by advances in early diagnostics and effective treatments resulting in significantly improved survival rates. However, breast cancer survivors often experience significantly reduced quality of life linked to the long-term health burden as a consequence of aggressive oncological treatments applied. Their most frequently recorded complains include chronic fatigue, reduced physical activity, disordered sleep, chronification of pain, and severe mental health impairments-all per evidence are associated with compromised mitochondrial health and impaired homeostasis. Self-report of a breast cancer survivor is included in this article to illustrate currently uncovered patient needs. This article highlights mechanisms behind the suboptimal health of breast cancer survivors associated with mitochondrial damage, and introduces a novel, mitochondria-based holistic approach addressing rehabilitation concepts for breast cancer survivors following advanced principles of predictive, preventive and personalised medicine (3PM). By operating via mitochondrial function, the proposed holistic approach triggers systemic effects at molecular, sub/cellular and organismal levels positively affecting energy metabolism, repair mechanisms as well as physical and mental health creating, therefore, highly effective rehabilitation algorithms tailored to an individualised patient profile. The proposed methodology integrates mitochondrial health assessments utilising mitochondrial homeostasis biomarkers in tear fluid as a non-invasive diagnostic tool, tailored nutraceuticals and lifestyle adjustments. The introduced approach aligns with advanced principles of 3PM, offering a holistic and proactive framework for managing persistent post-treatment symptoms of suboptimal health in the cohort of cancer survivors. Furthermore, presented approach is also applicable to pre-habilitation programmes considering needs of other patient cohorts affected by chronic diseases such as CVD and orthopaedic disorders with planned major surgical incisions, who require individually adapted pre- and rehabilitation programmes. Implementing such innovative pre- and rehabilitation strategies may lead to a full recovery, sustainable health conditions and, therefore, facilitating patients' comeback to normal daily activities, family and professional life. Contextually, presented approach is considered a 'proof-of-principle' model for the 3PM-related paradigm shift from reactive medicine to a cost-effective holistic health management in both primary and secondary care benefiting a large spectrum of affected patient cohorts, individuals in suboptimal health conditions as well as society at large.
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RATIONALE: Severe alcohol-associated hepatitis (SAH) is the most critical, acute, inflammatory phenotype within the alcohol-associated liver disease (ALD) spectrum, characterized by high 30- and 90-day mortality. Since several decades, corticosteroids (CS) are the only approved pharmacotherapy offering highly limited survival benefits. Contextually, there is an evident demand for 3PM innovation in the area meeting patients' needs and improving individual outcomes. Fecal microbiota transplantation (FMT) has emerged as one of the new potential therapeutic options. In this study, we aimed to address the crucial 3PM domains in order to assess (i) the impact of FMT on mortality in SAH patients beyond CS, (ii) to identify factors associated with the outcome to be improved (iii) the prediction of futility, (iv) prevention of suboptimal individual outcomes linked to increased mortality, and (v) personalized allocation of therapy. METHODS: We conducted a prospective study (NCT04758806) in adult patients with SAH who were non-responders (NR) to or non-eligible (NE) for CS between January 2018 and August 2022. The intervention consisted of five 100 ml of FMT, prepared from 30 g stool from an unrelated healthy donor and frozen at - 80 °C, administered daily to the upper gastrointestinal (GI) tract. We evaluated the impact of FMT on 30- and 90-day mortality which we compared to the control group selected by the propensity score matching and treated by the standard of care; the control group was derived from the RH7 registry of patients hospitalized at the liver unit (NCT04767945). We have also scrutinized the FMT outcome against established and potential prognostic factors for SAH - such as the model for end-stage liver disease (MELD), Maddrey Discriminant Function (MDF), acute-on-chronic liver failure (ACLF), Liver Frailty Index (LFI), hepatic venous-portal pressure gradient (HVPG) and Alcoholic Hepatitis Histologic Score (AHHS) - to see if the 3PM method assigns them a new dimension in predicting response to therapy, prevention of suboptimal individual outcomes, and personalized patient management. RESULTS: We enrolled 44 patients with SAH (NR or NE) on an intention-to-treat basis; we analyzed 33 patients per protocol for associated factors (after an additional 11 being excluded for receiving less than 5 doses of FMT), and 31 patients by propensity score matching for corresponding individual outcomes, respectively. The mean age was 49.6 years, 11 patients (33.3%) were females. The median MELD score was 29, and ACLF of any degree had 27 patients (81.8%). FMT improved 30-day mortality (p = 0.0204) and non-significantly improved 90-day mortality (p = 0.4386). Univariate analysis identified MELD ≥ 30, MDF ≥ 90, and ACLF grade > 1 as significant predictors of 30-day mortality, (p = 0.031; p = 0.014; p = 0.034). Survival was not associated with baseline LFI, HVPG, or AHHS. CONCLUSIONS AND RECOMMENDATIONS IN THE FRAMEWORK OF 3PM: In the most difficult-to-treat sub-cohort of patients with SAH (i.e., NR/NE), FMT improved 30-day mortality. Factors associated with benefit included MELD ≤ 30, MDF ≤ 90, and ACLF < 2. These results support the potential of gut microbiome as a therapeutic target in the context of 3PM research and vice versa - to use 3PM methodology as the expedient unifying template for microbiome research. The results allow for immediate impact on the innovative concepts of (i) personalized phenotyping and stratification of the disease for the clinical research and practice, (ii) multilevel predictive diagnosis related to personalized/precise treatment allocation including evidence-based (ii) prevention of futile and sub-optimally effective therapy, as well as (iii) targeted prevention of poor individual outcomes in patients with SAH. Moreover, our results add to the existing evidence with the potential to generate new research along the SAH's pathogenetic pathways such as diverse individual susceptibility to alcohol toxicity, host-specific mitochondrial function and systemic inflammation, and the role of gut dysbiosis thereof. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-024-00381-5.
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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.
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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.
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Due to the reactive medical approach applied to disease management, stroke has reached an epidemic scale worldwide. In 2019, the global stroke prevalence was 101.5 million people, wherefrom 77.2 million (about 76%) suffered from ischemic stroke; 20.7 and 8.4 million suffered from intracerebral and subarachnoid haemorrhage, respectively. Globally in the year 2019 - 3.3, 2.9 and 0.4 million individuals died of ischemic stroke, intracerebral and subarachnoid haemorrhage, respectively. During the last three decades, the absolute number of cases increased substantially. The current prevalence of stroke is 110 million patients worldwide with more than 60% below the age of 70 years. Prognoses by the World Stroke Organisation are pessimistic: globally, it is predicted that 1 in 4 adults over the age of 25 will suffer stroke in their lifetime. Although age is the best known contributing factor, over 16% of all strokes occur in teenagers and young adults aged 15-49 years and the incidence trend in this population is increasing. The corresponding socio-economic burden of stroke, which is the leading cause of disability, is enormous. Global costs of stroke are estimated at 721 billion US dollars, which is 0.66% of the global GDP. Clinically manifested strokes are only the "tip of the iceberg": it is estimated that the total number of stroke patients is about 14 times greater than the currently applied reactive medical approach is capable to identify and manage. Specifically, lacunar stroke (LS), which is characteristic for silent brain infarction, represents up to 30% of all ischemic strokes. Silent LS, which is diagnosed mainly by routine health check-up and autopsy in individuals without stroke history, has a reported prevalence of silent brain infarction up to 55% in the investigated populations. To this end, silent brain infarction is an independent predictor of ischemic stroke. Further, small vessel disease and silent lacunar brain infarction are considered strong contributors to cognitive impairments, dementia, depression and suicide, amongst others in the general population. In sub-populations such as diabetes mellitus type 2, proliferative diabetic retinopathy is an independent predictor of ischemic stroke. According to various statistical sources, cryptogenic strokes account for 15 to 40% of the entire stroke incidence. The question to consider here is, whether a cryptogenic stroke is fully referable to unidentifiable aetiology or rather to underestimated risks. Considering the latter, translational research might be of great clinical utility to realise innovative predictive and preventive approaches, potentially benefiting high risk individuals and society at large. In this position paper, the consortium has combined multi-professional expertise to provide clear statements towards the paradigm change from reactive to predictive, preventive and personalised medicine in stroke management, the crucial elements of which are:Consolidation of multi-disciplinary expertise including family medicine, predictive and in-depth diagnostics followed by the targeted primary and secondary (e.g. treated cancer) prevention of silent brain infarctionApplication of the health risk assessment focused on sub-optimal health conditions to effectively prevent health-to-disease transitionApplication of AI in medicine, machine learning and treatment algorithms tailored to robust biomarker patternsApplication of innovative screening programmes which adequately consider the needs of young populations.
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Thromboembolism is the third leading vascular disease, with a high annual incidence of 1 to 2 cases per 1000 individuals within the general population. The broader term venous thromboembolism generally refers to deep vein thrombosis, pulmonary embolism, and/or a combination of both. Therefore, thromboembolism can affect both - the central and peripheral veins. Arterial thromboembolism causes systemic ischemia by disturbing blood flow and oxygen supply to organs, tissues, and cells causing, therefore, apoptosis and/or necrosis in the affected tissues. Currently applied antithrombotic drugs used, e.g. to protect affected individuals against ischemic stroke, demonstrate significant limitations. For example, platelet inhibitors possess only moderate efficacy. On the other hand, thrombolytics and anticoagulants significantly increase hemorrhage. Contextually, new approaches are extensively under consideration to develop next-generation antithrombotics with improved efficacy and more personalized and targeted application. To this end, phytochemicals show potent antithrombotic efficacy demonstrated in numerous in vitro, ex vivo, and in vivo models as well as in clinical evaluations conducted on healthy individuals and persons at high risk of thrombotic events, such as pregnant women (primary care), cancer, and COVID-19-affected patients (secondary and tertiary care). Here, we hypothesized that specific antithrombotic and antiplatelet effects of plant-derived compounds might be of great clinical utility in primary, secondary, and tertiary care. To increase the efficacy, precise patient stratification based on predictive diagnostics is essential for targeted protection and treatments tailored to the person in the framework of 3P medicine. Contextually, this paper aims at critical review toward the involvement of specific classes of phytochemicals in antiplatelet and anticoagulation adapted to clinical needs. The paper exemplifies selected plant-derived drugs, plant extracts, and whole plant foods/herbs demonstrating their specific antithrombotic, antiplatelet, and fibrinolytic activities relevant for primary, secondary, and tertiary care. One of the examples considered is antithrombotic and antiplatelet protection specifically relevant for COVID-19-affected patient groups.
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Digital biomarkers are defined as objective, quantifiable physiological and behavioral data that are collected and measured by means of digital devices. Their use has revolutionized clinical research by enabling high-frequency, longitudinal, and sensitive measurements. In the field of neurodegenerative diseases, an example of a digital biomarker-based technology is instrumental activities of daily living (iADL) digital medical application, a predictive biomarker of conversion from mild cognitive impairment (MCI) due to Alzheimer's disease (AD) to dementia due to AD in individuals aged 55 + . Digital biomarkers show promise to transform clinical practice. Nevertheless, their use may be affected by variables such as demographics, genetics, and phenotype. Among these factors, sex is particularly important in Alzheimer's, where men and women present with different symptoms and progression patterns that impact diagnosis. In this study, we explore sex differences in Altoida's digital medical application in a sample of 568 subjects consisting of a clinical dataset (MCI and dementia due to AD) and a healthy population. We found that a biological sex-classifier, built on digital biomarker features captured using Altoida's application, achieved a 75% ROC-AUC (receiver operating characteristic - area under curve) performance in predicting biological sex in healthy individuals, indicating significant differences in neurocognitive performance signatures between males and females. The performance dropped when we applied this classifier to more advanced stages on the AD continuum, including MCI and dementia, suggesting that sex differences might be disease-stage dependent. Our results indicate that neurocognitive performance signatures built on data from digital biomarker features are different between men and women. These results stress the need to integrate traditional approaches to dementia research with digital biomarker technologies and personalized medicine perspectives to achieve more precise predictive diagnostics, targeted prevention, and customized treatment of cognitive decline.Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-022-00284-3.
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Breast cancer incidence is actually the highest one among all cancers. Overall breast cancer management is associated with challenges considering risk assessment and predictive diagnostics, targeted prevention of metastatic disease, appropriate treatment options, and cost-effectiveness of approaches applied. Accumulated research evidence indicates promising anti-cancer effects of phytochemicals protecting cells against malignant transformation, inhibiting carcinogenesis and metastatic spread, supporting immune system and increasing effectiveness of conventional anti-cancer therapies, among others. Molecular and sub-/cellular mechanisms are highly complex affecting several pathways considered potent targets for advanced diagnostics and cost-effective treatments. Demonstrated anti-cancer affects, therefore, are clinically relevant for improving individual outcomes and might be applicable to the primary (protection against initial cancer development), secondary (protection against potential metastatic disease development), and tertiary (towards cascading complications) care. However, a detailed data analysis is essential to adapt treatment algorithms to individuals' and patients' needs. Consequently, advanced concepts of patient stratification, predictive diagnostics, targeted prevention, and treatments tailored to the individualized patient profile are instrumental for the cost-effective application of natural anti-cancer substances to improve overall breast cancer management benefiting affected individuals and the society at large.
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In the early twenty-first century, societies around the world are facing the paradoxal epidemic development of PCa as a non-communicable disease. PCa is the most frequently diagnosed cancer for men in several countries such as the USA. Permanently improving diagnostics and treatments in the PCa management causes an impressive divergence between, on one hand, permanently increasing numbers of diagnosed PCa cases and, on the other hand, stable or even slightly decreasing mortality rates. Still, aspects listed below are waiting for innovate solutions in the context of predictive approaches, targeted prevention and personalisation of medical care (PPPM / 3PM).A.PCa belongs to the cancer types with the highest incidence worldwide. Corresponding economic burden is enormous. Moreover, the costs of treating PCa are currently increasing more quickly than those of any other cancer. Implementing individualised patient profiles and adapted treatment algorithms would make currently too heterogeneous landscape of PCa treatment costs more transparent providing clear "road map" for the cost saving.B.PCa is a systemic multi-factorial disease. Consequently, predictive diagnostics by liquid biopsy analysis is instrumental for the disease prediction, targeted prevention and curative treatments at early stages.C.The incidence of metastasising PCa is rapidly increasing particularly in younger populations. Exemplified by trends observed in the USA, prognosis is that the annual burden will increase by over 40% in 2025. To this end, one of the evident deficits is the reactive character of medical services currently provided to populations. Innovative screening programmes might be useful to identify persons in suboptimal health conditions before the clinical onset of metastasising PCa. Strong predisposition to systemic hypoxic conditions and ischemic lesions (e.g. characteristic for individuals with Flammer syndrome phenotype) and low-grade inflammation might be indicative for specific phenotyping and genotyping in metastasising PCa screening and disease management. Predictive liquid biopsy tests for CTC enumeration and their molecular characterisation are considered to be useful for secondary prevention of metastatic disease in PCa patients.D.Particular rapidly increasing PCa incidence rates are characteristic for adolescents and young adults aged 15-40 years. Patients with early onset prostate cancer pose unique challenges; multi-factorial risks for these trends are proposed. Consequently, multi-level diagnostics including phenotyping and multi-omics are considered to be the most appropriate tool for the risk assessment, prediction and prognosis. Accumulating evidence suggests that early onset prostate cancer is a distinct phenotype from both aetiological and clinical perspectives deserving particular attention from view point of 3P medical approaches.
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Biobanking is entering the new era-era of big data. New technologies, techniques, and knowledge opened the potential of the whole domain of biobanking. Biobanks collect, analyse, store, and share the samples and associated data. Both samples and especially associated data are growing enormously, and new innovative approaches are required to handle samples and to utilize the potential of biobanking data. The data reached the quantity and quality of big data, and the scientists are facing the questions how to use them more efficiently, both retrospectively and prospectively with the aim to discover new preventive methods, optimize treatment, and follow up and to optimize healthcare processes. Biobanking in the era of big data contribute to the development of predictive, preventive, and personalised medicine, for every patient providing the right treatment at the right time. Biobanking in the era of big data contributes to the paradigm shift towards personalising of healthcare.
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