Pre-pregnancy check-up of maternal vascular status and associated phenotype is crucial for the health of mother and offspring

Comprehensive genome-wide analysis of retinal vessel caliber reveals microvascular-blood pressure pathways: advancing predictive, preventive, and personalized medicine

Background

Retinal vessel caliber is strongly associated with systemic blood pressure (BP); however, the causal relationship between retinal vascular caliber and BP remains unclear. Understanding this relationship is essential for advancing predictive, preventive, and personalized medicine (PPPM) approaches to effectively manage hypertension and its related complications.

Working hypothesis

Microvessel morphology is causally related to blood pressure. By integrating genome-wide association studies, Mendelian randomization analysis, transcriptomic data, and multivariate genomic approaches, this study aims to identify predictive biomarkers, uncover preventive strategies, and develop personalized intervention targets, thereby advancing the principles of 3P medicine for improved cardiovascular health management.

Methods and results

We conducted a comprehensive investigation into the genetic factors underlying retinal vessel calibers and their complex relationship with BP traits. Our genome-wide association study (GWAS) assess retinal vessel calibers-central retinal arteriolar equivalent (CRAE), central retinal venular equivalent (CRVE), and the arteriole-to-venule ratio (AVR)-in a subset of 36,223 individuals of European descent from the UK Biobank. The analysis identified 9, 5, and 4 SNPs located in TNS, Y_RNA, PBLD, C10orf32-ASMT:AS3MT, GNB3:CDCA3, NTN4, COL4 A2, CTD-2378E21.1, WNT7B, VTA1, FCF1, NPLOC4, FUT1 and CSK region, which are significantly associated with CRAE, CRVE, and AVR, respectively. Genetic correlation analysis revealed shared heritability between BP traits and both CRAE and AVR, but not CRVE. Mendelian randomization analysis confirmed bidirectional causal relationships between CRAE and BP traits, whereas CRVE was neither influenced by nor influenced BP traits. To explore the potential regulatory mechanisms, we leveraged transcriptomic data and identified the following causal pathways in vessel tissue: The expression of MRPL23-AS1 and ULK3 was correlated with the elevation of blood pressure SBP and narrowing of the CRAE. Finally, we constructed a multivariable genetic model including CRAE, AVR, SBP, and DBP, suggesting a common driving factor which underlies these traits.

Conclusions

Our study elucidates the complex relationship between BP and retinal vessel caliber, highlighting potential intervention targets for lowering BP and vascular narrowing-related diseases. These findings contribute to the development of tailored prevention and treatment strategies aligned with PPPM principles.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-025-00411-w.

Maternal Metabolic Health and Mother and Baby Health Outcomes (MAMBO): Protocol of a Prospective Observational Study

BACKGROUND

Metabolic disease is increasingly impacting women of reproductive age. In pregnancy, uncontrolled metabolic disease can result in offspring with major congenital anomalies, preterm birth, and abnormal fetal growth. Pregnancy also accelerates the complications of metabolic diseases in mothers resulting in an increased risk of premature cardiovascular events. Despite the convincing evidence that preconception care can largely mitigate the risks of metabolic disease in pregnancy, there are few data about how to identify the highest-risk women so that they can be connected with appropriate preconception care services.

OBJECTIVE

The aim of the study is to determine the maternal phenotype that represents the highest risk of having adverse neonatal and maternal pregnancy outcomes.

METHODS

This will be a prospective cohort study of 500 women recruited in early pregnancy. The primary outcome is a composite of offspring born small for gestational age (SGA) or large for gestational age (LGA) (customized birthweight ≤10th and ≥90th centile for gestational age). Secondary outcomes are (1) composite of adverse neonatal birth outcomes (SGA, LGA, major congenital abnormalities, preterm birth [<37 weeks' gestation]) and (2) composite of new maternal metabolic outcomes (gestational diabetes, diabetes in pregnancy, type 2 diabetes [T2D] or prediabetes; gestational hypertension, preeclampsia, eclampsia or new essential hypertension after pregnancy; and gestational weight gain ≥20kg or new overweight/obesity at the 12-18 months postpartum visit). A multivariable logistic regression analysis will be conducted to identify candidate predictors of poor pregnancy outcomes due to metabolic disease. From this model, model coefficients and the associated 95% CIs will be extracted to derive the risk score for predicting the delivery of LGA/SGA offspring (primary outcome) and composites of adverse neonatal outcomes and maternal outcomes (secondary outcomes).

RESULTS

Seed funding for the project was acquired in November 2022 and subsequent funding was acquired in May 2024. The first participant was recruited on March 23, 2023. At the time of manuscript submission, 402 participants have been recruited. Data analysis has not yet been performed. Results are expected to be published in the first half of 2027.

CONCLUSIONS

This is a prospective observational cohort study that intends to identify the metabolic disease risk factors, or combination of factors, that are most likely to cause adverse maternal and fetal health outcomes. These characteristics will be used to develop a risk calculator which will assist in identifying the highest risk women and in triaging them to appropriate services. The study has been approved by the institutional Human Research Ethics Committee (HREC/90080/MH-2022).

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12623000037606; https://tinyurl.com/yeytsxtp.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/72542.

Pregnancy Termination Among Women of Reproductive Age: Evidence from the Indonesian Demographic and Health Survey

The consequences associated with pregnancy termination have garnered attention from healthcare professionals, particularly in Indonesia. However, national-level evidence on the factors driving pregnancy termination in Indonesia remains limited. This research aimed to identify patterns and characteristics associated with pregnancy termination among reproductive-age women in Indonesia. A cross-sectional study analyzed secondary data from the 2012 and 2017 Indonesian Demographic and Health Survey, involving women aged 15-49. The weighted sample included 42,269 individuals in 2012 and 47,001 in 2017. Binary logistic regression identified the correlates of pregnancy termination. Among 89,270 women of reproductive age, the prevalence of pregnancy termination was 12.68% in 2012 and 12.95% in 2017. Pregnancy termination was more frequently reported among women aged 44-49 years (adjusted odds ratio (AOR): 4.34, 95% confidence interval (CI): 3.54-5.33), those with secondary education (AOR: 1.29, 95% CI: 1.14-1.46), married women (AOR: 195.40, 95% CI: 114.70-332.90), employed women (AOR: 1.05, 95% CI: 1.00-1.09), individuals with health insurance (AOR: 1.07, 95% CI: 1.02-1.11), those who had experienced domestic violence (AOR: 1.07, 95% CI: 1.02-1.11), and regular television viewers (AOR: 1.10, 95% CI: 1.05-1.15). Conversely, pregnancy termination was less commonly reported among women with 1-2 living children (AOR: 0.80, 95% CI: 0.74-0.87), those who expressed no preference for having more children (AOR: 0.89, 95% CI: 0.84-0.94), and women using modern contraception (AOR: 0.76, 95% CI: 0.72-0.80). The findings revealed that the prevalence did not observe any changes in the incidence of pregnancy terminations between 2012 and 2017. Further evaluation by healthcare professionals is crucial to understanding the reasons behind pregnancy termination, especially among women of reproductive age. Insights into factors related to pregnancy termination, especially sociodemographic factors, can help mitigate the pregnancy termination in this population.

Mitochondria in cutaneous health, disease, ageing and rejuvenation-the 3PM-guided mitochondria-centric dermatology

Association of both intrinsic and extrinsic risk factors leading to accelerated skin ageing is reflected in excessive ROS production and ir/reversible mitochondrial injury and burnout, as abundantly demonstrated by accumulating research data. Due to the critical role of mitochondrial stress in the pathophysiology of skin ageing and disorders, maintained (primary care) and restored (secondary care) mitochondrial health, rejuvenation and homoeostasis are considered the most effective holistic approach to advance dermatological treatments based on systemic health-supportive and stimulating measures. Per evidence, an effective skin anti-ageing protection, wound healing and scarring quality - all strongly depend on the sustainable mitochondrial functionality and well-balanced homoeostasis. The latter can be objectively measured and, if necessary, restored in a systemic manner by pre- and rehabilitation algorithms tailored to individualised patient profiles. The entire spectrum of corresponding innovations in the area includes natural and systemic skin rejuvenation, aesthetic and reconstructive medicine, sustainable skin protection and targeted treatments of skin disorders. Contextually, mitochondria-centric dermatology is instrumental for advanced 3PM-guided approach which makes a good use of predictive multi-level diagnostics and targeted protection of skin against both - the health-to-disease transition and progression of relevant disorders. Cost-effective targeted protection and new treatment avenues focused on sustainable mitochondrial health and physiologic homoeostasis are proposed in the article including in-depth analysis of patient cases and exemplified 3PM-guided care with detailed mechanisms and corresponding expert recommendations presented.

Changes in the triglyceride-glucose-body mass index estimate the risk of hypertension among the middle-aged and older population: a prospective nationwide cohort study in China in the framework of predictive, preventive, and personalized medicine

Background

Hypertension is a major modifiable cause of cardiovascular diseases and premature death worldwide. The triglyceride-glucose-body mass index (TyG-BMI), as a novel indicator, has been proposed for assessing hypertension risk. Nevertheless, a paucity of studies has explored the predictive potential of dynamic TyG-BMI for hypertension. The purpose of this study was to investigate whether cumulative TyG-BMI could better predict hypertension incidence and explore the interplay between TyG and BMI in hypertension development. From the perspective of predictive, preventive, and personalized medicine (PPPM/3PM), we assumed that dynamic monitoring of TyG-BMI level and joint assessment of TyG and BMI provide novel insights for individual risk assessment, targeted prevention, and personalized intervention of cardiovascular diseases.

Methods

Using data from the China Health and Retirement Longitudinal Study (CHARLS), a nationwide cohort conducted between 2011 and 2018, the changes in TyG-BMI between 2012 and 2015 were categorized into four groups by K-means clustering analysis. Cumulative TyG-BMI was also divided into four levels based on quartile cutoffs. Logistic regression and restricted cubic spline analyses were performed to examine the associations of different TyG-BMI classes with hypertension. Mediating and interactive analyses were utilized to discern the mutual effects between TyG and BMI in hypertension development.

Results

A total of 2891 participants were enrolled, among whom 386 (13.4%) developed hypertension during a median 36.5-month follow-up period. Logistic regression analysis revealed that, compared to participants with persistently low TyG‑BMI, an increased risk of hypertension was observed among those with a moderate (odds ratio (OR) = 1.60, 95% confidence interval (CI) 1.15 to 2.22), a higher (OR = 1.93, 95% CI 1.28 to 2.89), and the highest TyG‑BMI (OR = 2.33, 95% CI 1.35 to 4.03). A positive linear association of cumulative TyG-BMI with hypertension was discovered (P for non-linear = 0.343). Furthermore, TyG partially mediated the relationship between BMI and hypertension, accounting for 13.18% of the total effect. The joint effect of BMI and TyG was positively affiliated to hypertension development.

Conclusions

This study demonstrated a significant positive association between dynamic TyG-BMI and hypertension among the Chinese middle-aged and older population. In the context of PPPM/3PM, long-term monitoring of TyG-BMI could assist in identifying individuals at high risk of hypertension, strengthening primary prevention efforts and facilitating prompt intervention strategies. In addition, this study revealed the mutual effect of TyG and BMI on hypertension development, which provides a novel approach for mitigating the risk of cardiovascular diseases via addressing metabolic disorders, thereby enhancing effective prevention and targeted intervention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00380-6.

Body fluid multiomics in 3PM-guided ischemic stroke management: health risk assessment, targeted protection against health-to-disease transition, and cost-effective personalized approach are envisaged

Because of its rapid progression and frequently poor prognosis, stroke is the third major cause of death in Europe and the first one in China. Many independent studies demonstrated sufficient space for prevention interventions in the primary care of ischemic stroke defined as the most cost-effective protection of vulnerable subpopulations against health-to-disease transition. Although several studies identified molecular patterns specific for IS in body fluids, none of these approaches has yet been incorporated into IS treatment guidelines. The advantages and disadvantages of individual body fluids are thoroughly analyzed throughout the paper. For example, multiomics based on a minimally invasive approach utilizing blood and its components is recommended for real-time monitoring, due to the particularly high level of dynamics of the blood as a body system. On the other hand, tear fluid as a more stable system is recommended for a non-invasive and patient-friendly holistic approach appropriate for health risk assessment and innovative screening programs in cost-effective IS management. This article details aspects essential to promote the practical implementation of highlighted achievements in 3PM-guided IS management.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00376-2.

Genetic association of lipid traits and lipid-related drug targets with normal tension glaucoma: a Mendelian randomization study for predictive preventive and personalized medicine

Background

Glaucoma is the leading cause of irreversible blindness worldwide. Normal tension glaucoma (NTG) is a distinct subtype characterized by intraocular pressures (IOP) within the normal range (< 21 mm Hg). Due to its insidious onset and optic nerve damage, patients often present with advanced conditions upon diagnosis. NTG poses an additional challenge as it is difficult to identify with normal IOP, complicating its prediction, prevention, and treatment. Observational studies suggest a potential association between NTG and abnormal lipid metabolism, yet conclusive evidence establishing a direct causal relationship is lacking. This study aims to explore the causal link between serum lipids and NTG, while identifying lipid-related therapeutic targets. From the perspective of predictive, preventive, and personalized medicine (PPPM), clarifying the role of dyslipidemia in the development of NTG could provide a new strategy for primary prediction, targeted prevention, and personalized treatment of the disease.

Working hypothesis and methods

In our study, we hypothesized that individuals with dyslipidemia may be more susceptible to NTG due to a dysregulation of microvasculature in optic nerve head. To verify the working hypothesis, univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) were utilized to estimate the causal effects of lipid traits on NTG. Drug target MR was used to explore possible target genes for NTG treatment. Genetic variants associated with lipid traits and variants of genes encoding seven lipid-related drug targets were extracted from the Global Lipids Genetics Consortium genome-wide association study (GWAS). GWAS data for NTG, primary open angle glaucoma (POAG), and suspected glaucoma (GLAUSUSP) were obtained from FinnGen Consortium. For apolipoproteins, we used summary statistics from a GWAS study by Kettunen et al. in 2016. For metabolic syndrome, summary statistics were extracted from UK Biobank participants. In the end, these findings could help identify individuals at risk of NTG by screening for lipid dyslipidemia, potentially leading to new targeted prevention and personalized treatment approaches.

Results

Genetically assessed high-density cholesterol (HDL) was negatively associated with NTG risk (inverse-variance weighted [IVW] model: OR per SD change of HDL level = 0.64; 95% CI, 0.49-0.85; P = 1.84 × 10-3), and the causal effect was independent of apolipoproteins and metabolic syndrome (IVW model: OR = 0.29; 95% CI, 0.14-0.60; P = 0.001 adjusted by ApoB and ApoA1; OR = 0.70; 95% CI, 0.52-0.95; P = 0.023 adjusted by BMI, HTN, and T2DM). Triglyceride (TG) was positively associated with NTG risk (IVW model: OR = 1.62; 95% CI, 1.15-2.29; P = 6.31 × 10-3), and the causal effect was independent of metabolic syndrome (IVW model: OR = 1.66; 95% CI, 1.18-2.34; P = 0.003 adjusted by BMI, HTN, and T2DM), but not apolipoproteins (IVW model: OR = 1.71; 95% CI, 0.99-2.95; P = 0.050 adjusted by ApoB and ApoA1). Genetic mimicry of apolipoprotein B (APOB) enhancement was associated with lower NTG risks (IVW model: OR = 0.09; 95% CI, 0.03-0.26; P = 9.32 × 10-6).

Conclusions

Our findings supported dyslipidemia as a predictive causal factor for NTG, independent of other factors such as metabolic comorbidities. Among seven lipid-related drug targets, APOB is a potential candidate drug target for preventing NTG. Personalized health profiles can be developed by integrating lipid metabolism with life styles, visual quality of life such as reading, driving, and walking. This comprehensive approach will aid in shifting from reactive medical services to PPPM in the management of NTG.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00373-5.

Digital biomarkers: 3PM approach revolutionizing chronic disease management - EPMA 2024 position

Non-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide. Medical condition-specific digital biomarker (DB) panels have emerged as valuable tools to manage NCDs. DBs refer to the measurable and quantifiable physiological, behavioral, and environmental parameters collected for an individual through innovative digital health technologies, including wearables, smart devices, and medical sensors. By leveraging digital technologies, healthcare providers can gather real-time data and insights, enabling them to deliver more proactive and tailored interventions to individuals at risk and patients diagnosed with NCDs. Continuous monitoring of relevant health parameters through wearable devices or smartphone applications allows patients and clinicians to track the progression of NCDs in real time. With the introduction of digital biomarker monitoring (DBM), a new quality of primary and secondary healthcare is being offered with promising opportunities for health risk assessment and protection against health-to-disease transitions in vulnerable sub-populations. DBM enables healthcare providers to take the most cost-effective targeted preventive measures, to detect disease developments early, and to introduce personalized interventions. Consequently, they benefit the quality of life (QoL) of affected individuals, healthcare economy, and society at large. DBM is instrumental for the paradigm shift from reactive medical services to 3PM approach promoted by the European Association for Predictive, Preventive, and Personalized Medicine (EPMA) involving 3PM experts from 55 countries worldwide. This position manuscript consolidates multi-professional expertise in the area, demonstrating clinically relevant examples and providing the roadmap for implementing 3PM concepts facilitated through DBs.

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.

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.

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.

Emerging frontiers of artificial intelligence and machine learning in ischemic stroke: a comprehensive investigation of state-of-the-art methodologies, clinical applications, and unraveling challenges

At present, stroke remains the second highest cause of death globally and a leading cause of disability. From 1990 to 2019, the absolute number of strokes worldwide increased by 70.0%, and the prevalence of stroke increased by 85.0%, causing millions of deaths and disability. Ischemic stroke accounts for the majority of strokes, which is caused by arterial occlusion. Effective primary prevention strategies, early diagnosis, and timely interventions such as rapid reperfusion are in urgent implementation to control ischemic stroke. Otherwise, the stroke burden will probably continue to grow across the world as a result of population aging and an ongoing high prevalence of risk factors. To help with the diagnosis and management of ischemic stroke, newer techniques such as artificial intelligence (AI) are highly anticipated and may bring a new revolution. AI is a recent fast-growing research area which aims to mimic cognitive processes through a number of techniques such as machine learning (ML) methods of random forest learning (RFL) and convolutional neural networks (CNNs). With the help of AI, several momentous milestones have already been attained across diverse dimensions of ischemic stroke. In the context of predictive, preventive, and personalized medicine (PPPM/3PM), we aim to transform stroke care from a reactive to a proactive and individualized paradigm. In this way, AI demonstrates strong clinical utility across all three levels of prevention in ischemic stroke. In this paper, we synoptically illustrated the history and current situation of AI and ML. Then, we summarized their clinical applications and efficacy in the management of stroke. We finally provided an outlook on how AI approaches might contribute to enhancing favorable outcomes after stroke and proposed our suggestions on developing AI-based PPPM strategies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00343-3.

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.

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.

Integrating oculomics with genomics reveals imaging biomarkers for preventive and personalized prediction of arterial aneurysms

Objective

Arterial aneurysms are life-threatening but usually asymptomatic before requiring hospitalization. Oculomics of retinal vascular features (RVFs) extracted from retinal fundus images can reflect systemic vascular properties and therefore were hypothesized to provide valuable information on detecting the risk of aneurysms. By integrating oculomics with genomics, this study aimed to (i) identify predictive RVFs as imaging biomarkers for aneurysms and (ii) evaluate the value of these RVFs in supporting early detection of aneurysms in the context of predictive, preventive and personalized medicine (PPPM).

Methods

This study involved 51,597 UK Biobank participants who had retinal images available to extract oculomics of RVFs. Phenome-wide association analyses (PheWASs) were conducted to identify RVFs associated with the genetic risks of the main types of aneurysms, including abdominal aortic aneurysm (AAA), thoracic aneurysm (TAA), intracranial aneurysm (ICA) and Marfan syndrome (MFS). An aneurysm-RVF model was then developed to predict future aneurysms. The performance of the model was assessed in both derivation and validation cohorts and was compared with other models employing clinical risk factors. An RVF risk score was derived from our aneurysm-RVF model to identify patients with an increased risk of aneurysms.

Results

PheWAS identified a total of 32 RVFs that were significantly associated with the genetic risks of aneurysms. Of these, the number of vessels in the optic disc ('ntreeA') was associated with both AAA (β = -0.36, P = 6.75e-10) and ICA (β = -0.11, P = 5.51e-06). In addition, the mean angles between each artery branch ('curveangle_mean_a') were commonly associated with 4 MFS genes (FBN1: β = -0.10, P = 1.63e-12; COL16A1: β = -0.07, P = 3.14e-09; LOC105373592: β = -0.06, P = 1.89e-05; C8orf81/LOC441376: β = 0.07, P = 1.02e-05). The developed aneurysm-RVF model showed good discrimination ability in predicting the risks of aneurysms. In the derivation cohort, the C-index of the aneurysm-RVF model was 0.809 [95% CI: 0.780-0.838], which was similar to the clinical risk model (0.806 [0.778-0.834]) but higher than the baseline model (0.739 [0.733-0.746]). Similar performance was observed in the validation cohort, with a C-index of 0.798 (0.727-0.869) for the aneurysm-RVF model, 0.795 (0.718-0.871) for the clinical risk model and 0.719 (0.620-0.816) for the baseline model. An aneurysm risk score was derived from the aneurysm-RVF model for each study participant. The individuals in the upper tertile of the aneurysm risk score had a significantly higher risk of aneurysm compared to those in the lower tertile (hazard ratio = 17.8 [6.5-48.8], P = 1.02e-05).

Conclusion

We identified a significant association between certain RVFs and the risk of aneurysms and revealed the impressive capability of using RVFs to predict the future risk of aneurysms by a PPPM approach. Our finds have great potential to support not only the predictive diagnosis of aneurysms but also a preventive and more personalized screening plan which may benefit both patients and the healthcare system.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00315-7.

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

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 infarction

Application of the health risk assessment focused on sub-optimal health conditions to effectively prevent health-to-disease transition

Application of AI in medicine, machine learning and treatment algorithms tailored to robust biomarker patterns

Application of innovative screening programmes which adequately consider the needs of young populations

Stroke is a severe brain disease which has reached an epidemic scale worldwide: in 2019, the global stroke prevalence was 101.5 million people. The World Stroke Organisation predicted that globally, 1 in 4 adults over the age of 25 will get a stroke in their lifetime. Not only old people but also teenagers and young adults are affected. Current global costs of stroke are estimated at 721 billion US dollars. Due to undiagnosed so-called “silent” brain infarction, the number of affected individuals is about 14 times greater in the population than clinically recorded. If it remains untreated, silent brain infarction may cause many severe and fatal disorders such as dementia, depression and even suicide. In this position paper, the consortium describes how the rudimental approach to treating severely diseased people could be replaced by an innovative predictive and preventive one to protect people against the health-to-disease transition.

Antithrombotic and antiplatelet effects of plant-derived compounds: a great utility potential for primary, secondary, and tertiary care in the framework of 3P medicine

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.