Caution, "normal" BMI: health risks associated with potentially masked individual underweight-EPMA Position Paper 2021

Investigation of heavy metals uptake in root-shoot of native plant species adjoining wastewater channels

Metal pollution in water, soil, and vegetation is an emerging environmental issue. Therefore, this study investigated the abundance of heavy metals (HMs) within roots and shoots of native plant species i.e., Bromus pectinatus, Cynodon dactylon, Poa annua, Euphorbia heliscopa, Anagallis arvensis, and Stellaria media grown in the adjoining area of municipal wastewater channels of a Pakistani city of Abbottabad. HMs concentrations (mg L-1) in municipal wastewater were: chromium (Cr) (0.55) > nickel (Ni) (0.09) > lead (Pb) (0.07) > cadmium (Cd) (0.03). Accumulation of HMs in both roots and shoots of plant species varied as B. pectinatus > C. dactylon > P. annua > E. heliscopa > A. arvensis > S. media. Irrespective of the plant species, roots exhibited higher concentrations of HMs than shoots. Higher amount of Cr (131.70 mg kg-1) was detected in the roots of B. pectinatus and the lowest amount (81 mg kg-1) in A. arvensis, Highest Cd concentration was found in the shoot of B. pectinatus and the lowest in the E. heliscopa. The highest concentration of Ni was found in the roots of S. media (37.40 mg kg-1) and the shoot of C. dactylon (15.70 mg kg-1) whereas the lowest Ni concentration was achieved in the roots of A. arvensis (12.10 mg kg-1) and the shoot of E. heliscopa (5.90 mg kg-1). The concentration of HMs in individual plant species was less than 1000 mg kg-1. Considering the higher values (> 1) of biological concentration factor (BCF), biological accumulation co-efficient (BAC), and translocation factor (TF), B. pectinatus and S. media species showed greater potential for HMs accumulation than other species. Therefore, these plants might be helpful for the remediation of HM-contaminated soil.

The clinical outcomes and effectiveness of antiviral agents among underweight patients with COVID-19

OBJECTIVES

This study investigated the outcomes of underweight patients with COVID-19 and the effectiveness of antiviral agents in this population.

METHODS

A retrospective cohort study using theTriNetX research network was conducted. Propensity score matching (PSM) was employed to balance the first cohort involving COVID-19 patients with underweight and normal-weight. In the second cohort, underweight patients receiving antiviral agents and untreated individuals were matched using PSM. The primary outcome was a composite of all-cause hospitalization and death during the 7-30-day follow-up period.

RESULTS

After PSM, the first cohort including each group of 13,502 patients with balanced baseline characteristics were identified for comparing the outcome of patients with underweight and normal weight. The underweight group had a higher risk of the composite primary outcome than those with normal weight (hazard ratio [HR], 1.251; 95% confidence interval [CI], 1.132-1.382). The second cohort included each 884 underweight patients with and without receiving antivirals.Compared with untreated patients, those receiving antiviral treatment had a lower risk of composite primary outcomes (HR, 0.426; 95% CI, 0.278-0.653).

CONCLUSION

Underweight status may be associated with a higher risk of all-cause hospitalization and death in patients with COVID-19.Among underweight patients, antiviral agents demonstrated clinically beneficial effects.

Association between underweight and risk of heart failure in diabetes patients

BACKGROUND

The risk of heart failure (HF) in underweight diabetes mellitus (DM) patients has rarely been studied. We conducted a cohort study to investigate the association between underweight (BMI < 18.5 kg/m2) and BMI change over time and the risk of HF in patients with type 2 DM.

METHODS

We utilized the health screening data from the National Health Insurance Service and the Korean National Health Screening database from 2009 to 2012, with follow-up until December 2018. Participants with DM were categorized into four groups based on their BMI at 4 years before study inclusion and BMI at the study entry: (1) Always Normal Weight (BMI at 4 years ago/BMI at study entry ≥18.5/≥18.5 kg/m2, reference group); (2) Transitioned to Underweight (≥18.5/<18.5 kg/m2); (3) Transitioned to Normal Weight (<18.5/≥18.5 kg/m2) and (4) Always Underweight (<18.5/<18.5 kg/m2). Participants were followed until the development of HF or at the end of the follow-up. Initial screening data included participants with DM who had the health screening during the study period (n = 2,746,079). Participants aged <20 years (n = 390), those who did not undergo health examination 4 years prior (n = 1,306,520), and those with missing data (n = 77,410) were excluded. Participants diagnosed with HF before study participation (n = 81,645) and within 1 year of study enrolment (n = 11,731) were excluded. After applying exclusion criteria, 1,268,383 participants were finally included in the analysis. The primary outcome was the development of HF. We employed Cox proportional hazards models, adjusting for various confounding factors, to assess the risk of developing HF.

RESULTS

Median follow-up duration was 6.88 years and men were 63.16%. The mean ages of each groups were as follows: Always Normal Weight (57.92 ± 11.64 years), Transitioned to Underweight (62 ± 13.5 years), Transitioned to Normal Weight (56.6 ± 15.29 years) and Always Underweight (57.76 ± 15.35 years). In comparison with the Always Normal Weight group (n = 1,245,381, HF = 76,360), Transitioned to Underweight group (≥18.5/<18.5 kg/m2, n = 9304, HF = 880, adjusted Hazard Ratio (aHR)1.389, 95% confidence interval (CI) 1.3-1.485) or Transitioned to Normal Weight (<18.5/≥18.5 kg/m2, n = 6024, HF = 478, aHR 1.385, 95% CI 1.266-1.515) exhibited an increased risk of HF. The highest risk was observed in the Always Underweight group (<18.5/<18.5 kg/m2, n = 7674, HF = 665, aHR 1.612, 95% CI 1.493-1.740).

CONCLUSIONS

Underweight was significantly associated with the risk of HF in the DM population. Active surveillance for HF in an underweight DM population is needed.

Trends in childhood body mass index between 1936 and 2011 showed that underweight remained more common than obesity among 398 970 Danish school children

AIM

To examine trends in all body mass index (BMI) groups in children from 1936 to 2011.

METHODS

We included 197 694 girls and 201 276 boys from the Copenhagen School Health Records Register, born between 1930 and 1996, with longitudinal weight and height measurements (6-14 years). Using International Obesity Task Force criteria, BMI was classified as underweight, normal-weight, overweight and obesity. Sex- and age-specific prevalences were calculated.

RESULTS

From the 1930s, the prevalence of underweight was stable until a small increase occurred from 1950 to 1970s, and thereafter it declined into the early 2000s. Using 7-year-olds as an example, underweight changed from 10% to 7% in girls and from 9% to 6% in boys during the study period. The prevalence of overweight plateaued from 1950 to 1970s and then steeply increased from 1970s onwards and in 1990-2000s 15% girls and 11% boys at 7 years had overweight. The prevalence of obesity particularly increased from 1980s onwards and in 1990-2000s 5% girls and 4% boys at 7 years had obesity. These trends slightly differed by age.

CONCLUSION

Among Danish schoolchildren, the prevalence of underweight was greater than overweight until the 1980s and greater than obesity throughout the period. Thus, monitoring the prevalence of childhood underweight remains an important public health issue.

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.

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.

A simulation framework to determine optimal strength training and musculoskeletal geometry for sprinting and distance running

Musculoskeletal geometry and muscle volumes vary widely in the population and are intricately linked to the performance of tasks ranging from walking and running to jumping and sprinting. As an alternative to experimental approaches, where it is difficult to isolate factors and establish causal relationships, simulations can be used to independently vary musculoskeletal geometry and muscle volumes, and develop a fundamental understanding. However, our ability to understand how these parameters affect task performance has been limited due to the high computational cost of modelling the necessary complexity of the musculoskeletal system and solving the requisite multi-dimensional optimization problem. For example, sprinting and running are fundamental to many forms of sport, but past research on the relationships between musculoskeletal geometry, muscle volumes, and running performance has been limited to observational studies, which have not established cause-effect relationships, and simulation studies with simplified representations of musculoskeletal geometry. In this study, we developed a novel musculoskeletal simulator that is differentiable with respect to musculoskeletal geometry and muscle volumes. This simulator enabled us to find the optimal body segment dimensions and optimal distribution of added muscle volume for sprinting and marathon running. Our simulation results replicate experimental observations, such as increased muscle mass in sprinters, as well as a mass in the lower end of the healthy BMI range and a higher leg-length-to-height ratio in marathon runners. The simulations also reveal new relationships, for example showing that hip musculature is vital to both sprinting and marathon running. We found hip flexor and extensor moment arms were maximized to optimize sprint and marathon running performance, and hip muscles the main target when we simulated strength training for sprinters. Our simulation results provide insight to inspire future studies to examine optimal strength training. Our simulator can be extended to other athletic tasks, such as jumping, or to non-athletic applications, such as designing interventions to improve mobility in older adults or individuals with movement disorders.

A review of biological targets and therapeutic approaches in the management of triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a heterogeneous, aggressive phenotype of breast cancer with associated chemoresistance. The development of chemo- or radioresistance could be attributed to diverse tumor microenvironments, overexpression of membrane proteins (transporters), epigenetic changes, and alteration of the cell signaling pathways/genes associated with the development of cancer stem cells (CSCs).

AIM OF REVIEW

Due to the diverse and heterogeneous nature of TNBC, therapeutic response to the existing modalities offers limited scope and thus results in reccurance after therapy. To establish landmark therapeutic efficacy, a number of novel therapeutic modalities have been proposed. In addition, reversal of the resistance that developed during treatment may be altered by employing appropriate therapeutic modalities. This review aims to discuss the plethora of investigations carried out, which will help readers understand and make an appropriate choice of therapy directed toward complete elimination of TNBC.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This manuscript addresses the major contributory factors from the tumor microenvironment that are responsible for the development of chemoresistance and poor prognosis. The associated cellular events and molecular mechanism-based therapeutic interventions have been explained in detail. Inhibition of ABC transporters, cell signaling pathways associated with CSCs, and epigenetic modification offers promising results in this regard. TNBC progression, invasion, metastasis and recurrence can also be inhibited by blocking multiple cell signaling pathways, targeting specific receptors/epigenetic targets, disrupting bioenergetics and generating reactive oxygen species (ROS).

Royal jelly: a predictive, preventive and personalised strategy for novel treatment options in non-communicable diseases

Royal jelly (RJ) is a bee product produced by young adult worker bees, composed of water, proteins, carbohydrates and lipids, rich in bioactive components with therapeutic properties, such as free fatty acids, mainly 10-hydroxy-trans-2-decenoic acid (10-H2DA) and 10-hydroxydecanoic acid (10-HDA), and major royal jelly proteins (MRJPs), as well as flavonoids, most flavones and flavonols, hormones, vitamins and minerals. In vitro, non-clinical and clinical studies have confirmed its vital role as an antioxidant and anti-inflammatory. This narrative review discusses the possible effects of royal jelly on preventing common complications of non-communicable diseases (NCDs), such as inflammation, oxidative stress and intestinal dysbiosis, from the viewpoint of predictive, preventive and personalised medicine (PPPM/3PM). It is concluded that RJ, predictively, can be used as a non-pharmacological therapy to prevent and mitigate complications related to NCDs, and the treatment must be personalised.

The correlation between primary open-angle glaucoma (POAG) and gut microbiota: a pilot study towards predictive, preventive, and personalized medicine

Background

Glaucoma is the leading cause of irreversible blindness worldwide. Emerged evidence has shown that glaucoma is considered an immune system related disorder. The gut is the largest immune organ in the human body and the gut microbiota (GM) plays an irreversible role in maintaining immune homeostasis. But, how the GM influences glaucoma remains unrevealed. This study aimed at investigating the key molecules/pathways mediating the GM and the glaucoma to provide new biomarkers for future predictive, preventive, and personalized medicine.

Methods

Datasets from the primary open-angle glaucoma (POAG) patients (GSE138125) and datasets for target genes of GM/GM metabolites were downloaded from a public database. For GSE138125, the differentially expressed genes (DEGs) between healthy and POAG samples were identified. And the online Venn diagram tool was used to obtain the DEGs from POAG related to GM. After which GM-related DEGs were analyzed by correlation analysis, pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. Human trabecular meshwork cells were used for validation, and the mRNA level of hub genes was verified by quantitative real-time polymerase chain reaction (RT-qPCR) in the in vitro glaucoma model.

Results

A total of 16 GM-related DEGs in POAG were identified from the above 2 datasets (9 upregulated genes and 7 downregulated genes). Pathway enrichment analysis indicated that these genes are mostly enriched in immune regulation especially macrophages-related pathways. Then 6 hub genes were identified by PPI network analysis and construction of key modules. Finally, RT-qPCR confirmed that the expression of the hub genes in the in vitro glaucoma model was consistent with the results of bioinformatics analysis of the mRNA chip.

Conclusion

This bioinformatic study elucidates NFKB1, IL18, KITLG, TLR9, FKBP2, and HDAC4 as hub genes for POAG and GM regulation. Immune response modulated by macrophages plays an important role in POAG and may be potential targets for future predictive, preventive, and personalized diagnosis and treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00336-2.

Body Mass Index and Associated Medical Expenditures in the US Among Privately Insured Individuals Aged 2 to 19 Years in 2018

Importance

Nearly 40% of US youth aged 2 to 19 years do not have a body mass index (BMI) in the healthy weight category. However, there are no recent estimates for BMI-associated expenditures using clinical or claims data.

Objective

To estimate medical expenditures among US youth across all BMI categories along with sex and age groups.

Design, Setting, Participants

This cross-sectional study used IQVIA's ambulatory electronic medical records (AEMR) data set linked with IQVIA's PharMetrics Plus Claims database from January 2018 through December 2018. Analysis was performed from March 25, 2022, through June 20, 2022. It included a convenience sample of a geographically diverse patient population from AEMR and PharMetrics Plus. The study sample included privately insured individuals with a BMI measurement in 2018 and excluded patients with pregnancy-related visits.

Exposure

BMI categories.

Main Outcomes and Measures

Total medical expenditures were estimated using generalized linear model regression with γ distribution and log-link function. For out-of-pocket (OOP) expenditures, a 2-part model was used that included logistic regression to estimate the probability of positive expenditures followed by generalized linear model. Estimates were shown with and without accounting for sex, race and ethnicity, payer type, geographic region, age interacted with sex and BMI categories, and confounding conditions.

Results

The sample included 205 876 individuals aged 2 to 19 years; 104 066 were male (50.5%) and the median age was 12 years. Compared with those with healthy weight, total and OOP expenditures were higher for all other BMI categories. Differences in total expenditures were highest for those with severe obesity ($909; 95% CI, $600-$1218) followed by underweight ($671; 95% CI, $286-$1055) compared with healthy weight. Differences in OOP expenditures were highest for those with severe obesity ($121; 95% CI, $86-$155) followed by underweight ($117; 95% CI, $78-$157) compared with healthy weight. Having underweight was associated with higher total expenditures at ages 2 to 5 years and 6 to 11 years by $679 (95% CI, $228-$1129) and $1166 (95% CI, $632-$1700), respectively; having severe obesity was associated with higher total expenditures at ages 2 to 5 years, 6 to 11 years, and 12 to 17 years by $1035 (95% CI, $208-$1863), $821 (95% CI, $414-$1227), and $1088 (95% CI, $594-$1582), respectively.

Conclusions and Relevance

The study team found medical expenditures to be higher for all BMI categories when compared with those with healthy weight. These findings may indicate potential economic value of interventions or treatments aimed at reducing BMI-associated health risks.

Current trends and perspectives in the exploration of anorexia athletica-clinical challenges and therapeutic considerations

Elite athletes are exposed to a considerable amount of physical and psychological stress throughout their entire professional life, but the exploration of the consequences of this stressful regimen on mental health is still in its early stages. Eating disorders (EDs), substance use disorders, and behavioral addictions represent only several domains that are worth more investigation in this vulnerable population, in order to find preventative and therapeutic strategies. The exploration of EDs in athletes is important because this population is very vulnerable to the impact that weight and body shape may have on their professional performances, and epidemiological studies support this concern, i.e., the prevalence of EDs in athletes is significantly higher than in the general population. This article is dedicated to the synthesis of available data regarding a specific pathology reported in elite athletes, i.e., anorexia athletica (AA), based on a narrative reviewing methodology. The information about risk factors, pathophysiology, positive and differential diagnosis, epidemiology, structured evaluation, and treatment of AA have been summarized and future research directions have been highlighted. While tentative diagnostic criteria for AA and a self-administered questionnaire exist, its pathophysiology is still insufficiently explored, and the treatment is not based on good-quality trials. According to the retrieved data, more research targeting the physical and mental health of elite athletes, especially those practicing esthetic sports, is needed, in order to implement adequate screening and early intervention programs. Future studies targeting various sub-populations of elite athletes, i.e., esthetic vs. non-esthetic sports, individuals presenting a history of ED vs. those without such a history, and those practicing individual sports vs. team sports are needed to reach the objective of improving the quality of life in this population.

Underexplored reciprocity between genome-wide methylation status and long non-coding RNA expression reflected in breast cancer research: potential impacts for the disease management in the framework of 3P medicine

Breast cancer (BC) is the most common female malignancy reaching a pandemic scale worldwide. A comprehensive interplay between genetic alterations and shifted epigenetic regions synergistically leads to disease development and progression into metastatic BC. DNA and histones methylations, as the most studied epigenetic modifications, represent frequent and early events in the process of carcinogenesis. To this end, long non-coding RNAs (lncRNAs) are recognized as potent epigenetic modulators in pathomechanisms of BC by contributing to the regulation of DNA, RNA, and histones' methylation. In turn, the methylation status of DNA, RNA, and histones can affect the level of lncRNAs expression demonstrating the reciprocity of mechanisms involved. Furthermore, lncRNAs might undergo methylation in response to actual medical conditions such as tumor development and treated malignancies. The reciprocity between genome-wide methylation status and long non-coding RNA expression levels in BC remains largely unexplored. Since the bio/medical research in the area is, per evidence, strongly fragmented, the relevance of this reciprocity for BC development and progression has not yet been systematically analyzed. Contextually, the article aims at:consolidating the accumulated knowledge on both-the genome-wide methylation status and corresponding lncRNA expression patterns in BC andhighlighting the potential benefits of this consolidated multi-professional approach for advanced BC management. Based on a big data analysis and machine learning for individualized data interpretation, the proposed approach demonstrates a great potential to promote predictive diagnostics and targeted prevention in the cost-effective primary healthcare (sub-optimal health conditions and protection against the health-to-disease transition) as well as advanced treatment algorithms tailored to the individualized patient profiles in secondary BC care (effective protection against metastatic disease). Clinically relevant examples are provided, including mitochondrial health control and epigenetic regulatory mechanisms involved.

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.

Differences in Telomere Length between Adolescent Females with Anorexia Nervosa Restricting Type and Anorexia Nervosa Binge-Purge Type

Physiological and psychological distress may accelerate cellular aging, manifested by shortening of telomere length (TL). The present study focused on TL shortening in anorexia nervosa (AN), an illness combining physiological and psychological distress. For that purpose, we measured TL in 44 female adolescents with AN at admission to inpatient treatment, in a subset of 18 patients also at discharge, and in 22 controls. No differences in TL were found between patients with AN and controls. At admission, patients with AN-binge/purge type (AN-B/P; n = 18) showed shorter TL compared with patients with AN-restricting type (AN-R; n = 26). No change in TL was found from admission to discharge, despite an improvement in body mass index standard deviation score (BMI-SDS) following inpatient treatment. Older age was the only parameter assessed to be correlated with greater TL shortening. Several methodological changes have to be undertaken to better understand the putative association of shorter TL with B/P behaviors, including increasing the sample size and the assessment of the relevant pathological eating disorder (ED) and non-ED psychological correlates in the two AN subtypes.

Therapy-resistant breast cancer in focus: Clinically relevant mitigation by flavonoids targeting cancer stem cells

Significant limitations of the reactive medical approach in breast cancer management are clearly reflected by alarming statistics recorded worldwide. According to the WHO updates, breast malignancies become the leading cancer type. Further, the portion of premenopausal breast cancer cases is permanently increasing and demonstrates particularly aggressive patterns and poor outcomes exemplified by young patients with triple-negative breast cancer that lacks targeted therapy. Accumulating studies suggest the crucial role of stem cells in tumour biology, high metastatic activity, and therapy resistance of aggressive breast cancer. Therefore, targeting breast cancer stem cells is a promising treatment approach in secondary and tertiary breast cancer care. To this end, naturally occurring substances demonstrate high potential to target cancer stem cells which, however, require in-depth analysis to identify effective anti-cancer agents for cost-effective breast cancer management. The current article highlights the properties of flavonoids particularly relevant for targeting breast cancer stem cells to mitigate therapy resistance. The proposed approach is conformed with the principles of 3P medicine by applying predictive diagnostics, patient stratification and treatments tailored to the individualised patient profile. Expected impacts are very high, namely, to overcome limitations of reactive medical services improving individual outcomes and the healthcare economy in breast cancer management. Relevant clinical applications are exemplified in the paper.

Mortality, Cardiovascular, and Medication Outcomes in Patients With Myocardial Infarction and Underweight in a Meta-Analysis of 6.3 Million Patients

Although most of the current evidence on myocardial infarction focuses on obesity, there is growing evidence that patients who are underweight have unfavorable prognosis. This study aimed to explore the prevalence, clinical characteristics, and prognosis of this population at risk. Embase and Medline were searched for studies reporting outcomes in populations who were underweight with myocardial infarction. Underweight and normal weight were defined according to the World Health Organization criteria. A single-arm meta-analysis of proportions was used to estimate the prevalence of underweight in patients with myocardial infarction, whereas a meta-analysis of proportions was used to estimate the odds ratio of all-cause mortality, medications prescribed, and cardiovascular outcomes. Twenty-one studies involving 6,368,225 patients were included, of whom 47,866 were underweight. The prevalence of underweight in patients with myocardial infarction was 2.96% (95% confidence interval 1.96% to 4.47%). Despite having fewer classical cardiovascular risk factors, patients who were underweight had 66% greater hazard for mortality (hazard ratio 1.66, 95% confidence interval 1.44 to 1.92, p <0.0001). The mortality of patients who were underweight increased from 14.1% at 30 days to 52.6% at 5 years. Nevertheless, they were less likely to receive guideline-directed medical therapy. Relative to subjects with normal weight, Asian populations who were underweight had greater mortality risks than those of their Caucasian counterparts (p = 0.0062). In conclusion, in patients with myocardial infarction, those who were underweight tend to have poorer prognostic outcomes. A lower body mass index is an independent predictor of mortality, which calls for global efforts in addressing this modifiable risk factor in clinical practice guidelines.

Phytochemical-based nanodrugs going beyond the state-of-the-art in cancer management-Targeting cancer stem cells in the framework of predictive, preventive, personalized medicine

Cancer causes many deaths worldwide each year, especially due to tumor heterogeneity leading to disease progression and treatment failure. Targeted treatment of heterogeneous population of cells - cancer stem cells is still an issue in protecting affected individuals against associated multidrug resistance and disease progression. Nanotherapeutic agents have the potential to go beyond state-of-the-art approaches in overall cancer management. Specially assembled nanoparticles act as carriers for targeted drug delivery. Several nanodrugs have already been approved by the US Food and Drug Administration (FDA) for treating different cancer types. Phytochemicals isolated from plants demonstrate considerable potential for nanomedical applications in oncology thanks to their antioxidant, anti-inflammatory, anti-proliferative, and other health benefits. Phytochemical-based NPs can enhance anticancer therapeutic effects, improve cellular uptake of therapeutic agents, and mitigate the side effects of toxic anticancer treatments. Per evidence, phytochemical-based NPs can specifically target CSCs decreasing risks of tumor relapse and metastatic disease manifestation. Therefore, this review focuses on current outlook of phytochemical-based NPs and their potential targeting CSCs in cancer research studies and their consideration in the framework of predictive, preventive, and personalized medicine (3PM).

Flavonoids attenuate cancer metabolism by modulating Lipid metabolism, amino acids, ketone bodies and redox state mediated by Nrf2

Metabolic reprogramming of cancer cells is a common hallmark of malignant transformation. The preference for aerobic glycolysis over oxidative phosphorylation in tumors is a well-studied phenomenon known as the Warburg effect. Importantly, metabolic transformation of cancer cells also involves alterations in signaling cascades contributing to lipid metabolism, amino acid flux and synthesis, and utilization of ketone bodies. Also, redox regulation interacts with metabolic reprogramming during malignant transformation. Flavonoids, widely distributed phytochemicals in plants, exert various beneficial effects on human health through modulating molecular cascades altered in the pathological cancer phenotype. Recent evidence has identified numerous flavonoids as modulators of critical components of cancer metabolism and associated pathways interacting with metabolic cascades such as redox balance. Flavonoids affect lipid metabolism by regulating fatty acid synthase, redox balance by modulating nuclear factor-erythroid factor 2-related factor 2 (Nrf2) activity, or amino acid flux and synthesis by phosphoglycerate mutase 1. Here, we discuss recent preclinical evidence evaluating the impact of flavonoids on cancer metabolism, focusing on lipid and amino acid metabolic cascades, redox balance, and ketone bodies.

Exploring the impact of body mass change on fatigue and activity of the muscular system during daily routine

BACKGROUND

Correct body weight is one of the factors that allows you to maintain a properly functioning body. Abnormal body weight can cause muscle tissue remodelling, affecting activity and muscle fatigue. Changes in the muscular system can cause occurrence of functional limitations.

OBJECTIVE

To determine the effect of weight change on fatigue and activity of the muscular system during daily activities.

METHODS

The evaluation of musculoskeletal functioning was based on the results of computer simulations conducted in the AnyBody Modeling System. The following activities were analysed: standing, sitting down and getting up from a chair, holding and lifting an object, and walking. The simulations of the activities were carried out using averaged kinematic data, and by changing body mass in the range of 50 kg to 100 kg by increments of 2 kg, to map different nutritional status from excessive thinness to extreme obesity. Identification of loads in the musculoskeletal system was based on solving an inverse dynamics problem and then the estimation of muscle force values using static optimization. The simulation results allowed to determine the value of muscle fatigue and the level of muscle activity.

RESULTS

For activities (i.e., standing, walking, sitting down and getting up from a chair) it was observed that the value of muscle fatigue increases with increasing body mass. However, for activities that cause more load on the musculoskeletal system, i.e. lifting and holding an object, the highest value of muscle fatigue was observed in underweight individuals.

CONCLUSION

The change in body weight alters the functioning of the muscular system and thus the ability to perform activities. It was shown that in case of underweight, overweight or obese people, abnormal body weight can be the reason for occurrence of difficulties in performing the activities of lifting and holding a 20 kg object, as well as walking.

Body mass index-based predictions and personalized clinical strategies for colorectal cancer in the context of PPPM

Currently colorectal cancer (CRC) is the third most prevalent cancer worldwide. Body mass index (BMI) is frequently used in CRC screening and risk assessment to quantitatively evaluate weight. However, the impact of BMI on clinical strategies for CRC has received little attention. Within the framework of the predictive, preventive, and personalized medicine (3PM/PPPM), we hypothesized that BMI stratification would affect the primary, secondary, and tertiary care options for CRC and we conducted a critical evidence-based review. BMI dynamically influences CRC outcomes, which helps avoiding adverse treatment effects. The outcome of surgical and radiation treatment is adversely affected by overweight (BMI ≥ 30) or underweight (BMI < 20). A number of interventions, such as enhanced recovery after surgery and robotic surgery, can be applied to CRC at all levels of BMI. BMI-controlling modalities such as exercise, diet control, nutritional therapy, and medications may be potentially beneficial for patients with CRC. Patients with overweight are advised to lose weight through diet, medication, and physical activity while patients suffering of underweight require more focus on nutrition. BMI assists patients with CRC in better managing their weight, which decreases the incidence of adverse prognostic events during treatment. BMI is accessible, noninvasive, and highly predictive of clinical outcomes in CRC. The cost-benefit of the PPPM paradigm in developing countries can be advanced, and the clinical benefit for patients can be improved with the promotion of BMI-based clinical strategy models for CRC.

Migration-Related Weight Changes among African Immigrants in the United States

(1) Background: people who migrate from low-to high-income countries are at an increased risk of weight gain, and excess weight is a risk factor for cardiovascular disease. Few studies have quantified the changes in body mass index (BMI) pre- and post-migration among African immigrants. We assessed changes in BMI pre- and post-migration from Africa to the United States (US) and its associated risk factors. (2) Methods: we performed a cross-sectional analysis of the African Immigrant Health Study, which included African immigrants in the Baltimore-Washington District of the Columbia metropolitan area. BMI category change was the outcome of interest, categorized as healthy BMI change or maintenance, unhealthy BMI maintenance, and unhealthy BMI change. We explored the following potential factors of BMI change: sex, age at migration, percentage of life in the US, perceived stress, and reasons for migration. We performed multinomial logistic regression adjusting for employment, education, income, and marital status. (3) Results: we included 300 participants with a mean (±SD) current age of 47 (±11.4) years, and 56% were female. Overall, 14% of the participants had a healthy BMI change or maintenance, 22% had an unhealthy BMI maintenance, and 64% had an unhealthy BMI change. Each year of age at immigration was associated with a 7% higher relative risk of maintaining an unhealthy BMI (relative risk ratio [RRR]: 1.07; 95% CI 1.01, 1.14), and compared to men, females had two times the relative risk of unhealthy BMI maintenance (RRR: 2.67; 95% CI 1.02, 7.02). Spending 25% or more of life in the US was associated with a 3-fold higher risk of unhealthy BMI change (RRR: 2.78; 95% CI 1.1, 6.97). (4) Conclusions: the age at immigration, the reason for migration, and length of residence in the US could inform health promotion interventions that are targeted at preventing unhealthy weight gain among African immigrants.

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.

Mutual effect of homocysteine and uric acid on arterial stiffness and cardiovascular risk in the context of predictive, preventive, and personalized medicine

Background

Arterial stiffness is a major risk factor and effective predictor of cardiovascular diseases and a common pathway of pathological vascular impairments. Homocysteine (Hcy) and uric acid (UA) own the shared metabolic pathways to affect vascular function. Serum uric acid (UA) has a great impact on arterial stiffness and cardiovascular risk, while the mutual effect with Hcy remains unknown yet. This study aimed to evaluate the mutual effect of serum Hcy and UA on arterial stiffness and 10-year cardiovascular risk in the general population. From the perspective of predictive, preventive, and personalized medicine (PPPM/3PM), we assumed that combined assessment of Hcy and UA provides a better tool for targeted prevention and personalized intervention of cardiovascular diseases via suppressing arterial stiffness.

Methods

This study consisted of 17,697 participants from Beijing Health Management Cohort, who underwent health examination between January 2012 and December 2019. Brachial-ankle pulse wave velocity (baPWV) was used as an index of arterial stiffness.

Results

Individuals with both high Hcy and UA had the highest baPWV, compared with those with low Hcy and low UA (β: 30.76, 95% CI: 18.36-43.16 in males; β: 53.53, 95% CI: 38.46-68.60 in females). In addition, these individuals owned the highest 10-year cardiovascular risk (OR: 1.49, 95% CI: 1.26-1.76 in males; OR: 7.61, 95% CI: 4.63-12.68 in females). Of note, males with high homocysteine and low uric acid were significantly associated with increased cardiovascular risk (OR: 1.30, 95% CI: 1.15-1.47), but not the high uric acid and low homocysteine group (OR: 1.02, 95% CI: 0.90-1.16).

Conclusions

This study found the significantly mutual effect of Hcy and UA on arterial stiffness and cardiovascular risk using a large population and suggested the clinical importance of combined evaluation and control of Hcy and UA for promoting cardiovascular health. The adverse effect of homocysteine on arteriosclerosis should be addressed beyond uric acid, especially for males. Monitoring of the level of both Hcy and UA provides a window opportunity for PPPM/3PM in the progression of arterial stiffness and prevention of CVD. Hcy provides a novel predictor beyond UA of cardiovascular health to identify individuals at high risk of arterial stiffness for the primary prevention and early treatment of CVD. In the progressive stage of arterial stiffness, active control of Hcy and UA levels from the aspects of dietary behavior and medication treatment is conducive to alleviating the level of arterial stiffness and reducing the risk of CVD. Further studies are needed to evaluate the clinical effect of Hcy and UA targeted intervention on arterial stiffness and cardiovascular health.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00298-x.

Identifying potential signatures for atherosclerosis in the context of predictive, preventive, and personalized medicine using integrative bioinformatics approaches and machine-learning strategies

Background

Atherosclerosis is a major contributor to morbidity and mortality worldwide. Although several molecular markers associated with atherosclerosis have been developed in recent years, the lack of robust evidence hinders their clinical applications. For these reasons, identification of novel and robust biomarkers will directly contribute to atherosclerosis management in the context of predictive, preventive, and personalized medicine (PPPM). This integrative analysis aimed to identify critical genetic markers of atherosclerosis and further explore the underlying molecular immune mechanism attributing to the altered biomarkers.

Methods

Gene Expression Omnibus (GEO) series datasets were downloaded from GEO. Firstly, differential expression analysis and functional analysis were conducted. Multiple machine-learning strategies were then employed to screen and determine key genetic markers, and receiver operating characteristic (ROC) analysis was used to assess diagnostic value. Subsequently, cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) and a single-cell RNA sequencing (scRNA-seq) data were performed to explore relationships between signatures and immune cells. Lastly, we validated the biomarkers' expression in human and mice experiments.

Results

A total of 611 overlapping differentially expressed genes (DEGs) included 361 upregulated and 250 downregulated genes. Based on the enrichment analysis, DEGs were mapped in terms related to immune cell involvements, immune activating process, and inflaming signals. After using multiple machine-learning strategies, dehydrogenase/reductase 9 (DHRS9) and protein tyrosine phosphatase receptor type J (PTPRJ) were identified as critical biomarkers and presented their high diagnostic accuracy for atherosclerosis. From CIBERSORT analysis, both DHRS9 and PTPRJ were significantly related to diverse immune cells, such as macrophages and mast cells. Further scRNA-seq analysis indicated DHRS9 was specifically upregulated in macrophages of atherosclerotic lesions, which was confirmed in atherosclerotic patients and mice.

Conclusions

Our findings are the first to report the involvement of DHRS9 in the atherogenesis, and the proatherogenic effect of DHRS9 is mediated by immune mechanism. In addition, we confirm that DHRS9 is localized in macrophages within atherosclerotic plaques. Therefore, upregulated DHRS9 could be a novel potential target for the future predictive diagnostics, targeted prevention, patient stratification, and personalization of medical services in atherosclerosis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00289-y.

Oculomics for sarcopenia prediction: a machine learning approach toward predictive, preventive, and personalized medicine

Aims

Sarcopenia is characterized by a gradual loss of skeletal muscle mass and strength with increased adverse outcomes. Recently, large-scale epidemiological studies have demonstrated a relationship between several chronic disorders and ocular pathological conditions using an oculomics approach. We hypothesized that sarcopenia can be predicted through eye examinations, without invasive tests or radiologic evaluations in the context of predictive, preventive, and personalized medicine (PPPM/3PM).

Methods

We analyzed data from the Korean National Health and Nutrition Examination Survey (KNHANES). The training set (80%, randomly selected from 2008 to 2010) data were used to construct the machine learning models. Internal (20%, randomly selected from 2008 to 2010) and external (from the KNHANES 2011) validation sets were used to assess the ability to predict sarcopenia. We included 8092 participants in the final dataset. Machine learning models (XGBoost) were trained on ophthalmological examinations and demographic factors to detect sarcopenia.

Results

In the exploratory analysis, decreased levator function (odds ratio [OR], 1.41; P value <0.001), cataracts (OR, 1.31; P value = 0.013), and age-related macular degeneration (OR, 1.38; P value = 0.026) were associated with an increased risk of sarcopenia in men. In women, an increased risk of sarcopenia was associated with blepharoptosis (OR, 1.23; P value = 0.038) and cataracts (OR, 1.29; P value = 0.010). The XGBoost technique showed areas under the receiver operating characteristic curves (AUCs) of 0.746 and 0.762 in men and women, respectively. The external validation achieved AUCs of 0.751 and 0.785 for men and women, respectively. For practical and fast hands-on experience with the predictive model for practitioners who may be willing to test the whole idea of sarcopenia prediction based on oculomics data, we developed a simple web-based calculator application (https://knhanesoculomics.github.io/sarcopenia) to predict the risk of sarcopenia and facilitate screening, based on the model established in this study.

Conclusion

Sarcopenia is treatable before the vicious cycle of sarcopenia-related deterioration begins. Therefore, early identification of individuals at a high risk of sarcopenia is essential in the context of PPPM. Our oculomics-based approach provides an effective strategy for sarcopenia prediction. The proposed method shows promise in significantly increasing the number of patients diagnosed with sarcopenia, potentially facilitating earlier intervention. Through patient oculometric monitoring, various pathological factors related to sarcopenia can be simultaneously analyzed, and doctors can provide personalized medical services according to each cause. Further studies are needed to confirm whether such a prediction algorithm can be used in real-world clinical settings to improve the diagnosis of sarcopenia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00292-3.

Hair cortisol level might be indicative for a 3PM approach towards suicide risk assessment in depression: comparative analysis of mentally stable and depressed individuals versus individuals after completing suicide

Depression and suicidal behavior are interrelated, stress-associated mental health conditions, each lacking biological verifiability. Concepts of predictive, preventive, and personalized medicine (3PM) are almost completely missing for both conditions but are of utmost importance. Prior research reported altered levels of the stress hormone cortisol in the scalp hair of depressed individuals, however, data on hair cortisol levels (HCL) for suicide completers (SC) are missing. Here, we aimed to identify differences in HCL between subject with depression (n = 20), SC (n = 45) and mentally stable control subjects (n = 12) to establish the usage of HCL as a new target for 3PM. HCL was measured in extracts of pulverized hair (1-cm and 3-cm hair segments) using ELISA. In 3-cm hair segments, an average increase in HCL for depressed patients (1.66 times higher; p = .011) and SC (5.46 times higher; p = 1.65 × 10⁻⁵) compared to that for controls was observed. Furthermore, the average HCL in SC was significantly increased compared to that in the depressed group (3.28 times higher; p = 1.4 × 10⁻⁵). A significant correlation between HCL in the 1-cm and the 3-cm hair segments, as well as a significant association between the severity of depressive symptoms and HCL (3-cm segment) was found. To conclude, findings of increased HCL in subjects with depression compared to that in controls were replicated and an additional increase in HCL was seen in SC in comparison to patients with depression. The usage of HCL for creating effective patient stratification and predictive approach followed by the targeted prevention and personalization of medical services needs to be validated in follow-up studies.

Fat–fat-free index in body mass assessment in young people

The study aimed to personalize the classification of body weight using the fat–fat-free (FFF) index with the percentage of body fat and to develop classification standards for the FFF index for men aged 18–25 years. Moreover, 1,642 adolescents (1,200 ♀) were examined. Using body composition analyzers, weight was determined, as well as overall and segmental body composition. Based on the obtained values for fat mass and fat-free tissue mass, an overall FFF index was calculated. According to the BMI classification, 9% of ♀ and 6% of ♂ are underweight, 29% of ♀ and 13% of ♂ are overweight, and 5% of the subjects are obese. Women and men classified in the same group according to BMI differed statistically significantly in terms of body weight, FM%, and FFM. In contrast to BMI and FM%, the FFF used takes into account the ratio of fat mass to fat-free tissue and muscle tissue mass. The proposed classification of FFF was made taking into account the differences that arise with sexual development and physiological changes occurring in ontogeny. Assessment of body mass using the FFF index should be used as part of preventive screening for the early diagnosis and prevention of overweight and thus many chronic diseases for which overweight or obesity is a risk factor.

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

Abstract

Cardiovascular disease remains the leading cause of disease burden globally with far-reaching consequences including enormous socio-economic burden to healthcare and society at large. Cardiovascular health is decisive for reproductive function, healthy pregnancy and postpartum. During pregnancy, maternal cardiovascular system is exposed to highly increased haemodynamic stress that significantly impacts health status of the mother and offspring. Resulting from sub-optimal maternal health conditions overlooked in pre-pregnancy time, progressive abnormalities can be expected during pregnancy and postpartum. Contextually, there are two main concepts to follow in the framework of predictive, preventive and personalised medicine, namely to develop:

1. advanced screening of sub-optimal health conditions in young populations to predict and prevent individual health risks prior to planned pregnancies

2. in-depth companion diagnostics during pregnancy to predict and prevent long-lasting postpartum health risks of the mother and offspring.

Data collected in the current study demonstrate group-specific complications to health of the mother and offspring and clinical relevance of the related phenotyping in pre-pregnant mothers. Diagnostic approach proposed in this study revealed its great clinical utility demonstrating important synergies between cardiovascular maladaptation and connective tissue dysfunction. Co-diagnosed pre-pregnancy low BMI of the mother, connective tissue dysfunction, increased stiffness of peripheral vessels and decreased blood pressure are considered a highly specific maternal phenotype useful for innovative screening programmes in young populations to predict and prevent severe risks to health of the mother and offspring. This crucial discovery brings together systemic effects characteristic, for example, for individuals with Flammer syndrome predisposed to the phenotype-specific primary vascular dysregulation, pregnancy-associated risks, normal tension glaucoma, ischemic stroke at young age, impaired wound healing and associated disorders. Proposed maternal phenotyping is crucial to predict and effectively protect both the mother and offspring against health-to-disease transition. Pre-pregnancy check-up focused on sub-optimal health and utilising here described phenotypes is pivotal for advanced health policy.

Plain English abstract

Cardiovascular health is decisive for reproductive function and healthy pregnancy. During pregnancy, maternal cardiovascular system may demonstrate health-to-disease transition relevant for the affected mother and offspring. Overlooked in pre-pregnancy time, progressive abnormalities can be expected during pregnancy and lifelong. Here we co-diagnosed maternal pre-pregnancy low bodyweight with systemic effects which may increase risks of pregnancy, eye and heart disorders and ischemic stroke at young age, amongst others. Innovative screening  programmes focused on sub-optimal health in young populations to predict and to mitigate individual health risks prior to pregnancy is an essential innovation for health policy proposed.

Underweight predicts poststroke cardiovascular events in patients without atrial fibrillation

BACKGROUND AND PURPOSE

The purpose of this study was to determine whether underweight is associated with poststroke cardiovascular events and whether such association is different according to the presence of atrial fibrillation (AF).

METHODS

Patients with acute stroke or transient ischemic attack who were prospectively registered in a multicenter stroke database from April 2008 to July 2020 were analyzed, excluding those aged 75 or older and those who were overweight. We prospectively captured major adverse cardiovascular events (MACE) within one year after stroke. Cox-proportional hazard regression analysis was conducted for each subgroup with or without AF after adjusting for predetermined vascular risk factors and potential confounders.

RESULTS

Among 30,912 patients, 1494 (4.8%) cases were underweight and 29,418 (95.2%) cases were normal weight. The cumulative event rate of 1-year MACE was higher in the underweight group (9.0%) than in the normal weight group (5.6%). In Cox-proportional regression, underweight was associated with significantly higher MACE (adjusted hazard ratio [HR]: 1.62, 95% confidence interval [CI]: 1.26-2.09) and recurrent stroke (adjusted HR: 1.42, 95% CI: 1.02-1.98) in all study patients. In patients with AF, the risk of MACE for the underweight group was not significantly increased. In contrast, in patients without AF, the underweight group had a consistently higher risk of MACE (adjusted HR: 1.66, 95% CI: 1.25-2.22) and recurrent stroke (adjusted HR: 1.50, 95% CI: 1.05-2.14).

CONCLUSIONS

Underweight increased the risk of MACE and recurrent stroke within one year after acute stroke, especially in stroke without AF.

miR-623 Targets Metalloproteinase-1 and Attenuates Extravasation of Brain Metastatic Triple-Negative Breast Cancer Cells

Background

Most breast cancer-related deaths result from metastasis. Understanding the molecular basis of metastasis is needed for the development of effective targeted and preventive strategies. Matrix metalloproteinase-1 (MMP1) plays an important role in brain metastasis (BM) of triple-negative breast cancer (TNBC) by promoting extravasation of cancer cells across the brain endothelium (BE). MMP1 expression is controlled by endogenous microRNAs. Preliminary bioinformatics analysis has revealed that miR-623, known to target the 3ʹUTR of MMP1, is significantly downregulated in brain metastatic tumors compared to primary BC tumors. However, the involvement of miR-623 in MMP1 upregulation in breast cancer brain metastatic cells (BCBMC) remains unexplored. Here, we investigated the role of miR-623 in MMP1 regulation and its impact on the extravasation of TNBC cells through the BE in vitro.

Materials and Methods

A loss-and-gain of function method was employed to address the effect of miR-623 modulation on MMP1 expression. MMP1 regulation by miR-623 was investigated by real-time PCR, western blot, luciferase and transwell migration assays using an in vitro human BE model.

Results

Our results confirmed that brain metastatic TNBC cells express lower levels of miR-623 compared with cells having low propensity to spread toward the brain. miR-623 binds to the 3′-untranslated region of MMP1 transcript and downregulates its expression. Restoring miR-623 expression significantly decreased MMP1 expression, preserved the endothelial barrier integrity, and attenuated transmigration of BCBMC through the BE.

Conclusion

Our study elucidates, for the first time, the crucial role of miR-623 as MMP1 direct regulator in BCBMC and sheds light on miR-623 as a novel therapeutic target that can be exploited to predict and prevent brain metastasis in TNBC. Importantly, the presents study helps in unraveling a brain metastasis-specific microRNA signature in TNBC that can be used as a guide to personalized metastasis prediction and preventive approach with better therapeutic outcome.

Undernourished patients do not have increased risk of severe COVID-19 outcomes

Background

Undernutrition has been previously identified as a deleterious factor in acute infections. In covid-19 infection, obesity is a risk-factor of severe evolution, but initial undernutrition has not been evaluated yet.

Methods

We retrospectively analyzed correlation between nutritional status at admission and severe outcomes (intensive care unit admission, invasive mechanical ventilation requirement and death) of patients hospitalized for confirmed covid-19 infection.

Results

Risk of intensive care unit admission and invasive mechanical ventilation requirement was not significantly different between undernutrition and normoweight sub-groups, but increased in excessive weight sub-group (ODDR (IC 95%) 1.048 (1.011-1.086), p = 0.011). Risk of death was the same in all sub-groups.

Conclusion

Undernutrition didn't appear as a factor of severe outcomes in covid-19 infection.

Combined First Month Body Weight Loss and Development of Tolerance as Predictors of 6-Month Efficacy of Mazindol in Mild and Moderate Obese Subjects

The weight loss response to anti-obesity drugs is highly variable and poorly understood, which does not allow us to know, in advance, in which subjects the drug will be effective and in which it will not. The objective of this study was to explore the body weight reduction in kilograms in the first month (1mo-BWRkg) and the development of tolerance as predictors of 6-month efficacy for treatment with 1 mg mazindol twice a day. One hundred ninety-six obese subjects were individually or jointly analyzed. Approximately 60% of subjects developed tolerance to mazindol and achieved increasing proportional levels of 6-month efficacy according to 1mo-BWRkg intervals (<1 kg, 1 to <2 kg, 2 to <4 kg and ≥4 kg). Both moT and 1mo-BWRkg were significantly correlated with the mean percentage body weight reduction (BWR%) after 6-months of treatment. The qualitative analysis of both predictors on the progressive efficacy of mazindol was used to classify patients according to expected efficacy (inefficient, slightly effective, partially effective, or fully effective), based on the mean percentage efficacy and the number of subjects reaching a BWR% of <5%, 5 to <10%, 10 to <15% or ≥15%. In conclusion, combined 1mo-BWRkg and moT were early predictors for the progressive efficacy of 6-month mazindol anti-obesity therapy. This finding represents progress in predictive, preventive, and personalized medicine which could serve for estimating the expectations of individual efficacy with the use of the drug. and highlights the basic principle of personalized medicine, “one size does not fit all”.

Implementing a preimplantation proteomic approach to advance assisted reproduction technologies in the framework of predictive, preventive, and personalized medicine

The evolution of the field of assisted reproduction technology (ART) in the last 40 years has significantly contributed to the management of global infertility. Despite the great numbers of live births that have been achieved through ART, there is still potential for increasing the success rates. As a result, there is a need to create optimum conditions in order to increase ART efficacy. The selection of the best sperm, oocyte, and embryo, as well as the achievement of optimal endometrial receptivity, through the contribution of new diagnostic and treatment methods, based on a personalized proteomic approach, may assist in the attainment of this goal. Proteomics represent a powerful new technological development, which seeks for protein biomarkers in human tissues. These biomarkers may aid to predict the outcome, prevent failure, and monitor in a personalized manner in vitro fertilization (IVF) cycles. In this review, we will present data from studies that have been conducted in the search for such biomarkers in order to identify proteins related to good sperm, oocyte, and embryo quality, as well as optimal endometrial receptivity, which may later lead to greater results and the desirable ART outcome.

Methods to evaluate vascular function: a crucial approach towards predictive, preventive, and personalised medicine

Endothelium, the gatekeeper of our blood vessels, is highly heterogeneous and a crucial physical barrier with the ability to produce vasoactive and protective mediators under physiological conditions. It regulates vascular tone, haemostasis, vascular inflammation, remodelling, and angiogenesis. Several cardio-, reno-, and cerebrovascular diseases begin with the dysfunction of endothelial cells, and more recently, COVID-19 was also associated with endothelial disease highlighting the need to monitor its function towards prevention and reduction of vascular dysfunction. Endothelial cells are an important therapeutic target in predictive, preventive, and personalised (3P) medicine with upmost importance in vascular diseases. The development of novel non-invasive techniques to access endothelial dysfunction for use in combination with existing clinical imaging modalities provides a feasible opportunity to reduce the burden of vascular disease.

This review summarises recent advances in the principles of endothelial function measurements. This article presents an overview of invasive and non-invasive techniques to determine vascular function and their major advantages and disadvantages. In addition, the article describes mechanisms underlying the regulation of vascular function and dysfunction and potential new biomarkers of endothelial damage. Recognising these biomarkers is fundamental towards a shift from reactive to 3P medicine in the vascular field. Identifying vascular dysfunction earlier with non-invasive or minimally invasive techniques adds value to predictive diagnostics and targeted prevention (primary, secondary, tertiary care). In addition, vascular dysfunction is a potential target for treatments tailored to the person.

The Predictive Effect of the 8th AJCC Pathological Prognostic Staging on the Benefit of Postmastectomy Radiotherapy in N2/N3 Breast Cancer

Background

The role of the 8th American Joint Committee on Cancer (AJCC) pathological prognostic staging (PPS) on treatment-decision making of breast cancer (BC) remains unclear. This study aimed to investigate the predictive effect of the 8th AJCC PPS on the benefit of postmastectomy radiotherapy (PMRT) in N2/N3 BC.

Methods

We included women with stage N2/3 BC diagnosed between 2010 and 2018 from the Surveillance, Epidemiology, and End Results database. The effect of PMRT on breast cancer-specific survival (BCSS) was evaluated using the multivariate Cox proportional-hazards models.

Results

A total of 13,445 patients were identified, including 10,547 (78.4%) patients treated with PMRT. All patients had reassigned stages based on the 8th AJCC PPS. There were 7102 patients (52.8%) that had stage changed, including 1160 patients (8.6%) were upstaged and 5942 patients (44.2%) were downstaged from the 7th AJCC anatomical staging (AS) to the 8th AJCC PPS. Regarding the 7th AJCC AS, 7603 (56.5%), 948 (7.1%), and 4895 (36.4%) were stage IIIA, IIIB, and IIIC diseases, respectively. Using the 8th AJCC PPS, 3525 (26.2%), 460 (3.4%), 1335 (9.9%), 3457 (25.7%), 2169 (19.1%), and 2100 (15.6%) patients were restaged as IB, IIA, IIB, IIIA, IIIB, and IIIC diseases, respectively. The PPS displayed increased prognostic accuracy and improved model fit with respect to BCSS compared to the 7th AS (C-index, 0.731 vs 0.605, P < 0.001; Akaike Information Criterion, 42141 vs 43118). Regarding the AS, the receipt of PMRT was associated with a better BCSS in those with stage IIIA (P = 0.004), IIIB (P = 0.003), and IIIC (P < 0.001) diseases. Using the PPS, the receipt of PMRT was not associated with a better BCSS among patients with stage IB (P = 0.446), IIA (P = 0.140), and IIB (P = 0.248) disease, while the receipt of PMRT was associated with a better BCSS for those with stage IIIA (P = 0.009), IIIB (P < 0.001), and IIIC (P < 0.001) disease.

Conclusion

The 8th AJCC staging provides superior risk stratification and a better tool to predict the benefit of PMRT in N2/3 BC.

Anti-breast cancer effects of phytochemicals: primary, secondary, and tertiary care

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.

Development and Validation of a New Multiparametric Random Survival Forest Predictive Model for Breast Cancer Recurrence with a Potential Benefit to Individual Outcomes

Purpose

Breast cancer (BC) is a multi-factorial disease. Its individual prognosis varies; thus, individualized patient profiling is instrumental to improving BC management and individual outcomes. An economical, multiparametric, and practical model to predict BC recurrence is needed.

Patients and Methods

We retrospectively investigated the clinical data of BC patients treated at the Third Affiliated Hospital of Sun Yat-sen University and Liuzhou Women and Children’s Medical Center from January 2013 to December 2020. Random forest-recursive feature elimination (run by R caret package) was used to determine the best variable set, and the random survival forest method was used to develop a predictive model for BC recurrence.

Results

The training and validations sets included 623 and 151 patients, respectively. We selected 14 variables, the pathological (TNM) stage, gamma-glutamyl transpeptidase, total cholesterol, Ki-67, lymphocyte count, low-density lipoprotein, age, apolipoprotein B, high-density lipoprotein, globulin, neutrophil count to lymphocyte count ratio, alanine aminotransferase, triglyceride, and albumin to globulin ratio, using random survival forest (RSF)-recursive feature elimination. We developed a recurrence prediction model using RSF. Using area under the receiver operating characteristic curve and Kaplan–Meier survival analyses, the model performance was determined to be accurate. C-indexes were 0.997 and 0.936 for the training and validation sets, respectively.

Conclusion

The model could accurately predict BC recurrence. It aids clinicians in identifying high-risk patients and making treatment decisions for Breast cancer patients in China. This new multiparametric RSF model is instrumental for breast cancer recurrence prediction and potentially improves individual outcomes.

Prostate cancer treatment costs increase more rapidly than for any other cancer—how to reverse the trend?

According to GLOBOCAN, about 1.41 million new prostate cancer (PCa) cases were registered in the year 2020 globally. The corresponding socio-economic burden is enormous. Anti-cancer mRNA-based therapy is a promising approach, the principle of which is currently applied for anti-COVID-19 vaccination, undergoing a detailed investigation in populations considering its short- and long-term effectiveness and potential side effects. Pragmatically considered, it will take years or even decades to make mRNA therapy working for any type of cancers, and if possible, for individual malignancy sub-types which are many specifically for the PCa. Actually, the costs of treating PCa are increasing more rapidly than those of any other cancer. The trend has to be reversed now, not in a couple of years. In general, two main components are making currently applied reactive (management of clinically manifested disease) PCa treatment particularly expensive. On one hand, it is rapidly increasing incidence of the disease and metastatic PCa as its subtype. To this end, rapidly increasing PCa incidence rates in young and middle-aged male sub-populations should be taken into account as a long-term contributor to the metastatic disease potentially developed later on in life. On the other hand, patient stratification to differentiate between non-metastatic PCa (no need for an extensive and costly treatment) and particularly aggressive cancer subtypes requiring personalised treatment algorithms is challenging. Considering current statistics, it becomes obvious that reactive medicine got at its limit in PCa management. Multi-professional expertise is unavoidable to create and implement anti-PCa programmes in the population. In our strategic paper, we exemplify challenging PCa management by providing detailed expert recommendations for primary (health risk assessment), secondary (prediction and prevention of metastatic disease in PCa) and tertiary (making palliative care to the management of chronic disease) care in the framework of predictive, preventive and personalised medicine.

Sleep duration and atrial fibrillation risk in the context of predictive, preventive, and personalized medicine: the Suita Study and meta-analysis of prospective cohort studies

Background

Short and long sleep durations are common behaviors that could predict several cardiovascular diseases. However, the association between sleep duration and atrial fibrillation (AF) risk is not well-established. AF is preventable, and risk prevention approaches could reduce its occurrence. Investigating whether sleep duration could predict AF incidence for possible preventive interventions and determining the impact of various lifestyle and clinical characteristics on this association to personalize such interventions are essential. Herein, we investigated the association between sleep duration and AF risk using a prospective cohort study and a meta-analysis of epidemiological evidence.

Methods

Data of 6898 people, aged 30-84 years, from the Suita Study, were analyzed. AF was diagnosed during the follow-up by ECG, medical records, checkups, and death certificates, while a baseline questionnaire was used to assess sleep duration. The Cox regression was used to compute the hazard ratios (HRs) and 95% confidence intervals (CIs) of AF risk for daily sleep ≤ 6 (short sleep), ≥ 8 (long sleep), and irregular sleep, including night-shift work compared with 7 h (moderate sleep). Then, we combined our results with those from other eligible prospective cohort studies in two meta-analyses for the short and long sleep.

Results

In the Suita Study, within a median follow-up period of 14.5 years, short and irregular sleep, but not long sleep, were associated with the increased risk of AF in the age- and sex-adjusted models: HRs (95% CIs) = 1.36 (1.03, 1.80) and 1.62 (1.16, 2.26) and the multivariable-adjusted models: HRs (95% CIs) = 1.34 (1.01, 1.77) and 1.63 (1.16, 2.30), respectively. The significant associations between short and irregular sleep and AF risk remained consistent across different ages, sex, smoking, and drinking groups. However, they were attenuated among overweight and hypertensive participants. In the meta-analyses, short and long sleep durations were associated with AF risk: pooled HRs (95% CIs) = 1.21 (1.02, 1.42) and 1.18 (1.03, 1.35). No signs of significant heterogeneity across studies or publication bias were detected.

Conclusion

Short, long, and irregular sleep could be associated with increased AF risk. In the context of predictive, preventive, and personalized medicine, sleep duration should be considered in future AF risk scores to stratify the general population for potential personalized lifestyle modification interventions. Sleep management services should be considered for AF risk prevention, and these services should be individualized according to clinical characteristics and lifestyle factors.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00275-4.

Evaluation of thermal sensitivity is of potential clinical utility for the predictive, preventive, and personalized approach advancing metabolic syndrome management

A possible association between metabolic disorders and ambient temperature has been suggested, and cold exposure as a way of increasing energy expenditure has gained considerable interest for preventative/therapeutic measures toward metabolic disorders. Although thermal sensitivity, which has recently been studied in regard to its utility as a risk assessment/patient stratification for various diseases, might influence physiological responses to ambient temperature on an individual basis, more studies are needed. We aimed to investigate the association between self-identified thermal intolerance/sensation and metabolic syndrome (MetS) to verify the working hypothesis that individuals with altered thermal sensitivity may have a predisposition to MetS. We fitted generalized additive models for thermal intolerance/sensation using body mass index (BMI) and waist–hip ratio in women, and identified those with higher/lower thermal intolerance/sensation than those predicted by the models. Higher heat intolerance, higher heat sensation, and lower cold intolerance were associated with a higher prevalence of MetS. The risk of having MetS was increased in those who had two or three associated conditions compared with those with none of these conditions. In an analysis for MetS components, significant associations of thermal sensitivity were present with high glucose, triglyceride, and blood pressure levels. Overall, higher heat intolerance/sensation and lower cold intolerance were associated with increased prevalence of MetS even at a similar level of obesity. Our study indicates that evaluation of thermal sensitivity may help identify individuals at high risk for MetS, and lead to more advanced patient stratification and personalized treatment strategies for MetS, including cold-induced thermogenesis.

Systemic Effects Reflected in Specific Biomarker Patterns Are Instrumental for the Paradigm Change in Prostate Cancer Management: A Strategic Paper

Prostate cancer (PCa) is reported as the most common malignancy and second leading cause of death in America. In Europe, PCa is considered the leading type of tumour in 28 European countries. The costs of treating PCa are currently increasing more rapidly than those of any other cancer. Corresponding economic burden is enormous, due to an overtreatment of slowly developing disease on one hand and underestimation/therapy resistance of particularly aggressive PCa subtypes on the other hand. The incidence of metastatic PCa is rapidly increasing that is particularly characteristic for young adults. PCa is a systemic multi-factorial disease resulting from an imbalanced interplay between risks and protective factors. Sub-optimal behavioural patterns, abnormal stress reactions, imbalanced antioxidant defence, systemic ischemia and inflammation, mitochondriopathies, aberrant metabolic pathways, gene methylation and damage to DNA, amongst others, are synergistically involved in pathomechanisms of PCa development and progression. To this end, PCa-relevant systemic effects are reflected in liquid biopsies such as blood patterns which are instrumental for predictive diagnostics, targeted prevention and personalisation of medical services (PPPM/3P medicine) as a new paradigm in the overall PCa management. This strategic review article highlights systemic effects in prostate cancer development and progression, demonstrates evident challenges in PCa management and provides expert recommendations in the framework of 3P medicine.

Association of Serum Complement C1q and C3 Level with Age-Related Macular Degeneration in Women

PURPOSE

To investigate the association between serum complement components and age-related macular degeneration (AMD).

PATIENTS AND METHODS

A total of 118 AMD patients and age- and sex-matched 106 control subjects were included. Demographic data and the level of serum complement component (C)1q, C3 and C4 were evaluated. Based on sex, the subjects were stratified into male and female subgroups.

RESULTS

The level of C1q (226.31±45.33mg/dL) was significantly higher and C3 (121.14±15.76mg/dL) was significantly lower than that in control group (200.03±38.54mg/dL) (128.42±19.81mg/dL) in the female AMD patients (p = 0.005, p = 0.045). Logistic regression showed that increased C1q (OR = 1.132, p = 0.016) and decreased C3 (OR = 0.960, p = 0.048) were independent risk factors for female AMD patients. No statistical significance was observed in the male.

CONCLUSION

Increased C1q and decreased C3 were associated with increased risk of AMD, suggesting that the complement classical pathway probably be involved in AMD, especially in female.

Integrated genomic analysis of proteasome alterations across 11,057 patients with 33 cancer types: clinically relevant outcomes in framework of 3P medicine

Relevance

Proteasome, a cylindrical complex containing 19S regulatory particle lid, 19S regulatory particle base, and 20S core particle, acted as a major mechanism to regulate the levels of intracellular proteins and degrade misfolded proteins, which involved in many cellular processes, and played important roles in cancer biological processes. Elucidation of proteasome alterations across multiple cancer types will directly contribute to cancer medical services in the context of predictive, preventive, and personalized medicine (PPPM / 3P medicine).

Purpose

This study aimed to investigate proteasome gene alterations across 33 cancer types for discovery of effective biomarkers and therapeutic targets in the framework of PPPM practice in cancers.

Methods

Proteasome gene data, including gene expression RNAseq, somatic mutation, tumor mutation burden (TMB), copy number variant (CNV), microsatellite instability (MSI) score, clinical characteristics, immune phenotype, 22 immune cells, cancer stemness index, drug sensitivity, and related pathways, were systematically analyzed with publically available database and bioinformatics across 11,057 patients with 33 cancer types.

Results

Differentially expressed proteasome genes were extensively found between tumor and control tissues. PSMB4 occurred the top mutation event among proteasome genes, and those proteasome genes were significantly associated with TMB and MSI score. Most of proteasome genes were positively related to CNV among single deletion, control copy number, and single gain. Kaplan-Meier curves and COX regression survival analysis showed proteasome genes were significantly associated with patient survival rate across 33 cancer types. Furthermore, the expressions of proteasome genes were significantly different among different clinical stages and immune subtypes. The expressions of proteasome genes were correlated with immune-related scores (ImmuneScore, StromalScore, and ESTIMATEScore), 22 immune cells, and cancer stemness. The sensitivities of multiple drugs were closely related to proteasome gene expressions. The identified proteasome and proteasome-interacted proteins were significantly enriched in various cancer-related pathways.

Conclusions

This study provided the first landscape of proteasome alterations across 11,057 patients with 33 cancer types and revealed that proteasome played a significant and wide functional role in cancer biological processes. These findings are the precious scientific data to reveal the common and specific alterations of proteasome genes among 33 cancer types, which benefits the research and practice of PPPM in cancers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-021-00256-z.

Superficial temperature distribution patterns before and after physical activity in school children are indicative for personalized exercise coaching and disease prevention

Background

Thermoregulation is highly individual and predictive for potentially cascading pathologies. Altered and deficient thermoregulation is considered an important diagnostic indicator which can be of great clinical utility for specialized screening programs and individualized prediction and prevention of severe pathologies triggered early in life.

Working hypothesis

Individual thermoregulation can be objectively assessed by thermovision camera before and after exercises in school children stratified by age and gender that may be of great clinical utility for personalized training early in life in the framework of 3P medicine.

Study design

In this study, 60 female and male primary school children were exposed to physical exercises in the form of 45-min general fitness training. The subjects under examination were stratified by age: group 1 (7-year-olds), group 2 (9-year-olds), and group 3 (12-year-olds). Superficial body temperature patterns were measured by means of thermovision camera before and immediately after exercises, as well as after the 15-min recovery time. Temperature patterns were analyzed in 12 areas of the body front and back, covering trunk and upper and lower limbs.

Results

The obtained results revealed an individual and age-depended difference in response of the body to exercises. The first measurement prior to exercise (measurement 1) revealed no statistically significant differences in the mean surface temperature of all analyzed areas between 7- and 9-year-old children. Further, 7- and 9-year-old children did not differ significantly in the mean temperature recorded in the trunk compared to the 12-year-old children. However, in 12-year-old children, statistically significant higher values of the mean temperature of the upper and lower limbs, were observed compared to the group of 7-year-olds and significantly higher values of the mean temperature of the lower limbs compared to the group of 9-year-olds. Immediately after exercises (measurement 2), a statistically significant decrease in the temperature was noted in all groups and in all areas of the body. The greatest temperature change was observed in 12-year-olds, while the least one was measured in the youngest subjects. The statistically significant relation between the average trunk temperature of 7-year-old and 12-year-old children was observed: lower values of the mean temperature of the front and back of the trunk were noted in the group of 12-year-old children compared to the group of 7-year-olds. A significantly lower average temperature of the back of the trunk compared to the youngest group was also recorded in 9-year-old children. The study performed after the 15-min recovery time (measurement 3) showed an increase in the average temperature of all analyzed areas. In all subjects, the mean temperature recorded in measurement 3 did not differ significantly from the initial ones (measurement 1, prior to exercises). Only the mean temperature of the trunk back of 12-year-old children was significantly lower after the rest period compared to the initial examination. In all groups, the temperatures after exercises followed by a 15-min recovery returned to the initial ones, except of the trunk backs of 12-year-old children, where the temperature was lower than before exercises.

Conclusions and expert recommendations in the framework of 3PM

Thermovision analysis is an effective tool to assess individual thermoregulation and to stratify school children for personalized exercise coaching. Body exercise-based disease prevention early in life is effective when tailored to the person: multi-parametric guidance for prescribing exercises individually is needed. Contextually, proposed individualized training approach should be adapted to the age-dependent particularities and individual thermoregulation.

How biomarker patterns can be utilized to identify individuals with a high disease burden: a bioinformatics approach towards predictive, preventive, and personalized (3P) medicine

Prevalences of non-communicable diseases such as depression and a range of somatic diseases are continuously increasing requiring simple and inexpensive ways to identify high-risk individuals to target with predictive and preventive approaches. Using k-mean cluster analytics, in study 1, we identified biochemical clusters (based on C-reactive protein, interleukin-6, fibrinogen, cortisol, and creatinine) and examined their link to diseases. Analyses were conducted in a US American sample (from the Midlife in the US study, N = 1234) and validated in a Japanese sample (from the Midlife in Japan study, N = 378). In study 2, we investigated the link of the biochemical clusters from study 1 to childhood maltreatment (CM). The three identified biochemical clusters included one cluster (with high inflammatory signaling and low cortisol and creatinine concentrations) indicating the highest disease burden. This high-risk cluster also reported the highest CM exposure. The current study demonstrates how biomarkers can be utilized to identify individuals with a high disease burden and thus, may help to target these high-risk individuals with tailored prevention/intervention, towards personalized medicine. Furthermore, our findings raise the question whether the found biochemical clusters have predictive character, as a tool to identify high-risk individuals enabling targeted prevention. The finding that CM was mostly prevalent in the high-risk cluster provides first hints that the clusters could indeed have predictive character and highlight CM as a central disease susceptibility factor and possibly as a leverage point for disease prevention/intervention.

All around suboptimal health - a joint position paper of the Suboptimal Health Study Consortium and European Association for Predictive, Preventive and Personalised Medicine

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person. This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions:Stress overload associated pathologiesMale and female healthPlanned pregnanciesPeriodontal healthEye disordersInflammatory disorders, wound healing and pain management with associated complicationsMetabolic disorders and suboptimal body weightCardiovascular pathologiesCancersStroke, particularly of unknown aetiology and in young individualsSleep medicineSports medicineImproved individual outcomes under pandemic conditions such as COVID-19.