Precision Medicine in Lifestyle Medicine: The Way of the Future?

Intelligent Care: A Scientometric Analysis of Artificial Intelligence in Precision Medicine

The integration of advanced computational methods into precision medicine represents a transformative advancement in healthcare, enabling highly personalized treatment strategies based on individual genetic, environmental, and lifestyle factors. These methodologies have significantly enhanced disease diagnostics, genomic analysis, and drug discovery. However, rapid expansion in this field has resulted in fragmented understandings of its evolution and persistent knowledge gaps. This study employs a scientometric approach to systematically map the research landscape, identify key contributors, and highlight emerging trends in precision medicine. Methods: A scientometric analysis was conducted using data retrieved from the Scopus database, covering publications from 2019 to 2024. Tools such as VOSviewer and R-bibliometrix package (version 4.3.0) were used to perform co-authorship analysis, co-citation mapping, and keyword evolution tracking. The study examined annual publication growth, citation impact, research productivity by country and institution, and thematic clustering to identify core research areas. Results: The analysis identified 4574 relevant publications, collectively amassing 70,474 citations. A rapid growth trajectory was observed, with a 34.3% increase in publications in 2024 alone. The United States, China, and Germany emerged as the top contributors, with Harvard Medical School, the Mayo Clinic, and Sichuan University leading in institutional productivity. Co-citation and keyword analysis revealed three primary research themes: diagnostics and medical imaging, genomic and multi-omics data integration, and personalized treatment strategies. Recent trends indicate a shift toward enhanced clinical decision support systems and precision drug discovery. Conclusions: Advanced computational methods are revolutionizing precision medicine, spurring increased global research collaboration and rapidly evolving methodologies. This study provides a comprehensive knowledge framework, highlighting key developments and future directions. The insights derived can inform policy decisions, funding allocations, and interdisciplinary collaborations, driving further advancements in healthcare solutions.

Exposure-Informed Care Following Toxic Environmental Exposures: A Lifestyle Medicine Approach

Exposure to environmental toxins presents substantial health risks, particularly for individuals facing heightened exposure due to occupational hazards. This analytic review highlights the critical need to address these risks through a lifestyle medicine approach, advocating for integrated care strategies to mitigate the long-term health impacts of toxic environmental exposures. We explore exposures to environmental toxins in 2 at-risk populations, military service members exposed to airborne hazards and burn pits during overseas deployments and first responders to the World Trade Center terrorist attack. The review highlights the immediate and long-term chronic health effects of toxic environmental exposures, emphasizing the variable symptoms, long latency, and long-term complex outcomes that necessitate an exposure-informed health care model. Exposure-informed care can enhance overall well-being and reduce the risks of chronic illnesses by incorporating lifestyle medicine principles supported by a learning community system. The proposed model makes recommendations for a shift to exposure-informed preventative care. This enhanced approach aims to promote a longer and healthier life for those at increased risks following toxic environmental exposures. Understanding the context of military burn pit and World Trade Center environmental exposures and the possibilities of exposure-informed care is paramount in shifting from a traditional disease-centered model to a holistic, person-centered approach.

An In Silico Modelling Approach to Predict Hemodynamic Outcomes in Diabetic and Hypertensive Kidney Disease

Early diagnosis of kidney disease remains an unmet clinical challenge, preventing timely and effective intervention. Diabetes and hypertension are two main causes of kidney disease, can often appear together, and can only be distinguished by invasive biopsy. In this study, we developed a modelling approach to simulate blood velocity, volumetric flow rate, and pressure wave propagation in arterial networks of ageing, diabetic, and hypertensive virtual populations. The model was validated by comparing our predictions for pressure, volumetric flow rate and waveform-derived indexes with in vivo data on ageing populations from the literature. The model simulated the effects of kidney disease, and was calibrated to align quantitatively with in vivo data on diabetic and hypertensive nephropathy from the literature. Our study identified some potential biomarkers extracted from renal blood flow rate and flow pulsatility. For typical patient age groups, resistive index values were 0.69 (SD 0.05) and 0.74 (SD 0.02) in the early and severe stages of diabetic nephropathy, respectively. Similar trends were observed in the same stages of hypertensive nephropathy, with a range from 0.65 (SD 0.07) to 0.73 (SD 0.05), respectively. Mean renal blood flow rate through a single diseased kidney ranged from 329 (SD 40, early) to 317 (SD 38, severe) ml/min in diabetic nephropathy and 443 (SD 54, early) to 388 (SD 47, severe) ml/min in hypertensive nephropathy, showing potential as a biomarker for early diagnosis of kidney disease. This modelling approach demonstrated its potential application in informing biomarker identification and facilitating the setup of clinical trials.

Lifestyle factors in the biomedical literature: an ontology and comprehensive resources for named entity recognition

MOTIVATION

Despite lifestyle factors (LSFs) being increasingly acknowledged in shaping individual health trajectories, particularly in chronic diseases, they have still not been systematically described in the biomedical literature. This is in part because no named entity recognition (NER) system exists, which can comprehensively detect all types of LSFs in text. The task is challenging due to their inherent diversity, lack of a comprehensive LSF classification for dictionary-based NER, and lack of a corpus for deep learning-based NER.

RESULTS

We present a novel lifestyle factor ontology (LSFO), which we used to develop a dictionary-based system for recognition and normalization of LSFs. Additionally, we introduce a manually annotated corpus for LSFs (LSF200) suitable for training and evaluation of NER systems, and use it to train a transformer-based system. Evaluating the performance of both NER systems on the corpus revealed an F-score of 64% for the dictionary-based system and 76% for the transformer-based system. Large-scale application of these systems on PubMed abstracts and PMC Open Access articles identified over 300 million mentions of LSF in the biomedical literature.

AVAILABILITY AND IMPLEMENTATION

LSFO, the annotated LSF200 corpus, and the detected LSFs in PubMed and PMC-OA articles using both NER systems, are available under open licenses via the following GitHub repository: https://github.com/EsmaeilNourani/LSFO-expansion. This repository contains links to two associated GitHub repositories and a Zenodo project related to the study. LSFO is also available at BioPortal: https://bioportal.bioontology.org/ontologies/LSFO.

Harnessing bacterial metabolites for enhanced cancer chemotherapy: unveiling unique therapeutic potentials

Cancer poses a serious threat to health globally, with millions diagnosed every year. According to Global Cancer Statistics 2024, about 20 million new cases were reported in 2022, and 9.7 million people worldwide died of this condition. Advanced therapies include combination of one or more treatment procedures, depending on the type, stage, and particular genetic constitution of the cancer, which may include surgery, radiotherapy, chemotherapy, immunotherapy, hormone therapy, targeted therapy, and stem cell transplant. Also, awareness about lifestyle changes, preventive measures and screening at early stages has reduced the incidence of the disease; still, there is a major failure in controlling the incidence of cancer because of its complex and multifaceted nature. With increasing interest in bacterial metabolites as possible novel and effective treatment options in cancer therapy, their main benefits include not only direct anticancer effects but also the modulation of the immune system and potential for targeted and combination therapies. They can therefore be used in combination with chemotherapy, radiotherapy, or immunotherapy to improve outcomes or reduce side effects. Furthermore, nanoparticle-based delivery systems have the potential to enhance the potency and safety of anticancer drugs by providing improved stability, targeted release, and controlled delivery.

Ferroptosis and circular RNAs: new horizons in cancer therapy

Cancer poses intricate challenges to treatment due to its complexity and diversity. Ferroptosis and circular RNAs (circRNAs) are emerging as innovative therapeutic avenues amid the evolving landscape of cancer therapy. Extensive investigations into circRNAs reveal their diverse roles, ranging from molecular regulators to pivotal influencers of ferroptosis in cancer cell lines. The results underscore the significance of circRNAs in modulating molecular pathways that impact crucial aspects of cancer development, including cell survival, proliferation, and metastasis. A detailed analysis delineates these pathways, shedding light on the molecular mechanisms through which circRNAs influence ferroptosis. Building upon recent experimental findings, the study evaluates the therapeutic potential of targeting circRNAs to induce ferroptosis. By identifying specific circRNAs associated with the etiology of cancer, this analysis paves the way for the development of targeted therapeutics that exploit vulnerabilities in cancer cells. This review consolidates the existing understanding of ferroptosis and circRNAs, emphasizing their role in cancer therapy and providing impetus for ongoing research in this dynamic field. See also the graphical abstract(Fig. 1).

Breast cancer stem cells as novel biomarkers

Breast cancer is the most common cancer and the leading cause of mortality worldwide. Despite advancements in detection and treatment, it remains a major cause of cancer-related deaths in women. Breast cancer stem cells (BCSCs) are a crucial group of cells responsible for carcinogenesis, metastasis, medication resistance, and tumor recurrence. Identifying and understanding their molecular pathways is essential for developing effective breast cancer therapy. BCSCs are responsible for tumor genesis, development, metastasis, treatment resistance, and recurrence. Biomarkers are essential tools for identifying high-risk patients, improving diagnostic accuracy, developing follow-up programs, assessing treatment susceptibility, and predicting prognostic outcomes. Stem cell intervention therapy can provide specialized tools for precision therapy. Biomarker analysis in cancer patients is crucial to identify cells associated with disease progression and post-therapeutic relapse. However, negative post-therapeutic impacts can enhance cancer stemness by boosting BCSCs plasticity phenotypes, activating stemness pathways in non-BCSCs, and promoting senescence escape, leading to tumor relapse and metastasis. Despite the advancements in precision medicine, challenges persist in identifying stem cell markers, limiting the number of eligible patients for treatment. The diversity of biomedical research hinders the development of individualization-based preventative, monitoring, and treatment strategies, especially in oncology. Integrating and interpreting clinical and scientific data remains challenging. The development of stem cell-related indicators could significantly improve disease precision, enabling stem cell-targeted therapy and personalized treatment plans, although BCSCs are promising for breast cancer treatment optimization, serving as biomarkers for current therapy modalities. This summary discusses recent advancements in breast cancer stem cell research, including biomarkers, identification methods, molecular mechanisms, and tools for studying their biological origin and lineage development for precision medicine.

Preventive Medicine via Lifestyle Medicine Implementation Practices Should Consider Individuals' Complex Psychosocial Profile

Noncommunicable chronic diseases are associated with lifestyle behaviors. Psychological and social factors may influence the adoption of such behaviors. Being mentally and physically energized or fatigued may influence the intention-behavior gap of healthy lifestyle adoption accordingly. We investigated the associations of age, sex, lifestyle behaviors, mood, and mental and physical energy and fatigue at both the trait and state levels. The participants (N = 670) completed questionnaires assessing their sleep, mood, mental and physical state energy and fatigue, physical activity, mental workload, and diet. The ordinary least squares regression models revealed an overlap between the mental state and trait energy levels for males who consume polyphenols, have a high mental workload, and sleep well. Being younger, having a high stress level, bad sleep habits, and being confused and depressed were associated with high mental fatigue. Physical energy and fatigue shared the same commonalities with the previous results, with greater discrepancies observed between the state and trait indicators compared to that between mental energy and fatigue. Diet and stress management seem to be predictors of high physical energy, and females report higher physical fatigue levels. Health care professionals should consider this psychosocial complex profiling in their differential diagnosis and when one is implementing lifestyle behavioral changes to address the facets of preventive medicine, wellness, and health promotion.

Social-Ecological Measurement of Daily Life: How Relationally Focused Ambulatory Assessment can Advance Clinical Intervention Science

Individuals’ daily behaviors and social interactions play a central role in the diagnosis and treatment of psychological disorders. Despite this, observational ambulatory assessment methods—research methods that allow for direct and passive assessment of individuals’ momentary activities and interactions—have a remarkably scant history in the clinical science field. Prior discussions of ambulatory assessment methods in clinical science have focused on subjective methods (e.g., ecological momentary assessment) and physiological methods (e.g., wearable heart rate monitoring). Comparatively less attention has been dedicated to ambulatory assessment methods that collect objective, relational data about individuals’ social behaviors and their interactions with their momentary environmental contexts. Drawing on extant social-ecological measurement frameworks, this article first provides a conceptual and psychometric rationale for the integration of daily relational data into clinical science research. Next, the nascent research applying such methods to clinical science is reviewed, and priorities for further research organized by the NIH Stage Model for Clinical Science Research are recommended. These data can provide unique information about the social contexts of diverse patient populations; identify social-ecological targets for transdiagnostic, precision, and culturally responsive interventions; and contribute novel data about the effectiveness of established interventions at creating behavioral and relational change.

The Niche of n-of-1 Trials in Precision Medicine for Weight Loss and Obesity Treatment: Back to the Future

PURPOSE OF REVIEW

The n-of-1 clinical trials are considered the epitome of individualized health care. They are employed to address differences in treatment response and adverse events between patients, in a comparative effectiveness manner, extending beyond the delivery of horizontal recommendations for all.

RECENT FINDINGS

The n-of-1 design has been applied to deliver precision exercise interventions, through eHealth and mHealth technologies. Regarding personalized and precision medical nutrition therapy, few trials have implemented dietary manipulations and one series of n-of-1 trials has applied comprehensive genetic data to improve body weight. With regard to anti-obesity medication, pharmacogenetic data could be applied using the n-of-1 trial design, although none have been implemented yet. The n-of-1 clinical trials consist of the only tool for the delivery of evidence-based, personalized obesity treatment (lifestyle and pharmacotherapy), reducing non-responders, while tailoring the best intervention to each patient, through "trial and error". Their application is expected to improve obesity treatment and mitigate the epidemic.

Personalised Nutritional Recommendations Based on Individual Post-Prandial Glycaemic Responses Improve Glycaemic Metrics and PROMs in Patients with Type 2 Diabetes: A Real-World Assessment

The recommended first-line therapy in type 2 diabetes (T2D) is lifestyle modification. In many patients, such interventions fail, and disease progresses inexorably to medication requirement. A potential reason for the failure of standard nutritional interventions is the use of generic dietary advice, with no personalisation to account for differences in the effect of food on blood glucose between different individuals. Another is the lack of instant feedback on the impact of dietary modification on glycaemic control, which supports sustained behaviour change. The use of continuous glucose monitoring (CGM) may help address both these shortcomings. We conducted an observational study to explore how personalised nutritional information impacts glycaemic control and patient-reported outcome measures (PROMs) of well-being. Free-living people with T2D eating their normal diet were provided with personalised nutritional recommendations by state-registered nutritionists based on the CGM-enabled analysis of individual post-prandial glycaemic responses (PPGRs). Participants demonstrated considerable inter-individual differences in PPGRs, reductions in post-prandial incremental area under the curve (iAUC) and daytime AUC, and improvements in energy levels, ability to concentrate, and other PROMs. These results suggest a role for personalised nutritional recommendations based on individual-level understanding of PPGRs in the non-pharmaceutical management of T2D.

Desafios atuais e futuros do uso da medicina de precisão no acesso ao diagnóstico e tratamento de câncer no Brasil

Este artigo busca refletir, cultural e eticamente, sobre os desafios atuais e futuros da incorporação de novas biotecnologias de diagnóstico e tratamento de câncer no Brasil, bem como seu impacto no acesso e no controle do câncer no país. Para tanto, esta pesquisa parte da problematização da literatura sobre o tema e dos resultados de um estudo, que realizou uma websurvey com especialistas médicos dos setores público e privado brasileiros, associados às dez sociedades oncológicas mais representativas do país, atuantes nas áreas da clínica, cirurgia, radioterapia, patologia e diagnóstico. A discussão do estudo desenvolve-se em torno de três eixos temáticos: conhecimento e expectativas sobre o advento das novas tecnologias para o diagnóstico e tratamento do câncer; considerações estruturais e éticas envolvidas no uso atual e futuro das novas tecnologias; e possíveis cenários associados ao uso e aplicação das novas tecnologias para o diagnóstico e tratamento do câncer. Foram suscitadas algumas questões: novos paradigmas tecnológicos beneficiarão todos os usuários do Sistema Único de Saúde (SUS) ou serão privilégios de poucos? Diminuirão as discrepâncias em termos de oferta de distribuição de serviços, de recursos tecnológicos e de acesso ao diagnóstico e tratamento do câncer? Como diversos segmentos da sociedade poderão participar e influir nesse processo? Que tipos de cenários poderão ainda compor esse quadro? Visando contribuir com o planejamento da atenção ao câncer no Brasil, o artigo finaliza propondo o desenvolvimento de futuras ações a partir de cinco dimensões estratégicas: dimensão econômica; dimensão científica, de inovação e tecnológica; dimensão estrutural; dimensão cultural; e dimensão reguladora.

Governing Personalized Health: A Scoping Review

Genetic research is advancing rapidly. One important area for the application of the results from this work is personalized health. These are treatments and preventive interventions tailored to the genetic profile of specific groups or individuals. The inclusion of personalized health in existing health systems is a challenge for policymakers. In this article, we present the results of a thematic scoping review of the literature dealing with governance and policy of personalized health. Our analysis points to four governance challenges that decisionmakers face against the background of personalized health. First, researchers have highlighted the need to further extend and harmonize existing research infrastructures in order to combine different types of genetic data. Second, decisionmakers face the challenge to create trust in personalized health applications, such as genetic tests. Third, scholars have pointed to the importance of the regulation of data production and sharing to avoid discrimination of disadvantaged groups and to facilitate collaboration. Fourth, researchers have discussed the challenge to integrate personalized health into regulatory-, financing-, and service provision structures of existing health systems. Our findings summarize existing research and help to guide further policymaking and research in the field of personalized health governance.

Lifestyle Medicine – New Concept, Innovative Discipline

A large percentage 63% of premature deaths and chronic diseases could be prevented by adhering to healthy dietary patterns, being physically active and avoid smoking. The concept of lifestyle medicine introduced 20 years ago by Rippe is defined as the integration of modern lifestyle practices into evidence-based medicine, in order to lower risk factors or to be support for chronic therapies. A new taxonomy is proposed in lifestyle medicine, with determinants, as drivers for chronic diseases, anthropogens and metaflammation, the metabolic inflammatory state. Other possible determinants are proposed for lack os scope in life, estrangement and lost identity. Despite all health messages, healthy behaviors are exceptions, not the rule. It will be important in the future to change how practitioners will support individuals in their efforts to live healthier. More psychological and social factors should be analyzed. Many doctors are not self-confident with prescribing healthy lifestyle or nutritional recommendations. Creating a new discipline should foster development of preventive recommendations. General practitioners will need specific academic trainings to learn how to promote recommendations for lifestyle changes for health, for prevention and for diseases management, starting by adopting themselves healthy lifestyles.