Pular para o conteúdo principal

ETHNOS_APP

Início • Busca • Periódicos • Lista 0

Health is beyond genetics

On the integration of lifestyle and environment in real-time for hyper-personalized medicine

Dados Bibliográficos

ID22082606
AutoresMyles Joshua Toledo Tan (0000-0002-1426-6526, University of Florida, autor correspondente), Harishwar Reddy Kasireddy (University of Florida Health), Alfredo Bayu Satriya (0009-0009-3055-0613, University of Florida), Hezerul Abdul Karim (0000-0002-7613-4596, Multimedia University, autor correspondente), Nouar AlDahoul (0000-0001-5522-0033, New York University Abu Dhabi)
Ano2025
Volume12
Páginas1522673-1522673
Data de publicação2025-01-07
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoFrontiers in Public Health (JOURNAL)
Identificadores do periódicoISSN: 2296-2565 • E-ISSN: 2296-2565
EditoraFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1522673
PMID39839379
OpenAlexW4406128677
IdiomaEN
Citações recebidas5
Referências citadas97

Hyper-personalized medicine represents the cutting edge of healthcare, which aims to tailor treatment and prevention strategies uniquely to each individual. Unlike traditional approaches, which often adopt a one-size-fits-all or even broadly personalized approach based on broad genetic categories, hyper-personalized medicine considers an individual’s comprehensive health data by integrating unique biological, genetic, lifestyle, and environmental influences. This method goes beyond simple genetic profiling by recognizing that health outcomes are influenced by complex interactions among our environment, daily routines, and physiological processes and responses.Central to hyper-personalized medicine is the integration of lifestyle and environmental factors. Lifestyle habits, such as diet (Dalwood et al., 2020; Genel et al., 2020; Marx et al., 2020; Hepsomali & Groeger, 2021; Dinu et al., 2022; Yang et al., 2022; Sadler et al., 2024), exercise (Chow et al., 2022; Qiu et al., 2022; Ross et al., 2022; D’Onofrio et al., 2023; Isath et al., 2023; Mahindru et al., 2023; Ashcroft et al., 2024; Ponzano et al., 2024), and sleep patterns (Hepsomali & Groeger, 2021; Baranwal et al., 2023; Eshera et al., 2023; Lim et al., 2023; Sletten et al., 2023; Uccella, 2023; Weinberger et al., 2023), directly impact health. Hence, understanding these factors helps tailor interventions that align with the day-to-day realities of an individual. Environmental factors, such as air quality (Cheek et al., 2020; Markandeya et al., 2020; Shukla et al., 2022; Tang et al., 2022; Abdul-Rahman et al., 2024; Bedi & Bhattacharya, 2024), climate (Coates et al., 2020; Ebi et al., 2021; Helldén et al., 2021; Reismann et al., 2021; Rocque et al., 2021; Zhang et al., 2021; Münzel et al., 2024; Palmeiro-Silva et al., 2024), and exposure to pollutants (Qadri & Faiq, 2019; Petroni et al., 2020; Lin et al., 2022; Sun et al., 2022; Xu et al., 2022; Yu et al., 2022; Levin et al., 2023; Shetty et al., 2023; Deziel & Villanueva 2024; Sharma et al., 2024), also play significant roles in determining health outcomes. By continuously monitoring and analyzing these elements, healthcare providers can create dynamic health plans that adapt to real-time changes. This would allow for proactive measures and optimized care.To enable such a complex model of care, advanced technologies like quantum computing, artificial general intelligence (AGI), internet of things (IoT), and 6G connectivity play crucial roles. Quantum computing offers the ability to process vast and intricate datasets, such as those required to model interactions between genetic markers, environmental exposures, and lifestyle choices, with far greater speed and accuracy than classical computing (Munshi et al., 2023; Kumar et al., 2024; Stefano, 2024; Ullah & Garcia-Zapirain, 2024; Yu et al., 2024). AGI, with its adaptive learning capabilities, can analyze and make sense of this data to provide precise, evolving recommendations that change as a patient’s environment or lifestyle does (Liu et al., 2024; Mitchell, 2024; Sun et al., 2024; Tu et al., 2024). IoT devices, including wearables and environmental sensors, gather continuous data from individuals, tracking physical activity, biometrics, and environmental conditions like air quality and humidity (Puri et al., 2021; Islam et al., 2024; Mathkor et al., 2024; Rocha et al., 2024; Šajnović et al., 2024; Salam, 2024). With the advent of 6G connectivity, this data is seamlessly transferred and processed in real time, enabling instant feedback and intervention (Nayak & Patgiri, 2021; Nguyen et al., 2021; Ahad et al., 2024; Kumar, Kaur, et al., 2024; Mahmood et al., 2024; Mihovska et al., 2024).Together, these technologies form the backbone of a hyper-personalized healthcare model, which will push beyond traditional medical practices to create a highly responsive, individual-centered approach to health. As these advancements continue to evolve, hyper-personalized medicine has the potential to fundamentally reshape healthcare, offering truly personalized interventions that support long-term health and well-being

Bioinformatics · Biology · Family medicine · Health care · Lifestyle medicine · Personalized medicine · Psychological intervention · Cardiovascular Health and Risk Factors · Health, Environment, Cognitive Aging · Medicine · Nursing · Nutrition, Genetics, and Disease · Psychology · Gerontology

  • Opportunities and challenges of artificial intelligence in public health

    Open Access•Qin Gao, Lin Chen et al.•Frontiers in Public Health•2026

  • A dialectical lens for AI and medical humanities

    Open Access•Sifan Chen, Zining Peng et al.•Frontiers in Public Health•2026

  • Equity at the point of care

    Open Access•Fan Gao, Danli Xie•Frontiers in Public Health•2026

  • The future of multimorbidity management in the older adults

    Open Access•Wei Deng, Liying Zhang et al.•Frontiers in Public Health•2026

  • Personalized medicine and health equity

    Open Access•Kishi Kobe Yee Francisco, Andrane Estelle Carnicer Apuhin et al.•International Journal for Equity…•2025

  • Health effects of climate change

    Open Access•Rhéa Rocque, Caroline Beaudoin et al.•BMJ Open•2021

  • Climate change and child health

    Open Access•Daniel Helldén, Camilla Andersson et al.•The Lancet Planetary Health•2021

  • Extreme Weather and Climate Change

    Open Access•Kristie L Ebi, Jennifer Vanos et al.•Annual Review of Public Health•2021

  • Moral Injury and the Ethic of Care

    Open Access•Carol Gilligan•Journal of Social Philosophy•2014

  • Role of Physical Activity on Mental Health and Well-Being

    Open Access•Aditya Mahindru, Pradeep Patil et al.•Cureus•2023

  • Shaping the future of AI in healthcare through ethics and governance

    Open Access•Rabaï Bouderhem•Humanities and Social Sciences…•2024

  • Moral distance, AI, and the ethics of care

    Open Access•Carolina Villegas-Galaviz, Enrique Castelló Muñoz et al.•AI & Society•2024

  • Hazardous air pollutant exposure as a contributing factor to Covid-19 mortality in the United States

    Open Access•Michael Petroni, Dustin Hill et al.•Environmental Research Letters•2020

  • Association between Diet Quality and Health Outcomes among Children in Rural Areas of Northwest China

    Open Access•Wanni Yang, Shaoping Li et al.•International Journal of…•2022

  • Groundwork for the Metaphysics of Morals

    Christoph Horn, Dieter Schönecker et al.•Groundwork for the Metaphysics of…•2006

Obras citantes distintas5
Citações por ano5
Intervalo de citações2025 - 2026 (2)
Velocidade de citaçãocurrent
Altamente citadoNão
Tipos de citaçãoNeutras: 5
Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae