Towards AI-driven longevity research: An overview

Marino, Nicola; Putignano, Guido; Cappilli, Simone; Chersoni, Emmanuele; Santuccione, Antonella; Calabrese, Giuliana; Bischof, Evelyne; Vanhaelen, Quentin; Zhavoronkov, Alex; Scarano, Bryan; Mazzotta, Alessandro; Santus, Enrico

doi:10.3389/fragi.2023.1057204

Cited by 15 publications

(7 citation statements)

References 127 publications

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“…In the present study, a higher blood biological age was associated with high SB and a trend of low PA. The ageing clock technology is currently being used in various products for health screening and is at the foundation of the emerging longevity medicine field [36,37]. Additionally, ageing clocks are widely used in anti-ageing research and are actively being patented for commercial applications [38,39].…”

Section: Association Of Blood Biological Age With Objectively Measure...mentioning

confidence: 99%

The association between blood biological age at rehabilitation admission and physical activity during rehabilitation in geriatric inpatients: RESORT

Lu,

Guan,

Wang

et al. 2024

GeroScience

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Geriatric rehabilitation inpatients have high levels of sedentary behaviour (SB) and low levels of physical activity (PA). Biological age predicted by blood biomarkers is indicative of adverse outcomes. The objective was to determine the association between blood biological age at rehabilitation admission and levels of SB and PA during rehabilitation in geriatric inpatients. Inpatients admitted to geriatric rehabilitation wards at the Royal Melbourne Hospital (Melbourne, Australia) from October 22, 2019, to March 29, 2020, in the REStORing health of acute unwell adulTs (RESORT) observational cohort were included. Blood biological age was predicted using SenoClock-BloodAge, a hematological ageing clock. Patients wore an inertial sensor to measure SB and PA. Logistic regression analyses were conducted. A total of 111 patients (57.7% female) with mean age 83.3 ± 7.5 years were included in the analysis. The mean blood biological age was 82.7 ± 8.4 years. Patients with 1-year higher blood biological age had higher odds of having high SB measured as non-upright time greater than 23 h/day (odds ratio (OR): 1.050, 95% confidence interval (CI): 1.000–1.102). Individuals having 1-year higher age deviation trended towards lower odds of having high levels of PA measured as stepping time greater than 7.4 min/day (OR: 0.916, CI: 0.836–1.005) and as greater than 19.5 sit-to-stand transitions/day (OR: 0.915, CI: 0.836–1.002). In conclusion, higher biological age was associated with higher levels of SB and trended towards lower PA. Incorporating blood biological age could facilitate resource allocation and the development of more tailored rehabilitation plans.

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Section: Association Of Blood Biological Age With Objectively Measure...mentioning

confidence: 99%

The association between blood biological age at rehabilitation admission and physical activity during rehabilitation in geriatric inpatients: RESORT

Lu,

Guan,

Wang

et al. 2024

GeroScience

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“…Currently, AI technologies for aging population are used in the robotic intervention ( 80 , 81 ), applications on smartphones or computers ( 82 , 83 ), social interaction and support, such as improved mental well-being and quality of life ( 84–86 ); rehabilitation therapy, such as its application in the recovery of upper and lower extremity functions, gait robotic rehabilitation, or improve sleep quality and daily living activities ( 87–90 ), and wearables, voice-activated ( 91–94 ). It can create more advanced algorithms to provide more precise holistic interventions tailored to address the elders’ multiple needs in a safer and more friendly manner ( 78 , 95 , 96 ). Ambient-assisted working and ambient-assisted living are examples of smart systems that can adapt themselves to older adult needs by exploiting ambient intelligence solutions.…”

Section: Ai In Population Agingmentioning

confidence: 99%

“…These systems focus on using technology to support and enhance the quality of life of the older adult population, either in work, or indoor and outdoor environments ( 97 , 98 ). Recently, a group of researchers have helped develop drugs that might potentially delay the effects of aging by eliminating senescent cells ( 96 , 99 ).…”

Section: Ai In Population Agingmentioning

confidence: 99%

The leading global health challenges in the artificial intelligence era

Zaidan

2023

Front. Public Health

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Millions of people’s health is at risk because of several factors and multiple overlapping crises, all of which hit the vulnerable the most. These challenges are dynamic and evolve in response to emerging health challenges and concerns, which need effective collaboration among countries working toward achieving Sustainable Development Goals (SDGs) and securing global health. Mental Health, the Impact of climate change, cardiovascular diseases (CVDs), diabetes, Infectious diseases, health system, and population aging are examples of challenges known to pose a vast burden worldwide. We are at a point known as the “digital revolution,” characterized by the expansion of artificial intelligence (AI) and a fusion of technology types. AI has emerged as a powerful tool for addressing various health challenges, and the last ten years have been influential due to the rapid expansion in the production and accessibility of health-related data. The computational models and algorithms can understand complicated health and medical data to perform various functions and deep-learning strategies. This narrative mini-review summarizes the most current AI applications to address the leading global health challenges. Harnessing its capabilities can ultimately mitigate the Impact of these challenges and revolutionize the field. It has the ability to strengthen global health through personalized health care and improved preparedness and response to future challenges. However, ethical and legal concerns about individual or community privacy and autonomy must be addressed for effective implementation.

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“…Moreover, artificial intelligence (AI)-driven platforms, such as PandaOmics, have facilitated the identification and prioritization of novel aging-associated targets for drug discovery and repurposing [7]. Recent studies have also demonstrated the value of AI in advancing longevity research by harnessing the power of nextgeneration sequencing data and omics technologies [8]. AGING Insilico Medicine has been at the forefront of using generative AI in biology since 2016 [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery

Urban¹,

Sidorenko²,

Zagirova³

et al. 2023

Aging

Self Cite

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Aging is a complex and multifactorial process that increases the risk of various age-related diseases and there are many aging clocks that can accurately predict chronological age, mortality, and health status. These clocks are disconnected and are rarely fit for therapeutic target discovery. In this study, we propose a novel approach to multimodal aging clock we call Precious1GPT utilizing methylation and transcriptomic data for interpretable age prediction and target discovery developed using a transformer-based model and transfer learning for casecontrol classification. While the accuracy of the multimodal transformer is lower within each individual data type compared to the state of art specialized aging clocks based on methylation or transcriptomic data separately it may have higher practical utility for target discovery. This method provides the ability to discover novel therapeutic targets that hypothetically may be able to reverse or accelerate biological age providing a pathway for therapeutic drug discovery and validation using the aging clock. In addition, we provide a list of promising targets annotated using the PandaOmics industrial target discovery platform.

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Towards AI-driven longevity research: An overview

Cited by 15 publications

References 127 publications

The association between blood biological age at rehabilitation admission and physical activity during rehabilitation in geriatric inpatients: RESORT

The association between blood biological age at rehabilitation admission and physical activity during rehabilitation in geriatric inpatients: RESORT

The leading global health challenges in the artificial intelligence era

Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery

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