TORNADO-Omics Techniques and Neural Networks for the Development of Predictive Risk Models

Cardiovascular Risk Factor Clinical Trial

Official title:

Integration of Omics-based Technologies and Artificial Intelligence to Identify Predictive Risk Models in a Air Force's Pilot Cohort for the Maintenance of Safety, Well-being, Health, and Performance to be Translated to Civil Population

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06372054
• Other study ID #: TORNADO
• Status: Recruiting
• Start date: February 5, 2024
• Est. completion date: February 5, 2027

Study information

• Verified date: March 2024
• Source: Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico
• Contact: Giovanni Marfia, MD, PhD
• Phone: 0256660100
• Email: giovanni.marfia[@]policlinico.mi.it
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

The goal of this observational study is to define a personalized risk model in the super healthy and homogeneous population of Italian Air Force high-performance pilots. This peculiar cohort conducts dynamic activities in an extreme environment, compared to a population of military people not involved in flight activity. The study integrates the analyses of biological samples (urine, blood, and saliva), clinical records, and occupational data collected at different time points and analyzed by omic-based approaches supported by Artificial Intelligence. Data resulting from the study will clarify many etiopathological mechanisms of diseases, allowing the creation of a model of analyses that can be extended to the civilian population and patient cohorts for the potentiation of precision and preventive medicine.

Description:

The high-performance pilots of the Italian Air Force are "super healthy" individuals subjected to particular working conditions, as changes in temperature, pressure, gravity, acceleration, exposure to cosmic rays and radiation, which determine psycho-physical adaptation mechanisms to maintain homeostasis. However, this environmental exposure may potentially affect human health, well-being and performance. The study aims to collect exposure data, clinical, physiological data through biosensors and molecular parameters (at different time point), to be integrated by an Artificial Intelligence algorithm expressly trained to create reliable risk models. The final outcome will consist of the identification of significant biomarkers of pathological risk, in order to better understand the etiopathological mechanisms of many human diseases and apply early and personalized countermeasures to maintain and empower workers' health status and performance, avoiding clinical symptom presentation.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 200
• Est. completion date: February 5, 2027
• Est. primary completion date: February 5, 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 26 Years to 38 Years

Eligibility

Inclusion Criteria:

• Being part of the Italian Air Force, as in active flight service or ground staff
• Age between 26 and 38 years
• Consent to collect biological samples and use the wearable device to monitor exposure parameters

Exclusion Criteria:

• Age < 25 years and > 39 years
• no signature on informed consent

Related Conditions & MeSH terms

• Cardiovascular Risk Factor
• Discogenic Pain
• Epigenetic Changes
• LONGEVITY 1
• Neuroplasticity
• Oxidative Injury
• Stress Physiological

Intervention

Other:
• Biological sample collection
Collection of biological samples (blood, urine, saliva) and clinical data

Locations

Country	Name	City	State
Italy	CeMATA - Joint Center for Aerospace Medicine and Advanced Therapy	Milan

Sponsors (5)

Lead Sponsor	Collaborator
Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico	A-Tono, Italian Air Force, Ministry of Defense, Italy, University of Milan

Country where clinical trial is conducted

Italy, 

References & Publications (2)

Marfia G, Guarnaccia L, Navone SE, Ampollini A, Balsamo M, Benelli F, Gaudino C, Garzia E, Fratocchi C, Di Murro C, Ligarotti GK, Campanella C, Landolfi A, Perelli P, Locatelli M, Ciniglio Appiani G. Microgravity and the intervertebral disc: The impact of — View Citation

Marfia G, Navone SE, Guarnaccia L, Campanella R, Locatelli M, Miozzo M, Perelli P, Della Morte G, Catamo L, Tondo P, Campanella C, Lucertini M, Ciniglio Appiani G, Landolfi A, Garzia E. Space flight and central nervous system: Friends or enemies? Challeng — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Assessment of flight-related exposure data and molecular modifications	Collection of information on: i) lifestyle, ii) medical examination, iii) previous trauma, iv) cumulative professional exposure to flying, determination of panel of genes and circulating markers to assess prognostic and predictive factors	Through study completion, an average of 3 year
Secondary	Assessment of General Health	Recording of general health condition and work stress by General Health Questionnaire by the Effort-Reward Imbalance Questionnaire (ERI)	Through study completion, an average of 3 year
Secondary	Assessment of Sleep Quality	Recording of sleep quality by the Sleeping Quality Questionnaire (SQQ)	Through study completion, an average of 3 year
Secondary	Assessment of eating habits	Recording of eating habits by Food Frequency Questionnaire (EPIC)	Through study completion, an average of 3 year
Secondary	Creation of reliable AI and disease-based models for personalized medicine	Integration of information obtained from anamnesis, questionnaires, biochemical, genomic, epigenomic, proteomic data with the measurement of heart rate, oxygenation, acceleration, external temperature, presence of ultrasound, infrasound and radiation with artificial intelligence algorithm for the creation of reliable models of disease based on personalized medicine	Through study completion, an average of 3 year