Predictive Cardio-Metabolic Trascrictomics Trajectories in the Barilla Offspring Follow-Up Study

Active, not recruiting

• Conditions: Healthy Volunteer

• Registration Number: NCT06876818
• Lead Sponsor: Azienda Ospedaliero-Universitaria di Parma

Brief Summary

Experimental, drug-free, longitudinal, single-centre study for the prediction of cardiometabolic risk in Barilla Off-Spring Study subjects by analysing the evolution of transcriptomic signatures

Detailed Description

In Westernized societies, common metabolic and cardiovascular diseases have complex etiologies involving dynamic genome-metagenome-environment interactions. The early molecular alterations that initiate and sustain their progression, although still only partially understood, are thought to share common roots in the terrain of insulin resistance (IR). In recent decades, reciprocal relationships between IR and inflammation have been unraveled, leading to the general concept of "meta-inflammation". In turn, the regulatory role played by metabolic signatures in immune cells has led to the concept of "immunometabolism". In particular, in these meta-inflammation-related disorders, there is a paucity of prospective gene expression data, especially in the early stages of their natural history. Gene expression profiling of peripheral blood mononuclear cells (PBMCs) may be a useful and accessible window into the pathophysiology of processes occurring in difficult-to-access organs and tissues. In a deeply phenotyped healthy cohort, the Barilla Offspring Study, a transcriptomic signature exclusively associated with IR was found by analyzing PBMC gene expression with a novel rank-based classification method, which was also found to discriminate diseased from healthy individuals in Alzheimer's disease, chronic heart failure and type 2 diabetes. The granularity of this approach can be further improved by examining gene expression in monocytes, as cells of innate immunity and mainly implicated in inflammatory/degenerative disorders and their risk factors. In this longitudinal study, we aim to identify the transcriptomic signature(s) in circulating immune cells and inflammatory biomarkers that predict or are associated with 15-year changes in glucose tolerance and/or carotid artery atherogenic phenotype. The study has solid premises: i. The cohort of subjects offers a unique opportunity to identify PBMC transcriptomic trajectories (baseline and 15-year follow-up) that predict changes in cardiometabolic phenotype; ii. cross-sectional assessment of monocyte transcriptomic profiling in the same cohort may uncover additional lineage-specific signatures associated with different cardio-metabotypes at follow-up, allowing comparison with PBMC; iii. an innovative rank-based classification method - SCUDO and its extensions - will be used, in addition to standard methods, to compute transcriptomic analyses. The results of the study may identify cellular transcriptomic signatures and trajectories, which could link cardiometabolic phenotypes at the molecular and cellular level, highlighting possible biological mechanisms of cardiometabolic disease susceptibility and progression, and unveiling a wide range of molecular targets in PBMC and, especially, monocytes, which can be further investigated for their validity as peripheral biomarkers for risk assessment. The findings will also provide new insights into targeted pharmacological strategies for the prevention and/or treatment of cardiometabolic diseases.

Study Timeline

• Study Start: 2024-05-23
• Status Verified: 2025-03
• Study First Submitted: 2025-03-10
• Study First Submitted QC: 2025-03-10
• Last Update Submitted: 2025-03-10
• Study First Posted: 2025-03-14
• Last Update Posted: 2025-03-14
• Primary Completion: 2025-07-01
• Study Completion: 2025-12-31

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 110

Inclusion Criteria

• Being enrolled in the Barilla Off-Spring Study (2006-2007)
• Ability to understand the methods, aims and implications of the study, and to give free and informed consent

Exclusion Criteria

• Pregnancy

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Selection of a set of candidate genes directly correlated with the development of altered metabolic phenotypes	within six months of the enrolment visit	All data related to the transcriptomics of PBMCs at T0 (2006-2007) will be retrieved. At T1, a blood sample will be collected from which PBMCs will be isolated. Total RNA will be purified and its quality tested using the Quibit fluorimetric technique and the Tape-station system. From the same blood sample, the monocyte subpopulation will also be isolated and used to identify the specific transcriptomic signature.; Both RNA datasets, collected at T0 and T1, will be processed to identify informative transcriptomic signatures of baseline and follow-up conditions. The sets will be converted to obtain a profile for a symbol gene; this will allow easier comparison of the calculated transcriptomic signatures between different datasets, facilitating the biological interpretation of the results.

Secondary Outcome Measures

Name	Time	Method
Selection of a set of candidate genes directly related to the development of altered vascular phenotypes	within six months of the enrolment visit	All data related to the transcriptomics of PBMCs at T0 (2006-2007) will be retrieved. At T1, a blood sample will be collected from which PBMCs will be isolated. Total RNA will be purified and its quality tested using the Quibit fluorimetric technique and the Tape-station system. From the same blood sample, the monocyte subpopulation will also be isolated and used to identify the specific transcriptomic signature.; Both RNA datasets, collected at T0 and T1, will be processed to identify informative transcriptomic signatures of baseline and follow-up conditions. The sets will be converted to obtain a profile for a symbol gene; this will allow easier comparison of the calculated transcriptomic signatures between different datasets, facilitating the biological interpretation of the results.
Selection of a set of candidate genes directly related to overt altered metabolic and/or vascular phenotypes.	within six months of the enrolment visit	All data related to the transcriptomics of PBMCs at T0 (2006-2007) will be retrieved. At T1, a blood sample will be collected from which PBMCs will be isolated. Total RNA will be purified and its quality tested using the Quibit fluorimetric technique and the Tape-station system. From the same blood sample, the monocyte subpopulation will also be isolated and used to identify the specific transcriptomic signature.; Both RNA datasets, collected at T0 and T1, will be processed to identify informative transcriptomic signatures of baseline and follow-up conditions. The sets will be converted to obtain a profile for a symbol gene; this will allow easier comparison of the calculated transcriptomic signatures between different datasets, facilitating the biological interpretation of the results.
Selection of markers directly related to the development of altered metabolic and/or vascular phenotypes.	within six months of the enrolment visit	All data related to the transcriptomics of PBMCs at T0 (2006-2007) will be retrieved. At T1, a blood sample will be collected from which PBMCs will be isolated. Total RNA will be purified and its quality tested using the Quibit fluorimetric technique and the Tape-station system. From the same blood sample, the monocyte subpopulation will also be isolated and used to identify the specific transcriptomic signature.; Both RNA datasets, collected at T0 and T1, will be processed to identify informative transcriptomic signatures of baseline and follow-up conditions. The sets will be converted to obtain a profile for a symbol gene; this will allow easier comparison of the calculated transcriptomic signatures between different datasets, facilitating the biological interpretation of the results.
Selection of a set of candidate genes directly related to alterations in biohumoral parameters and the inflammatory profile.	within six months of the enrolment visit	All data related to the transcriptomics of PBMCs at T0 (2006-2007) will be retrieved. At T1, a blood sample will be collected from which PBMCs will be isolated. Total RNA will be purified and its quality tested using the Quibit fluorimetric technique and the Tape-station system. From the same blood sample, the monocyte subpopulation will also be isolated and used to identify the specific transcriptomic signature.; Both RNA datasets, collected at T0 and T1, will be processed to identify informative transcriptomic signatures of baseline and follow-up conditions. The sets will be converted to obtain a profile for a symbol gene; this will allow easier comparison of the calculated transcriptomic signatures between different datasets, facilitating the biological interpretation of the results.
Selection of a set of candidate genes directly related to alterations in lifestyle.	within six months of the enrolment visit	All data related to the transcriptomics of PBMCs at T0 (2006-2007) will be retrieved. At T1, a blood sample will be collected from which PBMCs will be isolated. Total RNA will be purified and its quality tested using the Quibit fluorimetric technique and the Tape-station system. From the same blood sample, the monocyte subpopulation will also be isolated and used to identify the specific transcriptomic signature.; Both RNA datasets, collected at T0 and T1, will be processed to identify informative transcriptomic signatures of baseline and follow-up conditions. The sets will be converted to obtain a profile for a symbol gene; this will allow easier comparison of the calculated transcriptomic signatures between different datasets, facilitating the biological interpretation of the results.

Trial Locations

Locations (1)

University of Parma, Department of Medicine and Surgery; 🇮🇹 Parma, PR, Italy