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NCT Number: NCT06876818

Predictive Cardio-Metabolic Trascrictomics Trajectories In The Barilla Offspring Follow-Up Study

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

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Conditions

Healthy Volunteer

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University of Parma, Department of Medicine and Surgery

Parma, PR, 43126, Italy

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Evaluation of transcriptomic and cardio-metabolic profiles

Other

The parameters and variables collected in 2006-2007 (T0) will be re-evaluated at the follow-up visit (T1), including demographic, anthropometric, lifestyle data (smoking habit, physical activity, sleep quality) blood pressure, standard biochemical analysis and inflammatory profile. To assess the evolution of glucose tolerance and vascular damage, metabolic (OGTT) and cardiovascular (carotid ecodoppler) profile analyses will be repeated. For gene expression analyses, in addition to messenger RNA from PBMCs (as at T0), RNA from PBMC-derived monocytes will also be extracted and sequenced at T1.

Primary outcomes

  1. Selection of a set of candidate genes directly correlated with the development of altered metabolic phenotypes

    Time frame: 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 outcomes

  1. Selection of a set of candidate genes directly related to the development of altered vascular phenotypes

    Time frame: 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.

  2. Selection of a set of candidate genes directly related to overt altered metabolic and/or vascular phenotypes.

    Time frame: 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.

  3. Selection of markers directly related to the development of altered metabolic and/or vascular phenotypes.

    Time frame: 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.

  4. Selection of a set of candidate genes directly related to alterations in biohumoral parameters and the inflammatory profile.

    Time frame: 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.

  5. Selection of a set of candidate genes directly related to alterations in lifestyle.

    Time frame: 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.

Sponsors and collaborators

Lead sponsor

Azienda Ospedaliero-Universitaria di Parma

Other

Collaborators

  • University of Parma

Registry information

Official study title

Predictive Cardio-Metabolic Trascrictomics Trajectories In The Barilla Offspring Follow-Up STUDY: The PREDICT-OMICS Study.

Acronym: PREDICT-OMICS

Important dates

Study start
2024
Primary completion
2025
Study completion
2025
First posted
Mar 14, 2025
Registry last updated
Mar 14, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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