Update of the Novara Cohort Study (NCS): protocol evolution of a population-based longitudinal study on ageing in Northern Italy - cohort profile.

The NCS cohort had approximately 1000 participants enrolled as of mid-2025, with recruitment ongoing.

• The study is population-based and located in the Novara province of Northern Italy.
• Recruitment is ongoing with a target of at least 10,000 participants.
• The cohort's diversity in age, employment status and health conditions enhances its value for life-course analysis.

The NCS inclusion criteria were expanded from adults aged 35 and older to all residents aged 18 and over to facilitate study of ageing trajectories from early adulthood onward.

• The study was originally established enrolling adults aged 35 and older.
• The expansion to age 18 and over was intended to enable analysis of ageing trajectories from early adulthood.
• This protocol evolution occurred following a pilot phase in 2022–2023.

The NCS protocol includes over 90 laboratory biomarkers covering multiple physiological domains.

• Biomarkers cover inflammation, metabolism, hormonal function, and coagulation.
• The protocol also incorporates validated tools, comprehensive physical and cognitive assessments, and detailed demographic, clinical, behavioural, cognitive and psychosocial data.
• Biological samples are stored in the UPO Biobank.

A subset of NCS participants underwent advanced inflammatory profiling via simultaneous measurement of 92 immune-related proteins.

• The 92 immune-related proteins were measured simultaneously as part of advanced inflammatory profiling.
• This subset also underwent comprehensive genomic profiling using Illumina Single Nucleotide Polymorphism (SNP) arrays.
• The SNP arrays were described as capturing common genetic variation across multiple biological domains.

Preliminary results from NCS demonstrate the feasibility of integrating deep phenotyping and show initial evidence of age-related changes in inflammatory proteins.

• Preliminary results reveal the roles of frailty in ageing.
• Initial evidence of age-related changes in inflammatory proteins was observed.
• These findings support the feasibility of the study's deep phenotyping approach.

NCS plans to conduct long-term follow-up using both passive and active methods.

• Passive follow-up methods include linking with clinical records and administrative health databases.
• Active follow-up will involve in-person reassessments.
• Future phases will integrate clinical, behavioural and cognitive data with large-scale omics analyses including genomics, proteomics, metabolomics and transcriptomics.
• Machine learning techniques will be employed to model biological age, identify early signs of age-related decline, and develop personalised prevention strategies.