UGR-Longitudinal

Longitudinal Follow-Up & Phenotyping


Overview

UGR-Longitudinal (formerly UGR-Overlap) is a longitudinal research resource comprising 2,232 participants represented in both UGR-Core (Phase I) and UGR-NEXUS (Phase II). By linking data collected across successive phases of the Uganda Genome Resource, it enables investigations into changes in health, disease characteristics and cardiometabolic risk factors over time.

The resource provides opportunities to examine longitudinal patterns of disease progression, temporal variation in clinical traits and the relationship between genetic variation and changes in health outcomes. Its repeated phenotypic assessments support research into the long-term determinants of communicable and non-communicable diseases in Ugandan populations.


Cohort Information

  • Project identifier: UGR Overlap Sub-Cohort
  • Study period: 2011–2025
  • Participants: 2,232
  • Follow-up status: Recruitment and follow-up scheduled through October 2026
  • Study design: Longitudinal follow-up of participants represented in UGR-Core and UGR-NEXUS

Longitudinal and Phenotypic Data

  • Linked cohort data: Participants represented in both UGR-Core (Phase I) and UGR-NEXUS (Phase II)
  • Repeated phenotypic assessments: Data collected across study phases, enabling investigation of changes in health and disease characteristics over time
  • Cardiometabolic phenotyping: Cardiometabolic trait measurements supporting longitudinal epidemiological investigations
  • Genomic and multi-omics integration: Opportunities for whole-genome sequencing and multi-omics profiling within the longitudinal resource
  • Follow-up activities: Recruitment and follow-up activities scheduled through October 2026

Research Applications

UGR-Longitudinal supports longitudinal genetic epidemiology, investigation of cardiometabolic disease progression, assessment of temporal changes in risk factors and repeated-measures analyses.

The integration of genomic and molecular information with longitudinal phenotypic data provides opportunities to investigate biological mechanisms associated with disease development and progression, as well as the contribution of genetic and environmental factors to changes in health outcomes over time.


Cohort relationship: UGR-Longitudinal comprises participants represented in both UGR-Core and UGR-NEXUS. It is a linked sub-cohort rather than an independent additional population sample.