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Developing Clinical Phenotype Data Collection Standards for Research in Africa.

Lyndon ZassKatherine JohnstonAlia BenkahlaMelek ChaouchJudit KumuthiniFouzia RadouaniLiberata Alexander MwitaNihad AlsayedTaryn AllieDassen SathanUpendo MasamuMilaine Sergine Seuneu TchamgaTsaone TamuhlaChaimae SamtalVictoria NembawareZoe GillSamah AhmedYosr HamdiFaisal M FadlelmolaNicki TiffinNicola M Mulder
Published in: Global health, epidemiology and genomics (2023)
Modern biomedical research is characterised by its high-throughput and interdisciplinary nature. Multiproject and consortium-based collaborations requiring meaningful analysis of multiple heterogeneous phenotypic datasets have become the norm; however, such analysis remains a challenge in many regions across the world. An increasing number of data harmonisation efforts are being undertaken by multistudy collaborations through either prospective standardised phenotype data collection or retrospective phenotype harmonisation. In this regard, the Phenotype Harmonisation Working Group (PHWG) of the Human Heredity and Health in Africa (H3Africa) consortium aimed to facilitate phenotype standardisation by both promoting the use of existing data collection standards (hosted by PhenX), adapting existing data collection standards for appropriate use in low- and middle-income regions such as Africa, and developing novel data collection standards where relevant gaps were identified. Ultimately, the PHWG produced 11 data collection kits, consisting of 82 protocols, 38 of which were existing protocols, 17 were adapted, and 27 were novel protocols. The data collection kits will facilitate phenotype standardisation and harmonisation not only in Africa but also across the larger research community. In addition, the PHWG aims to feed back adapted and novel protocols to existing reference platforms such as PhenX.
Keyphrases
  • electronic health record
  • big data
  • high throughput
  • healthcare
  • mental health
  • physical activity
  • risk assessment
  • single cell
  • artificial intelligence
  • human health