Scripta Medica (Jan 2024)

Harnessing genomic and bioinformatic data to broaden understanding of leukaemia across continents

  • Gumelar Gugun,
  • Ulfa Mia Maria,
  • Amukti Danang Prasetyaning,
  • Irham Lalu Muhammad,
  • Yuliani Sapto,
  • Adikusuma Wirawan,
  • Khairi Sabiah,
  • Darmawi Darmawi,
  • Chong Rockie,
  • Ates Ilker,
  • Singh Dilpreet,
  • Chavan Aditya Ashok

DOI
https://doi.org/10.5937/scriptamed55-51720
Journal volume & issue
Vol. 55, no. 6
pp. 717 – 725

Abstract

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Background/Aim: Leukaemia is a malignant disease of blood cells found in the bone marrow, which can be divided into acute lymphocytic leukaemia and myelocytic leukaemia. Current management of acute leukaemia still uses chemo therapy as the main therapy but has many side effects, therefore a new approach is needed to identify genetic factors involved in leukaemia. The aim of this study was to investigate gene variations that have potential pathogenic properties in leukaemia. Methods: This study used genome-wide association study (GWAS) data obtained from the National Human Genome Research Institute (NHGRI) to search for genomic variants associated with leukaemia. The data was then screened using SNPnexus to detect potentially protein-damaging variants. Furthermore, the gene expression of these variants was analysed using the GTEx portal. Results: Of the 2115 genomic variants found, four were deleterious, namely rs12140153, rs140386498, rs757110 and rs2066827, representing four different genes, namely PATJ, MINDY1, ABCC8 and CDKN1B. Alterations in the expression of PATJ, MINDY1, CDKN1B and ABCC8 genes affect the brain and leukaemia development. PATJ maintains brain cell integrity, MINDY1 regulates gene expression, CDKN1B controls the cell cycle and ABCC8 regulates glucose levels. Their deregulation is associated with neurological dysfunction and leukaemia. Variation in allele frequencies showed differences between continents, with rs757110 and rs2066827 having higher expression than rs12140153 and rs140386498. Variant gene expression also varied between tissues, with rs757110 and rs2066827 showing higher expression than rs12140153 and rs140386498. Conclusion: This study successfully identified four genomic variants by harnessing a genomic and bioinformatic database, which are associated with leukemia and demonstrated variations in gene distribution and expression across different populations and tissues.

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