Local ancestry-aware genome-wide meta-analysis uncovers novel genetic loci for sickle cell disease nephropathy.

Blood AdvOct 16, 2026

Melanie E Garrett, Seyed Mehdi Nouraie, Roberto F Machado et al.

✦ AI-curated · Sources linked

In 30 seconds

This local ancestry-aware genome-wide association meta-analysis examined estimated glomerular filtration rate in participants from two well-characterized adult sickle cell disease cohorts, seeking genetic loci associated with sickle cell disease nephropathy. The analysis identified 12 significant genomic regions in African ancestry tracts and 38 in European ancestry tracts. Reported regions included genes linked to renal function and to processes relevant to sickle cell disease, such as inflammation, extracellular matrix integrity, and iron metabolism. The findings expand the set of candidate genetic factors associated with kidney dysfunction in adults with sickle cell disease.

Key findings

  • Meta-analysis identified 12 significant genomic regions in African ancestry tracts.
  • The analysis identified 38 significant genomic regions in European ancestry tracts.
  • Regions included genes and pathways related to renal function and sickle cell disease biology, including inflammation, extracellular matrix integrity, and iron metabolism.

Why it matters

Sickle cell disease nephropathy is a common complication associated with early mortality. Identifying genetic regions associated with estimated glomerular filtration rate may help clarify its biology and support future investigation of risk assessment and therapeutic targets. The reported overlap with pathways relevant to sickle cell disease also supports the possibility that its kidney complications have distinct underlying mechanisms.

What to keep in mind

The analysis used estimated glomerular filtration rate as the outcome, and the abstract does not report validation of the identified loci or clinical utility.

Source

Published in Blood Adv. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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