Roles of APOL1 G1 and G2 variants in sickle cell disease patients: kidney is the main target.
Raphael KormannAnne-Sophie JannotCéline NarjozJean-Antoine RibeilSandra ManceauMarianne DelvilleValentin JosteDominique PriéJacques PouchotEric ThervetMarie CourbebaisseJean-Benoît ArletPublished in: British journal of haematology (2017)
In African-American patients with sickle cell disease (SCD), APOL1 G1 and G2 variants are associated with increased risk of sickle cell nephropathy (SCN). To determine the role of APOL1 variants in SCD patients living in Europe, we genotyped 152 SCD patients [aged 30·4 (24·3-36·4) years], mainly of Sub-Saharan African ancestry, for APOL1 G1 and G2 and for variants of four genes with kidney tropism (GSTM1, GSTT1, GSTP1, and HMOX1). Homozygous or double-heterozygous APOL G1 and G2 genotypes were strongly associated with end stage renal disease (P = 0·003) and worse Kidney Disease: Improving Global Outcomes stages (P = 0·001). Further, these genotypes were associated in an age-dependent manner with lower estimated glomerular filtration rate (eGFR, P = 0·008), proteinuria (P = 0·009) and albuminuria (P < 0·001) but not with other SCD complications. Compared to APOL1 G1/wild type (WT), the APOL1 G2/WT genotype was associated with a lower eGFR (P = 0·04) in an age-dependent manner, suggesting that the G2/WT patients are likely to have worse kidney prognosis. Other genes variants analysed were not associated with SCN or other SCD complications. Our data indicate that APOL1 screening should be considered for the management of SCD patients, including those of non-African-American origin, as those with homozygous or double heterozygous variants are clearly at higher risk of SCN.
Keyphrases
- end stage renal disease
- chronic kidney disease
- peritoneal dialysis
- newly diagnosed
- ejection fraction
- african american
- small cell lung cancer
- prognostic factors
- type diabetes
- machine learning
- copy number
- sickle cell disease
- patient reported outcomes
- epidermal growth factor receptor
- adipose tissue
- skeletal muscle
- artificial intelligence
- tyrosine kinase
- wild type
- data analysis