Ferroptosis regulates hemolysis in stored murine and human red blood cells

Abstract

Red blood cell (RBC) metabolism regulates hemolysis during aging in vivo and in the blood bank. However, the genetic underpinnings of RBC metabolic heterogeneity and extravascular hemolysis at population scale are incompletely understood. On the basis of the breeding of 8 founder strains with extreme genetic diversity, the Jackson Laboratory diversity outbred population can capture the impact of genetic heterogeneity in like manner to population-based studies. RBCs from 350 outbred mice, either fresh or stored for 7 days, were tested for posttransfusion recovery, as well as metabolomics and lipidomics analyses. Metabolite and lipid quantitative trait loci (QTL) mapped >400 gene-metabolite associations, which we collated into an online interactive portal. Relevant to RBC storage, we identified a QTL hotspot on chromosome 1, mapping on the region coding for the ferrireductase 6-transmembrane epithelial antigen of the prostate 3 (Steap3), a transcriptional target to p53. Steap3 regulated posttransfusion recovery, contributing to a ferroptosis-like process of lipid peroxidation, as validated via genetic manipulation in mice. Translational validation of murine findings in humans, STEAP3 polymorphisms were associated with RBC iron content, lipid peroxidation, and in vitro hemolysis in 13 091 blood donors from the Recipient Epidemiology and Donor Evaluation Study. QTL analyses in humans identified a network of gene products (fatty acid desaturases 1 and 2, epoxide hydrolase 2, lysophosphatidylcholine acetyl-transferase 3, solute carrier family 22 member 16, glucose 6-phosphate dehydrogenase, very long chain fatty acid elongase, and phospholipase A2 group VI) associated with altered levels of oxylipins. These polymorphisms were prevalent in donors of African descent and were linked to allele frequency of hemolysis-linked polymorphisms for Steap3 or p53. These genetic variants were also associated with lower hemoglobin increments in thousands of single-unit transfusion recipients from the vein-to-vein database.

Graphical abstract

Figure 1.

Genetic underpinnings of RBC metabolic and storage quality heterogeneity in J:DO mice. (A) Diagram of genetically diverse mouse experiment. Eight founder strains were extensively intercrossed to produce highly recombinant outbred progeny. RBCs were collected and stored under conditions mimicking human RBC blood bank storage for 7 days, the end of shelf-life for pRBC in humans. RBCs were thus transfused into green fluorescent protein–positive (GFP⁺) mice to determine the percentage of transfused RBCs still circulating at 24 hours after transfusion (posttransfusion recovery [PTR]). Mice were genotyped, and fresh and stored RBCs were analyzed via mass spectrometry–based metabolomics and lipidomics. A quantitative trait locus (QTL) for PTR was mapped on chromosome 1 in the region encoding the ferrireductase Steap3, shown as the genome scan (B), haplotype effects at the QTL (C), and SNP associations in the QTL region (D). (E-J) Combined Manhattan plots of peak associations for metabolites, lipids, and oxylipins in fresh and stored RBCs reveal a hot spot region on chromosome 1 associated with changes in metabolite, lipid, and oxylipin levels specific to stored samples. Metabolites, lipids, and oxylipins with strong QTL are highlighted as labels. Molecular correlates to PTR identified lipid peroxidation products as strongly associated with PTR (K), including prostaglandin G2 and D2/E2 (isobars) (L-M). FL, fatty acid; LOD, logarithm (base 10) of odds.

Figure 1.

Genetic underpinnings of RBC metabolic and storage quality heterogeneity in J:DO mice. (A) Diagram of genetically diverse mouse experiment. Eight founder strains were extensively intercrossed to produce highly recombinant outbred progeny. RBCs were collected and stored under conditions mimicking human RBC blood bank storage for 7 days, the end of shelf-life for pRBC in humans. RBCs were thus transfused into green fluorescent protein–positive (GFP⁺) mice to determine the percentage of transfused RBCs still circulating at 24 hours after transfusion (posttransfusion recovery [PTR]). Mice were genotyped, and fresh and stored RBCs were analyzed via mass spectrometry–based metabolomics and lipidomics. A quantitative trait locus (QTL) for PTR was mapped on chromosome 1 in the region encoding the ferrireductase Steap3, shown as the genome scan (B), haplotype effects at the QTL (C), and SNP associations in the QTL region (D). (E-J) Combined Manhattan plots of peak associations for metabolites, lipids, and oxylipins in fresh and stored RBCs reveal a hot spot region on chromosome 1 associated with changes in metabolite, lipid, and oxylipin levels specific to stored samples. Metabolites, lipids, and oxylipins with strong QTL are highlighted as labels. Molecular correlates to PTR identified lipid peroxidation products as strongly associated with PTR (K), including prostaglandin G2 and D2/E2 (isobars) (L-M). FL, fatty acid; LOD, logarithm (base 10) of odds.

Figure 2.

Chromosome 1 QTL hotspot reveals Steap3 as a key regulator of metabolites, oxylipins, and lipids in stored RBCs. QTL for metabolites, oyxlipins, and lipids revealed comapping hotspots, including the STEAP3 locus on chromosome 1 specific to stored RBCs, depicted as hive plots (A-B), a network plot (C), and QTL density plots (D-F). Three-dimensional (3D) model of the membrane proximal oxidoreductase domain of human Steap3 (bound to NADP) is overlayed with the chromosome 1 hotspot. Other candidate gene drivers of hotspots are included as labels. Hydroxyoctadecadienoic acid (HODE) is an example of a metabolite that maps the Steap3 QTL (chromosome 1 scan and haplotype effects [G] and SNP associations [H]). The correlation structure among metabolites, lipids, oxylipins, and PTR reflects the Steap3 QTL, with fresh samples being uncoordinated across data types (I), but highly coordinated in stored samples, at both the individual-level data (J) and the QTL haplotype effects (K). STEAP3 KO also has a significant impact on RBC metabolism on storage (L), both KO and hypermorphic gain of function (GOF) resulting in decreases in PTR in mice (M). (N) However, only GOF mice but not KO show elevated levels of oxylpins in end of storage RBCs. ∗∗∗P < .001; ∗∗∗∗P < .0001.

Figure 2.

Chromosome 1 QTL hotspot reveals Steap3 as a key regulator of metabolites, oxylipins, and lipids in stored RBCs. QTL for metabolites, oyxlipins, and lipids revealed comapping hotspots, including the STEAP3 locus on chromosome 1 specific to stored RBCs, depicted as hive plots (A-B), a network plot (C), and QTL density plots (D-F). Three-dimensional (3D) model of the membrane proximal oxidoreductase domain of human Steap3 (bound to NADP) is overlayed with the chromosome 1 hotspot. Other candidate gene drivers of hotspots are included as labels. Hydroxyoctadecadienoic acid (HODE) is an example of a metabolite that maps the Steap3 QTL (chromosome 1 scan and haplotype effects [G] and SNP associations [H]). The correlation structure among metabolites, lipids, oxylipins, and PTR reflects the Steap3 QTL, with fresh samples being uncoordinated across data types (I), but highly coordinated in stored samples, at both the individual-level data (J) and the QTL haplotype effects (K). STEAP3 KO also has a significant impact on RBC metabolism on storage (L), both KO and hypermorphic gain of function (GOF) resulting in decreases in PTR in mice (M). (N) However, only GOF mice but not KO show elevated levels of oxylpins in end of storage RBCs. ∗∗∗P < .001; ∗∗∗∗P < .0001.

Figure 3.

Oxylipins, iron, and STEAP3 are associated with hemolysis in 13 000 REDS RBC Omics blood donors. (A) Hemolysis measurements in 13 091 donors from the REDS RBC Omics studies identified oxylipins (especially, HETEs and HODEs) as top predictors of end of storage hemolytic propensity. A second independent unit from 643 of the index donors who were contacted because of their extreme hemolytic propensity (5th vs 95th percentile). (B) Determination of vesiculation rates in the 643 units at storage day 10, 23, and 42 identified HETEs and HODEs as top markers of RBC vesiculation. (C) A total of 37 SNPs were monitored for STEAP3 in the REDS RBC Omics study. (C) Common nonsynonymous coding SNPs correlated with osmotic and oxidative hemolytic propensity and oxylipin levels. (D) Some of these SNPs were predicted to impact the ferrireductase function of the enzyme. (E) Three-dimensional (3D) uniform manifold approximation and projection (uMAP) representation of HETE levels and all nonsynonymous STEAP3 SNPs in homozygosity are shown. (F) Iron measurements via inductively coupled plasma mass spectrometry (ICP-MS) in the REDS RBC Omics recalled donor cohort showed significant association with hemolysis and oxylipins. (G) Hemolysis was significantly lower in donors carrying 2 alleles of rs17013371, the most common nonsynonymous STEAP3 coding SNP. (H) Multi-omics correlates in the same recalled donor cohort confirmed such association for the rs17013371, an SNP that is overrepresented in donors of African American descent (I). ∗∗P < .01; ∗∗∗∗P < .0001. FA, fatty acid.

Figure 3.

Oxylipins, iron, and STEAP3 are associated with hemolysis in 13 000 REDS RBC Omics blood donors. (A) Hemolysis measurements in 13 091 donors from the REDS RBC Omics studies identified oxylipins (especially, HETEs and HODEs) as top predictors of end of storage hemolytic propensity. A second independent unit from 643 of the index donors who were contacted because of their extreme hemolytic propensity (5th vs 95th percentile). (B) Determination of vesiculation rates in the 643 units at storage day 10, 23, and 42 identified HETEs and HODEs as top markers of RBC vesiculation. (C) A total of 37 SNPs were monitored for STEAP3 in the REDS RBC Omics study. (C) Common nonsynonymous coding SNPs correlated with osmotic and oxidative hemolytic propensity and oxylipin levels. (D) Some of these SNPs were predicted to impact the ferrireductase function of the enzyme. (E) Three-dimensional (3D) uniform manifold approximation and projection (uMAP) representation of HETE levels and all nonsynonymous STEAP3 SNPs in homozygosity are shown. (F) Iron measurements via inductively coupled plasma mass spectrometry (ICP-MS) in the REDS RBC Omics recalled donor cohort showed significant association with hemolysis and oxylipins. (G) Hemolysis was significantly lower in donors carrying 2 alleles of rs17013371, the most common nonsynonymous STEAP3 coding SNP. (H) Multi-omics correlates in the same recalled donor cohort confirmed such association for the rs17013371, an SNP that is overrepresented in donors of African American descent (I). ∗∗P < .01; ∗∗∗∗P < .0001. FA, fatty acid.

Figure 4.

Genetic factors contributing to heterogeneous lipid peroxidation in 13 091 human RBCs after storage for 42 days. (A) Genome-wide association studies (GWASs) were performed for lipid peroxidation products in the REDS RBC Omics index donor cohort (n = 13 091) against 870 000 SNPs from a precision transfusion medicine array. (B-H) Manhattan plots are shown for HETE, HPETE, leukotriene A4, prostaglandin A2, dinor-prostaglandin F2α, prostaglandin D2/E2, and G2. (I) A summary model of the pathway that emerges as a regulator of lipid peroxidation in stored human RBCs. (J-M) Representative locus zoom plots for selected top hits by significance (–log10 P values, y axes). ELOVL, very long chain fatty acid elongase; SLC22A16, solute carrier family 22 member 16.

Figure 4.

Genetic factors contributing to heterogeneous lipid peroxidation in 13 091 human RBCs after storage for 42 days. (A) Genome-wide association studies (GWASs) were performed for lipid peroxidation products in the REDS RBC Omics index donor cohort (n = 13 091) against 870 000 SNPs from a precision transfusion medicine array. (B-H) Manhattan plots are shown for HETE, HPETE, leukotriene A4, prostaglandin A2, dinor-prostaglandin F2α, prostaglandin D2/E2, and G2. (I) A summary model of the pathway that emerges as a regulator of lipid peroxidation in stored human RBCs. (J-M) Representative locus zoom plots for selected top hits by significance (–log10 P values, y axes). ELOVL, very long chain fatty acid elongase; SLC22A16, solute carrier family 22 member 16.

Figure 5.

Genetic polymorphisms in LPCAT3, FADS1/2, and EHPHX2. Analyses in the recalled donor cohort confirmed findings from the index donor studies showing a strong association between SNPs in LPCAT3, FADS1/2, and EPHX2 and lipid peroxidation products via linear discriminant analysis unadjusted or adjusted by storage day (A-C) and Spearman correlation (D-F). (G-I) Allele dosage was associated with a decrease in hemolytic propensity (on osmotic insult) in the larger index donor cohort. (J) Breakdown of allele frequency by ethnicity showed a strong enrichment in blood donors of African descent for LPCAT3 and EPHX2, whereas FADS1/2 was underrepresented in this ethnic group. ∗∗∗P < .001; ∗∗∗∗P < .0001. FA, fatty acid; ns, not significant.

Figure 5.

Genetic polymorphisms in LPCAT3, FADS1/2, and EHPHX2. Analyses in the recalled donor cohort confirmed findings from the index donor studies showing a strong association between SNPs in LPCAT3, FADS1/2, and EPHX2 and lipid peroxidation products via linear discriminant analysis unadjusted or adjusted by storage day (A-C) and Spearman correlation (D-F). (G-I) Allele dosage was associated with a decrease in hemolytic propensity (on osmotic insult) in the larger index donor cohort. (J) Breakdown of allele frequency by ethnicity showed a strong enrichment in blood donors of African descent for LPCAT3 and EPHX2, whereas FADS1/2 was underrepresented in this ethnic group. ∗∗∗P < .001; ∗∗∗∗P < .0001. FA, fatty acid; ns, not significant.

Figure 6.

TP53 is polymorphic in the healthy blood donor population and associates with hemolysis. Over 50 common TP53 SNPs were monitored in the 13 091 REDS RBC Omics blood donors (top 20 plotted [A] as a function of allele frequency), including common SNPs associated with increased likelihood to develop cancers. One of these SNPs was identified as the top TP53 SNP associated with hemolytic propensity, an SNP whose allele frequency significantly correlated with that of the alleles for all the genes contributing to lipid peroxidation from the GWAS analysis (B). In index (n = 13 091; C) and recalled donors (validation cohort; n = 643; D), the TP53 rs8064946 was associated with markers of osmotic fragility, oxylipins, and polyunsaturated fatty acids, as well as to allele frequency and protein levels for all lipid peroxidation-associated genes, when detected via proteomics (D). (E-H) Allele frequency as a function of ethnic breakdown shows a lower frequency of the potentially pathogenic mutations rs1042522 and rs105200764 and higher frequency of the noncoding rs8064946 in donors of African descent. (I) All these variants were associated with lower osmotic fragility. ∗∗∗P < .001; ∗∗∗∗P < .0001. ns, not significant.

Figure 6.

TP53 is polymorphic in the healthy blood donor population and associates with hemolysis. Over 50 common TP53 SNPs were monitored in the 13 091 REDS RBC Omics blood donors (top 20 plotted [A] as a function of allele frequency), including common SNPs associated with increased likelihood to develop cancers. One of these SNPs was identified as the top TP53 SNP associated with hemolytic propensity, an SNP whose allele frequency significantly correlated with that of the alleles for all the genes contributing to lipid peroxidation from the GWAS analysis (B). In index (n = 13 091; C) and recalled donors (validation cohort; n = 643; D), the TP53 rs8064946 was associated with markers of osmotic fragility, oxylipins, and polyunsaturated fatty acids, as well as to allele frequency and protein levels for all lipid peroxidation-associated genes, when detected via proteomics (D). (E-H) Allele frequency as a function of ethnic breakdown shows a lower frequency of the potentially pathogenic mutations rs1042522 and rs105200764 and higher frequency of the noncoding rs8064946 in donors of African descent. (I) All these variants were associated with lower osmotic fragility. ∗∗∗P < .001; ∗∗∗∗P < .0001. ns, not significant.

Figure 7.

Oxylipins and genetic polymorphisms that regulate them are associated with in vivo hemolysis critically ill individuals receiving nonautologous transfusion. By accessing the “vein-to-vein” database of the REDS RBC Omics program, we linked blood donor TP53 rs8064946 status (homozygous dominant [HD]; heterozygous [HET]; homozygous recessive [HR]) to adjusted hemoglobin increments in clinical recipients of single pRBC unit transfusions of different storage ages (A) or at storage day 36 to 42 (B). Similar analyses were performed for LPCAT3 rs60015123, focusing on Hgb increments immediately after transfusion (C) or at 24 hours (D) at any storage age, or for transfused units aged 36 to 42 days (E). (F) Similarly, we linked end of storage oxylipin levels (eg, hydroxyeicosatetraenoic acid [HETE]) by quartiles to hemoglobin increments on heterologous transfusion of products from the same donors to critically ill recipients requiring transfusion. ∗P < .05; ∗∗P < .01; ∗∗∗P < .001; ∗∗∗∗P < .0001.